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DrishtiSharma
commited on
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•
ccb4e8f
1
Parent(s):
fc4cfde
Update app.py
Browse files
app.py
CHANGED
@@ -19,6 +19,12 @@ model_name = "model-q4_K.gguf"
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#snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_name)
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def get_pdf_text(pdf_docs):
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text = ""
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@@ -50,6 +56,7 @@ def get_text_chunks(text):
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#return vectorstore
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def get_vectorstore(text_chunks, embedding_model_name="intfloat/multilingual-e5-large"):
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embeddings = HuggingFaceEmbeddings(model_name=embedding_model_name)
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vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
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@@ -78,24 +85,28 @@ def get_conversation_chain(vectorstore, model_name):
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return conversation_chain
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def handle_userinput(user_question):
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response = st.session_state.conversation({'question': user_question})
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st.session_state.chat_history = response['chat_history']
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st.session_state.retrieved_text = response['source_documents']
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for i, (message, text) in enumerate(zip(st.session_state.chat_history, st.session_state.retrieved_text)):
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if i %
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st.write(user_template.replace(
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"{{MSG}}",
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st.set_page_config(page_title="Chat with multiple PDFs",
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@@ -116,6 +127,7 @@ if user_question:
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with st.sidebar:
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st.subheader("Your documents")
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embedding_model_name = st.selectbox("Select embedding model", ["intfloat/multilingual-e5-large", "sentence-transformers/paraphrase-multilingual-mpnet-base-v2"])
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pdf_docs = st.file_uploader(
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"Upload your PDFs here and click on 'Process'", accept_multiple_files=True)
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if st.button("Process"):
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#snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_name)
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from transformers import pipeline
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# Initialize the summarization pipeline
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summarizer = pipeline("summarization")
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def get_pdf_text(pdf_docs):
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text = ""
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#return vectorstore
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def get_vectorstore(text_chunks, embedding_model_name="intfloat/multilingual-e5-large"):
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embeddings = HuggingFaceEmbeddings(model_name=embedding_model_name)
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vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings)
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return conversation_chain
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def summarize_text(text):
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summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
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return summary[0]['summary_text']
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def handle_userinput(user_question):
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response = st.session_state.conversation({'question': user_question})
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st.session_state.chat_history = response['chat_history']
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st.session_state.retrieved_text = response['source_documents']
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for i, (message, text) in enumerate(zip(st.session_state.chat_history, st.session_state.retrieved_text)):
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if i % 2 == 0: # User messages
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st.write(user_template.replace("{{MSG}}", message.content), unsafe_allow_html=True)
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else: # Bot messages
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st.write(bot_template.replace("{{MSG}}", message.content), unsafe_allow_html=True)
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if summarize_option and text.page_content: # Check if summarization is enabled
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summarized_text = summarize_text(text.page_content)
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st.write(bot_template.replace("{{MSG}}", summarized_text), unsafe_allow_html=True)
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else:
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st.write(bot_template.replace("{{MSG}}", text.page_content), unsafe_allow_html=True)
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st.set_page_config(page_title="Chat with multiple PDFs",
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with st.sidebar:
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st.subheader("Your documents")
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embedding_model_name = st.selectbox("Select embedding model", ["intfloat/multilingual-e5-large", "sentence-transformers/paraphrase-multilingual-mpnet-base-v2"])
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summarize_option = st.sidebar.checkbox("Enable Summarization", value=False)
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pdf_docs = st.file_uploader(
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"Upload your PDFs here and click on 'Process'", accept_multiple_files=True)
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if st.button("Process"):
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