updated requirements, created docker file for HF deployment, modified lifespan to load model, stopped tracking joblib files

.gitignore

@@ -5,6 +5,7 @@ data/outputs/
 
 # models
 models/distilbert_trace/
+models/*.joblib
 
 # python
 __pycache__/

Dockerfile

@@ -0,0 +1,12 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,3 +1,10 @@
+---
+title: OffRails API
+sdk: docker
+app_port: 7860
+pinned: false
+---
+
 # Agent Trace Anomaly Detection
 
 Detect when AI agents "go off the rails" — unnecessary tool calls, circular reasoning, and goal drift — by framing multi-step execution traces as a **sequence anomaly detection** problem.

app/main.py

@@ -21,6 +21,9 @@ import logging
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 
+from contextlib import asynccontextmanager
+from app.api.routes import _state
+
 # ── Make partner's scripts/ importable ───────────────────────────────────────
 # inference.py does `from model import ...` and `from build_features import ...`
 # so we need scripts/ on sys.path.
@@ -38,10 +41,32 @@ logging.basicConfig(
     datefmt="%H:%M:%S",
 )
 
+logger = logging.getLogger(__name__)
+
 # ── App ──────────────────────────────────────────────────────────────────────
 
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    from huggingface_hub import hf_hub_download
+    from scripts.inference import TraceAnomalyDetector
+    try:
+        model_path = hf_hub_download(
+            repo_id="mg643/offrails-models",
+            filename="xgboost_model.joblib",
+        )
+        _state["detector"] = TraceAnomalyDetector(
+            model_dir=os.path.dirname(model_path),
+            model_type="xgboost"
+        )
+        _state["model_type"] = "xgboost"
+        logger.info("XGBoost model loaded from HF Hub")
+    except Exception as e:
+        logger.warning(f"Could not load model: {e}")
+    yield
+
 app = FastAPI(
     title="Agent Trace Anomaly Detection API",
+    lifespan=lifespan,
     description=(
         "Detects anomalous agent execution traces — unnecessary tool calls, "
         "circular reasoning, and goal drift.\n\n"

requirements.txt

@@ -5,6 +5,8 @@ torch
 scikit-learn
 xgboost
 joblib
+uvicorn
+fastapi
 
 # evaluation + viz
 matplotlib