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app.py
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This demonstration shows:
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1. **PubMed RAG**: Retrieve abstracts, summarize, and feed them into an LLM.
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2. **Image Captioning**: Upload an image for analysis using a known stable model.
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3. **Separation of Concerns**: Each pipeline is in its own module.
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**Note**: If you previously encountered KeyError: 'idefics3', it's because the
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`SmolVLM-500M-Instruct` model was incompatible with your Transformers version.
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Here, we use a supported model such as `nlpconnect/vit-gpt2-image-captioning`.
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**Disclaimer**: This is a prototype, not medical advice.
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""")
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# Section A: Image Upload / Caption
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This demonstration shows:
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1. **PubMed RAG**: Retrieve abstracts, summarize, and feed them into an LLM.
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2. **Image Captioning**: Upload an image for analysis using a known stable model.
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""")
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# Section A: Image Upload / Caption
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