diff --git a/.gitignore b/.gitignore
index ea59eb5a..4b1d89cf 100644
--- a/.gitignore
+++ b/.gitignore
@@ -55,3 +55,6 @@ test_stage6_interactive.ipynb
# Secrets / local config
.env
+
+# python
+.venv
diff --git a/materials/ws/notebooks/00/introduction_to_context_engineering.ipynb b/materials/ws/notebooks/00/introduction_to_context_engineering.ipynb
index e8810e6c..1c9f88c7 100644
--- a/materials/ws/notebooks/00/introduction_to_context_engineering.ipynb
+++ b/materials/ws/notebooks/00/introduction_to_context_engineering.ipynb
@@ -39,7 +39,7 @@
"---\n",
"Visually, context can contain something like this:\n",
"\n",
- "\n"
+ "\n"
]
},
{
@@ -1040,7 +1040,7 @@
"\n",
"That remaining space (111,900) might look comforting but remember this is just one turn. \n",
"\n",
- "\n",
+ "\n",
"\n",
"\n",
"- Our inputs will likely only grow longer (especially around conversation history), and as they do models have a harder time producing effective results.\n",
@@ -1060,7 +1060,7 @@
"4. **Placement & structure matter**: Models attend unevenly across the window; key facts can be missed when buried. We should surface essentials early, chunk clearly, and summarize instead of pasting raw dumps. \n",
"\n",
"\n",
- "\n",
+ "\n",
"\n",
"**Figure**: Performance degradation with context length. \n",
"*Source: Adapted from \"Many-Shot In-Context Learning in Multimodal Foundation Models\" \n",
@@ -1084,7 +1084,7 @@
"## Other Challenges\n",
"\n",
"\n",
- "\n",
+ "\n",
"\n",
"While managing the size of your context window is critical, simply fitting everything in isn't the only hurdle. As D. Breunig highlights in [How Contexts Fail (and How to Fix Them)](https://www.dbreunig.com/2025/06/22/how-contexts-fail-and-how-to-fix-them.html), there are several other ways that context can degrade the performance of your agent, even when you are well within the token limits.\n",
"\n",
diff --git a/materials/ws/notebooks/01/baseline_rag.ipynb b/materials/ws/notebooks/01/baseline_rag.ipynb
index cba53c57..065345d3 100755
--- a/materials/ws/notebooks/01/baseline_rag.ipynb
+++ b/materials/ws/notebooks/01/baseline_rag.ipynb
@@ -87,15 +87,9 @@
},
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- "shell.execute_reply": "2026-03-25T21:04:00.753605Z"
- },
"tags": [
"setup"
]
@@ -147,15 +141,9 @@
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+ "execution_count": 5,
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- "iopub.status.idle": "2026-03-25T21:04:23.454720Z",
- "shell.execute_reply": "2026-03-25T21:04:23.454401Z"
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"tags": [
"setup"
]
@@ -169,6217 +157,68 @@
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+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "⚠️ This agent uses RAW context - no optimization!\n"
+ ]
},
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- " self._context.run(self._callback, *self._args)\n",
- " ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
- "RuntimeError: cannot enter context: <_contextvars.Context object at 0x108657e00> is already entered\n"
- ]
- },
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- },
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Agent is ready!\n"
+ ]
+ }
+ ],
+ "source": [
+ "from agent import setup_agent\n",
+ "\n",
+ "print(\"Initializing Baseline RAG Agent...\")\n",
+ "# auto_load_courses=True ensures we have data to query\n",
+ "workflow, course_manager = setup_agent(auto_load_courses=True)\n",
+ "print(\"Agent is ready!\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d7356857",
+ "metadata": {},
+ "source": [
+ "## Drowning in Data\n",
+ "\n",
+ "Imagine a student just wants a quick list of options. They ask:\n",
+ "\n",
+ "> *\"What computer science courses are available?\"*\n",
+ "\n",
+ "If this were a human advisor, they would likely reply with something like: *\"We have CS001 (Intro to ML) and CS002 (Deep Learning).\"*\n",
+ "\n",
+ "But will that be what our agent does? Let's observe. Run the code block below to send the query."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "aa7c49dc",
+ "metadata": {},
+ "outputs": [
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- " self._context.run(self._callback, *self._args)\n",
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- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Hierarchical courses not found at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/progressive_agents/src/redis_context_course/data/hierarchical/hierarchical_courses.json\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "⚠️ This agent uses RAW context - no optimization!\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Agent is ready!\n"
- ]
- }
- ],
- "source": [
- "from agent import setup_agent\n",
- "\n",
- "print(\"Initializing Baseline RAG Agent...\")\n",
- "# auto_load_courses=True ensures we have data to query\n",
- "workflow, course_manager = setup_agent(auto_load_courses=True)\n",
- "print(\"Agent is ready!\")"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "d7356857",
- "metadata": {},
- "source": [
- "## Drowning in Data\n",
- "\n",
- "Imagine a student just wants a quick list of options. They ask:\n",
