# Agent with RAG Memory (ChromaDB)

This project implements a Retrieval-Augmented Generation (RAG) agent that uses **ChromaDB** as its sole vector store. The agent can ingest documents, store their embeddings, retrieve relevant passages, and generate answers using OpenAI’s GPT models.

## Features

- **Vector Store** – Uses ChromaDB for storing and querying embeddings.
- **Embeddings** – Generated with OpenAI’s `text-embedding-ada-002`.
- **Chat** – Generates responses with OpenAI’s `gpt-3.5-turbo`.
- **Public API** – The `Agent` class exposes `init`, `ingest`, and `ask` methods, keeping the original interface unchanged.

## Setup

1. **Clone the repository**

   ```bash
   git clone https://git.brojs.ru/kuzakhmetovartur/agent-s-rag-pamyatyu.git
   cd agent-s-rag-pamyatyu
   ```

2. **Install dependencies**

   ```bash
   npm install
   ```

3. **Configure environment variables**

   Create a `.env` file in the project root (or export the variables in your shell):

   ```dotenv
   # ChromaDB
   CHROMA_URL=localhost
   CHROMA_PORT=8000

   # OpenAI
   OPENAI_API_KEY=YOUR_OPENAI_API_KEY
   ```

   - `CHROMA_URL` and `CHROMA_PORT` point to your ChromaDB instance.  
   - `OPENAI_API_KEY` is required for embeddings and chat completions.

4. **Run ChromaDB**

   Ensure a ChromaDB server is running on the specified host/port. You can start a local instance with Docker:

   ```bash
   docker run -d -p 8000:8000 chromadb/chroma
   ```

## Usage

```js
const { Agent } = require('./src');

(async () => {
  const agent = new Agent();
  await agent.init();

  // Ingest documents
  await agent.ingest('The quick brown fox jumps over the lazy dog.', { source: 'example.txt' });

  // Ask a question
  const answer = await agent.ask('What did the fox do?');
  console.log(answer);
})();
```

## API

| Method | Description |
|--------|-------------|
| `init()` | Initializes the vector store (creates collection if needed). |
| `ingest(text, metadata)` | Adds a document to the vector store. |
| `ask(question)` | Retrieves relevant passages and generates an answer. |

## Testing

If you have a test suite, run:

```bash
npm test
```

All tests should pass after the ChromaDB integration.

## Notes

- The agent’s public API remains unchanged; only the underlying vector store implementation has been swapped to ChromaDB.
- No new external services are introduced beyond ChromaDB and the existing OpenAI usage.
- Ensure that the ChromaDB server is reachable; otherwise, the agent will throw connection errors.

--- 

Happy coding!