From 41c24066efa3dc36d4a657a5182b473a52ef6b0b Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Thu, 4 Sep 2025 10:32:49 -0400 Subject: [PATCH 01/30] initial commit --- agents.py | 977 ------------------------------------------------------ app.py | 264 --------------- 2 files changed, 1241 deletions(-) delete mode 100644 app.py diff --git a/agents.py b/agents.py index 259e224..e69de29 100644 --- a/agents.py +++ b/agents.py @@ -1,977 +0,0 @@ -import copy -import time -from typing import Dict, Optional, Union, List -from openai import Client, OpenAI -from prompts import get_prompts -from internal_tools import feasibility_restoration, sensitivity_analysis, components_retrival, evaluate_modification -from internal_tools import syntax_guidance, fnArgsDecoder -from extractor import extract_component_descriptions, insert_code, run_with_exec -import json -import re -#import streamlit as st - - -class Agent: - def __init__(self, name, description, client, llm="gpt-4-turbo-preview", **kwargs): - self.name = name - self.description = description - self.client = client - self.system_prompt = "You're a helpful assistant." - self.kwargs = kwargs - self.llm = llm - - self.function_names = kwargs.get('function_names', None) - self.tools = kwargs.get('tools', None) - self.multiple_tools = kwargs.get('multiple_tools', None) - self.single_tools = kwargs.get('single_tools', None) - self.none_tools = kwargs.get('none_tools', None) - self.all_tools = kwargs.get('all_tools', None) - self.tool_choice = kwargs.get('tool_choice', None) - self.syntax_guidance_tool = kwargs.get('syntax_guidance_tool', None) - - self.team_conversation_filename = './logs/team_conversation.txt' - self.chat_history_filename = './logs/detailed_chat_history.txt' - - def llm_call(self, prompt: Optional[str] = None, messages: Optional[List] = None, - seed: int = 10, stream: bool = False) -> str: - # make sure exactly one of prompt or messages is provided - assert (prompt is None) != (messages is None) - # make sure if messages is provided, it is a list of dicts with role and content - if messages is not None: - assert isinstance(messages, list) - for message in messages: - assert isinstance(message, dict) - assert "role" in message - assert "content" in message - - if not prompt is None: - messages = [ - {"role": "system", "content": self.system_prompt}, - {"role": "user", "content": prompt}, - ] - - # print("=" * 10) - # print(f'llm_call is called, the following messages are sent to the llm: ') - # for message in messages: - # print(f'{message["role"]}: {message["content"]}') - # print("=" * 10) - - if type(self.client) in [OpenAI, Client]: - completion = self.client.chat.completions.create( - model=self.llm, - messages=messages, - seed=seed, - stream=stream, - ) - - if stream: - return completion - else: - content = completion.choices[0].message.content - return content - - @staticmethod - def generate_pseudo_messages(messages: List[Dict], team_conversation: List[Dict], - new_prompt: str) -> List[Dict]: - pseudo_messages = copy.deepcopy(messages) - if team_conversation: - for message in team_conversation: - if message["agent_name"] in ['Syntax reminder', 'Code reminder']: - pseudo_messages.append({"role": "system", - "content": f'{message["agent_name"]}: \n\n' + - message["agent_response"]}) - else: - pseudo_messages.append({"role": "assistant", - "content": f'I am {message["agent_name"]} in Assistant Team. \n\n' + - message["agent_response"]}) - pseudo_messages.append({"role": "user", "content": new_prompt}) - return pseudo_messages - - def save_team_conversation(self, team_conversation): - with open(self.team_conversation_filename, 'a') as f: - for message in team_conversation: - f.write(f"{message['agent_name']}: {message['agent_response']}\n\n") - - def print_in_and_out(self, prompt, llm_response, agent_name=None): - if agent_name is None: - agent_name = self.name - print("=" * 5 + agent_name + "=" * 5) - print('-' * 5 + 'prompt:' + '-' * 5) - print(prompt) - print('-' * 5 + 'llm_response:' + '-' * 5) - print(llm_response) - - def llm_call_exp(self, prompt: Optional[str] = None, messages: Optional[List] = None, - seed: int = 10, temperature: float = 0.1, - json_mode: bool = False, - stream: bool = False,) -> str: - # make sure exactly one of prompt or messages is provided - assert (prompt is None) != (messages is None) - # make sure if messages is provided, it is a list of dicts with role and content - if messages is not None: - assert isinstance(messages, list) - for message in messages: - assert isinstance(message, dict) - assert "role" in message - assert "content" in message - - if not prompt is None: - messages = [ - {"role": "system", "content": self.system_prompt}, - {"role": "user", "content": prompt}, - ] - - if json_mode: - response_format = {"type": "json_object"} - else: - response_format = {"type": "text"} - - if type(self.client) in [OpenAI, Client]: - if self.llm not in ["o3"]: - completion = self.client.chat.completions.create( - model=self.llm, - messages=messages, - seed=seed, - temperature=temperature, - response_format=response_format, - stream=stream, - ) - else: - completion = self.client.chat.completions.create( - model=self.llm, - messages=messages, - seed=seed, - response_format=response_format, - stream=stream, - ) - - if stream: - return completion - else: - content = completion.choices[0].message.content - return content - - -class Interpreter(Agent): - def __init__(self, client: Client, **kwargs): - super().__init__( - name="Interpreter", - description="This is an operations research agent that is an expert in interpreting optimization models and codes to non-experts.", - client=client, - **kwargs, - ) - - self._init_prompt_template() - - def _init_prompt_template(self): - self.interpretation_prompt_template = get_prompts("model_interpretation_prompt") - self.need2describe_prompt_template = get_prompts("need2describe_prompt") - self.interpretation_json_template = get_prompts("model_interpretation_json") - - self.illustration_prompt_template = get_prompts("model_illustration_prompt") - self.inference_prompt_template = get_prompts("model_inference_prompt") - - def _cat(self, cat_need2describe, component_names, component_type): - return cat_need2describe + self.need2describe_prompt_template.format(component_type=component_type, - component_names=component_names) - - def _cut(self, component_type): - if component_type in self.interpretation_json_template["components"]: - del self.interpretation_json_template["components"][component_type] - - def generate_interpretation(self, models_dict: Dict, code: str, model_name="model_1"): - task_complete = False - cnt = 3 - while not task_complete and cnt > 0: - self._init_prompt_template() - cat_need2describe_prompt = "" - need2describe = {} - for component_type in ['sets', 'parameters', 'variables', 'constraints', 'objective']: - need2describe[component_type] = [] - for key, value in models_dict[model_name]["components"][component_type].items(): - if value.get('description') in ['None', None]: - need2describe[component_type].append(key) - # if there are components that haven't been described, add them to the prompt - if len(need2describe[component_type]) > 0: - cat_need2describe_prompt = self._cat(cat_need2describe_prompt, - need2describe[component_type], component_type) - else: - self._cut(component_type) - # print('===' * 10) - # print('cat_need2describe_prompt:', cat_need2describe_prompt) - # print(f'interpretation_json_template: {self.interpretation_json_template}') - - if len(cat_need2describe_prompt) > 0: - model_interpretation_json = json.dumps(self.interpretation_json_template, indent=4) - # create complete prompt with components that haven't been described only - prompt = self.interpretation_prompt_template.format(code=code, - cat_need2describe_prompt=cat_need2describe_prompt, - model_interpretation_json=model_interpretation_json) - else: - # if all the components in all the component types have been described, then no need to call interpreter - return models_dict - - cnt -= 1 - try: - interpretation_json = self.llm_call(prompt=prompt, seed=cnt, stream=False) - print("=" * 10) - print(f'generate_interpretation... cnt left = {cnt}/3') - print(interpretation_json) - print("=" * 10) - output = interpretation_json - # delete until the first '```json' - if "```json" in output: - output = output[output.find("```json") + 7:] - output = output[: output.rfind("```")] - - start = output.find("{") - end = output.rfind("}") - output = output[start:end + 1] - - update = json.loads(output) - - task_complete = True # mark as complete first, if any component incorrect, mark as incomplete - for key in update["components"]: - print(f'Interpreting {key}') - for component in update["components"][key]: - print(f'component: {component}') - # update models_dict with the new descriptions if format is correct, - # next time less components will be included in the prompt - if ('name' in component) and ('description' in component): - models_dict[model_name]["components"][key][component["name"]]["description"] = component[ - "description"] - else: - print(f'Invalid component format marked!, {component}') - task_complete = False - - except Exception as e: - import traceback - - print(traceback.format_exc()) - print("=" * 10) - print(f'generate_interpretation error... cnt left = {cnt}/3') - print(e) - print("=" * 10) - print(f'generate_interpretation prompt that caused the error: ') - print(prompt) - print("=" * 10) - print(interpretation_json) - print("=" * 10) - print( - f"Invalid json format!\n{e}\n Try again ..." - ) - if cnt == 0: - raise Exception("Invalid json format, Failed 3 times!") - return models_dict - - def generate_illustration(self, model_representation: Dict): - prompt = self.illustration_prompt_template.format( - json_representation=model_representation) - print("=" * 10) - print(f'generate_illustration... ') - print("=" * 10) - stream = self.llm_call(prompt=prompt, stream=True) - return stream - - def generate_inference(self, model_representation: Dict): - def split_representation(representation): - # just split session_state.models_dict["model_representation"] into two parts - reduced_json_representation = copy.deepcopy(representation) - del reduced_json_representation["iis"] - del reduced_json_representation["iis_description"] - return representation["iis_description"], reduced_json_representation - - iis_info, reduced_model_representation = split_representation(model_representation) - prompt = self.inference_prompt_template.format( - iis_info=iis_info, - json_representation=reduced_model_representation) - print("=" * 10) - print(f'generate_inference... ') - print("=" * 10) - stream = self.llm_call(prompt=prompt, stream=True) - return stream - - def generate_interpretation_exp(self, args, models_dict: Dict, code: str, model_name="model_1"): - task_complete = False - cnt = 3 - while not task_complete and cnt > 0: - self._init_prompt_template() - cat_need2describe_prompt = "" - need2describe = {} - for component_type in ['sets', 'parameters', 'variables', 'constraints', 'objective']: - need2describe[component_type] = [] - for key, value in models_dict[model_name]["components"][component_type].items(): - if value.get('description') in ['None', None]: - need2describe[component_type].append(key) - # if there are components that haven't been described, add them to the prompt - if len(need2describe[component_type]) > 0: - cat_need2describe_prompt = self._cat(cat_need2describe_prompt, - need2describe[component_type], component_type) - else: - self._cut(component_type) - - if len(cat_need2describe_prompt) > 0: - model_interpretation_json = json.dumps(self.interpretation_json_template, indent=4) - # create complete prompt with components that haven't been described only - prompt = self.interpretation_prompt_template.format(code=code, - cat_need2describe_prompt=cat_need2describe_prompt, - model_interpretation_json=model_interpretation_json) - else: - # if all the components in all the component types have been described, then no need to call interpreter - task_complete = True - return models_dict, cnt, task_complete - - cnt -= 1 - try: - interpretation_json = self.llm_call_exp(prompt=prompt, seed=cnt, - temperature=args.temperature, - json_mode=args.json_mode, stream=False) - print("=" * 10) - print(f'generate_interpretation... cnt left = {cnt}/3') - print(interpretation_json) - print("=" * 10) - output = interpretation_json - - # print("=" * 10 + 'debug: for testing json mode only' + "=" * 10) - # print(output) - # print("=" * 10) - - # delete until the first '```json' - if "```json" in output: - output = output[output.find("```json") + 7:] - output = output[: output.rfind("```")] - - start = output.find("{") - end = output.rfind("}") - output = output[start:end + 1] - - update = json.loads(output) - - task_complete = True # mark as complete first, if any component incorrect, mark as incomplete - for key in update["components"]: - print(f'Interpreting {key}') - for component in update["components"][key]: - print(f'component: {component}') - # update models_dict with the new descriptions if format is correct, - # next time less components will be included in the prompt - if ('name' in component) and ('description' in component): - models_dict[model_name]["components"][key][component["name"]]["description"] = component[ - "description"] - else: - print(f'Invalid component format marked!, {component}') - task_complete = False - - except Exception as e: - import traceback - - print(traceback.format_exc()) - print("=" * 10) - print(f'generate_interpretation error... cnt left = {cnt}/3') - print(e) - print("=" * 10) - print( - f"Invalid json format!\n{e}\n Try again ..." - ) - if cnt == 0: - return models_dict, cnt, task_complete - return models_dict, cnt, task_complete - - def generate_illustration_exp(self, args, model_representation: Dict): - prompt = self.illustration_prompt_template.format( - json_representation=model_representation) - print("=" * 10) - print(f'generate_illustration... ') - print("=" * 10) - stream_or_completion = self.llm_call_exp(prompt=prompt, temperature=args.temperature, - stream=args.illustration_stream) - return stream_or_completion - - def generate_inference_exp(self, args, model_representation: Dict): - def split_representation(representation): - # just split session_state.models_dict["model_representation"] into two parts - reduced_json_representation = copy.deepcopy(representation) - del reduced_json_representation["iis"] - del reduced_json_representation["iis_description"] - return representation["iis_description"], reduced_json_representation - - iis_info, reduced_model_representation = split_representation(model_representation) - prompt = self.inference_prompt_template.format( - iis_info=iis_info, - json_representation=reduced_model_representation) - print("=" * 10) - print(f'generate_inference... ') - print("=" * 10) - stream_or_completion = self.llm_call_exp(prompt=prompt, temperature=args.temperature, - stream=args.inference_stream) - return stream_or_completion - - -class Coordinator(Agent): - def __init__( - self, client: Client, agents: [Agent], max_rounds: int = 5, **kwargs - ): - super().__init__( - name="Coordinator", - description="This is a coordinator agent that chooses which agent to work on the problem next and organizes " - "the conversation within its team. ", - client=client, - **kwargs, - ) - - self.agents = agents - self.max_rounds = max_rounds - - self.coordination_time = 0 - self.coordinator_success = False - self._init_cnt() - self._init_prompt_template() - - def _init_cnt(self): - self.coordinator_cnt = 3 - self.coordinator_success = False - - def _init_prompt_template(self): - self.prompt_template = get_prompts("coordinator_prompt") - self.agents_list = "".join( - [ - "-" + agent.name + ": " + agent.description + "\n" - for agent in self.agents - ] - ) - - def generate_decision(self, messages, team_conversation, agent_name, task): - status = 'In Progress' - - coordinate_prompt = self.prompt_template.format(agents=self.agents_list) - pseudo_messages = self.generate_pseudo_messages(messages, team_conversation, coordinate_prompt) - - cnt = 3 - while cnt > 0: - try: - response = self.llm_call(messages=pseudo_messages, seed=cnt) - decision = response.strip() - if "```json" in decision: - decision = decision.split("```json")[1].split("```")[0] - decision = decision.replace("\\", "") - - self.print_in_and_out(coordinate_prompt, response) - print('Decision:', decision) - - decision = json.loads(decision) - - if team_conversation: - # safeguard to prevent the coordinator from calling the agent - # after the user's query has been answered by explainer - if team_conversation[-1]["agent_name"] == "Explainer": - status = 'Completed' - OptiChat_out = team_conversation[-1]['agent_response'] - if "DONE" in decision.values(): - print("DONE, the user's query is answered.") - else: - print("DONE, the user's query is answered, though the coordinator did not output 'DONE'.") - return status, OptiChat_out - if "DONE" in decision.values() and team_conversation[-1]["agent_name"] == "Engineer": - decision = {'agent_name': 'Explainer', 'task': 'explain the technical feedback'} - - else: - # the first round of the conversation - if "DONE" in decision.values(): - # sometimes user does not ask a question (e.g. saying 'thank you') - # and coordinator considers no query there and outputs 'DONE' directly - decision = {'agent_name': 'Explainer', 'task': 'respond to the user'} - - agent_name.text(decision["agent_name"]) - task.text(decision["task"]) - - return status, decision - - except Exception as e: - print(e) - cnt -= 1 - print("Invalid decision. Trying again ...") - - task.text(f'distribution failed ({cnt}/3)') - - if cnt == 0: - import traceback - err = traceback.format_exc() - print(err) - - status = 'Terminated' - OptiChat_out = "LLM failed to assign tasks to experts! \n" + "Error: " + err + "\n" - - return status, OptiChat_out - - def generate_decision_exp(self, args, messages, team_conversation): - self._init_cnt() - coordinate_prompt = self.prompt_template.format(agents=self.agents_list) - while self.coordinator_cnt > 0: - # messages will only be updated outside the loop (in the OptiChat workflow fn) - # team_conversation will be updated inside the loop (in the Engineer and Explainer fns) - pseudo_messages = self.generate_pseudo_messages(messages, team_conversation, coordinate_prompt) - try: - # in current design, if coordinator has assigned the task once, - # actually there will be no need to call llm to generate the decision again - if team_conversation: - decision = {'agent_name': 'Explainer', 'task': 'explain the technical feedback'} - # last_agent = team_conversation[-1]["agent_name"] - # if last_agent == "Engineer": - # decision = {'agent_name': 'Explainer', 'task': 'explain the technical feedback'} - else: - response = self.llm_call_exp(messages=pseudo_messages, seed=self.coordinator_cnt, - temperature=args.temperature, - json_mode=args.json_mode, stream=False) - decision = response.strip() - if "```json" in decision: - decision = decision.split("```json")[1].split("```")[0] - decision = decision.replace("\\", "") - - print('Decision:', decision) - - decision = json.loads(decision) - assert "agent_name" in decision - assert decision["agent_name"] in [agent.name for agent in self.agents] - assert "task" in decision - - # in the first round of the conversation - # sometimes user does not ask a question (e.g. saying 'thank you') - # and coordinator considers no query there and outputs 'DONE' directly - if "DONE" in decision.values(): - decision = {'agent_name': 'Explainer', 'task': 'respond to the user'} - - self.coordinator_success = True - return decision - - except Exception as e: - print(e) - self.coordinator_cnt -= 1 - print("Invalid decision. Trying again ...") - - if self.coordinator_cnt == 0: - import traceback - err = traceback.format_exc() - print(err) - return None - - -class Explainer(Agent): - def __init__( - self, client: Client, max_rounds: int = 5, **kwargs - ): - super().__init__( - name="Explainer", - description="This is an explainer agent whose task is to either (1) directly answer user queries if the questions can be analyzed through natural language only, or (2) summarize the technical feedback obtained from engineers to answer user queries", - client=client, - **kwargs, - ) - self.explanation_time = 0 - self._init_prompt_template() - - def _init_prompt_template(self): - self.prompt_template = get_prompts("explainer_prompt") - - def generate_explanation_exp(self, args, messages, team_conversation): - prompt = self.prompt_template # nothing to format here - pseudo_messages = self.generate_pseudo_messages(messages, team_conversation, prompt) - - stream_or_completion = self.llm_call_exp(messages=pseudo_messages, temperature=args.temperature, - stream=args.explanation_stream) - return stream_or_completion - - -class Engineer(Agent): - def __init__(self, client: Client, **kwargs): - super().__init__( - name="Engineer", - description="This is an engineer agent whose task is to execute tools and functions when user's query requires an interaction with optimization model. The engineer agent provides technical feedback instead of natural-language explanations." - "Note that some ‘why’ questions are better answered with technical feedback." - "These questions often involve scenarios that differ from the current model.", - client=client, - **kwargs, - ) - - self.pattern = r"```[ \t]*(\w+)?[ \t]*\r?\n(.*?)\r?\n[ \t]*```" - - self._init_prompt_template() - - self.syntax_time = 0 - self.programing_time = 0 - self.evaluation_time = 0 - - self.programmer_cnt = 3 - self.evaluator_cnt = 3 - - self.syntax_success = False - self.operator_success = False - self.programmer_success = False - self.evaluator_success = False - - self.unparsed_queried_components = None - self.queried_components = None - self.queried_model = None - self.queried_function = None - - def _init_prompt_template(self): - self.syntax_reminder_prompt_template = get_prompts("syntax_reminder_prompt") - self.operator_prompt_template = get_prompts("operator_prompt") - - self.code_reminder_prompt_template = get_prompts("code_reminder_prompt") - self.programmer_prompt_template = get_prompts("programmer_prompt") - self.evaluator_prompt_template = get_prompts("evaluator_prompt") - - self.test_prompt_template = get_prompts("test_prompt") - - def _init_fake_team_conversation(self, team_conversation, code_wo_labels): - self.fake_team_conversation = copy.deepcopy(team_conversation) - self.source_code = self.code_reminder_prompt_template.format(source_code=code_wo_labels) - self.fake_team_conversation.append({"agent_name": 'Code reminder', "agent_response": self.source_code}) - - def _init_cnt(self): - self.syntax_cnt = 3 - self.operator_cnt = 3 - self.programmer_cnt = 3 # cnt for programmer output format - self.evaluator_cnt = 3 # cnt for evaluator output format - self.debug_times_left = 3 # cnt for debugging (format correct but not satisfactory code) - self.syntax_success = False - self.operator_success = False - self.programmer_success = False - self.evaluator_success = False - - self.queried_components = None - self.queried_model = None - self.queried_function = None - - def execute_code(self, revision_code, print_code): - #src_code = insert_code(self.source_code, revision_code, 'REVISION') - # src_code = insert_code(src_code, print_code, 'PRINT') - src_code = self.source_code + "\n" + revision_code - execution_rst = run_with_exec(src_code) - - # save the complete code as .py - with open(f"./logs/code_draft/complete_code_{self.debug_times_left}.py", "w") as f: - f.write(src_code) - # save the execution result as .txt - with open(f"./logs/code_draft/execution_result_{self.debug_times_left}.txt", "w") as f: - f.write(execution_rst) - self.fake_team_conversation.append({"agent_name": 'Execution result', "agent_response": execution_rst}) - return src_code, execution_rst - - def tool_call_exp(self, prompt: Optional[str] = None, messages: Optional[List] = None, - seed: int = 10, temperature: float = 0.1, - is_syntax_guidance: bool = False, - syntax_mode: str = 'none'): - - # make sure exactly one of prompt or messages is provided - assert (prompt is None) != (messages is None) - # make sure if messages is provided, it is a list of dicts with role and content - if messages is not None: - assert isinstance(messages, list) - for message in messages: - assert isinstance(message, dict) - assert "role" in message - assert "content" in message - - if not prompt is None: - messages = [ - {"role": "system", "content": self.system_prompt}, - {"role": "user", "content": prompt}, - ] - - if is_syntax_guidance: - tools = self.syntax_guidance_tool - tool_choice = {"type": "function", "function": {"name": "syntax_guidance"}} - else: - if syntax_mode == 'multiple': - tools = self.multiple_tools - elif syntax_mode == 'single': - tools = self.single_tools - elif syntax_mode == 'none': - tools = self.none_tools - elif syntax_mode == 'all': - tools = self.all_tools - else: - raise Exception("Invalid mode!") - tool_choice = "required" - - if type(self.client) in [OpenAI, Client]: - if self.llm not in ["o3"]: - completion = self.client.chat.completions.create( - model=self.llm, - messages=messages, - seed=seed, - temperature=temperature, - tools=tools, - tool_choice=tool_choice - ) - else: - completion = self.client.chat.completions.create( - model=self.llm, - messages=messages, - seed=seed, - tools=tools, - tool_choice=tool_choice - ) - - if completion.choices[0].message.tool_calls: - # internal tool is called - fn_call = completion.choices[0].message.tool_calls[0].function - fn_name = fn_call.name - fn_args = fn_call.arguments - print(f'function name = {fn_name}') - print(f'function arguments = {fn_args}') - else: - raise Exception("No tool call executed by Operator, perhaps because of the 'auto' tool choice!") - else: - raise Exception("Client type not supported!") - return fn_name, fn_args - - def generate_syntax_exp(self, args, messages, team_conversation, models_dict): - while not self.syntax_success and self.syntax_cnt > 0: - component_descriptions = extract_component_descriptions(models_dict) - - if models_dict['model_representation']['model type'] != 'LP': - function_names = [fn for fn in self.function_names if fn != 'sensitivity_analysis'] - else: - function_names = [fn for fn in self.function_names] - - prompt = self.syntax_reminder_prompt_template.format(function_names=function_names, - component_name_meaning_pairs=str(component_descriptions)) - pseudo_messages = self.generate_pseudo_messages(messages, team_conversation, prompt) - self.syntax_cnt -= 1 - try: - syntax_start = time.time() - fn_name, fn_args = self.tool_call_exp(messages=pseudo_messages, - seed=self.syntax_cnt, temperature=args.temperature, - is_syntax_guidance=True) - syntax_end = time.time() - self.syntax_time += (syntax_end - syntax_start) - - self.queried_function = json.loads(fn_args).get("queried_function") - self.queried_components = json.loads(fn_args).get("queried_components") - self.queried_model = json.loads(fn_args).get("queried_model") - # forced syntax_guidance to be called - syntax_output, syntax_mode = syntax_guidance(self.queried_function, - self.queried_components, - self.queried_model, - models_dict) - self.syntax_success = True - return syntax_output, syntax_mode - - except Exception as e: - print(e) - # import traceback - # err = traceback.format_exc() - # print(err) - if self.syntax_cnt == 0: - self.syntax_success = False - return "LLM failed", "none" - - def generate_feedback_exp(self, args, messages, team_conversation, models_dict, syntax_mode): - while not self.operator_success and self.operator_cnt > 0: - prompt = self.operator_prompt_template # nothing to format here - pseudo_messages = self.generate_pseudo_messages(messages, team_conversation, prompt) - self.operator_cnt -= 1 - try: - syntax_start = time.time() - fn_name, fn_args = self.tool_call_exp(messages=pseudo_messages, - seed=self.operator_cnt, temperature=args.temperature, - is_syntax_guidance=False, - syntax_mode=syntax_mode) - syntax_end = time.time() - self.syntax_time += (syntax_end - syntax_start) - - self.queried_function = fn_name - self.queried_model = json.loads(fn_args).get("queried_model") - self.unparsed_queried_components = json.loads(fn_args).get("queried_components") - self.queried_components = fnArgsDecoder(self.unparsed_queried_components) - - # pass the function name and arguments to the function - if fn_name == 'feasibility_restoration': - fn_output = feasibility_restoration(self.queried_components, self.queried_model, models_dict) - elif fn_name == 'sensitivity_analysis': - fn_output = sensitivity_analysis(self.queried_components, self.queried_model, models_dict) - elif fn_name == 'components_retrival': - fn_output = components_retrival(self.queried_components, self.queried_model, models_dict) - elif fn_name == 'evaluate_modification': - fn_output = evaluate_modification(self.queried_components, self.queried_model, models_dict) - else: - raise Exception("invalid function name") - self.operator_success = True - return fn_output - - except Exception as e: - print(e) - import traceback - err = traceback.format_exc() - # embed the error message into the syntax reminder in team_conversation - error_response = f"\n\nProblematic queried_components: {self.unparsed_queried_components} \n\nError: {err}" - team_conversation.append({"agent_name": 'Execution result', "agent_response": error_response}) - - if self.operator_cnt == 0: - self.operator_success = False - return "LLM failed" - - def programmer_loop_exp(self, args, pseudo_messages): - while self.programmer_cnt > 0: - program_start = time.time() - code_output = self.llm_call_exp(messages=pseudo_messages, - seed=self.programmer_cnt, temperature=args.temperature, stream=False) - program_end = time.time() - self.programing_time += (program_end - program_start) - - self.programmer_cnt -= 1 - try: - snippets = re.findall(self.pattern, code_output, flags=re.DOTALL) - # assert len(snippets) <= 2 - # assert snippets[0][0] == 'python' - # assert snippets[1][0] == 'python' - # revision_code = snippets[0][1] - # print_code = snippets[1][1] - revision_code = snippets[0][1] - print_code = "" - self.programmer_success = True - self.fake_team_conversation.append({"agent_name": 'Programmer', "agent_response": code_output}) - return code_output, revision_code, print_code - - except AssertionError as e: - print(e) - # import traceback - # err = traceback.format_exc() - # print(err) - if self.programmer_cnt == 0: - self.programmer_success = False - return None, None, None - - def evaluator_loop_exp(self, args, pseudo_messages): - while self.evaluator_cnt > 0: - evaluation_start = time.time() - # evaluation_output = self.llm_call_exp(messages=pseudo_messages, - # seed=self.evaluator_cnt, temperature=args.temperature, - # json_mode=args.json_mode, stream=False) - evaluation_output = self.llm_call_exp(messages=pseudo_messages, - seed=self.evaluator_cnt, temperature=args.temperature, - json_mode=True, stream=False) - evaluation_end = time.time() - self.evaluation_time += (evaluation_end - evaluation_start) - - self.evaluator_cnt -= 1 - try: - # evaluation = evaluation_output.strip() - # if "```json" in evaluation: - # evaluation = evaluation.split("```json")[1].split("```")[0] - # evaluation = evaluation.replace("\\", "") - # # print('Code review:', evaluation) - # evaluation = json.loads(evaluation) - - # delete until the first '```json' - if "```json" in evaluation_output: - evaluation_output = evaluation_output[evaluation_output.find("```json") + 7:] - evaluation_output = evaluation_output[: evaluation_output.rfind("```")] - start = evaluation_output.find("{") - end = evaluation_output.rfind("}") - evaluation_output = evaluation_output[start:end + 1] - evaluation = json.loads(evaluation_output) - decision = evaluation["decision"] - comment = evaluation["comment"] - - self.evaluator_success = True - self.fake_team_conversation.append({"agent_name": 'Evaluator', "agent_response": evaluation_output}) - return evaluation_output, decision, comment - - except AssertionError as e: - print(e) - # import traceback - # err = traceback.format_exc() - # print(err) - if self.evaluator_cnt == 0: - self.evaluator_success = False - return None, None, None - - def generate_code_exp(self, args, messages, team_conversation, models_dict): - # initialize - self._init_prompt_template() - self._init_fake_team_conversation(team_conversation, models_dict['model_representation']['code']) - - # until the programmer generates the code that evaluator approves - while self.debug_times_left > 0: - # Only init the cnt for programmer and evaluator for every debugging loop - # because _init_cnt() will reset all the success, cnt, debug_times_left - self.programmer_cnt = 2 - self.evaluator_cnt = 2 - # until the programmer generates the code in correct format - programmer_prompt = self.programmer_prompt_template - pseudo_messages = self.generate_pseudo_messages(messages, self.fake_team_conversation, programmer_prompt) - code_output, revision_code, print_code = self.programmer_loop_exp(args, pseudo_messages) - if not self.programmer_success: - return "LLM failed", 'None', 'None' - - # simply executing the code - complete_code, execution_rst = self.execute_code(revision_code, print_code) - - # until the evaluator evaluates the code in correct format - evaluator_prompt = self.evaluator_prompt_template - pseudo_messages = self.generate_pseudo_messages(messages, self.fake_team_conversation, evaluator_prompt) - evaluation_output, decision, comment = self.evaluator_loop_exp(args, pseudo_messages) - if not self.evaluator_success: - return code_output, execution_rst, "LLM failed" - - if decision == 'accept': - return code_output, execution_rst, evaluation_output - else: - self.debug_times_left -= 1 - if self.debug_times_left == 0: - # return the last evaluation output though it is rejected by evaluator - return code_output, execution_rst, evaluation_output - - def generate_report_exp(self, args, messages, team_conversation, models_dict): - self._init_cnt() - - if args.external_experiment: - syntax_output, syntax_mode = 'external_tools', 'none' - self.syntax_success = True - else: - syntax_output, syntax_mode = self.generate_syntax_exp(args, messages, team_conversation, models_dict) - - if not self.syntax_success: - team_conversation.append({"agent_name": 'Syntax reminder', "agent_response": syntax_output}) - messages.append({"role": "assistant", "content": syntax_output}) - else: - if syntax_output != 'external_tools': - # add code reminder to the team_conversation as well to help find correct component indexes - # add syntax reminder - team_conversation.append({"agent_name": 'Code reminder', - "agent_response": models_dict['model_representation']['code']}) - team_conversation.append({"agent_name": 'Syntax reminder', "agent_response": syntax_output}) - function_output = self.generate_feedback_exp(args, messages, team_conversation, models_dict, - syntax_mode) - - team_conversation = [item for item in team_conversation if - item["agent_name"] not in ['Code reminder', 'Syntax reminder']] - - team_conversation.append({"agent_name": 'Operator', "agent_response": function_output}) - if self.operator_success: - messages.append({"role": "assistant", "content": function_output}) - else: - syntax_output = 'external_tools' - - if not args.internal_experiment: - if syntax_output == 'external_tools': - code_output, execution_rst, evaluation_output = self.generate_code_exp(args, messages, - team_conversation, - models_dict) - team_conversation.append({"agent_name": 'Programmer', "agent_response": code_output}) - team_conversation.append({"agent_name": 'Execution result', "agent_response": execution_rst}) - team_conversation.append({"agent_name": 'Evaluator', "agent_response": evaluation_output}) - - messages.append({"role": "assistant", "content": "Programmer:\n\n" + code_output}) - messages.append({"role": "assistant", "content": "Execution result:\n\n" + execution_rst}) - messages.append({"role": "assistant", "content": "Evaluator:\n\n" + evaluation_output}) - - return messages, team_conversation - - def generate_test_result_exp(self, args, messages, gt_a): - self._init_prompt_template() - prompt = self.test_prompt_template.format(human_expert_answer=gt_a) - pseudo_messages = self.generate_pseudo_messages(messages, [], prompt) - pass_or_fail = self.llm_call_exp(messages=pseudo_messages, temperature=args.temperature, stream=False) - return pass_or_fail \ No newline at end of file diff --git a/app.py b/app.py deleted file mode 100644 index 612f17e..0000000 --- a/app.py +++ /dev/null @@ -1,264 +0,0 @@ -import streamlit as st -from openai import OpenAI -import os -from io import StringIO -import time -import tempfile -import io -from extractor import initial_loading -from extractor import update_model_representation, get_skipJSON, feed_skipJSON -from utils import get_agents -from utils import OptiChat_workflow_exp -from pyomo.opt import TerminationCondition -import json - - -def string_generator(long_string, chunk_size=50): - for i in range(0, len(long_string), chunk_size): - yield long_string[i:i+chunk_size] - time.sleep(0.1) # Optionally add a small delay between each yield - - -client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) -st.session_state['client'] = client -st.session_state['temperature'] = 0.1 # by default -st.session_state['json_mode'] = True # by default -st.session_state['illustration_stream'] = True # by default -st.session_state['inference_stream'] = True # by default -st.session_state['explanation_stream'] = True # by default -st.session_state['internal_experiment'] = False # by default -st.session_state['external_experiment'] = False # by default - -st.set_page_config(layout='wide') - -st.title("OptiChat: Talk to your Optimization Model") - - -gpt_model = st.sidebar.selectbox(label="GPT-Model", options=["gpt-4-turbo-preview", "gpt-4-turbo", "gpt-4-1106-preview", "gpt-4", "gpt-3.5-turbo", "gpt-3.5-turbo-16k"], ) -st.session_state["gpt_model"] = gpt_model -# Set a default model -if "gpt_model" not in st.session_state: - st.session_state["gpt_model"] = "gpt-4-turbo-preview" -if "models_dict" not in st.session_state: - st.session_state["models_dict"] = {"model_representation": {}} -if "code" not in st.session_state: - st.session_state["code"] = "" - -st.sidebar.subheader("Load Pyomo File") -uploaded_file = st.sidebar.file_uploader("Upload Model", type=["py"]) -uploaded_json = st.sidebar.file_uploader("Upload JSON", type=["json"]) -st.session_state['py_path'] = None -st.session_state['fn_names'] = ["feasibility_restoration", - "sensitivity_analysis", - "components_retrival", - "evaluate_modification", - "external_tools"] - -interpreter, explainer, engineer, coordinator = get_agents(st.session_state.fn_names, - st.session_state.client, - st.session_state.gpt_model) -st.session_state['Interpreter'] = interpreter -st.session_state['Explainer'] = explainer -st.session_state['Engineer'] = engineer -st.session_state['Coordinator'] = coordinator - - -if not st.session_state.get("messages"): - st.session_state["messages"] = [] - -if not st.session_state.get("team_conversation"): - st.session_state["team_conversation"] = [] - -if not st.session_state.get("chat_history"): - st.session_state["chat_history"] = [] - -if not st.session_state.get("detailed_chat_history"): - st.session_state["detailed_chat_history"] = [] - - -def process(): - if uploaded_file is None: - st.error("Please upload your model first.") - return - - models_dict, code = initial_loading(uploaded_file) - - with st.chat_message("user"): - st.markdown("I have uploaded a Pyomo model.") - st.session_state.messages.append({"role": "user", "content": "I have uploaded a Pyomo model."