Upload 34 files

app.py

@@ -30,7 +30,7 @@ from src.anomaly_model import score_reading
 from src.data_generation import generate_inventory_db, generate_orders_db
 from src.intent_model import INTENT_DESCRIPTIONS, load_pipeline, predict as intent_predict
 from src.inventory_db import query_inventory, query_orders
-from src.llm_client import answer_query, test_connection
+from src.llm_client import answer_query, test_connection, _get_hf_token, TOKEN_ENV_VAR_CANDIDATES
 from src.retriever import KBRetriever
 
 ROOT = os.path.dirname(os.path.abspath(__file__))
@@ -104,7 +104,7 @@ anomaly_eval = _load_json("anomaly_eval.json")
 retrieval_eval = _load_json("retrieval_eval.json")
 latency_eval = _load_json("latency_eval.json")
 
-HF_TOKEN_SET = bool(os.environ.get("HF_TOKEN"))
+HF_TOKEN_SET = bool(_get_hf_token())
 
 # --------------------------------------------------------------------------
 # ZeroGPU compatibility shim
@@ -493,10 +493,10 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue"), css=CUSTOM_CSS, title="
     )
     if not HF_TOKEN_SET:
         gr.Markdown(
-            "> ⚠️ **No `HF_TOKEN` secret detected.** The AI Assistant tab will run in "
+            "> ⚠️ **No HF token secret detected.** The AI Assistant tab will run in "
             "**retrieval-only fallback mode** (still functional, just not LLM-generated "
-            "prose). Add an `HF_TOKEN` secret in *Space settings → Variables and secrets* "
-            "to enable full LLM responses."
+            f"prose). Add a secret named `HF_TOKEN` (or one of: {', '.join(TOKEN_ENV_VAR_CANDIDATES[1:])}) "
+            "in *Space settings → Variables and secrets* to enable full LLM responses."
         )
 
     with gr.Tab("💬 AI Assistant"):

src/llm_client.py

@@ -47,6 +47,27 @@ if _env_model:
 
 DEFAULT_MODEL_ID = MODEL_CANDIDATES[0]
 
+# The token is normally expected as `HF_TOKEN`, but we also accept a few
+# common alternate secret names in case the Space was set up with a
+# different name. First one found wins. Add your own name here if needed.
+TOKEN_ENV_VAR_CANDIDATES = [
+    "HF_TOKEN",
+    "Smart_Warehouse",
+    "HUGGINGFACE_TOKEN",
+    "HUGGINGFACEHUB_API_TOKEN",
+    "HF_API_TOKEN",
+    "HUGGING_FACE_HUB_TOKEN",
+    "HF_ACCESS_TOKEN",
+]
+
+
+def _get_hf_token() -> Optional[str]:
+    for var in TOKEN_ENV_VAR_CANDIDATES:
+        val = os.environ.get(var)
+        if val:
+            return val
+    return None
+
 SYSTEM_PROMPT = (
     "You are the Smart Warehouse AI Assistant, a helpful operations copilot "
     "for a large automated distribution center (conveyors, AS/RS, AGVs/AMRs, "
@@ -96,7 +117,7 @@ def answer_query(
     sources = retriever.retrieve(query, k=k)
     context_block = "\n\n".join(f"[{s.title}]\n{s.text}" for s in sources)
 
-    hf_token = os.environ.get("HF_TOKEN")
+    hf_token = _get_hf_token()
 
     if not hf_token:
         answer = _extractive_fallback(query, sources)
@@ -106,7 +127,11 @@ def answer_query(
             sources=sources,
             latency_s=time.time() - start,
             model_id="extractive-fallback",
-            debug_errors=["No HF_TOKEN secret is set on this Space."],
+            debug_errors=[
+                "No HF token secret found. Checked env vars: "
+                + ", ".join(TOKEN_ENV_VAR_CANDIDATES)
+                + ". Set one of these as a Space secret (Settings -> Variables and secrets)."
+            ],
         )
 
     try: