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app.py

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+import gradio as gr
+from langchain.llms.openai import OpenAI
+import os 
+from langchain.agents import initialize_agent
+from langchain.agents import load_tools
+
+os.environ["OPENAI_API_KEY"] = "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"
+os.environ["SERPAPI_API_KEY"] = "e109a79c9b6a844c889c8b3f65430f3ea17c4362de514eafeb6030414ec6f808"
+
+llm = OpenAI(temperature=0, max_tokens=1000, model_name='text-davinci-003')
+
+def answer_question(question):
+    agent_exe = initialize_agent(
+        llm=OpenAI(temperature=0),
+        tools=load_tools(["python_repl", "serpapi", "llm-math"], llm=llm),
+        return_intermediate_steps=True,
+        verbose=True,
+    )
+    response = agent_exe({"input": question})
+    answer = response["output"]
+    steps = response["intermediate_steps"]
+    return answer, steps
+
+ifaces = gr.Interface(
+    fn=answer_question,
+    inputs=gr.Textbox(label="Question", 
+    placeholder="What's the square root, of the age, of Leonardo DiCaprio's latest girlfriend"),
+    outputs=[gr.Textbox(label="Answer"), gr.JSON(label="Steps", show_label=False)],
+    title="Helpful Agent",
+    description="This is an Agent, which uses OpenAI's text-davinci-003 model, and the tools: SerpAPI, Python REPL, and Language Learning Machine Math, depending on your request"
+)
+ifaces.launch()
+