}) - # interpret the model components - models_dict, cnt, completion = st.session_state.Interpreter.generate_interpretation_exp(st.session_state, - models_dict, code) - st.session_state['models_dict'] = models_dict - st.session_state['code'] = code - # update model representation with component descriptions - update_model_representation(st.session_state.models_dict) - # illustrate the model - illustration_stream = st.session_state.Interpreter.generate_illustration_exp(st.session_state, - models_dict["model_representation"]) - with st.chat_message("assistant"): - illustration = st.write_stream(illustration_stream) - # update model representation with model description - st.session_state.models_dict['model_1']['model description'] = illustration - update_model_representation(st.session_state.models_dict) - # if the model is infeasible, generate inference - if st.session_state.models_dict['model_1']['model status'] in [TerminationCondition.infeasible, - TerminationCondition.infeasibleOrUnbounded]: - inference_stream = st.session_state.Interpreter.generate_inference_exp(st.session_state, - st.session_state.models_dict["model_representation"]) - with st.chat_message("assistant"): - inference = st.write_stream(inference_stream) - # update model representation with inference description - st.session_state.models_dict['model_1']['model description'] = illustration + '\n' + inference - update_model_representation(st.session_state.models_dict) - - # append model representation to messages - st.session_state.messages.append({"role": "assistant", - "content": st.session_state.models_dict["model_representation"]["model description"]}) - - # append detailed chat history - st.session_state.chat_history.append("user: I have uploaded a Pyomo model.") - st.session_state.chat_history.append("assistant: " + - st.session_state.models_dict["model_representation"]["model description"]) - st.session_state.detailed_chat_history.append("user: I have uploaded a Pyomo model.") - st.session_state.detailed_chat_history.append("assistant: " + - st.session_state.models_dict["model_representation"]["model description"]) - - # save model_description and description of every component - if not os.path.exists("logs/model_json"): - os.makedirs("logs/model_json") - if not os.path.exists("logs/code_draft"): - os.makedirs("logs/code_draft") - if not os.path.exists("logs/ilps"): - os.makedirs("logs/ilps") - - json2save = get_skipJSON(st.session_state.models_dict["model_representation"]) - with open(f"logs/model_json/{os.path.splitext(uploaded_file.name)[0]}.json", "w") as f: - json.dump(json2save, f) - - -def load_json(): - if uploaded_file is None: - st.error("Please upload your model first.") - return - if uploaded_json is None: - st.error("Please upload your json file first.") - return - - models_dict, code = initial_loading(uploaded_file) - - with st.chat_message("user"): - st.markdown("I have uploaded a Pyomo model.") - st.session_state.messages.append({"role": "user", "content": "I have uploaded a Pyomo model."}) - - skipJSON = json.load(uploaded_json) - models_dict = feed_skipJSON(skipJSON, models_dict) - - st.session_state["models_dict"] = models_dict - st.session_state['code'] = code - # update model representation with component and model descriptions - update_model_representation(st.session_state.models_dict) - - time.sleep(8) - stream = string_generator(skipJSON["model description"]) - with st.chat_message("assistant"): - st.write_stream(stream) - - # append model representation to messages - st.session_state.messages.append({"role": "assistant", - "content": st.session_state.models_dict["model_representation"][ - "model description"]}) - - # append detailed chat history - st.session_state.chat_history.append("user: I have uploaded a Pyomo model.") - st.session_state.chat_history.append("assistant: " + - st.session_state.models_dict["model_representation"]["model description"]) - st.session_state.detailed_chat_history.append("user: I have uploaded a Pyomo model.") - st.session_state.detailed_chat_history.append("assistant: " + - st.session_state.models_dict["model_representation"][ - "model description"]) - - -chat_history_texts = '\n\n'.join(st.session_state.chat_history) -detailed_chat_history_texts = '\n\n'.join(st.session_state.detailed_chat_history) - -st.sidebar.button("Process", on_click=process) -st.sidebar.button("Load JSON", on_click=load_json) - - -show_model_representation = st.sidebar.checkbox("Show Model Representation", False) -model_representation_placeholder = st.empty() -show_code = st.sidebar.checkbox("Show Code", False) -code_placeholder = st.empty() -show_tech_feedback = st.sidebar.checkbox("Show Technical Feedback", False) -tech_feedback_placeholder = st.empty() - -st.sidebar.download_button(label="Export Chat History", data=chat_history_texts, - file_name='chat_history.txt', mime='text/plain') -st.sidebar.download_button(label="Export Detailed Chat History", data=detailed_chat_history_texts, - file_name='detailed_chat_history.txt', mime='text/plain') - - -st.sidebar.markdown("### Status") -status = st.sidebar.empty() - -st.sidebar.markdown("### Round") -cur_round = st.sidebar.empty() - -st.sidebar.markdown("### Agent") -agent_name = st.sidebar.empty() - -st.sidebar.markdown("### Task") -task = st.sidebar.empty() - - -if show_model_representation: - with model_representation_placeholder.container(): - st.json(st.session_state.models_dict["model_representation"]) -else: - model_representation_placeholder.empty() - -if show_code: - with code_placeholder.container(): - st.code(st.session_state.code) -else: - code_placeholder.empty() - -if show_tech_feedback: - with tech_feedback_placeholder.container(): - for message in st.session_state.team_conversation: - st.write(message['agent_name'] + ': ' + message['agent_response']) - # if message['agent_name'] in ['Programmer', 'Operator', 'Syntax reminder', 'Explainer', 'Coordinator']: - # st.write(message['agent_name'] + ': ' + message['agent_response']) -else: - tech_feedback_placeholder.empty() - - -# Display chat messages from history on app rerun -for message in st.session_state.messages: - with st.chat_message(message["role"]): - st.markdown(message["content"]) - -# Accept user input -if prompt := st.chat_input("Enter your query here..."): - st.session_state.messages.append({"role": "user", "content": prompt}) - with st.chat_message("user"): - st.markdown(prompt) - - updated_messages, team_conversation = OptiChat_workflow_exp(st.session_state, - st.session_state.Coordinator, - st.session_state.Engineer, - st.session_state.Explainer, - st.session_state.messages, - st.session_state.models_dict) - print('OptiChat_out:', updated_messages) - st.session_state.messages = updated_messages - - # # update detailed chat history - # st.session_state.chat_history.append("user: " + prompt) - # st.session_state.chat_history.append("assistant: " + OptiChat_out) - - # st.session_state.detailed_chat_history.append("user: " + prompt) - # for message in st.session_state.team_conversation: - # st.session_state.detailed_chat_history.append(f"***{message['agent_name']}***: {message['agent_response']}") - # st.session_state.detailed_chat_history.append("assistant: " + OptiChat_out) From bdc05f8f4eed52063051e244c1081dfa571cccac Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Thu, 4 Sep 2025 10:53:29 -0400 Subject: [PATCH 02/30] update gitignore to ignore local testing --- .gitignore | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index e2d11a0..179ec43 100644 --- a/.gitignore +++ b/.gitignore @@ -52,4 +52,11 @@ ENV/ __gams* index*.bin -*.ilp \ No newline at end of file +*.ilp + +# Ignore local testing +create_code_testset.py +create_tool_testset.py +grading.py +run_exp.py +show_results.ipynb \ No newline at end of file From 0759232382070fc7602d9dfb880d68a8d688a5de Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Mon, 15 Sep 2025 22:02:17 -0400 Subject: [PATCH 03/30] draft; todo: pyomo shortcuts, no-shortcuts-prompt, rag, processing models in cfg --- agents.py => optichat/.env | 0 optichat/__init__.py | 1 + optichat/agent.py | 11 ++ optichat/config/cfg_template.py | 27 +++ optichat/config/constants.py | 61 +++++++ optichat/config/llm_cfg.py | 12 ++ optichat/config/pyomo_mapping.py | 4 + optichat/expl_recipes/expl_recipes.py | 16 ++ optichat/llm.py | 13 ++ optichat/sub_agents/expert/agent.py | 39 +++++ optichat/sub_agents/expert/prompt.py | 84 ++++++++++ optichat/sub_agents/root/agent.py | 53 ++++++ optichat/sub_agents/root/prompt.py | 27 +++ optichat/tools/callback_tool.py | 195 ++++++++++++++++++++++ optichat/tools/extract_tool.py | 232 ++++++++++++++++++++++++++ optichat/tools/python_repl.py | 47 ++++++ optichat/tools/rag_tool.py | 52 ++++++ optichat/tools/search_tool.py | 117 +++++++++++++ optichat/tools/shortcut_functions.py | 94 +++++++++++ 19 files changed, 1085 insertions(+) rename agents.py => optichat/.env (100%) create mode 100644 optichat/__init__.py create mode 100644 optichat/agent.py create mode 100644 optichat/config/cfg_template.py create mode 100644 optichat/config/constants.py create mode 100644 optichat/config/llm_cfg.py create mode 100644 optichat/config/pyomo_mapping.py create mode 100644 optichat/expl_recipes/expl_recipes.py create mode 100644 optichat/llm.py create mode 100644 optichat/sub_agents/expert/agent.py create mode 100644 optichat/sub_agents/expert/prompt.py create mode 100644 optichat/sub_agents/root/agent.py create mode 100644 optichat/sub_agents/root/prompt.py create mode 100644 optichat/tools/callback_tool.py create mode 100644 optichat/tools/extract_tool.py create mode 100644 optichat/tools/python_repl.py create mode 100644 optichat/tools/rag_tool.py create mode 100644 optichat/tools/search_tool.py create mode 100644 optichat/tools/shortcut_functions.py diff --git a/agents.py b/optichat/.env similarity index 100% rename from agents.py rename to optichat/.env diff --git a/optichat/__init__.py b/optichat/__init__.py new file mode 100644 index 0000000..63bd45e --- /dev/null +++ b/optichat/__init__.py @@ -0,0 +1 @@ +from . import agent \ No newline at end of file diff --git a/optichat/agent.py b/optichat/agent.py new file mode 100644 index 0000000..f0aba39 --- /dev/null +++ b/optichat/agent.py @@ -0,0 +1,11 @@ +import os +import logging + +# Disable OpenTelemetry to avoid context management issues +os.environ["OTEL_SDK_DISABLED"] = "true" +# Suppress OpenTelemetry warnings +logging.getLogger("opentelemetry").setLevel(logging.ERROR) + +from optichat.sub_agents.root.agent import create_root_agent + +root_agent = create_root_agent(workflow="default") \ No newline at end of file diff --git a/optichat/config/cfg_template.py b/optichat/config/cfg_template.py new file mode 100644 index 0000000..5e5af06 --- /dev/null +++ b/optichat/config/cfg_template.py @@ -0,0 +1,27 @@ +import json + +cfg_template = { + "models": { + "local_resources": [ + "models/*", + "models/**/*.pkl" + ] + }, + "models_code": { + "local_resources": [ + "models_code/*", + "models_code/**/*.py" + ] + }, + "models_paper": { + "local_resources": [ + "models_paper/*", + "models_paper/**/*.txt", + "models_paper/**/*.pdf" + ] + } +} + +# json dump example +with open("cfg_template.json", "w") as f: + json.dump(cfg_template, f, indent=4) diff --git a/optichat/config/constants.py b/optichat/config/constants.py new file mode 100644 index 0000000..2e9a5d2 --- /dev/null +++ b/optichat/config/constants.py @@ -0,0 +1,61 @@ + +IS_SESSION_INITIALIZED = "IS_SESSION_INITIALIZED" + +OUTPUT_KEY_ROOT_AGENT = "OUTPUT_KEY_ROOT_AGENT" + +IS_EXPERT_AGENT_USED = "IS_EXPERT_AGENT_USED" +EXPERT_AGENT_PYTHON_REPL_FUNC_USES = "EXPERT_AGENT_PYTHON_REPL_FUNC_USES" +EXPERT_AGENT_PYTHON_REPL_FUNC_MAX_USES = "EXPERT_AGENT_PYTHON_REPL_FUNC_MAX_USES" +EXPERT_AGENT_PYTHON_REPL_FUNC_MAX_TOKENS = "EXPERT_AGENT_PYTHON_REPL_FUNC_MAX_TOKENS" +EXPERT_AGENT_CODE_RAG_USES = "EXPERT_AGENT_CODE_RAG_USES" +EXPERT_AGENT_CODE_RAG_MAX_USES = "EXPERT_AGENT_CODE_RAG_MAX_USES" +EXPERT_AGENT_CODE_BLOCK = "EXPERT_AGENT_CODE_BLOCK" +EXPERT_AGENT_PAPER_RAG_USES = "EXPERT_AGENT_PAPER_RAG_USES" +EXPERT_AGENT_PAPER_RAG_MAX_USES = "EXPERT_AGENT_PAPER_RAG_MAX_USES" +EXPERT_AGENT_PAPER_CONTENT = "EXPERT_AGENT_PAPER_CONTENT" +EXPERT_AGENT_START_TIME = "EXPERT_AGENT_START_TIME" +OUTPUT_KEY_EXPERT_AGENT = "OUTPUT_KEY_EXPERT_AGENT" + +MODELS_DICTIONARY = "MODELS_DICTIONARY" +MODEL_VERSIONS = "MODEL_VERSIONS" +NUM_OF_MODELS = "NUM_OF_MODELS" +IS_MODELS_DICTIONARY_AVAILABLE = "IS_MODELS_DICTIONARY_AVAILABLE" +IS_MODELS_CODE_AVAILABLE = "IS_MODELS_CODE_AVAILABLE" +IS_MODELS_PAPER_AVAILABLE = "IS_MODELS_PAPER_AVAILABLE" + +CFG = "CFG" + +TMP_ROOT_FOLDER = "tmp" +TMP_MODEL_OBJECT_FOLDER = "tmp/model_objects" + + +# NOT reset within a session +PERSISTENT_STATES = { + IS_SESSION_INITIALIZED: False, + OUTPUT_KEY_ROOT_AGENT: "", + EXPERT_AGENT_PYTHON_REPL_FUNC_MAX_USES: 5, + EXPERT_AGENT_PYTHON_REPL_FUNC_MAX_TOKENS: 10000, + EXPERT_AGENT_CODE_RAG_MAX_USES: 1, + EXPERT_AGENT_CODE_BLOCK: "", + EXPERT_AGENT_PAPER_RAG_MAX_USES: 1, + EXPERT_AGENT_PAPER_CONTENT: "", + OUTPUT_KEY_EXPERT_AGENT: "", + MODELS_DICTIONARY: {}, + MODEL_VERSIONS: [], + NUM_OF_MODELS: 0, + IS_MODELS_DICTIONARY_AVAILABLE: False, + IS_MODELS_CODE_AVAILABLE: False, + IS_MODELS_PAPER_AVAILABLE: False, + CFG: {}, +} + + +# reset for every query +TEMPORARY_STATES = { + IS_EXPERT_AGENT_USED: False, + EXPERT_AGENT_PYTHON_REPL_FUNC_USES: 5, + EXPERT_AGENT_CODE_RAG_USES: 1, + EXPERT_AGENT_PAPER_RAG_USES: 1, + EXPERT_AGENT_START_TIME: None, +} + diff --git a/optichat/config/llm_cfg.py b/optichat/config/llm_cfg.py new file mode 100644 index 0000000..1c88ce7 --- /dev/null +++ b/optichat/config/llm_cfg.py @@ -0,0 +1,12 @@ +# LLM MODELS +GPT_5 = "openai/gpt-5" +GPT_5_TEMPERATURE = 1 # gpt-5 models don't support temperature=0. Only temperature=1 is supported +GPT_5_MAX_TOKENS = 30000 + +GPT_5_MINI = "openai/gpt-5-mini" +GPT_5_MINI_TEMPERATURE = 1 +GPT_5_MINI_MAX_TOKENS = 30000 + +GPT_5_NANO = "openai/gpt-5-nano" +GPT_5_NANO_TEMPERATURE = 1 +GPT_5_NANO_MAX_TOKENS = 30000 diff --git a/optichat/config/pyomo_mapping.py b/optichat/config/pyomo_mapping.py new file mode 100644 index 0000000..2d24598 --- /dev/null +++ b/optichat/config/pyomo_mapping.py @@ -0,0 +1,4 @@ +from pyomo.opt import SolverStatus, TerminationCondition + +TerminationConditionMap = {TerminationCondition.infeasible, + TerminationCondition.infeasibleOrUnbounded} \ No newline at end of file diff --git a/optichat/expl_recipes/expl_recipes.py b/optichat/expl_recipes/expl_recipes.py new file mode 100644 index 0000000..f5f103e --- /dev/null +++ b/optichat/expl_recipes/expl_recipes.py @@ -0,0 +1,16 @@ +EXPL_RECIPES = """ +**FACTUAL EXPLANATION: TRADE-OFFS** +- Users may be curious about the rationale behind certain decisions made by the model. +This is caused by the trade-offs that the model balances competing objectives while satisfying all constraints. +- To locate the root cause, focus on what decision variables are penalized in the objective function, and by how much, +and how these decision variables interact with other decision variables through constraints. + +**COUNTERFACTUAL EXPLANATION: NEW SCENARIO** +- Users may be suspicious of certain decisions or interested in exploring alternatives. +This represents a new scenario that requires the original model to be modified and re-solved for comparison. +- Since resolving new models is costly, this explanation strategy should only be used +when the user explicitly requests it in the query and indicates a clear modification object and extent. + e.g. "What will happen if the penalty of overage is doubled?" + e.g. "What if we need the generator A and B to produce at least X MW in total every hour?" + e.g. "Why can't we force the station to have Y routes instead of Z routes every day?" +""" \ No newline at end of file diff --git a/optichat/llm.py b/optichat/llm.py new file mode 100644 index 0000000..b4d386c --- /dev/null +++ b/optichat/llm.py @@ -0,0 +1,13 @@ +from google.adk.models.lite_llm import LiteLlm +from optichat.config.llm_cfg import * + +gpt_5 = LiteLlm(model=GPT_5, + temperature=GPT_5_TEMPERATURE, + max_tokens=GPT_5_MAX_TOKENS) +gpt_5_mini = LiteLlm(model=GPT_5_MINI, + temperature=GPT_5_MINI_TEMPERATURE, + max_tokens=GPT_5_MINI_MAX_TOKENS) +gpt_5_nano = LiteLlm(model=GPT_5_NANO, + temperature=GPT_5_NANO_TEMPERATURE, + max_tokens=GPT_5_NANO_MAX_TOKENS) + diff --git a/optichat/sub_agents/expert/agent.py b/optichat/sub_agents/expert/agent.py new file mode 100644 index 0000000..8eab6d4 --- /dev/null +++ b/optichat/sub_agents/expert/agent.py @@ -0,0 +1,39 @@ +from google.adk.agents import LlmAgent, BaseAgent, LoopAgent, SequentialAgent, ParallelAgent, Agent +# from google.adk.tools.agent_tool import AgentTool +# from google.adk.events import Event +from optichat.llm import * +from optichat.config.constants import * +from optichat.sub_agents.expert.prompt import EXPERT_AGENT_PROMPTS +from optichat.tools.search_tool import get_model_components +from optichat.tools.python_repl import python_repl_func +from optichat.tools.rag_tool import code_rag, paper_rag +from optichat.tools.callback_tool import (check_is_expert_agent_used, check_expert_agent_runtime, + check_llm_response, check_tool_usage, check_tool_response) + + +def create_expert_agent(prompt_version=1, tools_version=1): + expert_agent_prompt = EXPERT_AGENT_PROMPTS.get(prompt_version, None) + if expert_agent_prompt is None: + raise NotImplementedError(f"Prompt version '{prompt_version}' is not implemented.") + if tools_version == 1: + expert_agent_tools = [get_model_components, + python_repl_func, + code_rag, + paper_rag] + else: + raise NotImplementedError(f"Tools version '{tools_version}' is not implemented.") + + expert_agent = Agent(name="expert_agent", + model=gpt_5, + tools=expert_agent_tools, + description=("Optimization & operations research expert that " + "interacts with , , "), + instruction=expert_agent_prompt, + output_key=OUTPUT_KEY_EXPERT_AGENT, + before_agent_callback=check_is_expert_agent_used, + after_agent_callback=check_expert_agent_runtime, + after_model_callback=check_llm_response, + before_tool_callback=check_tool_usage, + after_tool_callback=check_tool_response + ) + return expert_agent diff --git a/optichat/sub_agents/expert/prompt.py b/optichat/sub_agents/expert/prompt.py new file mode 100644 index 0000000..fbd387a --- /dev/null +++ b/optichat/sub_agents/expert/prompt.py @@ -0,0 +1,84 @@ +EXPERT_AGENT_PROMPT = """ +USER QUERY +{USER_QUERY} + +RESPONSIBILITIES +You are an optimization & operations research expert that +use CONTEXT TOOLS to interact with RESOURCES following the WORKFLOW, +and answers the USER QUERY based on the interactions. + +RESOURCES + (dynamic availability: {IS_MODELS_DICTIONARY_AVAILABLE}): + the optimization models labelled with version names, {MODEL_VERSIONS}, {num_of_models} models in total. + + (dynamic availability: {IS_MODELS_CODE_AVAILABLE}): + code used to implement the optimization models. + + (dynamic availability: {IS_MODELS_PAPER_AVAILABLE}): + scientific papers associated with the optimization models. + +CONTEXT TOOLS + - `get_model_components` + resource access: + result type: deterministic and fast, retrieve information about model components in existing + - `python_repl_func` (Limited Uses Left: {EXPERT_AGENT_PYTHON_REPL_FUNC_USES}) + resource access: + result type: dynamic and slow (error-prone), load, modify and solve new ONLY + - `code_rag` (Limited Uses Left: {EXPERT_AGENT_CODE_RAG_USES}) + resource access: + result type: dynamic and slow, retrieve code blocks + - `paper_rag` (Limited Uses Left: {EXPERT_AGENT_PAPER_RAG_USES}) + resource access: + result type: dynamic and slow, retrieve code contents + +WORKFLOW +1. classify the USER QUERY and find the appropriate explanation strategy from PRIOR KNOWLEDGE +2. use CONTEXT TOOLS to interact with RESOURCES for information gathering +3. answer the USER QUERY + +PRIOR KNOWLEDGE +__MODELS_RECIPE_PLACEHOLDER__ +__EXPLANATIONS_RECIPE_PLACEHOLDER__ + +TOOL CONVENTIONS +`get_model_components` conventions + - searching by component_type provides complete information about a component type efficiently + through a single tool call, but may be truncated if too many components are in . + - searching by pattern provides more granular filtering to prevent truncation, + but requires much more tool calls if complete information about a component type is desired. + - if new was solved in previous `python_repl_func` call, + complete information about the new can be retrieved by `get_model_components`. + - Examples: + get_model_components(["v1", "v2"], "objective", "", tool_context) compares objective between v1 and v2 + get_model_components(["v1"], "variable", "", tool_context) gets all decision variables in v1 + get_model_components(["v1"], "constraint", "", tool_context) gets all constraints in v1 + get_model_components(["v1"], "", "ramp*", tool_context) gets ramp-related components in v1 when previous result was truncated + get_model_components(["v2"], "constraint", "transport*", tool_context) gets transport-related constraints in v2 when previous result was truncated +`python_repl_func` conventions + - ONLY used when necessary: + only when USER QUERY explicitly falls into the categories that requires new in PRIOR KNOWLEDGE + - Concise code snippet: + STOP the code snippet as soon as new are programmed to be solved. + NEVER look up information about new in the code snippet. Use `get_model_components` instead + - Generic code snippet: + the code snippet MUST be generic to built by different modelling languages, + NEVER use Pyomo's methods, function, and attributes, + because the code snippet MUST be reviewed by various researchers without Pyomo expertise + e.g. when iterating over components in , NEVER use a for-loop and ```model.component_map``` (Pyomo's method) + ONLY use the following generic shortcut functions to interact with + __SHORTCUT_FUNCTIONS_PLACEHOLDER__ +`code_rag` & `paper_rag` conventions + - ONLY used in the end: + only when have been thoroughly analyzed with PRIOR KNOWLEDGE, + the code blocks and paper contents are version-agnostic and can ONLY serve as supplementary information + prioritize using `get_model_components` and `python_repl_func` first + +RESPONSE STYLE +- coherent and information-grounded narrative +- NEVER be obsessed with calculating statistics and verifying user's observations +- focus on **explanations and analysis** to answer the USER QUERY +- NEVER do extra work. NEVER explore randomly. +""" + + +EXPERT_AGENT_PROMPTS = {1: EXPERT_AGENT_PROMPT} \ No newline at end of file diff --git a/optichat/sub_agents/root/agent.py b/optichat/sub_agents/root/agent.py new file mode 100644 index 0000000..fbb91b7 --- /dev/null +++ b/optichat/sub_agents/root/agent.py @@ -0,0 +1,53 @@ +from google.adk.agents import LlmAgent, BaseAgent, LoopAgent, SequentialAgent, ParallelAgent, Agent +from google.adk.tools.agent_tool import AgentTool +from optichat.llm import * +from optichat.config.constants import * +from optichat.sub_agents.root.prompt import * +from optichat.sub_agents.expert.agent import create_expert_agent +from optichat.tools.callback_tool import (initialize_session, initialize_query) + + + +def get_weather(city: str) -> dict: + """Retrieves the current weather report for a specified city. + + Args: + city (str): The name of the city (e.g., "New York", "London", "Tokyo"). + + Returns: + dict: A dictionary containing the weather information. + Includes a 'status' key ('success' or 'error'). + If 'success', includes a 'report' key with weather details. + If 'error', includes an 'error_message' key. + """ + print(f"--- Tool: get_weather called for city: {city} ---") # Log tool execution + city_normalized = city.lower().replace(" ", "") # Basic normalization + + # Mock weather data + mock_weather_db = { + "newyork": {"status": "success", "report": "The weather in New York is sunny with a temperature of 25°C."}, + "london": {"status": "success", "report": "It's cloudy in London with a temperature of 15°C."}, + "tokyo": {"status": "success", "report": "Tokyo is experiencing light rain and a temperature of 18°C."}, + } + + if city_normalized in mock_weather_db: + return mock_weather_db[city_normalized] + else: + return {"status": "error", "error_message": f"Sorry, I don't have weather information for '{city}'."} + + + +def create_root_agent(workflow="default"): + if workflow == "default": + expert_agent = create_expert_agent(prompt_version=1, tools_version=1) + root_agent = Agent(name="root_agent", + model=gpt_5_nano, + tools=[AgentTool(expert_agent)], + description="first point of contact for all user queries", + instruction=ROOT_AGENT_PROMPT, + output_key=OUTPUT_KEY_ROOT_AGENT, + before_agent_callback=initialize_session, + before_model_callback=initialize_query) + return root_agent + else: + raise NotImplementedError(f"Workflow '{workflow}' is not implemented.") \ No newline at end of file diff --git a/optichat/sub_agents/root/prompt.py b/optichat/sub_agents/root/prompt.py new file mode 100644 index 0000000..98bf3b4 --- /dev/null +++ b/optichat/sub_agents/root/prompt.py @@ -0,0 +1,27 @@ +ROOT_AGENT_PROMPT = """ +You're the root agent, a coordinator between the user and sub-agents. +Your task is to understand the user's queries and delegate them to the appropriate sub-agents for processing. + +RESOURCES + (Dynamic Availability: {IS_MODELS_DICTIONARY_AVAILABLE}): + The optimization models labelled with version names {MODEL_VERSIONS} + ({NUM_OF_MODELS} in total). + + (Dynamic Availability: {IS_MODELS_CODE_AVAILABLE}): + Code used to implement the optimization models. + + (Dynamic Availability: {IS_MODELS_PAPER_AVAILABLE}): + Scientific papers associated with the optimization models. + +TOOLS +expert_agent + Resource access: , , + +RESPONSE STYLE +information-grounded but user-friendly response is preferred. +- the sub-agents gather trustworthy and technical information from the available resources. +NEVER speculate. NEVER make up information. +- the user has little knowledge of optimization and operations research, but is familiar with the problem context that +the optimization models are designed for. +Avoid jargon, complex terminology without explanations, and overwhelming mathematical expressions and code snippets. +""" \ No newline at end of file diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py new file mode 100644 index 0000000..e7cb977 --- /dev/null +++ b/optichat/tools/callback_tool.py @@ -0,0 +1,195 @@ +import time +import json +import os +import glob +import tiktoken +from loguru import logger +from typing import Dict, Any, List +from typing import Optional +from copy import deepcopy +from google.genai import types +from google.adk.agents.callback_context import CallbackContext +from google.adk.tools.tool_context import ToolContext +from google.adk.tools.base_tool import BaseTool +from google.adk.models import LlmResponse, LlmRequest +from optichat.config.constants import (IS_SESSION_INITIALIZED, PERSISTENT_STATES, TEMPORARY_STATES, + CFG, IS_EXPERT_AGENT_USED, EXPERT_AGENT_START_TIME) + + +def initialize_session(callback_context: CallbackContext): + if IS_SESSION_INITIALIZED not in callback_context.state: + callback_context.state.update(PERSISTENT_STATES) + callback_context.state.update(TEMPORARY_STATES) + + user_content = callback_context.user_content + parts_wo_json = [] + for part in user_content.parts: + if getattr(part, "inline_data", None) is not None: + if part.inline_data.mime_type == "application/json": + if callback_context.state[IS_SESSION_INITIALIZED]: + raise NotImplementedError("Session is already initialized, cannot re-initialize with a new cfg. Open a new session instead.") + else: + raw = part.inline_data.data + cfg = json.loads(raw.decode("utf-8")) + cfg = _init_cfg(cfg) + callback_context.state[CFG] = cfg + else: + parts_wo_json.append(part) + else: + parts_wo_json.append(part) + # replace user_content with parts without json part (if a part has json, it cannot be processed) + callback_context.user_content.parts = parts_wo_json + return None + + +def initialize_query(callback_context: CallbackContext, llm_request: LlmRequest): + # reset temporary states for every query + callback_context.state.update(TEMPORARY_STATES) + return None + + +def _init_cfg(cfg: dict): + cfg_out = deepcopy(cfg) + + required_sections = ["models", "models_code", "models_paper"] + extension_filters = { + "models": [".pkl"], + "models_code": [".py"], + "models_paper": [".txt", ".pdf"] + } + + for section_key, section_cfg in cfg.items(): + if section_key in required_sections: + local_resources = section_cfg.get("local_resources", []) + allowed_extensions = extension_filters.get(section_key, None) + expanded_resources = _expand_resources(local_resources, allowed_extensions) + cfg_out[section_key]["local_resources"] = expanded_resources + + return cfg_out + + +def _expand_resources(local_resources: List[str], allowed_extensions: Optional[List[str]]): + """ + Expand wildcard * patterns with allowed extensions filtering + """ + expanded_resources = [] + for resource_path in local_resources: + if "*" in resource_path: + matches = glob.glob(resource_path) + else: + matches = [resource_path] + if not matches: + raise FileNotFoundError(f"No files matched: {resource_path}") + if allowed_extensions: + filtered_matches = [ + match for match in matches + if any(match.lower().endswith(ext) for ext in allowed_extensions) + ] + else: + filtered_matches = matches + expanded_resources.extend(sorted(filtered_matches)) + return expanded_resources + + +def check_is_expert_agent_used(callback_context: CallbackContext): + is_expert_agent_used = callback_context.state.get(IS_EXPERT_AGENT_USED, None) + start_time = callback_context.state.get(EXPERT_AGENT_START_TIME, None) + if is_expert_agent_used is None: + raise ValueError("check_is_expert_agent_used: IS_EXPERT_AGENT_USED is not set in the state.") + if start_time is None: + raise ValueError("check_is_expert_agent_used: EXPERT_AGENT_START_TIME is not set in the state.") + + if is_expert_agent_used: + return types.Content( + parts=[types.Part(text=f"[system message]: Expert agent has already been used. " + f"Expert agent can ONLY be used once per user query. " + f"Explain the last response from expert agent to the user first. ")], + role="model" + ) + else: + callback_context.state[IS_EXPERT_AGENT_USED] = True + callback_context.state[EXPERT_AGENT_START_TIME] = time.time() + return None + + +def check_expert_agent_runtime(callback_context: CallbackContext): + is_expert_agent_used = callback_context.state.get(IS_EXPERT_AGENT_USED) + if is_expert_agent_used: + start_time = callback_context.state.get(EXPERT_AGENT_START_TIME) + if start_time: + elapsed_time = time.time() - start_time + logger.debug(f"*** Expert Agent Runtime: {elapsed_time:.2f} s " + f"({elapsed_time/60:.2f} min) ***") + return None + + +def check_llm_response(callback_context: CallbackContext, llm_response: LlmResponse): + agent_name = callback_context.agent_name + if llm_response.content and llm_response.content.parts: + if llm_response.content.parts[0].text: + original_text = llm_response.content.parts[0].text + logger.info((f"[Callback] Inspecting LLM response from '{agent_name}': " + f"{original_text}")) + elif llm_response.content.parts[0].function_call: + logger.info((f"[Callback] Inspecting LLM function call from '{agent_name}': " + f"{llm_response.content.parts[0].function_call.name}")) + else: + logger.info("[Callback] Inspected LLM response: No text content found.") + elif llm_response.error_message: + logger.error((f"[Callback] Inspected LLM response: " + f"Contains error '{llm_response.error_message}'. ")) + else: + logger.warning("[Callback] Inspected LLM response: Empty LlmResponse.") + return None + + +def check_tool_usage(tool: BaseTool, tool_context: ToolContext): + agent_name = tool_context.agent_name + tool_name = tool.name + + usage_key = f"{agent_name.upper()}_{tool_name.upper()}_USES" + if usage_key in tool_context.state: + uses_left = tool_context.state[usage_key] + if uses_left <= 0: + logger.debug(f"Usage key '{usage_key}' has no remaining uses.") + return {"result": f"\n[system message]: **WARNING** '{tool_name}' tool cannot be used anymore! "} + else: + tool_context.state[usage_key] -= 1 + logger.debug(f"Usage key '{usage_key}' decremented. Remaining uses: {tool_context.state[usage_key]}") + else: + logger.debug(f"Usage key '{usage_key}' not found in the state. Skipping tool usage check.") + return None + + +def check_tool_response(tool: BaseTool, + args: Dict[str, Any], + tool_context: ToolContext, + tool_response: Dict): + agent_name = tool_context.agent_name + tool_name = tool.name + result = tool_response.get("result", "") + max_tokens_key = f"{agent_name.upper()}_{tool_name.upper()}_MAX_TOKENS" + if max_tokens_key in tool_context.state: + max_tokens = tool_context.state[max_tokens_key] + try: + encoding = tiktoken.get_encoding("cl100k_base") + tokens = encoding.encode(result) + token_count = len(tokens) + if token_count > max_tokens: + # truncate the result to max_tokens + truncated_tokens = tokens[:max_tokens] + truncated_result = encoding.decode(truncated_tokens) + truncated_result += ("... \n[system message]: **WARNING** " + "Execution result was truncated due to token limit.") + logger.warning(f"'{tool_name.upper()}' execution (truncated) result: {truncated_result}") + # return a truncated tool_response dictionary + truncated_tool_response = deepcopy(tool_response) + truncated_tool_response["result"] = truncated_result + return truncated_tool_response + except Exception as e: + raise RuntimeError(f"Token counting failed: {e}.") + else: + logger.debug(f"max tokens key '{max_tokens_key}' not found in the state. Skipping tool response check.") + logger.info(f"'{tool_name.upper()}' execution result: {result}") + return None # Return None to indicate no modification to tool_response + diff --git a/optichat/tools/extract_tool.py b/optichat/tools/extract_tool.py new file mode 100644 index 0000000..d36f403 --- /dev/null +++ b/optichat/tools/extract_tool.py @@ -0,0 +1,232 @@ +import pyomo.environ as pe +from pyomo.opt import SolverFactory, SolverStatus, TerminationCondition +import cloudpickle +import os +from optichat.config.constants import TMP_MODEL_OBJECT_FOLDER + + +def extract_expressions_from_lp(lp_local_file_path: str): + """ + Process the .lp file given by lp_local_file_path, + get all expressions (constraints and objective) from the LP file. + TODO: This function works for modelling languages that load and write .lp files, + not very applicable to Pyomo (as far as I know) + + Args: + lp_local_file_path(str): path to the local LP file + + Returns: + dict: {name: {'expression': expression, 'component_type': "objective" or "constraint"}}. + """ + info = {} + with open(lp_local_file_path, 'r') as f: + lp_content = f.read() + obj_keywords_to_check = ["Minimize", "Maximize"] + existing_obj_keywords = [k for k in obj_keywords_to_check if k in lp_content] + if len(existing_obj_keywords) > 1: + raise ValueError(f"The LP file contains both {obj_keywords_to_check} sections.") + elif len(existing_obj_keywords) == 1: + obj_keyword = existing_obj_keywords[0] + else: + raise ValueError(f"The LP file does not contain any of {obj_keywords_to_check} section.") + if "Subject To" not in lp_content: + raise ValueError("The LP file does not contain 'Subject To' section.") + + objective_start = lp_content.find(obj_keyword) + objective_end = lp_content.find("Subject To") + objective_section = lp_content[objective_start:objective_end].strip() + # Parse the objective expression + lines = objective_section.split('\n') + objective_expr = obj_keyword + for line in lines: + line = line.strip() + if line and not line.startswith('\\'): # Skip comment lines + if ":" in line: + # Remove the objective name part (e.g., "__OBJ__:") + expr_part = line[line.find(":") + 1:].strip() + if expr_part: + objective_expr += " " + expr_part + elif line.startswith(('+', '-')) or any(char.isdigit() for char in line): + # This is a continuation line with coefficients and variables + objective_expr += " " + line + # TODO: address the special characters parsed by .lp file (check .lp file's parser and parse it back) + parsed_objective_expr = objective_expr.replace("@2D", "-") + info["obj"] = {"expression": parsed_objective_expr.strip(), "component_type": "objective"} + + # Extract constraint expressions + sections = lp_content.split("Subject To")[1] + # TODO: currently NOT handle constraints in "Bounds", "General", "Binary", "End" sections + next_sections = ["Bounds", "General", "Binary", "End"] + for section in next_sections: + if section in sections: + constraints_section = sections.split(section)[0] + break + else: + constraints_section = sections + lines = constraints_section.strip().split('\n') + i = 0 + while i < len(lines): + line = lines[i].strip() + # Check if this line starts with a constraint name followed by a colon + if ":" in line: + constraint_name = line.split(":")[0].strip() + # Extract the expression part (after the colon) + expression = line[line.find(":") + 1:].strip() + # Continue reading lines until the next constraint or end of section is found + j = i + 1 + while j < len(lines) and ":" not in lines[j] and lines[j].strip(): + expression += " " + lines[j].strip() + j += 1 + # TODO: address the special characters parsed by .lp file + parsed_constraint_name = constraint_name.replace("@2D", "-") + parsed_constraint_expr = expression.replace("@2D", "-") + info[parsed_constraint_name] = {"expression": parsed_constraint_expr.strip(), + "component_type": "constraint"} + # update i to j to skip the lines that have been processed + i = j - 1 + i += 1 + return info + + + +def extract_model_param(model, termination_condition): + """ + Extract parameters from a Pyomo model. + Information includes name, component_type, value, TODO:is_RHS? + """ + param_info = {} + for param in model.component_objects(pe.Param, active=True): + for idx in param: + param_info[pe.name(param[idx])] = {"component_type": "parameter", + "value": param[idx].value} + return param_info + + +def extract_model_var(model, termination_condition): + """ + Extract variables from a Pyomo model. + Information includes name, component_type, solution. + """ + var_info = {} + for var in model.component_objects(pe.Var, active=True): + for idx in var: + var_info[pe.name(var[idx])] = {"component_type": "variable", + "solution": var[idx].value} + return var_info + + +def extract_model_constraint(model, termination_condition): + """ + Extract constraints from a Pyomo model. + Information includes name, component_type, expression, TODO: is_binding needs verification + """ + eps = 1e-5 + constraint_info = {} + for constraint in model.component_objects(pe.Constraint, active=True): + for idx in constraint: + if str(termination_condition) == 'optimal': + if abs(constraint.lslack()) < eps or abs(constraint.uslack()) < eps: + is_binding = True + else: + is_binding = False + else: + is_binding = "unknown" + constraint_info[pe.name(constraint[idx])] = {"component_type": "constraint", + "expression": str(constraint[idx].expr), + "is_binding": is_binding} + return constraint_info + + +def extract_model_objective(model, termination_condition): + """ + Extract objectives from a Pyomo model. + Information includes name, component_type, expression (with sense: min/max), value. + """ + objective_info = {} + if len(model.component_objects(pe.Objective, active=True)) > 1: + raise ValueError("The model has multiple objectives, which is not supported.") + else: + obj = model.component_objects(pe.Objective, active=True)[0] + if obj.sense == pe.minimize: + obj_sense = "MINIMIZE: " + elif obj.sense == pe.maximize: + obj_sense = "MAXIMIZE: " + else: + raise ValueError(f"Unknown objective sense {obj.sense} for objective {pe.name(obj)}") + objective_info["obj"] = {"component_type": "objective", + "expression": obj_sense + str(obj.expr), + "sol_status": str(termination_condition), + "value": pe.value(obj) if str(termination_condition) == 'optimal' else "unknown"} + return objective_info + + +def extract_model_info(model, termination_condition='unknown'): + # parameters + param_info = extract_model_param(model, termination_condition) + # variables + var_info = extract_model_var(model, termination_condition) + # constraints + constraint_info = extract_model_constraint(model, termination_condition) + # objective + objective_info = extract_model_objective(model, termination_condition) + # combine all info + info = {**param_info, **var_info, **constraint_info, **objective_info} + return info + + +def restore_model_object(file_path): + """ + use cloudpickle to restore a Pyomo model object from a file. + """ + with open(file_path, mode='rb') as file: + model = cloudpickle.load(file) + return model + + +def save_model_object(model, file_name): + """ + use cloudpickle to save a Pyomo model object to a file. + """ + folder_name = os.path.join(os.getcwd(), TMP_MODEL_OBJECT_FOLDER) + os.makedirs(folder_name, exist_ok=True) + local_path_to_object = os.path.join(folder_name, f"{file_name}.pkl") + + with open(local_path_to_object, mode='wb') as file: + cloudpickle.dump(model, file) + return local_path_to_object + + +def auto_extract_function_docs(module_path: str) -> str: + """ + Automatically extracts function documentation from docstrings + for all functions in the specified module path. + Returns formatted strings that can be directly used in prompts. + + Args: + module_path (str): Path to the module to extract docs + (e.g., 'optichat.tools.shortcut_functions'). + + Returns: + str: Formatted documentation strings extracted from docstrings. + """ + try: + # Import the module dynamically + import importlib + module = importlib.import_module(module_path) + import inspect + docs = [] + for name, obj in inspect.getmembers(module, inspect.isfunction): + # Skip private functions and utility functions + if name.startswith("_") or name in ["auto_extract_function_docs"]: + continue + # Skip functions not defined in the target module + if obj.__module__ != module.