- "\n",
- "> *\"What computer science courses are available?\"*\n",
- "\n",
- "If this were a human advisor, they would likely reply with something like: *\"We have CS001 (Intro to ML) and CS002 (Deep Learning).\"*\n",
- "\n",
- "But will that be what our agent does? Let's observe. Run the code block below to send the query."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "id": "aa7c49dc",
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T21:04:23.455852Z",
- "iopub.status.busy": "2026-03-25T21:04:23.455791Z",
- "iopub.status.idle": "2026-03-25T21:04:37.052037Z",
- "shell.execute_reply": "2026-03-25T21:04:37.051079Z"
- }
- },
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "User asks: 'What computer science courses are available?'\n",
- "Running workflow...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "No hierarchical data for CS003\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "No hierarchical data for CS004\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "No hierarchical data for CS007\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "No hierarchical data for CS002\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "No hierarchical data for CS005\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "No hierarchical courses found, using basic courses\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "⚠️ Returning FULL details (including syllabi) for ALL 5 courses!\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "⚠️ This wastes tokens on courses the user doesn't care about!\n"
- ]
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "User asks: 'What computer science courses are available?'\n",
+ "Running workflow...\n"
+ ]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
+ "⚠️ Returning FULL details (including syllabi) for ALL 5 courses!\n",
+ "⚠️ This wastes tokens on courses the user doesn't care about!\n",
"⚠️ No progressive disclosure, no context engineering!\n"
]
},
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- "output_type": "stream",
- "text": [
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- "task: .run_in_context() done, defined at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/ipykernel/utils.py:57> wait_for= cb=[Task.__wakeup()]> cb=[ZMQStream._run_callback.._log_error() at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/zmq/eventloop/zmqstream.py:563]>\n"
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- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/Users/nitin.kanukolanu/.local/share/uv/python/cpython-3.13.7-macos-aarch64-none/lib/python3.13/typing.py:1366: RuntimeWarning: coroutine 'Kernel.shell_main' was never awaited\n",
- " raise AttributeError(attr)\n",
- "RuntimeWarning: Enable tracemalloc to get the object allocation traceback\n",
- "Task was destroyed but it is pending!\n",
- "task: cb=[Task.__wakeup()]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: .run_in_context() done, defined at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/ipykernel/utils.py:57> wait_for= cb=[Task.__wakeup()]> cb=[ZMQStream._run_callback.._log_error() at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/zmq/eventloop/zmqstream.py:563]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: cb=[Task.__wakeup()]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: .run_in_context() done, defined at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/ipykernel/utils.py:57> wait_for= cb=[Task.__wakeup()]> cb=[ZMQStream._run_callback.._log_error() at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/zmq/eventloop/zmqstream.py:563]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: cb=[Task.__wakeup()]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: .run_in_context() done, defined at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/ipykernel/utils.py:57> wait_for= cb=[Task.__wakeup()]> cb=[ZMQStream._run_callback.._log_error() at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/zmq/eventloop/zmqstream.py:563]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: cb=[Task.__wakeup()]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: .run_in_context() done, defined at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/ipykernel/utils.py:57> wait_for= cb=[Task.__wakeup()]> cb=[ZMQStream._run_callback.._log_error() at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/.venv/lib/python3.13/site-packages/zmq/eventloop/zmqstream.py:563]>\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Task was destroyed but it is pending!\n",
- "task: cb=[Task.__wakeup()]>\n"
- ]
- },
{
"name": "stdout",
"output_type": "stream",
@@ -6683,7 +522,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.13.7"
+ "version": "3.12.8"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
diff --git a/materials/ws/notebooks/01/data_engineered_rag.ipynb b/materials/ws/notebooks/01/data_engineered_rag.ipynb
index 9fd3c200..5d51df4f 100755
--- a/materials/ws/notebooks/01/data_engineered_rag.ipynb
+++ b/materials/ws/notebooks/01/data_engineered_rag.ipynb
@@ -46,15 +46,6 @@
"execution_count": 1,
"id": "3ffa9c24",
"metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T21:04:52.050206Z",
