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app.py

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+import gradio as gr
+from sentence_transformers import SentenceTransformer, util
+import os
+
+# Load data
+with open("data/handshape_book.txt", encoding="utf-8") as f:
+    book_text = f.read()
+
+# Split into chunks
+chunks = [chunk.strip() for chunk in book_text.split('\n\n') if len(chunk.strip()) > 100]
+
+# Create embeddings
+model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+corpus_embeddings = model.encode(chunks, convert_to_tensor=True)
+
+# Search function
+def ask_question(question):
+    question_embedding = model.encode(question, convert_to_tensor=True)
+    hits = util.semantic_search(question_embedding, corpus_embeddings, top_k=3)[0]
+    results = "\n\n---\n\n".join([chunks[hit['corpus_id']] for hit in hits])
+    return results
+
+# Gradio UI
+iface = gr.Interface(fn=ask_question,
+                     inputs=gr.Textbox(lines=2, placeholder="Ask about handshapes..."),
+                     outputs="text",
+                     title="ASL Handshape RAG",
+                     description="Semantic search over American Sign Language Handshape Dictionary.")
+
+iface.launch()

requirements.txt

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+transformers>=4.39.3
+sentence-transformers>=2.7.0
+faiss-cpu>=1.7.4
+gradio>=5.0.0
+python-multipart
+pydub
+orjson
+pdfplumber>=0.10.0
+fastapi>=0.115.2
+uvicorn>=0.34.0