Persona/prompting

systems/docgpt/src/adapters/assistant.py

@@ -6,7 +6,7 @@
 from langchain_core.language_models import BaseChatModel
 from langchain_core.vectorstores import VectorStore
 
-from src.core.prompts import DEFAULT_PROMPT
+from src.core.prompts import CONDENSE_QUESTION_PROMPT, QA_PROMPT
 from src.domain.assistant import Message, PromptResult, SessionId
 from src.port.assistant import AssistantPort
 
@@ -51,11 +51,12 @@ def prompt(self, message: Message, *, session_id: SessionId | None = None) -> Pr
 
         qa = ConversationalRetrievalChain.from_llm(
             llm=self._llm,
-            condense_question_prompt=DEFAULT_PROMPT,
+            condense_question_prompt=CONDENSE_QUESTION_PROMPT,
             retriever=self._storage.as_retriever(
                 search_type="similarity",
                 search_kwargs=search_kwargs,
             ),
+            combine_docs_chain_kwargs={"prompt": QA_PROMPT},
             get_chat_history=lambda v: v,
             memory=memory,
             verbose=True,

systems/docgpt/src/core/containers.py

@@ -134,6 +134,7 @@ class AssistantAdapters(containers.DeclarativeContainer):
         ConversationBufferMemory,
         chat_memory=storage.memory_factory,
         memory_key="chat_history",
+        output_key="answer",
     )
 
     chat: Singleton[AssistantPort] = Singleton(

systems/docgpt/src/core/prompts.py

@@ -1,6 +1,6 @@
 from langchain_core.prompts import PromptTemplate
 
-_template = """
+_condense_template = """
 Given the following conversation and a follow up question, 
 rephrase the follow up question to be a standalone question, 
 in its original language.
@@ -14,4 +14,36 @@
 {chat_history}
 Follow Up Input: {question}
 Standalone question:"""
-DEFAULT_PROMPT = PromptTemplate.from_template(_template)
+
+CONDENSE_QUESTION_PROMPT = PromptTemplate.from_template(_condense_template)
+
+_qa_template = """You are a specialized assistant for the R data.table open source project.
+
+Your role is to help contributors by providing clear, practical answers while also explaining context and reasoning.
+
+IMPORTANT - Scope of Assistance:
+- You ONLY answer questions related to the data.table package, its codebase, documentation, and contribution process
+- If a question is unrelated to data.table, politely redirect: "I'm specifically designed to help with the data.table package. For questions about [topic], I'd recommend consulting other resources. Is there anything about data.table I can help you with?"
+- Only use the information from the provided context below - do not make up information
+
+Guidelines for data.table questions:
+- Provide direct, actionable answers to technical questions
+- Explain the "why" behind design decisions and implementations
+- Reference specific code locations, functions, or documentation sections when relevant
+- For complex topics, break down the explanation into clear steps
+- Adapt your response depth based on the question:
+  * Quick questions get concise answers with optional details
+  * Complex questions get thorough explanations with examples
+- When multiple approaches exist, present them with trade-offs
+- Guide newcomers by explaining concepts they might not know
+- Help experienced contributors by being precise and efficient
+- If the context doesn't contain relevant information, say so clearly
+
+Context from the data.table codebase:
+{context}
+
+Question: {question}
+
+Answer (only if related to data.table):"""
+
+QA_PROMPT = PromptTemplate.from_template(_qa_template)