Update agent.py

agent.py

@@ -11,8 +11,7 @@ from langchain_core.output_parsers import StrOutputParser # Explicitly imported
 
 from langgraph.graph import StateGraph, END
 
-# --- Revert to Hugging Face LLM imports ---
-from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace # Correct imports for Hugging Face LLMs
+from langchain_huggingface import HuggingFaceEndpoint, HuggingFaceEmbeddings, HuggingFaceTextGenInference
 
 # Import tools_for_llm from your tools.py file
 from tools import tools_for_llm
@@ -24,13 +23,13 @@ load_dotenv()
 # --- Initialize the language model (using Hugging Face Inference Endpoint) ---
 # Ensure that your HF_TOKEN is available as an environment variable
 # If using a specific endpoint, verify it's correct.
-endpoint = HuggingFaceEndpoint(
-   # endpoint_url="https://api-inference.huggingface.co/models/meta-llama/Llama-3-70b-instruct", # Using Llama-3-70b-instruct as per your original code
-   # endpoint_url="https://api-inference.huggingface.co/models/meta-llama/Llama-3-8b-instruct",
+
+llm = HuggingFaceTextGenInference(
     endpoint_url="https://api-inference.huggingface.co/models/Meta-DeepLearning/llama-2-7b-chat-hf",
     temperature=0.01, # Keep a low temperature for consistent tool-use decisions
+    # Si tu HF_TOKEN no se está cargando automáticamente, puedes añadirlo aquí:
+    # huggingfacehub_api_token=os.getenv("HF_TOKEN")
 )
-llm = ChatHuggingFace(llm=endpoint)
 
 # Load the system prompt from file
 with open("system_prompt.txt", "r", encoding="utf-8") as f:
@@ -60,7 +59,7 @@ def get_tool_descriptions(tool_list):
                 for k, v in pydantic_args.items():
                     arg_type = v.get('type', 'any')
                     arg_description = v.get('description', '')
-                    args_str_list.append(f"{k}: {arg_type} ({arg_description})")
+                    args_str_list.append(f"{k}: {arg_type}: {arg_description}") # Typo fixed here: arg_type: arg_description
                 if args_str_list:
                     args_schema_str = f"Arguments: ({', '.join(args_str_list)})"
             except Exception: