FastAPI App

Fast App using LangChain framework

This is a FastAPI app that interacts with the OpenAI API and performs similarity search on a vectorstore. It provides an endpoint for sending a message and receiving a response.

LangChain docs

Prerequisites

• Python 3.10
• OpenAI API key

Usage

You can deploy the project via Docker.

Docker website.

install Docker Desktop.

Getting Started

Clone this repository:

git clone git@github.com:Truewaydm/nifty_bridge_ai_assistant.git

Install the dependencies:

pip install -r requirements.txt

Environment

.env

OPENAI_API_KEY={Add OpenAI API key}
MODEL_NAME=gpt-3.5-turbo

Run

Using Docker

>> docker-compose up -d --build

...
...
...
src_api_1 ... done

Without Docker

uvicorn app.main:app --host 0.0.0.0 --port 3000 --reload

Open Swagger documentation - http://127.0.0.1:3000/docs

We use the chatGPT 3.5 API to communicate with a PDF file, we can request any information contained in this file.

For example:

Request:
curl --location 'http://localhost:3000/api/send' \
--header 'x-api-key-token: {Add OpenAI API key}' \
--header 'Content-Type: application/json' \
--data '{
  "message": "Hello"
}'
---------------------------------------------------
Response:
{
"message": "Hello I am NiftyBridge AI assistant. How could I help you?"
}