main.py

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from huggingface_hub import InferenceClient

app = FastAPI()

# Define the API URL for the model
API_URL = "https://api-inference.huggingface.co/models/meta-llama/CodeLlama-13b-hf"

# Define the request model
class GenerateRequest(BaseModel):
    prompt: str
    instructions: str
    api_key: str

def format_prompt(message, custom_instructions=None):
    """
    Format the prompt with optional custom instructions.
    """
    prompt = ""
    if custom_instructions:
        prompt += f"{custom_instructions}\n"
    prompt += f"{message}"
    return prompt

def CodeLlama(prompt, instructions, api, temperature=0.1, max_new_tokens=2000, top_p=0.95, repetition_penalty=1.0):
    """
    Generate text using the CodeLlama model with specified parameters.
    """
    try:
        # Ensure parameters are valid
        temperature = float(temperature)
        if temperature < 1e-2:
            temperature = 1e-2
        top_p = float(top_p)

        generate_kwargs = dict(
            temperature=temperature,
            max_new_tokens=max_new_tokens,
            top_p=top_p,
            repetition_penalty=repetition_penalty,
            do_sample=True,
            seed=69,
        )

        # Format the prompt
        formatted_prompt = format_prompt(prompt, instructions)

        # Initialize the client and make the request
        head = {"Authorization": f"Bearer {api}"}
        client = InferenceClient(API_URL, headers=head)
        response = client.text_generation(formatted_prompt, **generate_kwargs)
        return response
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Error: {str(e)}")

@app.post("/generate-text")
async def generate_text(request: GenerateRequest):
    """
    FastAPI endpoint to generate text based on the input request.
    """
    if not request.prompt or not request.instructions or not request.api_key:
        raise HTTPException(status_code=400, detail="Missing required fields")

    try:
        response = CodeLlama(request.prompt, request.instructions, request.api_key)
        return {"response": response}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Error: {str(e)}")