api/utils.py

from datetime import datetime
import json
from typing import Any, Dict, Optional
import uuid

import httpx
from fastapi import Depends, HTTPException
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials

from api import validate
from api.config import (
    MODEL_MAPPING,
    headers,
    AGENT_MODE,
    TRENDING_AGENT_MODE,
    APP_SECRET,
    BASE_URL,
)
from api.models import ChatRequest

from api.logger import setup_logger

logger = setup_logger(__name__)

# Initialize the HTTPBearer security scheme
bearer_scheme = HTTPBearer()


def create_chat_completion_data(
    content: str, model: str, timestamp: int, finish_reason: Optional[str] = None
) -> Dict[str, Any]:
    """
    Create a dictionary representing a chat completion chunk.
    """
    return {
        "id": f"chatcmpl-{uuid.uuid4()}",
        "object": "chat.completion.chunk",
        "created": timestamp,
        "model": model,
        "choices": [
            {
                "index": 0,
                "delta": {"content": content, "role": "assistant"},
                "finish_reason": finish_reason,
            }
        ],
        "usage": None,
    }


def verify_app_secret(credentials: HTTPAuthorizationCredentials = Depends(bearer_scheme)):
    """
    Verify the APP_SECRET from the authorization credentials.
    """
    if credentials.credentials != APP_SECRET:
        logger.warning("Invalid APP_SECRET provided.")
        raise HTTPException(status_code=403, detail="Invalid APP_SECRET")
    logger.debug("APP_SECRET verified successfully.")
    return credentials.credentials


def message_to_dict(message):
    """
    Convert a message object to a dictionary suitable for the API request.
    Handles different content types gracefully.
    """
    message_dict = {"role": message.role}

    if isinstance(message.content, str):
        message_dict["content"] = message.content
    elif isinstance(message.content, list):
        # Handle list content more robustly
        try:
            if len(message.content) >= 2:
                # Assuming the first element has 'text' and the second has 'image_url'
                text_content = message.content[0].get("text", "")
                image_url = message.content[1].get("image_url", {}).get("url", "")
                message_dict["content"] = text_content
                message_dict["data"] = {
                    "imageBase64": image_url,
                    "fileText": "",
                    "title": "snapshot",
                }
            else:
                # Fallback if the list doesn't have expected structure
                message_dict["content"] = json.dumps(message.content)
        except (AttributeError, KeyError, TypeError) as e:
            logger.error(f"Error parsing message content: {e}")
            message_dict["content"] = "Invalid message format."
    else:
        # Fallback for unexpected content types
        message_dict["content"] = str(message.content)

    return message_dict


def get_agent_mode(model: str) -> Dict[str, Any]:
    """
    Retrieves the agent mode configuration.
    Falls back to an empty dictionary if not found.
    """
    agent_mode = AGENT_MODE.get(model, {})
    if not agent_mode:
        logger.warning(f"No AGENT_MODE configuration found for model: {model}")
    return agent_mode


def get_trending_agent_mode(model: str) -> Dict[str, Any]:
    """
    Retrieves the trending agent mode configuration.
    Falls back to an empty dictionary if not found.
    """
    trending_agent_mode = TRENDING_AGENT_MODE.get(model, {})
    if not trending_agent_mode:
        logger.warning(f"No TRENDING_AGENT_MODE configuration found for model: {model}")
    return trending_agent_mode


async def process_streaming_response(request: ChatRequest):
    """
    Process a streaming response for a chat completion request.
    """
    agent_mode = get_agent_mode(request.model)
    trending_agent_mode = get_trending_agent_mode(request.model)

    # Log reduced information
    logger.info(
        f"Streaming request for model: '{request.model}', "
        f"agent mode: {agent_mode}, trending agent mode: {trending_agent_mode}"
    )

    json_data = {
        "messages": [message_to_dict(msg) for msg in request.messages],
        "previewToken": None,
        "userId": None,
        "codeModelMode": True,
        "agentMode": agent_mode,
        "trendingAgentMode": trending_agent_mode,
        "isMicMode": False,
        "userSystemPrompt": None,
        "maxTokens": request.max_tokens,
        "playgroundTopP": request.top_p,
        "playgroundTemperature": request.temperature,
        "isChromeExt": False,
        "githubToken": None,
        "clickedAnswer2": False,
        "clickedAnswer3": False,
        "clickedForceWebSearch": False,
        "visitFromDelta": False,
        "mobileClient": False,
        "userSelectedModel": MODEL_MAPPING.get(request.model),
        "validated": validate.getHid(),
    }

