Update app.py

app.py

@@ -11,11 +11,6 @@ import shutil
 import re
 import psutil
 import subprocess
-import logging
-
-# Configure logging
-logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
 
 # Persistent directory
 persistent_dir = "/data/hf_cache"
@@ -65,16 +60,13 @@ def extract_priority_pages(file_path: str, max_pages: int = 20) -> str:
                     text_chunks.append(f"=== Page {i} ===\n{page_text.strip()}")
         return "\n\n".join(text_chunks)
     except Exception as e:
-        logger.error(f"PDF processing error for {file_path}: {e}")
         return f"PDF processing error: {str(e)}"
 
 def convert_file_to_json(file_path: str, file_type: str) -> str:
-    logger.debug(f"Converting file {file_path} (type: {file_type})")
     try:
         h = file_hash(file_path)
         cache_path = os.path.join(file_cache_dir, f"{h}.json")
         if os.path.exists(cache_path):
-            logger.debug(f"Using cached JSON for {file_path}")
             with open(cache_path, "r", encoding="utf-8") as f:
                 return f.read()
 
@@ -97,54 +89,47 @@ def convert_file_to_json(file_path: str, file_type: str) -> str:
             result = json.dumps({"error": f"Unsupported file type: {file_type}"})
         with open(cache_path, "w", encoding="utf-8") as f:
             f.write(result)
-        logger.debug(f"Cached JSON for {file_path}")
         return result
     except Exception as e:
-        logger.error(f"Error processing {file_path}: {e}")
         return json.dumps({"error": f"Error processing {os.path.basename(file_path)}: {str(e)}"})
 
 def log_system_usage(tag=""):
     try:
         cpu = psutil.cpu_percent(interval=1)
         mem = psutil.virtual_memory()
-        logger.info(f"[{tag}] CPU: {cpu}% | RAM: {mem.used // (1024**2)}MB / {mem.total // (1024**2)}MB")
+        print(f"[{tag}] CPU: {cpu}% | RAM: {mem.used // (1024**2)}MB / {mem.total // (1024**2)}MB")
         result = subprocess.run(
             ["nvidia-smi", "--query-gpu=memory.used,memory.total,utilization.gpu", "--format=csv,nounits,noheader"],
             capture_output=True, text=True
         )
         if result.returncode == 0:
             used, total, util = result.stdout.strip().split(", ")
-            logger.info(f"[{tag}] GPU: {used}MB / {total}MB | Utilization: {util}%")
+            print(f"[{tag}] GPU: {used}MB / {total}MB | Utilization: {util}%")
     except Exception as e:
-        logger.warning(f"[{tag}] GPU/CPU monitor failed: {e}")
+        print(f"[{tag}] GPU/CPU monitor failed: {e}")
 
 def init_agent():
-    logger.info("🔁 Initializing model...")
+    print("🔁 Initializing model...")
     log_system_usage("Before Load")
     default_tool_path = os.path.abspath("data/new_tool.json")
     target_tool_path = os.path.join(tool_cache_dir, "new_tool.json")
     if not os.path.exists(target_tool_path):
-        logger.debug(f"Copying tool file from {default_tool_path} to {target_tool_path}")
         shutil.copy(default_tool_path, target_tool_path)
 
-    try:
-        agent = TxAgent(
-            model_name="mims-harvard/TxAgent-T1-Llama-3.1-8B",
-            rag_model_name="mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B",
-            tool_files_dict={"new_tool": target_tool_path},
-            force_finish=True,
-            enable_checker=True,
-            step_rag_num=8,
-            seed=100,
-            additional_default_tools=[],
-        )
-        agent.init_model()
-        log_system_usage("After Load")
-        logger.info("✅ Agent Ready")
-        return agent
-    except Exception as e:
-        logger.error(f"Failed to initialize agent: {e}", exc_info=True)
-        raise
+    agent = TxAgent(
+        model_name="mims-harvard/TxAgent-T1-Llama-3.1-8B",
+        rag_model_name="mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B",
+        tool_files_dict={"new_tool": target_tool_path},
+        force_finish=True,
+        enable_checker=True,
+        step_rag_num=8,
+        seed=100,
+        additional_default_tools=[],
+    )
+    agent.init_model()
+    log_system_usage("After Load")
+    print("✅ Agent Ready")
+    return agent
 
 def create_ui(agent):
     with gr.Blocks(theme=gr.themes.Soft()) as demo:
@@ -156,34 +141,19 @@ def create_ui(agent):
         download_output = gr.File(label="Download Full Report")
 
