app.py

import os
import json
from datetime import datetime
from typing import List, Dict

import requests
from fastapi import FastAPI, HTTPException
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
from pydantic import BaseModel
import plotly.graph_objs as go
from apscheduler.schedulers.asyncio import AsyncIOScheduler

from huggingface_hub import AsyncInferenceClient

app = FastAPI()

# Configuration
models = [
    "meta-llama/Meta-Llama-3.1-8B-Instruct",
    "meta-llama/Meta-Llama-3.1-70B-Instruct",
    "meta-llama/Meta-Llama-3-8B-Instruct",
    "meta-llama/Meta-Llama-3-70B-Instruct",
    "meta-llama/Llama-Guard-3-8B",
    "meta-llama/Llama-2-7b-chat-hf",
    "meta-llama/Llama-2-13b-chat-hf",
    "deepseek-ai/DeepSeek-Coder-V2-Instruct",
    "mistralai/Mistral-7B-Instruct-v0.3",
    "mistralai/Mixtral-8x7B-Instruct-v0.1",
]
LOG_FILE = "/data/api_logs.json"


client = AsyncInferenceClient(token=os.environ["HF_INFERENCE_API_TOKEN"])

# Ensure log file exists
if not os.path.exists(LOG_FILE):
    with open(LOG_FILE, "w") as f:
        json.dump([], f)

class LogEntry(BaseModel):
    model: str
    success: bool
    timestamp: str
    failure_message: str

async def check_apis():
    results = []
    for model in models:
        try:
            response = await client.chat_completion(
            	messages=[{"role": "user", "content": "What is the capital of France?"}],
            	max_tokens=10,
            )
            success = True
            e = 'success'
        except Exception as e:
            print(e)
            success = False
        
        results.append(LogEntry(
            model=model,
            success=success,
            timestamp=datetime.now().isoformat(),
            failure_message=str(e)
        ))
    
    with open(LOG_FILE, "r+") as f:
        logs = json.load(f)
        logs.extend([result.dict() for result in results])
        f.seek(0)
        json.dump(logs, f)

@app.on_event("startup")
async def start_scheduler():
    scheduler = AsyncIOScheduler()
    scheduler.add_job(check_apis, 'interval', minutes=10)
    scheduler.start()

@app.get("/")
async def index():
    return FileResponse("static/index.html")

@app.get("/api/logs", response_model=List[LogEntry])
async def get_logs():
    with open(LOG_FILE, "r") as f:
        logs = json.load(f)
    return logs

@app.get("/api/chart-data", response_model=Dict[str, Dict[str, Dict[str, List]]])
async def get_chart_data():
    with open(LOG_FILE, "r") as f:
        logs = json.load(f)
    
    chart_data = {}
    for log in logs:
        model = log['model']
        if model not in chart_data:
            chart_data[model] = {
                'success': {'x': [], 'y': []},
                'failure': {'x': [], 'y': []}
            }
        
        status = 'success' if log['success'] else 'failure'
        chart_data[model][status]['x'].append(log['timestamp'])
        chart_data[model][status]['y'].append(1)
    
    return chart_data

# Mount the static files directory
app.mount("/static", StaticFiles(directory="static"), name="static")

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=7860)