__name__: + continue + # Get docstrings + docstring = inspect.getdoc(obj) + if docstring: + docs.append(docstring) + return "\n".join(docs) + except ImportError as e: + return f"Error importing module {module_path}: {e}" + diff --git a/optichat/tools/python_repl.py b/optichat/tools/python_repl.py new file mode 100644 index 0000000..4a20042 --- /dev/null +++ b/optichat/tools/python_repl.py @@ -0,0 +1,47 @@ +from typing import List, Dict, Any +from typing import Optional +from loguru import logger +from langchain_experimental.utilities import PythonREPL +# from langchain_core.tools import Tool +from google.adk.tools import ToolContext +from optichat.config.constants import * + +python_repl = PythonREPL() +# python_repl_tool = Tool( +# name="python_repl", +# description="A Python shell. Use this to execute python commands. Input should be a valid python snippet", +# func=python_repl.run, +# ) + + +def python_repl_func(code_snippet: str, tool_context: ToolContext) -> Dict[str, str]: + """ + Execute Python code and return the result. + ONLY interact with in code_snippet. + + Args: + code_snippet (str): Python code to execute + + Returns: + Dict[str, str]: a single key named "result" and its value as the execution result + """ + import optichat.tools.shortcut_functions as shortcut_functions + for name in dir(shortcut_functions): + item = getattr(shortcut_functions, name) + if callable(item) and not name.startswith("_"): + python_repl.globals[name] = item + logger.info(f"Injected shortcut function: {name} into REPL") + models_dictionary = tool_context.state[MODELS_DICTIONARY].copy() + python_repl.globals[MODELS_DICTIONARY.lower()] = models_dictionary + logger.info(f"Injected models_dictionary into REPL") + # execute the code snippet + logger.info(f"Python code to execute:\n{code_snippet}") + result = str(python_repl.run(code_snippet)) + # update MODELS_DICTIONARY if a model was modified and solved in REPL + tool_context.state[MODELS_DICTIONARY] = models_dictionary + tool_context.state[MODEL_VERSIONS] = list(models_dictionary.keys()) + return {"result": result} + + + + diff --git a/optichat/tools/rag_tool.py b/optichat/tools/rag_tool.py new file mode 100644 index 0000000..a9917c0 --- /dev/null +++ b/optichat/tools/rag_tool.py @@ -0,0 +1,52 @@ +from loguru import logger +from typing import Dict, Any +from typing import Optional +from google.genai import types +from google.adk.agents.callback_context import CallbackContext +from google.adk.tools.tool_context import ToolContext +from google.adk.tools.base_tool import BaseTool + + +def rag(request: str, models_code_cfg: Dict, number_of_results: int) -> str: + """ + TODO: check langchain rag + """ + return "todo: implement rag" + + +def code_rag(request: str, number_of_results: int, tool_context: ToolContext) -> str: + """ + code_rag retrieves code blocks from by + performing semantic similarity search against the submitted request. + + Args: + request: the information that you want to get from , be specific and detailed + number_of_results: The maximum number of search results to retrieve + (No more than 5 each time, so make your query specific and detailed). + + Returns: + string containing the code blocks that are relevant to the request submitted by you. + """ + cfg = tool_context.state["cfg"] + models_code_cfg = cfg.get("models_code", None) + result = rag(request, models_code_cfg, number_of_results) + return {"result": result} + + +def paper_rag(request: str, number_of_results: int, tool_context: ToolContext) -> str: + """ + paper_rag retrieves paper contents from by + performing semantic similarity search against the submitted request. + + Args: + request: the information that you want to get from , be specific and detailed + number_of_results: The maximum number of search results to retrieve + (No more than 5 each time, so make your query specific and detailed). + + Returns: + string containing the paper contents that are relevant to the request submitted by you. + """ + cfg = tool_context.state["cfg"] + models_paper_cfg = cfg.get("models_paper", None) + result = rag(request, models_paper_cfg, number_of_results) + return {"result": result} \ No newline at end of file diff --git a/optichat/tools/search_tool.py b/optichat/tools/search_tool.py new file mode 100644 index 0000000..4e43c76 --- /dev/null +++ b/optichat/tools/search_tool.py @@ -0,0 +1,117 @@ +from typing import List, Dict, Any +from typing import Optional +import re +import json +from loguru import logger +from google.adk.tools.tool_context import ToolContext +from optichat.config.constants import * + + +def wildcard_to_regex(pattern: str) -> str: + """ + Convert a wildcard pattern to a regex pattern. + The intuition of this function is to escape all regex special characters, as pyomo's component names usually contain "[", "]", "(", ")", etc. + Then only rely on '*' and '?' for wildcard matching. + + Args: + pattern (str): The wildcard pattern to convert. + + Returns: + str: The corresponding regex pattern. + """ + # Escape all regex special characters + regex_pattern = re.escape(pattern) + # Replace escaped wildcards with regex equivalents + regex_pattern = regex_pattern.replace(r'\*', '.*').replace(r'\?', '.') + # Anchor the pattern to match the whole string + return f'^{regex_pattern}$' + + +def get_model_components(version: List[str], component_type: str, pattern: str, + tool_context: ToolContext) -> Dict[str, str]: + """ + get_model_components is a robust and efficient searching method for model components. + This function retrieves information about specified model components that are stored in the session. + + Args: + version (List[str]): Model version(s) to search. Must be provided. Maximum 2 versions allowed. + component_type (str): **PRIMARY METHOD** Type of components to match against component. + Must be one of: ['objective', 'variable', 'constraint', or '' (empty string for all types)] + pattern (str): **BACKUP METHOD** Naming pattern to match against component. + Use this for additional filtering when the output by component_type alone is truncated. + Supports: + - Wildcard patterns: '*' (matches any characters), '?' (matches a single character). + Example: "x_*" matches "x_1", "x_transport", etc. + - Substring matching: Simple text matching (case-insensitive). + Example: "transport" matches "transport", "x_transport_A", "transport_cost", etc. + - Empty string: "" matches all component names. + + Returns: + Dict[str, str]: a dictionary with two keys: "status" and "result" + "status": "success" or "error" + "result": the information about the model components that match the specified version, component_type and pattern + """ + models_dictionary = tool_context.state[MODELS_DICTIONARY].copy() + versions = version + is_valid = True + result = "" + if len(versions) > 2: + is_valid = False + result += "**ERROR** Maximum 2 versions allowed at a time" + if pattern == "" and component_type == "": + is_valid = False + result += "**ERROR** At least one of [pattern, component_type] must be non-empty" + valid_component_types = ['objective', 'variable', 'constraint', ''] + if component_type not in valid_component_types: + is_valid = False + result += (f"**ERROR** component_type must be one of {valid_component_types}, " + f"but got '{component_type}'") + available_versions = list(models_dictionary.keys()) + missing_versions = [v for v in versions if v not in available_versions] + if missing_versions: + is_valid = False + result += (f"**ERROR** available versions are {available_versions}, " + f"but got '{missing_versions}'") + + result_dictionary = {} + # Process each version + for ver in versions: + # Pre-processing: solve if not solved yet + if models_dictionary[ver]["obj"].get("sol_status", "unknown") != "optimal": + model = load_model(ver, models_dictionary) + models_dictionary = solve_model(model, ver, models_dictionary) + tool_context.state[MODELS_DICTIONARY] = models_dictionary + tool_context.state[MODEL_VERSIONS] = list(models_dictionary.keys()) + + # Pattern searching logic + if pattern != "": + info = models_dictionary[ver] + pattern_matches = {} + if '*' in pattern or '?' in pattern: + regex_pattern = wildcard_to_regex(pattern) + compiled_pattern = re.compile(regex_pattern, re.IGNORECASE) + for k in info.keys(): + if compiled_pattern.match(k): + pattern_matches[k] = models_dictionary[ver][k] + else: + for k in info.keys(): + if pattern.lower() in k.lower(): + pattern_matches[k] = models_dictionary[ver][k] + else: + pattern_matches = models_dictionary[ver] + + # Type searching logic + if component_type != "": + type_matches = {} + for comp_name, comp_data in pattern_matches.items(): + if isinstance(comp_data, dict) and comp_data.get("component_type") == component_type: + # Exclude component_type field to save tokens since it's already filtered + comp_data_filtered = {k: v for k, v in comp_data.items() if k != "component_type"} + type_matches[comp_name] = comp_data_filtered + else: + type_matches = pattern_matches + + result_dictionary[ver] = type_matches # type_matches has already applied both pattern and type filtering + + return {"status": "success" if is_valid else "error", + "result": json.dumps(result_dictionary, indent=4) if is_valid else result} \ No newline at end of file diff --git a/optichat/tools/shortcut_functions.py b/optichat/tools/shortcut_functions.py new file mode 100644 index 0000000..daadfcb --- /dev/null +++ b/optichat/tools/shortcut_functions.py @@ -0,0 +1,94 @@ +from loguru import logger +import pyomo.environ as pe +from pyomo.opt import SolverFactory, SolverStatus, TerminationCondition +from optichat.tools.extract_tool import extract_model_info, restore_model_object, save_model_object + + +def load_model(version: str, models_dictionary: dict): + """ + ```model = load_model(version: str, models_dictionary: dict)``` + loads a model associated with a given version + """ + info = models_dictionary[version] + local_path_to_object = info["local_path_to_object"] + sol_status = info["obj"].get('sol_status', 'unknown') + objval = info["obj"].get('value', 'unknown') + + model = restore_model_object(local_path_to_object) + + print(f"Model, in version of {version}, is loaded.") + print(f"{version} Model status: {sol_status}") + print(f"{version} Model optimal objective value: {objval}") + return model + + +def solve_model(model: pe.ConcreteModel, version: str, models_dictionary: dict): + """ + ```new_models_dictionary = solve_model(model, version: str, models_dictionary: dict)``` + solves the model and update it in the models_dictionary by labelling it with the given version. + """ + time_limit_seconds = 180 + print(f"Solving model with time limit of {time_limit_seconds} seconds...") + solver = SolverFactory('gurobi') + solver.options['TimeLimit'] = time_limit_seconds + results = solver.solve(model, tee=False) + info = extract_model_info(model, results.solver.termination_condition) + + sol_status = info["obj"].get('sol_status', 'unknown') + objval = info["obj"].get('value', 'unknown') + + if sol_status != "optimal": + print(f"Model, in version of {version}, is NOT solved.") + else: + print(f"Model, in version of {version}, is solved.") + print(f"{version} Model status: {sol_status}") + print(f"{version} Model optimal objective value: {objval}") + + local_path_to_object = save_model_object(model, version) + info.update({ + "local_path_to_object": local_path_to_object, + }) + print(f"Model, in version of {version}, is updated in the models_dictionary.") + + models_dictionary.update({version: info}) + return models_dictionary + + +# def fix_variable(variable_name: str, value_to_fix: float | int, model: pe.ConcreteModel): +# """ +# ```fix_variable(variable_name: str, value_to_fix: float | int, model)``` +# fixes a variable in the model to a given value in place, returns nothing. +# """ +# var = model.find_component(variable_name) +# var.fix(value_to_fix) + + +# def unfix_variable(variable_name: str, model: pe.ConcreteModel): +# """ +# ```unfix_variable(variable_name: str, model)``` +# unfixes a variable in the model in place, returns nothing. +# """ +# var = model.find_component(variable_name) +# var.unfix() + + +# def add_constraint(constraint_name: str, expression: str, model: pe.ConcreteModel): +# """ +# ```add_constraint(constraint_name: str, expression: str, model)``` +# adds a constraint to the model in place, returns nothing. +# TODO: +# reconstruct pyomo expression from string +# - model.find_component(component_name) can get the actual pyomo component +# - need a way to rearrange the components into a valid pyomo expression from expression string +# need a way to parse indexed expression into pyomo rule function +# """ +# pass + + +# def deactivate_constraint(constraint_name: str, model: pe.ConcreteModel): +# """ +# ```deactivate_constraint(constraint_name: str, model)``` +# deactivates a constraint in the model in place, returns nothing. +# """ +# constraint = model.find_component(constraint_name) +# constraint.deactivate() \ No newline at end of file From c512ba048234a60681e0a7f4098bf13d2400608f Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Tue, 16 Sep 2025 10:49:03 -0400 Subject: [PATCH 04/30] add init models --- optichat/config/constants.py | 2 - optichat/sub_agents/expert/prompt.py | 2 +- optichat/sub_agents/root/agent.py | 32 +--------------- optichat/sub_agents/root/prompt.py | 3 +- optichat/tools/callback_tool.py | 57 +++++++++++++++++++++++++++- optichat/tools/extract_tool.py | 5 ++- optichat/tools/search_tool.py | 3 +- optichat/tools/shortcut_functions.py | 2 +- 8 files changed, 65 insertions(+), 41 deletions(-) diff --git a/optichat/config/constants.py b/optichat/config/constants.py index 2e9a5d2..0afeded 100644 --- a/optichat/config/constants.py +++ b/optichat/config/constants.py @@ -18,7 +18,6 @@ MODELS_DICTIONARY = "MODELS_DICTIONARY" MODEL_VERSIONS = "MODEL_VERSIONS" -NUM_OF_MODELS = "NUM_OF_MODELS" IS_MODELS_DICTIONARY_AVAILABLE = "IS_MODELS_DICTIONARY_AVAILABLE" IS_MODELS_CODE_AVAILABLE = "IS_MODELS_CODE_AVAILABLE" IS_MODELS_PAPER_AVAILABLE = "IS_MODELS_PAPER_AVAILABLE" @@ -42,7 +41,6 @@ OUTPUT_KEY_EXPERT_AGENT: "", MODELS_DICTIONARY: {}, MODEL_VERSIONS: [], - NUM_OF_MODELS: 0, IS_MODELS_DICTIONARY_AVAILABLE: False, IS_MODELS_CODE_AVAILABLE: False, IS_MODELS_PAPER_AVAILABLE: False, diff --git a/optichat/sub_agents/expert/prompt.py b/optichat/sub_agents/expert/prompt.py index fbd387a..4b8972b 100644 --- a/optichat/sub_agents/expert/prompt.py +++ b/optichat/sub_agents/expert/prompt.py @@ -9,7 +9,7 @@ RESOURCES (dynamic availability: {IS_MODELS_DICTIONARY_AVAILABLE}): - the optimization models labelled with version names, {MODEL_VERSIONS}, {num_of_models} models in total. + the optimization models labelled with version names, {MODEL_VERSIONS}. (dynamic availability: {IS_MODELS_CODE_AVAILABLE}): code used to implement the optimization models. diff --git a/optichat/sub_agents/root/agent.py b/optichat/sub_agents/root/agent.py index fbb91b7..c4a4cf7 100644 --- a/optichat/sub_agents/root/agent.py +++ b/optichat/sub_agents/root/agent.py @@ -1,42 +1,12 @@ from google.adk.agents import LlmAgent, BaseAgent, LoopAgent, SequentialAgent, ParallelAgent, Agent from google.adk.tools.agent_tool import AgentTool from optichat.llm import * -from optichat.config.constants import * +from optichat.config.constants import OUTPUT_KEY_ROOT_AGENT from optichat.sub_agents.root.prompt import * from optichat.sub_agents.expert.agent import create_expert_agent from optichat.tools.callback_tool import (initialize_session, initialize_query) - - - -def get_weather(city: str) -> dict: - """Retrieves the current weather report for a specified city. - - Args: - city (str): The name of the city (e.g., "New York", "London", "Tokyo"). - - Returns: - dict: A dictionary containing the weather information. - Includes a 'status' key ('success' or 'error'). - If 'success', includes a 'report' key with weather details. - If 'error', includes an 'error_message' key. - """ - print(f"--- Tool: get_weather called for city: {city} ---") # Log tool execution - city_normalized = city.lower().replace(" ", "") # Basic normalization - - # Mock weather data - mock_weather_db = { - "newyork": {"status": "success", "report": "The weather in New York is sunny with a temperature of 25°C."}, - "london": {"status": "success", "report": "It's cloudy in London with a temperature of 15°C."}, - "tokyo": {"status": "success", "report": "Tokyo is experiencing light rain and a temperature of 18°C."}, - } - - if city_normalized in mock_weather_db: - return mock_weather_db[city_normalized] - else: - return {"status": "error", "error_message": f"Sorry, I don't have weather information for '{city}'."} - def create_root_agent(workflow="default"): if workflow == "default": expert_agent = create_expert_agent(prompt_version=1, tools_version=1) diff --git a/optichat/sub_agents/root/prompt.py b/optichat/sub_agents/root/prompt.py index 98bf3b4..cdf3848 100644 --- a/optichat/sub_agents/root/prompt.py +++ b/optichat/sub_agents/root/prompt.py @@ -4,8 +4,7 @@ RESOURCES (Dynamic Availability: {IS_MODELS_DICTIONARY_AVAILABLE}): - The optimization models labelled with version names {MODEL_VERSIONS} - ({NUM_OF_MODELS} in total). + The optimization models labelled with version names {MODEL_VERSIONS}. (Dynamic Availability: {IS_MODELS_CODE_AVAILABLE}): Code used to implement the optimization models. diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py index e7cb977..bb44692 100644 --- a/optichat/tools/callback_tool.py +++ b/optichat/tools/callback_tool.py @@ -2,6 +2,7 @@ import json import os import glob +from xml.parsers.expat import model import tiktoken from loguru import logger from typing import Dict, Any, List @@ -13,12 +14,15 @@ from google.adk.tools.base_tool import BaseTool from google.adk.models import LlmResponse, LlmRequest from optichat.config.constants import (IS_SESSION_INITIALIZED, PERSISTENT_STATES, TEMPORARY_STATES, - CFG, IS_EXPERT_AGENT_USED, EXPERT_AGENT_START_TIME) + CFG, IS_EXPERT_AGENT_USED, EXPERT_AGENT_START_TIME, + MODELS_DICTIONARY, MODEL_VERSIONS, IS_MODELS_DICTIONARY_AVAILABLE, + IS_MODELS_CODE_AVAILABLE, IS_MODELS_PAPER_AVAILABLE) +from optichat.tools.extract_tool import restore_model_object, extract_model_info def initialize_session(callback_context: CallbackContext): if IS_SESSION_INITIALIZED not in callback_context.state: - callback_context.state.update(PERSISTENT_STATES) + callback_context.state.update(PERSISTENT_STATES) # add IS_SESSION_INITIALIZED as False callback_context.state.update(TEMPORARY_STATES) user_content = callback_context.user_content @@ -33,6 +37,19 @@ def initialize_session(callback_context: CallbackContext): cfg = json.loads(raw.decode("utf-8")) cfg = _init_cfg(cfg) callback_context.state[CFG] = cfg + models_dictionary, model_versions = _init_models(cfg) + is_model_dictionary_available = len(models_dictionary) > 0 + callback_context.state[MODELS_DICTIONARY] = models_dictionary + callback_context.state[MODEL_VERSIONS] = model_versions + callback_context.state[IS_MODELS_DICTIONARY_AVAILABLE] = is_model_dictionary_available + # TODO: complete these two functions after rag function is ready + some_output_for_code_rag_fn_use = _init_models_code(cfg) + callback_context.state["some_output_for_code_rag_fn_use"] = some_output_for_code_rag_fn_use + callback_context.state[IS_MODELS_CODE_AVAILABLE] = False # TODO + some_output_for_paper_rag_fn_use = _init_models_paper(cfg) + callback_context.state["some_output_for_paper_rag_fn_use"] = some_output_for_paper_rag_fn_use + callback_context.state[IS_MODELS_PAPER_AVAILABLE] = False # TODO + callback_context.state[IS_SESSION_INITIALIZED] = True else: parts_wo_json.append(part) else: @@ -48,6 +65,42 @@ def initialize_query(callback_context: CallbackContext, llm_request: LlmRequest) return None +def _init_models(cfg: dict): + models_dictionary = {} + model_versions = [] + if "models" in cfg: + for resource_path in cfg["models"].get("local_resources", []): + model, version = restore_model_object(resource_path) + # TODO: need some way to introduce termination_condition smartly + # pyomo model's termination_condition is stored in results = solver.solve(model, tee=False) + from pyomo.opt import SolverFactory + solver = SolverFactory('gurobi') + results = solver.solve(model, tee=False) + termination_condition = results.solver.termination_condition + # but we only stored the model object. + # here assume we solve the model again no matter whether .pkl object is solved before. + info = extract_model_info(model, termination_condition=termination_condition) + models_dictionary.update({version: info}) + model_versions.append(version) + return models_dictionary, model_versions + + +def _init_models_code(cfg: dict): + some_output_for_rag_fn_use = None + if "models_code" in cfg: + for resource_path in cfg["models_code"].get("local_resources", []): + pass + return some_output_for_rag_fn_use + + +def _init_models_paper(cfg: dict): + some_output_for_rag_fn_use = None + if "models_paper" in cfg: + for resource_path in cfg["models_paper"].get("local_resources", []): + pass + return some_output_for_rag_fn_use + + def _init_cfg(cfg: dict): cfg_out = deepcopy(cfg) diff --git a/optichat/tools/extract_tool.py b/optichat/tools/extract_tool.py index d36f403..5264731 100644 --- a/optichat/tools/extract_tool.py +++ b/optichat/tools/extract_tool.py @@ -177,15 +177,18 @@ def extract_model_info(model, termination_condition='unknown'): def restore_model_object(file_path): """ use cloudpickle to restore a Pyomo model object from a file. + Note that file_name without suffix. .pkl is returned as well. """ with open(file_path, mode='rb') as file: model = cloudpickle.load(file) - return model + file_name = os.path.splitext(os.path.basename(file_path))[0] + return model, file_name def save_model_object(model, file_name): """ use cloudpickle to save a Pyomo model object to a file. + Note that file_name is without suffix .pkl """ folder_name = os.path.join(os.getcwd(), TMP_MODEL_OBJECT_FOLDER) os.makedirs(folder_name, exist_ok=True) diff --git a/optichat/tools/search_tool.py b/optichat/tools/search_tool.py index 4e43c76..701e092 100644 --- a/optichat/tools/search_tool.py +++ b/optichat/tools/search_tool.py @@ -4,7 +4,8 @@ import json from loguru import logger from google.adk.tools.tool_context import ToolContext -from optichat.config.constants import * +from optichat.config.constants import MODELS_DICTIONARY, MODEL_VERSIONS +from optichat.tools.shortcut_functions import load_model, solve_model def wildcard_to_regex(pattern: str) -> str: diff --git a/optichat/tools/shortcut_functions.py b/optichat/tools/shortcut_functions.py index daadfcb..c714624 100644 --- a/optichat/tools/shortcut_functions.py +++ b/optichat/tools/shortcut_functions.py @@ -14,7 +14,7 @@ def load_model(version: str, models_dictionary: dict): sol_status = info["obj"].get('sol_status', 'unknown') objval = info["obj"].get('value', 'unknown') - model = restore_model_object(local_path_to_object) + model, file_name = restore_model_object(local_path_to_object) print(f"Model, in version of {version}, is loaded.") print(f"{version} Model status: {sol_status}") From 3a2c49caa69726e948c4a734299f66027b4ede4b Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Wed, 17 Sep 2025 15:37:58 -0400 Subject: [PATCH 05/30] add rag --- optichat/config/cfg_template.py | 1 + optichat/config/rag_cfg.py | 35 ++++++++ optichat/tools/callback_tool.py | 51 +++++++---- optichat/tools/extract_tool.py | 6 +- optichat/tools/rag_tool.py | 128 +++++++++++++++++++++++---- optichat/tools/shortcut_functions.py | 2 +- 6 files changed, 182 insertions(+), 41 deletions(-) create mode 100644 optichat/config/rag_cfg.py diff --git a/optichat/config/cfg_template.py b/optichat/config/cfg_template.py index 5e5af06..5e4691e 100644 --- a/optichat/config/cfg_template.py +++ b/optichat/config/cfg_template.py @@ -1,6 +1,7 @@ import json cfg_template = { + "model_name": "your_model_name_here", "models": { "local_resources": [ "models/*", diff --git a/optichat/config/rag_cfg.py b/optichat/config/rag_cfg.py new file mode 100644 index 0000000..e760627 --- /dev/null +++ b/optichat/config/rag_cfg.py @@ -0,0 +1,35 @@ +EMBEDDING_MODEL = "text-embedding-3-large" +PERSIST_DIRECTORY = "./chroma_langchain_db" + + +# the minimum number of lines that the source code file must have to be segmented using the parser +CODE_RAG_PARSER_THRESHOLD = 100 +CODE_RAG_IS_SPLITTED = False +CODE_RAG_CHUNK_SIZE = 100 +CODE_RAG_CHUNK_OVERLAP = 10 +CODE_RAG_SEARCH_TYPE = "similarity" # similarity”, “mmr”, or “similarity_score_threshold” +CODE_RAG_NUM_OF_RESULTS = 4 +CODE_RAG_NUM_OF_FETCH_K = 10 # only for mmr +CODE_RAG_LAMBDA_MULT = 0.5 # only for mmr +CODE_RAG_SCORE_THRESHOLD = 0.8 # only for similarity_score_threshold +CODE_RAG_SEARCH_KWARGS = {"k": CODE_RAG_NUM_OF_RESULTS, + "fetch_k": CODE_RAG_NUM_OF_FETCH_K, + "lambda_mult": CODE_RAG_LAMBDA_MULT, + "score_threshold": CODE_RAG_SCORE_THRESHOLD} + + +PAPER_RAG_IS_SPLITTED = False +PAPER_RAG_CHUNK_SIZE = 1000 +PAPER_RAG_CHUNK_OVERLAP = 100 +PAPER_RAG_SEARCH_TYPE = "similarity" # similarity”, “mmr”, or “similarity_score_threshold” +PAPER_RAG_NUM_OF_RESULTS = 4 +PAPER_RAG_NUM_OF_FETCH_K = 10 # only for mmr +PAPER_RAG_LAMBDA_MULT = 0.5 # only for mmr +PAPER_RAG_SCORE_THRESHOLD = 0.8 # only for similarity_score_threshold +PAPER_RAG_SEARCH_KWARGS = {"k": PAPER_RAG_NUM_OF_RESULTS, + "fetch_k": PAPER_RAG_NUM_OF_FETCH_K, + "lambda_mult": PAPER_RAG_LAMBDA_MULT, + "score_threshold": PAPER_RAG_SCORE_THRESHOLD} + + + diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py index bb44692..eee9788 100644 --- a/optichat/tools/callback_tool.py +++ b/optichat/tools/callback_tool.py @@ -18,11 +18,12 @@ MODELS_DICTIONARY, MODEL_VERSIONS, IS_MODELS_DICTIONARY_AVAILABLE, IS_MODELS_CODE_AVAILABLE, IS_MODELS_PAPER_AVAILABLE) from optichat.tools.extract_tool import restore_model_object, extract_model_info +from optichat.tools.rag_tool import init_paper_rag, init_code_rag def initialize_session(callback_context: CallbackContext): if IS_SESSION_INITIALIZED not in callback_context.state: - callback_context.state.update(PERSISTENT_STATES) # add IS_SESSION_INITIALIZED as False + callback_context.state.update(PERSISTENT_STATES) # which also set IS_SESSION_INITIALIZED as False callback_context.state.update(TEMPORARY_STATES) user_content = callback_context.user_content @@ -42,13 +43,10 @@ def initialize_session(callback_context: CallbackContext): callback_context.state[MODELS_DICTIONARY] = models_dictionary callback_context.state[MODEL_VERSIONS] = model_versions callback_context.state[IS_MODELS_DICTIONARY_AVAILABLE] = is_model_dictionary_available - # TODO: complete these two functions after rag function is ready - some_output_for_code_rag_fn_use = _init_models_code(cfg) - callback_context.state["some_output_for_code_rag_fn_use"] = some_output_for_code_rag_fn_use - callback_context.state[IS_MODELS_CODE_AVAILABLE] = False # TODO - some_output_for_paper_rag_fn_use = _init_models_paper(cfg) - callback_context.state["some_output_for_paper_rag_fn_use"] = some_output_for_paper_rag_fn_use - callback_context.state[IS_MODELS_PAPER_AVAILABLE] = False # TODO + is_models_code_available = _init_models_code(cfg) + callback_context.state[IS_MODELS_CODE_AVAILABLE] = is_models_code_available + is_models_paper_available = _init_models_paper(cfg) + callback_context.state[IS_MODELS_PAPER_AVAILABLE] = is_models_paper_available callback_context.state[IS_SESSION_INITIALIZED] = True else: parts_wo_json.append(part) @@ -86,19 +84,27 @@ def _init_models(cfg: dict): def _init_models_code(cfg: dict): - some_output_for_rag_fn_use = None if "models_code" in cfg: - for resource_path in cfg["models_code"].get("local_resources", []): - pass - return some_output_for_rag_fn_use + paths = cfg["models_code"].get("local_resources", []) + model_name = cfg.get("model_name", "default_model") + init_code_rag(paths, model_name) + is_models_code_available = True + else: + logger.debug("No 'models_code' in cfg") + is_models_code_available = False + return is_models_code_available def _init_models_paper(cfg: dict): - some_output_for_rag_fn_use = None if "models_paper" in cfg: - for resource_path in cfg["models_paper"].get("local_resources", []): - pass - return some_output_for_rag_fn_use + paths = cfg["models_paper"].get("local_resources", []) + model_name = cfg.get("model_name", "default_model") + init_paper_rag(paths, model_name) + is_models_paper_available = True + else: + logger.debug("No 'models_paper' in cfg") + is_models_paper_available = False + return is_models_paper_available def _init_cfg(cfg: dict): @@ -115,9 +121,16 @@ def _init_cfg(cfg: dict): if section_key in required_sections: local_resources = section_cfg.get("local_resources", []) allowed_extensions = extension_filters.get(section_key, None) - expanded_resources = _expand_resources(local_resources, allowed_extensions) - cfg_out[section_key]["local_resources"] = expanded_resources - + # TODO: temporary solution to use init_code_rag() in rag_tool.py + if section_key == "models_code": + logger.warning(("For 'models_code', ONLY one path is supported for now, " + "which must be a .py file or a wildcard path to indicate a folder. " + "No expand_resources() is performed for 'models_code' in cfg.")) + assert len(local_resources) == 1, "ONLY one path for models_code is supported for now." + assert local_resources[0].endswith(".py") or local_resources[0].endswith("*"), "models_code path must be a .py file or a wildcard path." + else: + expanded_resources = _expand_resources(local_resources, allowed_extensions) + cfg_out[section_key]["local_resources"] = expanded_resources return cfg_out diff --git a/optichat/tools/extract_tool.py b/optichat/tools/extract_tool.py index 5264731..1419a42 100644 --- a/optichat/tools/extract_tool.py +++ b/optichat/tools/extract_tool.py @@ -9,8 +9,10 @@ def extract_expressions_from_lp(lp_local_file_path: str): """ Process the .lp file given by lp_local_file_path, get all expressions (constraints and objective) from the LP file. - TODO: This function works for modelling languages that load and write .lp files, + + **This function works for modelling languages that load and write .lp files, not very applicable to Pyomo (as far as I know) + Therefore this is NOT USED for now.** Args: lp_local_file_path(str): path to the local LP file @@ -118,7 +120,7 @@ def extract_model_var(model, termination_condition): def extract_model_constraint(model, termination_condition): """ Extract constraints from a Pyomo model. - Information includes name, component_type, expression, TODO: is_binding needs verification + Information includes name, component_type, expression, TODO: is_binding implementation here needs verification """ eps = 1e-5 constraint_info = {} diff --git a/optichat/tools/rag_tool.py b/optichat/tools/rag_tool.py index a9917c0..6bc7d3b 100644 --- a/optichat/tools/rag_tool.py +++ b/optichat/tools/rag_tool.py @@ -1,52 +1,142 @@ from loguru import logger -from typing import Dict, Any +from typing import Dict, Any, List from typing import Optional from google.genai import types from google.adk.agents.callback_context import CallbackContext from google.adk.tools.tool_context import ToolContext from google.adk.tools.base_tool import BaseTool +from langchain_chroma import Chroma +from langchain_openai import OpenAIEmbeddings +from langchain_community.document_loaders import PyPDFLoader +from langchain_community.document_loaders.text import TextLoader +from langchain_community.document_loaders.generic import GenericLoader +from langchain_community.document_loaders.parsers import LanguageParser +from langchain_text_splitters import Language, RecursiveCharacterTextSplitter +from openai import embeddings +from optichat.config.constants import CFG +from optichat.config.rag_cfg import * -def rag(request: str, models_code_cfg: Dict, number_of_results: int) -> str: + +def init_code_rag(path: str, model_name: str): + """ +path -> docs -> update vector store collection +Recommended way to load source code: +https://docs.langchain.com/oss/python/integrations/document_loaders/source_code +The parser can be disabled for small files. +This approach needs path to be a folder (or a single file) and uses glob pattern to load files. +TODO: Not sure if there exists an alternative way to load files from a list of specific files. + """ + code_loader = GenericLoader.from_filesystem( + path, + glob="*", + suffixes=[".py"], + parser=LanguageParser(language=Language.PYTHON, parser_threshold=CODE_RAG_PARSER_THRESHOLD)) + docs = code_loader.load() + + if CODE_RAG_IS_SPLITTED: + code_splitter = RecursiveCharacterTextSplitter.from_language( + language=Language.PYTHON, chunk_size=CODE_RAG_CHUNK_SIZE, chunk_overlap=CODE_RAG_CHUNK_OVERLAP) + docs = code_splitter.split_documents(docs) + + collection_name = f"{model_name}_code" + init_chroma_collection(collection_name, docs, empty_existing=True) + + +def init_paper_rag(paths: List[str], model_name: str): """ - TODO: check langchain rag + path -> docs -> update vector store collection """ - return "todo: implement rag" + docs = [] + for path in paths: + if path.endswith(".pdf"): + pdf_loader = PyPDFLoader(path) + docs.extend(pdf_loader.load()) + elif path.endswith(".txt"): + txt_loader = TextLoader(path) + docs.extend(txt_loader.load()) + else: + raise ValueError(f"File type of {path} not supported.") + if PAPER_RAG_IS_SPLITTED: + paper_splitter = RecursiveCharacterTextSplitter( + chunk_size=PAPER_RAG_CHUNK_SIZE, chunk_overlap=PAPER_RAG_CHUNK_OVERLAP, add_start_index=True) + docs = paper_splitter.split_documents(docs) -def code_rag(request: str, number_of_results: int, tool_context: ToolContext) -> str: + collection_name = f"{model_name}_paper" + init_chroma_collection(collection_name, docs, empty_existing=True) + + +def init_chroma_collection(collection_name, docs, empty_existing): + embeddings = OpenAIEmbeddings(model=EMBEDDING_MODEL) + persist_directory = PERSIST_DIRECTORY + if empty_existing: + # TODO: for development only, delete the collection first and then add documents to re-build the collection again + vector_store = get_chroma_vs(collection_name, embeddings, persist_directory) + logger.debug(f"Deleting collection {[col.name for col in vector_store._client.list_collections()]} first for re-building.") + vector_store._client.delete_collection(name=collection_name) + logger.debug(f"After deletion, existing collections are {[col.name for col in vector_store._client.list_collections()]}") + vector_store = get_chroma_vs(collection_name, embeddings, persist_directory) + logger.debug(f"Building collection {vector_store.collection_name} by adding documents...") + vector_store.add_documents(documents=docs) + logger.debug(f"After adding documents, existing collections are {[col.name for col in vector_store._client.list_collections()]}") + + +def get_chroma_vs(collection_name, embeddings, persist_directory): + vector_store = Chroma( + collection_name=collection_name, + embedding_function=embeddings, + persist_directory=persist_directory) + return vector_store + + +def code_rag(request: str, tool_context: ToolContext) -> str: """ code_rag retrieves code blocks from by performing semantic similarity search against the submitted request. Args: request: the information that you want to get from , be specific and detailed - number_of_results: The maximum number of search results to retrieve - (No more than 5 each time, so make your query specific and detailed). Returns: string containing the code blocks that are relevant to the request submitted by you. """ - cfg = tool_context.state["cfg"] - models_code_cfg = cfg.get("models_code", None) - result = rag(request, models_code_cfg, number_of_results) - return {"result": result} - + cfg = tool_context.state[CFG] + if "models_code" in cfg: + model_name = cfg["model_name"] + collection_name = f"{model_name}_code" + vector_store = get_chroma_vs(collection_name=collection_name, + embeddings=OpenAIEmbeddings(model=EMBEDDING_MODEL), + persist_directory=PERSIST_DIRECTORY) + retriever = vector_store.as_retriever(search_type=CODE_RAG_SEARCH_TYPE, + search_kwargs=CODE_RAG_SEARCH_KWARGS) + result = retriever.invoke(request) + return {"result": result} + else: + return {"result": "No 'models_code' in cfg, cannot use code_rag."} + -def paper_rag(request: str, number_of_results: int, tool_context: ToolContext) -> str: +def paper_rag(request: str, tool_context: ToolContext) -> str: """ paper_rag retrieves paper contents from by performing semantic similarity search against the submitted request. Args: request: the information that you want to get from , be specific and detailed - number_of_results: The maximum number of search results to retrieve - (No more than 5 each time, so make your query specific and detailed). Returns: string containing the paper contents that are relevant to the request submitted by you. """ - cfg = tool_context.state["cfg"] - models_paper_cfg = cfg.get("models_paper", None) - result = rag(request, models_paper_cfg, number_of_results) - return {"result": result} \ No newline at end of file + cfg = tool_context.state[CFG] + if "models_paper" in cfg: + model_name = cfg["model_name"] + collection_name = f"{model_name}_paper" + vector_store = get_chroma_vs(collection_name=collection_name, + embeddings=OpenAIEmbeddings(model=EMBEDDING_MODEL), + persist_directory=PERSIST_DIRECTORY) + retriever = vector_store.as_retriever(search_type=PAPER_RAG_SEARCH_TYPE, + search_kwargs=PAPER_RAG_SEARCH_KWARGS) + result = retriever.invoke(request) + return {"result": result} + else: + return {"result": "No 'models_paper' in cfg, cannot use paper_rag."