         def analyze(message: str, history: List[dict], files: List):
-            logger.debug(f"Analyze called with message: {message[:100]}, history length: {len(history)}, files: {len(files)}")
-            
-            # Initialize history if empty
-            if not history:
-                history = []
-            
             # Append user message
             history.append({"role": "user", "content": message})
             history.append({"role": "assistant", "content": "⏳ Analyzing records for potential oversights..."})
             yield history, None
-            logger.debug("Yielded initial history with analyzing message")
 
             extracted = ""
             file_hash_value = ""
             if files:
-                logger.debug(f"Processing {len(files)} files")
-                try:
-                    with ThreadPoolExecutor(max_workers=4) as executor:
-                        futures = [executor.submit(convert_file_to_json, f.name, f.name.split(".")[-1].lower()) for f in files]
-                        results = [sanitize_utf8(f.result()) for f in as_completed(futures)]
-                        extracted = "\n".join(results)
-                        file_hash_value = file_hash(files[0].name) if files else ""
-                    logger.debug(f"Extracted file content: {extracted[:100]}")
-                except Exception as e:
-                    logger.error(f"File processing failed: {e}")
-                    history.append({"role": "assistant", "content": f"❌ File processing error: {str(e)}"})
-                    yield history, None
-                    return
+                with ThreadPoolExecutor(max_workers=4) as executor:
+                    futures = [executor.submit(convert_file_to_json, f.name, f.name.split(".")[-1].lower()) for f in files]
+                    results = [sanitize_utf8(f.result()) for f in as_completed(futures)]
+                    extracted = "\n".join(results)
+                    file_hash_value = file_hash(files[0].name) if files else ""
 
             prompt = f"""Review these medical records and identify EXACTLY what might have been missed:
 1. List potential missed diagnoses
@@ -194,54 +164,44 @@ Medical Records:
 {extracted[:12000]}
 ### Potential Oversights:
 """
-            logger.debug(f"Constructed prompt: {prompt[:100]}")
 
             try:
                 # Remove the temporary "Analyzing..." message
                 if history and history[-1]["content"].startswith("⏳"):
                     history.pop()
-                    logger.debug("Removed analyzing message")
 
                 # Process agent response
                 for chunk in agent.run_gradio_chat(
                     message=prompt,
-                    history=history,
+                    history=[],
                     temperature=0.2,
                     max_new_tokens=2048,
                     max_token=4096,
                     call_agent=False,
                     conversation=[],
                 ):
-                    logger.debug(f"Received chunk: {chunk}")
                     if chunk is None:
-                        logger.warning("Chunk is None, skipping")
                         continue
 
-                    # Handle chunk as a list of ChatMessage objects
                     if isinstance(chunk, list):
                         for m in chunk:
                             if hasattr(m, 'content') and m.content:
                                 history.append({"role": m.role, "content": sanitize_utf8(m.content)})
-                                logger.debug(f"Appended message: {m.content[:50]}")
                                 yield history, None
-                    # Handle chunk as a string
                     elif isinstance(chunk, str) and chunk.strip():
+                        # Append new assistant message or update the last one
                         if history and history[-1]["role"] == "assistant":
-                            history[-1]["content"] += "\n" + sanitize_utf8(chunk)
+                            history[-1]["content"] += sanitize_utf8(chunk)
                         else:
                             history.append({"role": "assistant", "content": sanitize_utf8(chunk)})
-                        logger.debug(f"Updated history with string chunk: {chunk[:50]}")
                         yield history, None
-                    else:
-                        logger.warning(f"Unexpected chunk type: {type(chunk)}")
 
                 # Provide report path if available
                 report_path = os.path.join(report_dir, f"{file_hash_value}_report.txt") if file_hash_value else None
-                logger.debug(f"Report path: {report_path}")
                 yield history, report_path if report_path and os.path.exists(report_path) else None
 
             except Exception as e:
-                logger.error(f"Error in analyze: {e}", exc_info=True)
+                print("🚨 ERROR:", e)
                 history.append({"role": "assistant", "content": f"❌ Error occurred: {str(e)}"})
                 yield history, None
 
@@ -250,18 +210,13 @@ Medical Records:
     return demo
 
 if __name__ == "__main__":
-    logger.info("🚀 Launching app...")
-    try:
-        agent = init_agent()
-        demo = create_ui(agent)
-        demo.queue(api_open=False).launch(
-            server_name="0.0.0.0",
-            server_port=7860,
-            show_error=True,
-            allowed_paths=[report_dir],
-            share=False,
-            debug=True  # Enable debug mode for better error reporting
-        )
-    except Exception as e:
-        logger.error(f"Failed to launch app: {e}", exc_info=True)
-        raise
+    print("🚀 Launching app...")
+    agent = init_agent()
+    demo = create_ui(agent)
+    demo.queue(api_open=False).launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True,
+        allowed_paths=[report_dir],
+        share=False
+    )