Spaces:
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fix pdf viewer when asking questions
Browse files- streamlit_app.py +17 -9
streamlit_app.py
CHANGED
@@ -52,6 +52,9 @@ if 'ner_processing' not in st.session_state:
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if 'uploaded' not in st.session_state:
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st.session_state['uploaded'] = False
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st.set_page_config(
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page_title="Scientific Document Insights Q/A",
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page_icon="📝",
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@@ -265,28 +268,33 @@ with st.sidebar:
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@st.cache_resource
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def get_pdf_display(binary):
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base64_pdf = base64.b64encode(binary).decode('utf-8')
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return F'<
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if uploaded_file and not st.session_state.loaded_embeddings:
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if model not in st.session_state['api_keys']:
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st.error("Before uploading a document, you must enter the API key. ")
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st.stop()
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with st.spinner('Reading file, calling Grobid, and creating memory embeddings...'):
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binary = uploaded_file.getvalue()
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tmp_file = NamedTemporaryFile()
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tmp_file.write(bytearray(binary))
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-
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chunk_size=chunk_size,
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perc_overlap=0.1)
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-
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-
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# timestamp = datetime.utcnow()
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with right_column:
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if st.session_state.loaded_embeddings and question and len(question) > 0 and st.session_state.doc_id:
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for message in st.session_state.messages:
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if 'uploaded' not in st.session_state:
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st.session_state['uploaded'] = False
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if 'binary' not in st.session_state:
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st.session_state['binary'] = None
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st.set_page_config(
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page_title="Scientific Document Insights Q/A",
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page_icon="📝",
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@st.cache_resource
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def get_pdf_display(binary):
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base64_pdf = base64.b64encode(binary).decode('utf-8')
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return F'<iframe src="data:application/pdf;base64,{base64_pdf}" width="600" height="800" type="application/pdf"></embed>'
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if uploaded_file and not st.session_state.loaded_embeddings:
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if model not in st.session_state['api_keys']:
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st.error("Before uploading a document, you must enter the API key. ")
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st.stop()
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with right_column:
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with st.spinner('Reading file, calling Grobid, and creating memory embeddings...'):
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binary = uploaded_file.getvalue()
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tmp_file = NamedTemporaryFile()
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tmp_file.write(bytearray(binary))
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st.session_state['binary'] = binary
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st.session_state['doc_id'] = hash = st.session_state['rqa'][model].create_memory_embeddings(tmp_file.name,
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chunk_size=chunk_size,
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perc_overlap=0.1)
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st.session_state['loaded_embeddings'] = True
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st.session_state.messages = []
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# timestamp = datetime.utcnow()
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with left_column:
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if st.session_state['binary']:
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left_column.markdown(get_pdf_display(st.session_state['binary']), unsafe_allow_html=True)
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with right_column:
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if st.session_state.loaded_embeddings and question and len(question) > 0 and st.session_state.doc_id:
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for message in st.session_state.messages:
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