} \ No newline at end of file diff --git a/optichat/tools/shortcut_functions.py b/optichat/tools/shortcut_functions.py index c714624..067cd64 100644 --- a/optichat/tools/shortcut_functions.py +++ b/optichat/tools/shortcut_functions.py @@ -76,7 +76,7 @@ def solve_model(model: pe.ConcreteModel, version: str, models_dictionary: dict): # """ # ```add_constraint(constraint_name: str, expression: str, model)``` # adds a constraint to the model in place, returns nothing. -# TODO: +# TODO: the most difficult part # reconstruct pyomo expression from string # - model.find_component(component_name) can get the actual pyomo component # - need a way to rearrange the components into a valid pyomo expression from expression string From 91a93980b59e7fe1160dceea11d3d0bc37748766 Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Wed, 17 Sep 2025 15:47:53 -0400 Subject: [PATCH 06/30] add prompt to NOT use sc fn --- optichat/sub_agents/expert/prompt.py | 84 +++++++++++++++++++++++++++- optichat/sub_agents/root/prompt.py | 13 +++-- 2 files changed, 91 insertions(+), 6 deletions(-) diff --git a/optichat/sub_agents/expert/prompt.py b/optichat/sub_agents/expert/prompt.py index 4b8972b..80ed7e6 100644 --- a/optichat/sub_agents/expert/prompt.py +++ b/optichat/sub_agents/expert/prompt.py @@ -1,3 +1,84 @@ +EXPERT_AGENT_PROMPT_NO_SC = """ +USER QUERY +{USER_QUERY} + +RESPONSIBILITIES +You are an optimization & operations research expert that +use CONTEXT TOOLS to interact with RESOURCES following the WORKFLOW, +and answers the USER QUERY based on the interactions. + +RESOURCES + (dynamic availability: {IS_MODELS_DICTIONARY_AVAILABLE}): + the optimization models labelled with version names, {MODEL_VERSIONS}. + + (dynamic availability: {IS_MODELS_CODE_AVAILABLE}): + code used to implement the optimization models. + + (dynamic availability: {IS_MODELS_PAPER_AVAILABLE}): + scientific papers associated with the optimization models. + +CONTEXT TOOLS + - `get_model_components` + resource access: + result type: deterministic and fast, retrieve information about model components in existing + - `python_repl_func` (Limited Uses Left: {EXPERT_AGENT_PYTHON_REPL_FUNC_USES}) + resource access: + result type: dynamic and slow (error-prone), load, modify and solve new ONLY + - `code_rag` (Limited Uses Left: {EXPERT_AGENT_CODE_RAG_USES}) + resource access: + result type: dynamic and slow, retrieve code blocks + - `paper_rag` (Limited Uses Left: {EXPERT_AGENT_PAPER_RAG_USES}) + resource access: + result type: dynamic and slow, retrieve code contents + +WORKFLOW +1. classify the USER QUERY and find the appropriate explanation strategy from PRIOR KNOWLEDGE +2. use CONTEXT TOOLS to interact with RESOURCES for information gathering +3. answer the USER QUERY + +PRIOR KNOWLEDGE +__MODELS_RECIPE_PLACEHOLDER__ +__EXPLANATIONS_RECIPE_PLACEHOLDER__ + +TOOL CONVENTIONS +`get_model_components` conventions + - searching by component_type provides complete information about a component type efficiently + through a single tool call, but may be truncated if too many components are in . + - searching by pattern provides more granular filtering to prevent truncation, + but requires much more tool calls if complete information about a component type is desired. + - if new was solved in previous `python_repl_func` call, + complete information about the new can be retrieved by `get_model_components`. + - Examples: + get_model_components(["v1", "v2"], "objective", "", tool_context) compares objective between v1 and v2 + get_model_components(["v1"], "variable", "", tool_context) gets all decision variables in v1 + get_model_components(["v1"], "constraint", "", tool_context) gets all constraints in v1 + get_model_components(["v1"], "", "ramp*", tool_context) gets ramp-related components in v1 when previous result was truncated + get_model_components(["v2"], "constraint", "transport*", tool_context) gets transport-related constraints in v2 when previous result was truncated +`python_repl_func` conventions + - ONLY used when necessary: + only when USER QUERY explicitly falls into the categories that requires new in PRIOR KNOWLEDGE + - Concise code snippet: + STOP the code snippet as soon as new are programmed to be solved. + NEVER look up information about new in the code snippet. Use `get_model_components` instead + - Shortcut functions: + models_dictionary is a internal object that stores all and has already been loaded for you. + use the following generic shortcut functions and models_dictionary to load and solve . + HOWEVER, NEVER interact with models_dictionary directly as it is for internal use only. + __SHORTCUT_FUNCTIONS_PLACEHOLDER__ +`code_rag` & `paper_rag` conventions + - ONLY used in the end: + only when have been thoroughly analyzed with PRIOR KNOWLEDGE, + the code blocks and paper contents are version-agnostic and can ONLY serve as supplementary information + prioritize using `get_model_components` and `python_repl_func` first + +RESPONSE STYLE +- coherent and information-grounded narrative +- NEVER be obsessed with calculating statistics and verifying user's observations +- focus on **explanations and analysis** to answer the USER QUERY +- NEVER do extra work. NEVER explore randomly. +""" + + EXPERT_AGENT_PROMPT = """ USER QUERY {USER_QUERY} @@ -81,4 +162,5 @@ """ -EXPERT_AGENT_PROMPTS = {1: EXPERT_AGENT_PROMPT} \ No newline at end of file +EXPERT_AGENT_PROMPTS = {1: EXPERT_AGENT_PROMPT_NO_SC, + 2: EXPERT_AGENT_PROMPT} \ No newline at end of file diff --git a/optichat/sub_agents/root/prompt.py b/optichat/sub_agents/root/prompt.py index cdf3848..d9a9acc 100644 --- a/optichat/sub_agents/root/prompt.py +++ b/optichat/sub_agents/root/prompt.py @@ -1,6 +1,6 @@ ROOT_AGENT_PROMPT = """ You're the root agent, a coordinator between the user and sub-agents. -Your task is to understand the user's queries and delegate them to the appropriate sub-agents for processing. +Your task is to understand the user's queries and delegate them to the appropriate sub-agents for processing if applicable. RESOURCES (Dynamic Availability: {IS_MODELS_DICTIONARY_AVAILABLE}): @@ -13,13 +13,16 @@ Scientific papers associated with the optimization models. TOOLS -expert_agent +`expert_agent` Resource access: , , RESPONSE STYLE -information-grounded but user-friendly response is preferred. -- the sub-agents gather trustworthy and technical information from the available resources. -NEVER speculate. NEVER make up information. +information-grounded response is preferred. +- the `expert_agent` gather trustworthy and technical information from the available resources. +if the query requires deep analysis and explanation, use the `expert_agent` first. +NEVER speculate yourself. NEVER make up information yourself. + +user-friendly response is preferred. - the user has little knowledge of optimization and operations research, but is familiar with the problem context that the optimization models are designed for. Avoid jargon, complex terminology without explanations, and overwhelming mathematical expressions and code snippets. From 86998cad6c1ba3dd4d4d6c19d54927b82add7cb8 Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Mon, 22 Sep 2025 10:03:49 -0400 Subject: [PATCH 07/30] fix start_time not init, args missing in check_tool_usage; monitor root agent output --- optichat/config/constants.py | 5 ++++- optichat/sub_agents/expert/agent.py | 2 +- optichat/sub_agents/root/agent.py | 6 ++++-- optichat/tools/callback_tool.py | 12 +++++++----- 4 files changed, 16 insertions(+), 9 deletions(-) diff --git a/optichat/config/constants.py b/optichat/config/constants.py index 0afeded..fc9e0d1 100644 --- a/optichat/config/constants.py +++ b/optichat/config/constants.py @@ -1,6 +1,8 @@ IS_SESSION_INITIALIZED = "IS_SESSION_INITIALIZED" +USER_QUERY = "USER_QUERY" + OUTPUT_KEY_ROOT_AGENT = "OUTPUT_KEY_ROOT_AGENT" IS_EXPERT_AGENT_USED = "IS_EXPERT_AGENT_USED" @@ -50,10 +52,11 @@ # reset for every query TEMPORARY_STATES = { + USER_QUERY: "", IS_EXPERT_AGENT_USED: False, EXPERT_AGENT_PYTHON_REPL_FUNC_USES: 5, EXPERT_AGENT_CODE_RAG_USES: 1, EXPERT_AGENT_PAPER_RAG_USES: 1, - EXPERT_AGENT_START_TIME: None, + EXPERT_AGENT_START_TIME: False, } diff --git a/optichat/sub_agents/expert/agent.py b/optichat/sub_agents/expert/agent.py index 8eab6d4..aaa3e08 100644 --- a/optichat/sub_agents/expert/agent.py +++ b/optichat/sub_agents/expert/agent.py @@ -24,7 +24,7 @@ def create_expert_agent(prompt_version=1, tools_version=1): raise NotImplementedError(f"Tools version '{tools_version}' is not implemented.") expert_agent = Agent(name="expert_agent", - model=gpt_5, + model=gpt_5_nano, # remember to change it back under debugging tools=expert_agent_tools, description=("Optimization & operations research expert that " "interacts with , , "), diff --git a/optichat/sub_agents/root/agent.py b/optichat/sub_agents/root/agent.py index c4a4cf7..441de5f 100644 --- a/optichat/sub_agents/root/agent.py +++ b/optichat/sub_agents/root/agent.py @@ -4,7 +4,8 @@ from optichat.config.constants import OUTPUT_KEY_ROOT_AGENT from optichat.sub_agents.root.prompt import * from optichat.sub_agents.expert.agent import create_expert_agent -from optichat.tools.callback_tool import (initialize_session, initialize_query) +from optichat.tools.callback_tool import (initialize_session, initialize_query, + check_llm_response) def create_root_agent(workflow="default"): @@ -17,7 +18,8 @@ def create_root_agent(workflow="default"): instruction=ROOT_AGENT_PROMPT, output_key=OUTPUT_KEY_ROOT_AGENT, before_agent_callback=initialize_session, - before_model_callback=initialize_query) + before_model_callback=initialize_query, + after_model_callback=check_llm_response) return root_agent else: raise NotImplementedError(f"Workflow '{workflow}' is not implemented.") \ No newline at end of file diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py index eee9788..ad4f2b9 100644 --- a/optichat/tools/callback_tool.py +++ b/optichat/tools/callback_tool.py @@ -16,7 +16,7 @@ from optichat.config.constants import (IS_SESSION_INITIALIZED, PERSISTENT_STATES, TEMPORARY_STATES, CFG, IS_EXPERT_AGENT_USED, EXPERT_AGENT_START_TIME, MODELS_DICTIONARY, MODEL_VERSIONS, IS_MODELS_DICTIONARY_AVAILABLE, - IS_MODELS_CODE_AVAILABLE, IS_MODELS_PAPER_AVAILABLE) + IS_MODELS_CODE_AVAILABLE, IS_MODELS_PAPER_AVAILABLE, USER_QUERY) from optichat.tools.extract_tool import restore_model_object, extract_model_info from optichat.tools.rag_tool import init_paper_rag, init_code_rag @@ -60,6 +60,10 @@ def initialize_session(callback_context: CallbackContext): def initialize_query(callback_context: CallbackContext, llm_request: LlmRequest): # reset temporary states for every query callback_context.state.update(TEMPORARY_STATES) + if llm_request.contents and llm_request.contents[-1].role == 'user': + if llm_request.contents[-1].parts: + user_query = llm_request.contents[-1].parts[0].text + callback_context.state[USER_QUERY] = user_query return None @@ -159,11 +163,8 @@ def _expand_resources(local_resources: List[str], allowed_extensions: Optional[L def check_is_expert_agent_used(callback_context: CallbackContext): is_expert_agent_used = callback_context.state.get(IS_EXPERT_AGENT_USED, None) - start_time = callback_context.state.get(EXPERT_AGENT_START_TIME, None) if is_expert_agent_used is None: raise ValueError("check_is_expert_agent_used: IS_EXPERT_AGENT_USED is not set in the state.") - if start_time is None: - raise ValueError("check_is_expert_agent_used: EXPERT_AGENT_START_TIME is not set in the state.") if is_expert_agent_used: return types.Content( @@ -209,7 +210,7 @@ def check_llm_response(callback_context: CallbackContext, llm_response: LlmRespo return None -def check_tool_usage(tool: BaseTool, tool_context: ToolContext): +def check_tool_usage(tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext): agent_name = tool_context.agent_name tool_name = tool.name @@ -233,6 +234,7 @@ def check_tool_response(tool: BaseTool, tool_response: Dict): agent_name = tool_context.agent_name tool_name = tool.name + # AgentTool may return str instead of Dict as tool_response result = tool_response.get("result", "") max_tokens_key = f"{agent_name.upper()}_{tool_name.upper()}_MAX_TOKENS" if max_tokens_key in tool_context.state: From 6a7546faa50b623a9006468d3433fd130bebeeb2 Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Mon, 22 Sep 2025 15:24:37 -0400 Subject: [PATCH 08/30] fix: immutable_param has no value; constraint slack access needs idx; len(obj objects) validation --- optichat/tools/extract_tool.py | 33 ++++++++++++++++++++++++++------- 1 file changed, 26 insertions(+), 7 deletions(-) diff --git a/optichat/tools/extract_tool.py b/optichat/tools/extract_tool.py index 1419a42..f76a8d5 100644 --- a/optichat/tools/extract_tool.py +++ b/optichat/tools/extract_tool.py @@ -93,14 +93,19 @@ def extract_expressions_from_lp(lp_local_file_path: str): def extract_model_param(model, termination_condition): """ - Extract parameters from a Pyomo model. + Extract (mutable) parameters from a Pyomo model. Information includes name, component_type, value, TODO:is_RHS? """ param_info = {} for param in model.component_objects(pe.Param, active=True): - for idx in param: - param_info[pe.name(param[idx])] = {"component_type": "parameter", - "value": param[idx].value} + if param.mutable: + for idx in param: + try: + v = param[idx].value + except Exception as e: + raise ValueError(f"Error accessing value of parameter {pe.name(param)} with index {idx}: {e}") + param_info[pe.name(param[idx])] = {"component_type": "parameter", + "value": param[idx].value} return param_info @@ -112,6 +117,10 @@ def extract_model_var(model, termination_condition): var_info = {} for var in model.component_objects(pe.Var, active=True): for idx in var: + try: + v = var[idx].value + except Exception as e: + raise ValueError(f"Error accessing value of variable {pe.name(var)} with index {idx}: {e}") var_info[pe.name(var[idx])] = {"component_type": "variable", "solution": var[idx].value} return var_info @@ -126,8 +135,17 @@ def extract_model_constraint(model, termination_condition): constraint_info = {} for constraint in model.component_objects(pe.Constraint, active=True): for idx in constraint: + try: + v = constraint[idx].expr + except Exception as e: + raise ValueError(f"Error accessing expression of constraint {pe.name(constraint)} with index {idx}: {e}") + try: + lslack = constraint[idx].lslack() + uslack = constraint[idx].uslack() + except Exception as e: + raise ValueError(f"Error accessing slack of constraint {pe.name(constraint)} with index {idx}: {e}") if str(termination_condition) == 'optimal': - if abs(constraint.lslack()) < eps or abs(constraint.uslack()) < eps: + if abs(constraint[idx].lslack()) < eps or abs(constraint[idx].uslack()) < eps: is_binding = True else: is_binding = False @@ -145,10 +163,11 @@ def extract_model_objective(model, termination_condition): Information includes name, component_type, expression (with sense: min/max), value. """ objective_info = {} - if len(model.component_objects(pe.Objective, active=True)) > 1: + objectives = list(model.component_objects(pe.Objective, active=True)) + if len(objectives) > 1: raise ValueError("The model has multiple objectives, which is not supported.") else: - obj = model.component_objects(pe.Objective, active=True)[0] + obj = objectives[0] if obj.sense == pe.minimize: obj_sense = "MINIMIZE: " elif obj.sense == pe.maximize: From c1ccfebb3bd6970b7bddd2891cb7998833d3b500 Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Mon, 22 Sep 2025 15:31:47 -0400 Subject: [PATCH 09/30] fix: code_rag currently only takes one path --- optichat/tools/callback_tool.py | 3 ++- optichat/tools/rag_tool.py | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py index ad4f2b9..a9c42e9 100644 --- a/optichat/tools/callback_tool.py +++ b/optichat/tools/callback_tool.py @@ -91,7 +91,8 @@ def _init_models_code(cfg: dict): if "models_code" in cfg: paths = cfg["models_code"].get("local_resources", []) model_name = cfg.get("model_name", "default_model") - init_code_rag(paths, model_name) + # TODO: temporary solution to use GenericLoader in rag_tool.py, which only supports one path + init_code_rag(paths[0], model_name) is_models_code_available = True else: logger.debug("No 'models_code' in cfg") diff --git a/optichat/tools/rag_tool.py b/optichat/tools/rag_tool.py index 6bc7d3b..6b680bd 100644 --- a/optichat/tools/rag_tool.py +++ b/optichat/tools/rag_tool.py @@ -77,7 +77,7 @@ def init_chroma_collection(collection_name, docs, empty_existing): vector_store._client.delete_collection(name=collection_name) logger.debug(f"After deletion, existing collections are {[col.name for col in vector_store._client.list_collections()]}") vector_store = get_chroma_vs(collection_name, embeddings, persist_directory) - logger.debug(f"Building collection {vector_store.collection_name} by adding documents...") + logger.debug(f"Building collection {collection_name} by adding documents...") vector_store.add_documents(documents=docs) logger.debug(f"After adding documents, existing collections are {[col.name for col in vector_store._client.list_collections()]}") From ef9e0a114f1f27c1ae376ed674d10cee65f30917 Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Mon, 22 Sep 2025 20:09:04 -0400 Subject: [PATCH 10/30] fix: rag kwargs is search-type-specific; convert rag result to str; reduce logger output --- optichat/config/rag_cfg.py | 30 ++++++++++++++++++++++-------- optichat/tools/callback_tool.py | 7 +++++-- optichat/tools/rag_tool.py | 11 +++++++++-- 3 files changed, 36 insertions(+), 12 deletions(-) diff --git a/optichat/config/rag_cfg.py b/optichat/config/rag_cfg.py index e760627..2f126de 100644 --- a/optichat/config/rag_cfg.py +++ b/optichat/config/rag_cfg.py @@ -12,10 +12,17 @@ CODE_RAG_NUM_OF_FETCH_K = 10 # only for mmr CODE_RAG_LAMBDA_MULT = 0.5 # only for mmr CODE_RAG_SCORE_THRESHOLD = 0.8 # only for similarity_score_threshold -CODE_RAG_SEARCH_KWARGS = {"k": CODE_RAG_NUM_OF_RESULTS, - "fetch_k": CODE_RAG_NUM_OF_FETCH_K, - "lambda_mult": CODE_RAG_LAMBDA_MULT, - "score_threshold": CODE_RAG_SCORE_THRESHOLD} +if CODE_RAG_SEARCH_TYPE == "similarity": + CODE_RAG_SEARCH_KWARGS = {"k": CODE_RAG_NUM_OF_RESULTS} +elif CODE_RAG_SEARCH_TYPE == "mmr": + CODE_RAG_SEARCH_KWARGS = {"k": CODE_RAG_NUM_OF_RESULTS, + "fetch_k": CODE_RAG_NUM_OF_FETCH_K, + "lambda_mult": CODE_RAG_LAMBDA_MULT} +elif CODE_RAG_SEARCH_TYPE == "similarity_score_threshold": + CODE_RAG_SEARCH_KWARGS = {"k": CODE_RAG_NUM_OF_RESULTS, + "score_threshold": CODE_RAG_SCORE_THRESHOLD} +else: + raise ValueError(f"CODE_RAG_SEARCH_TYPE {CODE_RAG_SEARCH_TYPE} not supported.") PAPER_RAG_IS_SPLITTED = False @@ -26,10 +33,17 @@ PAPER_RAG_NUM_OF_FETCH_K = 10 # only for mmr PAPER_RAG_LAMBDA_MULT = 0.5 # only for mmr PAPER_RAG_SCORE_THRESHOLD = 0.8 # only for similarity_score_threshold -PAPER_RAG_SEARCH_KWARGS = {"k": PAPER_RAG_NUM_OF_RESULTS, - "fetch_k": PAPER_RAG_NUM_OF_FETCH_K, - "lambda_mult": PAPER_RAG_LAMBDA_MULT, - "score_threshold": PAPER_RAG_SCORE_THRESHOLD} +if PAPER_RAG_SEARCH_TYPE == "similarity": + PAPER_RAG_SEARCH_KWARGS = {"k": PAPER_RAG_NUM_OF_RESULTS} +elif PAPER_RAG_SEARCH_TYPE == "mmr": + PAPER_RAG_SEARCH_KWARGS = {"k": PAPER_RAG_NUM_OF_RESULTS, + "fetch_k": PAPER_RAG_NUM_OF_FETCH_K, + "lambda_mult": PAPER_RAG_LAMBDA_MULT} +elif PAPER_RAG_SEARCH_TYPE == "similarity_score_threshold": + PAPER_RAG_SEARCH_KWARGS = {"k": PAPER_RAG_NUM_OF_RESULTS, + "score_threshold": PAPER_RAG_SCORE_THRESHOLD} +else: + raise ValueError(f"PAPER_RAG_SEARCH_TYPE {PAPER_RAG_SEARCH_TYPE} not supported.") diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py index a9c42e9..6b2e76d 100644 --- a/optichat/tools/callback_tool.py +++ b/optichat/tools/callback_tool.py @@ -233,6 +233,7 @@ def check_tool_response(tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext, tool_response: Dict): + show_first_n_chars = 500 agent_name = tool_context.agent_name tool_name = tool.name # AgentTool may return str instead of Dict as tool_response @@ -250,7 +251,8 @@ def check_tool_response(tool: BaseTool, truncated_result = encoding.decode(truncated_tokens) truncated_result += ("... \n[system message]: **WARNING** " "Execution result was truncated due to token limit.") - logger.warning(f"'{tool_name.upper()}' execution (truncated) result: {truncated_result}") + logger.warning((f"'{tool_name.upper()}' execution (truncated) result: {truncated_result[:show_first_n_chars]}" + "\n... (showing only the first {show_first_n_chars} characters)")) # return a truncated tool_response dictionary truncated_tool_response = deepcopy(tool_response) truncated_tool_response["result"] = truncated_result @@ -259,6 +261,7 @@ def check_tool_response(tool: BaseTool, raise RuntimeError(f"Token counting failed: {e}.") else: logger.debug(f"max tokens key '{max_tokens_key}' not found in the state. Skipping tool response check.") - logger.info(f"'{tool_name.upper()}' execution result: {result}") + logger.info(f"'{tool_name.upper()}' execution result: {result[:show_first_n_chars]}" + f"\n... (showing only the first {show_first_n_chars} characters)") return None # Return None to indicate no modification to tool_response diff --git a/optichat/tools/rag_tool.py b/optichat/tools/rag_tool.py index 6b680bd..15eaaab 100644 --- a/optichat/tools/rag_tool.py +++ b/optichat/tools/rag_tool.py @@ -90,6 +90,13 @@ def get_chroma_vs(collection_name, embeddings, persist_directory): return vector_store +def convert_docs_to_str(result_docs): + result_str = f"Retrieved {len(result_docs)} documents: " + for i, doc in enumerate(result_docs): + result_str += f"\nSource {i+1}: {doc.metadata.get('source', 'unknown source')} \nContent {i+1}: {doc.page_content}\n" + return result_str + + def code_rag(request: str, tool_context: ToolContext) -> str: """ code_rag retrieves code blocks from by @@ -110,7 +117,7 @@ def code_rag(request: str, tool_context: ToolContext) -> str: persist_directory=PERSIST_DIRECTORY) retriever = vector_store.as_retriever(search_type=CODE_RAG_SEARCH_TYPE, search_kwargs=CODE_RAG_SEARCH_KWARGS) - result = retriever.invoke(request) + result = convert_docs_to_str(retriever.invoke(request)) return {"result": result} else: return {"result": "No 'models_code' in cfg, cannot use code_rag."} @@ -136,7 +143,7 @@ def paper_rag(request: str, tool_context: ToolContext) -> str: persist_directory=PERSIST_DIRECTORY) retriever = vector_store.as_retriever(search_type=PAPER_RAG_SEARCH_TYPE, search_kwargs=PAPER_RAG_SEARCH_KWARGS) - result = retriever.invoke(request) + result = convert_docs_to_str(retriever.invoke(request)) return {"result": result} else: return {"result": "No 'models_paper' in cfg, cannot use paper_rag."} \ No newline at end of file From 35cece8160bcf1cdb3357c4b7c5ac093db65edfb Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Mon, 22 Sep 2025 22:56:42 -0400 Subject: [PATCH 11/30] add: sc fn docs to prompts; llm prompt to logger --- optichat/sub_agents/expert/agent.py | 9 ++++----- optichat/sub_agents/expert/prompt.py | 19 +++++++++++++++++-- optichat/tools/callback_tool.py | 19 +++++++++++++++++++ 3 files changed, 40 insertions(+), 7 deletions(-) diff --git a/optichat/sub_agents/expert/agent.py b/optichat/sub_agents/expert/agent.py index aaa3e08..599c759 100644 --- a/optichat/sub_agents/expert/agent.py +++ b/optichat/sub_agents/expert/agent.py @@ -3,18 +3,16 @@ # from google.adk.events import Event from optichat.llm import * from optichat.config.constants import * -from optichat.sub_agents.expert.prompt import EXPERT_AGENT_PROMPTS +from optichat.sub_agents.expert.prompt import get_expert_agent_prompt from optichat.tools.search_tool import get_model_components from optichat.tools.python_repl import python_repl_func from optichat.tools.rag_tool import code_rag, paper_rag from optichat.tools.callback_tool import (check_is_expert_agent_used, check_expert_agent_runtime, - check_llm_response, check_tool_usage, check_tool_response) + check_llm_request, check_llm_response, check_tool_usage, check_tool_response) def create_expert_agent(prompt_version=1, tools_version=1): - expert_agent_prompt = EXPERT_AGENT_PROMPTS.get(prompt_version, None) - if expert_agent_prompt is None: - raise NotImplementedError(f"Prompt version '{prompt_version}' is not implemented.") + expert_agent_prompt = get_expert_agent_prompt(prompt_version) if tools_version == 1: expert_agent_tools = [get_model_components, python_repl_func, @@ -32,6 +30,7 @@ def create_expert_agent(prompt_version=1, tools_version=1): output_key=OUTPUT_KEY_EXPERT_AGENT, before_agent_callback=check_is_expert_agent_used, after_agent_callback=check_expert_agent_runtime, + before_model_callback=check_llm_request, after_model_callback=check_llm_response, before_tool_callback=check_tool_usage, after_tool_callback=check_tool_response diff --git a/optichat/sub_agents/expert/prompt.py b/optichat/sub_agents/expert/prompt.py index 80ed7e6..42fee30 100644 --- a/optichat/sub_agents/expert/prompt.py +++ b/optichat/sub_agents/expert/prompt.py @@ -1,3 +1,6 @@ +from optichat.tools.extract_tool import auto_extract_function_docs + + EXPERT_AGENT_PROMPT_NO_SC = """ USER QUERY {USER_QUERY} @@ -162,5 +165,17 @@ """ -EXPERT_AGENT_PROMPTS = {1: EXPERT_AGENT_PROMPT_NO_SC, - 2: EXPERT_AGENT_PROMPT} \ No newline at end of file +def get_expert_agent_prompt(prompt_version=1): + EXPERT_AGENT_PROMPTS = {1: EXPERT_AGENT_PROMPT_NO_SC, + 2: EXPERT_AGENT_PROMPT} + if prompt_version in EXPERT_AGENT_PROMPTS: + prompt = EXPERT_AGENT_PROMPTS[prompt_version] + else: + raise NotImplementedError(f"Prompt version '{prompt_version}' is not implemented.") + + shortcut_functions_docs = auto_extract_function_docs("optichat.tools.shortcut_functions") + + if prompt_version in [1, 2]: + prompt = prompt.replace("__SHORTCUT_FUNCTIONS_PLACEHOLDER__", shortcut_functions_docs) + + return prompt \ No newline at end of file diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py index 6b2e76d..521d8dd 100644 --- a/optichat/tools/callback_tool.py +++ b/optichat/tools/callback_tool.py @@ -58,12 +58,15 @@ def initialize_session(callback_context: CallbackContext): def initialize_query(callback_context: CallbackContext, llm_request: LlmRequest): + is_debug = True # reset temporary states for every query callback_context.state.update(TEMPORARY_STATES) if llm_request.contents and llm_request.contents[-1].role == 'user': if llm_request.contents[-1].parts: user_query = llm_request.contents[-1].parts[0].text callback_context.state[USER_QUERY] = user_query + if is_debug: + check_llm_request(callback_context, llm_request) return None @@ -191,6 +194,22 @@ def check_expert_agent_runtime(callback_context: CallbackContext): return None +def check_llm_request(callback_context: CallbackContext, llm_request: LlmRequest): + agent_name = callback_context.agent_name + original_instruction = llm_request.config.system_instruction or types.Content(role="system", parts=[]) + # Ensure system_instruction is Content and parts list exists + if not isinstance(original_instruction, types.Content): + # Handle case where it might be a string (though config expects Content) + original_instruction = types.Content(role="system", parts=[types.Part(text=str(original_instruction))]) + if not original_instruction.parts: + original_instruction.parts.append(types.Part(text="")) # Add an empty part if none exist + + original_text = original_instruction.parts[0].text or "" + logger.info((f"[Callback] Inspecting LLM request from '{agent_name}': " + f"{original_text}")) + return None + + def check_llm_response(callback_context: CallbackContext, llm_response: LlmResponse): agent_name = callback_context.agent_name if llm_response.content and llm_response.content.parts: From 53ee37118423dcdf5ff66af28e2469050bfe49dd Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Mon, 22 Sep 2025 23:32:39 -0400 Subject: [PATCH 12/30] fix: local_path_to_object not stored when init; merge init_query to init_session --- optichat/config/constants.py | 2 +- optichat/sub_agents/expert/agent.py | 2 +- optichat/sub_agents/root/agent.py | 4 ++-- optichat/tools/callback_tool.py | 18 +++++------------- 4 files changed, 9 insertions(+), 17 deletions(-) diff --git a/optichat/config/constants.py b/optichat/config/constants.py index fc9e0d1..25827d1 100644 --- a/optichat/config/constants.py +++ b/optichat/config/constants.py @@ -54,7 +54,7 @@ TEMPORARY_STATES = { USER_QUERY: "", IS_EXPERT_AGENT_USED: False, - EXPERT_AGENT_PYTHON_REPL_FUNC_USES: 5, + EXPERT_AGENT_PYTHON_REPL_FUNC_USES: 3, EXPERT_AGENT_CODE_RAG_USES: 1, EXPERT_AGENT_PAPER_RAG_USES: 1, EXPERT_AGENT_START_TIME: False, diff --git a/optichat/sub_agents/expert/agent.py b/optichat/sub_agents/expert/agent.py index 599c759..4ab42cf 100644 --- a/optichat/sub_agents/expert/agent.py +++ b/optichat/sub_agents/expert/agent.py @@ -22,7 +22,7 @@ def create_expert_agent(prompt_version=1, tools_version=1): raise NotImplementedError(f"Tools version '{tools_version}' is not implemented.") expert_agent = Agent(name="expert_agent", - model=gpt_5_nano, # remember to change it back under debugging + model=gpt_5, # remember to change it back under debugging tools=expert_agent_tools, description=("Optimization & operations research expert that " "interacts with , , "), diff --git a/optichat/sub_agents/root/agent.py b/optichat/sub_agents/root/agent.py index 441de5f..e633c19 100644 --- a/optichat/sub_agents/root/agent.py +++ b/optichat/sub_agents/root/agent.py @@ -4,7 +4,7 @@ from optichat.config.constants import OUTPUT_KEY_ROOT_AGENT from optichat.sub_agents.root.prompt import * from optichat.sub_agents.expert.agent import create_expert_agent -from optichat.tools.callback_tool import (initialize_session, initialize_query, +from optichat.tools.callback_tool import (initialize_session, check_llm_request, check_llm_response) @@ -18,7 +18,7 @@ def create_root_agent(workflow="default"): instruction=ROOT_AGENT_PROMPT, output_key=OUTPUT_KEY_ROOT_AGENT, before_agent_callback=initialize_session, - before_model_callback=initialize_query, + before_model_callback=check_llm_request, after_model_callback=check_llm_response) return root_agent else: diff --git a/optichat/tools/callback_tool.py b/optichat/tools/callback_tool.py index 521d8dd..9e02fe4 100644 --- a/optichat/tools/callback_tool.py +++ b/optichat/tools/callback_tool.py @@ -17,7 +17,7 @@ CFG, IS_EXPERT_AGENT_USED, EXPERT_AGENT_START_TIME, MODELS_DICTIONARY, MODEL_VERSIONS, IS_MODELS_DICTIONARY_AVAILABLE, IS_MODELS_CODE_AVAILABLE, IS_MODELS_PAPER_AVAILABLE, USER_QUERY) -from optichat.tools.extract_tool import restore_model_object, extract_model_info +from optichat.tools.extract_tool import restore_model_object, save_model_object, extract_model_info from optichat.tools.rag_tool import init_paper_rag, init_code_rag @@ -25,8 +25,8 @@ def initialize_session(callback_context: CallbackContext): if IS_SESSION_INITIALIZED not in callback_context.state: callback_context.state.update(PERSISTENT_STATES) # which also set IS_SESSION_INITIALIZED as False callback_context.state.update(TEMPORARY_STATES) - user_content = callback_context.user_content + user_query = callback_context.user_content.parts[0].text parts_wo_json = [] for part in user_content.parts: if getattr(part, "inline_data", None) is not None: @@ -54,19 +54,9 @@ def initialize_session(callback_context: CallbackContext): parts_wo_json.append(part) # replace user_content with parts without json part (if a part has json, it cannot be processed) callback_context.user_content.parts = parts_wo_json - return None - - -def initialize_query(callback_context: CallbackContext, llm_request: LlmRequest): - is_debug = True # reset temporary states for every query callback_context.state.update(TEMPORARY_STATES) - if llm_request.contents and llm_request.contents[-1].role == 'user': - if llm_request.contents[-1].parts: - user_query = llm_request.contents[-1].parts[0].text - callback_context.state[USER_QUERY] = user_query - if is_debug: - check_llm_request(callback_context, llm_request) + callback_context.state[USER_QUERY] = user_query return None @@ -85,6 +75,8 @@ def _init_models(cfg: dict): # but we only stored the model object. # here assume we solve the model again no matter whether .pkl object is solved before. info = extract_model_info(model, termination_condition=termination_condition) + local_path_to_object = save_model_object(model, version) + info.update({"local_path_to_object": local_path_to_object,}) models_dictionary.update({version: info}) model_versions.append(version) return models_dictionary, model_versions From f0a3bfad4eb91b3e0f9d764a2bbaded3275afff9 Mon Sep 17 00:00:00 2001 From: GeraltSHEN <100735135+GeraltSHEN@users.noreply.github.com> Date: Wed, 15 Oct 2025 10:43:15 -0400 Subject: [PATCH 13/30] update gitignore --- .gitignore | 7 +- cfg_debug_use.json | 12 + .../data_level0.bin | 4787 +++ .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 chroma_langchain_db/chroma.sqlite3 | Bin 0 -> 937984 bytes .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | 25114 ++++++++++++++++ .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | 18721 ++++++++++++ .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 .../data_level0.bin | Bin 0 -> 1242800 bytes .../header.bin | Bin 0 -> 100 bytes .../length.bin | Bin 0 -> 400 bytes .../link_lists.bin | 0 my_model.pkl | Bin 0 -> 28082 bytes quick_test.ipynb | 535 + tmp/model_objects/my_model.pkl | Bin 0 -> 30627 bytes tmp/model_objects/xyz.pkl | Bin 0 -> 30644 bytes 63 files changed, 49175 insertions(+), 1 deletion(-) create mode 100644 cfg_debug_use.json create mode 100644 chroma_langchain_db/070dfd3b-6abb-44da-a44a-105b984297f9/data_level0.bin create mode 100644 chroma_langchain_db/070dfd3b-6abb-44da-a44a-105b984297f9/header.bin create mode 100644 chroma_langchain_db/070dfd3b-6abb-44da-a44a-105b984297f9/length.bin create mode 100644 chroma_langchain_db/070dfd3b-6abb-44da-a44a-105b984297f9/link_lists.bin create mode 100644 chroma_langchain_db/26255034-4baf-4bc4-bda0-41b881eaca40/data_level0.bin create mode 100644 chroma_langchain_db/26255034-4baf-4bc4-bda0-41b881eaca40/header.bin create mode 100644 chroma_langchain_db/26255034-4baf-4bc4-bda0-41b881eaca40/length.bin create mode 100644 chroma_langchain_db/26255034-4baf-4bc4-bda0-41b881eaca40/link_lists.bin create mode 100644 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chroma_langchain_db/f8f34fb5-0674-4a07-8695-f6c2ab55eb61/data_level0.bin create mode 100644 chroma_langchain_db/f8f34fb5-0674-4a07-8695-f6c2ab55eb61/header.bin create mode 100644 chroma_langchain_db/f8f34fb5-0674-4a07-8695-f6c2ab55eb61/length.bin create mode 100644 chroma_langchain_db/f8f34fb5-0674-4a07-8695-f6c2ab55eb61/link_lists.bin create mode 100644 chroma_langchain_db/f948c7ec-bb01-43bc-90e1-a6e59b682dff/data_level0.bin create mode 100644 chroma_langchain_db/f948c7ec-bb01-43bc-90e1-a6e59b682dff/header.bin create mode 100644 chroma_langchain_db/f948c7ec-bb01-43bc-90e1-a6e59b682dff/length.bin create mode 100644 chroma_langchain_db/f948c7ec-bb01-43bc-90e1-a6e59b682dff/link_lists.bin create mode 100644 chroma_langchain_db/fb38e9ac-2c72-4f29-8abc-f0093806e252/data_level0.bin create mode 100644 chroma_langchain_db/fb38e9ac-2c72-4f29-8abc-f0093806e252/header.bin create mode 100644 chroma_langchain_db/fb38e9ac-2c72-4f29-8abc-f0093806e252/length.bin create mode 100644 chroma_langchain_db/fb38e9ac-2c72-4f29-8abc-f0093806e252/link_lists.bin create mode 100644 chroma_langchain_db/ff36c0ba-765e-4de5-aeb2-e5946756d92e/data_level0.bin create mode 100644 chroma_langchain_db/ff36c0ba-765e-4de5-aeb2-e5946756d92e/header.bin create mode 100644 chroma_langchain_db/ff36c0ba-765e-4de5-aeb2-e5946756d92e/length.bin create mode 100644 chroma_langchain_db/ff36c0ba-765e-4de5-aeb2-e5946756d92e/link_lists.bin create mode 100644 my_model.pkl create mode 100644 quick_test.ipynb create mode 100644 tmp/model_objects/my_model.pkl create mode 100644 tmp/model_objects/xyz.pkl diff --git a/.gitignore b/.gitignore index 179ec43..65f6763 100644 --- a/.gitignore +++ b/.gitignore @@ -59,4 +59,9 @@ create_code_testset.py create_tool_testset.py grading.py run_exp.py -show_results.ipynb \ No newline at end of file +show_results.ipynb +quick_test.ipynb +tmp/ + +# Ignore kb +chroma_langchain_db/ \ No newline at end of file diff --git a/cfg_debug_use.json b/cfg_debug_use.json new file mode 100644 index 0000000..3312d62 --- /dev/null +++ b/cfg_debug_use.json @@ -0,0 +1,12 @@ +{ "model_name": "debug", + "models": { + "local_resources": [ + "my_model.pkl" + ] + }, + "models_code": { + "local_resources": [ + "Feas/aircraft.py" + ] + } +} \ No newline at end of file diff --git a/chroma_langchain_db/070dfd3b-6abb-44da-a44a-105b984297f9/data_level0.bin b/chroma_langchain_db/070dfd3b-6abb-44da-a44a-105b984297f9/data_level0.bin new file mode 100644 index 0000000..ce33a50 --- /dev/null +++ b/chroma_langchain_db/070dfd3b-6abb-44da-a44a-105b984297f9/data_level0.bin @@ -0,0 +1,4787 @@ +()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOP +  !"#$%&'d + +d + +pd + d  d d  d d +d + d d d d @d dddd + d +P d d ddddPdd +d +d d pd d d `d`dc@c c c`c cccPc@c +c + c cc c +c +@c c c Pc +c + +c + `c  cPc0ccc c`ccc`c@cc 0c c c c c @cccpcccccccc`c0cccc + c +cccpccpc +c + +`c +`c@c0c +c +cccpcPc@c0ccc c c c c c +c +ccccpccccpc +@c +c +c + +c + +c + 0c cc +Pc + +@c + c +c + +c + +pc +cбc c pc `c@c c c c 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"\u0120spring": 11037, "subclass": 11038, "issues": 11039, "\u0120fails": 11040, "\u0120newspaper": 11041, "nut": 11042, "\u0120Mock": 11043, "\u00d0\u00be\u00d0\u00b4": 11044, "catalog": 11045, "\u0120fourth": 11046, "\u0120approximately": 11047, "\\\":\\\"": 11048, ".<": 11049, "\u00f0\u0132": 11050, "\u0120sr": 11051, "\u0120SP": 11052, "\u0120plays": 11053, "\u0120park": 11054, "\u0120sugar": 11055, "\u0120silver": 11056, "Suppose": 11057, "bank": 11058, "nam": 11059, "\u0120nicht": 11060, "without": 11061, "\u0120percentage": 11062, "dh": 11063, "absolute": 11064, "(\"[": 11065, "\u0120timedelta": 11066, "\u0120factory": 11067, "\u00e5\u0143\u0132": 11068, "\u0120girls": 11069, "\u0125\u00bd": 11070, "\u0120warn": 11071, "\u0120Tag": 11072, "moid": 11073, "\u0120attract": 11074, "identity": 11075, "\u0120virt": 11076, "\u0120pregn": 11077, "\u0120advance": 11078, "\u0120proteins": 11079, "\u0120neither": 11080, "savefig": 11081, "\u0120songs": 11082, "\u0120encoded": 11083, "vid": 11084, "\u0120Task": 11085, "strings": 11086, "\u0120thousands": 11087, "\u0120derivative": 11088, "VENT": 11089, "eh": 11090, "\u0120bare": 11091, "\u0120rent": 11092, "Standard": 11093, "\u0120Ref": 11094, "\u0120Its": 11095, "calendar": 11096, "general": 11097, "tid": 11098, "erior": 11099, "\u0120blow": 11100, "\u0120dy": 11101, "\u0120drag": 11102, "permissions": 11103, "\u0120Martin": 11104, "\u0120purchase": 11105, "\u0120Description": 11106, "\u0120Media": 11107, "\u0120Committee": 11108, "))]": 11109, "\u0120Button": 11110, "\u0120sock": 11111, "notify": 11112, "visit": 11113, "\u0120nuclear": 11114, "recip": 11115, "\u0120dropped": 11116, "Est": 11117, "uits": 11118, "\u0120gal": 11119, "\u0120agency": 11120, "\u0120fh": 11121, "\u0120''.": 11122, "\u0120formula": 11123, "\u0120equation": 11124, "\u0120Corps": 11125, "\u0120slowly": 11126, "\u0120department": 11127, "detect": 11128, "\u0120proceed": 11129, "\u0120plants": 11130, "extensions": 11131, "registry": 11132, ".**": 11133, "\u0120confidence": 11134, "WIN": 11135, "xef": 11136, "\u0120processed": 11137, "102": 11138, "\u00e6\u012a\u00b7": 11139, "\u0120procedure": 11140, "\"/>": 11141, "\u0120thr": 11142, "lopen": 11143, "\u0120strateg": 11144, "\u0120spend": 11145, "\u0120curve": 11146, "rolling": 11147, "\u0120horse": 11148, "\u0120watching": 11149, "Accept": 11150, "ih": 11151, "strap": 11152, "\u0120driving": 11153, "mkdir": 11154, "\u0120sqrt": 11155, "%,": 11156, "emit": 11157, "\u0120Central": 11158, "FS": 11159, "tor": 11160, "\u00ec\u0140": 11161, "validators": 11162, "\u0120confirmed": 11163, "hop": 11164, "\u0120buildings": 11165, "Identifier": 11166, "\u0120conversation": 11167, "Section": 11168, "uming": 11169, "\u0120colour": 11170, "\u0120sqlite": 11171, "MR": 11172, "street": 11173, "\u0120purch": 11174, "\u0120sections": 11175, "outube": 11176, "rey": 11177, "\u0120thank": 11178, "uesday": 11179, "Folder": 11180, "Good": 11181, "\u0120ctypes": 11182, "outer": 11183, "%.": 11184, "\u0120txt": 11185, "\u0120dip": 11186, "charge": 11187, "---------": 11188, "\u0120accounts": 11189, "\u0120drawn": 11190, "\u0120symp": 11191, "prediction": 11192, "\u0120cpp": 11193, "asarray": 11194, "\u0120Jo": 11195, "\u0120prem": 11196, "accounts": 11197, "Rule": 11198, "squ": 11199, "tit": 11200, "\u0120asking": 11201, ")^": 11202, "350": 11203, "stud": 11204, "\u0120sand": 11205, "\u0120Search": 11206, "noise": 11207, "\u0120equipment": 11208, "cdot": 11209, "\u0120Down": 11210, "\u012054": 11211, "monitor": 11212, "\u0120carbon": 11213, "\u0120infect": 11214, "\u0120favorite": 11215, "\u00e6\u0123": 11216, "\u0120tor": 11217, "\u0120sounds": 11218, "ems": 11219, "\u0120continuous": 11220, "Begin": 11221, "Bad": 11222, "hosts": 11223, "analy": 11224, "\u0120Island": 11225, "maps": 11226, "langle": 11227, "\u0120cnt": 11228, "\u0120ws": 11229, "\u0120Information": 11230, "a\u00c3\u00a7\u00c3\u00a3o": 11231, "hours": 11232, "lc": 11233, "\u0120Mur": 11234, "izard": 11235, "\u0120atoms": 11236, "\u0120Ell": 11237, "\u0120chapter": 11238, "\u0120anyway": 11239, "cod": 11240, "\u0120draft": 11241, "\u0120sem": 11242, "gery": 11243, "digit": 11244, "sex": 11245, "essel": 11246, "\u0120Haw": 11247, "\u0120particles": 11248, "\u0120senior": 11249, "\u0120pag": 11250, "\u0120increases": 11251, "cycle": 11252, "Abstract": 11253, "................": 11254, "pw": 11255, "reward": 11256, "\u0120ha": 11257, "ika": 11258, "\u00d0\u00b8\u00d1\u0124": 11259, "-------": 11260, "\u0120arbit": 11261, "\u0120och": 11262, "\u0120discussion": 11263, "\u0120stores": 11264, "(\"\")": 11265, "makedirs": 11266, "RGB": 11267, "\u0120som": 11268, "Labels": 11269, "\u010a\u010a\u010a\u010a\u010a\u010a\u010a\u010a": 11270, "\u0120explan": 11271, "\u0120improved": 11272, "\u0120candidates": 11273, "\u00e6\u00af": 11274, "\u0120Pop": 11275, "machine": 11276, "\u012053": 11277, "These": 11278, "\u0120bott": 11279, "\u0120Power": 11280, "\u0120credentials": 11281, "\u0120affected": 11282, "\u0120ic": 11283, "external": 11284, "\u0120timezone": 11285, "\u0120cheese": 11286, "\u0120customers": 11287, ")+\"": 11288, "\u0120submit": 11289, "\u0120provider": 11290, "\u0120Organ": 11291, "\u00c3\u00b6r": 11292, "tolist": 11293, "QED": 11294, "\u0120administr": 11295, "\u0120Flask": 11296, "\u0120Dee": 11297, "Metadata": 11298, "\u0120fd": 11299, "IDD": 11300, "\u0120crime": 11301, "xce": 11302, ":],": 11303, "\u0120impossible": 11304, "\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd": 11305, "Li": 11306, "\u0120Rights": 11307, "\u0120memb": 11308, "\u0120priority": 11309, "Render": 11310, "uke": 11311, "\u00e8\u0129": 11312, "expect": 11313, "\u0120nearest": 11314, "\u0120creates": 11315, "negative": 11316, "\u0120vertical": 11317, "#:": 11318, "/')": 11319, "\u0120eg": 11320, "\u0120COP": 11321, "Login": 11322, "WH": 11323, "\u0120sticky": 11324, "\u0120pil": 11325, "iger": 11326, "010": 11327, "logits": 11328, "bunt": 11329, "who": 11330, "\u0120Construct": 11331, "\u0120Control": 11332, "112": 11333, "\u0120sight": 11334, "\u0120adapt": 11335, "104": 11336, "xfa": 11337, "\u0120nucle": 11338, "ipt": 11339, "\">\",": 11538, "\u0120returning": 11539, "rained": 11540, "Anim": 11541, "\u0120capture": 11542, "mysql": 11543, "aration": 11544, "arity": 11545, "\u0120pel": 11546, "\u0120conference": 11547, "\u0120Mall": 11548, "\u01201980": 11549, "\u0120skills": 11550, "threads": 11551, "\u0120\",\"": 11552, "rible": 11553, "\u0120colle": 11554, "\u0120fraction": 11555, "oppi": 11556, "aggregate": 11557, "egr": 11558, "verb": 11559, "))))": 11560, "ellant": 11561, "\u0120secure": 11562, "\u0120circumstances": 11563, "ctxt": 11564, "\u0120IMP": 11565, "Cons": 11566, "solution": 11567, "\u0120loading": 11568, "Copy": 11569, "Len": 11570, "\u0120planning": 11571, "\u0120serving": 11572, "\u0120specifically": 11573, "\u00d0\u00b5\u00d0\u00bc": 11574, "\u0120electron": 11575, "variance": 11576, "Non": 11577, "\u0120nut": 11578, "\u0120Sunday": 11579, "\u00e6\u013e\u0122": 11580, "Filename": 11581, "pite": 11582, "xed": 11583, "\u0120Music": 11584, "\u0120chop": 11585, "\u0120wealth": 11586, "boolean": 11587, "\u0120INTO": 11588, "\u0120association": 11589, "General": 11590, "\u0120illustr": 11591, "\u0120cognitive": 11592, "Make": 11593, "PW": 11594, "|_": 11595, "\u0120ox": 11596, "amos": 11597, "REE": 11598, "\u0120usual": 11599, "flat": 11600, "Team": 11601, "\u0120cc": 11602, "clone": 11603, "repeat": 11604, "uries": 11605, "__.