Update app.py

app.py

@@ -1,10 +1,9 @@
+import gradio as gr
+from langchain_core.messages import HumanMessage
 from langgraph.graph import StateGraph, MessagesState, START, END
 from langgraph.checkpoint.memory import MemorySaver
 from langgraph.prebuilt import ToolNode
-from langchain_core.messages import HumanMessage
-from langchain_huggingface import HuggingFaceEndpoint
 from langchain_huggingface import ChatHuggingFace
-from langchain_core.tools import tool
 from typing import Literal
 import os
 
@@ -18,10 +17,7 @@ llm = ChatHuggingFace(
     max_new_tokens=150,
 )
 
-# Bind tools to the chat model
-
 # Define tools for travel planning
-@tool
 def search_destination(query: str):
     """Search for travel destinations based on preferences."""
     if "beach" in query.lower():
@@ -30,12 +26,10 @@ def search_destination(query: str):
         return "Destinations: Patagonia, Kilimanjaro, Swiss Alps"
     return "Popular Destinations: Paris, New York, Tokyo"
 
-@tool
 def fetch_flights(destination: str):
     """Fetch flight options to the destination."""
     return f"Flights available to {destination}: Option 1 - $500, Option 2 - $700."
 
-@tool
 def fetch_hotels(destination: str):
     """Fetch hotel recommendations for the destination."""
     return f"Hotels in {destination}: Hotel A ($200/night), Hotel B ($150/night)."
@@ -77,15 +71,37 @@ checkpointer = MemorySaver()
 # Compile the graph
 app = workflow.compile(checkpointer=checkpointer)
 
-# Use the graph
-initial_state = {"messages": [HumanMessage(content="I want a beach vacation.")]}
+# Function to process user input and generate response
+def chat(user_input, history):
+    # Prepare the initial state with the user's message
+    initial_state = {"messages": [HumanMessage(content=user_input)]}
 
-final_state = app.invoke(initial_state)
-print(final_state["messages"][-1].content)
+    # Invoke the workflow
+    final_state = app.invoke(initial_state)
 
-# Continue the conversation
-next_state = app.invoke(
-    {"messages": [HumanMessage(content="Tell me about flights to Bali.")]},
-    config={"configurable": {"thread_id": 123}}  # Reuse thread_id to maintain context
-)
-print(next_state["messages"][-1].content)
+    # Extract the response content
+    response = final_state["messages"][-1].content
+
+    # Append the user input and response to history
+    history.append((user_input, response))
+
+    return history, history
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    with gr.Row():
+        with gr.Column():
+            user_input = gr.Textbox(
+                show_label=False,
+                placeholder="Enter your message...",
+            ).style(container=False)
+        with gr.Column():
+            submit_btn = gr.Button("Send")
+
+    # Set up the event handler for the submit button
+    submit_btn.click(chat, [user_input, chatbot], [chatbot, chatbot])
+    user_input.submit(chat, [user_input, chatbot], [chatbot, chatbot])
+
+# Launch the Gradio app
+demo.launch()