Solution published: update README.md

README.md

@@ -1,14 +1,15 @@
-# LangGraph research brief generator
+# LangGraph Comparison Agent
 
 ## Overview
 
-This repository contains a LangGraph agent that generates a connected research brief on a single topic. The agent:
+This repository contains a **LangGraph** agent that, given three entities (e.g. vector databases, frameworks, or products), builds a comparative review. The agent:
 
-1. Uses an LLM to generate concise section headings for the brief.
-2. For each heading, performs a Tavily web search to fetch relevant content.
-3. Aggregates the sections into a single Markdown brief with a summary.
+1. **Plans criteria** – LLM generates 3‑5 comparison criteria based on the entities.
+2. **Researches each entity‑criterion pair** – uses **Tavily** web search to fetch a short note for each pair.
+3. **Builds a Markdown table** – rows are criteria, columns are entities.
+4. **Produces a verdict** – LLM gives a concise recommendation.
 
-The agent is implemented in `src/main.py` and can be run from the command line.
+The final output is a Markdown table followed by a verdict paragraph.
 
 ## Requirements
 
@@ -16,7 +17,7 @@ The agent is implemented in `src/main.py` and can be run from the command line.
 pip install -r requirements.txt
 ```
 
-The following environment variables must be set:
+Environment variables:
 
 - `OPENAI_API_KEY` – key for the OpenAI model used by LangChain.
 - `TAVILY_API_KEY` – key for the Tavily API.
@@ -24,11 +25,11 @@ The following environment variables must be set:
 ## Usage
 
 ```bash
-# Default demo – generates a brief on "Artificial Intelligence"
+# Default demo – compares Chroma, FAISS, Qdrant
 python -m src.main
 
-# Custom topic
-python -m src.main "Quantum Computing"
+# Custom entities
+python -m src.main "Chroma,FAISS,Qdrant"
 ```
 
-The script prints the generated brief in Markdown format.
+The script prints the comparison table and verdict in Markdown format.