__": 11606, "ogra": 11607, "\u0120importance": 11608, "tan": 11609, "\u0120bag": 11610, "\u0120Cons": 11611, "linux": 11612, "xfe": 11613, "\u0120ske": 11614, "there": 11615, "\u0120:]": 11616, "\u0120converted": 11617, "dam": 11618, "\u00e7\u0142\u0123": 11619, "\u012046": 11620, "pioppi": 11621, "\u00e5\u012b\u012f": 11622, "_'": 11623, "\u0120(?": 11624, "\u0120becoming": 11625, "\u00d8\u00a7": 11626, "\u0120cu": 11627, "attrib": 11628, "don": 11629, "xac": 11630, "()).": 11631, "\u0120Hal": 11632, "IDs": 11633, "\u0120knock": 11634, "\u0120smile": 11635, "\u0120writes": 11636, "Are": 11637, "Bot": 11638, "Free": 11639, "fh": 11640, "imize": 11641, "\u0120Nov": 11642, "\u0120arrange": 11643, "LETE": 11644, "\u0120famous": 11645, "\u0120walls": 11646, "rection": 11647, "\u0120lr": 11648, "\u0120Cy": 11649, "103": 11650, "BY": 11651, "lif": 11652, "\u0120forth": 11653, "tector": 11654, "packet": 11655, "\u0120correspond": 11656, "npy": 11657, "\u0120Tensor": 11658, "\u0120AT": 11659, "\u0120accident": 11660, "\u0120statements": 11661, "processor": 11662, "\u0120breast": 11663, "places": 11664, "resol": 11665, "\")),": 11666, "\u012072": 11667, "\u00e3\u0123\u00a7": 11668, "\u0120frames": 11669, "\u0120indicating": 11670, "\u0120attacks": 11671, "WIDTH": 11672, "linalg": 11673, "ouds": 11674, "\u0120dates": 11675, "\u0120ly": 11676, "oggle": 11677, "\u0120turns": 11678, "\u0120threads": 11679, "\u00e9\u0129\u0131": 11680, "\u0120aux": 11681, "stood": 11682, "\u0120'':": 11683, "\u0120gap": 11684, "istical": 11685, "\u0120prompt": 11686, "xbd": 11687, "\u0120\u00e2\u012a\u0134": 11688, "\u0120marriage": 11689, "through": 11690, "('./": 11691, "estival": 11692, "\u0120telling": 11693, "\u00e4\u00bf\u00a1": 11694, "\u0120LIMIT": 11695, "Init": 11696, "\u0120sauce": 11697, "LANG": 11698, "\u0120coe": 11699, "until": 11700, "\u00d1\u0122\u00d0\u00b0\u00d0": 11701, "\u0120originally": 11702, "Help": 11703, "\u0120Trump": 11704, "\u0120concerned": 11705, "\u0120latter": 11706, "experiment": 11707, "\u0120contribut": 11708, "xcb": 11709, "\u010a\u0120\u0120\u010a\u0120": 11710, "EO": 11711, "Speed": 11712, "onic": 11713, "\u0120FI": 11714, "\u0120Old": 11715, "Driver": 11716, "\u0120functional": 11717, "URITY": 11718, "\u0120drawing": 11719, "\u0120normalize": 11720, "\u00ec\u013f\u00b4": 11721, "Http": 11722, "\u00e5\u00a7": 11723, "\u0120cols": 11724, "Args": 11725, "SF": 11726, "bbox": 11727, "probs": 11728, "mpler": 11729, "rootd": 11730, "xcf": 11731, "Entity": 11732, "PIPE": 11733, "Memory": 11734, "ipping": 11735, "\u0120Chicago": 11736, "existing": 11737, "\u0120gender": 11738, "\u0120claimed": 11739, "gradient": 11740, "SETTINGS": 11741, ",%": 11742, "elmer": 11743, "irty": 11744, "\u0120Palest": 11745, "\u00e2\u0136\u0122": 11746, "BP": 11747, "xrootd": 11748, "\u0120Graph": 11749, "acts": 11750, "haust": 11751, "onald": 11752, "\u0120123": 11753, "\u0120infection": 11754, "\u0120Change": 11755, "Allow": 11756, "\u0120'/'": 11757, "\u0120brand": 11758, "MessageBox": 11759, "may": 11760, "\u00e6\u013d": 11761, "\u00e9\u013d": 11762, "\u0120Life": 11763, "central": 11764, "\u0120fmt": 11765, "\u0120ble": 11766, "published": 11767, "onymous": 11768, "Living": 11769, "uh": 11770, "\u0120Jew": 11771, "cipl": 11772, "\u0120Club": 11773, "Phone": 11774, "patcher": 11775, "concatenate": 11776, ")==": 11777, "Bind": 11778, "^[@": 11779, "qs": 11780, "\u0120milk": 11781, "\u0120shel": 11782, "\u0120addresses": 11783, "\u0120flavor": 11784, "]\\]": 11785, "PSet": 11786, "\u0120acknow": 11787, "\u0120manual": 11788, "]{": 11789, "\u00d1\u0130": 11790, "\u0120pit": 11791, "chr": 11792, "\u0120Current": 11793, "\u0120fruit": 11794, "\u0120networks": 11795, "\u0120photograph": 11796, "\u0120lic": 11797, "\u0120Federal": 11798, "acs": 11799, ":#": 11800, "\u0120harm": 11801, "\u0120Edit": 11802, "\")[": 11803, "relative": 11804, "xfd": 11805, "\u0120itertools": 11806, "\u0120Churchill": 11807, "\u00e2\u00ac\u013d": 11808, "\u0120SECURITY": 11809, "More": 11810, "rance": 11811, "xdb": 11812, "\u0120scalar": 11813, "2006": 11814, "\u0120solutions": 11815, "\u0120guys": 11816, "\u0120iteration": 11817, "\u01201996": 11818, "Unknown": 11819, "\u0120grew": 11820, "\u0120Figure": 11821, "\u00e6\u00a8": 11822, "\u0120Random": 11823, "\u0120shadow": 11824, "\u0120interaction": 11825, "CLUD": 11826, "semble": 11827, "\u0120maintain": 11828, "ArgumentParser": 11829, "\u0120Document": 11830, "fume": 11831, "{{": 11832, "onest": 11833, "\u0120Offic": 11834, "\u0120unable": 11835, "CN": 11836, "\u0120gray": 11837, "\u0120framework": 11838, "CLUDING": 11839, "candid": 11840, "\u0120IF": 11841, "pairs": 11842, "\u0120bridge": 11843, "\u0120reprodu": 11844, "\u0120Dar": 11845, "\u0120suite": 11846, "\u0120guar": 11847, "\u0120drugs": 11848, "eler": 11849, "\u0120rating": 11850, "plain": 11851, "STER": 11852, "('/')": 11853, "embedding": 11854, "BM": 11855, "SN": 11856, "hw": 11857, "\u0120git": 11858, "\u0120ju": 11859, ".]": 11860, "\u0120batt": 11861, "three": 11862, "\u0120yellow": 11863, "nergy": 11864, "\u00e8\u00bf\u0136": 11865, "\u0120pepper": 11866, "kins": 11867, "\u0120Ill": 11868, "\u0120recipe": 11869, "urrence": 11870, "\u0120ingred": 11871, "Cmd": 11872, "\u0120sust": 11873, "\u00e1\u0122\u00ba": 11874, "Cast": 11875, "Oct": 11876, "\u0120hell": 11877, "\"%(": 11878, "Pt": 11879, "\u0120cum": 11880, "\u0120arrays": 11881, "\u0120repeat": 11882, "eros": 11883, "\u0120mixture": 11884, "ctypes": 11885, "\u0120ancient": 11886, "\u0120hadn": 11887, "\u0120ideal": 11888, "heat": 11889, "uracy": 11890, "uling": 11891, "\u0120Naz": 11892, "indu": 11893, "\u0120assumed": 11894, "\u0120Configuration": 11895, "\u0120Florida": 11896, "KEN": 11897, "\u0120bread": 11898, "vertex": 11899, "\u0120kne": 11900, "priv": 11901, "\u0120complaint": 11902, "Na": 11903, "mad": 11904, "\u00c3\u0142": 11905, "sender": 11906, "itors": 11907, "ndarray": 11908, "\u0120vary": 11909, "\u0120RT": 11910, "classifier": 11911, "\u0120logs": 11912, "scriptions": 11913, "\u0120checkpoint": 11914, "\u00e5\u00a4\u00a7": 11915, "\u0120fans": 11916, "\u0120Dave": 11917, "override": 11918, "henticated": 11919, "\u00e5\u012c\u0142": 11920, "\u0120experimental": 11921, "cards": 11922, "sb": 11923, "\u00e2\u0122\u0136\u00e2\u0122\u0136": 11924, "\u0120reasonable": 11925, "Producer": 11926, "\u0120COPY": 11927, "$(": 11928, "212": 11929, "Lock": 11930, "\\.": 11931, "\u00e7\u0132": 11932, "\u0120aid": 11933, "maker": 11934, "RESS": 11935, "rison": 11936, "\u0120digits": 11937, "\u00d0\u00b3": 11938, "utely": 11939, "\u0120250": 11940, "allery": 11941, "cohol": 11942, "\u0120commission": 11943, "\u0120attached": 11944, "\u0120liquid": 11945, "scroll": 11946, "xfb": 11947, "\u0120Security": 11948, "Buffer": 11949, "WOR": 11950, "\u0120perman": 11951, "Usage": 11952, "utch": 11953, "\u0120convent": 11954, "\u0120resolve": 11955, "\u0120uncert": 11956, "rypto": 11957, "Hits": 11958, "ZH": 11959, "mom": 11960, "stage": 11961, "credentials": 11962, "\u0120checking": 11963, "2001": 11964, "employ": 11965, "cid": 11966, "')],": 11967, "\u0120Ev": 11968, "\u0120apps": 11969, "nce": 11970, "\u00e4\u00bd\u00bf": 11971, "precision": 11972, "Role": 11973, "\u0120--------------------------------": 11974, "ailability": 11975, "\u00e4\u00bd\u013e": 11976, "\u0120concentr": 11977, "fac": 11978, "mix": 11979, "ulus": 11980, "proj": 11981, "serialized": 11982, "mitive": 11983, "\u0120remainder": 11984, "\u0120principal": 11985, "\u0120stable": 11986, "\u0120permit": 11987, "blit": 11988, "MEDI": 11989, "\u0120Delete": 11990, "xaa": 11991, "\u0120employees": 11992, "\u0120Instead": 11993, "\u0120debate": 11994, "Scal": 11995, "\u00d7\u013b": 11996, "\u0120\u00ea": 11997, "isition": 11998, "changes": 11999, "omal": 12000, "cccc": 12001, "\u0120pointed": 12002, "aze": 12003, "books": 12004, "DU": 12005, "Lambda": 12006, "xdf": 12007, "xbe": 12008, "\u0120mental": 12009, "\u0120receiving": 12010, "\u0120Italian": 12011, "\u0120substantial": 12012, "\u0120Sir": 12013, "usiness": 12014, "major": 12015, "weets": 12016, "\u0120Stop": 12017, "\u0120helps": 12018, "\u0120highlight": 12019, "margin": 12020, "will": 12021, "edDict": 12022, "\u0120Arab": 12023, "AlterField": 12024, "Cross": 12025, "QSize": 12026, "\u00e9\u0136": 12027, "\u0120uint": 12028, "verter": 12029, "\u0120appearance": 12030, "deployment": 12031, "YY": 12032, "pur": 12033, "xcc": 12034, "\u0120alive": 12035, "\u0120plas": 12036, "Properties": 12037, "\u0120closer": 12038, "\u0120anxiety": 12039, "Equ": 12040, "\u0120bbox": 12041, "\u0120BUT": 12042, "\u0120Select": 12043, "Generated": 12044, "Double": 12045, "\u0120fuel": 12046, "roles": 12047, "\u0120Pack": 12048, "\u0120Invalid": 12049, "acher": 12050, "\u0120median": 12051, "\u0120stopper": 12052, "\u0120cups": 12053, "WSGI": 12054, "Done": 12055, "\u0120coast": 12056, "\u0120thoughts": 12057, "HP": 12058, "gence": 12059, "lot": 12060, "\u0120tuples": 12061, "obby": 12062, "dictionary": 12063, "handlers": 12064, "normalize": 12065, "song": 12066, "\u0120incorpor": 12067, "\u0120nested": 12068, "\u0120appreci": 12069, "';": 12070, "mh": 12071, "oauth": 12072, "\u0120Module": 12073, "\u012058": 12074, "frequency": 12075, "\u00e6\u012c": 12076, "\u0120hide": 12077, "adj": 12078, "\u0120Olymp": 12079, "\u0120calendar": 12080, "EMAIL": 12081, "coin": 12082, "\u0120whereas": 12083, "/{}": 12084, "\u0120AM": 12085, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 12086, "xfc": 12087, "Counter": 12088, "SK": 12089, "zil": 12090, "\u0120Tre": 12091, "\u010a\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120\u0120": 12092, "\u0120occasion": 12093, "ursday": 12094, "\u0120merely": 12095, "iner": 12096, "enda": 12097, "\u0120univers": 12098, "\u0120classification": 12099, "\u0120allowing": 12100, "\u0120humans": 12101, "\u00e7\u00a4\u00ba": 12102, "bow": 12103, "\u0120Civil": 12104, "\u0120doctor": 12105, "\u0120Rev": 12106, "={\"": 12107, "NG": 12108, "rename": 12109, "ala": 12110, "\u0120Link": 12111, "ivot": 12112, "\u0120Standard": 12113, "\u0120quit": 12114, "\u0120actor": 12115, "Weight": 12116, "\u0120competition": 12117, "xec": 12118, "\u0120Friday": 12119, "\u0120excess": 12120, "\u0120attempts": 12121, "Package": 12122, "\u0120VALUES": 12123, "radi": 12124, "\u012057": 12125, "median": 12126, "\u0120Player": 12127, "\u0120fing": 12128, "ahoo": 12129, "posts": 12130, "\u0120Joseph": 12131, "\u0120cash": 12132, "\u0120pid": 12133, "\u012010000": 12134, "Decimal": 12135, "\u0120winning": 12136, "\u0120currency": 12137, "\u0120vision": 12138, "\u0120defic": 12139, "\u0120symbols": 12140, "\u0120Leg": 12141, "destination": 12142, "hh": 12143, "\u0120Greek": 12144, "bling": 12145, "Handle": 12146, "mutation": 12147, "Card": 12148, "hlt": 12149, "rink": 12150, "\u0120counsel": 12151, "\u0120nan": 12152, "\u0120Cath": 12153, "getattr": 12154, "cov": 12155, "located": 12156, "\u0120brush": 12157, "Fill": 12158, "\u0120\"))": 12159, "()])": 12160, "-----------": 12161, "\u0120END": 12162, "\u00e6\u013e\u00ac": 12163, "---------------": 12164, "\u0120religious": 12165, "gres": 12166, "xda": 12167, "rient": 12168, "aks": 12169, "flatten": 12170, "\u0120Where": 12171, "\u0120chemical": 12172, "echo": 12173, "\u0120GPIO": 12174, "acent": 12175, "auc": 12176, "\u0120magazine": 12177, "\u00e8\u00bf\u013d": 12178, "supermod": 12179, "Ger": 12180, "\u00e7\u013b": 12181, "\u0120tweet": 12182, "leaf": 12183, "mph": 12184, "\"\",": 12185, "ialect": 12186, "\u0120terminal": 12187, "\u0120controlled": 12188, "){#": 12189, "Monitor": 12190, "\u0120AL": 12191, "\u0120apparently": 12192, "\u0120Secretary": 12193, "\u0120pip": 12194, "\u0120sizes": 12195, "\u0120anchor": 12196, "\u0120LICENSE": 12197, "2003": 12198, "such": 12199, "\u0120Bes": 12200, "special": 12201, "\u0120Series": 12202, "\u0120frequently": 12203, "live": 12204, "006": 12205, "terms": 12206, "\u0120Mont": 12207, "('#": 12208, "poon": 12209, "\u0120Channel": 12210, "DIRECT": 12211, "gression": 12212, "\u00e6\u0131": 12213, "\u0120alias": 12214, "\u0120Bur": 12215, "\u0120Win": 12216, "ATT": 12217, "\u0120600": 12218, "Detail": 12219, "\u00e6\u0123\u00af": 12220, "]==": 12221, "music": 12222, "album": 12223, "\u0120vars": 12224, "interfaces": 12225, "msgs": 12226, "\u00e5\u00bd\u0137": 12227, "metry": 12228, "\u0120detailed": 12229, "004": 12230, "\u0120Status": 12231, "\u0120variant": 12232, "\u0120immun": 12233, "\u00e6\u012b\u0122": 12234, "Day": 12235, "\u0120winter": 12236, "\u0120loved": 12237, "\u0120handling": 12238, "csrf": 12239, "\u0120environmental": 12240, ">')": 12241, "wind": 12242, "\u0120expr": 12243, "\u0120recognized": 12244, "210": 12245, "Will": 12246, "\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 12247, "\u0120Pan": 12248, "\u0120Joe": 12249, "xdc": 12250, "\u0120technique": 12251, "Sheet": 12252, "\u0120spectrum": 12253, "\u00e9\u00a1\u00b5": 12254, "ierarchy": 12255, "Since": 12256, "\u0120($": 12257, "\u0120\u00d0\u00b7": 12258, "\u00e4\u00b8\u012c": 12259, "\u0120queryset": 12260, "catch": 12261, "dw": 12262, "\u00a6\u0124": 12263, "uli": 12264, "\u0120r\u00c3\u00a9": 12265, "Wtagged": 12266, "bmc": 12267, "\u0120native": 12268, "\u0120bear": 12269, "Calculate": 12270, "\u0120tou": 12271, "\u0120nom": 12272, "\u0120coach": 12273, "\u0120Produ": 12274, "deepcopy": 12275, "vous": 12276, "}\\\\": 12277, "\u0120Source": 12278, "\u0120electro": 12279, "\u0120habit": 12280, "Provider": 12281, "Static": 12282, "cases": 12283, "qq": 12284, "isdir": 12285, "oster": 12286, "\u0120loan": 12287, "\u0120Indeed": 12288, "\u0120seek": 12289, "AddField": 12290, "ori": 12291, "odd": 12292, "\u0120upd": 12293, "azz": 12294, "\u0120decades": 12295, "\u0120digit": 12296, "Summer": 12297, "quantity": 12298, "\u0120tumor": 12299, "220": 12300, "asant": 12301, "\u0120Map": 12302, "flip": 12303, "\u0120quantity": 12304, "closed": 12305, "lee": 12306, "\u0120mad": 12307, "TEGER": 12308, "nesday": 12309, "Po": 12310, "World": 12311, "tro": 12312, "repository": 12313, "\u0120Sil": 12314, "rift": 12315, "\u0120Password": 12316, "\u0120rig": 12317, "\u0120Common": 12318, "sat": 12319, "\u0120furn": 12320, "\u0120dress": 12321, "\u0120Frame": 12322, "\u0120routes": 12323, "\u0120characteristics": 12324, "\u00d0\u00bb\u00d0\u00b8": 12325, "\u0120funds": 12326, "nger": 12327, "Export": 12328, "\u0120shouldn": 12329, "\u0120relax": 12330, "Member": 12331, "HS": 12332, "deg": 12333, "\u0120Another": 12334, ":')": 12335, "\u0120sav": 12336, "\u0120willing": 12337, "REAM": 12338, "167": 12339, "WI": 12340, "\u0120Such": 12341, "formats": 12342, "Objects": 12343, "amento": 12344, "IAL": 12345, "\u00e5\u00bb": 12346, "\u0120investment": 12347, "\u0120involve": 12348, "\u0120geometry": 12349, "FORMAT": 12350, "EVT": 12351, "\\\",": 12352, "sch": 12353, "\u0120\u00d0\u00bc": 12354, "\u0120matched": 12355, "\u0120syntax": 12356, "\u0120familiar": 12357, "\u0120African": 12358, "Pattern": 12359, "Sigma": 12360, "\u0120pprint": 12361, "esis": 12362, "\u0120debut": 12363, "\u0120Temp": 12364, "\u0120acts": 12365, "\u0120INS": 12366, "sensor": 12367, "\u00e7\u00ac\u00a6": 12368, "!--": 12369, "Gu": 12370, "NV": 12371, "xdd": 12372, "\u0120Aust": 12373, "theme": 12374, "\u0120recording": 12375, "\u0120grant": 12376, "\u0120helper": 12377, "eb": 12378, "rant": 12379, "\u0120\u00d1\u0124": 12380, "\u0120encrypt": 12381, "\u00e5\u00ba\u00a6": 12382, "064": 12383, "\u0120ich": 12384, "\u0120elected": 12385, "\u0120acade": 12386, "\u0120neighborhood": 12387, "xde": 12388, "\u0120ton": 12389, "hemat": 12390, "alg": 12391, "\u0120sports": 12392, "\u0120lots": 12393, "unched": 12394, "\u0120interpol": 12395, "\u0120temporary": 12396, "CONT": 12397, "Video": 12398, "\u0120Sol": 12399, "\u0120III": 12400, "\u0120Fore": 12401, "outs": 12402, "\u0120nova": 12403, "65000": 12404, "\u0120protected": 12405, "AST": 12406, "\u0120beam": 12407, "\u0120Who": 12408, "outfile": 12409, "phrase": 12410, "{\\\\": 12411, "LOAD": 12412, "\u0120emphas": 12413, "\u0120focused": 12414, "ilarly": 12415, "\u0120Global": 12416, "ESP": 12417, "\u0120demonstrated": 12418, "166": 12419, "\u0120timer": 12420, "\u0120references": 12421, "\u0120lap": 12422, "iterator": 12423, "\u0120Comple": 12424, "\u0120slug": 12425, "\u00e9\u013f\u00a2": 12426, "EY": 12427, "chars": 12428, "\u012067": 12429, "Formatter": 12430, "typ": 12431, "\u0120Options": 12432, "xee": 12433, "\u0120stone": 12434, "minute": 12435, "FieldDescriptor": 12436, "\u0120magic": 12437, "\u00e8\u00af\u00b7": 12438, "\u0120Maybe": 12439, "jud": 12440, "rooms": 12441, "\u0120Matt": 12442, "\u0120mesh": 12443, "\u0120Kim": 12444, "According": 12445, "\u0120extremely": 12446, "Null": 12447, "\u00d0\u00a7": 12448, "stal": 12449, "arters": 12450, "\u0120sick": 12451, "\u0120bacter": 12452, "\u0120raises": 12453, "\u0120retrie": 12454, "RY": 12455, "editor": 12456, "\u0120exposed": 12457, "ilarity": 12458, "\u0120tiny": 12459, "rac": 12460, "getitem": 12461, "sessed": 12462, "\u00e3\u0123\u00a8": 12463, "\u0120combine": 12464, "mosph": 12465, "\u0120Play": 12466, "\u0120Human": 12467, "\u012068": 12468, "lazy": 12469, "iguous": 12470, "abb": 12471, "\u0120meat": 12472, "ernet": 12473, "\u0120subsequent": 12474, "orough": 12475, "staff": 12476, "\u0120Images": 12477, "\u0120Put": 12478, "visor": 12479, "?)": 12480, "rp": 12481, "inated": 12482, "\u0120pert": 12483, "(\"#": 12484, "\u0120advice": 12485, "789": 12486, "\u00e4\u00bd\u012f": 12487, "fixture": 12488, "\u00d1\u012a": 12489, "\u0120Bad": 12490, "\u0120ou": 12491, "loose": 12492, "\u0120IL": 12493, "ptime": 12494, "asted": 12495, "\u0120smallest": 12496, "Short": 12497, "translation": 12498, "\u0120continues": 12499, "\u0120PyQt": 12500, "\u0120fundament": 12501, "Comment": 12502, "assertNot": 12503, "iously": 12504, "\u00e3\u0123\u00af": 12505, "\u0120begins": 12506, "\u0120dollars": 12507, "\u0120absol": 12508, "linspace": 12509, "\u0120executive": 12510, "cest": 12511, "iva": 12512, "xbb": 12513, "\u0120jsonify": 12514, "\u0120separated": 12515, "\u00ec\u0126": 12516, "\u0120ms": 12517, "ista": 12518, "amm": 12519, "gap": 12520, "atoes": 12521, "\u0120Lake": 12522, "\u0120scatter": 12523, "\u0120veget": 12524, "products": 12525, "\u0120Republican": 12526, "encrypt": 12527, "\u0120simulation": 12528, "Win": 12529, "\u0120Son": 12530, "rise": 12531, "107": 12532, "\u0120owned": 12533, "\u0120thousand": 12534, "650": 12535, "\u0120theore": 12536, "environment": 12537, "\u0120answers": 12538, "\u0120subjects": 12539, "\u0120pg": 12540, "\u0120quad": 12541, "brand": 12542, "\u0120figures": 12543, "bgp": 12544, "ea": 12545, "sphinx": 12546, "\u0120pub": 12547, "\u0120shares": 12548, "205": 12549, "dog": 12550, "agon": 12551, "saved": 12552, "\u0120Tim": 12553, "\u0120SD": 12554, "\u0120articles": 12555, "\u0120developing": 12556, "character": 12557, "\u0120dome": 12558, "igan": 12559, "\u0120Non": 12560, "\u0120chicken": 12561, "\u0120Supreme": 12562, "rices": 12563, "\u0120Sou": 12564, "\u0120jury": 12565, "\u0120communities": 12566, "Debug": 12567, "\u0120Valley": 12568, "\u0120largely": 12569, "ANGO": 12570, "\u0120boundary": 12571, "\u0120watched": 12572, "Har": 12573, "\u00e5\u0140": 12574, "\u0120cros": 12575, "\u0120strange": 12576, "\u0120truly": 12577, "147": 12578, "\u0120advanced": 12579, "Body": 12580, "\u0120duty": 12581, "\u0120discovery": 12582, "\u0120describes": 12583, "\u0120Davis": 12584, "ascade": 12585, "\u0120NY": 12586, "\u0120underlying": 12587, "\u0120filtered": 12588, "\u0120bowl": 12589, "\u0120nick": 12590, "\u0120Cir": 12591, "\u0120Battle": 12592, "\u0120Whether": 12593, "\u010a\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 12594, "\u0120dom": 12595, "unct": 12596, "\u0120setattr": 12597, "\u0120THIS": 12598, "Mo": 12599, "represent": 12600, "heg": 12601, "\u0120Jac": 12602, "ERT": 12603, "\u0120retrieve": 12604, "\u0120CONTR": 12605, ":[": 12606, "Am": 12607, "\u00e0\u00a5": 12608, "\u0120mas": 12609, "\u0120sector": 12610, "workers": 12611, "\u0120mainly": 12612, "\u0120putting": 12613, "Power": 12614, "Socket": 12615, "yellow": 12616, "Exist": 12617, "\u0120initially": 12618, "\u00e5\u0132\u012a": 12619, "Fore": 12620, "XC": 12621, "avas": 12622, "\u0120Static": 12623, "mbed": 12624, "900": 12625, "PM": 12626, "\u0120lista": 12627, "AE": 12628, "Our": 12629, "clo": 12630, "\u00c4\u012f": 12631, "una": 12632, "204": 12633, "\u0120pointer": 12634, "\u0120fragment": 12635, "arma": 12636, "\u0120fs": 12637, "ported": 12638, "poll": 12639, "\u0120Space": 12640, "\u0120Corpor": 12641, "finished": 12642, "\u00c3\u00a8re": 12643, "\u0120alleged": 12644, "\u0120Angeles": 12645, "\u0120ride": 12646, "\u0120bins": 12647, "\u0120disabled": 12648, "\u0120capable": 12649, "Generic": 12650, ")_": 12651, "lb": 12652, "\u010a\u0109\u0109\u0120\u0120\u0120": 12653, "cred": 12654, "\u0120readers": 12655, "2005": 12656, "\u0120tracks": 12657, "vvvv": 12658, "Joint": 12659, "\u0120negot": 12660, "\u0120Twitter": 12661, "TON": 12662, "Ticket": 12663, "\u0120passes": 12664, "\u0120sync": 12665, "\u0120Ale": 12666, "('.')": 12667, "launch": 12668, "Mask": 12669, "bundle": 12670, "enance": 12671, "\u0120welcome": 12672, "izable": 12673, "Exit": 12674, "standard": 12675, "multiple": 12676, "\u0120troops": 12677, "\u0120Hitler": 12678, "rigger": 12679, "\u0120bgcolor": 12680, "cour": 12681, "\u0120------------------------------------------------": 12682, "\u0120Gar": 12683, "\u0120annual": 12684, "sensitive": 12685, "============================================================================": 12686, "\u0120crisis": 12687, ";\"": 12688, "Cursor": 12689, "xaf": 12690, "\u0120IOError": 12691, "\u0120tall": 12692, "erg": 12693, "\u0120Camb": 12694, "\u0120persons": 12695, "\u0120particle": 12696, "\u00e7\u0132\u0128": 12697, "Ro": 12698, "onto": 12699, "\u0120sweet": 12700, "angular": 12701, "Where": 12702, "Tube": 12703, "\\])": 12704, "qty": 12705, "smo": 12706, "xcd": 12707, "\u0120broke": 12708, "\u0120walking": 12709, "HH": 12710, "Her": 12711, "VAR": 12712, "lis": 12713, "\u00e5\u0134\u012e": 12714, "\u0120bodies": 12715, "aylor": 12716, "\u0120Four": 12717, "ferent": 12718, "\u0120boys": 12719, "stdin": 12720, "\u0120restored": 12721, "middle": 12722, "\u0120Given": 12723, "URCE": 12724, "\u0120territ": 12725, "facts": 12726, "\u0120Cost": 12727, "rence": 12728, "Leg": 12729, "\u0120Which": 12730, "\u0120discrimin": 12731, "allenge": 12732, "precated": 12733, "Kit": 12734, "\u0120fish": 12735, "\u0120conversion": 12736, "udd": 12737, "positive": 12738, "gypt": 12739, "\u0120trend": 12740, "\u0120bien": 12741, "evaluate": 12742, "xab": 12743, "\u0120Education": 12744, "\u0120absor": 12745, "predictions": 12746, "\u0120massive": 12747, "\u0120Monday": 12748, "\u0120typical": 12749, "\u0120okay": 12750, "artist": 12751, "weather": 12752, "aneous": 12753, "tpl": 12754, "\u0120Save": 12755, "\u0120interact": 12756, "\u0120Chamber": 12757, "\u0120charged": 12758, "dimensional": 12759, "prompt": 12760, "\u0120truck": 12761, "ALLOW": 12762, "\u0120Development": 12763, "Mean": 12764, "\u0120literature": 12765, "capitalize": 12766, "bach": 12767, "\u0120excell": 12768, "argmax": 12769, "\u012063": 12770, "Attributes": 12771, ")>": 12772, "east": 12773, "\u0120bs": 12774, "ctools": 12775, "\u0120Local": 12776, "aci\u00c3\u00b3n": 12777, "\u0120wheel": 12778, "\u0120planet": 12779, "human": 12780, "vt": 12781, "wra": 12782, "\u0120ban": 12783, "lya": 12784, "izon": 12785, "decimal": 12786, "\u0120fly": 12787, "perform": 12788, "pending": 12789, "priority": 12790, "xea": 12791, "Edge": 12792, "\u0120suitable": 12793, "\u0120scenario": 12794, "AMPLES": 12795, "\u0120Environment": 12796, "remo": 12797, "\u0120Card": 12798, "setGeometry": 12799, "\u0120aus": 12800, "\u0120crack": 12801, "\u0120gt": 12802, "\u0120mini": 12803, "serializer": 12804, "\u0120denied": 12805, "Extension": 12806, "\u0120werden": 12807, "xls": 12808, "\u0120Cast": 12809, "\u0120Marg": 12810, "avid": 12811, "ANN": 12812, "\u0120silent": 12813, "\u0120necessarily": 12814, "\u0120concerns": 12815, "\u00e8\u00bf\u0136\u00e5\u013d\u0140": 12816, "RF": 12817, "hl": 12818, "than": 12819, "\u0120AP": 12820, "\u0120mess": 12821, "\u0120manip": 12822, "\u0120homes": 12823, "fx": 12824, "\u00f0\u0133": 12825, "\u01201970": 12826, "axy": 12827, "\u0120closest": 12828, "230": 12829, "ATES": 12830, "\u012066": 12831, "\u0120theano": 12832, "\u0120lon": 12833, "ntest": 12834, "\u0120vul": 12835, "combo": 12836, "\u0120extend": 12837, "\u00e5\u012e\u0138": 12838, "collections": 12839, "Dem": 12840, "Div": 12841, "Wrapper": 12842, "rog": 12843, "apsed": 12844, "\u0120Word": 12845, "\u0120ops": 12846, "\u00e7\u00a8\u012d": 12847, "Cred": 12848, "Hor": 12849, "tract": 12850, "zo": 12851, "\u0120Award": 12852, "\u0120Fed": 12853, "\u0120alarm": 12854, "strong": 12855, "hyper": 12856, "esterday": 12857, "\u0120chrom": 12858, "\u0120desire": 12859, "\u0120ROOT": 12860, ",[": 12861, "\u0120flo": 12862, "mente": 12863, "\u0120coord": 12864, "\u0120distingu": 12865, "\u0120eth": 12866, "\u0120Britain": 12867, "Pay": 12868, "\u0120languages": 12869, "race": 12870, "\u0120abstract": 12871, "\u01201994": 12872, "\u0120incident": 12873, "\u00e2\u0139\u00bc": 12874, "cached": 12875, "\u0120ga": 12876, "\u0120MP": 12877, "\u0120expansion": 12878, "mond": 12879, "\u0120realized": 12880, "\u0120numerous": 12881, "\u0120architecture": 12882, "\u00e2\u0139\u00bc\u00ef\u00b8\u0131": 12883, "FIL": 12884, "\\[": 12885, "omp": 12886, "illery": 12887, "xbc": 12888, "\u0120possibility": 12889, "\u0120citizens": 12890, "\u0120eps": 12891, "IMAGE": 12892, "BD": 12893, "brid": 12894, "\u0120grav": 12895, "\u00c3\u00a1n": 12896, "Bytes": 12897, "\u0120worst": 12898, "\u0120Turn": 12899, "\u0120Cur": 12900, "\u0120Ho": 12901, "\u0120disappe": 12902, "\u0120movies": 12903, "\u012085": 12904, "905": 12905, "Ms": 12906, "every": 12907, "lain": 12908, "nl": 12909, "wing": 12910, "meeting": 12911, "')])": 12912, "108": 12913, "\u0120shoulder": 12914, "Board": 12915, "svn": 12916, "\u0120achieved": 12917, "lepton": 12918, "\u0120pictures": 12919, "ican": 12920, "\u0120exhaust": 12921, "\u0120rose": 12922, "\u0120codes": 12923, "inite": 12924, "information": 12925, "ocy": 12926, "\u0120Victor": 12927, "\u0120decisions": 12928, "\u0120politics": 12929, "\u0120researchers": 12930, "\u0120understood": 12931, "Sequential": 12932, "Events": 12933, "Under": 12934, "\u0120tb": 12935, "\u0120skill": 12936, "\u0120victory": 12937, "\u0120Tuesday": 12938, "\u0120Joh": 12939, "\u0120neur": 12940, "maximum": 12941, "\u0120committed": 12942, "\u0120declared": 12943, "\u0120Moreover": 12944, "Mr": 12945, "\u0120thro": 12946, "\u0120stem": 12947, "transport": 12948, "Gets": 12949, "\u0120conj": 12950, "\u0120protest": 12951, "\u0120coffee": 12952, "appoint": 12953, "selector": 12954, "MSG": 12955, "\u00e6\u0139\u00a5": 12956, "\u0120perspective": 12957, "\u0120cere": 12958, "\u0120conce": 12959, "\u0120Microsoft": 12960, "\u0120Resource": 12961, "\\)": 12962, "\u0120amaz": 12963, "\u0120eu": 12964, "\u0120Ans": 12965, "\u0120Did": 12966, "\u0120recurs": 12967, "igrate": 12968, "\u0120worry": 12969, "rotate": 12970, "\u0120Token": 12971, "\u0120Api": 12972, "resolve": 12973, "utional": 12974, "Quant": 12975, "\u0120criminal": 12976, "\u0120aspects": 12977, "xl": 12978, "\u0120Saturday": 12979, "\u01201995": 12980, "\u0120heads": 12981, "\u0120Parse": 12982, "\u0120coordinate": 12983, "\u0120ao": 12984, "asty": 12985, "')))": 12986, "\u0120organizations": 12987, "\u0120Daniel": 12988, "fortunately": 12989, "\u0120catalog": 12990, "\u0120ui": 12991, "\u0120approved": 12992, "\u0120Perry": 12993, "\u0120Championship": 12994, "bec": 12995, "\u0120replied": 12996, "iry": 12997, "endant": 12998, "}},": 12999, "paper": 13000, "ati": 13001, "\u0120rgb": 13002, "240": 13003, "ILD": 13004, "softmax": 13005, "CG": 13006, "Question": 13007, "rnn": 13008, "\u0120Iran": 13009, "\u0120WS": 13010, "\u0120somewhere": 13011, "\u0120Real": 13012, "FFFF": 13013, "camera": 13014, "\u00e6\u00ac": 13015, "\u0120discover": 13016, "ighter": 13017, "door": 13018, "ainty": 13019, "igo": 13020, "quet": 13021, "\u0120tempfile": 13022, "\u0120standards": 13023, "\u0120\u00c2\u00ab": 13024, "\u0120kitchen": 13025, "Tip": 13026, "ftype": 13027, "rg": 13028, "\u0120dangerous": 13029, "\u0120fg": 13030, "\u0120lip": 13031, "\u0120Pac": 13032, "\u0120Rest": 13033, "\u0120centre": 13034, "\u0120Look": 13035, "_[": 13036, "\u0120sir": 13037, "imony": 13038, "\u00e3\u0123\u00a6": 13039, "contenttypes": 13040, "\u0120Carolina": 13041, "DJANGO": 13042, "\u00e4\u00bd\u00bf\u00e7\u0136\u00a8": 13043, "bian": 13044, "your": 13045, "isinstance": 13046, "contract": 13047, "\u0120phosph": 13048, "\u0120authentication": 13049, "fraid": 13050, "\u00e7\u00bb\u0135": 13051, "kes": 13052, "onna": 13053, "\u0120Does": 13054, "crement": 13055, "slots": 13056, ":(": 13057, "Json": 13058, "reams": 13059, "\u0120Mrs": 13060, "154": 13061, "TYP": 13062, "\u0120metab": 13063, "\u0120chest": 13064, "\u0120assignment": 13065, "GEN": 13066, "Success": 13067, "browse": 13068, "\u0120pump": 13069, "icing": 13070, "\u0120withdraw": 13071, "\u0120defaultdict": 13072, "RS": 13073, "\u00eb\u00a1": 13074, "imately": 13075, "['_": 13076, "\u0120dataframe": 13077, "ATURE": 13078, "customer": 13079, "variant": 13080, "\u0120Move": 13081, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13082, "FIEL": 13083, "ircraft": 13084, "MEDIA": 13085, "\u0120independ": 13086, "osing": 13087, "Loop": 13088, "shortcuts": 13089, "\u00e7\u013d\u00ae": 13090, "avascript": 13091, "categ": 13092, "lass": 13093, "\u00c3\u00a6": 13094, "\u0120pushed": 13095, "\u0120ml": 13096, "\u0120noticed": 13097, "ICES": 13098, "versions": 13099, "\u00d0\u00be\u00d0\u00bc": 13100, "\u0120Canadian": 13101, ".+": 13102, "\u0120cel": 13103, "\u0120sep": 13104, "ATTR": 13105, "ENABLE": 13106, "POINT": 13107, "\u0120measurement": 13108, "lapse": 13109, "FloatField": 13110, ",:]": 13111, "yield": 13112, "\u0120contro": 13113, "Lin": 13114, "sit": 13115, "\u0120signs": 13116, "LANGU": 13117, "\u0120bought": 13118, "\u0120TEST": 13119, "\u00e5\u0140\u012d": 13120, "Domain": 13121, "Lines": 13122, "gly": 13123, "\u0120nl": 13124, "\u0120rv": 13125, "\u0120mel": 13126, "scrib": 13127, "website": 13128, "COUNT": 13129, "\u00e5\u0131\u0124": 13130, "Engine": 13131, ")#": 13132, "\u0120lookup": 13133, "\u0120audience": 13134, "vet": 13135, "\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120": 13136, "\u0120newly": 13137, "\u00d0\u00bd\u00d0\u00be": 13138, "Direction": 13139, "\u00e7\u00ab": 13140, "\u0120marks": 13141, "\u0120consumer": 13142, "\u0120chronic": 13143, "\u0120Chief": 13144, "DEL": 13145, "\u00e3\u0123\u0141": 13146, "\u0120kinds": 13147, "Append": 13148, "Has": 13149, "_):": 13150, "dynamic": 13151, "ilty": 13152, "\u0120preferred": 13153, "\u0120abund": 13154, "\u012061": 13155, "decoder": 13156, "\u0120strides": 13157, "alarm": 13158, "\u0120rein": 13159, "\u0120);": 13160, "\u0120executed": 13161, "cular": 13162, "\u0120bond": 13163, "\u0120gran": 13164, "clusters": 13165, "']):": 13166, "\u0120obs": 13167, "114": 13168, "Interval": 13169, "Distance": 13170, "\u0120appointed": 13171, "MAN": 13172, "had": 13173, "uset": 13174, "\u0120founded": 13175, "\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13176, "usal": 13177, "\u0120Grand": 13178, "(_('": 13179, "\u0120decrease": 13180, "\u0120orientation": 13181, "pix": 13182, "\u0120basket": 13183, "\u0120(**": 13184, "\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13185, "problem": 13186, "ARK": 13187, "henticate": 13188, ">,": 13189, "inher": 13190, "\u0120fant": 13191, "\u0120nx": 13192, "\u0120Sing": 13193, "\u0120MD": 13194, "\u0120collab": 13195, "corpus": 13196, "\u0120criteria": 13197, "QRect": 13198, "_\"": 13199, "angles": 13200, "Positive": 13201, "VM": 13202, "prof": 13203, "curve": 13204, "\u0120refresh": 13205, "\u0120\u00c2\u00a3": 13206, "However": 13207, "\u0120Kingdom": 13208, "Tools": 13209, "\u0120cp": 13210, "\u0120ftype": 13211, "\u0120dc": 13212, "inton": 13213, "\u0120Hot": 13214, "\u0120abort": 13215, "\u0120verb": 13216, "\u012062": 13217, "attack": 13218, "Character": 13219, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13220, "LINK": 13221, "Bu": 13222, "Vari": 13223, "nabla": 13224, "\u0120Dev": 13225, "avelength": 13226, "IH": 13227, "\u00e8\u0122": 13228, "\u0120wrap": 13229, "\u0120gest": 13230, "\u0120Publ": 13231, "\u0120Rog": 13232, "\u0120Wol": 13233, "\u0120permitted": 13234, "ENCE": 13235, "working": 13236, "dos": 13237, "floor": 13238, "take": 13239, "design": 13240, "\u0120somewhat": 13241, "director": 13242, "InputTag": 13243, "${": 13244, "wik": 13245, "chines": 13246, "\u0120youth": 13247, "ensure": 13248, "\u0120spending": 13249, "manage": 13250, "party": 13251, "\u0120Cover": 13252, "\u0120metavar": 13253, "\u00e8\u00bf\u0129": 13254, "rotation": 13255, "\u0120epochs": 13256, "Redirect": 13257, "\u0120juris": 13258, "\u00e5\u00bb\u00ba": 13259, "}-": 13260, "detection": 13261, "\u0120Try": 13262, "Loss": 13263, "\u0120ped": 13264, "\u0120dinner": 13265, "xca": 13266, "\u0120snapshot": 13267, "\u0120strongly": 13268, "Ant": 13269, "Every": 13270, "wan": 13271, "racy": 13272, "\u0120Cross": 13273, "food": 13274, "Center": 13275, "Limit": 13276, "agn": 13277, "('[": 13278, "\u0120[*": 13279, "\u0120Far": 13280, "\u0120alert": 13281, "\u0120backup": 13282, "\u0120entre": 13283, "\u0120phrase": 13284, "\u0120liked": 13285, "+^": 13286, "Ptr": 13287, "iral": 13288, "\u0120sear": 13289, "\u0120argv": 13290, "\u00eb\u012d\u00a4": 13291, "tu": 13292, "\u0120housing": 13293, "abe": 13294, "\u0120contemp": 13295, "\u0120Bre": 13296, "\u0120listing": 13297, "\u0120speaking": 13298, "\u0120Template": 13299, "mf": 13300, "\u0120island": 13301, "\u0120knowing": 13302, "bounds": 13303, "\u0120Sets": 13304, "quality": 13305, "254": 13306, "\u0120attitude": 13307, "ordering": 13308, "\u0120surgery": 13309, "market": 13310, "\u0120validators": 13311, "\u0120Atl": 13312, "LIED": 13313, "Bi": 13314, "even": 13315, "\u0120branches": 13316, "Insert": 13317, "geq": 13318, "\u012069": 13319, "\u0120matters": 13320, "Constraint": 13321, "oured": 13322, "\u0120manifest": 13323, "\u0120historical": 13324, "\u0120widely": 13325, "trip": 13326, "alive": 13327, "\u0120Bot": 13328, "\u00d0\u00b8\u00d1\u0123": 13329, "=('": 13330, "Dense": 13331, "adjust": 13332, "\u0120Museum": 13333, "\u0120Rail": 13334, "flux": 13335, "OBD": 13336, "\u0120normally": 13337, ")}\\": 13338, "must": 13339, "\u0120fer": 13340, "\u0120TType": 13341, "\u0120Sat": 13342, "118": 13343, "\u0120acquired": 13344, "\u0120Force": 13345, "latex": 13346, "\u0120hardware": 13347, "\u0120\u00e0\u00a4": 13348, "anch": 13349, "\u0120rear": 13350, "\u0120aside": 13351, "\u0120Kent": 13352, "TOKEN": 13353, "crop": 13354, "inline": 13355, "\u0120fashion": 13356, "\u0120'(": 13357, "\u0120hurt": 13358, "utorial": 13359, "ungs": 13360, "clf": 13361, "\u0120Before": 13362, "adel": 13363, "\u0120teacher": 13364, "\u0120crowd": 13365, "]'": 13366, "union": 13367, "\u0120supplied": 13368, "\u0120accompl": 13369, "ologists": 13370, "Utils": 13371, "Ma": 13372, "nf": 13373, "___": 13374, "...')": 13375, "placement": 13376, "\u0120trained": 13377, "inciple": 13378, "+'/": 13379, "\u0120Special": 13380, "VS": 13381, "\u0120pocket": 13382, "servative": 13383, "Home": 13384, "inent": 13385, "ummer": 13386, "\u0120Cam": 13387, "\u0120finds": 13388, "\u0120selenium": 13389, "\u0120measurements": 13390, "\u00e7\u00ae\u0139": 13391, "\u00e5\u00bf": 13392, "\u0120\"\":": 13393, "\u0120university": 13394, "\u0120span": 13395, "Cannot": 13396, "\u0120consum": 13397, "subfield": 13398, "Setting": 13399, "\u01204096": 13400, "\u0120chopped": 13401, "Even": 13402, "\u00e9\u013a": 13403, "remain": 13404, "\u0120pdf": 13405, "\u0120mirror": 13406, "\u0120aband": 13407, "aland": 13408, "\u0120Finally": 13409, "\u01201992": 13410, "MET": 13411, "itespace": 13412, "\u00d7\u0137\u00d7": 13413, "mont": 13414, "\u0124\u00ac": 13415, "\u0120sender": 13416, "157": 13417, "\u0120{}),": 13418, "ologist": 13419, "\u00e5\u0128\u0127": 13420, "\u0120powers": 13421, "\u00e8\u00be\u0135\u00e5\u0127\u00a5": 13422, "four": 13423, "gh": 13424, "\u00e5\u0141": 13425, "fox": 13426, "\u0120transformation": 13427, "xford": 13428, "snap": 13429, "Clean": 13430, "\u0120ti": 13431, "\u0120nose": 13432, "\u0120certificate": 13433, "\u00e5\u013e\u00b0": 13434, "\u0120sampling": 13435, "\u0120Should": 13436, "\u0120photos": 13437, "poss": 13438, "usepackage": 13439, "initialize": 13440, "AW": 13441, "Fast": 13442, "wave": 13443, "\u0120aver": 13444, "utter": 13445, "othes": 13446, "\u0120weapon": 13447, "\u0120HE": 13448, "shapes": 13449, "155": 13450, "oving": 13451, "\u0120invoice": 13452, "ende": 13453, "\u0120inverse": 13454, "ulative": 13455, "\u0120Han": 13456, "asters": 13457, "spot": 13458, "\u0120Child": 13459, "\u0120brig": 13460, "ylim": 13461, "\u0120\u00d0\u00bf\u00d1\u0122": 13462, "\u0120imagine": 13463, "means": 13464, "\u0120mol": 13465, "\u0120Bern": 13466, "2004": 13467, "\u0120Ohio": 13468, "\u00e5\u00a7\u012d": 13469, "\u0120papers": 13470, "elled": 13471, "ulin": 13472, "PROTO": 13473, "\u0120experienced": 13474, "oir": 13475, "\u0120':": 13476, "\u0120coords": 13477, "anna": 13478, "\u0120cream": 13479, "\u0120transforms": 13480, "}}^": 13481, "\u0120Assert": 13482, "\u0120accurate": 13483, "publish": 13484, "\u0120Academy": 13485, "\u00e6\u00a8\u00a1": 13486, "*)": 13487, "iy": 13488, "\u0120sad": 13489, "\u0120Hon": 13490, "\u0120xs": 13491, "\u012096": 13492, "iri": 13493, "\u0120rom": 13494, "\u0120tone": 13495, "itable": 13496, "\u0120flight": 13497, "\u00e3\u0123\u012e": 13498, "\u0120svntest": 13499, "Analysis": 13500, "&#": 13501, "Who": 13502, "mq": 13503, "\u010d\u010a\u0120\u0120\u0120\u0120\u0120\u0120": 13504, "\u0120dedic": 13505, "plane": 13506, "3308": 13507, "ToMany": 13508, "\u0120Wilson": 13509, "\u0120hits": 13510, "\u0120encount": 13511, "SES": 13512, "both": 13513, "rv": 13514, "including": 13515, "stron": 13516, "=\"%": 13517, "ollowing": 13518, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13519, "\u0120serializers": 13520, "\u0120promote": 13521, "\u0120tkinter": 13522, "Pad": 13523, "\u0120nic": 13524, "chmark": 13525, "\u0120yards": 13526, "need": 13527, "audit": 13528, "\u0120Georgia": 13529, "Public": 13530, "odes": 13531, "ubs": 13532, "\u0120climate": 13533, "\u0120tradition": 13534, "\u0120normalized": 13535, "\u0120Cr": 13536, "ensus": 13537, "buff": 13538, "MAIN": 13539, "cmg": 13540, "Offsets": 13541, "/>.": 13542, "\u0120phenomen": 13543, "VD": 13544, "aire": 13545, "\u0120Iter": 13546, "logout": 13547, "\u0120supporting": 13548, "Enable": 13549, "White": 13550, "\u0120evaluated": 13551, "\u0120\u010a\u0120\u0120\u0120\u0120\u0120": 13552, "velocity": 13553, "\u00d0\u00bd\u00d1\u012d": 13554, "\u0120horizontal": 13555, "\u0120Prime": 13556, "\u00d0\u00b5\u00d0\u00bd\u00d0\u00b8": 13557, "\u0120SELECT": 13558, "'%(": 13559, "\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13560, "='')": 13561, "\u0120Stat": 13562, "\u0120ending": 13563, "Send": 13564, "\u00c5\u00a1": 13565, "\u0120afraid": 13566, "\u0120resc": 13567, "STREAM": 13568, "ATCH": 13569, "\u0120scr": 13570, "Projects": 13571, "hips": 13572, "\u00e6\u012d": 13573, "\u00e8\u00b7": 13574, "itled": 13575, "router": 13576, "\u0120dummy": 13577, "\u0120cond": 13578, "they": 13579, "\u0120industrial": 13580, "Flags": 13581, "\u0120heaven": 13582, "organization": 13583, "\u0120behaviour": 13584, "\u0120'\u00e2": 13585, "\u0120Ray": 13586, "INPUT": 13587, "\u0120oblig": 13588, "\u0120substr": 13589, "loading": 13590, "away": 13591, "\u0120survival": 13592, "focus": 13593, "mx": 13594, "\u0120conclusion": 13595, "letes": 13596, "TTTo": 13597, "\u0120publication": 13598, "\u0120analog": 13599, "\u0120considering": 13600, "\u0120charges": 13601, "NULL": 13602, "\u0120vacc": 13603, "\u0120Pos": 13604, "ishment": 13605, "\u0120locale": 13606, "arrier": 13607, "\u0120Define": 13608, "=&": 13609, "CAC": 13610, "Like": 13611, "\u0120award": 13612, "antly": 13613, "UTC": 13614, "recogn": 13615, "\u0120temper": 13616, "\u0120slot": 13617, "cookies": 13618, "\u0120municip": 13619, "\u0120vast": 13620, "\u0120scientists": 13621, "rics": 13622, "\u0120frag": 13623, "\u0120sport": 13624, "\u0120Es": 13625, "communic": 13626, "checker": 13627, "\u0120bigger": 13628, "pushButton": 13629, "ository": 13630, "=#": 13631, "\u00e5\u0133": 13632, "leton": 13633, "\u0120Conv": 13634, "fraction": 13635, "Full": 13636, "via": 13637, "\u0120Circ": 13638, "\u0120Dig": 13639, "Setup": 13640, "\u0120bases": 13641, "powheg": 13642, "OU": 13643, "\u00c4\u0129": 13644, "\u0120Deter": 13645, "\u0120Hard": 13646, "\u0120subset": 13647, "queryset": 13648, "\u0120confusion": 13649, "Band": 13650, "into": 13651, "(\"{": 13652, "\u0120Hunt": 13653, "\u0120wear": 13654, "uality": 13655, "\u0120,_('": 13656, "ElementType": 13657, "losure": 13658, "_>": 13659, "aser": 13660, "015": 13661, "\u0120roles": 13662, "\u0120vectors": 13663, "PasswordValidator": 13664, "\u0120Jewish": 13665, "\u0120replic": 13666, "rage": 13667, "\u0120Fall": 13668, "additional": 13669, "\u0120Management": 13670, "\u0120Matrix": 13671, "\u0120southern": 13672, "/.": 13673, "rob": 13674, "\u0120todo": 13675, "sentry": 13676, "\u012073": 13677, "DELETE": 13678, "@@@@": 13679, "retry": 13680, "\u0120decomp": 13681, "\u0120Bow": 13682, "\u00e2\u0122\u0132": 13683, "\u0120champions": 13684, "UPDATE": 13685, "/-": 13686, "133": 13687, "SG": 13688, "itis": 13689, "\u0120bid": 13690, "\u0120contest": 13691, "endo": 