Upload folder using huggingface_hub

NITDAA_HEALTHEXPERT_USER_GUIDE.md

@@ -26,6 +26,7 @@ When a question is submitted:
 - Your question will instantly appear in the output window.
 - The system will display a **"Generating answer.. (1.2s)"** timer.
 - Once context is retrieved from the Vector and Graph databases, the LLM will stream the Markdown-formatted answer back to the screen.
+- analysis may take upto 300 seconds due to slow shared resources. please keep patience.
 - Responses remain preserved in the scrollable window for the duration of your session.
 
 ## 5. Security & Session Handling

NITDAA_HEALTHEXPERT_USER_GUIDE.pdf

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:33ef917007a829549380a693db443608e2304a24b0937ca445ce542f7902e48b
-size 189435
+oid sha256:71a1e46234c285f04912e31d4ef6739285ac60b4a6f0f9d9770ec877463627c1
+size 189859

app.py

@@ -106,7 +106,7 @@ _hf_api = None
 def get_hf_api():
     global _hf_api
     if _hf_api is None:
-        token = os.environ.get("HF_SECRET_KEY")
+        token = os.environ.get("HF_PRIVATE_TOKEN")
         if token:
             _hf_api = HfApi(token=token)
     return _hf_api
@@ -694,10 +694,9 @@ def sync_he_data():
     try:
         import os, shutil
         from huggingface_hub import snapshot_download
-        
-        token = os.environ.get("HF_SECRET_KEY")
+        token = os.environ.get("HF_PRIVATE_TOKEN")
         if not token:
-            log.error("HF_SECRET_KEY environment variable is not set. Dataset synchronization will be skipped.")
+            log.error("HF_PRIVATE_TOKEN environment variable is not set. Dataset synchronization will be skipped.")
             return
                 
         # --- 2-Way Log Sync on Startup ---
@@ -790,7 +789,7 @@ def sync_he_data():
 threading.Thread(target=sync_he_data, daemon=True).start()
 
 @app.route("/api/ingest", methods=["POST"])
-@limiter.limit("50 per hour")
+@limiter.limit("10 per minute")
 def ingest():
     """Upload and asynchronously ingest one or more documents."""
     log.info("Ingest request received. Files in request: %s",

start.sh

@@ -90,6 +90,10 @@ else
   echo "[pre-flight] Done."
 fi
 
+# ── Uninstall conflicting torchaudio to prevent OSError ─────────────────────────
+echo "[pre-flight] Removing torchaudio to prevent transformers loading issues on HF..."
+python -m pip uninstall -y torchaudio || true
+
 # ── Start embed_llm on port 8003 ──────────────────────────────────────────────
 echo "[1/3] Starting embed_llm (port 8003)..."
 python agents/embed_llm.py &