api/utils.py

# api/utils.py

from datetime import datetime
import json
import uuid
import asyncio
import random
import string
from typing import Any, Dict, Optional, AsyncGenerator

import httpx
from fastapi import HTTPException
from api.config import (
    MODELS,
    MODEL_ALIASES,
    DEFAULT_MODEL,
    API_ENDPOINT,
    get_headers_api_chat,
    BASE_URL,
    MODEL_PREFIXES,
    MODEL_REFERERS
)
from api.models import ChatRequest, Message
from api.logger import setup_logger

logger = setup_logger(__name__)

# Helper function to create a random alphanumeric chat ID
def generate_chat_id(length: int = 7) -> str:
    characters = string.ascii_letters + string.digits
    return ''.join(random.choices(characters, k=length))

# Helper function to create a chat completion data chunk
def create_chat_completion_data(
    content: str, model: str, timestamp: int, finish_reason: Optional[str] = None
) -> Dict[str, Any]:
    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,
    }

# Function to convert message to dictionary format, ensuring base64 data and optional model prefix
def message_to_dict(message: Message, model_prefix: Optional[str] = None):
    content = message.content if isinstance(message.content, str) else message.content[0]["text"]
    if model_prefix:
        content = f"{model_prefix} {content}"
    if isinstance(message.content, list) and len(message.content) == 2 and "image_url" in message.content[1]:
        # Ensure base64 images are always included for all models
        return {
            "role": message.role,
            "content": content,
            "data": {
                "imageBase64": message.content[1]["image_url"]["url"],
                "fileText": "",
                "title": "snapshot",
            },
        }
    return {"role": message.role, "content": content}

# Function to strip model prefix from content if present
def strip_model_prefix(content: str, model_prefix: Optional[str] = None) -> str:
    """Remove the model prefix from the response content if present."""
    if model_prefix and content.startswith(model_prefix):
        logger.debug(f"Stripping prefix '{model_prefix}' from content.")
        return content[len(model_prefix):].strip()
    return content

# Function to get the correct referer URL for logging
def get_referer_url(chat_id: str, model: str) -> str:
    """Generate the referer URL based on specific models listed in MODEL_REFERERS."""
    if model in MODEL_REFERERS:
        return f"{BASE_URL}/chat/{chat_id}?model={model}"
    return BASE_URL

# Helper function to format messages
def format_messages(messages: list[Message]) -> str:
    # Assuming messages need to be concatenated in some way
    return "\n".join([msg.content if isinstance(msg.content, str) else msg.content[0]["text"] for msg in messages])

# Process streaming response
async def process_streaming_response(request: ChatRequest) -> AsyncGenerator[str, None]:
    chat_id = generate_chat_id()
    referer_url = get_referer_url(chat_id, request.model)
    logger.info(f"Generated Chat ID: {chat_id} - Model: {request.model} - URL: {referer_url}")

    model = request.model if request.model in MODELS else MODEL_ALIASES.get(request.model, DEFAULT_MODEL)
    model_prefix = MODEL_PREFIXES.get(model, "")

    headers_api_chat = get_headers_api_chat(referer_url)

    # Prepare data based on model type
    if model in ['flux1', 'sdxl', 'sd', 'sd35']:  # Image models
        prompt = request.messages[-1].content if isinstance(request.messages[-1].content, str) else request.messages[-1].content[0]["text"]
        data = {
            "model": model,
            "input": {
                "width": "1024",
                "height": "1024",
                "steps": 4,
                "output_format": "webp",
                "batch_size": 1,
                "mode": "plan",
                "prompt": prompt
            }
        }
    else:  # Chat models
        data = {
            "model": model,
            "input": {
                "messages": [
                    {
                        "type": "human",
                        "content": f"{model_prefix} {format_messages(request.messages)}" if model_prefix else format_messages(request.messages)
                    }
                ],
                "mode": "plan"
            },
            "noStream": False  # Assuming streaming
        }

    async with httpx.AsyncClient() as client:
        try:
            async with client.post(
                API_ENDPOINT,
                headers=headers_api_chat,
                json=data,
                timeout=100
            ) as response:
                response.raise_for_status()
                # Assuming the API returns a streaming response
                async for line in response.aiter_lines():
                    timestamp = int(datetime.now().timestamp())
                    if line:
                        content = line
                        # Depending on GizAI's response format, adjust parsing
                        # Placeholder for content processing
                        # Assuming content contains the message
                        cleaned_content = strip_model_prefix(content, model_prefix)
                        yield f"data: {json.dumps(create_chat_completion_data(cleaned_content, model, timestamp))}\n\n"

                # Indicate end of stream
                yield f"data: {json.dumps(create_chat_completion_data('', model, int(datetime.now().timestamp()), 'stop'))}\n\n"
                yield "data: [DONE]\n\n"
        except httpx.HTTPStatusError as e:
            logger.error(f"HTTP error occurred for Chat ID {chat_id}: {e}")
            raise HTTPException(status_code=e.response.status_code, detail=str(e))
        except httpx.RequestError as e:
            logger.error(f"Error occurred during request for Chat ID {chat_id}: {e}")
            raise HTTPException(status_code=500, detail=str(e))

# Process non-streaming response
async def process_non_streaming_response(request: ChatRequest) -> Dict[str, Any]:
    chat_id = generate_chat_id()
    referer_url = get_referer_url(chat_id, request.model)
    logger.info(f"Generated Chat ID: {chat_id} - Model: {request.model} - URL: {referer_url}")

    model = request.model if request.model in MODELS else MODEL_ALIASES.get(request.model, DEFAULT_MODEL)
    model_prefix = MODEL_PREFIXES.get(model, "")

    headers_api_chat = get_headers_api_chat(referer_url)

    # Prepare data based on model type
    if model in ['flux1', 'sdxl', 'sd', 'sd35']:  # Image models
        prompt = request.messages[-1].content if isinstance(request.messages[-1].content, str) else request.messages[-1].content[0]["text"]
        data = {
            "model": model,
            "input": {
                "width": "1024",
                "height": "1024",
                "steps": 4,
                "output_format": "webp",
                "batch_size": 1,
                "mode": "plan",
                "prompt": prompt
            }
        }
    else:  # Chat models
        data = {
            "model": model,
            "input": {
                "messages": [
                    {
                        "type": "human",
                        "content": f"{model_prefix} {format_messages(request.messages)}" if model_prefix else format_messages(request.messages)
                    }
                ],
                "mode": "plan"
            },
            "noStream": True  # Non-streaming
        }

    async with httpx.AsyncClient() as client:
        try:
            response = await client.post(
                API_ENDPOINT,
                headers=headers_api_chat,
                json=data,
                timeout=100
            )
            response.raise_for_status()
            response_data = response.json()

            # Process response based on GizAI's API response structure
            # Placeholder: assuming 'output' contains the generated content
            if model in ['flux1', 'sdxl', 'sd', 'sd35']:  # Image models
                if response_data.get('status') == 'completed' and response_data.get('output'):
                    images = response_data['output']
                    # Assuming images is a list of URLs
                    # For non-streaming, return all images at once
                    # Adjust according to actual response
                    return {
                        "id": f"chatcmpl-{uuid.uuid4()}",
                        "object": "chat.completion",
                        "created": int(datetime.now().timestamp()),
                        "model": model,
                        "choices": [
                            {
                                "index": 0,
                                "message": {"role": "assistant", "content": "", "images": images},
                                "finish_reason": "stop",
                            }
                        ],
                        "usage": None,
                    }
            else:  # Chat models
                # Assuming response_data contains the full response
                content = response_data.get('output', '')
                cleaned_content = strip_model_prefix(content, model_prefix)
                return {
                    "id": f"chatcmpl-{uuid.uuid4()}",
                    "object": "chat.completion",
                    "created": int(datetime.now().timestamp()),
                    "model": model,
                    "choices": [
                        {
                            "index": 0,
                            "message": {"role": "assistant", "content": cleaned_content},
                            "finish_reason": "stop",
                        }
                    ],
                    "usage": None,
                }
        except httpx.HTTPStatusError as e:
            logger.error(f"HTTP error occurred for Chat ID {chat_id}: {e}")
            raise HTTPException(status_code=e.response.status_code, detail=str(e))
        except httpx.RequestError as e:
            logger.error(f"Error occurred during request for Chat ID {chat_id}: {e}")
            raise HTTPException(status_code=500, detail=str(e))