13692, "\u0120datasets": 13693, "earning": 13694, "APPS": 13695, "\u0120artists": 13696, "\u0120\"{}": 13697, "\u0120Ba": 13698, "\u0120imported": 13699, "Real": 13700, "Prompt": 13701, "XXXX": 13702, "\u0120hundreds": 13703, "\u0120Furthermore": 13704, "\u0120Mallory": 13705, "\u0120Ly": 13706, "igned": 13707, "\u0120Array": 13708, "HEADER": 13709, "\u0120fontsize": 13710, "\u0120nearby": 13711, "Extract": 13712, "#-": 13713, "THE": 13714, "tcp": 13715, "entities": 13716, "\u0120rac": 13717, "\u0120policies": 13718, "ECK": 13719, "\u00e5\u012f\u0137": 13720, "attention": 13721, "\u0120violence": 13722, "pause": 13723, "worth": 13724, "ami": 13725, "plays": 13726, "\u00e2\u0122\u013f.": 13727, "\u0120archive": 13728, "UST": 13729, "\u0142\u0122": 13730, "heast": 13731, "\u0120templates": 13732, "roadcast": 13733, "West": 13734, "pressed": 13735, "\u0120hole": 13736, "\u0120estate": 13737, "ells": 13738, "ishop": 13739, "\u0120consists": 13740, "Axis": 13741, "mazon": 13742, "\u0120Egypt": 13743, "\u0120legs": 13744, "Poly": 13745, "\u0120silence": 13746, "\u0120Berlin": 13747, "\u0120wrapped": 13748, "CAP": 13749, "\u0120tie": 13750, "associ": 13751, "\u0120Bit": 13752, "omes": 13753, "\u0120unpack": 13754, "\u0120Three": 13755, "\u0120obst": 13756, "Stats": 13757, "ski": 13758, "\u0120falling": 13759, "nbsp": 13760, "XCUI": 13761, "\u00ec\u013c": 13762, "\u0120alignment": 13763, "\u0120responsibility": 13764, "',)": 13765, "\u0120Li": 13766, "aren": 13767, "ReLU": 13768, "prise": 13769, "production": 13770, "=\"\",": 13771, "\u0120fabric": 13772, "Hy": 13773, "\u0120\u0120\u010a": 13774, "adas": 13775, "\u0120Ha": 13776, "prog": 13777, "\u00d0\u00be\u00d1\u0124": 13778, "\\\",\\\"": 13779, "CSS": 13780, "rug": 13781, "icMock": 13782, "ella": 13783, "POS": 13784, "\u00e2\u0136\u0122\u00e2\u0136\u0122": 13785, "eu": 13786, "five": 13787, "vc": 13788, "\u0120Head": 13789, "\u0120ordering": 13790, "COMP": 13791, "distribution": 13792, "ToManyField": 13793, "XCUIElementType": 13794, ",**": 13795, "jam": 13796, "vard": 13797, "\u0120fee": 13798, "cmst": 13799, "\u0120DEBUG": 13800, "\u0120explanation": 13801, "\u0120fid": 13802, "veh": 13803, "\u0120Right": 13804, "workflow": 13805, "ocker": 13806, "\u0120synd": 13807, "+'_": 13808, "\u0120funding": 13809, "between": 13810, "\u0120conventional": 13811, "\u00c3\u00b8": 13812, "sections": 13813, "\u0120lean": 13814, "ateral": 13815, "reland": 13816, "\u00d0\u00b5\u00d0\u00bb": 13817, "Sort": 13818, "mell": 13819, "\u0120Sand": 13820, "\u0120Case": 13821, "\u0120sha": 13822, "\u0120jet": 13823, "rawler": 13824, "forcement": 13825, "33333333": 13826, "rst": 13827, "anz": 13828, "develop": 13829, "parsed": 13830, "neut": 13831, "\u0120Young": 13832, "\u0120merged": 13833, "\u00e8\u00bf\u013b": 13834, "VO": 13835, "\\].": 13836, "\u0120hi": 13837, "\u0120alcohol": 13838, "Elements": 13839, "\u0120histor": 13840, "finish": 13841, "Origin": 13842, "\u0120Sar": 13843, "indexes": 13844, "\u0120Const": 13845, "LANGUAGE": 13846, "\u010d\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13847, "\u0120asc": 13848, "\u0120Bul": 13849, "\u0120younger": 13850, "ansas": 13851, "0000000": 13852, "\u0120Convert": 13853, "GROUP": 13854, "FN": 13855, "\u00ec\u00a7": 13856, "175": 13857, "FILES": 13858, "\u0120decreased": 13859, "Clear": 13860, "ynchronous": 13861, "English": 13862, "\u0120Ukraine": 13863, "mans": 13864, "\u0120Pass": 13865, "('')": 13866, "rowth": 13867, "\u0120classifier": 13868, "\u0120crash": 13869, "\u00e5\u00bc\u0122": 13870, "320": 13871, "Using": 13872, "\u00e9\u0123": 13873, "\u0120\u010a\u0109": 13874, "106": 13875, "Release": 13876, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13877, ")$.": 13878, "BOT": 13879, "gender": 13880, "\u0120ade": 13881, "\u0120lies": 13882, "ayes": 13883, "\u0120NE": 13884, "\u0120DAM": 13885, "\u0120magnetic": 13886, "patTuple": 13887, "\u0120deploy": 13888, "\u0120Zealand": 13889, "rehen": 13890, "\u0120bc": 13891, "\u0120evol": 13892, "\u0120GET": 13893, "222": 13894, "\u0120approaches": 13895, "networks": 13896, "marily": 13897, "ManyToManyField": 13898, "\u0120tid": 13899, "plural": 13900, "strategy": 13901, "lectric": 13902, "\u0120molecular": 13903, "\u0120weapons": 13904, "cmgtools": 13905, "\u0120pron": 13906, "\u0120bio": 13907, "='/": 13908, "\u0120preserve": 13909, "\u0120Unit": 13910, "players": 13911, "disp": 13912, "\u0120expensive": 13913, "\u00e5\u0131\u0133": 13914, "vlan": 13915, "\u0120hotel": 13916, "\u0120fingers": 13917, "\u0120\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 13918, "\u0120incorrect": 13919, "\u0120clusters": 13920, "\u0120voltage": 13921, "\u0120destroyed": 13922, "TZ": 13923, "vila": 13924, "\u0120fuck": 13925, "\u0120honest": 13926, "\u0120TR": 13927, "cker": 13928, "\u0120planned": 13929, "\u0120adult": 13930, "\u0120abuse": 13931, "\u0120**$": 13932, "dense": 13933, "rell": 13934, "styles": 13935, "\u0120profit": 13936, "ensors": 13937, "IBUT": 13938, "\u0120Senate": 13939, "horizontalLayout": 13940, "}=": 13941, "\u00eb\u012c": 13942, "\u0120migration": 13943, "\u0120composition": 13944, "anny": 13945, "subset": 13946, "...,": 13947, "\u0120county": 13948, "\u0120alongside": 13949, "\u0120employee": 13950, "\u00e7\u0136\u00a8\u00e6\u012a\u00b7": 13951, "cin": 13952, "ders": 13953, "recur": 13954, "\u0120bold": 13955, "urlopen": 13956, "\u0120Wis": 13957, "\u0120hero": 13958, "\u0120Yet": 13959, "\u0120desktop": 13960, "syn": 13961, "trial": 13962, "\u0120vm": 13963, "\u0120voc": 13964, "\u0120proposal": 13965, "\u0120coal": 13966, "\u01201930": 13967, "Contents": 13968, ":``": 13969, "Abs": 13970, "inch": 13971, "\u0120{:": 13972, "\u0120atmosph": 13973, "\u0120unexpected": 13974, "Did": 13975, "\u0120\u00e2\u0122\u00a2": 13976, "azure": 13977, "transfer": 13978, "\u0120launched": 13979, "\u0120cruc": 13980, "chrom": 13981, "chant": 13982, "moves": 13983, "regs": 13984, "\u00c3\u00a7\u00c3\u00b5es": 13985, "\u0120professor": 13986, "\u0120vehicles": 13987, "\u0120IMPLIED": 13988, "Ct": 13989, "\u0120blo": 13990, "ushing": 13991, "\u00c3\u00a4r": 13992, "\u0120closely": 13993, "(\",": 13994, "225": 13995, "\u0120tv": 13996, "ivid": 13997, "\u0120correlation": 13998, "\u00e6\u00b5\u012d": 13999, "During": 14000, "Final": 14001, "hdf": 14002, "sz": 14003, "atoms": 14004, "\u0120waves": 14005, "\u0120mile": 14006, "achuset": 14007, "\u0120intensity": 14008, "\u0120lowest": 14009, "\u00d0\u00ba\u00d0\u00b0": 14010, "\u0120recognition": 14011, "nex": 14012, "sil": 14013, "determin": 14014, "\u0120Thread": 14015, "\u0120refused": 14016, "leneck": 14017, "ipedia": 14018, "\u0120trib": 14019, "\u0120instruction": 14020, "\u0120mp": 14021, "Information": 14022, "\u0120Thursday": 14023, "\u0120StringIO": 14024, "\u0120Medic": 14025, "\u0120soul": 14026, "\u0120recommended": 14027, "bridge": 14028, "mAh": 14029, "\u0120revolution": 14030, "\u0120plastic": 14031, "\u0120clip": 14032, "375": 14033, "Cut": 14034, "Hit": 14035, "\u0120pressed": 14036, "\u0120gent": 14037, "\u0120Mil": 14038, "====================": 14039, "pipe": 14040, "\u0120moments": 14041, "PRESS": 14042, "Cookie": 14043, "Site": 14044, "km": 14045, "routine": 14046, "\u0120Ren": 14047, "\u01201960": 14048, "Unicode": 14049, "staticfiles": 14050, "\u0120technical": 14051, "\u0120Mexico": 14052, "achusetts": 14053, "gel": 14054, "cretion": 14055, "colour": 14056, "APPL": 14057, "}\\(": 14058, "\u0120rendered": 14059, "Assert": 14060, "\u0120titles": 14061, "\u0120rooms": 14062, "olds": 14063, "atern": 14064, "ANCE": 14065, "gorithms": 14066, "Accuracy": 14067, "\u0120neighbors": 14068, "132": 14069, "Press": 14070, "\u0120hate": 14071, "\u00e2\u0122\u013a": 14072, "\u0120soil": 14073, "224": 14074, "Basic": 14075, "\u00d0\u00be\u00d0\u00b3": 14076, "\u0120twisted": 14077, "\u0120snap": 14078, "\u0120Regiment": 14079, "\u0120constructed": 14080, "\u0120relationships": 14081, "\u0120Director": 14082, "Actions": 14083, "ktop": 14084, "thresh": 14085, "rightarrow": 14086, "387": 14087, "\u0120Andrew": 14088, "\u0120\u00c3\u00bc": 14089, "\u0120authorities": 14090, "IDDLE": 14091, "Imp": 14092, "\u0120proved": 14093, "\u0120HO": 14094, "\u0120Store": 14095, "stein": 14096, "\u0120calculation": 14097, "\u00e8\u0129\u00aa": 14098, "LM": 14099, "gments": 14100, "\u0120formal": 14101, "\u0120directories": 14102, "\u0120sentences": 14103, "PLAY": 14104, "\u0120improvement": 14105, "\u0120embedding": 14106, "folio": 14107, "Most": 14108, "jd": 14109, "\u0120vessel": 14110, "\u0120[**": 14111, "ometric": 14112, "compan": 14113, "corr": 14114, "senger": 14115, "\u0120dependent": 14116, "mia": 14117, "ashes": 14118, "struments": 14119, "Groups": 14120, "Popen": 14121, "Tw": 14122, "gold": 14123, "\u0120ec": 14124, "\u0120translate": 14125, "Cent": 14126, "\u0120DataFrame": 14127, "\u00e2\u00ac\u013d\u00e2\u00ac\u013d": 14128, "iscal": 14129, "\u0120PIL": 14130, "subscription": 14131, "Selected": 14132, "ietf": 14133, "uplicates": 14134, "\u0120delivered": 14135, "\u0120excellent": 14136, "Mass": 14137, "ourier": 14138, "urations": 14139, "icted": 14140, "\u0120resulted": 14141, "ozilla": 14142, "Db": 14143, "tg": 14144, "sea": 14145, "\u0120infra": 14146, "idf": 14147, "\u0120Pa": 14148, "rains": 14149, "prior": 14150, "\u0120Orig": 14151, "pkl": 14152, "\u0120feelings": 14153, "\u0120Mean": 14154, "0000000000000000": 14155, "FB": 14156, "elve": 14157, "\u0120hung": 14158, "\u0120definitely": 14159, "\u0120hunt": 14160, "\u0120Op": 14161, "\u0120apartment": 14162, "\u0120interactions": 14163, "\u0120acting": 14164, "Phil": 14165, "\u0120potentially": 14166, "Dat": 14167, "\u00eb\u00a5": 14168, "\u0120torn": 14169, "listen": 14170, "\u00e3\u0125\u00b3": 14171, "\u0120winner": 14172, "Backend": 14173, "\u00e4\u00bf\u00a1\u00e6\u0123\u00af": 14174, "Tk": 14175, "heel": 14176, "irl": 14177, "getcwd": 14178, "\u0120Ram": 14179, "017": 14180, "ceding": 14181, "\u0120ourselves": 14182, "\u0120decade": 14183, "\u0120committee": 14184, "\u0120Wednesday": 14185, "hus": 14186, "wart": 14187, "\u012a\u013a": 14188, "\u0120infer": 14189, "\u0120reversed": 14190, "\u0120LET": 14191, "ostic": 14192, "\u0120Trust": 14193, "Split": 14194, "asset": 14195, "ophy": 14196, "\u0120muscle": 14197, "\u0120Italy": 14198, "xies": 14199, "addle": 14200, "\u0120argued": 14201, "Console": 14202, "([(": 14203, "303": 14204, "\u00c3\u00a9n": 14205, "prising": 14206, "\u0120docs": 14207, "\u0120ports": 14208, "generated": 14209, "\u00e5\u0127\u0125": 14210, "\u0120animation": 14211, "Pen": 14212, "serving": 14213, "\u0120als": 14214, "\u0120resident": 14215, "\u0120loader": 14216, "ANY": 14217, "overline": 14218, "\u0120filenames": 14219, "Phys": 14220, "Details": 14221, "\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100\u0100": 14222, "mobile": 14223, "\u00e8\u0125\u00bd": 14224, "\u0120CPU": 14225, "\u012071": 14226, "\u012098": 14227, "\u00e4\u00ba\u0128": 14228, "\u0120scrapy": 14229, "\u0120experiences": 14230, "\u0120millions": 14231, "\u0120Middle": 14232, "\u0120{{": 14233, "\u0120seeking": 14234, "\u0120quantum": 14235, "\u0120doub": 14236, "\u0120JavaScript": 14237, "\u0120Catholic": 14238, "\u0120hal": 14239, "\u0120hack": 14240, "\u0120Foot": 14241, "scen": 14242, "\u0120Confed": 14243, "\u0120trigram": 14244, ")\"\"\"": 14245, "\u0120houses": 14246, "definition": 14247, "shots": 14248, "\u0120upgrade": 14249, "\u0120entities": 14250, "\u0120drift": 14251, "\u0120grown": 14252, "\u0120employed": 14253, "\u0120Edward": 14254, "\u0120settlement": 14255, "\u0120strugg": 14256, "Cancel": 14257, "bur": 14258, "\u0120tort": 14259, "chdir": 14260, "\u0120whis": 14261, "\u0120HIV": 14262, "\u01201991": 14263, "2002": 14264, "Signal": 14265, "\u0120Multi": 14266, "ultural": 14267, "121": 14268, "ASH": 14269, "\u0120steel": 14270, "PREFIX": 14271, "Expand": 14272, "\u0120petition": 14273, "ZX": 14274, "rine": 14275, "entropy": 14276, "\u0120Women": 14277, "\u0120Represent": 14278, "suite": 14279, "Library": 14280, "PG": 14281, "\u0120Pay": 14282, "\u0120EN": 14283, "ampion": 14284, "\u0120diet": 14285, "Factor": 14286, "\u0120Major": 14287, "Children": 14288, "\u0120belongs": 14289, "\u0120IndexError": 14290, "\u0120surprise": 14291, "\u00e5\u012a\u0139\u00e8\u00a1\u00a8": 14292, "'\\\\": 14293, "511": 14294, "kill": 14295, "\u00e8\u00b5": 14296, "itan": 14297, "serves": 14298, "\u0120prospect": 14299, "\u0120tries": 14300, "opes": 14301, "\u0120minimal": 14302, "ordered": 14303, "\u00d0\u00b5\u00d0\u00b4": 14304, "msgid": 14305, "\u0120cooker": 14306, "''''''''": 14307, "Fac": 14308, "Iso": 14309, "cpp": 14310, "iga": 14311, "odium": 14312, "\u0120rising": 14313, "\u0120compound": 14314, "\u0120Consort": 14315, "\u0120carrying": 14316, "\u0120writers": 14317, "\u0120guilty": 14318, "\u0120carefully": 14319, "Prep": 14320, "\u0120tact": 14321, "\u0120tank": 14322, "\u0120cub": 14323, "\u0120ssl": 14324, "\u0120transmission": 14325, "\u0120edition": 14326, "\u0120promise": 14327, "Background": 14328, "Omega": 14329, "Yeah": 14330, "oon": 14331, "\u0120puzz": 14332, "verted": 14333, "\u0120RNA": 14334, "ORM": 14335, "\u0120principle": 14336, "\u0120dogs": 14337, "spe": 14338, "ionError": 14339, "amine": 14340, "Running": 14341, "\u0120Scot": 14342, "\u0120asyncio": 14343, "courses": 14344, "Another": 14345, "Images": 14346, "\u0120CR": 14347, "\u010a\u010a\u010a\u0120": 14348, "\u0120simpl": 14349, "Notes": 14350, "\u0120modes": 14351, "tected": 14352, "\u0120analyses": 14353, "\u0120immediate": 14354, "\u00e7\u00ac\u00ac": 14355, "!\\": 14356, "FD": 14357, "Sizer": 14358, "\u0120resid": 14359, "minus": 14360, "failure": 14361, "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~": 14362, "/**": 14363, ">%": 14364, "bzr": 14365, "rin": 14366, "restrict": 14367, "\u0120recovery": 14368, "\u0120Pak": 14369, "\u0120fluid": 14370, "{}'.": 14371, "\u0120effectively": 14372, "\u0120restaurant": 14373, "radio": 14374, "\u0120computed": 14375, "\u00e4\u00be\u012d": 14376, "\u0120controvers": 14377, "DER": 14378, "sound": 14379, "\u0120aircraft": 14380, "almost": 14381, "rove": 14382, "\u0120invent": 14383, "oton": 14384, "irk": 14385, "imm": 14386, "too": 14387, "207": 14388, "iano": 14389, "\u0120crew": 14390, "156": 14391, "Exists": 14392, "\u0120operators": 14393, "\u0120projection": 14394, "\u0120commonly": 14395, "\u0120bath": 14396, "\u0120intra": 14397, "\u00e3\u0123\u00aa": 14398, "\u0120Steve": 14399, "\u0120losses": 14400, "\u0120analyzed": 14401, "\u0120medicine": 14402, "\u0120DI": 14403, "oku": 14404, "\u0120disput": 14405, "\u0120peer": 14406, "\u0120FLAGS": 14407, "]',": 14408, "unior": 14409, "\u0120Rom": 14410, "CMD": 14411, "\u0120Palestin": 14412, ":{": 14413, "eur": 14414, "inda": 14415, "1999": 14416, "iii": 14417, "cdots": 14418, "\u0120OrderedDict": 14419, "330820": 14420, "Pass": 14421, "tweet": 14422, "icient": 14423, "\u0120Ty": 14424, "endment": 14425, "made": 14426, "interpre": 14427, "ushButton": 14428, "\u0120delimiter": 14429, "\u0120closing": 14430, "\u0120killing": 14431, "\u0120emergency": 14432, "\u0120guns": 14433, "allet": 14434, "strptime": 14435, "aret": 14436, "ibilities": 14437, "manual": 14438, "\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd": 14439, "Almost": 14440, "\u0120constructor": 14441, "About": 14442, "\u0120constraints": 14443, "Bel": 14444, "utor": 14445, "agues": 14446, "\u0120SU": 14447, "\u00e4\u00ba\u00ba": 14448, "\u0120Article": 14449, "Pi": 14450, "deps": 14451, "\u0120isolated": 14452, "ertainment": 14453, "\u0120android": 14454, "\u0120conclude": 14455, "__))": 14456, "ulty": 14457, "\u0120submitted": 14458, "\u0120encoder": 14459, "ominator": 14460, "\u0120hashlib": 14461, "\u00eb\u00a1\u013e": 14462, "\u0120Tour": 14463, "\u0120PL": 14464, "keywords": 14465, "\u012078": 14466, "\u0120Review": 14467, "pended": 14468, "CLI": 14469, "\u0120feedback": 14470, "\u0120LIMITED": 14471, ",--": 14472, "Hash": 14473, "vx": 14474, "\u00c5\u0141": 14475, "\u0120crop": 14476, "\u0120bomb": 14477, "\u0120initi": 14478, "\u0120Counter": 14479, "\u00e9\u0122\u013c": 14480, "401": 14481, "\u0120gdal": 14482, "\u01201989": 14483, "PropertyTypeSub": 14484, "\u0120practical": 14485, "\u0120legisl": 14486, "?,": 14487, "restore": 14488, "\u0120unus": 14489, "Progress": 14490, "\u0120Plaintiff": 14491, "WA": 14492, "lbl": 14493, "roc": 14494, "urllib": 14495, "construct": 14496, "\u0120Light": 14497, "\u0120Chapter": 14498, "\u0120regression": 14499, "skin": 14500, "\u0120grass": 14501, "\u0120significance": 14502, "windows": 14503, "\u0120captured": 14504, "\u00e2\u0137\u0132\u00e2\u0137\u0132\u00e2\u0137\u0132\u00e2\u0137\u0132": 14505, "QB": 14506, "aron": 14507, "\u0120mc": 14508, "\u0120ls": 14509, "\u0120BC": 14510, "\u0120Greg": 14511, "\u0120xbmc": 14512, "\u0120insurance": 14513, "\u0120ingredients": 14514, "Because": 14515, "[[": 14516, "dose": 14517, "nom": 14518, "}]": 14519, "heet": 14520, "unist": 14521, "\u0120DIS": 14522, "1234": 14523, "umni": 14524, "\u0120Plot": 14525, "Dictionary": 14526, "\u0120vertices": 14527, "\u0120western": 14528, "\u0120Initialize": 14529, "\u0120explicitly": 14530, "Rot": 14531, "bour": 14532, "lam": 14533, "113": 14534, "\u0120refers": 14535, "\u00d0\u00bd\u00d0\u00b0": 14536, "\u0120happening": 14537, "dark": 14538, "icol": 14539, "\u0120Way": 14540, "\u010a\u0109\u0109\u010a": 14541, "\u0120temple": 14542, "\u0120iterator": 14543, "\u0120surrounding": 14544, "utdown": 14545, "=\"/": 14546, "isement": 14547, "logo": 14548, "inesses": 14549, "CHECK": 14550, "Although": 14551, "Arch": 14552, "\u0120\u00c3\u00a4": 14553, "\u0120Content": 14554, "approx": 14555, "neighbors": 14556, "\u0120efficiency": 14557, "hole": 14558, "\u0120Profile": 14559, "HEIGHT": 14560, "\u0120assessment": 14561, "\u0120LETTER": 14562, "Fake": 14563, "gian": 14564, "\u00bd\u00e6\u0137\u00b0": 14565, "\u0120cod": 14566, "\u0120UI": 14567, "forum": 14568, "Permission": 14569, "imedia": 14570, "\u0120Reserved": 14571, "&&": 14572, "Sol": 14573, "TOP": 14574, "adium": 14575, "operations": 14576, "\u00e5\u0132\u00a6": 14577, "\u0120mountain": 14578, "\u0120suffered": 14579, "\u0120sought": 14580, "ubble": 14581, "\u0120/=": 14582, "\u0120urls": 14583, "CREATE": 14584, "\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 14585, "\u0120leadership": 14586, "journal": 14587, "mongo": 14588, "inp": 14589, "ques": 14590, "arios": 14591, "vertices": 14592, "xygen": 14593, "\u0120involving": 14594, "\u00c3\u00a8s": 14595, "\u0120Otherwise": 14596, ".),": 14597, "youtube": 14598, "itches": 14599, "\u0120saving": 14600, "\u0120wet": 14601, "\u0120onion": 14602, "///": 14603, "CLASS": 14604, "################################################################################": 14605, "\u0120volumes": 14606, "Zero": 14607, "\u0120\u010a\u010a": 14608, "\u0120wins": 14609, "\u0120dash": 14610, "\u0120Access": 14611, "\u0120Northern": 14612, "\u0120Draw": 14613, "\u0120internet": 14614, "swap": 14615, "ships": 14616, "\u0120victim": 14617, "\u00e2\u013b": 14618, "\u0120PC": 14619, "Theta": 14620, "moving": 14621, "\u0120subnet": 14622, "notification": 14623, "MMMM": 14624, "\u0120amplitude": 14625, ")|": 14626, "Err": 14627, "alert": 14628, "\u0120bird": 14629, "\"\"\",": 14630, "\u0120Der": 14631, "\u0120DES": 14632, "\u0120enzy": 14633, "\u0120composed": 14634, "configs": 14635, "\u0120glu": 14636, "Encoder": 14637, "ZONE": 14638, "cht": 14639, "\u0120divide": 14640, "\u0120biological": 14641, "\u00e4\u00ba\u0130": 14642, "=-=-": 14643, "ALLOWED": 14644, "Ui": 14645, "aler": 14646, "\u0120pipe": 14647, "\u0120integers": 14648, "VEL": 14649, "mor": 14650, "\u00e5\u013b": 14651, "ulse": 14652, "\u0120stead": 14653, "\u0120conscious": 14654, "\u01201993": 14655, "0002": 14656, "\u0120divis": 14657, "\u00e6\u013e\u00ba": 14658, "\u0120amounts": 14659, "\u0120\"/\"": 14660, "\u0120Without": 14661, "SOURCE": 14662, "\u0120dropout": 14663, "\u0120Auto": 14664, "\u0120OSError": 14665, "QLabel": 14666, "draft": 14667, "\u00e7\u00a9": 14668, "leting": 14669, "\u0120pdb": 14670, "\u0120sched": 14671, "\u0120hang": 14672, "\u0120gc": 14673, "00400": 14674, "ometer": 14675, "expl": 14676, "attice": 14677, "235": 14678, "\u0120Massachusetts": 14679, "(&": 14680, "cers": 14681, "native": 14682, "zi": 14683, "\u0120\u00e4\u00b8\u0143": 14684, "secs": 14685, "rocess": 14686, "isons": 14687, "\u0120Stan": 14688, "\u0120manually": 14689, "\u0120helping": 14690, "\u0120reporting": 14691, "\u0120Boolean": 14692, "Summary": 14693, "\u0120buried": 14694, "\u0120streets": 14695, "coordinates": 14696, "Angle": 14697, "NB": 14698, "\u0120tp": 14699, "\u0120plug": 14700, "])]": 14701, "\u0120clothes": 14702, "ICAL": 14703, "\u0120regional": 14704, "\u0120Constitution": 14705, "\u00e7\u0136\u0141": 14706, "\u0120cb": 14707, "leave": 14708, "\u0120bounds": 14709, "\u0120flour": 14710, "AUT": 14711, "zing": 14712, "\u0120banks": 14713, "\u0120protot": 14714, "encia": 14715, "AAA": 14716, "limits": 14717, "\u0120Corporation": 14718, ".>>>": 15461, "\u0120producing": 15462, "QUE": 15463, "\u00e4\u00bb\u00a3": 15464, "\u0120frequencies": 15465, "\u0120investigate": 15466, "\u0120Records": 15467, "\u0120diagnosis": 15468, "WORK": 15469, "adelphia": 15470, "GO": 15471, "\u0120soc": 15472, "\u0120opposition": 15473, "MESS": 15474, "\u0120SET": 15475, "\u0120assuming": 15476, "lessly": 15477, "\u0120MAV": 15478, "\u00e5\u0129\u00bd\u00e6\u0137\u00b0": 15479, "\u0120teaching": 15480, "\u0120tournament": 15481, "\u0120adopted": 15482, "erk": 15483, "\u0120Taylor": 15484, "\u0120Comb": 15485, "\u0120Give": 15486, "\u0120Kenn": 15487, "formatter": 15488, "\u010d\u010a\u010d\u010a\u0109": 15489, "\u0120paying": 15490, "inned": 15491, "writerow": 15492, "\u0120Comiss": 15493, "\u0120bulk": 15494, "likely": 15495, "bury": 15496, "\u0120Walk": 15497, "\u0120ET": 15498, "\u0120404": 15499, "\u0120teeth": 15500, "\u0120incred": 15501, "\u0120cookies": 15502, "\u0120examined": 15503, "\u0120interpretation": 15504, "\u00e6\u013d\u00b4": 15505, "\u0120Southern": 15506, "\u0120tu": 15507, "\u0120northern": 15508, "\u0120adap": 15509, "\u0120applies": 15510, "\u0120mechanisms": 15511, "\u0120sessions": 15512, "\u0120POST": 15513, "Prefix": 15514, "\u0120Saf": 15515, "\u0120videos": 15516, "addon": 15517, "sprite": 15518, "297": 15519, "dependency": 15520, "\u0120recognize": 15521, "\u0120plasma": 15522, "IFT": 15523, "\u0120tub": 15524, "\u012097": 15525, "\u00e3\u0123\u00be": 15526, "\u0120estimates": 15527, "\u0120ham": 15528, "\u0120subclass": 15529, "\u0120picking": 15530, "\u00e9\u013b\u00a4": 15531, "\u0120arrested": 15532, "kernwin": 15533, "eme": 15534, "\u0120\u00e5\u012a": 15535, "checked": 15536, "\u0120increment": 15537, "\u0120grey": 15538, "\u0120adjacent": 15539, "Jets": 15540, "Master": 15541, "\u0120exe": 15542, "backward": 15543, "CHAR": 15544, "Unable": 15545, "\u0120Temple": 15546, ":`.": 15547, "\u0120Queue": 15548, "Green": 15549, "\u0120deput": 15550, "\u0120Send": 15551, "\u0120genetic": 15552, ".'''": 15553, "rees": 15554, "\u0120IV": 15555, "\u0120Mah": 15556, "ailing": 15557, "116": 15558, "matory": 15559, "\u0120classic": 15560, "\u0120providers": 15561, "\u0120producer": 15562, "operative": 15563, "\u0120Box": 15564, "\u0120totally": 15565, ")$,": 15566, "Microsoft": 15567, "father": 15568, "\u0120Si": 15569, "**)": 15570, "\u0120Games": 15571, "\u0120360": 15572, "\u0120plots": 15573, "\u0120computing": 15574, "\u0120Medical": 15575, "binding": 15576, "+',": 15577, "birth": 15578, "\u0120Bas": 15579, "\u0120lect": 15580, "\u012079": 15581, "generation": 15582, "Sn": 15583, "YE": 15584, "\u0120Has": 15585, "ellite": 15586, "\u0120Ther": 15587, "lename": 15588, "\u01201988": 15589, "Services": 15590, "\u0120charset": 15591, "ELL": 15592, "affe": 15593, "annotation": 15594, "written": 15595, "\u0120intelligence": 15596, "MIDDLEWARE": 15597, "\u0120Wild": 15598, "\u0120rol": 15599, "\u0120argue": 15600, "\u0120flux": 15601, "\u0120immune": 15602, "\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd": 15603, "Encoding": 15604, "\u0120Colorado": 15605, "\u0120memo": 15606, "\u0120contribution": 15607, "117": 15608, "148": 15609, "\u0120summar": 15610, "\u0120featured": 15611, "databases": 15612, "aturally": 15613, "\u0120institutions": 15614, "\u0120corporate": 15615, "PromptReco": 15616, "Btn": 15617, "Pixmap": 15618, "]\")": 15619, "\u0120UP": 15620, "206": 15621, "blast": 15622, "\u0120transparent": 15623, "405": 15624, "URN": 15625, "\u010d\u010a\u010d\u010a\u010d\u010a\u010d\u010a": 15626, "\u0120Keep": 15627, "effective": 15628, "\u0120inherit": 15629, "=\",": 15630, "Img": 15631, "fw": 15632, "\u0120Business": 15633, "SED": 15634, "138": 15635, "aneously": 15636, "\u0120...)": 15637, "\u0120scholarship": 15638, "\u00e8\u00bd\u00ac": 15639, "BACKEND": 15640, "\u0120ticket": 15641, "\u0120amp": 15642, "\u0120lunch": 15643, "\u0120Soc": 15644, "\u0120Energy": 15645, "ibration": 15646, "ARABIC": 15647, "IDE": 15648, "640": 15649, "ockey": 15650, "\u0120breaks": 15651, "ruption": 15652, "\u0120Comment": 15653, "\u00e4\u00bf\u013f": 15654, "VPNt": 15655, "scheduler": 15656, "squeeze": 15657, "yard": 15658, "angers": 15659, "\u0120resume": 15660, "302": 15661, "\u0120receiver": 15662, "\u0120dirs": 15663, "\u010a\u0120\u010a\u0120\u010a\u0120\u010a\u0120": 15664, "TEMPLATE": 15665, "cx": 15666, "gas": 15667, "gather": 15668, "\u0120oh": 15669, "\u010a\u010a\u010a\u010a\u0120\u0120\u0120": 15670, "athy": 15671, "\u0120props": 15672, "\u0120suppose": 15673, "temperature": 15674, "\u0120experts": 15675, "solve": 15676, "\u00ea\u00b0\u0122": 15677, "\u0120\".\"": 15678, "\u0120IT": 15679, "\u0120cha": 15680, "RET": 15681, "\u0120overwrite": 15682, "\u0120facilit": 15683, "oning": 15684, "\u0120duplicate": 15685, "imo": 15686, "\u0120asset": 15687, "\u0120Ep": 15688, "187": 15689, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 15690, "species": 15691, "\u0120Manager": 15692, "\u0120Swed": 15693, "\u0120essentially": 15694, "DEVICE": 15695, "CY": 15696, "zw": 15697, "again": 15698, "\u0120Next": 15699, "\u0120LE": 15700, "\u0120valu": 15701, "\u01201950": 15702, "\u0120glad": 15703, "+\"\\": 15704, "\u0120directions": 15705, "ranges": 15706, "gettext": 15707, "\u0120contributions": 15708, "OTE": 15709, "\u0120retry": 15710, "\u0120variation": 15711, "\u0120Parliament": 15712, "sigmoid": 15713, "WINDO": 15714, ">\")": 15715, "?\\": 15716, "ZW": 15717, "\u0120127": 15718, "ango": 15719, "ippet": 15720, "ENS": 15721, "NotExist": 15722, "\u0120Tele": 15723, "\u0120talked": 15724, "patient": 15725, "INSTALLED": 15726, "Trigger": 15727, "\u0120innov": 15728, "\u0120Fri": 15729, "\u0120Was": 15730, "dimensions": 15731, "\u0120removing": 15732, "\u0120numerical": 15733, "xlim": 15734, "\u0120../": 15735, "\u0120tied": 15736, "\u0120wake": 15737, "\u0120mk": 15738, "\u0120Oxford": 15739, "\u0120quot": 15740, "\u0120queries": 15741, "\u0120relat": 15742, "\u0120advoc": 15743, "\u0120principles": 15744, "\u0120slope": 15745, "assets": 15746, "\u0120dass": 15747, "ett": 15748, "\u01201987": 15749, "errupt": 15750, "fficients": 15751, "(?:": 15752, "\u0120announce": 15753, "EVENT": 15754, "\u0120purchased": 15755, "+')": 15756, "\u0120####": 15757, "deli": 15758, "\u0120bom": 15759, "\u0120Ilya": 15760, ")/(-": 15761, "\u00e5\u0132\u012e": 15762, "\u0120dealing": 15763, "\u0120demonstrate": 15764, "\u0120ultimately": 15765, "xxxxxxxx": 15766, ".](": 15767, "\u0120sink": 15768, "\u0120sparse": 15769, "\u0120vor": 15770, "\u0120rho": 15771, "\u0120paragraph": 15772, "\u0120Still": 15773, "tracker": 15774, "\u0120molecules": 15775, "\u0120LIABILITY": 15776, "\u0120proportion": 15777, "mus": 15778, "ticks": 15779, "\u00d9\u0126": 15780, "\u0120\u00d1\u0129": 15781, "\u0120Target": 15782, "\u0120approval": 15783, "\u0120radical": 15784, "\u0120magnitude": 15785, "RM": 15786, "fan": 15787, "\u0120ci": 15788, "\u0120gonna": 15789, "Three": 15790, "\u0120passion": 15791, "mony": 15792, "\u0120practices": 15793, "\u0120procedures": 15794, "\u0120dynamics": 15795, "\u0120ss": 15796, "\u0120Mom": 15797, "**(": 15798, "ogg": 15799, "\u0120Ken": 15800, "\u0120heavily": 15801, "\u0120Jackson": 15802, "\u0120taught": 15803, "\u0120parsing": 15804, "\u0120helpful": 15805, "\u0120Export": 15806, "/(?": 15807, "=(\"": 15808, "Ep": 15809, "FG": 15810, "Family": 15811, "UUID": 15812, "\u0120waste": 15813, "\u0120react": 15814, "peg": 15815, "thumbnail": 15816, "formula": 15817, "\u01201986": 15818, "\u0120whenever": 15819, "\u012083": 15820, "theless": 15821, "\u0120impress": 15822, "\u0120modification": 15823, "frak": 15824, "Adapter": 15825, "Software": 15826, "\u0120perfectly": 15827, "\u0120amazing": 15828, "Dif": 15829, "reload": 15830, "icide": 15831, "iece": 15832, "aky": 15833, "velope": 15834, "nsure": 15835, "\u0120interfaces": 15836, "LOC": 15837, "\u00e3\u0124\u00b9": 15838, "\u0120brings": 15839, "\u0120potatoes": 15840, "\u0120engineering": 15841, "\u0120meetings": 15842, "\u0120macro": 15843, "BUTTON": 15844, "Gra": 15845, "RUN": 15846, "orse": 15847, "\u0120anno": 15848, "\u0120machines": 15849, "\u0120disappoint": 15850, "started": 15851, "\u0120tracking": 15852, "\u0120selling": 15853, "jelmer": 15854, "\u0120recover": 15855, "ulates": 15856, "ffi": 15857, "163": 15858, "ACH": 15859, "Colour": 15860, "\u0120esc": 15861, "burgh": 15862, "Month": 15863, "clusions": 15864, "\u0120Radio": 15865, "\u0120crucial": 15866, "tions": 15867, "zu": 15868, "\u0120'&": 15869, "\u0120Today": 15870, "\u0120stability": 15871, "tered": 15872, "excel": 15873, "\u0120intermediate": 15874, "\u0120volunte": 15875, "\u0120albums": 15876, "\u0120rapidly": 15877, "iti": 15878, "\u0120stuck": 15879, "\u0120COL": 15880, "\u0120Math": 15881, "\u0120Basic": 15882, "227": 15883, "symbols": 15884, "\u0120libraries": 15885, "Once": 15886, "\u0120driven": 15887, "\u0120Appe": 15888, "////////////////": 15889, "rocessing": 15890, "\u0120sbox": 15891, "oresc": 15892, "\u0120doors": 15893, "boy": 15894, "\u012088": 15895, "\u0120markets": 15896, "\u0120evident": 15897, "\u0120Eastern": 15898, "\u0120enhance": 15899, "Sound": 15900, "_=": 15901, "gtk": 15902, "kel": 15903, "oose": 15904, "\u00d0\u013a": 15905, "\u0120fasc": 15906, "\u0120liver": 15907, "abeth": 15908, "\u0120Psych": 15909, "\u0120Moscow": 15910, "('{": 15911, "updates": 15912, "\u0120disp": 15913, "recision": 15914, "ova": 15915, "\u0120keeps": 15916, "\u0120wonderful": 15917, "Makes": 15918, "ez": 15919, "\u0120\u00cf": 15920, "\u0120wounded": 15921, "\u0120battery": 15922, "\u0120CHE": 15923, "StringIO": 15924, "\u0120horses": 15925, "\u0120corresponds": 15926, "\u0120installation": 15927, "Blue": 15928, "Processor": 15929, "GPIO": 15930, "jan": 15931, "\u0120reput": 15932, "\u0120epsilon": 15933, "aga": 15934, "\u0120Mike": 15935, "\u0120EVENT": 15936, "\u0120intervals": 15937, "153": 15938, "rawl": 15939, "runs": 15940, "ramid": 15941, "\u0120Despite": 15942, "decorators": 15943, "\u00e7\u00b4\u0142": 15944, "Impl": 15945, "ruit": 15946, "uity": 15947, "\u0120concrete": 15948, "\u0120yesterday": 15949, "\u0120Normal": 15950, "\u012086": 15951, "\u012089": 15952, "\u012092": 15953, "games": 15954, "\u0120Allen": 15955, "\u0120increasingly": 15956, "\u0120suffering": 15957, "vik": 15958, "\u00e8\u00b0": 15959, "\u00e9\u013e": 15960, "()}": 15961, "\u0120CL": 15962, "\u0120Master": 15963, "truth": 15964, "149": 15965, "ENTRY": 15966, "tocols": 15967, "\u0120Contin": 15968, "\u0120engaged": 15969, "cion": 15970, "vendor": 15971, "stick": 15972, "\u0120Sphinx": 15973, "interest": 15974, "quick": 15975, "\u0120ERR": 15976, "colored": 15977, "\u0120workflow": 15978, "amble": 15979, "\u0120est\u00c3\u00a1": 15980, "\u0120occas": 15981, "Feed": 15982, "\u0120\u00d0\u00bd\u00d0\u00b0": 15983, "wav": 15984, "alette": 15985, "deserialize": 15986, "\u0120fi": 15987, "ammatory": 15988, "\u0120[{'": 15989, "scaled": 15990, "auses": 15991, "\u0120serves": 15992, "\u0120possession": 15993, "\u0120terrible": 15994, "FLAG": 15995, "lm": 15996, "\u00d1\u012b": 15997, "\u0120reviews": 15998, "\u0120emit": 15999, "\u0120egg": 16000, "\u0120Area": 16001, "\u0120Kult": 16002, "\u0120URLs": 16003, "\u0120electronic": 16004, "hom": 16005, "\u010d\u010a\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109": 16006, "dead": 16007, "\u012002": 16008, "\u0120unsigned": 16009, "403": 16010, "\u0120configure": 16011, "``,": 16012, "alignment": 16013, "\u00c3\u00aame": 16014, "Lat": 16015, "nome": 16016, "\u0120cand": 16017, "\u0120council": 16018, "ceeds": 16019, "gradu": 16020, "\u0120Anderson": 16021, "\u0120seriously": 16022, "subplots": 16023, "Surface": 16024, "AuthenticationMiddleware": 16025, "\u0120Chamberlain": 16026, ".\u00e2\u0122\u013b": 16027, "\u0120dance": 16028, "ulous": 16029, "\u0120Row": 16030, "\u0120Raises": 16031, "\u0120Live": 16032, "\u0120Email": 16033, "\u0120intervention": 16034, "Prob": 16035, "copyright": 16036, "TERN": 16037, "\u0120Query": 16038, "\u0120equally": 16039, "Foo": 16040, "qdm": 16041, "strength": 16042, "\u0120pending": 16043, "\u0120dys": 16044, "estyle": 16045, "\u0120Ok": 16046, "202": 16047, "\"]))": 16048, "\u00e2\u0138\u0122": 16049, "\u0120searching": 16050, "\u0120Appro": 16051, "rupted": 16052, "Google": 16053, "\u00ec\u0139\u0132": 16054, "\u0120academic": 16055, "uis": 16056, "\u0120tender": 16057, "\u0120aza": 16058, "\u0120mime": 16059, "asse": 16060, "omed": 16061, "oker": 16062, "\u0120texts": 16063, "PRP": 16064, "\u00e6\u0143\u00a3": 16065, "\u00e2\u0139\u00bc\u00ef\u00b8\u0131\u00e2\u0139\u00bc\u00ef\u00b8\u0131": 16066, "\u0120jurisdiction": 16067, "\u00c5\u00be": 16068, "\u0120Sample": 16069, "])):": 16070, "\u0120backward": 16071, "\u0120possess": 16072, "\u0120calm": 16073, "},{\"": 16074, "\u010a\u010a\u0109\u0109\u0109": 16075, "\u0120Linux": 16076, "\u0120eggs": 16077, "toggle": 16078, "\u0120sind": 16079, "\u0120wrt": 16080, "igs": 16081, "quer": 16082, "aka": 16083, "\u0120passage": 16084, "\u00d0\u00b0\u00d0\u00bb": 16085, "swig": 16086, "\u0120completion": 16087, "Templates": 16088, "\u0120compatible": 16089, "\u0120resolved": 16090, "\u0120diplo": 16091, "Fire": 16092, "Pub": 16093, "\u00e1\u00bb": 16094, "\u00ec\u012d": 16095, "verts": 16096, "\u0120Range": 16097, "\u0120chan": 16098, "fft": 16099, "\u0120valor": 16100, "\u0120moon": 16101, "159": 16102, "oucher": 16103, "Turn": 16104, "voice": 16105, "\u0120110": 16106, "setUp": 16107, "304": 16108, "137": 16109, "Cloud": 16110, "\u0120vec": 16111, "gnore": 16112, "\u0120About": 16113, "Operator": 16114, "cup": 16115, "\u0120cer": 16116, "\u0120Sher": 16117, "quot": 16118, "\u0120studio": 16119, "\u00d0\u00be\u00d0\u00b1": 16120, "Given": 16121, "density": 16122, "nv": 16123, "\u0120aqu": 16124, "\u0120mapped": 16125, "\u0120ni": 16126, "\u0120dust": 16127, "\u0120lui": 16128, "))[": 16129, "\u0120GO": 16130, "\u0120compression": 16131, "mble": 16132, "\u0120acute": 16133, "\u010d\u010a\u010d\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 16134, "RP": 16135, "\u0120ess": 16136, "pointer": 16137, "PROC": 16138, "\u0120Jersey": 16139, "537": 16140, "Idx": 16141, "Definition": 16142, "\u00e7\u00bb\u0126": 16143, "Trade": 16144, "\u0120garlic": 16145, "\u0120complicated": 16146, "\u00d1\u0128\u00d0\u00b8": 16147, "guest": 16148, "wat": 16149, "\u00f0\u013f": 16150, "\u0120ln": 16151, "\u0120appar": 16152, "ERY": 16153, "\u0120thereby": 16154, "nova": 16155, "sense": 16156, "\u0120afford": 16157, "\u0120Brook": 16158, "\u0120Nazi": 16159, "233": 16160, "tech": 16161, "getvalue": 16162, "\u0120Bell": 16163, "arts": 16164, "\u0120java": 16165, "locals": 16166, "\u0120Conference": 16167, "\u0120Alexander": 16168, "\u0120arbitrary": 16169, "LAB": 16170, "rh": 16171, "\u0120ABC": 16172, "\u0120FA": 16173, "buy": 16174, "\u0120simult": 16175, "\u0120webdriver": 16176, "Repository": 16177, "AlmostEqual": 16178, "'<": 16179, "Diff": 16180, "\u0120\u00e1\u0122": 16181, "\u0120gui": 16182, "\u0120rhs": 16183, "rites": 16184, "visual": 16185, "\u0120Fields": 16186, "\u0120Israeli": 16187, "materials": 16188, "attachment": 16189, "OFFSET": 16190, "ANNEL": 16191, "IZE": 16192, "bob": 16193, "mgr": 16194, "\u0120marg": 16195, "assed": 16196, "\u0120Position": 16197, "IDENT": 16198, "\u0120regulation": 16199, "predicted": 16200, "\u00e9\u013d\u0128": 16201, "induced": 16202, "!)": 16203, "`:": 16204, "\u0120################": 16205, "\u0120AUTH": 16206, "Health": 16207, "BoxLayout": 16208, "twitter": 16209, "fam": 16210, "pv": 16211, "\u0120ai": 16212, "dispatch": 16213, "\u00e5\u0127\u00b3": 16214, "****************************************************************": 16215, "Term": 16216, "ENGTH": 16217, "*]{}": 16218, "Average": 16219, "Course": 16220, "\u0120tough": 16221, "imread": 16222, "\u0120PY": 16223, "\u0120Pur": 16224, "\u0120Hospital": 16225, "gressive": 16226, "\u0120organized": 16227, "SERV": 16228, "apture": 16229, "\u0120extracted": 16230, "\u0120Again": 16231, "655": 16232, "\u0120tong": 16233, "athan": 16234, "\u0120Ra": 16235, "lista": 16236, "\u0120XXX": 16237, "\\\\\\\\": 16238, "\u0120confident": 16239, "\u0120psychological": 16240, "\u0120Brazil": 16241, "5000": 16242, "Ben": 16243, "SIG": 16244, "bx": 16245, "hon": 16246, "\u0120LA": 16247, "preview": 16248, "ticket": 16249, "enna": 16250, "\u0120rely": 16251, "\u0120drew": 16252, "\u0120hint": 16253, "\u0120lying": 16254, "conduct": 16255, "\u0120Question": 16256, "\u0120Asia": 16257, "\u0120Spain": 16258, "\u0120suggesting": 16259, "\u0120applying": 16260, "\u0120\u00e2\u012b": 16261, "\u0120lifetime": 16262, "DoesNotExist": 16263, "Audio": 16264, "cad": 16265, "\u00d1\u0138": 16266, "aria": 16267, "\u0120narr": 16268, "ownt": 16269, "\u0120shapes": 16270, "\u0120mood": 16271, "\u0120populations": 16272, "\u0120graphs": 16273, "\u0120facilities": 16274, "\u0120platforms": 16275, "\u0120teachers": 16276, "\u0120fet": 16277, "ented": 16278, "\u0120Ariz": 16279, "\u0120PDF": 16280, "\u0120Lat": 16281, "ureau": 16282, "\u0120Job": 16283, "\u0120intersection": 16284, "runner": 16285, "```": 16286, "Optional": 16287, "\u0120stayed": 16288, "GRE": 16289, "Pa": 16290, "\u0120cf": 16291, "\u0120fur": 16292, "\u0120bib": 16293, "\u0120loud": 16294, "\u0120Sever": 16295, "\u0120Brad": 16296, "ldp": 16297, "uleiro": 16298, "178": 16299, "\u0120operate": 16300, "\u0120Guard": 16301, ",*": 16302, "280": 16303, "Side": 16304, "Tri": 16305, "tility": 16306, "attemp": 16307, "isl": 16308, "\u0120nos": 16309, "\u0120Doug": 16310, "\u0120Invest": 16311, "REMO": 16312, "\u0120Student": 16313, "},\\": 16314, "\u0120formatted": 16315, "nonzero": 16316, "RB": 16317, "rose": 16318, "\u0120chr": 16319, "exact": 16320, "\u0120processor": 16321, "markdown": 16322, "HEAD": 16323, "\u0120patches": 16324, "Period": 16325, "\u0120PROVID": 16326, "\u0120concepts": 16327, "\u0120fifth": 16328, "\u0120Captain": 16329, "\u0120slices": 16330, "DATABASES": 16331, "iest": 16332, "\u0120ger": 16333, "agan": 16334, "unlink": 16335, "allclose": 16336, "perf": 16337, "\u0120hasn": 16338, "\u0120recur": 16339, "HAVE": 16340, "coding": 16341, "tas": 16342, "ctime": 16343, "\u0120vine": 16344, "\u0120indexes": 16345, "\u0120domains": 16346, "hooks": 16347, "VIEW": 16348, "did": 16349, "fred": 16350, "\u010d\u010d": 16351, "124": 16352, "\u0120Story": 16353, "mathfrak": 16354, "\u0120Cloud": 16355, "\u0120belief": 16356, "\u0120therap": 16357, "\u0120burning": 16358, "rer": 16359, "erated": 16360, "\u0120\"\".": 16361, "emies": 16362, "\u0120Kon": 16363, "...)": 16364, "\u0120surve": 16365, "Contains": 16366, "\u0120grab": 16367, "\u00e5\u012a\u013b": 16368, "Transport": 16369, "\u0120Display": 16370, "\u0120rejected": 16371, "Brush": 16372, "YX": 16373, "\u00e0\u00b6": 16374, "\u0120pc": 16375, "\u0120Ast": 16376, "apis": 16377, "\u0120Norm": 16378, "\u0120Fund": 16379, "Inf": 16380, "\u0120opener": 16381, "\u0120boost": 16382, "\u0120equations": 16383, "ValidationError": 16384, "feedback": 16385, "ORMAL": 16386, ":]:": 16387, "National": 16388, "sx": 16389, "):_": 16390, "\u0120beer": 16391, "\u0120compounds": 16392, "\u012087": 16393, "\u0120Android": 16394, "\u0120libvlc": 16395, "Photo": 16396, "BOX": 16397, "WRITE": 16398, "260": 16399, "\u00e9\u0137": 16400, "\u0120{:.": 16401, "making": 16402, "\u0120agric": 16403, "\u0120transferred": 16404, "\u0120captain": 16405, "normalized": 16406, "ennis": 16407, "\u0120induced": 16408, "\u00ec\u0142": 16409, "\u0120trim": 16410, "Desktop": 16411, "caption": 16412, "TCP": 16413, "Light": 16414, "Round": 16415, "bidden": 16416, "cum": 16417, "))/": 16418, "\u0120scroll": 16419, "194": 16420, "ENV": 16421, "postgres": 16422, "BEGIN": 16423, "\u0120Pacific": 16424, "GH": 16425, "wich": 16426, "\u0120CT": 16427, "ibr": 16428, "\u0120attended": 16429, "Numeric": 16430, "\u0120Struct": 16431, "sensors": 16432, "\u0120ordinary": 16433, "\u0120receptor": 16434, "\u0120dedicated": 16435, "kb": 16436, "\u0120Sn": 16437, "']}": 16438, "ocol": 16439, "Inline": 16440, "rowing": 16441, "iko": 16442, "runk": 16443, "\u0120Perform": 16444, "splitext": 16445, "\u0120innoc": 16446, "\u00eb\u00a5\u00bc": 16447, "ACTION": 16448, "Clock": 16449, "craft": 16450, "six": 16451, "ellect": 16452, "\u0120roots": 16453, "\u0120compiler": 16454, "Rece": 16455, "\u0120distribute": 16456, "\u012094": 16457, "\u0120representative": 16458, "News": 16459, "\u00e9\u0122\u012b": 16460, "\u0120drinking": 16461, "Training": 16462, "\u0120aggreg": 16463, "Movie": 16464, "PK": 16465, "\u0120ought": 16466, "\u0120deck": 16467, "omatic": 16468, "\u0120shout": 16469, "\u0120Reference": 16470, "\u0120polynomial": 16471, "bases": 16472, "\u0120surprising": 16473, "picture": 16474, "\u0120btn": 16475, "\u0120Fox": 16476, "ption": 16477, "plate": 16478, "([],": 16479, "voltage": 16480, "objs": 16481, "\u0120solar": 16482, "Tracker": 16483, "\u0120nltk": 16484, "Tune": 16485, "\u010a\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 16486, "\u0120smell": 16487, "uters": 16488, "\u0120Revolution": 16489, "\u00d0\u00b8\u00d0\u00bc": 16490, "\u0120presentation": 16491, "Advert": 16492, "\u00e6\u0125": 16493, "\u00ea\u00b3": 16494, "enti": 16495, "unes": 16496, "\u0120consequences": 16497, "uscript": 16498, "acks": 16499, "\u0120chap": 16500, "cose": 16501, "numeric": 16502, "\u0120polar": 16503, "{})": 16504, "UNK": 16505, "xxx": 16506, "\u0120opportunities": 16507, "Join": 16508, "wick": 16509, "onia": 16510, "\u0120mx": 16511, "iggs": 16512, "00300": 16513, "\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 16514, "\u0120Drop": 16515, "\u0120plugins": 16516, "\u0120consumption": 16517, "\u0120stepped": 16518, "installed": 16519, "HOSTS": 16520, "\u00e7\u012b\u0129": 16521, "SCO": 16522, "vation": 16523, "\u0120thrown": 16524, "iley": 16525, "\u0120plenty": 16526, "ponents": 16527, "\u0120registry": 16528, "Regex": 16529, "\u0120angry": 16530, "completed": 16531, "\u0120mistake": 16532, "\u0120Analysis": 16533, "625": 16534, "DICT": 16535, "Fn": 16536, "oct": 16537, "onder": 16538, "aya": 16539, "#########": 16540, "\u0120cli": 16541, "\u0120scoring": 16542, "\u0120Exp": 16543, "\u0120performing": 16544, "\u0120deviation": 16545, "Download": 16546, "\u0120awarded": 16547, "Mozilla": 16548, "bw": 16549, "bird": 16550, "arct": 16551, "\u0120bat": 16552, "opic": 16553, "Members": 16554, "\u00e9\u0129\u012f": 16555, "bial": 16556, "\u0120td": 16557, "\u0120cig": 16558, "('''": 16559, "transition": 16560, "\u0120describing": 16561, "\u0120cutting": 16562, "Environment": 16563, "DH": 16564, "\\/": 16565, "sdk": 16566, "yal": 16567, "zA": 16568, "\u0120faced": 16569, "eda": 16570, "irms": 16571, "fileName": 16572, "\u0120Sea": 16573, "\u0120basically": 16574, "ingerprint": 16575, "MINIAOD": 16576, "Bound": 16577, "Da": 16578, "cdf": 16579, "given": 16580, "\u00c5\u0124": 16581, "\u00e8\u00a8": 16582, "\u0120Sav": 16583, "\u0120IM": 16584, "constructor": 16585, "\u0120prod": 16586, "\u0120flip": 16587, "TRAN": 16588, "\u0120facing": 16589, "\u0120integral": 16590, "\u0120Korea": 16591, "\u00e6\u00b0": 16592, "\u00eb\u0142": 16593, "\u0120eating": 16594, "\u0120falls": 16595, "+-": 16596, "CLO": 16597, "FM": 16598, "kappa": 16599, "\u0120Sort": 16600, "uma": 16601, "\u0120Festival": 16602, "\u0120EU": 16603, "\u0120elle": 16604, "\u0120Third": 16605, "others": 16606, "\u00c3\u00a7a": 16607, "\u0120musical": 16608, "\u0120HttpResponseRedirect": 16609, "rwxrwx": 16610, "\u0120tolerance": 16611, "_\"+": 16612, "fish": 16613, "money": 16614, "\u00e9\u0127": 16615, "\u0120fired": 16616, "\u0120MS": 16617, "\u0120routine": 16618, "\u0120satisfied": 16619, "\u0120strategies": 16620, "\u00d7\u013b\u00d7": 16621, "\u0120beneath": 16622, "Virtual": 16623, "\u0120Jr": 16624, "ENU": 16625, "288": 16626, "ounced": 16627, "armac": 16628, "\u0120asks": 16629, "TRAIN": 16630, "\u0120\u00ec\u0140": 16631, "\u0120gateway": 16632, "\u0120whisper": 16633, "aki": 16634, "\u0120serum": 16635, "\u00e5\u00a4\u013c": 16636, "helpers": 16637, "incipal": 16638, "\u0120beside": 16639, "ILLUS": 16640, "\u0120citizen": 16641, "?