From 0231c1f318a72802d6b019c29bb1caf7244fdf50 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=AD=D0=BC=D0=B8=D0=BB=D1=8C=20=D0=90=D0=BC=D0=B8=D1=80?=
 =?UTF-8?q?=D0=BE=D0=B2?= <emillamirov555777@mail.ru>
Date: Fri, 5 Jun 2026 11:24:08 +0000
Subject: [PATCH] add README.md

---
 README.md | 38 +++++++++++++++++++-------------------
 1 file changed, 19 insertions(+), 19 deletions(-)

diff --git a/README.md b/README.md
index e18df7f..3a732bb 100644
--- a/README.md
+++ b/README.md
@@ -1,15 +1,16 @@
-# FAQ Bot – ChromaDB + MCP Tool
+# FAQ Bot – ChromaDB + MCP‑tool
 
-## Overview
+## What it does
 
-This repository contains a simple FAQ bot that answers questions about course materials using a local Chroma vector store and, when needed, calls a mock MCP‑style tool that returns course metadata.
-
-The bot is built with **LangGraph** and **LangChain** and uses **Ollama** embeddings (`nomic-embed-text`).
+* Loads a small set of markdown FAQ files into a local Chroma vector store.
+* Provides a single MCP‑style tool `fetch_course_meta` that returns course metadata from a static JSON file.
+* Uses a LangGraph React agent that routes a user question either to the vector store (Chroma) or to the MCP tool based on simple keyword detection.
+* Interactive CLI with three example questions and a free‑form mode.
 
 ## Prerequisites
 
-* Python 3.10+
-* Ollama server running locally with the `nomic-embed-text` model:
+* Python 3.10+
+* Ollama running locally with the `nomic-embed-text` model:
   ```bash
   ollama pull nomic-embed-text
   ```
@@ -20,22 +21,21 @@ The bot is built with **LangGraph** and **LangChain** and uses **Ollama** embedd
 pip install -r requirements.txt
 ```
 
-## Running the Bot
+## Running the bot
 
 ```bash
 python main.py
 ```
 
-You will be prompted to enter a question.  The bot will decide whether to answer from the FAQ documents (Chroma) or to call the mock MCP tool.
+The script will:
+1. Load `data/*.md` into Chroma.
+2. Build the agent.
+3. Run three sample questions.
+4. Enter an interactive prompt.
 
-## FAQ Files
+## Files
 
-The `data/` directory contains three example Markdown files that are loaded into the vector store.
-
-## MCP‑style Tool
-
-The tool `fetch_course_meta` simulates an external MCP call by reading a local `course_meta.json` file.  In a real deployment this would be an HTTP request to an MCP server.
-
-## License
-
-MIT
+* `main.py` – entry point.
+* `data/*.md` – FAQ documents.
+* `mock_meta.json` – static metadata used by the MCP tool.
+* `requirements.txt` – dependencies.