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Create app.py

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  1. app.py +59 -0
app.py ADDED
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+ import gradio as gr
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+ from langchain.agents import load_tools, initialize_agent
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+ from langchain.agents import AgentType
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+ from langchain.chat_models import ChatOpenAI
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+ import os
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+
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+ # Set your OpenAI API key (ensure to store it securely in Hugging Face Spaces environment variables)
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+ #os.environ["OPENAI_API_KEY"] = "your_openai_api_key"
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+ import warnings
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+ warnings.filterwarnings("ignore", message=".*TqdmWarning.*")
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+ from dotenv import load_dotenv
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+
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+ _ = load_dotenv()
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+
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+ # Define the LLM model
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+ llm_model = "gpt-3.5-turbo"
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+ llm = ChatOpenAI(temperature=0, model=llm_model)
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+
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+ # Load tools
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+ tools = load_tools(["llm-math", "wikipedia"], llm=llm)
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+
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+ # Initialize agent
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+ agent = initialize_agent(
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+ tools,
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+ llm,
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+ agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
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+ handle_parsing_errors=True,
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+ verbose=True
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+ )
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+
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+ def chatbot(query):
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+ """Handles user query and returns agent response."""
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+ try:
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+ response = agent.run(query)
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+ return response
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+ except Exception as e:
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+ return str(e)
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+
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+ # Create Gradio interface
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+ #demo = gr.Interface(
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+ #fn=chatbot,
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+ #inputs=gr.Textbox(placeholder="Ask me anything..."),
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+ #outputs="text",
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+ #title="LangChain Agent Chatbot",
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+ #description="An interactive chatbot powered by LangChain, OpenAI, and external tools."
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+ #)
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+
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+ demo = gr.Interface(
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+ fn=chatbot,
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+ inputs=gr.Textbox(label="Your Question", placeholder="Ask me anything..."),
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+ outputs=gr.Textbox(label="Response"),
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+ title="LangChain AI Chatbot",
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+ description="A smart AI chatbot powered by OpenAI and LangChain.",
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+ theme="compact"
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+ )
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+
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+
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+ # Launch the app
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+ demo.launch()