\u00e2\u0122\u013f": 16642, "Bal": 16643, "Sun": 16644, "\u0120inventory": 16645, "\u0120dont": 16646, "\u0120Cas": 16647, "\u0120Buff": 16648, "paragraph": 16649, "330": 16650, "648": 16651, "172": 16652, "\u0120posit": 16653, "\u0120statistical": 16654, "ISH": 16655, "genes": 16656, "\u0120linewidth": 16657, "\u0120ansible": 16658, "XCUIElementTypeOther": 16659, "Dic": 16660, "Pred": 16661, "redd": 16662, "\u0120cyl": 16663, "\u0120wie": 16664, "riber": 16665, "\u0120residual": 16666, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 16667, "\u0120Station": 16668, "146": 16669, "transl": 16670, "\u0120Short": 16671, "bbed": 16672, "\u0120membership": 16673, "Activity": 16674, "\u0120pregnancy": 16675, "QSizePolicy": 16676, "due": 16677, "pixels": 16678, "\u0120retain": 16679, "\u0120operand": 16680, "\u0120discord": 16681, "\u0120likes": 16682, "\u0120employment": 16683, "\u0120mechanical": 16684, "pieces": 16685, "\u0120acknowled": 16686, "esian": 16687, "lywood": 16688, "\u0120[{\"": 16689, "\u0120heter": 16690, "143": 16691, "\u0120accused": 16692, "\u0120forever": 16693, "GGER": 16694, "Bul": 16695, "Low": 16696, "hover": 16697, "\u0120fool": 16698, "\u0120bundle": 16699, "igation": 16700, "\u0120gay": 16701, "\u0120Ni": 16702, "\u0120Unt": 16703, "\u0120roof": 16704, "\u0120servers": 16705, "traj": 16706, "\u0120brothers": 16707, "\u0120activate": 16708, "\u0120anticip": 16709, "\u0120combinations": 16710, "\u0120STAT": 16711, "\u0120maintained": 16712, "Rows": 16713, "claimer": 16714, "\u0120Football": 16715, "Bool": 16716, "\u00ec\u012c": 16717, "\u0120ttk": 16718, "\u0120lad": 16719, "\u0120Foreign": 16720, "\u0120Dummy": 16721, "Reset": 16722, "Star": 16723, "Interrupt": 16724, "execution": 16725, "\u0120Perhaps": 16726, "'>": 16727, "Mesh": 16728, "eness": 16729, "\u0120tok": 16730, "\u0120hill": 16731, "igible": 16732, "angel": 16733, "valry": 16734, "\u0120discipl": 16735, "305": 16736, "genre": 16737, "authorized": 16738, "\u00e6\u013a\u00af\u00e5\u0132\u00a6": 16739, "rwxrwxr": 16740, "\u00e8\u00b1": 16741, "\u00eb\u0131": 16742, "ndrwxrwxr": 16743, "\u0120Size": 16744, "ema": 16745, "\u0120Econom": 16746, "Thanks": 16747, "\u0120disturb": 16748, "\u0120retire": 16749, "\u0120confront": 16750, "\u0120swap": 16751, "\u0120survive": 16752, "\u0120restriction": 16753, "\u0120syndrome": 16754, ".[@": 16755, "Language": 16756, "\u0120\u010a\u010a\u0120\u0120\u0120": 16757, "\u0120ct": 16758, "\u0120fut": 16759, "istically": 16760, "\u0120Morgan": 16761, "articles": 16762, "\u0120Ga": 16763, "science": 16764, "trical": 16765, "\u0120classical": 16766, "Internal": 16767, "Forward": 16768, "\u0120moral": 16769, "compatible": 16770, "\u0120robust": 16771, "\u00e7\u00a9\u00ba": 16772, ":].": 16773, "hell": 16774, "\u0120hip": 16775, "iline": 16776, "\u0120Course": 16777, "\u0120Community": 16778, "Topic": 16779, "]},": 16780, "\u00e7\u013e": 16781, "uto": 16782, "ceil": 16783, "\u0120clim": 16784, "\u0120trunc": 16785, "Listener": 16786, "ckets": 16787, "\u0120hostname": 16788, "\u0120emotion": 16789, "mot": 16790, "\"\")": 16791, "izabeth": 16792, "\u0120managers": 16793, "\u0120marketing": 16794, "tracks": 16795, "writing": 16796, "NECTION": 16797, "\u0120administrative": 16798, "GU": 16799, "ZZ": 16800, "\u00e5\u00a6\u0124": 16801, "inth": 16802, "\u0120thorough": 16803, "\u0120Stock": 16804, "\u0120Avenue": 16805, "\u0120CP": 16806, "253": 16807, "connector": 16808, "\u0120Enter": 16809, "\u0120explore": 16810, "candidate": 16811, "270": 16812, "\\],": 16813, "nie": 16814, "\u0120Tri": 16815, "\u0120orbit": 16816, "compet": 16817, "\u0120mathemat": 16818, "\u0120artillery": 16819, "\u0120inserted": 16820, "##############################################################################": 16821, "\u0120favour": 16822, "\u00e9\u013c": 16823, "\u0120pause": 16824, "oub": 16825, "vere": 16826, "\u0120rational": 16827, "\u0120alphabet": 16828, "mention": 16829, "\u0120Du": 16830, "ftp": 16831, "\u0120produces": 16832, "\u0120Redist": 16833, "\u0120diseases": 16834, "Failure": 16835, "\u00e2\u0138\u0133\u00e2\u0138\u0133": 16836, "\u0120FIXME": 16837, "vex": 16838, "imag": 16839, "ponential": 16840, "\u0120relates": 16841, "groupBox": 16842, "ASA": 16843, "\u0120everybody": 16844, "\u0120harvest": 16845, "\u0120regardless": 16846, "\u0120legislation": 16847, "BIN": 16848, "Evalu": 16849, "PAGE": 16850, "bear": 16851, "rss": 16852, "\u0120dies": 16853, "idity": 16854, "\u0120perf": 16855, "\u0120zeros": 16856, "\u0120Unicode": 16857, "letters": 16858, "\u0120portal": 16859, "\u0120programming": 16860, "\u0120m\u00c3\u00a1s": 16861, "Symbol": 16862, "TEMPLATES": 16863, "((\"": 16864, "DV": 16865, "Effect": 16866, "mv": 16867, "inverse": 16868, "\u0120Sus": 16869, "\u0120concat": 16870, "\u0120ME": 16871, "\u0120Gi": 16872, "posals": 16873, "\u0120urlparse": 16874, "checklist": 16875, "\u0120thinks": 16876, "LineEdit": 16877, "holbach": 16878, "vable": 16879, "\u0120tired": 16880, "\u0120cmap": 16881, "userid": 16882, "iteration": 16883, "\u0120formats": 16884, "\u0120drivers": 16885, "\u0120organic": 16886, "\u0120'-'": 16887, "\u0120Connection": 16888, "gid": 16889, "sales": 16890, "\u00e6\u00a1": 16891, "inator": 16892, "\u0120flying": 16893, "aman": 16894, "=======": 16895, "MED": 16896, "HOME": 16897, "digest": 16898, "\u0120Christmas": 16899, "\u0120investigated": 16900, "GY": 16901, "goto": 16902, "mime": 16903, "\u00e2\u0142\u0122": 16904, "\u0120cried": 16905, "ulp": 16906, "quarters": 16907, "ificant": 16908, "iterations": 16909, "uitable": 16910, "\u0120angles": 16911, "\u0120decorator": 16912, "ACCESS": 16913, "FIELD": 16914, "\u0120rolled": 16915, "fle": 16916, "\u0120spark": 16917, "\u0120gues": 16918, "\u012001": 16919, "\u0120defer": 16920, "\u0120anger": 16921, "STEM": 16922, "\u0120reducing": 16923, "patches": 16924, "\u0120determination": 16925, "\u0120persu": 16926, ")].": 16927, "Hsp": 16928, "IES": 16929, "\u0120avec": 16930, "dell": 16931, "agne": 16932, "009": 16933, "\u0120Cab": 16934, "\u0120runtime": 16935, "apple": 16936, "movies": 16937, "\u00e3\u0124\u012e": 16938, "\u0120Norway": 16939, "\"/": 16940, "Words": 16941, "kan": 16942, "rounded": 16943, "\u0120SER": 16944, "exper": 16945, "STM": 16946, "\u0120anymore": 16947, "\u0120minim": 16948, "}/{": 16949, "\u0120\u00c3\u00bcber": 16950, "Scope": 16951, "orate": 16952, "\u0120[{": 16953, "eman": 16954, "\u0120filepath": 16955, "\u0120scales": 16956, "\u0120scaling": 16957, "Soft": 16958, "Features": 16959, "CSV": 16960, "PV": 16961, "Pixel": 16962, "\u00d0\u0140": 16963, "esome": 16964, "\u0120','": 16965, "\u0120Core": 16966, "unsigned": 16967, "\u0120BL": 16968, "\u0120arrow": 16969, "\u012082": 16970, "\u0120pady": 16971, "EMP": 16972, "gain": 16973, "\u00d0\u0134": 16974, "\u0120garden": 16975, "\u0120Square": 16976, "\")]": 16977, "\u0120assistant": 16978, "Thank": 16979, "174": 16980, "survey": 16981, "\u0120Jefferson": 16982, "Face": 16983, "bing": 16984, "salt": 16985, "\u0120ALL": 16986, "\u0120Cro": 16987, "\u0120Fake": 16988, "acquire": 16989, "\u0120resist": 16990, "\u0120comprehen": 16991, "reads": 16992, "}}(": 16993, "\u00d1\u0122\u00d0\u00b0": 16994, "radient": 16995, "\u0120episodes": 16996, "izzle": 16997, "\u0120ownership": 16998, "?\",": 16999, "Browser": 17000, "HC": 17001, "\u00d0\u0141": 17002, "\u0120cable": 17003, "construction": 17004, "coef": 17005, "assertAlmostEqual": 17006, "\u0120decoder": 17007, "datas": 17008, "\u0120electrical": 17009, "Shell": 17010, "\u0120shooting": 17011, "OUR": 17012, "Rich": 17013, "TAG": 17014, "xAH": 17015, "oli": 17016, "\u0120beef": 17017, "\u0120votes": 17018, "\u0120Miller": 17019, "\u0120alg": 17020, "\u01201940": 17021, "\u0120myth": 17022, "());": 17023, "647": 17024, "imgs": 17025, "\u0120Stephen": 17026, "\u0120Ross": 17027, "ixtures": 17028, "\u0120thickness": 17029, "###############################################################################": 17030, "\u00e5\u0131\u00af\u00e4\u00bb\u00a5": 17031, "inherit": 17032, "lip": 17033, "\u0120borrow": 17034, "\u0120mysql": 17035, "\u0120'\\\\": 17036, "\u0120vit": 17037, "endif": 17038, "\u0120assemb": 17039, "shadow": 17040, "\u0120\\|": 17041, "geon": 17042, "coln": 17043, "\u0120boss": 17044, "\u0120payments": 17045, "\u0120REBT": 17046, "\u00ec\u013f\u0126": 17047, "Iteration": 17048, "DecimalField": 17049, "\u0120prototype": 17050, "Ann": 17051, "dan": 17052, "uu": 17053, "\u0120'.'": 17054, "\u0120desert": 17055, "\u0120beans": 17056, "('//": 17057, "\u0120Five": 17058, "\u0120entropy": 17059, "disconnect": 17060, "\u0120provision": 17061, "\u0120initialized": 17062, "visions": 17063, "Byte": 17064, "ourage": 17065, "\u0120valuable": 17066, "?',": 17067, "Gate": 17068, "\u0120Navy": 17069, "\u0120probe": 17070, "\u0120classified": 17071, "ADDR": 17072, "does": 17073, "\u0120Contact": 17074, "\u0120attachment": 17075, "Sch": 17076, "\u0120renew": 17077, "third": 17078, "\u0120Equ": 17079, "\u0120Json": 17080, "minutes": 17081, "UTE": 17082, "\u0120handlers": 17083, "\u0120cooking": 17084, "\u0120combat": 17085, "\u0120Dictionary": 17086, "\u0120monitoring": 17087, "Hey": 17088, "LENGTH": 17089, "YW": 17090, "uum": 17091, "\u0120amin": 17092, "\u0120birds": 17093, "\u0120Cred": 17094, "\u0120advent": 17095, "beam": 17096, "\u0120matrices": 17097, "modify": 17098, "\u00e5\u0131\u013a": 17099, "social": 17100, "\u0120dur": 17101, "\u0120stupid": 17102, "\u0120Creek": 17103, "\u0120veter": 17104, "uggest": 17105, "\u0120clf": 17106, "185": 17107, "\u0120twelve": 17108, "infos": 17109, "histogram": 17110, "assertIsInstance": 17111, "66666666": 17112, ")^{": 17113, "\u0120turb": 17114, "\u0120Title": 17115, "conj": 17116, "\u0120Bal": 17117, ".\".": 17118, "\u0120Asian": 17119, "\u0120frustr": 17120, "dtuple": 17121, "\u0120pushing": 17122, "Combo": 17123, "\u0120succeed": 17124, "\u0120definitions": 17125, "\u0120hypothesis": 17126, "]].": 17127, "mr": 17128, "oices": 17129, "tun": 17130, "\u0120breed": 17131, "raq": 17132, "\u0120Mid": 17133, "clause": 17134, "former": 17135, "REC": 17136, "ARGET": 17137, "\u0120comfortable": 17138, "\u0120Mountain": 17139, "RU": 17140, "\u0120categ": 17141, "\u0120Lock": 17142, "\u0120ships": 17143, "\u0120compact": 17144, "\u01201985": 17145, "122": 17146, "209": 17147, "\u0120offices": 17148, "(((": 17149, "signals": 17150, "\u0120Howard": 17151, "BUILD": 17152, "\u0120Keyboard": 17153, "\u0120reveal": 17154, "+)\\": 17155, "SUP": 17156, "vir": 17157, "\u0120delic": 17158, "\u0120Latin": 17159, "169": 17160, "ighth": 17161, "\u0120defendants": 17162, "\u0120Hamilton": 17163, ">/": 17164, "mse": 17165, "mate": 17166, "sudo": 17167, "\u00e9\u00aa": 17168, "\u0120bn": 17169, "ughed": 17170, "208": 17171, "documents": 17172, "Runner": 17173, "losses": 17174, "\u0120deeply": 17175, "something": 17176, "Ideal": 17177, "_'+": 17178, "itzer": 17179, "parame": 17180, "199": 17181, "384": 17182, "\u0120privacy": 17183, "\u0120servings": 17184, "\u0120atmosphere": 17185, "Mc": 17186, "fib": 17187, "atype": 17188, "amaz": 17189, "\u0120Dark": 17190, "\u0120Wat": 17191, "\u0120rounded": 17192, "\u012093": 17193, "plots": 17194, "heading": 17195, ")*(-": 17196, "\u0120struggle": 17197, "Embed": 17198, "Hi": 17199, "\u0120bother": 17200, "ivari": 17201, "190": 17202, "\u0120accompan": 17203, "\u0120readonly": 17204, "URLCONF": 17205, "CKM": 17206, "301": 17207, "cros": 17208, "wers": 17209, "\u0120Family": 17210, "emale": 17211, "valence": 17212, "crease": 17213, "colog": 17214, "registration": 17215, "\u00e2\u0138\u0126": 17216, "\u0120computation": 17217, "ANGE": 17218, "Assign": 17219, "\u0120chunks": 17220, "\u0120Products": 17221, "\u0120roughly": 17222, "caps": 17223, "\u0120Pres": 17224, "\u0120Gree": 17225, "\u0120Stream": 17226, "\u0120spokes": 17227, "manifest": 17228, "\u0120Device": 17229, "\u0120multimedia": 17230, "Percent": 17231, "\u0120burden": 17232, "Small": 17233, "gd": 17234, "\u0120cort": 17235, "\u0120Wal": 17236, "\u0120Wait": 17237, "])[": 17238, "itionally": 17239, "Segment": 17240, "Which": 17241, "cleanup": 17242, "\u0120arrive": 17243, "\u00e9\u00a2\u013a": 17244, "sector": 17245, "\u0120luck": 17246, "\u0120lazy": 17247, "\u0120va": 17248, "\"\"\")": 17249, "\u0120Week": 17250, "\u0120GUI": 17251, "shutdown": 17252, "257": 17253, "prices": 17254, "\u0120consideration": 17255, "svg": 17256, "]\\],": 17257, "\u0120drove": 17258, "DQ": 17259, "iences": 17260, "\u00ce\u00b1": 17261, "\u0120Aud": 17262, "\u0120Jah": 17263, "mlink": 17264, "locator": 17265, "\u0120grace": 17266, "\u0120Dataset": 17267, "\u0120Harvard": 17268, "iq": 17269, "itical": 17270, "\u0120redis": 17271, "antages": 17272, "\u0120transformed": 17273, "\u0120extensive": 17274, "functional": 17275, "\u0120removal": 17276, "uar": 17277, "wner": 17278, "\u00e6\u013b": 17279, "\u0120giant": 17280, "\u0120Ten": 17281, "\u0120Nothing": 17282, "pretrained": 17283, "ATOR": 17284, "lengths": 17285, "---|": 17286, "\u00e6\u013f\u00a5": 17287, "\u00e4\u00bc\u013c": 17288, "David": 17289, "\u0120TF": 17290, "\u0120LINE": 17291, "]);": 17292, "ommod": 17293, "spawn": 17294, "Expected": 17295, "\u0120lawyer": 17296, "}^{-": 17297, "requirements": 17298, "Cam": 17299, "lag": 17300, "\u0120sab": 17301, "\u0120Later": 17302, "\u0120Os": 17303, "\":[": 17304, "\u01201982": 17305, "Subject": 17306, "\u0120digest": 17307, "idae": 17308, "\u0120Harvest": 17309, "\u00ec\u013f\u013a": 17310, "\u0120subsequently": 17311, "%%%%%%%%": 17312, ",:,": 17313, "Scan": 17314, "basis": 17315, "oria": 17316, "\u0120ocean": 17317, "\u0120inqu": 17318, "\u0120restart": 17319, "\u0120nm": 17320, "\u0120Bool": 17321, "\u0120Wales": 17322, "\u0120boat": 17323, "\u0120functionality": 17324, "\u0120corn": 17325, "\u0120handles": 17326, "Integr": 17327, "\u0120exped": 17328, "Mini": 17329, "Implementation": 17330, "\u0120Julie": 17331, "\u0120doctest": 17332, "\u0120Spring": 17333, "\u00e9\u0125\u00a8": 17334, "*^": 17335, "stan": 17336, "\u0120chip": 17337, "177": 17338, "\u0120statute": 17339, "\u0120Coast": 17340, "\u0120\"-\"": 17341, "\u0120remembered": 17342, "\u0120witness": 17343, "MASK": 17344, "TX": 17345, "bes": 17346, "\u0120tent": 17347, "exchange": 17348, "LEVEL": 17349, "\u0120promised": 17350, "\u0120integrated": 17351, "\u00f0\u0141\u0136": 17352, "ogenic": 17353, "\u0120Empire": 17354, "\u0120Film": 17355, "lights": 17356, "\u0120Tro": 17357, "(\"{}": 17358, "setLevel": 17359, "INET": 17360, "\u0120forming": 17361, "\u0120Assembly": 17362, "Adam": 17363, "zzle": 17364, "\u0120suspic": 17365, "\u00e6\u00b1\u0124": 17366, "moment": 17367, "CAT": 17368, "Der": 17369, "\u010d\u010a\u0109\u0109\u0109\u0109\u0109": 17370, "\u0120tqdm": 17371, "\u0120enthus": 17372, "writeField": 17373, "\u0120priest": 17374, "\u0120Leon": 17375, "\u0120prominent": 17376, "\u0120Summer": 17377, "builtin": 17378, ":\\\\": 17379, "South": 17380, "Self": 17381, "stable": 17382, "arse": 17383, "\u0120oxygen": 17384, "\u0120gear": 17385, "\u0120correction": 17386, "solver": 17387, "\u00e8\u00af\u0123": 17388, "\u0120Harry": 17389, "\u0120incub": 17390, "\u0120burst": 17391, "\u0120rarely": 17392, "\u0120lp": 17393, "\u0120ease": 17394, "\u0120Jews": 17395, "ceptions": 17396, "ROP": 17397, "\u0120longest": 17398, "\u0120portions": 17399, "Perfume": 17400, "\u0120speaker": 17401, "cussion": 17402, "\u0120\u00d1\u0126": 17403, "\u0120earned": 17404, "UBL": 17405, "oser": 17406, "inction": 17407, "received": 17408, "\u0120bunch": 17409, "\u0120Trial": 17410, "\u01201979": 17411, "\u0120Muslim": 17412, "Okay": 17413, "titles": 17414, "/?": 17415, "God": 17416, "IK": 17417, "validator": 17418, "\u0120everywhere": 17419, "inois": 17420, "sequently": 17421, "\u0120Among": 17422, "\u0120Linear": 17423, "fm": 17424, "challenge": 17425, "\u0120MB": 17426, "quota": 17427, "icked": 17428, "\u0120workspace": 17429, "\u0120comic": 17430, "Spin": 17431, "\u0120crossed": 17432, "\u0120Circuit": 17433, "CAN": 17434, "_='": 17435, "hatt": 17436, "\u0120ACTION": 17437, "\u0120Pho": 17438, "athers": 17439, "\u0120weird": 17440, "\u0120}}": 17441, "162": 17442, "\u0120INCLUDING": 17443, "simulation": 17444, "sensus": 17445, "iw": 17446, "anne": 17447, "\u0120fert": 17448, "oped": 17449, "\u0120argues": 17450, "Organ": 17451, "\u00e5\u00ba\u0136": 17452, "holders": 17453, "\u0120examination": 17454, "\u0120hoping": 17455, "employee": 17456, "isch": 17457, "icular": 17458, "\u0120gained": 17459, "chrome": 17460, "\u01201984": 17461, "195": 17462, "encer": 17463, "matched": 17464, "\u0120randomly": 17465, "\u00c3\u00a4n": 17466, "capacity": 17467, "Spider": 17468, "\u0120nervous": 17469, "thro": 17470, "\u0120jack": 17471, "\u0120topics": 17472, "Plan": 17473, "\u00c3\u00a4t": 17474, "\u0120regularly": 17475, "\u0120Michigan": 17476, "\u0120Extract": 17477, "\u0120implicit": 17478, "\u0120ERROR": 17479, "\u0120'>": 17480, "\u0120({": 17481, "\u0120Come": 17482, "\u012008": 17483, "\u0120laughed": 17484, "Shadow": 17485, "\u0120renderer": 17486, "tml": 17487, "\u0120\u010a\u0109\u0109": 17488, "\u0120\u010d\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 17489, "\u013d\u00e5\u00bb\u00ba": 17490, "\u0120detector": 17491, "\u0120stops": 17492, "\u0120Cri": 17493, "\u0120proud": 17494, "psy": 17495, "\u0120embedded": 17496, "nombre": 17497, "\u0120pes": 17498, "aders": 17499, "pection": 17500, "\u0120ranges": 17501, "\u0120Luc": 17502, "oche": 17503, "],'": 17504, "\u0120Sept": 17505, "\u0120histogram": 17506, "\u0120soldier": 17507, "cooker": 17508, "\u0120Cleo": 17509, "\u0120defeated": 17510, "\u0120Lesser": 17511, "\u0120Toronto": 17512, "]--": 17513, "gent": 17514, "mill": 17515, "zt": 17516, "\u0120Ak": 17517, "anti": 17518, "\u0120js": 17519, "geom": 17520, "Chain": 17521, "\u0120102": 17522, "\u0120Centre": 17523, "\u0120Republicans": 17524, "camp": 17525, "\u0120implements": 17526, "consumer": 17527, "\u0120HD": 17528, "shp": 17529, "\u0120somebody": 17530, "198": 17531, "\u0120Arm": 17532, "Times": 17533, "\u0120gotten": 17534, "mptotic": 17535, "\u0120\u00ec\u013f": 17536, "\u0120basketball": 17537, "\u0120encountered": 17538, "DNA": 17539, "Mal": 17540, "Suite": 17541, "know": 17542, "\u0120inference": 17543, "agree": 17544, "agents": 17545, "cko": 17546, "__',": 17547, "orem": 17548, "\u0120Dun": 17549, "\u0120orange": 17550, "minor": 17551, "molec": 17552, "\u0120imaging": 17553, "([('": 17554, "\u00e3\u0123\u012d": 17555, "\u0120desper": 17556, "\u0120Decimal": 17557, ")<": 17558, "\u00d9\u0127": 17559, "\u0120gs": 17560, "\u0120consecutive": 17561, "234": 17562, "ETHER": 17563, "Cooking": 17564, "EXP": 17565, "\u0120covering": 17566, "\u0120occupied": 17567, "CURRENT": 17568, "Uns": 17569, "fly": 17570, "want": 17571, "\u0120din": 17572, "\u0120lamp": 17573, "berry": 17574, "136": 17575, "\u0120codecs": 17576, "ISING": 17577, "\u0120fewer": 17578, "\u0120Result": 17579, "Scene": 17580, "\u0120EXPRESS": 17581, "\u0120voters": 17582, "Examples": 17583, "wp": 17584, "\u00e2\u012a": 17585, "\u0120STR": 17586, "\u0120stamp": 17587, "\u0120Results": 17588, "\u0120designs": 17589, "OBJECT": 17590, "\u00e7\u013b\u00bb": 17591, "WT": 17592, "YS": 17593, "nested": 17594, "vd": 17595, "\u0120Tai": 17596, "\u0120Track": 17597, "ifts": 17598, "ippi": 17599, "\u0120resize": 17600, "\u0120Though": 17601, "mox": 17602, "\u0120manuscript": 17603, "\u0120logits": 17604, "Expression": 17605, "\u00d0\u00b0\u00d0\u00ba": 17606, "choose": 17607, "Iterator": 17608, "\u0120defeat": 17609, "Focus": 17610, "jacking": 17611, "\u0120semi": 17612, "__(*": 17613, "308": 17614, "Platform": 17615, "\u0120introduce": 17616, "CommonMiddleware": 17617, "capture": 17618, "\u00e9\u013e\u0122": 17619, "LT": 17620, "mers": 17621, "motion": 17622, "\u0120fits": 17623, "\u0120Saint": 17624, "\u0120Ah": 17625, "\u0120NT": 17626, "\u0120[%": 17627, "\u0120ongoing": 17628, "\u0120Layer": 17629, "ellar": 17630, "\u0120unw": 17631, "605": 17632, "Super": 17633, "ControlIdentifiers": 17634, "routineControlIdentifiers": 17635, "\u0120unusual": 17636, "\u00e9\u00bb": 17637, "\u0120sf": 17638, "thm": 17639, "\u0120Bush": 17640, "989": 17641, "OPEN": 17642, "Design": 17643, "\u0120mounted": 17644, "SessionMiddleware": 17645, "Maybe": 17646, "\u00d0\u00b0\u00d0\u00bd\u00d0\u00b8": 17647, "\u0120teaspoon": 17648, "\u0120PROVIDED": 17649, "bsp": 17650, "orne": 17651, "\u0120fate": 17652, "\u0120vice": 17653, "endants": 17654, "aware": 17655, "Identity": 17656, "ischen": 17657, "\u0120religion": 17658, "Gl": 17659, "\u0120cd": 17660, "\u0120rats": 17661, "\u0120dataDict": 17662, "\u0120Vari": 17663, "workspace": 17664, "\u0120Sequence": 17665, "certificate": 17666, "\u0120females": 17667, "\u00e5\u00bd\u0135": 17668, "\u0120DAMAGES": 17669, "\u0120Bol": 17670, "ikes": 17671, "\u0120genome": 17672, "\u0120landscape": 17673, "\u0120flesh": 17674, "Csrf": 17675, "Hook": 17676, "Vs": 17677, "speak": 17678, "zoom": 17679, "\u0120flood": 17680, "\u0120od": 17681, "eties": 17682, "regon": 17683, "243": 17684, "clients": 17685, "262": 17686, "randn": 17687, "\u0120barely": 17688, "\u00ea\u00b8\u00b0": 17689, "bast": 17690, "een": 17691, "whel": 17692, "yc": 17693, "death": 17694, "utation": 17695, "\u0120Night": 17696, "plant": 17697, "\u0120excluded": 17698, "tran": 17699, "\u0120['-": 17700, "sampling": 17701, "probability": 17702, "uniq": 17703, "Dropout": 17704, "hits": 17705, "\u0120fought": 17706, "preprocessing": 17707, "307": 17708, "risk": 17709, "Agg": 17710, "\u0120Front": 17711, "\u0120fraud": 17712, "\u0120examine": 17713, "\u0120Philadelphia": 17714, "ticker": 17715, "\u0120recipient": 17716, "multiply": 17717, "\u0120metabol": 17718, "020": 17719, "Cr": 17720, "CALL": 17721, "replic": 17722, "\u0120craft": 17723, "\u0120oct": 17724, "\u0120dough": 17725, "\u0120delib": 17726, "thur": 17727, "\u0120Bridge": 17728, "usive": 17729, "(\"_": 17730, "\u0120UTC": 17731, "poons": 17732, "\u01201918": 17733, "linked": 17734, "\u0120Policy": 17735, "\u0120maintenance": 17736, "hardware": 17737, "cube": 17738, "sters": 17739, "ilib": 17740, "197": 17741, "139": 17742, "ViewMiddleware": 17743, "777": 17744, "\u0120swim": 17745, "\u0120Parameter": 17746, "pkt": 17747, "\u0120believes": 17748, "\u0120Spirit": 17749, "\u0120Professor": 17750, "\u0120Columbia": 17751, "hm": 17752, "\u00e9\u0124": 17753, "\u0120Pit": 17754, "parallel": 17755, "\u0120unlikely": 17756, "Station": 17757, "\u0120retired": 17758, "supplementary": 17759, "\u00d0\u00bb\u00d1\u0131": 17760, "\u0120MySQL": 17761, "Water": 17762, "hang": 17763, "}),": 17764, "relevant": 17765, "\u0120Batch": 17766, "\u0120Ubuntu": 17767, "minded": 17768, "wegian": 17769, "\u0120politicians": 17770, "\u0120padx": 17771, "Radio": 17772, "Old": 17773, "cus": 17774, "\u0120pale": 17775, "\u0120soci": 17776, "idle": 17777, "\u0120concert": 17778, "_{-": 17779, "\u0120playlist": 17780, "\u0120courses": 17781, "\u0120'./": 17782, "\u0120tears": 17783, "\u00e5\u00a5": 17784, "\u0120Site": 17785, "ifax": 17786, "\u0120Father": 17787, "']).": 17788, "phan": 17789, "\u0120activated": 17790, "Trace": 17791, "\u0120Province": 17792, "CsrfViewMiddleware": 17793, "Each": 17794, "HR": 17795, "crib": 17796, "\u0120ld": 17797, "\u0120reson": 17798, "avour": 17799, "\u0120admit": 17800, "\u0120compress": 17801, "within": 17802, "238": 17803, "United": 17804, "Modified": 17805, "]')": 17806, "burn": 17807, "rn": 17808, "wm": 17809, "\u0120sle": 17810, "\u0120IC": 17811, "ensing": 17812, "lices": 17813, "\u0120interior": 17814, "webdriver": 17815, "\u0120demands": 17816, "\u00e8\u00b1\u00a1": 17817, "zeta": 17818, "\u0120dual": 17819, "etree": 17820, "\u0120140": 17821, "\u0120Mu": 17822, "\u0120MPI": 17823, "\u0120algorithms": 17824, "herp": 17825, "\u0120@@": 17826, "\u0120buying": 17827, "\u0120pylab": 17828, "\u0120accommod": 17829, "interpol": 17830, "Collect": 17831, "\u00d0\u00b5\u00d0\u00ba": 17832, "MessageMiddleware": 17833, "\u00e5\u00ae\u00b9": 17834, "Starting": 17835, "\u0120arrival": 17836, "\u0120presidential": 17837, "\u0120Member": 17838, "\u0120compatibility": 17839, "\u00e6\u0138\u00b9\u00e6\u00b3\u0137": 17840, "\u0120nobody": 17841, "%;": 17842, ":_": 17843, "\u00f0\u0134": 17844, "ische": 17845, "\u0120instruments": 17846, "univ": 17847, "\u0120alleg": 17848, "\u0120enorm": 17849, "119": 17850, "necess": 17851, "\u0120shortly": 17852, "\u0120urban": 17853, "\u0120Enable": 17854, "\u0120Ministry": 17855, "\u00e5\u012c\u0141": 17856, "\u0120constitu": 17857, "CLIENT": 17858, "\u0120Lewis": 17859, "Life": 17860, "\u0120cir": 17861, "\u0120=============================================================================": 17862, "\u0120sword": 17863, "utive": 17864, "\u0120alumni": 17865, "\u0120\\,": 17866, "\u0120});": 17867, "\u0120Chrome": 17868, "IDS": 17869, "\u0120retail": 17870, "\u0120Germans": 17871, "\u0120acceptable": 17872, "secondary": 17873, "\u0120attempting": 17874, "\u0120interpolation": 17875, "\u00e7\u00b3": 17876, "heses": 17877, "peer": 17878, "\u0120stared": 17879, "umi": 17880, "\u0120telephone": 17881, "Advertisement": 17882, "bage": 17883, "\u0120tan": 17884, "\u0120ptr": 17885, "\u0120mic": 17886, "\u0120Have": 17887, "keyboard": 17888, "addItem": 17889, "ReReco": 17890, "182": 17891, "504": 17892, "rollers": 17893, "\u0120Communic": 17894, "\u0120convin": 17895, "STRU": 17896, "SUCCESS": 17897, "370": 17898, "Bro": 17899, "Den": 17900, "FIN": 17901, "t\u00c3\u00a9": 17902, "\u0120cette": 17903, "\u0120glo": 17904, "\u0120Tell": 17905, "\u0120MOD": 17906, "\u0120fileName": 17907, "\u0120rap": 17908, "\u0120observ": 17909, "essages": 17910, "1998": 17911, "\u0120quoted": 17912, "visited": 17913, "\u0120virus": 17914, "Renderer": 17915, "\")))": 17916, "opher": 17917, "\u0120ki": 17918, "=\"+": 17919, "\u0120Vill": 17920, "ABC": 17921, "388": 17922, "\u0120pr\u00c3\u00a9": 17923, "\u0120wooden": 17924, "\u0120Studies": 17925, "\u00d7\u0136": 17926, "ifs": 17927, "\u0120FC": 17928, "scriber": 17929, "609": 17930, "ahl": 17931, "\u0120este": 17932, "Also": 17933, "\u0120collision": 17934, "ivariate": 17935, "Che": 17936, "Early": 17937, "zc": 17938, "refer": 17939, "\u0120Iraq": 17940, "quis": 17941, "')):": 17942, "\u0120:-": 17943, "ugby": 17944, "pretty": 17945, "Prop": 17946, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 17947, "}}_{": 17948, "\u0120TestCase": 17949, "Company": 17950, "volumes": 17951, "\u0120outcomes": 17952, "\u0120preparation": 17953, "\u0120brigade": 17954, "PN": 17955, "Raster": 17956, "kk": 17957, "\u0120wound": 17958, "ials": 17959, "grama": 17960, "\u0120***": 17961, "967": 17962, "\u0120brill": 17963, "CLAS": 17964, "\u00e6\u012f\u00a2": 17965, "\u00e8\u00a7\u00a3": 17966, "dney": 17967, "enet": 17968, "\u0120PAR": 17969, "\u0120Da": 17970, "\u0120infantry": 17971, "\u0120Loop": 17972, "guard": 17973, "\u0120Roger": 17974, "+\".": 17975, "Hex": 17976, "NORMAL": 17977, "]\",": 17978, "enemy": 17979, "itals": 17980, "deck": 17981, "\u0120nargs": 17982, "\u0120lady": 17983, "\u0120listener": 17984, "ITION": 17985, "176": 17986, "\u00e2\u0138\u012a\u00e2\u0138\u012a\u00e2\u0138\u012a\u00e2\u0138\u012a": 17987, "\u0120aggregate": 17988, "dhcp": 17989, ">.*": 17990, "Music": 17991, "cnn": 17992, "\u0120coinc": 17993, "obar": 17994, "prep": 17995, "\u0120assay": 17996, "submission": 17997, "Checker": 17998, "Optim": 17999, "\u0120FORM": 18000, "\u0120globals": 18001, "\u0120colleagues": 18002, "\u00e6\u012b\u0122\u00e6\u013e\u012b": 18003, "Cert": 18004, "hub": 18005, "\u0120cust": 18006, "\u0120inp": 18007, "\u0120males": 18008, "ATORS": 18009, "\u0120actors": 18010, "\u00d0\u00be\u00d0\u00b9": 18011, "\u0120Adv": 18012, "\u0120denominator": 18013, "\u0120waited": 18014, "\u0120annotation": 18015, "\u0120SHALL": 18016, "GPL": 18017, "Writ": 18018, "\u010a\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 18019, "\u0120baking": 18020, "\u0120Age": 18021, "\u0120yeah": 18022, "(\"./": 18023, "\u0120Ele": 18024, "\u0120VER": 18025, "\u0120subsid": 18026, "\u0120Tests": 18027, "\u0120frequent": 18028, "Comments": 18029, "\u0120ValidationError": 18030, "decorator": 18031, "\u0120Determine": 18032, "[/": 18033, "setStyle": 18034, "ochem": 18035, "anto": 18036, "018": 18037, "CHANNEL": 18038, "\u0120Clinton": 18039, "\u0120considerable": 18040, "\u0120filtering": 18041, "Phase": 18042, "Generate": 18043, "\u00e7\u013d\u00b8": 18044, "iatric": 18045, "EG": 18046, "gies": 18047, "slow": 18048, "alion": 18049, "routes": 18050, "ether": 18051, "\u0120AC": 18052, "\u0120Hart": 18053, "forced": 18054, "\u0120agencies": 18055, "151": 18056, "188": 18057, "\u0120insulin": 18058, "\u0120laser": 18059, "\u00e5\u00be\u0139": 18060, "Reports": 18061, "\u0120crystal": 18062, ">`": 18063, "Tur": 18064, "daily": 18065, "}|": 18066, "\u00ce\u00b2": 18067, "\u00e9\u0135": 18068, "\u0120instruct": 18069, "\u0120Cra": 18070, "\u0120Mill": 18071, "\u0120Files": 18072, "**(-": 18073, "\u0120ancest": 18074, "\u0120headed": 18075, "\u0120Hou": 18076, "189": 18077, "\u0120caller": 18078, "graphs": 18079, "Travel": 18080, "\u0120Price": 18081, "RESULT": 18082, "IZATION": 18083, "\u0120diabetes": 18084, "Camera": 18085, "\u0120\u010d\u010a\u0120\u0120\u0120": 18086, "inic": 18087, "olis": 18088, "\u0120Menu": 18089, "conc": 18090, "\u0120Full": 18091, "\u0120Dense": 18092, "plications": 18093, "tmpdir": 18094, "\u0120multiprocessing": 18095, "\u00e6\u0122\u00a7": 18096, "\u0120glyphs": 18097, "QWidget": 18098, "Try": 18099, "isdigit": 18100, "\u0120hierarchy": 18101, "\u0120threw": 18102, "olen": 18103, "izar": 18104, "Revision": 18105, "\u0120displays": 18106, "164": 18107, "\u0120transactions": 18108, "\u0120Albert": 18109, "\u0120initialization": 18110, "\u0120puts": 18111, "ByName": 18112, "\u0120Room": 18113, "\u0120palette": 18114, "\u00e6\u012e\u0129": 18115, "MESSAGE": 18116, "LB": 18117, "lane": 18118, "rang": 18119, "\u0120singer": 18120, "\u0120wird": 18121, "\u0120vig": 18122, "\u0120Ms": 18123, "\u0120GPU": 18124, "\u0120covers": 18125, "ahn": 18126, "olester": 18127, "\u0120Adding": 18128, "\u0120characterized": 18129, "ennes": 18130, "\u0120cleaning": 18131, "\u0120Clean": 18132, "\u0120ultimate": 18133, "\u0120unsuitable": 18134, "XFrame": 18135, "dire": 18136, "rust": 18137, "\u0120prohib": 18138, "sentences": 18139, "\u0120backwards": 18140, "}}_": 18141, "\u0120caps": 18142, "\u0120baseball": 18143, "executable": 18144, "Upload": 18145, "\u0120'_'": 18146, "\u0120ipv": 18147, "\u0120molecule": 18148, "Precision": 18149, "\\(": 18150, "meter": 18151, "chem": 18152, "\u0120centers": 18153, "\u0120excited": 18154, "finite": 18155, "\u0120arranged": 18156, "\u0120territory": 18157, "CACHE": 18158, "Dr": 18159, "bio": 18160, "give": 18161, "\u00d0\u0132": 18162, "\u00e8\u012c": 18163, "\u0120pup": 18164, "ifact": 18165, "imited": 18166, "\u0120rs": 18167, "\u0120absent": 18168, "mbic": 18169, "\u0120creative": 18170, "relations": 18171, "043": 18172, "\u0120inspired": 18173, "removed": 18174, "\u0120Pakistan": 18175, "833": 18176, "OIN": 18177, "itage": 18178, "\u0120===": 18179, "ete": 18180, "eloc": 18181, "\u0120handed": 18182, "\u012009": 18183, "\u0120Wel": 18184, "\u01201983": 18185, "\u0120submission": 18186, "\u0120offense": 18187, "\u0120entering": 18188, "igrants": 18189, "++)": 18190, "Ca": 18191, "PD": 18192, "town": 18193, "\u0120genu": 18194, "':['": 18195, "enders": 18196, "\u0120\\(": 18197, "\u0120teen": 18198, "\u0120poem": 18199, "\u0120foundation": 18200, "\u0120lifeless": 18201, "\u0120Setup": 18202, "RAME": 18203, "uerite": 18204, "\u0120translated": 18205, "\u0120substrate": 18206, "]--[@": 18207, "Further": 18208, "school": 18209, "\u0120reserve": 18210, "owa": 18211, "\u0120rg": 18212, "\u010a\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120": 18213, "\u0120parking": 18214, "\u0120|=": 18215, "factors": 18216, "smart": 18217, "\u0120injured": 18218, "\u0120Simon": 18219, "=_(\"": 18220, "\u0120hello": 18221, "\u0120hydrogen": 18222, "\u0120CHECK": 18223, "criter": 18224, "wrong": 18225, "\u0120bol": 18226, "lov": 18227, "\u0120meal": 18228, "\u0120contributed": 18229, "lineno": 18230, "baseline": 18231, "\u0120susp": 18232, "\u0120introduction": 18233, "RAW": 18234, "OptionsMiddleware": 18235, "Analy": 18236, "\u0120concerning": 18237, "Dimension": 18238, "\u0120coefficients": 18239, "\u0120masses": 18240, "\u0120#:": 18241, "\u0120exceed": 18242, "\u0120Video": 18243, "\u0120Kong": 18244, "245": 18245, "\u0120Arts": 18246, "\u0120continuing": 18247, "\u00d1\u0123\u00d1\u0131": 18248, "zech": 18249, "\u0120Support": 18250, "\u0120spectral": 18251, "\u0120bugs": 18252, "Cy": 18253, "Tom": 18254, "kn": 18255, "\u0120emission": 18256, "osv": 18257, "observation": 18258, "express": 18259, "161": 18260, "\u0120fees": 18261, "237": 18262, "\u0120blocked": 18263, "clickjacking": 18264, "\u0120Prem": 18265, "\u0120mandatory": 18266, "XFrameOptionsMiddleware": 18267, "baz": 18268, "hou": 18269, "ssue": 18270, "\u0120Rod": 18271, "\u0120exerc": 18272, "\u0120kb": 18273, "ientific": 18274, "ickness": 18275, "interp": 18276, "\u0120stronger": 18277, "Horizontal": 18278, "javascript": 18279, "\u0120naturally": 18280, "lop": 18281, "ulatory": 18282, "\u0120styles": 18283, "\u0120conform": 18284, "\u010d\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u010d\u010a\u0120\u0120\u0120": 18285, "mnist": 18286, "\u0120graduate": 18287, "\u0120Rhod": 18288, "WISE": 18289, "\u0120NC": 18290, "ften": 18291, "STOP": 18292, "\u0120actu": 18293, "\u00e4\u00b8\u00b2": 18294, "\u0120loads": 18295, "restaurant": 18296, "'-": 18297, "Sync": 18298, "shtml": 18299, "\u0120mere": 18300, "\u0120*(": 18301, "\u0120jag": 18302, "\u0120assumption": 18303, "REGI": 18304, "\u0120Stim": 18305, "awa": 18306, "transforms": 18307, "\u0120downloaded": 18308, "\u0120politician": 18309, "Geo": 18310, "\u0120randint": 18311, "\u0120infrastructure": 18312, "060": 18313, "recent": 18314, "\u0120oauth": 18315, "\u0120holid": 18316, "\u0120Kell": 18317, "\u0120intellect": 18318, "\u0120pose": 18319, "ighte": 18320, "FilePath": 18321, "\u0120grams": 18322, "\u0120cleanup": 18323, "\u0120Sometimes": 18324, "\u0120bullet": 18325, "CFG": 18326, "METHOD": 18327, "\u0120radiation": 18328, "\u0120fifty": 18329, "\u00e3\u0123\u013b\u00e3\u0124\u012d": 18330, "IFI": 18331, "jj": 18332, "\u010d\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 18333, "\u0120\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd": 18334, "isse": 18335, "\u0120deprecated": 18336, "chk": 18337, "\u0120prog": 18338, "\u0120exclusive": 18339, "Coll": 18340, "\u0120solver": 18341, "\u0120worried": 18342, "\u0120transcript": 18343, "\u0120liability": 18344, "boldsymbol": 18345, "\u00ec\u00a7\u0122": 18346, "\u0120reputation": 18347, "Ni": 18348, "\u0120nous": 18349, "\u0120TYPE": 18350, "\u0120130": 18351, "ugar": 18352, "ModelAdmin": 18353, "\u0120delight": 18354, "\u0120diary": 18355, "\u00e5\u0131\u00a3": 18356, "\u0120flows": 18357, "callbacks": 18358, "\u0120bounding": 18359, "\u0120violent": 18360, "911": 18361, "\u0120\u010a\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 18362, "anes": 18363, "desk": 18364, "\u0120psy": 18365, "metrical": 18366, "\u0120Food": 18367, "\u0120oral": 18368, "\u0120Lady": 18369, "\u0120overwhel": 18370, "\u0120reliable": 18371, "DEFINE": 18372, "\u0120Ansible": 18373, "'$": 18374, "Take": 18375, "\u0120tt": 18376, "\u0120vital": 18377, "\u0120rice": 18378, "\u0120ranks": 18379, "**,": 18380, "\u0120Ve": 18381, "\u0120regarded": 18382, "passwd": 18383, "\u0120developers": 18384, "\u0120identification": 18385, "responses": 18386, "\u0120cycles": 18387, "MTP": 18388, "Pickle": 18389, "\u0120recursive": 18390, "stem": 18391, "\u0120mari": 18392, "\u0120dut": 18393, "rients": 18394, "\u0120Ali": 18395, "apon": 18396, "\u0120Nob": 18397, "setattr": 18398, "\u01201941": 18399, "Additional": 18400, "\u00e5\u0132\u0133": 18401, "\u0120talks": 18402, "\u0120worship": 18403, "\u0120elections": 18404, "\u0120gathered": 18405, "pwd": 18406, "erty": 18407, "itched": 18408, "\u0120reform": 18409, "aternal": 18410, "Christ": 18411, "\u0120specim": 18412, "compressed": 18413, "\u0120genre": 18414, "\u0120obtaining": 18415, "\u0120respective": 18416, "\u0120clubs": 18417, "\u0120transcription": 18418, "amazon": 18419, "QR": 18420, "restart": 18421, "\u0120wed": 18422, "\u0120dB": 18423, "\u0120Im": 18424, "\u0120shit": 18425, "\u0120overl": 18426, "\u0120ethn": 18427, "\u0120Quant": 18428, "\u0120aligned": 18429, "bootstrap": 18430, "\u0120criterion": 18431, "\u0120mortality": 18432, "Orient": 18433, "\u0120tap": 18434, "\u0120tape": 18435, "\u0120defining": 18436, "\u0120Pers": 18437, "\u0120Dog": 18438, "\u0120Thanks": 18439, "\u0120comprom": 18440, "LIB": 18441, "\u0120succeeded": 18442, "\u0120juice": 18443, "\u00e9\u0127\u012f": 18444, "HM": 18445, "uno": 18446, "\u0120Dor": 18447, "],\"": 18448, "\u0120viewed": 18449, "\u0120solo": 18450, "\u0120movements": 18451, "iliation": 18452, "\u0120participate": 18453, "\u0120educational": 18454, "\u0120Format": 18455, "hjph": 18456, "\u0120peaks": 18457, "xlsx": 18458, "possible": 18459, "MER": 18460, "electron": 18461, "\u0120til": 18462, "\u0120omitted": 18463, "\u0120Rid": 18464, "\u0120Early": 18465, "\u0120Ol": 18466, "\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd',": 18467, "\u0120runner": 18468, "ovi": 18469, "offs": 18470, "\u0120ORDER": 18471, "\u0120failing": 18472, "\u0120qualified": 18473, "\u0120masks": 