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fix: replace print() with structured logging in HTTPS server #191

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fix: replace print() with structured logging in HTTPS server #191

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43 changes: 24 additions & 19 deletions server-https/app.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,11 @@
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import uvicorn
import logging

# Configure logging
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(message)s')
from typing import Dict, Any, List, Optional, AsyncGenerator
from sentence_transformers import SentenceTransformer
from pymilvus import connections, Collection
Expand Down Expand Up @@ -148,7 +153,7 @@ def milvus_search(query: str, top_k: int = 5) -> Dict[str, Any]:
})
return {"results": hits}
except Exception as e:
print(f"[ERROR] Milvus search failed: {e}")
logger.error("Milvus search failed: %s", e)
return {"results": []}
finally:
try:
Expand All @@ -166,7 +171,7 @@ async def execute_tool(tool_call: Dict[str, Any]) -> tuple[str, List[str]]:
query = arguments.get("query", "")
top_k = arguments.get("top_k", 5)

print(f"[TOOL] Executing Milvus search for: '{query}' (top_k={top_k})")
logger.info("Executing Milvus search for: '%s' (top_k=%d)", query, top_k)
result = milvus_search(query, top_k)

# Collect citations
Expand All @@ -191,7 +196,7 @@ async def execute_tool(tool_call: Dict[str, Any]) -> tuple[str, List[str]]:
return f"Unknown tool: {function_name}", []

except Exception as e:
print(f"[ERROR] Tool execution failed: {e}")
logger.error("Tool execution failed: %s", e)
return f"Tool execution failed: {e}", []

async def stream_llm_response(payload: Dict[str, Any]) -> AsyncGenerator[str, None]:
Expand All @@ -203,7 +208,7 @@ async def stream_llm_response(payload: Dict[str, Any]) -> AsyncGenerator[str, No
async with client.stream("POST", KSERVE_URL, json=payload) as response:
if response.status_code != 200:
error_msg = f"LLM service error: HTTP {response.status_code}"
print(f"[ERROR] {error_msg}")
logger.error(error_msg)
yield f"data: {json.dumps({'type': 'error', 'content': error_msg})}\n\n"
return

Expand Down Expand Up @@ -262,14 +267,14 @@ async def stream_llm_response(payload: Dict[str, Any]) -> AsyncGenerator[str, No

# Handle finish reason - execute tools if needed
if finish_reason == "tool_calls":
print(f"[TOOL] Finish reason: tool_calls, executing {len(tool_calls_buffer)} tools")
logger.info("Finish reason: tool_calls, executing %d tools", len(tool_calls_buffer))

# Execute all accumulated tool calls
for tool_call in tool_calls_buffer.values():
if tool_call["function"]["name"] and tool_call["function"]["arguments"]:
try:
print(f"[TOOL] Executing: {tool_call['function']['name']}")
print(f"[TOOL] Arguments: {tool_call['function']['arguments']}")
logger.info("Executing tool: %s", tool_call["function"]["name"])
logger.info("Tool arguments: %s", tool_call["function"]["arguments"])

result, tool_citations = await execute_tool(tool_call)

Expand All @@ -284,14 +289,14 @@ async def stream_llm_response(payload: Dict[str, Any]) -> AsyncGenerator[str, No
yield follow_up_chunk

except Exception as e:
print(f"[ERROR] Tool execution error: {e}")
logger.error("Tool execution error: %s", e)
yield f"data: {json.dumps({'type': 'error', 'content': f'Tool execution failed: {e}'})}\n\n"

tool_calls_buffer.clear()
break # Tool execution complete, exit streaming loop

except json.JSONDecodeError as e:
print(f"[ERROR] JSON decode error: {e}, line: {line}")
logger.error("JSON decode error: %s, line: %s", e, line)
continue

# Send citations if any were collected
Expand All @@ -308,13 +313,13 @@ async def stream_llm_response(payload: Dict[str, Any]) -> AsyncGenerator[str, No
yield f"data: {json.dumps({'type': 'done'})}\n\n"

except Exception as e:
print(f"[ERROR] Streaming failed: {e}")
logger.error("Streaming failed: %s", e)
yield f"data: {json.dumps({'type': 'error', 'content': f'Streaming failed: {e}'})}\n\n"

async def handle_tool_follow_up(original_payload: Dict[str, Any], tool_call: Dict[str, Any], tool_result: str, citations_collector: List[str]) -> AsyncGenerator[str, None]:
"""Handle follow-up request after tool execution"""
try:
print("[TOOL] Handling follow-up request with tool results")
logger.info("Handling follow-up request with tool results")

# Create messages with tool call and result
messages = original_payload["messages"].copy()
Expand Down Expand Up @@ -345,7 +350,7 @@ async def handle_tool_follow_up(original_payload: Dict[str, Any], tool_call: Dic
yield chunk

except Exception as e:
print(f"[ERROR] Tool follow-up failed: {e}")
logger.error("Tool follow-up failed: %s", e)
yield f"data: {json.dumps({'type': 'error', 'content': f'Tool follow-up failed: {e}'})}\n\n"

async def get_non_streaming_response(payload: Dict[str, Any]) -> tuple[str, List[str]]:
Expand Down Expand Up @@ -397,7 +402,7 @@ async def options_health():
async def chat(request: ChatRequest):
"""Chat endpoint with RAG capabilities - supports both streaming and non-streaming"""
try:
print(f"[CHAT] Processing message: {request.message[:100]}...")
logger.info("Processing message: %s...", request.message[:100])

# Create initial payload
payload = {
Expand Down Expand Up @@ -440,15 +445,15 @@ async def chat(request: ChatRequest):
}

except Exception as e:
print(f"[ERROR] Chat handling failed: {e}")
logger.error("Chat handling failed: %s", e)
raise HTTPException(status_code=500, detail=f"Request failed: {e}")

if __name__ == "__main__":
print("🚀 Starting Kubeflow Docs HTTP API Server")
print(f" Port: {PORT}")
print(f" LLM Service: {KSERVE_URL}")
print(f" Milvus: {MILVUS_HOST}:{MILVUS_PORT}")
print(f" Collection: {MILVUS_COLLECTION}")
logger.info("Starting Kubeflow Docs HTTP API Server")
logger.info("Port: %s", PORT)
logger.info("LLM Service: %s", KSERVE_URL)
logger.info("Milvus: %s:%s", MILVUS_HOST, MILVUS_PORT)
logger.info("Collection: %s", MILVUS_COLLECTION)

uvicorn.run(
app,
Expand Down