Update app.py

app.py

@@ -302,115 +302,6 @@ def bot(history, choice, tts_choice, retrieval_mode):
 
     history.append([response, None])  # Ensure the response is added in the correct format
 
-# Langchain imports
-from langchain_openai import ChatOpenAI
-from langchain.agents import tool
-from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
-from langchain_core.messages import AIMessage, HumanMessage
-from langchain.agents.format_scratchpad.openai_tools import (
-    format_to_openai_tool_messages,)
-from langchain.agents.output_parsers.openai_tools import OpenAIToolsAgentOutputParser
-from langchain.agents import AgentExecutor
-from langchain import OpenAI
-
-
-
-# Step 1: Define the restaurant tool
-@tool
-def fetch_restaurant_info(query: str) -> str:
-    """
-    Fetches restaurant-related information from SERP API based on the given query.
-    """
-    from serpapi.google_search import GoogleSearch
-
-    # Define parameters for SERP API
-    params = {
-        "engine": "yelp",
-        "find_desc": query,
-        "find_loc": "Birmingham, AL, USA",
-        "api_key": os.getenv("SERP_API")
-    }
-
-    # Fetch data from SERP API
-    search = GoogleSearch(params)
-    results = search.get_dict()
-    organic_results = results.get("organic_results", [])
-
-    # Prepare the output in plain text
-    if organic_results:
-        response = ""
-        for result in organic_results:
-            name = result.get("title", "No name")
-            rating = result.get("rating", "No rating")
-            reviews = result.get("reviews", "No reviews")
-            phone = result.get("phone", "Not Available")
-            snippet = result.get("snippet", "Not Available")
-            services = result.get("service_options", "Not Known")
-
-            if isinstance(services, list):
-                services = ", ".join(services)
-            elif isinstance(services, dict):
-                services = ", ".join([f"{key}: {value}" for key, value in services.items()])
-
-            link = result.get("link", "#")
-            response += f"Name: {name}\nRating: {rating}\nReviews: {reviews}\nPhone: {phone}\nSnippet: {snippet}\nServices: {services}\nLink: {link}\n\n"
-        
-        return response
-    else:
-        return "No restaurant information found."
-
-# Step 2: Integrate the tool with the agent
-tools = [fetch_restaurant_info]
-
-# Define the prompt template
-MEMORY_KEY = "chat_history"
-prompt = ChatPromptTemplate.from_messages(
-    [
-        (
-            "system",
-            "You are a very powerful assistant, but you only respond with restaurant information when asked about restaurants.",
-        ),
-        MessagesPlaceholder(variable_name=MEMORY_KEY),
-        ("user", "{input}"),
-        MessagesPlaceholder(variable_name="agent_scratchpad"),
-    ]
-)
-
-# Define the chat history
-chat_history = []
-
-# Create the agent with the tool
-llm = OpenAI(api_key=os.getenv("OPENAI_API_KEY"), temperature=0, model="gpt-4o")
-agent = (
-    {
-        "input": lambda x: x["input"],
-        "agent_scratchpad": lambda x: format_to_openai_tool_messages(x["intermediate_steps"]),
-        "chat_history": lambda x: x["chat_history"],
-    }
-    | prompt
-    | llm
-    | OpenAIToolsAgentOutputParser(tools=tools)
-)
-
-agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
-
-# Step 3: Update the chatbot function
-def chatbot_response(user_input, history, choice, tts_choice, retrieval_mode):
-    # Check if the user input is related to restaurants
-    if "restaurant" in user_input.lower():
-        result = agent_executor.invoke({"input": user_input, "chat_history": history})
-        history.append([user_input, result["output"]])
-        return history, None
-    else:
-        # Use the existing logic for non-restaurant-related queries
-        response, addresses = generate_answer(user_input, choice, retrieval_mode)
-        history.append([user_input, response])
-        return history, None
-
-
-
-
-
 def add_message(history, message):
     history.append((message, None))
     return history, gr.Textbox(value="", interactive=True, placeholder="Enter message or upload file...", show_label=False)