Update agents/agents_nodes.py

agents/agents_nodes.py

@@ -38,21 +38,42 @@ llm = HuggingFacePipeline(pipeline=text_generator)
 #     )
 # )
 
-llm_instantiated = llm | RunnableLambda(
-    lambda x: x.bind(
-        [time_value_tool],
-        tool_choice={"type": "function", "function": {"name": "time_value_tool"}}
-    )
+# llm_instantiated = llm | RunnableLambda(
+#     lambda x: x.bind(
+#         [time_value_tool],
+#         tool_choice={"type": "function", "function": {"name": "time_value_tool"}}
+#     )
+# )
+
+# Replace this
+
+
+# With this
+llm_instantiated = llm.bind(
+    tools=[time_value_tool],
+    tool_choice="time_value_tool"
 )
 
 
+
+# def agent_node(state: AgentState):
+#     response = llm_instantiated.invoke(state["messages"])
+#     if not (hasattr(response, 'tool_calls') and response.tool_calls):
+#         error_message = AIMessage(content="Error: Model failed to generate tool call.")
+#         return {"messages": [error_message]}
+#     return {"messages": [response]}
+
+
+# Update tool invocation in agent_node
 def agent_node(state: AgentState):
     response = llm_instantiated.invoke(state["messages"])
-    if not (hasattr(response, 'tool_calls') and response.tool_calls):
-        error_message = AIMessage(content="Error: Model failed to generate tool call.")
-        return {"messages": [error_message]}
+    if not hasattr(response, 'tool_calls') or not response.tool_calls:
+        return {"messages": [AIMessage(content="Error: No tool call generated")]}
+    tool_call = response.tool_calls
     return {"messages": [response]}
 
+
+
 # Tool node executes the tool
 tool_node = ToolNode([time_value_tool])