Update app.py

app.py

@@ -11,73 +11,60 @@ from tooluniverse import ToolUniverse
 CONFIG = {
     "model_name": "mims-harvard/TxAgent-T1-Llama-3.1-8B",
     "rag_model_name": "mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B",
-    "embedding_filename": "ToolRAG-T1-GTE-Qwen2-1.5Btool_embedding.pt",
+    "embedding_filename": "ToolRAG-T1-GTE-Qwen2-1.5Btool_embedding_e27fb393f3144ec28f620f33d4d79911.pt",
     "local_dir": "./models",
     "tool_files": {
         "new_tool": "./data/new_tool.json"
     }
 }
 
-# Logging setup
+# Logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
 def prepare_tool_files():
     os.makedirs("./data", exist_ok=True)
     if not os.path.exists(CONFIG["tool_files"]["new_tool"]):
-        logger.info("Generating tool list using ToolUniverse...")
         tu = ToolUniverse()
         tools = tu.get_all_tools()
         with open(CONFIG["tool_files"]["new_tool"], "w") as f:
             json.dump(tools, f, indent=2)
         logger.info(f"Saved {len(tools)} tools to {CONFIG['tool_files']['new_tool']}")
 
-
 def download_model_files():
     os.makedirs(CONFIG["local_dir"], exist_ok=True)
-    print("Downloading model files...")
+    logger.info("Downloading model files...")
 
     snapshot_download(
         repo_id=CONFIG["model_name"],
         local_dir=os.path.join(CONFIG["local_dir"], CONFIG["model_name"]),
         resume_download=True
     )
-
     snapshot_download(
         repo_id=CONFIG["rag_model_name"],
         local_dir=os.path.join(CONFIG["local_dir"], CONFIG["rag_model_name"]),
         resume_download=True
     )
 
-    try:
-        hf_hub_download(
-            repo_id=CONFIG["rag_model_name"],
-            filename=CONFIG["embedding_filename"],
-            local_dir=CONFIG["local_dir"],
-            resume_download=True
-        )
-        print("Embeddings file downloaded successfully")
-    except Exception as e:
-        print(f"Could not download embeddings file: {e}")
-        print("Will attempt to generate it instead")
-
 def generate_embeddings(agent):
-    embedding_path = os.path.join(CONFIG["local_dir"], CONFIG["embedding_filename"])
-
-    if os.path.exists(embedding_path):
-        print("Embeddings file already exists")
-        return
-
-    print("Generating missing tool embeddings...")
+    """Generates and assigns embeddings manually"""
+    path = os.path.join(CONFIG["local_dir"], CONFIG["embedding_filename"])
     try:
+        if os.path.exists(path):
+            logger.info("Embedding file already exists, loading...")
+            agent.rag_model.tool_desc_embedding = torch.load(path)
+            return
+
+        logger.info("Generating embeddings and saving...")
         tools = agent.tooluniverse.get_all_tools()
-        descriptions = [tool["description"] for tool in tools]
-        embeddings = agent.rag_model.generate_embeddings(descriptions)
-        torch.save(embeddings, embedding_path)
+        descs = [t["description"] for t in tools]
+        embeddings = agent.rag_model.generate_embeddings(descs)
+        torch.save(embeddings, path)
         agent.rag_model.tool_desc_embedding = embeddings
-        print(f"Embeddings saved to {embedding_path}")
+        logger.info("✅ Embeddings generated and saved")
+
     except Exception as e:
-        print(f"Failed to generate embeddings: {e}")
+        logger.error(f"Failed to generate embeddings: {e}")
         raise
 
 class TxAgentApp:
@@ -124,7 +111,6 @@ class TxAgentApp:
                 max_round=30
             ):
                 response += chunk
-
             return history + [(message, response)]
         except Exception as e:
             return history + [(message, f"Error: {str(e)}")]