app.py

import os
import logging
import httpx
from dotenv import load_dotenv
import gradio as gr
from typing import AsyncGenerator, List, Dict

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Load environment variables
load_dotenv()
logger.info("Environment variables loaded from .env file")
logger.info(f"OPENAI_API_KEY present: {'OPENAI_API_KEY' in os.environ}")
logger.info(f"ANTHROPIC_API_KEY present: {'ANTHROPIC_API_KEY' in os.environ}")
logger.info(f"GEMINI_API_KEY present: {'GEMINI_API_KEY' in os.environ}")

async def ask_openai(query: str, history: List[Dict[str, str]]) -> AsyncGenerator[str, None]:
    openai_api_key = os.getenv("OPENAI_API_KEY")
    if not openai_api_key:
        logger.error("OpenAI API key not provided")
        yield "Error: OpenAI API key not provided."
        return

    # Build message history
    messages = []
    for msg in history:
        messages.append({"role": "user", "content": msg["user"]})
        if msg["bot"]:
            messages.append({"role": "assistant", "content": msg["bot"]})
    messages.append({"role": "user", "content": query})

    headers = {
        "Authorization": f"Bearer {openai_api_key}",
        "Content-Type": "application/json"
    }

    payload = {
        "model": "gpt-3.5-turbo",
        "messages": messages,
        "stream": True
    }

    try:
        async with httpx.AsyncClient() as client:
            async with client.stream("POST", "https://api.openai.com/v1/chat/completions", headers=headers, json=payload) as response:
                response.raise_for_status()
                async for chunk in response.aiter_text():
                    if chunk:
                        # Parse the streaming chunk (JSON lines)
                        lines = chunk.splitlines()
                        for line in lines:
                            if line.startswith("data: "):
                                data = line[6:]  # Remove "data: " prefix
                                if data == "[DONE]":
                                    break
                                try:
                                    json_data = eval(data)  # Safely parse JSON
                                    if "choices" inㅇ json_data and json_data["choices"]:
                                        delta = json_data["choices"][0].get("delta", {})
                                        if "content" in delta:
                                            yield delta["content"]
                                except Exception as e:
                                    logger.error(f"Error parsing OpenAI stream chunk: {str(e)}")
                                    yield f"Error parsing stream: {str(e)}"

    except httpx.HTTPStatusError as e:
        logger.error(f"OpenAI HTTP Status Error: {e.response.status_code}, {e.response.text}")
        yield f"Error: OpenAI HTTP Status Error: {e.response.status_code}, {e.response.text}"
    except Exception as e:
        logger.error(f"OpenAI Error: {str(e)}")
        yield f"Error: OpenAI Error: {str(e)}"

async def ask_anthropic(query: str, history: List[Dict[str, str]]) -> str:
    anthropic_api_key = os.getenv("ANTHROPIC_API_KEY")
    if not anthropic_api_key:
        logger.error("Anthropic API key not provided")
        return "Error: Anthropic API key not provided."

    # Build message history
    messages = []
    for msg in history:
        messages.append({"role": "user", "content": msg["user"]})
        if msg["bot"]:
            messages.append({"role": "assistant", "content": msg["bot"]})
    messages.append({"role": "user", "content": query})

    headers = {
        "x-api-key": anthropic_api_key,
        "anthropic-version": "2023-06-01",
        "Content-Type": "application/json"
    }

    payload = {
        "model": "claude-3-5-sonnet-20241022",
        "max_tokens": 1024,
        "messages": messages
    }

    try:
        async with httpx.AsyncClient() as client:
            logger.info(f"Sending Anthropic request: {payload}")
            response = await client.post("https://api.anthropic.com/v1/messages", headers=headers, json=payload)
        
        response.raise_for_status()
        logger.info(f"Anthropic response: {response.json()}")
        return response.json()['content'][0]['text']

    except httpx.HTTPStatusError as e:
        logger.error(f"Anthropic HTTP Status Error: {e.response.status_code}, {e.response.text}")
        return f"Error: Anthropic HTTP Status Error: {e.response.status_code}, {e.response.text}"
    except Exception as e:
        logger.error(f"Anthropic Error: {str(e)}")
        return f"Error: Anthropic Error: {str(e)}"

async def ask_gemini(query: str, history: List[Dict[str, str]]) -> str:
    gemini_api_key = os.getenv("GEMINI_API_KEY")
    if not gemini_api_key:
        logger.error("Gemini API key not provided")
        return "Error: Gemini API key not provided."

    # Gemini doesn't natively support chat history in the same way, so we concatenate history as text
    history_text = ""
    for msg in history:
        history_text += f"User: {msg['user']}\nAssistant: {msg['bot']}\n" if msg["bot"] else f"User: {msg['user']}\n"
    full_query = history_text + f"User: {query}\n"

    headers = {
        "Content-Type": "application/json"
    }

    payload = {
        "contents": [{"parts": [{"text": full_query}]}]
    }

    try:
        async with httpx.AsyncClient() as client:
            response = await client.post(
                f"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent?key={gemini_api_key}",
                headers=headers,
                json=payload
            )
        
        response.raise_for_status()
        return response.json()['candidates'][0]['content']['parts'][0]['text']

    except httpx.HTTPStatusError as e:
        logger.error(f"Gemini HTTP Status Error: {e.response.status_code}, {e.response.text}")
        return f"Error: Gemini HTTP Status Error: {e.response.status_code}, {e.response.text}"
    except Exception as e:
        logger.error(f"Gemini Error: {str(e)}")
        return f"Error: Gemini Error: {str(e)}"

async def query_model(query: str, provider: str, history: List[Dict[str, str]]):
    provider = provider.lower()
    if provider == "openai":
        async for chunk in ask_openai(query, history):
            yield chunk
    elif provider == "anthropic":
        yield await ask_anthropic(query, history)
    elif provider == "gemini":
        yield await ask_gemini(query, history)
    else:
        yield f"Error: Unknown provider: {provider}"

# Gradio interface
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# Multi-Model Chat")
    gr.Markdown("Chat with OpenAI, Anthropic, or Gemini. Select a provider and start typing!")
    
    provider = gr.Dropdown(choices=["OpenAI", "Anthropic", "Gemini"], label="Select Provider", value="OpenAI")
    chatbot = gr.ChatInterface(
        fn=query_model,
        additional_inputs=[provider],
        title="",
        description=""
    )

# Launch the Gradio app
demo.launch()