Update src/qa.py
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src/qa.py
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@@ -6,6 +6,7 @@ qa.py — GPT-4o (SAP Gen AI Hub) + ReRank Retrieval
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✅ Embedding caching (per PDF)
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✅ Smart factual mode (fast)
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✅ Deep reasoning mode (ChatGPT-like)
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"""
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import os
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@@ -247,7 +248,31 @@ def generate_answer(query: str, retrieved_chunks: list, reasoning_mode: bool = F
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return "⚠️ Error: Could not generate an answer."
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# ==========================================================
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# 8️⃣
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# ==========================================================
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if __name__ == "__main__":
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from vectorstore import build_faiss_index
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✅ Embedding caching (per PDF)
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✅ Smart factual mode (fast)
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✅ Deep reasoning mode (ChatGPT-like)
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✅ genai_generate() helper for suggestions
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"""
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import os
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return "⚠️ Error: Could not generate an answer."
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# ==========================================================
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# 8️⃣ Generic Text Generation Helper (for AI suggestions)
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# ==========================================================
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def genai_generate(prompt: str) -> str:
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"""
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Utility for single-turn GPT-4o generation (e.g., query suggestions, summaries).
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Uses the same SAP Gen AI Hub connection as main assistant.
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"""
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global chat_llm
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if chat_llm is None:
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raise RuntimeError("⚠️ GPT-4o not initialized. Check credentials or rebuild the Space.")
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messages = [
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{"role": "system", "content": "You are a concise, intelligent text generator."},
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{"role": "user", "content": prompt.strip()},
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]
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try:
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response = chat_llm.invoke(messages)
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return response.content.strip()
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except Exception as e:
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print(f"⚠️ genai_generate() failed: {e}")
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return "⚠️ Unable to generate response."
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# ==========================================================
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# 9️⃣ Local Test
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# ==========================================================
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if __name__ == "__main__":
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from vectorstore import build_faiss_index
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