DereAbdulhameed commited on
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1 Parent(s): d65a497

Delete app.py

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  1. app.py +0 -71
app.py DELETED
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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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-
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- # Set the title for the Streamlit app
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- st.title("Simple Chatbot")
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-
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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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-
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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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-
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- # Set the API key for OpenAI
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- openai.api_key = openai_api_key
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-
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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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-
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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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-
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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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-
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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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-
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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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-
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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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-
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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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-
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- # Call the chat_gpt function
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- result = chat_gpt(prompt)
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-
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- # Display the assistant's response
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- botmsg.write(result)
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-
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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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-
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- # Store the updated prompt in the session state
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- st.session_state["prompt"] = prompt