https://github.com/anqorithm/fastflowwrapper
A FastAPI application that wraps Flowise APIs to be compatible with OpenAI's API standards, enabling seamless integration with OpenAI-compatible clients.
https://github.com/anqorithm/fastflowwrapper
Last synced: 3 months ago
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A FastAPI application that wraps Flowise APIs to be compatible with OpenAI's API standards, enabling seamless integration with OpenAI-compatible clients.
- Host: GitHub
- URL: https://github.com/anqorithm/fastflowwrapper
- Owner: anqorithm
- License: mit
- Created: 2024-10-16T11:13:39.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-10-16T14:33:42.000Z (7 months ago)
- Last Synced: 2025-02-15T18:53:42.192Z (3 months ago)
- Language: Python
- Homepage:
- Size: 198 KB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Flowise OpenAI Wrapper
A FastAPI application that wraps Flowise APIs to be compatible with OpenAI's API standards, enabling seamless integration with OpenAI-compatible clients.
## Features
- **OpenAI-Compatible Endpoints**: Supports `/v1/models` and `/v1/chat/completions`.
- **Flowise Integration**: Translates and forwards requests to Flowise API.
- **Dockerized**: Easily deployable using Docker and Docker Compose.
- **Configurable**: Utilizes environment variables for flexible setup.
## Installation
1. **Clone the Repository**
```bash
git clone https://github.com/anqorithm/flowise-openai-wrapper.git
cd flowise-openai-wrapper
```
2. **Set Up Environment Variables**
Create a `.env` file in the project root with the following content:
```env
FLOWISE_API_BASE_URL=http://flowise:3000/api/v1
FLOWISE_CHATFLOW_ID=your_flowise_chatflow_id
```
- **`FLOWISE_API_BASE_URL`**: Base URL for the Flowise API.
- **`FLOWISE_CHATFLOW_ID`**: ID of your specific Flowise chatflow.
3. **Build and Run with Docker Compose**
```bash
docker-compose up -d --build
```
This command builds the Docker images and starts the services in detached mode.
## Usage
- **List Models**
```bash
curl http://localhost:8080/v1/models
```
- **Chat Completion**
```bash
curl --location 'http://localhost:8080/v1/chat/completions' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-4o-mini",
"messages": [
{
"role": "user",
"content": "Say this is a test!"
}
],
"temperature": 0.7
}'
## Architecture
## Project Structure
```
project_root/
├── Dockerfile
├── docker-compose.yaml
├── .env.example
├── pyproject.toml
├── poetry.lock
├── README.md
└── src/
├── main.py
├── config/
│ ├── config.py
├── api/
│ └── v1/
│ └── router.py
├── models/
│ ├── openai.py
│ └── flowise.py
└── utils/
└── helpers.py
```
- **`Dockerfile`**: Builds the Docker image for the FastAPI application.
- **`docker-compose.yaml`**: Defines the Docker services for the application and Flowise.
- **`.env.example`**: Template for environment variables.
- **`pyproject.toml` & `poetry.lock`**: Manage project dependencies with Poetry.
- **`README.md`**: Project documentation.
- **`src/`**: Contains the application source code.
- **`main.py`**: Entry point for the FastAPI application.
- **`config/config.py`**: Configuration settings using Pydantic.
- **`api/v1/router.py`**: API endpoint definitions.
- **`models/`**: Pydantic models for data validation.
- **`openai.py`**: Models representing OpenAI API data structures.
- **`flowise.py`**: Models representing Flowise data structures.
- **`utils/helpers.py`**: Utility functions like date conversions.
## Explanation
1. **Client (OpenAI-Compatible)**: Any application or user making requests in the OpenAI API format.
2. **FastAPI Wrapper**: Your FastAPI application that receives OpenAI-formatted requests.
3. **Flowise API**: The Flowise service's API endpoint that processes the translated requests.
4. **Flowise Model**: The underlying model in Flowise that generates responses.
5. **Flowise API**: Receives the response from the model and sends it back to the FastAPI wrapper.
6. **FastAPI Wrapper**: Translates Flowise responses back into OpenAI API format and returns them to the client.
## License
This project is licensed under the MIT License.