genai-rest-builder 0.1.0

A tool to generate python code with GenAI RestAPIs.

GenAI REST Builder

The GenAI REST Builder is a tool that helps create RESTful services around AI models using a YAML configuration file. It automates the setup of FastAPI endpoints, configurations, and environment files for easy deployment of AI-powered services.

Key Features

• Service Configuration with Custom Prompts: Define each service's prompt, model configuration, and provider-specific details in YAML format.
• Cloud Provider Compatibility: Supports major providers, including AWS and Azure.
• Automated Code Generation: Quickly create FastAPI service endpoints based on YAML configurations.

Installation

1. Install the GenAI REST Builder Tool:

   Start by installing the genai-rest-builder package:

   pip install genai-rest-builder
   

2. Generate Project Structure:

   Use the command below to generate the full project structure with REST APIs for all defined services based on your YAML configuration file:

   genai-rest-proj-build
   

   This reads from prompt_service.yaml (user needs to create it with prompt details) and creates a structured project with service files, configuration settings, and the main FastAPI application.

3. Install Project Dependencies:

   Once the project structure is generated, install the required dependencies:

   pip install -r requirements.txt
   

4. Run the Server:

   Launch the FastAPI server using serve_app.py:

   python serve_app.py
   

   The server will start based on the host and port specified in the .env file, defaulting to localhost:8080 if not configured otherwise.

Example YAML - prompt_service.yaml Configuration File

Here’s the structure of a sample YAML configuration file that defines services:

PromptServices:
  - <servicename>:
      prompt: <prompt template>
      model:
        provider: [aws, azure]
        modelId: <model id>
        temperature: <temperature>
        maxTokens: <maximum tokens>

YAML Configuration Details

• servicename: Unique identifier for the service.
• prompt: Template for the AI model’s prompt.
• model: Contains model details such as:
  • provider: Cloud provider (either aws or azure).
  • modelId: ID for the specific model.
  • temperature: Controls randomness in the output.
  • maxTokens: Specifies the maximum tokens the model should generate.

Project Structure

The following structure is generated after running the project build command:

.
├── service_chains/
│   ├── <servicename>_chain.py          # Generated service chain files for each service
│   ├── __init__.py                      # Package initialization file
├── serve_app.py                         # Main FastAPI application
├── .env                                 # Environment configuration file
├── requirements.txt                     # Dependencies file
├── prompt_service.yaml                  # YAML configuration file (user-defined)

Accessing API Documentation

After starting the server, the OpenAPI documentation is available at:

http://<GENAI_SERVER_HOST>:<GENAI_SERVER_PORT>/docs

This page provides an interactive UI to explore and test the API endpoints.

Invoking Services

Each service can be accessed via its unique REST API path, structured as follows:

http://<GENAI_SERVER_HOST>:<GENAI_SERVER_PORT>/<service>/invoke

Replace <service> with the name defined in the YAML configuration file to make requests to that service.