# documents-retrieval-agent

**Repository Path**: xiye1994/documents-retrieval-agent

## Basic Information

- **Project Name**: documents-retrieval-agent
- **Description**: No description available
- **Primary Language**: Python
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-03-07
- **Last Updated**: 2024-03-07

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Chat With Multiple PDF Documents using Conversational RAG on CPU with LLAMA2, Langchain ChromaDB

This is a Conversational Retrieval Augmented Generation (RAG) Knowledge Base Chat built on top of LLAMA2 (Embeddings & Model), Langchain and ChromaDB and orchestrated by FastAPI framework to provide and Endpoint for easy communication.

---

## Quickstart

### Conversational RAG runs offline on local CPU

1. Setup a virtual environement & Install the requirements:

```{python}
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt`
```

2. Copy your PDF files to the `documents` folder.

3. Run the FastAPI server, to process and ingest your data on start with the LLM RAG and return the answer:

```{python}
python main.py "What is the invoice number value?"
```