Update app.py
Browse files
app.py
CHANGED
@@ -98,17 +98,13 @@ def summarize_pdf_with_tooltips(_pdf_file_path, num_clusters=10):
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2. Main methodologies used
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3. Important data points
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4. Limitations mentioned
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-
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For any information directly derived from the context excerpts provided below, insert an in-text citation as an HTML tooltip.
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For each citation, use the following HTML format:
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<span class="tooltip" data-tooltip="{full_text}">[{n}]</span>
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-
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Where:
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- {n} is the citation number.
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- {full_text} is the complete excerpt text for that citation.
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-
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Do not provide a separate reference list. Instead, embed the full citation text directly in the tooltip.
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-
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Context Excerpts:
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{contexts}"""
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)
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@@ -150,7 +146,7 @@ Context Excerpts:
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@handle_errors
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def qa_pdf(_pdf_file_path, query, num_clusters=5):
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embeddings_model = OpenAIEmbeddings(model="text-embedding-3-small", api_key=openai_api_key)
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llm = ChatOpenAI(model="gpt-
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prompt = ChatPromptTemplate.from_template(
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"""Answer this question: {question}
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@@ -190,7 +186,7 @@ def process_pdf(_pdf_file_path):
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scale_factor = 300 / 50 # High-res to low-res ratio
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for page in doc:
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low_res = page.get_pixmap(dpi=
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low_res_img = np.frombuffer(low_res.samples, dtype=np.uint8).reshape(low_res.height, low_res.width, 3)
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results = model.predict(low_res_img)
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@@ -378,4 +374,4 @@ st.markdown("""
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width: 300px; /* Adjust width as needed */
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}
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</style>
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""", unsafe_allow_html=True)
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2. Main methodologies used
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3. Important data points
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4. Limitations mentioned
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For any information directly derived from the context excerpts provided below, insert an in-text citation as an HTML tooltip.
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For each citation, use the following HTML format:
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<span class="tooltip" data-tooltip="{full_text}">[{n}]</span>
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Where:
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- {n} is the citation number.
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- {full_text} is the complete excerpt text for that citation.
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Do not provide a separate reference list. Instead, embed the full citation text directly in the tooltip.
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Context Excerpts:
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{contexts}"""
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)
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@handle_errors
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def qa_pdf(_pdf_file_path, query, num_clusters=5):
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embeddings_model = OpenAIEmbeddings(model="text-embedding-3-small", api_key=openai_api_key)
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llm = ChatOpenAI(model="gpt-4", api_key=openai_api_key, temperature=0.3)
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prompt = ChatPromptTemplate.from_template(
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"""Answer this question: {question}
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scale_factor = 300 / 50 # High-res to low-res ratio
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for page in doc:
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low_res = page.get_pixmap(dpi=50)
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low_res_img = np.frombuffer(low_res.samples, dtype=np.uint8).reshape(low_res.height, low_res.width, 3)
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results = model.predict(low_res_img)
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width: 300px; /* Adjust width as needed */
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}
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</style>
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""", unsafe_allow_html=True)
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