Update app.py
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app.py
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@@ -30,9 +30,11 @@ desc = """
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It works by first retrieving relevant documents from an external knowledge source (like PDF files) and then using a LLM model to produce responses based on both the input query and the retrieved content.
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This method enhances factual correctness and allows the model to access up-to-date or domain-specific information without retraining.
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Click the button below to load a **User Guide** and an **Installation Guide** for a smoke alarm device into the vector database.
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Once you see the message *"PDF indexed successfully!"*, go to the **Chatbot** tab to ask any relevant questions about the device.
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"""
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sample_button = "Load User Guide and Installation Guide documents"
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It works by first retrieving relevant documents from an external knowledge source (like PDF files) and then using a LLM model to produce responses based on both the input query and the retrieved content.
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This method enhances factual correctness and allows the model to access up-to-date or domain-specific information without retraining.
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Click the button below to load a **User Guide** and an **Installation Guide** for a smoke alarm device into the vector database. It could take a couple of minutes to process.
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Once you see the message *"PDF indexed successfully!"*, go to the **Chatbot** tab to ask any relevant questions about the device.
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You can change the LLM models in the **Additional Inputs** at the bottom of the **Chatbot** tab, you can also adjust the LLM parameters there.
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"""
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sample_button = "Load User Guide and Installation Guide documents"
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