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This commit is contained in:
yangdx
2025-01-17 14:27:27 +08:00
parent fa9765ecd9
commit a561879040
1 changed files with 34 additions and 47 deletions
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81
lightrag/api/lightrag_ollama.py
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@@ -541,13 +541,13 @@ def create_app(args):
async def stream_generator(): async def stream_generator():
if isinstance(response, str): if isinstance(response, str):
# 如果是字符串，一次性发送 # If it's a string, send it all at once
yield f"{json.dumps({'response': response})}\n" yield f"{json.dumps({'response': response})}\n"
else: else:
# 如果是异步生成器，逐块发送 # If it's an async generator, send chunks one by one
try: try:
async for chunk in response: async for chunk in response:
if chunk: # 只发送非空内容 if chunk: # Only send non-empty content
yield f"{json.dumps({'response': chunk})}\n" yield f"{json.dumps({'response': chunk})}\n"
except Exception as e: except Exception as e:
logging.error(f"Streaming error: {str(e)}") logging.error(f"Streaming error: {str(e)}")
@@ -563,7 +563,7 @@ def create_app(args):
"Access-Control-Allow-Origin": "*", "Access-Control-Allow-Origin": "*",
"Access-Control-Allow-Methods": "POST, OPTIONS", "Access-Control-Allow-Methods": "POST, OPTIONS",
"Access-Control-Allow-Headers": "Content-Type", "Access-Control-Allow-Headers": "Content-Type",
"X-Accel-Buffering": "no", # 禁用 Nginx 缓冲 "X-Accel-Buffering": "no", # Disable Nginx buffering
}, },
) )
except Exception as e: except Exception as e:
@@ -760,7 +760,6 @@ def create_app(args):
last_chunk_time = first_chunk_time last_chunk_time = first_chunk_time
total_response = response total_response = response
# 第一次发送查询内容
data = { data = {
"model": LIGHTRAG_MODEL, "model": LIGHTRAG_MODEL,
"created_at": LIGHTRAG_CREATED_AT, "created_at": LIGHTRAG_CREATED_AT,
@@ -773,41 +772,35 @@ def create_app(args):
} }
yield f"{json.dumps(data, ensure_ascii=False)}\n" yield f"{json.dumps(data, ensure_ascii=False)}\n"
# 计算各项指标
completion_tokens = estimate_tokens(total_response) completion_tokens = estimate_tokens(total_response)
total_time = last_chunk_time - start_time # 总时间 total_time = last_chunk_time - start_time
prompt_eval_time = ( prompt_eval_time = (
first_chunk_time - start_time first_chunk_time - start_time
) # 首个响应之前的时间 )
eval_time = ( eval_time = (
last_chunk_time - first_chunk_time last_chunk_time - first_chunk_time
) # 生成响应的时间 )
# 第二次发送统计信息
data = { data = {
"model": LIGHTRAG_MODEL, "model": LIGHTRAG_MODEL,
"created_at": LIGHTRAG_CREATED_AT, "created_at": LIGHTRAG_CREATED_AT,
"done": True, "done": True,
"total_duration": total_time, # 总时间 "total_duration": total_time,
"load_duration": 0, # 加载时间为0 "load_duration": 0,
"prompt_eval_count": prompt_tokens, # 输入token数 "prompt_eval_count": prompt_tokens,
"prompt_eval_duration": prompt_eval_time, # 首个响应之前的时间 "prompt_eval_duration": prompt_eval_time,
"eval_count": completion_tokens, # 输出token数 "eval_count": completion_tokens,
"eval_duration": eval_time, # 生成响应的时间 "eval_duration": eval_time,
} }
yield f"{json.dumps(data, ensure_ascii=False)}\n" yield f"{json.dumps(data, ensure_ascii=False)}\n"
else: else:
# 流式响应
async for chunk in response: async for chunk in response:
if chunk: # 只发送非空内容 if chunk:
# 记录第一个chunk的时间
if first_chunk_time is None: if first_chunk_time is None:
first_chunk_time = time.time_ns() first_chunk_time = time.time_ns()
# 更新最后一个chunk的时间
last_chunk_time = time.time_ns() last_chunk_time = time.time_ns()
# 累积响应内容
total_response += chunk total_response += chunk
