Upload app-5.py

app-5.py

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+
+import gradio as gr
+from groq import ChatGroq
+from llama_index import load_index_from_storage, ServiceContext, set_global_service_context
+from llama_index.vector_stores.faiss import FaissVectorStore
+from llama_index.embeddings.huggingface import HuggingFaceEmbedding
+from llama_index.storage.storage_context import StorageContext
+from PIL import Image
+
+# Initialize Groq Vision LLM
+vision_llm = ChatGroq(
+    model_name="meta-llama/llama-4-scout-17b-16e-instruct",
+    api_key="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"
+)
+
+# Load FAISS index from persisted directory
+faiss_index_path = "faiss_store"
+vector_store = FaissVectorStore.from_persist_dir(faiss_index_path)
+storage_context = StorageContext.from_defaults(vector_store=vector_store)
+index = load_index_from_storage(storage_context)
+
+# Setup embedding context
+embed_model = HuggingFaceEmbedding(model_name="BAAI/bge-small-en")
+service_context = ServiceContext.from_defaults(embed_model=embed_model)
+set_global_service_context(service_context)
+
+# Setup query engine
+query_engine = index.as_query_engine()
+
+def multimodal_skin_rag(image, question):
+    context = query_engine.query(question)
+    user_prompt = f"""Based on the following skincare context, answer the user's question with reference to the image (if relevant):
+
+Context:
+{context}
+
+Question:
+{question}
+"""
+    messages = [
+        {"role": "system", "content": "You are a skincare advisor who understands image-based inputs and medical-grade text."},
+        {"role": "user", "content": user_prompt}
+    ]
+    response = vision_llm.chat(messages=messages, images=[image])
+    return response.choices[0].message.content
+
+demo = gr.Interface(
+    fn=multimodal_skin_rag,
+    inputs=[
+        gr.Image(type="pil", label="Upload Skin Image"),
+        gr.Textbox(label="Describe your skin concern or ask a question")
+    ],
+    outputs="text",
+    title="SkinCare Assistant: FAISS + Groq LLM",
+    description="Upload a skin image and ask any skincare-related question. This system retrieves relevant content using FAISS and answers using Groq's Vision LLM."
+)
+
+if __name__ == "__main__":
+    demo.launch()