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# LangGraph research brief generator
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# LangGraph Comparison Agent
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## Overview
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## Overview
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This repository contains a LangGraph agent that generates a connected research brief on a single topic. The agent:
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This repository contains a **LangGraph** agent that, given three entities (e.g. vector databases, frameworks, or products), builds a comparative review. The agent:
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1. Uses an LLM to generate concise section headings for the brief.
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1. **Plans criteria** – LLM generates 3‑5 comparison criteria based on the entities.
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2. For each heading, performs a Tavily web search to fetch relevant content.
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2. **Researches each entity‑criterion pair** – uses **Tavily** web search to fetch a short note for each pair.
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3. Aggregates the sections into a single Markdown brief with a summary.
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3. **Builds a Markdown table** – rows are criteria, columns are entities.
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4. **Produces a verdict** – LLM gives a concise recommendation.
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The agent is implemented in `src/main.py` and can be run from the command line.
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The final output is a Markdown table followed by a verdict paragraph.
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## Requirements
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## Requirements
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pip install -r requirements.txt
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pip install -r requirements.txt
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```
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```
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The following environment variables must be set:
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Environment variables:
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- `OPENAI_API_KEY` – key for the OpenAI model used by LangChain.
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- `OPENAI_API_KEY` – key for the OpenAI model used by LangChain.
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- `TAVILY_API_KEY` – key for the Tavily API.
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- `TAVILY_API_KEY` – key for the Tavily API.
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## Usage
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## Usage
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```bash
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```bash
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# Default demo – generates a brief on "Artificial Intelligence"
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# Default demo – compares Chroma, FAISS, Qdrant
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python -m src.main
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python -m src.main
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# Custom topic
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# Custom entities
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python -m src.main "Quantum Computing"
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python -m src.main "Chroma,FAISS,Qdrant"
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```
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```
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The script prints the generated brief in Markdown format.
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The script prints the comparison table and verdict in Markdown format.
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