Implement Summary Agents skeletton

langgraph.json

@@ -4,7 +4,8 @@
   ],
   "graphs": {
     "POC: Simple Agent": "./src/poc/simple_agent.py:graph",
-    "POC: Deep Agent": "./src/poc/deep_agent.py:graph"
+    "POC: Deep Agent": "./src/poc/deep_agent.py:graph",
+    "Walk and Learn Summary": "./src/agents/walkandlearn_summary/graph.py:graph"
   },
   "env": ".env"
 }

src/__init__.py

@@ -0,0 +1 @@
+"""Source package."""

src/agents/__init__.py

@@ -0,0 +1 @@
+"""Agents package."""

src/agents/walkandlearn_summary/__init__.py

@@ -0,0 +1,5 @@
+"""Walk and Learn summary agent."""
+
+from .graph import graph
+
+__all__ = ["graph"]

src/agents/walkandlearn_summary/graph.py

@@ -0,0 +1,85 @@
+"""LangGraph agent for summarizing conversations with emotional and technical summaries."""
+
+from typing_extensions import TypedDict
+
+from langchain.agents import create_agent
+from langchain.chat_models import init_chat_model
+from langchain_core.messages import HumanMessage
+from langgraph.graph import StateGraph, START, END, MessagesState
+
+from agents.walkandlearn_summary.io import read_file, write_file, format_summary
+from agents.walkandlearn_summary.prompts import EMOTIONAL_SUMMARY_PROMPT, TECHNICAL_SUMMARY_PROMPT
+
+
+MODEL_NAME = "gpt-4o-mini"
+MODEL_TEMPERATURE = 0
+
+INPUT_FILE_PATH = "TODO_INPUT_FILE_PATH.txt"  # TODO: Replace with actual input file path
+OUTPUT_FILE_PATH = "TODO_OUTPUT_FILE_PATH.md"  # TODO: Replace with actual output file path
+
+
+class SummaryState(MessagesState):
+    conversation: str
+    emotional_summary: str
+    technical_summary: str
+
+
+model = init_chat_model(MODEL_NAME, temperature=MODEL_TEMPERATURE)
+
+emotional_agent = create_agent(
+    model=model,
+    tools=[],
+    system_prompt=EMOTIONAL_SUMMARY_PROMPT
+)
+
+technical_agent = create_agent(
+    model=model,
+    tools=[],
+    system_prompt=TECHNICAL_SUMMARY_PROMPT
+)
+
+
+def load_conversation_node(state: SummaryState) -> dict:
+    return {"conversation": read_file(INPUT_FILE_PATH)}
+
+
+def emotional_summary_node(state: SummaryState) -> dict:
+    result = emotional_agent.invoke({
+        "messages": [HumanMessage(content=f"Please provide an emotional summary of the following conversation:\n\n{state['conversation']}")]
+    })
+    return {"emotional_summary": result["messages"][-1].content}
+
+
+def technical_summary_node(state: SummaryState) -> dict:
+    # TODO: Uncomment below to enable technical agent (currently placeholder to save API costs)
+    return {"technical_summary": "[Technical summary placeholder - agent commented out for cost savings]"}
+
+    # result = technical_agent.invoke({
+    #     "messages": [HumanMessage(content=f"Please provide a technical summary of the following conversation:\n\n{state['conversation']}")]
+    # })
+    # return {"technical_summary": result["messages"][-1].content}
+
+
+def write_output_node(state: SummaryState) -> dict:
+    content = format_summary(state['emotional_summary'], state['technical_summary'])
+    write_file(OUTPUT_FILE_PATH, content)
+    return {}
+
+
+graph = (
+    StateGraph(SummaryState)
+
+    .add_node("load_conversation", load_conversation_node)
+    .add_node("emotional_summary", emotional_summary_node)
+    .add_node("technical_summary", technical_summary_node)
+    .add_node("write_output", write_output_node)
+
+    .add_edge(START, "load_conversation")
+    .add_edge("load_conversation", "emotional_summary")
+    .add_edge("load_conversation", "technical_summary")
+    .add_edge("emotional_summary", "write_output")
+    .add_edge("technical_summary", "write_output")
+    .add_edge("write_output", END)
+
+    .compile()
+)

src/agents/walkandlearn_summary/io.py

@@ -0,0 +1,34 @@
+"""File I/O utilities for the summarization workflow."""
+
+from pathlib import Path
+
+
+def read_file(file_path: str) -> str:
+    try:
+        with open(Path(file_path), "r", encoding="utf-8") as f:
+            return f.read()
+    except FileNotFoundError:
+        return f"File not found: {file_path}. Please set the correct file path in the configuration constants."
+
+
+def write_file(file_path: str, content: str) -> None:
+    with open(Path(file_path), "w", encoding="utf-8") as f:
+        f.write(content)
+
+
+def format_summary(emotional_summary: str, technical_summary: str) -> str:
+    return f"""# Emotional Summary
+
+{emotional_summary}
+
+
+
+================================================================
+================================================================
+
+
+
+# Technical Summary
+
+{technical_summary}
+"""

src/agents/walkandlearn_summary/prompts.py

@@ -0,0 +1,9 @@
+"""System prompts for summarization agents."""
+
+EMOTIONAL_SUMMARY_PROMPT = """You are the emotional summary agent.
+
+TODO: Replace this placeholder with the actual system prompt for emotional summarization."""
+
+TECHNICAL_SUMMARY_PROMPT = """You are the technical summary agent.
+
+TODO: Replace this placeholder with the actual system prompt for technical summarization."""