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Update app.py
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app.py
CHANGED
@@ -10,7 +10,7 @@ import base64
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# Load environment variables
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load_dotenv()
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icons = {"assistant": "
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# Configure the Llama index settings
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Settings.llm = HuggingFaceInferenceAPI(
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@@ -105,12 +105,12 @@ with st.sidebar:
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user_prompt = st.chat_input("Ask me anything about the content of the PDF:")
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if user_prompt and uploaded_file:
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st.session_state.messages.append({'role': 'user', "content": user_prompt})
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with st.chat_message("user", avatar="human-
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st.write(user_prompt)
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# Generate a new response if last message is not from assistant
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if st.session_state.messages[-1]["role"] != "assistant":
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with st.chat_message("assistant",avatar="
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response = handle_query(user_prompt)
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full_response = st.write_stream(response)
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message = {"role": "assistant", "content": full_response}
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# Load environment variables
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load_dotenv()
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icons = {"assistant": "robot.png", "user": "human-kddi.png"}
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# Configure the Llama index settings
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Settings.llm = HuggingFaceInferenceAPI(
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user_prompt = st.chat_input("Ask me anything about the content of the PDF:")
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if user_prompt and uploaded_file:
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st.session_state.messages.append({'role': 'user', "content": user_prompt})
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with st.chat_message("user", avatar="human-kddi.png"):
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st.write(user_prompt)
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# Generate a new response if last message is not from assistant
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if st.session_state.messages[-1]["role"] != "assistant":
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with st.chat_message("assistant",avatar="robot.png"):
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response = handle_query(user_prompt)
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full_response = st.write_stream(response)
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message = {"role": "assistant", "content": full_response}
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