Upload README.md

README.md

@@ -1,13 +1,120 @@
 ---
-title: LibraryRAG
+title: Ask GC Library Guides
 emoji: 📚
-colorFrom: purple
-colorTo: purple
+colorFrom: blue
+colorTo: green
 sdk: streamlit
 sdk_version: 1.44.0
 app_file: app.py
 pinned: false
-license: mit
+hf_oauth: false
+hf_username: ''
+hf_token: ''
+hf_private: false
+hf_space_id: ''
+hf_disable_embedding: false
+hf_disable_inference: false
+hf_disable_sharing: false
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 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Ask GC Library Guides (RAG Demo)
+
+This Space demonstrates a Retrieval-Augmented Generation (RAG) application built with Streamlit. It allows users to ask questions about the CUNY Graduate Center library guides.
+
+**How it works:**
+
+1.  **Data Source:** Content extracted from LibGuides (`extracted_content.jsonl`).
+2.  **Embedding:** On first startup, the application uses the `BAAI/bge-m3` sentence transformer model (run locally within the Space) to embed the LibGuides content and stores it in a ChromaDB vector database (`./chroma_db`). This database persists if the Space uses persistent storage.
+3.  **Query Processing:**
+    *   User queries are optionally expanded using the generation model.
+    *   Queries are embedded using the same local `BAAI/bge-m3` model (handled internally by ChromaDB).
+    *   ChromaDB performs a similarity search to find relevant text chunks.
+4.  **Generation:** The relevant chunks and the original query are passed to the `google/gemma-3-27b-it` model via the Hugging Face Inference API to generate a final answer.
+
+**Configuration:**
+
+*   **Embedding Model:** `BAAI/bge-m3` (local via `sentence-transformers` & ChromaDB)
+*   **Generation Model:** `google/gemma-3-27b-it` (via HF Inference API)
+*   **Requires Secret:** A Hugging Face User Access Token must be added as a Space Secret named `HF_TOKEN`.
+
+**Note:** The initial embedding process when the Space first starts (or restarts without persistent storage) can take some time as the model needs to process all the documents.