data = { data = {
"model": LIGHTRAG_MODEL, "model": LIGHTRAG_MODEL,
@@ -821,30 +814,28 @@ def create_app(args):
} }
yield f"{json.dumps(data, ensure_ascii=False)}\n" yield f"{json.dumps(data, ensure_ascii=False)}\n"
# 计算各项指标
completion_tokens = estimate_tokens(total_response) completion_tokens = estimate_tokens(total_response)
total_time = last_chunk_time - start_time # 总时间 total_time = last_chunk_time - start_time
prompt_eval_time = ( prompt_eval_time = (
first_chunk_time - start_time first_chunk_time - start_time
) # 首个响应之前的时间 )
eval_time = ( eval_time = (
last_chunk_time - first_chunk_time last_chunk_time - first_chunk_time
) # 生成响应的时间 )
# 发送完成标记，包含性能统计信息
data = { data = {
"model": LIGHTRAG_MODEL, "model": LIGHTRAG_MODEL,
"created_at": LIGHTRAG_CREATED_AT, "created_at": LIGHTRAG_CREATED_AT,
"done": True, "done": True,
"total_duration": total_time, # 总时间 "total_duration": total_time,
"load_duration": 0, # 加载时间为0 "load_duration": 0,
"prompt_eval_count": prompt_tokens, # 输入token数 "prompt_eval_count": prompt_tokens,
"prompt_eval_duration": prompt_eval_time, # 首个响应之前的时间 "prompt_eval_duration": prompt_eval_time,
"eval_count": completion_tokens, # 输出token数 "eval_count": completion_tokens,
"eval_duration": eval_time, # 生成响应的时间 "eval_duration": eval_time,
} }
yield f"{json.dumps(data, ensure_ascii=False)}\n" yield f"{json.dumps(data, ensure_ascii=False)}\n"
return # 确保生成器在发送完成标记后立即结束 return # Ensure the generator ends immediately after sending the completion marker
except Exception as e: except Exception as e:
logging.error(f"Error in stream_generator: {str(e)}") logging.error(f"Error in stream_generator: {str(e)}")
raise raise
@@ -862,37 +853,33 @@ def create_app(args):
}, },
) )
else: else:
# 非流式响应
first_chunk_time = time.time_ns() first_chunk_time = time.time_ns()
response_text = await rag.aquery(cleaned_query, param=query_param) response_text = await rag.aquery(cleaned_query, param=query_param)
last_chunk_time = time.time_ns() last_chunk_time = time.time_ns()
# 确保响应不为空
if not response_text: if not response_text:
response_text = "No response generated" response_text = "No response generated"
# 计算各项指标
completion_tokens = estimate_tokens(str(response_text)) completion_tokens = estimate_tokens(str(response_text))
total_time = last_chunk_time - start_time # 总时间 total_time = last_chunk_time - start_time
prompt_eval_time = first_chunk_time - start_time # 首个响应之前的时间 prompt_eval_time = first_chunk_time - start_time
eval_time = last_chunk_time - first_chunk_time # 生成响应的时间 eval_time = last_chunk_time - first_chunk_time
# 构造响应，包含性能统计信息
return { return {
"model": LIGHTRAG_MODEL, "model": LIGHTRAG_MODEL,
"created_at": LIGHTRAG_CREATED_AT, "created_at": LIGHTRAG_CREATED_AT,
"message": { "message": {
"role": "assistant", "role": "assistant",
"content": str(response_text), # 确保转换为字符串 "content": str(response_text),
"images": None, "images": None,
}, },
"done": True, "done": True,
"total_duration": total_time, # 总时间 "total_duration": total_time,
"load_duration": 0, # 加载时间为0 "load_duration": 0,
"prompt_eval_count": prompt_tokens, # 输入token数 "prompt_eval_count": prompt_tokens,
"prompt_eval_duration": prompt_eval_time, # 首个响应之前的时间 "prompt_eval_duration": prompt_eval_time,
"eval_count": completion_tokens, # 输出token数 "eval_count": completion_tokens,
"eval_duration": eval_time, # 生成响应的时间 "eval_duration": eval_time,
} }
except Exception as e: except Exception as e:
raise HTTPException(status_code=500, detail=str(e)) raise HTTPException(status_code=500, detail=str(e))