Update agent.py

agent.py

@@ -153,10 +153,9 @@ tools = [
 
 # Build graph function
 def build_graph(provider: str = "huggingface", huggingface_model: str = "mistral"):
-    """Build the graph"""
+    """Build the graph with tool binding."""
 
     if provider == "google":
-        # Google Gemini
         llm = ChatGoogleGenerativeAI(
             model="gemini-2.0-flash",
             temperature=0,
@@ -164,11 +163,10 @@ def build_graph(provider: str = "huggingface", huggingface_model: str = "mistral
         )
 
     elif provider == "huggingface":
-        # Choose between supported Hugging Face models
         if huggingface_model == "mistral":
-            model_url = "https://api-inference.huggingface.co/models/mistralai/Mistral-7B-Instruct-v0.1"
+            repo_id = "mistralai/Mistral-7B-Instruct-v0.1"
         elif huggingface_model == "llama":
-            model_url = "https://api-inference.huggingface.co/models/Meta-DeepLearning/llama-2-7b-chat-hf"
+            repo_id = "Meta-DeepLearning/llama-2-7b-chat-hf"
         else:
             raise ValueError("Unsupported Hugging Face model")
 
@@ -177,7 +175,7 @@ def build_graph(provider: str = "huggingface", huggingface_model: str = "mistral
 
         llm = ChatHuggingFace(
             llm=HuggingFaceEndpoint(
-                url=model_url,
+                repo_id=repo_id,
                 temperature=0,
                 headers=headers
             )
@@ -186,10 +184,8 @@ def build_graph(provider: str = "huggingface", huggingface_model: str = "mistral
     else:
         raise ValueError("Invalid provider. Choose 'google' or 'huggingface'.")
 
-    return llm
-        
-    # Bind tools to LLM
-    llm_with_tools = llm.bind_tools(tools)
+    # ✅ Bind tools if defined
+    llm_with_tools = llm.bind_tools(tools)  # Make sure `tools` is defined/imported
     return llm_with_tools
 
     # Node