import json import time import math import asyncio from typing import List, Dict, Any, Callable, Union from fastapi.responses import JSONResponse, StreamingResponse from google.auth.transport.requests import Request as AuthRequest from google.genai import types from google import genai # Needed if _execute_gemini_call uses genai.Client directly # Local module imports from models import OpenAIRequest, OpenAIMessage # Changed from relative from message_processing import deobfuscate_text, convert_to_openai_format, convert_chunk_to_openai, create_final_chunk # Changed from relative import config as app_config # Changed from relative def create_openai_error_response(status_code: int, message: str, error_type: str) -> Dict[str, Any]: return { "error": { "message": message, "type": error_type, "code": status_code, "param": None, } } def create_generation_config(request: OpenAIRequest) -> Dict[str, Any]: config = {} if request.temperature is not None: config["temperature"] = request.temperature if request.max_tokens is not None: config["max_output_tokens"] = request.max_tokens if request.top_p is not None: config["top_p"] = request.top_p if request.top_k is not None: config["top_k"] = request.top_k if request.stop is not None: config["stop_sequences"] = request.stop if request.seed is not None: config["seed"] = request.seed if request.presence_penalty is not None: config["presence_penalty"] = request.presence_penalty if request.frequency_penalty is not None: config["frequency_penalty"] = request.frequency_penalty if request.n is not None: config["candidate_count"] = request.n config["safety_settings"] = [ types.SafetySetting(category="HARM_CATEGORY_HATE_SPEECH", threshold="OFF"), types.SafetySetting(category="HARM_CATEGORY_DANGEROUS_CONTENT", threshold="OFF"), types.SafetySetting(category="HARM_CATEGORY_SEXUALLY_EXPLICIT", threshold="OFF"), types.SafetySetting(category="HARM_CATEGORY_HARASSMENT", threshold="OFF"), types.SafetySetting(category="HARM_CATEGORY_CIVIC_INTEGRITY", threshold="OFF") ] return config def is_response_valid(response): if response is None: return False if hasattr(response, 'text') and response.text: return True if hasattr(response, 'candidates') and response.candidates: candidate = response.candidates[0] if hasattr(candidate, 'text') and candidate.text: return True if hasattr(candidate, 'content') and hasattr(candidate.content, 'parts'): for part in candidate.content.parts: if hasattr(part, 'text') and part.text: return True if hasattr(response, 'candidates') and response.candidates: return True # For fake streaming for attr in dir(response): if attr.startswith('_'): continue try: if isinstance(getattr(response, attr), str) and getattr(response, attr): return True except: pass print("DEBUG: Response is invalid, no usable content found") return False async def fake_stream_generator(client_instance, model_name: str, prompt: Union[types.Content, List[types.Content]], current_gen_config: Dict[str, Any], request_obj: OpenAIRequest): response_id = f"chatcmpl-{int(time.time())}" async def fake_stream_inner(): print(f"FAKE STREAMING: Making non-streaming request to Gemini API (Model: {model_name})") api_call_task = asyncio.create_task( client_instance.aio.models.generate_content( model=model_name, contents=prompt, config=current_gen_config ) ) while not api_call_task.done(): keep_alive_data = { "id": "chatcmpl-keepalive", "object": "chat.completion.chunk", "created": int(time.time()), "model": request_obj.model, "choices": [{"delta": {"content": ""}, "index": 0, "finish_reason": None}] } yield f"data: {json.dumps(keep_alive_data)}\n\n" await asyncio.sleep(app_config.FAKE_STREAMING_INTERVAL_SECONDS) try: response = api_call_task.result() if not is_response_valid(response): raise ValueError(f"Invalid/empty response in fake stream: {str(response)[:200]}") full_text = "" if hasattr(response, 'text'): full_text = response.text elif hasattr(response, 'candidates') and response.candidates: candidate = response.candidates[0] if hasattr(candidate, 'text'): full_text = candidate.text elif hasattr(candidate.content, 'parts'): full_text = "".join(part.text for part in candidate.content.parts if hasattr(part, 'text')) if request_obj.model.endswith("-encrypt-full"): full_text = deobfuscate_text(full_text) chunk_size = max(20, math.ceil(len(full_text) / 10)) for i in range(0, len(full_text), chunk_size): chunk_text = full_text[i:i+chunk_size] delta_data = { "id": response_id, "object": "chat.completion.chunk", "created": int(time.time()), "model": request_obj.model, "choices": [{"index": 0, "delta": {"content": chunk_text}, "finish_reason": None}] } yield f"data: {json.dumps(delta_data)}\n\n" await asyncio.sleep(0.05) yield create_final_chunk(request_obj.model, response_id) yield "data: [DONE]\n\n" except Exception as e: err_msg = f"Error in fake_stream_generator: {str(e)}" print(err_msg) err_resp = create_openai_error_response(500, err_msg, "server_error") yield f"data: {json.dumps(err_resp)}\n\n" yield "data: [DONE]\n\n" return fake_stream_inner() async def execute_gemini_call( current_client: Any, # Should be genai.Client or similar AsyncClient model_to_call: str, prompt_func: Callable[[List[OpenAIMessage]], Union[types.Content, List[types.Content]]], gen_config_for_call: Dict[str, Any], request_obj: OpenAIRequest # Pass the whole request object ): actual_prompt_for_call = prompt_func(request_obj.messages) if request_obj.stream: if app_config.FAKE_STREAMING_ENABLED: return StreamingResponse( await fake_stream_generator(current_client, model_to_call, actual_prompt_for_call, gen_config_for_call, request_obj), media_type="text/event-stream" ) response_id_for_stream = f"chatcmpl-{int(time.time())}" cand_count_stream = request_obj.n or 1 async def _stream_generator_inner_for_execute(): # Renamed to avoid potential clashes try: for c_idx_call in range(cand_count_stream): async for chunk_item_call in await current_client.aio.models.generate_content_stream( model=model_to_call, contents=actual_prompt_for_call, config=gen_config_for_call ): yield convert_chunk_to_openai(chunk_item_call, request_obj.model, response_id_for_stream, c_idx_call) yield create_final_chunk(request_obj.model, response_id_for_stream, cand_count_stream) yield "data: [DONE]\n\n" except Exception as e_stream_call: print(f"Streaming Error in _execute_gemini_call: {e_stream_call}") err_resp_content_call = create_openai_error_response(500, str(e_stream_call), "server_error") yield f"data: {json.dumps(err_resp_content_call)}\n\n" yield "data: [DONE]\n\n" raise # Re-raise to be caught by retry logic if any return StreamingResponse(_stream_generator_inner_for_execute(), media_type="text/event-stream") else: response_obj_call = await current_client.aio.models.generate_content( model=model_to_call, contents=actual_prompt_for_call, config=gen_config_for_call ) if not is_response_valid(response_obj_call): raise ValueError("Invalid/empty response from non-streaming Gemini call in _execute_gemini_call.") return JSONResponse(content=convert_to_openai_format(response_obj_call, request_obj.model))