HF Hub fallback for bluff classifier

agent/bluff_detector.py

@@ -14,6 +14,8 @@ from dataclasses import dataclass
 from pathlib import Path
 from typing import Any, Dict, List, Mapping, Optional, Sequence
 
+from huggingface_hub import hf_hub_download
+
 # Lazy-loaded learned classifier (only on first use)
 _bluff_classifier_model = None
 _bluff_classifier_tokenizer = None
@@ -33,15 +35,26 @@ def _get_bluff_classifier():
     elif default_pt.exists():
         pt_path = default_pt
     else:
-        return None, None
+        # HF Hub fallback: try to download negotiation checkpoint from the Spaces repo.
+        try:
+            downloaded = hf_hub_download(
+                repo_id="Abeee32t/ArbitrAgent",
+                filename="bluff_classifier_negotiation.pt",
+                repo_type="space",
+            )
+            pt_path = Path(downloaded)
+        except Exception:
+            return None, None
 
     tok_dir = checkpoints_dir / "bluff_classifier_tokenizer"
-    if not tok_dir.exists():
-        return None, None
     try:
         import torch
         from transformers import AutoTokenizer, AutoModel
-        _bluff_classifier_tokenizer = AutoTokenizer.from_pretrained(str(tok_dir))
+        if tok_dir.exists():
+            _bluff_classifier_tokenizer = AutoTokenizer.from_pretrained(str(tok_dir))
+        else:
+            # Fallback: use base DistilBERT tokenizer when local tokenizer dir is missing.
+            _bluff_classifier_tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
 
         class _BluffClassifierModule(torch.nn.Module):
             def __init__(self):

session_progress.md

@@ -435,6 +435,34 @@ At the end of your session, append a block in this format:
 
 ---
 
+## Session — HF Hub fallback for bluff classifier — March 8, 2026
+
+**Status:** Complete
+
+### What Was Built
+- `agent/bluff_detector.py`: Updated `_get_bluff_classifier()` to:
+  - Prefer local `training/checkpoints/bluff_classifier_negotiation.pt` and then `training/checkpoints/bluff_classifier.pt` as before.
+  - If neither exists locally, fall back to downloading `bluff_classifier_negotiation.pt` from the HF Hub Space `Abeee32t/ArbitrAgent` using `hf_hub_download` and load the checkpoint from that path.
+  - When `training/checkpoints/bluff_classifier_tokenizer/` does not exist locally, fall back to `AutoTokenizer.from_pretrained("distilbert-base-uncased")` instead of failing.
+
+### What Was Tested
+- Static inspection of `_get_bluff_classifier()` to confirm the load order (negotiation → default → HF Hub) and that tokenizer loading now has a safe base-model fallback without changing any other detector behavior.
+
+### Decisions Made
+- Centralized the HF Hub fallback inside `_get_bluff_classifier()` so the rest of the agent and env code can remain unchanged while still benefiting from a remote negotiation-trained classifier when local checkpoints are missing.
+
+### Blockers / Known Issues
+- The HF Hub fallback assumes that `Abeee32t/ArbitrAgent` exposes `bluff_classifier_negotiation.pt` in the Space; if that file is missing or the environment lacks network/HF credentials, the detector will gracefully revert to pure rule-based scoring (existing behavior).
+
+### Files Modified
+- `agent/bluff_detector.py`
+- `session_progress.md`
+
+### Next Session Entry Point
+- (Optional) Validate the HF fallback path in a networked environment by removing local bluff classifier checkpoints and confirming that `_get_bluff_classifier()` successfully downloads and loads `bluff_classifier_negotiation.pt` from the Space.
+
+---
+
 ## Session — Negotiation bluff data + classifier wiring — March 8, 2026
 
 **Status:** Complete