refactor: enhance stream error handling and optimize code structure
- Initialize timestamps at start to avoid null checks - Add detailed error handling for streaming response - Handle CancelledError and other exceptions separately - Unify exception handling with trace_exception - Clean up redundant code and simplify logic
This commit is contained in:
yangdx
@@ -203,16 +203,16 @@ class OllamaAPI:
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)
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async def stream_generator():
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first_chunk_time = time.time_ns()
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last_chunk_time = first_chunk_time
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total_response = ""
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try:
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first_chunk_time = None
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last_chunk_time = None
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total_response = ""
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# Ensure response is an async generator
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if isinstance(response, str):
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# If it's a string, send in two parts
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first_chunk_time = time.time_ns()
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last_chunk_time = first_chunk_time
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last_chunk_time = time.time_ns()
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total_response = response
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data = {
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@@ -241,21 +241,48 @@ class OllamaAPI:
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}
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yield f"{json.dumps(data, ensure_ascii=False)}\n"
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else:
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async for chunk in response:
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if chunk:
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if first_chunk_time is None:
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first_chunk_time = time.time_ns()
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try:
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async for chunk in response:
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if chunk:
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if first_chunk_time is None:
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first_chunk_time = time.time_ns()
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last_chunk_time = time.time_ns()
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last_chunk_time = time.time_ns()
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total_response += chunk
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data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"response": chunk,
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"done": False,
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}
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yield f"{json.dumps(data, ensure_ascii=False)}\n"
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total_response += chunk
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data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"response": chunk,
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"done": False,
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}
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yield f"{json.dumps(data, ensure_ascii=False)}\n"
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except (asyncio.CancelledError, Exception) as e:
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error_msg = str(e)
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if isinstance(e, asyncio.CancelledError):
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error_msg = "Stream was cancelled by server"
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else:
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error_msg = f"Provider error: {error_msg}"
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logging.error(f"Stream error: {error_msg}")
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# Send error message to client
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error_data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"response": f"\n\nError: {error_msg}",
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"done": False,
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}
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yield f"{json.dumps(error_data, ensure_ascii=False)}\n"
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# Send final message to close the stream
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final_data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"done": True,
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}
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yield f"{json.dumps(final_data, ensure_ascii=False)}\n"
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return
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completion_tokens = estimate_tokens(total_response)
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total_time = last_chunk_time - start_time
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@@ -381,16 +408,15 @@ class OllamaAPI:
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)
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async def stream_generator():
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first_chunk_time = None
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last_chunk_time = None
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first_chunk_time = time.time_ns()
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last_chunk_time = first_chunk_time
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total_response = ""
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try:
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# Ensure response is an async generator
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if isinstance(response, str):
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# If it's a string, send in two parts
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first_chunk_time = time.time_ns()
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last_chunk_time = first_chunk_time
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last_chunk_time = time.time_ns()
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total_response = response
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data = {
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@@ -474,45 +500,27 @@ class OllamaAPI:
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yield f"{json.dumps(final_data, ensure_ascii=False)}\n"
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return
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if last_chunk_time is not None:
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completion_tokens = estimate_tokens(total_response)
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total_time = last_chunk_time - start_time
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prompt_eval_time = first_chunk_time - start_time
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eval_time = last_chunk_time - first_chunk_time
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completion_tokens = estimate_tokens(total_response)
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total_time = last_chunk_time - start_time
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prompt_eval_time = first_chunk_time - start_time
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eval_time = last_chunk_time - first_chunk_time
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data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"done": True,
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"total_duration": total_time,
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"load_duration": 0,
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"prompt_eval_count": prompt_tokens,
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"prompt_eval_duration": prompt_eval_time,
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"eval_count": completion_tokens,
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"eval_duration": eval_time,
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}
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yield f"{json.dumps(data, ensure_ascii=False)}\n"
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data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"done": True,
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"total_duration": total_time,
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"load_duration": 0,
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"prompt_eval_count": prompt_tokens,
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"prompt_eval_duration": prompt_eval_time,
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"eval_count": completion_tokens,
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"eval_duration": eval_time,
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}
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yield f"{json.dumps(data, ensure_ascii=False)}\n"
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except Exception as e:
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error_msg = f"Error in stream_generator: {str(e)}"
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logging.error(error_msg)
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# Send error message to client
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error_data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"error": {"code": "STREAM_ERROR", "message": error_msg},
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}
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yield f"{json.dumps(error_data, ensure_ascii=False)}\n"
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# Ensure sending end marker
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final_data = {
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"model": self.ollama_server_infos.LIGHTRAG_MODEL,
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"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
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"done": True,
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}
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yield f"{json.dumps(final_data, ensure_ascii=False)}\n"
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return
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trace_exception(e)
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raise
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return StreamingResponse(
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stream_generator(),
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