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Delete app.py
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app.py
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# Import necessary libraries
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import streamlit as st
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import openai
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import os
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# Set the title for the Streamlit app
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st.title("Simple Chatbot")
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# Load the OpenAI API key from Hugging Face's environment variables
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openai_api_key = os.getenv("OPENAI_API_KEY")
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# Check if the API key is loaded
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if openai_api_key is None:
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st.error("API key not found. Please set the OpenAI API key in the environment.")
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st.stop()
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# Set the API key for OpenAI
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openai.api_key = openai_api_key
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# Define the template for the chatbot prompt
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prompt_template = """
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You are a helpful Assistant who answers users' questions
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based on your general knowledge. Keep your answers short
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and to the point.
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"""
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# Get the current prompt from the session state or set default
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if "prompt" not in st.session_state:
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st.session_state["prompt"] = [{"role": "system",
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"content": prompt_template}]
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prompt = st.session_state["prompt"]
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# Display previous chat messages
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for message in prompt:
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if message["role"] != "system":
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with st.chat_message(message["role"]):
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st.write(message["content"])
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# Get the user's question using Streamlit's chat input
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question = st.chat_input("Ask anything")
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# Handle the user's question
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if question:
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# Add the user's question to the prompt and display it
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prompt.append({"role": "user", "content": question})
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with st.chat_message("user"):
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st.write(question)
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# Display an empty assistant message while waiting for response
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with st.chat_message("assistant"):
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botmsg = st.empty()
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# Define a function to interact with OpenAI API
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def chat_gpt(messages):
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response = openai.ChatCompletion.create(
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model="gpt-3.5-turbo",
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messages=messages
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)
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return response.choices[0].message['content'].strip()
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# Call the chat_gpt function
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result = chat_gpt(prompt)
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# Display the assistant's response
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botmsg.write(result)
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# Add the assistant's response to the prompt
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prompt.append({"role": "assistant", "content": result})
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# Store the updated prompt in the session state
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st.session_state["prompt"] = prompt
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