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: print("DEBUG: Response is None, therefore invalid.") return False # Check for direct text attribute if hasattr(response, 'text') and isinstance(response.text, str) and response.text.strip(): # print("DEBUG: Response valid due to response.text") return True # Check candidates for text content if hasattr(response, 'candidates') and response.candidates: for candidate in response.candidates: # Iterate through all candidates if hasattr(candidate, 'text') and isinstance(candidate.text, str) and candidate.text.strip(): # print(f"DEBUG: Response valid due to candidate.text in candidate") return True if hasattr(candidate, 'content') and hasattr(candidate.content, 'parts') and candidate.content.parts: for part in candidate.content.parts: if hasattr(part, 'text') and isinstance(part.text, str) and part.text.strip(): # print(f"DEBUG: Response valid due to part.text in candidate's content part") return True # Removed prompt_feedback as a sole criterion for validity. # It should only be valid if actual text content is found. # Block reasons will be checked explicitly by callers if they need to treat it as an error for retries. print("DEBUG: Response is invalid, no usable text content found by is_response_valid.") 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, is_auto_attempt: bool): 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() # Check for safety blocks first, as this should trigger a retry in auto-mode if hasattr(response, 'prompt_feedback') and \ hasattr(response.prompt_feedback, 'block_reason') and \ response.prompt_feedback.block_reason: block_message = f"Response blocked by safety filter: {response.prompt_feedback.block_reason}" if hasattr(response.prompt_feedback, 'block_reason_message') and response.prompt_feedback.block_reason_message: block_message = f"Response blocked by safety filter: {response.prompt_feedback.block_reason_message} (Reason: {response.prompt_feedback.block_reason})" print(f"DEBUG: {block_message} (in fake_stream_generator)") # Log this specific condition raise ValueError(block_message) # This will be caught by the except Exception as e below it if not is_response_valid(response): # is_response_valid now only checks for actual text raise ValueError(f"Invalid/empty response in fake stream (no text content): {str(response)[:200]}") full_text = "" if hasattr(response, 'text'): full_text = response.text or "" # Coalesce None to empty string elif hasattr(response, 'candidates') and response.candidates: # Typically, we focus on the first candidate for non-streaming synthesis candidate = response.candidates[0] if hasattr(candidate, 'text'): full_text = candidate.text or "" # Coalesce None to empty string elif hasattr(candidate, 'content') and hasattr(candidate.content, 'parts') and candidate.content.parts: # Ensure parts are iterated and text is joined correctly even if some parts have no text or part.text is None texts = [] for part in candidate.content.parts: if hasattr(part, 'text') and part.text is not None: # Check part.text exists and is not None texts.append(part.text) full_text = "".join(texts) 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") # It's good practice to log the JSON payload here too for consistency, # though the main concern was the true streaming path. json_payload_for_fake_stream_error = json.dumps(err_resp) # Log the error JSON that WOULD have been sent if not in auto-mode or if this was the final error handler. print(f"DEBUG: Internal error in fake_stream_generator. JSON error for handler: {json_payload_for_fake_stream_error}") if not is_auto_attempt: yield f"data: {json_payload_for_fake_stream_error}\n\n" yield "data: [DONE]\n\n" raise e # Re-raise the original exception e 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 is_auto_attempt: bool = False ): 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, is_auto_attempt=is_auto_attempt), 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}") error_message_str = str(e_stream_call) # Truncate very long error messages to prevent excessively large JSON payloads. if len(error_message_str) > 1024: # Max length for the error string error_message_str = error_message_str[:1024] + "..." err_resp_content_call = create_openai_error_response(500, error_message_str, "server_error") json_payload_for_error = json.dumps(err_resp_content_call) # Log the error JSON that WOULD have been sent if not in auto-mode or if this was the final error handler. print(f"DEBUG: Internal error in _stream_generator_inner_for_execute. JSON error for handler: {json_payload_for_error}") if not is_auto_attempt: # is_auto_attempt is from execute_gemini_call's scope yield f"data: {json_payload_for_error}\n\n" yield "data: [DONE]\n\n" raise e_stream_call # Re-raise the original exception 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 ) # Check for safety blocks first for non-streaming calls if hasattr(response_obj_call, 'prompt_feedback') and \ hasattr(response_obj_call.prompt_feedback, 'block_reason') and \ response_obj_call.prompt_feedback.block_reason: block_message = f"Response blocked by safety filter: {response_obj_call.prompt_feedback.block_reason}" if hasattr(response_obj_call.prompt_feedback, 'block_reason_message') and response_obj_call.prompt_feedback.block_reason_message: block_message = f"Response blocked by safety filter: {response_obj_call.prompt_feedback.block_reason_message} (Reason: {response_obj_call.prompt_feedback.block_reason})" print(f"DEBUG: {block_message} (in execute_gemini_call non-streaming)") # Log this specific condition raise ValueError(block_message) if not is_response_valid(response_obj_call): # is_response_valid now only checks for actual text raise ValueError("Invalid/empty response from non-streaming Gemini call (no text content).") return JSONResponse(content=convert_to_openai_format(response_obj_call, request_obj.model))