- "iopub.status.busy": "2026-03-25T21:04:52.050102Z",
- "iopub.status.idle": "2026-03-25T21:04:52.055169Z",
- "shell.execute_reply": "2026-03-25T21:04:52.054539Z"
- },
- "jupyter": {
- "source_hidden": true
- },
"tags": [
"setup"
]
@@ -95,15 +86,6 @@
"id": "e37ed621",
"metadata": {
"editable": true,
- "execution": {
- "iopub.execute_input": "2026-03-25T21:04:52.056694Z",
- "iopub.status.busy": "2026-03-25T21:04:52.056591Z",
- "iopub.status.idle": "2026-03-25T21:04:53.269092Z",
- "shell.execute_reply": "2026-03-25T21:04:53.268706Z"
- },
- "jupyter": {
- "source_hidden": true
- },
"slideshow": {
"slide_type": ""
},
@@ -116,20 +98,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Initializing Data-Engineered RAG Agent...\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "Hierarchical courses not found at /Users/nitin.kanukolanu/workspace/lab-contexteng/materials/ws/progressive_agents/src/redis_context_course/data/hierarchical/hierarchical_courses.json\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
+ "Initializing Data-Engineered RAG Agent...\n",
"Agent is ready!\n"
]
}
@@ -886,7 +855,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.13.7"
+ "version": "3.12.8"
}
},
"nbformat": 4,
diff --git a/materials/ws/progressive_agents/stage1_baseline_rag/agent/nodes.py b/materials/ws/progressive_agents/stage1_baseline_rag/agent/nodes.py
index 99cdc4d5..f3ec34a2 100644
--- a/materials/ws/progressive_agents/stage1_baseline_rag/agent/nodes.py
+++ b/materials/ws/progressive_agents/stage1_baseline_rag/agent/nodes.py
@@ -22,7 +22,6 @@
# Suppress httpx INFO logs
logging.getLogger("httpx").setLevel(logging.WARNING)
from langchain_core.messages import HumanMessage
-
from redis_context_course import CourseManager
from redis_context_course.hierarchical_context import RawContextAssembler
from redis_context_course.hierarchical_models import HierarchicalCourse
@@ -68,7 +67,8 @@ def initialize_nodes(manager: CourseManager):
# Load hierarchical courses with full syllabi
try:
data_path = (
- Path(__file__).parent.parent.parent / "src"
+ Path(__file__).parent.parent.parent.parent
+ / "src"
/ "redis_context_course"
/ "data"
/ "hierarchical"
diff --git a/materials/ws/progressive_agents/stage2_context_engineered/agent/nodes.py b/materials/ws/progressive_agents/stage2_context_engineered/agent/nodes.py
index f769862d..f7713ec6 100644
--- a/materials/ws/progressive_agents/stage2_context_engineered/agent/nodes.py
+++ b/materials/ws/progressive_agents/stage2_context_engineered/agent/nodes.py
@@ -64,7 +64,8 @@ def initialize_nodes(manager: CourseManager):
# Load hierarchical courses
try:
data_path = (
- Path(__file__).parent.parent.parent / "src"
+ Path(__file__).parent.parent.parent.parent
+ / "src"
/ "redis_context_course"
/ "data"
/ "hierarchical"
diff --git a/materials/ws/progressive_agents/stage3_full_agent_without_memory/agent/tools.py b/materials/ws/progressive_agents/stage3_full_agent_without_memory/agent/tools.py
index 0a7246eb..40860f8b 100644
--- a/materials/ws/progressive_agents/stage3_full_agent_without_memory/agent/tools.py
+++ b/materials/ws/progressive_agents/stage3_full_agent_without_memory/agent/tools.py
@@ -19,10 +19,7 @@
from pydantic import BaseModel, Field
from redis_context_course import CourseManager
from redis_context_course.hierarchical_context import HierarchicalContextAssembler
-from redis_context_course.hierarchical_models import (
- CourseSummary,
- HierarchicalCourse,
-)
+from redis_context_course.hierarchical_models import CourseSummary, HierarchicalCourse
from redis_context_course.models import Course
# Configure logger
@@ -47,7 +44,8 @@ def initialize_tools(manager: CourseManager):
# Load hierarchical courses with full syllabi
try:
data_path = (
- Path(__file__).parent.parent.parent / "src"
+ Path(__file__).parent.parent.parent.parent
+ / "src"
/ "redis_context_course"
/ "data"
/ "hierarchical"
@@ -216,11 +214,11 @@ def search_courses_sync(
format=basic_course.format,
instructor=basic_course.instructor,
short_description=basic_course.description[:200],
- prerequisite_codes=[
- p.course_code for p in basic_course.prerequisites
- ]
- if basic_course.prerequisites
- else [],
+ prerequisite_codes=(
+ [p.course_code for p in basic_course.prerequisites]
+ if basic_course.prerequisites
+ else []
+ ),
tags=[],
)
summaries.append(summary)
@@ -316,11 +314,11 @@ async def search_courses(
format=basic_course.format,
instructor=basic_course.instructor,
short_description=basic_course.description[:200],
- prerequisite_codes=[
- p.course_code for p in basic_course.prerequisites
- ]
- if basic_course.prerequisites
- else [],
+ prerequisite_codes=(
+ [p.course_code for p in basic_course.prerequisites]
+ if basic_course.prerequisites
+ else []
+ ),
tags=[],
)
summaries.append(summary)
diff --git a/start.sh b/start.sh
index 46029438..05f0ff9e 100755
--- a/start.sh
+++ b/start.sh
@@ -30,6 +30,9 @@ else
echo "Copied ./all to ./dist/"
fi
+# Copy doc assets (e.g. redis_logo.png) into the served static site
+cp -r ./doc/ ./dist/client/
+
docker-compose up -d --scale jupyter=0 --scale docs=0
echo "Waiting for litellm to be ready (healthcheck)..."