18474, "\u0120Angel": 18475, "\u0120glucose": 18476, "IAN": 18477, "tbl": 18478, "it\u00c3\u00a9": 18479, "\u0120pros": 18480, "assertAll": 18481, "viewer": 18482, "\u0120transmit": 18483, "parsers": 18484, "webkit": 18485, "\u0120filling": 18486, "hjms": 18487, "hjps": 18488, "\u0120spiritual": 18489, "\u0120neutron": 18490, "\u0120Organization": 18491, "\u00c3\u0139": 18492, "\u0120astron": 18493, "ande": 18494, "depart": 18495, "\u0120destruction": 18496, "\u0120Song": 18497, "\u0120Iron": 18498, "228": 18499, "\u0120diction": 18500, "\\\\\\": 18501, "\u0120operated": 18502, "CLU": 18503, "\u0120affairs": 18504, "12345": 18505, "hjmh": 18506, "\u0120pleasure": 18507, "percentage": 18508, "+)": 18509, "zie": 18510, "\u0120tack": 18511, "\u0120lob": 18512, "ldots": 18513, "ivated": 18514, "\u0120jew": 18515, "\u0120%}": 18516, "\u0120plural": 18517, "avatar": 18518, "\u0120192": 18519, "\u0120quota": 18520, "\u0120retval": 18521, "\u0120technologies": 18522, "tensorflow": 18523, "TIMEOUT": 18524, "=\"\")": 18525, "\u0120manufacturer": 18526, "Structure": 18527, "\u0120intrins": 18528, "BIT": 18529, "mtime": 18530, "paid": 18531, "tel": 18532, "__),": 18533, "\u0120Eric": 18534, "=''):": 18535, "\u0120pret": 18536, "Include": 18537, "\u01201981": 18538, "\u0120peripher": 18539, "\u0120generates": 18540, "\u0120Develop": 18541, "\u0120Newton": 18542, "\u0120personally": 18543, "poolie": 18544, "\u0120snake": 18545, "\u0120grounds": 18546, "\u0120persist": 18547, "lstm": 18548, "\u0120Lincoln": 18549, "\u0120LIABLE": 18550, "Finished": 18551, "BAD": 18552, "TW": 18553, "\u0120sons": 18554, "\u0120reactions": 18555, "\u0120Sab": 18556, "odb": 18557, "\u0120rd": 18558, "ordon": 18559, "\u0120Init": 18560, "\u0120discount": 18561, "\u0120specifies": 18562, "regions": 18563, "iterable": 18564, "\u0120Permission": 18565, "\u0120ARISING": 18566, "\u00e6\u0131\u0132": 18567, "#-#-": 18568, "graduate": 18569, "Sent": 18570, "`)": 18571, "\u0120tamb": 18572, "illo": 18573, "\u0120conservative": 18574, "defs": 18575, "Separ": 18576, "SHA": 18577, "\u0120golden": 18578, "literal": 18579, "\u0120Illinois": 18580, "CEL": 18581, "Patch": 18582, "Tile": 18583, "\u00d1\u0126": 18584, "leman": 18585, "eding": 18586, "\u0120170": 18587, "andy": 18588, "\u01201917": 18589, "logic": 18590, "\u0120spir": 18591, "\u0120spacing": 18592, "\u0120reflected": 18593, "entials": 18594, "specs": 18595, "\u0120Corp": 18596, "ocratic": 18597, "\u0120enjoyed": 18598, "utcnow": 18599, "/\")": 18600, "docker": 18601, "zes": 18602, "__)))": 18603, "\u0120chlor": 18604, "666": 18605, "\u0120Settings": 18606, "\u0120Meade": 18607, "\u0120determining": 18608, "friends": 18609, "Depend": 18610, "QPushButton": 18611, "\u0120CONTRACT": 18612, "FROM": 18613, "inel": 18614, "antee": 18615, "\u0120pse": 18616, "\u0120wiki": 18617, "\u0120wavelength": 18618, "\u0120(),": 18619, "\u0120CN": 18620, "\u0120Rome": 18621, "asting": 18622, "\u0120%%": 18623, "\u0120xx": 18624, "\u0120Through": 18625, "qualified": 18626, "1997": 18627, "merged": 18628, "authors": 18629, "\u00d1\u0124\u00d0\u00be": 18630, "\u0120Plugin": 18631, "\u0120officially": 18632, "\u00e5\u013d\u00bd": 18633, "fetchone": 18634, "\u0120Argent": 18635, ")})": 18636, "Ev": 18637, "Gm": 18638, "aton": 18639, "\u0120Sem": 18640, "\u0120BBC": 18641, "\u0120Daily": 18642, "actic": 18643, "annie": 18644, "326": 18645, "conds": 18646, "liest": 18647, "\u0120validity": 18648, "\u0120wheat": 18649, "\u0120legit": 18650, "\u0120dried": 18651, "GRAM": 18652, "\u0120Guide": 18653, "\u0120Elizabeth": 18654, "QQ": 18655, "WM": 18656, "yers": 18657, "\u0120\u0120\u010a\u0120\u0120\u0120": 18658, "eror": 18659, "\u0120dying": 18660, "\u0120todos": 18661, "0025": 18662, "conscious": 18663, "\u0120rt": 18664, "\u0120LLC": 18665, "oko": 18666, "reading": 18667, "\u0120dispatch": 18668, "lichen": 18669, "Excel": 18670, "\u0120boundaries": 18671, "traceback": 18672, "\u0120squad": 18673, "segments": 18674, "\u0120antibody": 18675, "KS": 18676, "\u0120Tool": 18677, "\u0120Fifth": 18678, "Rev": 18679, "\u0120Conf": 18680, "[:,:,": 18681, "\u0120utter": 18682, "\u0120behaviors": 18683, "\u0120Historic": 18684, "\u0120gravity": 18685, "\u0120temperatures": 18686, "Quest": 18687, "iop": 18688, "\u0120\u00ed\u0137": 18689, "\u0120Sie": 18690, "ected": 18691, "\u0120lets": 18692, "addresses": 18693, "\u0120neural": 18694, "Regression": 18695, "mapper": 18696, "randrange": 18697, "\u0120yields": 18698, "\u010a\u010a\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120": 18699, "^^": 18700, "\u0120gang": 18701, "\u0120gym": 18702, "asts": 18703, "\u0120aged": 18704, "\u0120suppress": 18705, "\u0120polling": 18706, "Testing": 18707, "\u0120Colon": 18708, "CONN": 18709, "\u0120greatly": 18710, "\u0120risks": 18711, "evin": 18712, "lapsed": 18713, "\u0120calculations": 18714, "\u0120acquisition": 18715, "because": 18716, "\u00e5\u0123": 18717, "omach": 18718, "trig": 18719, "\u0120disorder": 18720, "\u0120slave": 18721, "\u0120Left": 18722, "equality": 18723, "\u0120votre": 18724, "\u0120convinced": 18725, "Sensor": 18726, "Wc": 18727, "nos": 18728, "\u0120theories": 18729, "ication": 18730, "classification": 18731, "\u0120entrance": 18732, "ttle": 18733, "equals": 18734, "\u0120landing": 18735, "&\\": 18736, "kish": 18737, "\u0120deeper": 18738, "\u0120Six": 18739, "\u0120Script": 18740, "\u0120specification": 18741, "authenticated": 18742, "metic": 18743, "\u0120invited": 18744, "glish": 18745, "\u00e7\u0130\u00b0": 18746, "\u0120WHETHER": 18747, "Es": 18748, "VL": 18749, "online": 18750, "rend": 18751, "\u0120oven": 18752, "\u0120tower": 18753, "\u0120throws": 18754, "osome": 18755, "ivy": 18756, "\u0120Gib": 18757, "\u0120Us": 18758, "327": 18759, "\u0120complement": 18760, "Primary": 18761, "gridLayoutWidget": 18762, "Quantity": 18763, "iar": 18764, "\u0120inev": 18765, "',),": 18766, "ifi": 18767, "\u0120Fair": 18768, "\u0120Bang": 18769, "\u0120raising": 18770, "\u0120Insert": 18771, "\u01202048": 18772, "overlap": 18773, "\u0120Poly": 18774, "\u0120flowers": 18775, "Bitmap": 18776, "\u0120apparatus": 18777, "AX": 18778, "Room": 18779, "\u00e7\u00a1": 18780, "\u0120\u00d1\u0125": 18781, "\u0120oc": 18782, "\u0120bass": 18783, "opa": 18784, "versal": 18785, "\u0120smoking": 18786, "\u0120confused": 18787, "cores": 18788, "\u0120variations": 18789, "\u0120begun": 18790, "friendly": 18791, "Alignment": 18792, "constraints": 18793, "\u0120guarante": 18794, "Mart": 18795, "NF": 18796, "OH": 18797, "dag": 18798, "\u00e7\u0137": 18799, "seng": 18800, "']/": 18801, "\u0120advis": 18802, "\u0120disclaimer": 18803, "8080": 18804, "409": 18805, "\u0120hyp": 18806, "\u0120Sciences": 18807, "++++++++": 18808, "brew": 18809, "\u0120\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 18810, "\u0120dating": 18811, "\u0120grain": 18812, "\u0120assessed": 18813, "aca": 18814, "\u0120canonical": 18815, "subdir": 18816, "179": 18817, "masks": 18818, "\u0120Attributes": 18819, "\u0120latitude": 18820, "\u00e9\u0139\u00bb": 18821, "\u00e6\u00b5\u012d\u00e8\u00af\u0137": 18822, "wr": 18823, "\u00ec\u012a\u013a": 18824, "\u0120gpu": 18825, "\u0120meters": 18826, "\u0120HOLD": 18827, "resnet": 18828, "\u0120climb": 18829, "\u0120Var": 18830, "\u01201978": 18831, "Strip": 18832, "fghan": 18833, "!!!": 18834, "\u00e9\u00aa\u012e": 18835, "hattan": 18836, ".$$": 18837, "?\")": 18838, "AQ": 18839, "Mouse": 18840, "Stock": 18841, "talk": 18842, "always": 18843, "ifold": 18844, "\u0120beauty": 18845, "\u0120Root": 18846, "ubar": 18847, "\u0120chips": 18848, "\u0120newline": 18849, "323": 18850, "242": 18851, "\u0120approx": 18852, "displaystyle": 18853, "\u00e5\u00ae\u0140": 18854, "vehicle": 18855, "=_('": 18856, "cff": 18857, "\u00e5\u0137": 18858, "\u00e9\u0138": 18859, "\u0120forum": 18860, "abama": 18861, "\u0120anch": 18862, "\u0120printing": 18863, "\u0120dish": 18864, "lineEdit": 18865, "ITLE": 18866, "charset": 18867, "simplefilter": 18868, "jump": 18869, "\u00f0\u0138": 18870, "\u0120################################################################": 18871, "individual": 18872, "extended": 18873, "ITEM": 18874, "\u0120personnel": 18875, "UNCTION": 18876, "\u0120sorting": 18877, "kwds": 18878, "\u0120Turkey": 18879, "juana": 18880, "VOL": 18881, "\u0120dh": 18882, "\u0120hh": 18883, "\u0120hub": 18884, "\u0120lyr": 18885, "\u0120Tbsp": 18886, "queries": 18887, "\u01201933": 18888, "early": 18889, "spring": 18890, "306": 18891, "\u0120behalf": 18892, "\u00e7\u00bb\u0135\u00e6\u0140\u013e": 18893, "categorical": 18894, "BGR": 18895, "SCH": 18896, "iert": 18897, "jk": 18898, "uart": 18899, "ilog": 18900, "\u0120Ted": 18901, "\u0120Mother": 18902, "\u0120Len": 18903, "\u0120OAuth": 18904, "\u0120kin": 18905, "Recall": 18906, "1996": 18907, "grav": 18908, "flash": 18909, "ufficient": 18910, "\u0120probabilities": 18911, "Similarity": 18912, "Visible": 18913, "\u012007": 18914, "\u0120convention": 18915, "\u0120BUS": 18916, "\u0120Lar": 18917, "\u0120EL": 18918, "\u0120coin": 18919, "\u0120elder": 18920, "\u0120pathway": 18921, "\u00d0\u00be\u00d0\u00bd": 18922, "filenames": 18923, "\u0120studying": 18924, "domin": 18925, "\u0120setuptools": 18926, "\u0120drama": 18927, "SingleMuon": 18928, "\u0120bacteria": 18929, ")+'": 18930, "Zone": 18931, "bat": 18932, "\u0120march": 18933, "\u0120repair": 18934, "\u0120Match": 18935, "\u0120autos": 18936, "rappe": 18937, "cellular": 18938, "\u0120sends": 18939, "\u00e5\u00a4\u0126": 18940, "Calendar": 18941, "annotations": 18942, "\u0120Holy": 18943, "Schedule": 18944, "\u0120eastern": 18945, "\u0120Halifax": 18946, "JS": 18947, "irts": 18948, "quiet": 18949, "\u0120Ground": 18950, "555": 18951, "\u0120province": 18952, "273": 18953, "688": 18954, "\u0120interpreted": 18955, "Confirm": 18956, "Foot": 18957, "VIS": 18958, "instrument": 18959, "orable": 18960, "\u0120dm": 18961, "\u0120forty": 18962, "lder": 18963, "\u0120unlike": 18964, "\u0120paras": 18965, "REL": 18966, "\u0120appellant": 18967, "Username": 18968, "\u0120structural": 18969, "\u0120limitation": 18970, "\u0120responded": 18971, "\u0120dirname": 18972, "\u0120analyze": 18973, "repeated": 18974, "\u0120Officer": 18975, "Math": 18976, "oled": 18977, "\u0120og": 18978, "\u0120nc": 18979, "\u0120Lem": 18980, "probe": 18981, "creator": 18982, "States": 18983, "LEASE": 18984, "\u0120addressed": 18985, "\u0120corps": 18986, "\u0120Photo": 18987, "enny": 18988, "nesota": 18989, "\u0120casual": 18990, "SYS": 18991, "separator": 18992, "*/": 18993, "etary": 18994, "rises": 18995, "\u0120Ped": 18996, "\u0120Gil": 18997, ").\\": 18998, "ATH": 18999, "\u0120scrap": 19000, "258": 19001, "\u0120finance": 19002, "99999999": 19003, "Canvas": 19004, "\u0120Internationalization": 19005, "\u0120Democrats": 19006, "\u0120Schema": 19007, "PCR": 19008, "geld": 19009, "\u0120fiction": 19010, "throw": 19011, "\u0120Cell": 19012, "\u0120Gtk": 19013, "\u0120comparing": 19014, "inking": 19015, "'],'": 19016, "\u0120Called": 19017, "\u0120beliefs": 19018, "DOC": 19019, "\u0120stdin": 19020, "CREEN": 19021, "\u0120psychology": 19022, "\u0120universal": 19023, "\u0120Scotland": 19024, "\u0120ion": 19025, "isy": 19026, "\u0120bull": 19027, "iche": 19028, "\u0120gp": 19029, "\u0120stabil": 19030, "\u0120CEO": 19031, "\u0120Writ": 19032, "\u0120Oregon": 19033, "STO": 19034, "spam": 19035, "Condition": 19036, "295": 19037, "intersection": 19038, "hydro": 19039, "\u0120constantly": 19040, "QPalette": 19041, "\u0120occasionally": 19042, "Have": 19043, "Im": 19044, "San": 19045, "\u00f0\u0135": 19046, "\u0120themes": 19047, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 19048, "\u0120Tk": 19049, "\u0120Boy": 19050, "\u0120shake": 19051, "])/": 19052, "=\"\\": 19053, "\u0120VM": 19054, "retched": 19055, "\u0120forecast": 19056, "\u0120labeled": 19057, "275": 19058, "\u0120bike": 19059, "\u0120milit": 19060, "igest": 19061, "\u0120rm": 19062, "\u0120ruling": 19063, "assador": 19064, "ERE": 19065, "\u0120Ven": 19066, "\u0120trunk": 19067, "\u0120supplies": 19068, "\u0120Univers": 19069, "transactions": 19070, "}})": 19071, "\u0120Level": 19072, "\u0120sentiment": 19073, "ursing": 19074, "\u0120engineer": 19075, "\u0120tongue": 19076, "Four": 19077, "Mich": 19078, "lf": 19079, "aly": 19080, "\u0120dup": 19081, "\u0120Could": 19082, "\u0120CNN": 19083, "\u0120shots": 19084, "igne": 19085, "\u0120counting": 19086, "\u0120slip": 19087, "popup": 19088, "\u0120releases": 19089, "\u0120complexity": 19090, "264": 19091, "Bra": 19092, "Used": 19093, "das": 19094, "\u0120cid": 19095, "0101": 19096, "ugs": 19097, "RESP": 19098, "\u0120shoulders": 19099, "\u0120decline": 19100, "\u0120Trade": 19101, "\u0120Olympics": 19102, "\u0120augment": 19103, "SMS": 19104, "ghan": 19105, "\u0142\u00e7\u00ba": 19106, "\u0120fatal": 19107, "aden": 19108, "\u0120Based": 19109, "\u0120Dat": 19110, "\u0120URI": 19111, "\u0120preci": 19112, "joined": 19113, "\u0120surfaces": 19114, "fragment": 19115, "\u0120characteristic": 19116, "\u0120IDs": 19117, "Neg": 19118, "\u00e5\u00b0\u0128": 19119, "\u00c3\u00bamer": 19120, "\u0120laboratory": 19121, "\u00e6\u0136\u00b9": 19122, "ADDRESS": 19123, "\u0120contemporary": 19124, "\u0120Comiss\u00c3\u00a3o": 19125, "olesterol": 19126, "Brit": 19127, "Em": 19128, "Fri": 19129, "\u00e0\u00a6": 19130, "\u0120af": 19131, "\u0120Mit": 19132, "\u0120notion": 19133, "\u0120Hence": 19134, "Chat": 19135, "324": 19136, "\u0120xmlns": 19137, "mutations": 19138, "\u0120einer": 19139, "regularizer": 19140, "\u00e8\u00b0\u0125": 19141, "\u0120amino": 19142, "\"')": 19143, "bas": 19144, "sis": 19145, "vens": 19146, "\u0120tc": 19147, "\u0120fallen": 19148, "ndim": 19149, "\u0120rename": 19150, "\u0120ik": 19151, "xticks": 19152, "important": 19153, "\u0120encounter": 19154, "\u0120Info": 19155, "Errors": 19156, "discount": 19157, "LOB": 19158, "\u0120patent": 19159, "explo": 19160, "\u0120Poland": 19161, "Represent": 19162, "\u0120panic": 19163, "\u0120adjusted": 19164, "MN": 19165, "Marg": 19166, "could": 19167, "sav": 19168, "\u00d9\u0128": 19169, "throp": 19170, "('{}": 19171, "\u0120Elect": 19172, "\u0120Enum": 19173, "\u0120comedy": 19174, "\u0120lett": 19175, "phizzle": 19176, "\u0120ray": 19177, "locate": 19178, "221": 19179, "229": 19180, "issippi": 19181, "\u0120locally": 19182, "NOWN": 19183, "\u0120attacked": 19184, "\u0120funny": 19185, "aurants": 19186, "ncia": 19187, "\u0120gods": 19188, "\u0120convenient": 19189, "\u0120FILE": 19190, ")['": 19191, ">[": 19192, "Hard": 19193, "MY": 19194, "Mus": 19195, "uom": 19196, "))),": 19197, "getCurrent": 19198, "iber": 19199, "\u0120Kansas": 19200, "ONSE": 19201, "\u0120partially": 19202, "\u0120103": 19203, "\u0120trailing": 19204, "ROW": 19205, "building": 19206, "\u0120optimization": 19207, "successful": 19208, "\u0120consisting": 19209, "\u0120improvements": 19210, "\u0120Palestinian": 19211, "\u00e6\u013d\u00b4\u00e6\u0138\u00b0": 19212, "bag": 19213, "tos": 19214, "altern": 19215, "\u0120dialect": 19216, "\u0120Single": 19217, "\u0120Alec": 19218, "\u0120Bible": 19219, "\u010d\u010a\u010d\u010a\u010d\u010a\u010d": 19220, "\u0120testified": 19221, "icker": 19222, "aude": 19223, "prints": 19224, "Std": 19225, "0003": 19226, "subscribe": 19227, "\u0120\u00c2\u00b0": 19228, "nny": 19229, "\u0120liberal": 19230, "occup": 19231, "GV": 19232, "dia": 19233, "\u00ce\u00bc": 19234, "\u0120cant": 19235, "\u0120sans": 19236, "abling": 19237, "\u0120240": 19238, "placed": 19239, "\u0120Dutch": 19240, "\u0120Wind": 19241, "\u0120rabb": 19242, "\u0120overcome": 19243, "\"]),": 19244, "993": 19245, "\u0120carri": 19246, "rollment": 19247, "\u0120Interest": 19248, "levance": 19249, "\u0120oxid": 19250, "\u0120tonight": 19251, "WINDOW": 19252, "July": 19253, "jer": 19254, "lvl": 19255, "tour": 19256, "inations": 19257, "chip": 19258, "\u0120Fra": 19259, "\u0120BOO": 19260, "\u0120proven": 19261, "asta": 19262, "\u0120YouTube": 19263, "\u0120carrier": 19264, "\u0120centuries": 19265, "\u0120Associ": 19266, "\u0120constitutional": 19267, "\u0120uncertainty": 19268, "/\"+": 19269, "Si": 19270, "\u0120ng": 19271, "\u0120Batt": 19272, "\u00e2\u0122\u012d": 19273, "\u0120Ron": 19274, "\u0120Gaussian": 19275, "astro": 19276, "icking": 19277, "\u0120regulations": 19278, "Union": 19279, "\u0120Collection": 19280, "\u00e3\u0125\u00bc\u00e3\u0125": 19281, "\u0120OTHERWISE": 19282, "\u0120gauge": 19283, "PositiveIntegerField": 19284, "-',": 19285, "^+^": 19286, "qc": 19287, "xsl": 19288, "inating": 19289, "\u0120Amb": 19290, "\u0120Corn": 19291, "strand": 19292, "016": 19293, "\u0120{'$": 19294, "337": 19295, "\u0120Country": 19296, "\u00e8\u00bf\u013d\u00e8\u00a1\u012e": 19297, "\u0120Ukrainian": 19298, "Ns": 19299, "Russ": 19300, "\u0120\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd": 19301, "inha": 19302, "\u0120sheets": 19303, "\u0120logo": 19304, "...'": 19305, "\u0120extends": 19306, "\u0120]),": 19307, "\u0120[\"-": 19308, "tablename": 19309, "}^{(": 19310, "\u0120Prince": 19311, "Slider": 19312, "Je": 19313, "tom": 19314, "\u0120tiles": 19315, "\u0120aimed": 19316, "\u0120cattle": 19317, "\u0120wrest": 19318, "\u0120iso": 19319, "riel": 19320, "\u0120MC": 19321, "0123": 19322, "preds": 19323, "\u0120Stir": 19324, "apeut": 19325, "starting": 19326, "806": 19327, "\u0120availability": 19328, "267": 19329, "\u0120shorter": 19330, "\u0120harder": 19331, "\u0120secretary": 19332, "CIAL": 19333, "\u0120Jean": 19334, "MINIAODSIM": 19335, "\u0120CONFIG": 19336, "\u00e5\u0127\u0125\u00e7\u00b4\u0142": 19337, "\u0120simultaneously": 19338, "mates": 19339, "uario": 19340, "\u0120wid": 19341, "\u0120rural": 19342, "\u0120alien": 19343, "\u0120observe": 19344, "velt": 19345, "\u0120104": 19346, "grey": 19347, "succ": 19348, "\u0120voices": 19349, "\u0120Wolfe": 19350, "CLASSES": 19351, "Dot": 19352, "NM": 19353, "]=='": 19354, "^-": 19355, "mirror": 19356, "\u00c3\u00bb": 19357, "\u0120reuse": 19358, "\u0120nombre": 19359, "uls": 19360, "\u0120ash": 19361, "([-": 19362, "\u0120blame": 19363, "empt": 19364, "describe": 19365, "\u0120engines": 19366, "\u0120Jacob": 19367, "214": 19368, "\u0120CC": 19369, "\u0120Blo": 19370, "\u0120prosec": 19371, "protected": 19372, "\u0120substance": 19373, "131": 19374, "loyd": 19375, "\u00e6\u013e\u0141": 19376, "\u0120chairman": 19377, "\u0120knee": 19378, "\u00e9\u0136\u013b": 19379, "TED": 19380, "WF": 19381, "olly": 19382, "pem": 19383, "\u0120Cut": 19384, "\u0120consp": 19385, "CTYPE": 19386, "libs": 19387, "eroid": 19388, "Dev": 19389, "\u0120\u00c3\u00b6": 19390, "TeX": 19391, "\u0120USB": 19392, "\u0120cmds": 19393, "Scroll": 19394, "\u0120Agent": 19395, "\u00e5\u00b9\u00b6": 19396, "Skip": 19397, "\u0142\u00e7\u00ba\u00b7": 19398, "Europe": 19399, "Sales": 19400, "nw": 19401, "\u00c4\u0123": 19402, "\u0120crypt": 19403, "\u0120lift": 19404, "\u0120eleg": 19405, "('../": 19406, "\u0120prints": 19407, "isect": 19408, "\u01205000": 19409, "weak": 19410, "vely": 19411, "codec": 19412, "works": 19413, "184": 19414, "186": 19415, "bye": 19416, "\u0120Coll": 19417, "\u0120monthly": 19418, "tracking": 19419, "Reading": 19420, "\u0120READ": 19421, "\u0120wondering": 19422, "INSTALL": 19423, "Authorization": 19424, "Statistics": 19425, "\u00e7\u00b4\u00a2": 19426, "\u0120poetry": 19427, "Merge": 19428, "Mid": 19429, "Watch": 19430, "iB": 19431, "wild": 19432, "\u0120wis": 19433, "\u0120mn": 19434, "\u0120nations": 19435, "\u0120AB": 19436, "\u0120armed": 19437, "mini": 19438, "Constant": 19439, "efe": 19440, "ALIGN": 19441, "\u0120reli": 19442, "\u0120belt": 19443, "\u0120esta": 19444, "footer": 19445, "\u0120museum": 19446, "\u0120TORT": 19447, "\u0120Lu": 19448, "\u0120coat": 19449, "\u00d0\u00b8\u00d0\u00bd": 19450, "\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd\u00ef\u00bf\u00bd": 19451, "\u0120authorized": 19452, "\u0120Region": 19453, "labeled": 19454, "looking": 19455, "\u0120MagicMock": 19456, "detach": 19457, "\u0120sliced": 19458, "\u0120throat": 19459, "\u010d\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 19460, "itud": 19461, "\u0120oste": 19462, "\u0120Following": 19463, "\u0120Dest": 19464, "manded": 19465, "786": 19466, "\u0120moderate": 19467, "SYSTEM": 19468, "\u0120flexible": 19469, "\u0120infected": 19470, "\u0120sustain": 19471, "\u00ec\u0126\u013e": 19472, "PROCESS": 19473, ">(": 19474, "Bank": 19475, "FONT": 19476, "die": 19477, "arrays": 19478, "\u0120toxic": 19479, "()-": 19480, "lyn": 19481, "apor": 19482, "\u0120vic": 19483, "\u0120PCR": 19484, "\u0120unf": 19485, "Charge": 19486, "\u0120spell": 19487, "osevelt": 19488, "azard": 19489, "\u0120Allow": 19490, "richt": 19491, "\"}.": 19492, "\u0120horror": 19493, "\u0120signaling": 19494, "Measure": 19495, "\u00e8\u00ae\u00a4": 19496, "\u0120Systems": 19497, "\u00e5\u00b8\u00b8": 19498, "planes": 19499, "\u00e7\u00ba\u0142\u00e7\u00ba\u00b7": 19500, "\u0120Help": 19501, "\u00e7\u00a7\u00b0": 19502, "\u0120divisor": 19503, ">&": 19504, "[%": 19505, "san": 19506, "\u0120cited": 19507, "\u0120wise": 19508, "\u0120111": 19509, "\u0120vivo": 19510, "\u0120residence": 19511, "\u0120Symbol": 19512, "\u0120pilot": 19513, "8000": 19514, "CPU": 19515, "MON": 19516, "\u00e6\u00b7": 19517, "\u0120tau": 19518, "stroke": 19519, "amo": 19520, "\u0120Ont": 19521, "shaped": 19522, "\u0120myst": 19523, "\u0120substit": 19524, "ashing": 19525, "\u0120weekly": 19526, "\u0120Notes": 19527, "\u0120promoted": 19528, "\u0120rolling": 19529, "\u0120burned": 19530, "\u0120aber": 19531, "isol": 19532, "\u0120mM": 19533, "\u0120mild": 19534, "thumb": 19535, "\u0120perception": 19536, "dicts": 19537, "aska": 19538, "Threshold": 19539, "141": 19540, "OTAL": 19541, "unto": 19542, "IPV": 19543, "\u0120lengths": 19544, "limited": 19545, "\u0120violation": 19546, "\u0120Parks": 19547, "Pal": 19548, "SMB": 19549, "cg": 19550, "dj": 19551, "rpt": 19552, "roit": 19553, "verty": 19554, "\u012004": 19555, "\u0120consequence": 19556, "keley": 19557, "\u0120dozen": 19558, "wealth": 19559, "initions": 19560, "1994": 19561, "arsing": 19562, "overflow": 19563, "\u0120breakfast": 19564, "\u0120realm": 19565, "\u0120precise": 19566, "\u0120Jimmy": 19567, "Syntax": 19568, "\u00e5\u00b7\u00b2": 19569, "Execution": 19570, "\u0120enhanced": 19571, "VED": 19572, "targ": 19573, "otimes": 19574, "ching": 19575, "\u0120seeds": 19576, "\u0120EEC": 19577, "\u0120chains": 19578, "\u0120opponent": 19579, "\u0120agenda": 19580, "1990": 19581, "329": 19582, "umptions": 19583, "784": 19584, "pires": 19585, "LOCAL": 19586, "\u0120Combine": 19587, "fund": 19588, "\u0120tube": 19589, "ono": 19590, "\u0120cipher": 19591, "arl": 19592, "\u0120f\u00c3\u00b6r": 19593, "\u0120synchron": 19594, "\u0120\"&": 19595, "\u0120champion": 19596, "contour": 19597, "nox": 19598, "\u0120Context": 19599, "\u0120slide": 19600, "\u0120physics": 19601, "magic": 19602, "\u0120lifted": 19603, "\u0120Visual": 19604, "\u0120turtle": 19605, "CrossRef": 19606, "\u0120adequate": 19607, "SING": 19608, "TAB": 19609, "icons": 19610, "\u0120SA": 19611, "\u0120cock": 19612, "isen": 19613, "logged": 19614, "196": 19615, "1995": 19616, "bras": 19617, "Disc": 19618, "\u0120declare": 19619, "\u0120pulse": 19620, "\u0120footballers": 19621, "\u00e5\u0143\u013a\u00e5\u013e\u00a8": 19622, "\u0120Consider": 19623, "\u0120Atlantic": 19624, "!\",": 19625, "samp": 19626, "inplace": 19627, "\u0120tissues": 19628, "\u0120flower": 19629, "\u0120horm": 19630, "\u0120ghost": 19631, "\u0120stomach": 19632, "\u0120Raw": 19633, "defer": 19634, "\u0120plates": 19635, ".\"),": 19636, "\u0120Know": 19637, "\"]/": 19638, "705": 19639, "linewidth": 19640, "\u0120selector": 19641, "Special": 19642, "squared": 19643, "YES": 19644, "\\,": 19645, "lh": 19646, "lings": 19647, "\u0120\u00ea\u00b0": 19648, "ouri": 19649, "\u0120Scal": 19650, "iface": 19651, "#######": 19652, "opener": 19653, "phones": 19654, "ARR": 19655, "223": 19656, "807": 19657, "\u0120\u00c3\u00ba": 19658, "income": 19659, "FAIL": 19660, "\u0120explains": 19661, "\u0120Feature": 19662, "'^$',": 19663, "\u0120appointment": 19664, "animation": 19665, "EF": 19666, "Ital": 19667, "rings": 19668, "\u00c2\u00a7": 19669, "atable": 19670, "\u0120cmp": 19671, "\u0120pounds": 19672, "\u0120osc": 19673, "rade": 19674, "\u0120deals": 19675, "\u0120Dra": 19676, "\u0120Rating": 19677, "\u010a\u0120\u010a\u0120\u0120\u0120": 19678, "\u0120105": 19679, "...]": 19680, "seqs": 19681, "\u00d0\u00bb\u00d0\u00b0": 19682, "\u0120waters": 19683, "\u0120Administration": 19684, "XYZ": 19685, "larg": 19686, "vine": 19687, "\u0120################################": 19688, "htm": 19689, "\u0120prolif": 19690, "\u0120compiled": 19691, "\u0120compressed": 19692, "comfort": 19693, "0004": 19694, "\u0120knife": 19695, "\u0120\u00c3\u00a5": 19696, "\u0120associate": 19697, "\u010a\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109\u0109": 19698, "methyl": 19699, "NI": 19700, "PUS": 19701, "Ratio": 19702, "pitti": 19703, "held": 19704, "\u0120incoming": 19705, "\u0120batter": 19706, "\u0120Dall": 19707, "\u0120prosecut": 19708, "\u0120shoes": 19709, "elli": 19710, "\u0120401": 19711, "\u0120zi": 19712, "\u0120trap": 19713, "\u00e5\u012a\u00b6": 19714, "Country": 19715, "reedy": 19716, "Launch": 19717, "\u0120holes": 19718, "DY": 19719, "GM": 19720, "PARE": 19721, "Sel": 19722, "Today": 19723, "vr": 19724, "\u00e8\u0123": 19725, "stmt": 19726, "alone": 19727, "rock": 19728, "urers": 19729, "\u0120Tony": 19730, "iev": 19731, "INDEX": 19732, "\u0120phases": 19733, "iteral": 19734, "LOAT": 19735, "\u010d\u010a\u0109\u0120\u0120\u0120": 19736, "\u00d1\u0122\u00d0\u00b5": 19737, "Loading": 19738, "setuptools": 19739, "\u0120referring": 19740, "\u0120hopes": 19741, "Curve": 19742, "sects": 19743, "Complete": 19744, "\u0120towns": 19745, "ChoiceField": 19746, "TARGET": 19747, "hdr": 19748, "\u0120m\u00c3\u00a9": 19749, "\u0120Cat": 19750, "\u0120Ball": 19751, "\u01201974": 19752, "\u0120spoken": 19753, "\u0120sizePolicy": 19754, "\u0120connecting": 19755, "doo": 19756, "retrieve": 19757, "descr": 19758, "\u0120literally": 19759, "\u0120Philip": 19760, "\u0120gradually": 19761, "\u00e8\u00ae\u00be\u00e7\u00bd\u00ae": 19762, "()['": 19763, "__'": 19764, "\u0120REST": 19765, "\u0120scaled": 19766, "mature": 19767, "\u0120offsets": 19768, "\u0120comme": 19769, "\u0120\u00c3\u012b": 19770, "\u0120builtin": 19771, "\u0120Hollywood": 19772, "\u0120Empty": 19773, "\u0120manufacturing": 19774, "Got": 19775, "Occ": 19776, "vault": 19777, "\u0120\u00e8\u0130\u00b7\u00e5\u0131\u0138": 19778, "\u0120wing": 19779, "\u0120collapse": 19780, "\u0120numeric": 19781, "\u0120authenticate": 19782, "\u010d\u010a\u0120\u0120\u0120\u0120\u010d": 19783, "Support": 19784, "\u0120engage": 19785, "\u0120Operation": 19786, "receive": 19787, "\u0120ruled": 19788, "\u0120bottleneck": 19789, "critical": 19790, "\u00e5\u0143\u0139\u00e7\u00ac\u00a6\u00e4\u00b8\u00b2": 19791, "City": 19792, "Lab": 19793, "cro": 19794, "lined": 19795, "\u0120112": 19796, "\u0120Mode": 19797, "\u0120Bru": 19798, "\u0120RGB": 19799, "ONLY": 19800, "ITID": 19801, "refs": 19802, "newaxis": 19803, "\u0120edited": 19804, "\u0109\u0109\u0109\u0109\u0109": 19805, "\u00e6\u0138\u00b0\u00e9\u0139\u00bb": 19806, "polygon": 19807, "345": 19808, "KB": 19809, "Nor": 19810, "_*": 19811, "dtypes": 19812, "itarian": 19813, "\u0120frappe": 19814, "\u0120dd": 19815, "andra": 19816, "\u0120Pour": 19817, "**]{},": 19818, "\u0120orm": 19819, "\u0120preference": 19820, "\u0120Thank": 19821, "\u0120zoom": 19822, "oths": 19823, "errno": 19824, "ViewSet": 19825, "\u00c3\u00a1s": 19826, "\u0120governor": 19827, "\u0120infinite": 19828, "\u0120accessible": 19829, "\u0120-----": 19830, "Variables": 19831, "\u0120pulling": 19832, "DjangoTemplates": 19833, "German": 19834, "*[@": 19835, "Capture": 19836, "Ty": 19837, "\u0132\u013e": 19838, "\u0120muit": 19839, "\u0120#'": 19840, "oda": 19841, "acao": 19842, "\u0120Ot": 19843, "\u0120cheap": 19844, "\u0120dirty": 19845, "\u00d0\u00ba\u00d0\u00b8": 19846, "UMENT": 19847, "\u0120guidelines": 19848, "\u0120perturb": 19849, "nexth": 19850, "\u0120accordance": 19851, "Gre": 19852, "Sorry": 19853, "\u0120ARE": 19854, "tections": 19855, "upgrade": 19856, "\u0120enforcement": 19857, "\u0120Zero": 19858, "Compute": 19859, "\u0120geo": 19860, "\u0120conviction": 19861, "\u0120steam": 19862, "\u0120emerged": 19863, "\u00e8\u00bd\u00bd": 19864, "\u0120Several": 19865, "HD": 19866, "xFF": 19867, "\u0120wel": 19868, "\u0120Solve": 19869, "ptic": 19870, "\u01201973": 19871, "0005": 19872, "\u0120primer": 19873, "solid": 19874, "\u0120Online": 19875, "\u0120badly": 19876, "makers": 19877, "EAfg": 19878, "\u0120decoded": 19879, "aternion": 19880, "tup": 19881, "erance": 19882, "\u0120SSL": 19883, "setitem": 19884, "\u0120Ensure": 19885, "\u0120Vi": 19886, "corner": 19887, "\u00c3\u00a1rio": 19888, "\u00e6\u012a\u0133": 19889, "\u0120pkt": 19890, "\u00e2\u00ac\u013e": 19891, "\u0120Maryland": 19892, "!!!!!!!!": 19893, "\u0120abandoned": 19894, "\u0120enormous": 19895, "Disk": 19896, "Route": 19897, "dar": 19898, "\u0120._": 19899, "inical": 19900, "\u0120fal": 19901, "\u0120eager": 19902, "rik": 19903, "\u0120Walter": 19904, "profiles": 19905, "\u0120Chap": 19906, "\u0120creator": 19907, "dfs": 19908, "286": 19909, "umes": 19910, "\u0120targeted": 19911, "\u0120validated": 19912, "\u0120existed": 19913, "metaclass": 19914, "Calo": 19915, "\u0120------": 19916, "Avg": 19917, "\u0120DateTime": 19918, "\u0120anxious": 19919, "\u0120guarantee": 19920, "broadcast": 19921, "sure": 19922, "tod": 19923, "\u0120census": 19924, "\u0120prag": 19925, "\u0120bron": 19926, "\u0120115": 19927, "\u0120Sin": 19928, "\u0120SPE": 19929, "\u0120Az": 19930, "\u0120Close": 19931, "\u0120FDR": 19932, "\u0120Host": 19933, "fts": 19934, "\u0120Stone": 19935, "\u0120Property": 19936, "\u0120childhood": 19937, "\u0120approached": 19938, "\u0120darkness": 19939, "\u0120consumers": 19940, "\u0120AssertionError": 19941, "\u0120Confederate": 19942, "parametri": 19943, "Age": 19944, "Bundle": 19945, "gro": 19946, "\u0120ears": 19947, "\u0120NEW": 19948, "shall": 19949, "\u0120Jane": 19950, "iese": 19951, "\u0120rode": 19952, "\u0120pointing": 19953, "\u0120rendering": 19954, "\u0120Harris": 19955, "hora": 19956, "\u0120Engineering": 19957, "CAD": 19958, "FRAME": 19959, "vstring": 19960, "\u0120s\u00c3\u00a5": 19961, "\u0120175": 19962, "peat": 19963, "ulum": 19964, "\u0120chi": 19965, "###########": 19966, "\u0120controlling": 19967, "\u01201972": 19968, "filer": 19969, "([^": 19970, "::::": 19971, "USB": 19972, "\u0120variants": 19973, "\u0120rounds": 19974, "NotFoundError": 19975, "passed": 19976, "'\")": 19977, ".).": 19978, "Owner": 19979, "hexd": 19980, "iters": 19981, "\u0120Afghan": 19982, "amon": 19983, "\u0120rx": 19984, "avors": 19985, "\u0120Kn": 19986, "\u0120poverty": 19987, "\u0120offensive": 19988, "995": 19989, "173": 19990, "290": 19991, "\u0120wheels": 19992, "\u0120expecting": 19993, "\u0120influenced": 19994, "MU": 19995, "MENU": 19996, "easy": 19997, "\u0120convolution": 19998, "\u0120ya": 19999, "':[": 20000, "\u0120colored": 20001, "\u0120disorders": 20002, "eyond": 20003, "inside": 20004, "\u0120Alabama": 20005, "\u0120letting": 20006, "\u0120McG": 20007, "Neighb": 20008, "\u0120Market": 20009, "\u0120touched": 20010, "\u0120championship": 20011, "\"<": 20012, "James": 20013, "tow": 20014, "\u00c3\u012b": 20015, "\u0120dice": 20016, "olute": 20017, "\u0120Tal": 20018, "oping": 20019, "\u0120promp": 20020, "\u0120xl": 20021, "\u0120discrete": 20022, "\u0120scar": 20023, "************": 20024, "\u0120legacy": 20025, "\u0120memories": 20026, "\u0120magnet": 20027, "ustry": 20028, "ragon": 20029, "\u0120replacing": 20030, "equiv": 20031, "\u0120Korean": 20032, "\u0120philosoph": 20033, "\u0120lymph": 20034, "tls": 20035, "\u0120tim": 20036, "\u0120ren": 20037, "\u0120rend": 20038, "\u0120Sound": 20039, "\u0120Chen": 20040, "\u0120PH": 20041, "\u0120Virtual": 20042, "\u0120cheek": 20043, "\u0120angular": 20044, "ordinate": 20045, "Creation": 20046, "\u0120Sydney": 20047, "\u0120Authors": 20048, "\u00e7\u00ba\u00bf": 20049, "bulk": 20050, "\u0120Lawrence": 20051, "pherical": 20052, "\u0120environments": 20053, "Legend": 20054, "215": 20055, "French": 20056, "Hidden": 20057, "Solve": 20058, "wen": 20059, "\u00c5\u012f": 20060, "\u0120han": 20061, "\u0120vault": 20062, "\u0120Billy": 20063, "\u0120GL": 20064, "pars": 20065, "='+": 20066, "='\\": 20067, "listener": 20068, "beit": 20069, "\u0120Clark": 20070, "masked": 20071, "URLField": 20072, "NODE": 20073, "iliary": 20074, "\u0120salary": 20075, "\u0120threatened": 20076, "ocolate": 20077, "Sal": 20078, "TK": 20079, "gpkg": 20080, "\u00ec\u013e": 20081, "\u0120Abb": 20082, "\u0120Hong": 20083, "ocs": 20084, "\u0120:'": 20085, "cedure": 20086, "444": 20087, "\u0120declaration": 20088, "\u00e5\u00ba\u0135": 20089, "\u0120mutation": 20090, "\u0120PointCast": 20091, "Available": 20092, "\u0120scenes": 20093, "\u00e3\u0125\u00bc\u00e3\u0124": 20094, "SecurityMiddleware": 20095, "\u0120fragments": 20096, "*[": 20097, "RD": 20098, "\u00e5\u0125": 20099, "edy": 20100, "\u0120Self": 20101, "\u0120Por": 20102, "eping": 20103, "193": 20104, "ICS": 20105, "\u0120distant": 20106, "\u0120requiring": 20107, "\u0120receives": 20108, "\u0120severity": 20109, "\u0120treatments": 20110, "1011": 20111, "\u0120repeatedly": 20112, "\u00e8\u00ae\u00a1\u00e7\u00ae\u0139": 20113, "$)": 20114, "cit": 20115, "pit": 20116, "pct": 20117, "\u00d8\u00b1": 20118, "degrees": 20119, "eling": 20120, "\u0120lig": 20121, "\u0120lung": 20122, "\u0120beings": 20123, "uddy": 20124, "\u0120loans": 20125, "\u0120{}\\": 20126, "\u0120longitude": 20127, "bsites": 20128, "\u0120bench": 20129, "\u0120campus": 20130, "Remote": 20131, "\u00e2\u0138\u0134\u00e2\u0138\u0134\u00e2\u0138\u0134\u00e2\u0138\u0134": 20132, "orescence": 20133, "\u0120Kultur": 20134, "duplicate": 20135, "eenth": 20136, "kov": 20137, "stim": 20138, "\u0120bay": 20139, "\u0120bags": 20140, "\u0120Abs": 20141, "terior": 20142, "\u0120Rot": 20143, "\u0120races": 20144, "\u0120suicide": 20145, "\u0120logout": 20146, "\u0120distributions": 20147, "485": 20148, "markers": 20149, "Statement": 20150, "weighted": 20151, "\u0120Minnesota": 20152, "\u0120diagno": 20153, "\u0120newspapers": 20154, "\u0120injection": 20155, "\u0120municipal": 20156, "UAL": 20157, "WITH": 20158, "\u0120dressed": 20159, "idades": 20160, "\u0120CLI": 20161, "\u0120defensive": 20162, "ordinary": 20163, "\u0120outline": 20164, "\u01201914": 20165, "hero": 20166, "\u00e5\u0127\u00a8": 20167, "Regular": 20168, "cvt": 20169, "\u0120collective": 20170, "\u0120precisely": 20171, "Rank": 20172, "\\{": 20173, "\\|": 20174, "iu": 20175, "\u00e6\u0126": 20176, "atz": 20177, "elapsed": 20178, "\u0120Tar": 20179, "templ": 20180, "resume": 20181, "\u0120clouds": 20182, "\u0120traces": 20183, "bugs": 20184, "\u0120democracy": 20185, "\u0120separately": 20186, "\u0120callbacks": 20187, "Slot": 20188, "\u0120accompanied": 20189, "NEXT": 20190, "Ring": 20191, "}=\\": 20192, "\u00e7\u0141": 20193, "sta": 20194, "dee": 20195, "\u0120resemb": 20196, "\u0120Tok": 20197, "omorph": 20198, "compiler": 20199, "\u0120generations": 20200, "\u0120apple": 20201, "ahoma": 20202, "Registry": 20203, "\u0120errno": 20204, "peaks": 20205, "\u0120delayed": 20206, "Estim": 20207, "FILTER": 20208, "\u0120\u00cc\u0123": 20209, "reddit": 20210, "\u0120KeyboardInterrupt": 20211, "cannot": 20212, "\u0120lake": 20213, "\u0120lucky": 20214, "\u0120atomic": 20215, "\u0120Vin": 20216, "ANK": 20217, "\u0120flush": 20218, "being": 20219, "\u0120curves": 20220, "VERT": 20221, "insertion": 20222, "\u0120Private": 20223, "\u0120affects": 20224, "\u0120districts": 20225, "\u0120injuries": 20226, "funcs": 20227, "\u00d0\u00b0\u00d1\u0124\u00d1\u012e": 20228, "\u00e5\u013d\u00be\u00e7\u012b\u0129": 20229, "QCD": 20230, "uant": 20231, "\u0120\u00c5": 20232, "ingham": 20233, "\u0120rewards": 20234, "\u0120Fel": 20235, "\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u0120\u010a\u0120\u0120\u0120\u0120\u0120\u0120\u0120": 20236, "\u0120namedtuple": 20237, "listed": 20238, "\u0120intense": 20239, "checkout": 20240, "\u0120skull": 20241, "\u0120qs": 20242, "\u0120Additionally": 20243, "\u0120freeze": 20244, "canonical": 20245, "\u0120computers": 20246, "\u0120shopping": 20247, "\u0120prayer": 20248, "\u0120puzzle": 20249, "\u0120steady": 20250, "ComboBox": 20251, "\u0120gently": 20252, "\u0120Dif": 20253, "ordan": 20254, "013": 20255, "iaz": 20256, "\u0120scal": 20257, "iox": 20258, "\u0120peas": 20259, "ngthen": 20260, "608": 20261, "ASC": 20262, "}}{": 20263, "\u0120descent": 20264, "\u00c3\u00a7o": 20265, "\u0120Amendment": 20266, "\u0120bedroom": 20267, "\u0120briefly": 20268, "Robert": 20269, "\u00e5\u00af\u00b9\u00e8\u00b1\u00a1": 20270, "\u0120varying": 20271, "lct": 20272, "vised": 20273, "\u0120mul": 20274, "elly": 20275, "agu": 20276, "resid": 20277, "\u010d\u010a\u010d\u010a\u010d\u010a\u0120\u0120\u0120": 20278, "\u0120partly": 20279, "\u0120programme": 20280, "naire": 20281, "\u0120Roosevelt": 20282, "renderer": 20283, "Creates": 20284, "Digite": 20285, "\u00e9\u0137\u00bf": 20286, "\u00e7\u00b3\u00bb": 20287, "Air": 20288, "AMP": 20289, "motor": 20290, "\u0120\"|": 20291, "\u0120gam": 20292, "\u0120shirt": 20293, "\u01201916": 20294, "moz": 20295, "EDIT": 20296, "\u0120avo": 20297, "\u0120triangle": 20298, "}^{+": 20299, "\u0120reviewed": 20300, "\u0120Rhodry": 20301, "440": 20302, "Sig": 20303, "efficient": 20304, "\u00e6\u00bb": 20305, "meas": 20306, "\u0120thumbnail": 20307, "\u0120Rate": 20308, "arehouse": 20309, "credential": 20310, "\u0120signing": 20311, "454": 20312, "swagger": 20313, "\u0120cleared": 20314, "ModelForm": 20315, "\u00e1\u0122\u00b8": 20316, "\u0120annotations": 20317, "\u0120Emma": 20318, "\u0120philosophy": 20319, "LABEL": 20320, "sengers": 20321, "brief": 20322, "wire": 20323, "\u0132\u00d7": 20324, "\u0120pts": 20325, "\u0120SS": 20326, "umbs": 20327, "\u0120FBI": 20328, "iah": 20329, "706": 20330, "Keyboard": 20331, "nonumber": 20332, "\u0120notebook": 20333, "\u0120brightness": 20334, "madgraph": 20335, "Mail": 20336, "mob": 20337, "\u00ec\u0138": 20338, "readed": 20339, "\u0120holder": 20340, "\u0120Mun": 20341, "\u0120BSD": 20342, "=[('": 20343, "\u0120commander": 20344, "\u0120patron": 20345, "modes": 20346, "Notification": 20347, "\u0120failures": 20348, "$$\\": 20349, "ICAgICAgICAgICAg": 20350, "wikipedia": 20351, "PubMed": 20352, "\u0120Arizona": 20353, "./(": 20354, "Pur": 20355, "WP": 20356, "wct": 20357, "\u00c3\u00ae": 20358, "\u0120pace": 20359, "racle": 20360, "\u0120Hur": 20361, "\u0120abilities": 20362, "\u010a\u0109\u0109\u0109\u010a\u0109\u0109": 20363, "\u0120imposed": 20364, "\u0120basestring": 20365, "3600": 20366, "\u0120Integr": 20367, "\u0120surely": 20368, "\u00c3\u00bch": 20369, "Trajectory": 20370, "\u0120Books": 20371, "\u0120prisoners": 20372, "COMMAND": 20373, "\u00e5\u013f\u0122": 20374, "\u00e6\u00af\u0131": 20375, "hexdigest": 20376, "'(": 20377, "Hub": 20378, "[['": 20379, "xR": 20380, "orange": 20381, "']],": 20382, "\u0120rod": 20383, "Received": 20384, "\u0120provisions": 20385, "\u0120worldwide": 20386, "\u0120Phill": 20387, "\u0120governments": 20388, "likelihood": 20389, "\u0120Forest": 20390, "ompson": 20391, "vial": 20392, "\u0120fy": 20393, "\u0120114": 20394, "techn": 20395, "\u0120Nick": 20396, "\u0120kann": 20397, "medium": 20398, "80386": 20399, "\u0120tempor": 20400, "\u0120placement": 20401, "\u0120bitter": 20402, "\u0120embarr": 20403, "\u0120similarity": 20404, "EMENT": 20405, "\u0120birthday": 20406, "ienna": 20407, "trees": 20408, "\u0120nerve": 20409, "parametrize": 20410, "480": 20411, "corn": 20412, "migration": 20413, "\u00e9\u0134": 20414, "\u00eb\u0135": 20415, "heim": 20416, "iones": 20417, "\u0120mRNA": 20418, "atest": 20419, "\u0120Sky": 20420, "\u0120Cart": 20421, "\u0120Had": 20422, "propag": 20423, "\u0120printf": 20424, "phant": 20425, "\u0120subscription": 20426, "][-": 20427, "SetLine": 20428, "707": 20429, "\u0120identifying": 20430, "\u0120Gecko": 20431, "\u0120normalization": 20432, "\u0120physi": 20433, "\u0120Created": 20434, "\u0120Creates": 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"\u0120Mississippi": 20486, "missed": 20487, "\u0120antibodies": 20488, "\u0120railway": 20489, "Article": 20490, "AUC": 20491, "\u0120arrangement": 20492, "cgi": 20493, "frozen": 20494, "vstack": 20495, "}+": 20496, "ilateral": 20497, "\u0120Implement": 20498, "\u0120220": 20499, "\u0120Wy": 20500, "\u0120trav": 20501, "\u0120differential": 20502, "Delegate": 20503, "lastic": 20504, "\u00e3\u0124\u012b": 20505, "ooser": 20506, "\u0120invasion": 20507, "\u0120Indiana": 20508, "\u00d0\u00b0\u00d0\u00b2": 20509, "Execute": 20510, "\u0120Reserve": 20511, "SCRIPT": 20512, "`\")": 20513, "\u0120'@": 20514, "\u0120dee": 20515, "\u0120algo": 20516, "\u0120BO": 20517, "attn": 20518, "\u0120texture": 20519, "7890": 20520, "offsets": 20521, "viously": 20522, "\u0120divor": 20523, "\u0120swing": 20524, "\u0120insight": 20525, "\u0120planes": 20526, "\u0120declined": 20527, "APIView": 20528, "toolbar": 20529, "superuser": 20530, "Indent": 20531, "\u0120\u00d0\u00bd\u00d0\u00b5": 20532, 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