Metadata-Version: 2.4
Name: pyragapi
Version: 1.0.5
Summary: A rag api for extending your applicaiton 
Author: Barry
License-Expression: MIT
Requires-Python: >=3.8
Requires-Dist: fastapi
Requires-Dist: langchain
Requires-Dist: langchain-community
Requires-Dist: langchain-core
Requires-Dist: langchain-openai
Requires-Dist: langchain-qdrant
Requires-Dist: langchain-text-splitters
Requires-Dist: pypdf
Requires-Dist: python-dotenv
Requires-Dist: uvicorn
Description-Content-Type: text/markdown

# The RAG API
Query your documents powered by AI

## Requirements
Have the following tools installed on your computer
- Git
- Docker
## Usage
1. Start by cloning the project.  
```sh
    git clone -b java-to-python-rag-app --single-branch <repo_url>
```
2. Open the project with an IDE or a text editor
3. In the project root directory, rename the **.env.example** file to **.env** and fill in the values
    > **Note:** Make sure that the container_name of the qdrant service in the docker-compose.yaml file matches the QDRANT_HOST in the .env file
4. Open a terminal and run: 
``` sh 
    docker-compose up --build
```
5. Once the download is complete and the applicaiton has been started, go the [http://localhost:8000/docs](http://localhost:8000/docs) to use the api.

## Use the api as a module

If you want to use the api to extend your application capabilities with rag support already made, please follow these steps:
1. Open a terminal in your project directory  and run the following commands 
```sh
    pip install pyragapi
```
2. import the router from pyragapi.routers
3. link it to your fastapi instance 
>**Note:** Do not forget to create a .env file and fill in the values.