README.md

metadata

title: OpenAI compatible Chatbot API
emoji: 🤯
colorFrom: pink
colorTo: yellow
sdk: docker
pinned: false
short_description: OpenAI compatible Chatbot API

OpenAI Compatible Chatbot API Template

A FastAPI based OpenAI compatible Chatbot API with Visualization.

🔗 Links

• Github URL
• HF SPACE URL
• SwaggerUI
• Redoc
• OpenAPI

🚀 Features

• OpenAI compatible API

  • /v1/chat/completions
  • /v1/chat/completions/{completion_id}
  • /v1/chat/completions/{completion_id}/messages
  • /v1/chat/completions/{completion_id}/messages/{message_id}/plots
  • /v1/conversation
  • /v1/conversation/{completion_id}

• Complete mock implementation with USE_MOCK_API environment variable

• Secure API key generation with HMAC signatures and API key authentication

• In-memory storage for chat history and plots for mock implementation

• MongoDB storage for chat history and plots for production

• Support for all major OpenAI API endpoints

• Gradio UI for testing the chatbot : http://127.0.0.1:7860/ui

📋 Endpoints

• GET - /chat/completions list stored chat completions - for first load the chatbot
• POST - /chat/completions create a new chat completion - when user starts a new chat
• GET - /chat/completions/{completion_id} get a stored chat completion by completion_id - when user clicks on a chat on the list
• POST - /chat/completions/{completion_id} modify a stored chat completion by completion_id - NOT IMPLEMENTED YET
• DELETE - /chat/completions/{completion_id} delete a stored chat completion by completion_id - NOT IMPLEMENTED YET
• GET - /chat/completions/{completion_id}/messages get the messages in a stored chat completion by completion_id - when user clicks on a chat on the list
• GET - /chat/completions/{completion_id}/messages/{message_id}/plots get the plots/graph-data/figure-json in a stored chat completion by completion_id and message_id

🛠️ Installation

1. Clone the repository:

git clone https://github.com/lokumai/openai-openapi-template.git

2. Create a .env file in the root directory and add the following variables:

cp .env.example .env

• Set your own values for the variables in the .env file.

3. Install dependencies:

uv sync

4. Start MongoDB:

docker compose -f docker/mongodb-docker-compose.yaml up -d

5. Run API and Gradio UI on your local machine:

./run.sh

# or

uv run uvicorn main:app --host 0.0.0.0 --port 7860 --reload

Usage

🔑 API Key Generation

./scripts/generate_api_key.sh <username> <secret_key>

• This will generate a API_KEY and save it to the api_key.txt file.

API Key generated:
Username: template
API Key: sk-template-token

API Key saved to api_key.txt

🔒 Security Configuration

There are various security configurations that can be set in the .env file for development and production environments.

• SECURITY_ENABLED=True or False, If security is enabled, the API will require an API_KEY to be provided in the request header.
• SECURITY_DEFAULT_USERNAME=admin, If security is disabled, the API will not require an API_KEY to be provided in the request header and will use this for current user.
• SECURITY_SECRET_KEY=your-secret-key-here, This is the secret key for the API_KEY generation. It is used to generate and verify the API_KEY for the user.
• API_KEY, If you want to use the Gradio UI, you can set the API_KEY in the .env file. GradioUI will use the API_KEY to make requests to the API. Especially POST/chat/completions endpoint.

🔑 API Key Authentication

curl -X POST "http://localhost:7860/v1/chat/completions" \
     -H "Authorization: Bearer sk-template-token" \
     -H "Content-Type: application/json" \
     -d '{"model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": "Hello!"}]}'

💾 Embedded MongoDB for local machine development

• database_type environment variable is set to embedded, the API will use embedded MongoDB for local machine development. Default is mongodb.
• mongodb_host environment variable is set to localhost, the API will use localhost for MongoDB. Default is localhost.
• mongodb_port environment variable is set to 27017, the API will use 27017 for MongoDB. Default is 27017.
• mongodb_database environment variable is set to openai_openapi_template, the API will use openai_openapi_template for MongoDB. Default is openai_openapi_template.

🤝 Contributing Attention Please!!!

When you make changes to the code, please run the following commands to ensure the code is running on your local machine and formatted and linted correctly.

• Fork the repository

git clone https://github.com/yourname/openai-openapi-template.git

• cd to the project directory

cd openai-openapi-template

• Create a new branch

git checkout -b feature/new-feature
# or
git checkout -b bug/fix-issue
# or
git checkout -b hotfix/critical-fix

• Make your changes and commit them

git status
git add .
git commit -m "Add new feature"

• Push your changes to the branch

git push origin feature/new-feature

• Merge from main branch to your branch

git fetch origin main
git merge origin/main

• Validate the code is running on your local machine

uv run uvicorn app:app --reload

• Format and lint the code

ruff check --fix

ruff format

• Everything is working, create a pull request

git push origin feature/new-feature

• Create a pull request

gh pr create --base main --head feature/new-feature --title "Add new feature" --body "This PR adds a new feature to the project"

Open Issue

Mock Implementation:

• Implement Mock response for all endpoints
• Implement API-Key Authentication and validation in all endpoints

Production Implementation:

• POST chat/completions - create a new chat completion
• GET chat/completions - list stored chat completions
• GET chat/completions/{completion_id} - get a stored chat completion by id
• GET chat/completions/{completion_id}/messages - get the messages in a stored chat completion by id
• GET chat/completions/{completion_id}/messages/{message_id}/plots - get the plots/graph-data/figure-json in a stored chat completion by id and message id
• GET conversation - get all conversations
• GET conversation/{completion_id} - get a conversation by completion_id