    async with httpx.AsyncClient() as client:
        try:
            async with client.stream(
                "POST",
                f"{BASE_URL}/api/chat",
                headers=headers,
                json=json_data,
                timeout=httpx.Timeout(100.0),
            ) as response:
                response.raise_for_status()
                timestamp = int(datetime.now().timestamp())
                async for line in response.aiter_lines():
                    if line:
                        content = line.strip() + "\n"
                        if "https://www.blackbox.ai" in content:
                            validate.getHid(True)
                            content = "hid已刷新,重新对话即可\n"
                            yield f"data: {json.dumps(create_chat_completion_data(content, request.model, timestamp))}\n\n"
                            break
                        if content.startswith("$@$v=undefined-rv1$@$"):
                            content = content[21:]
                        yield f"data: {json.dumps(create_chat_completion_data(content, request.model, timestamp))}\n\n"

                # Indicate the end of the stream
                yield f"data: {json.dumps(create_chat_completion_data('', request.model, timestamp, 'stop'))}\n\n"
                yield "data: [DONE]\n\n"
        except httpx.HTTPStatusError as e:
            logger.error(f"HTTP error occurred: {e.response.status_code} - {e.response.text}")
            raise HTTPException(status_code=e.response.status_code, detail="Error from upstream service.")
        except httpx.RequestError as e:
            logger.error(f"Request error occurred: {e}")
            raise HTTPException(status_code=500, detail="Internal server error.")
        except Exception as e:
            logger.error(f"Unexpected error: {e}")
            raise HTTPException(status_code=500, detail="Internal server error.")


async def process_non_streaming_response(request: ChatRequest):
    """
    Process a non-streaming response for a chat completion request.
    """
    agent_mode = get_agent_mode(request.model)
    trending_agent_mode = get_trending_agent_mode(request.model)

    # Log reduced information
    logger.info(
        f"Non-streaming request for model: '{request.model}', "
        f"agent mode: {agent_mode}, trending agent mode: {trending_agent_mode}"
    )

    json_data = {
        "messages": [message_to_dict(msg) for msg in request.messages],
        "previewToken": None,
        "userId": None,
        "codeModelMode": True,
        "agentMode": agent_mode,
        "trendingAgentMode": trending_agent_mode,
        "isMicMode": False,
        "userSystemPrompt": None,
        "maxTokens": request.max_tokens,
        "playgroundTopP": request.top_p,
        "playgroundTemperature": request.temperature,
        "isChromeExt": False,
        "githubToken": None,
        "clickedAnswer2": False,
        "clickedAnswer3": False,
        "clickedForceWebSearch": False,
        "visitFromDelta": False,
        "mobileClient": False,
        "userSelectedModel": MODEL_MAPPING.get(request.model),
        "validated": validate.getHid(),
    }

    try:
        async with httpx.AsyncClient() as client:
            response = await client.post(
                f"{BASE_URL}/api/chat",
                headers=headers,
                json=json_data,
                timeout=httpx.Timeout(100.0),
            )
            response.raise_for_status()
            full_response = response.text

        # Process the full response
        if "https://www.blackbox.ai" in full_response:
            validate.getHid(True)
            full_response = "hid已刷新，重新对话即可"
        if full_response.startswith("$@$v=undefined-rv1$@$"):
            full_response = full_response[21:]

        return {
            "id": f"chatcmpl-{uuid.uuid4()}",
            "object": "chat.completion",
            "created": int(datetime.now().timestamp()),
            "model": request.model,
            "choices": [
                {
                    "index": 0,
                    "message": {"role": "assistant", "content": full_response},
                    "finish_reason": "stop",
                }
            ],
            "usage": None,
        }
    except httpx.HTTPStatusError as e:
        logger.error(f"HTTP error occurred: {e.response.status_code} - {e.response.text}")
        raise HTTPException(status_code=e.response.status_code, detail="Error from upstream service.")
    except httpx.RequestError as e:
        logger.error(f"Request error occurred: {e}")
        raise HTTPException(status_code=500, detail="Internal server error.")
    except Exception as e:
        logger.error(f"Unexpected error: {e}")
        raise HTTPException(status_code=500, detail="Internal server error.")