Update app.py

app.py

@@ -2,18 +2,24 @@ from fastapi import FastAPI
 from pydantic import BaseModel, conlist, confloat
 from typing import Dict, Any, List, Literal
 from datetime import datetime
+import os
 
-# LangSmith (OTel) tracing via Traceloop SDK
-# Set these in the Space Settings → Variables (key/value):
-# TRACELOOP_BASE_URL = https://api.smith.langchain.com/otel
-# TRACELOOP_HEADERS  = x-api-key=<YOUR_LANGSMITH_API_KEY>
-from traceloop.sdk import Traceloop
-Traceloop.init(app_name="ssra-auditor")  # traces show up under this name
-from traceloop.sdk.decorators import workflow
+# --- Optional tracing (won't crash if key missing) ---
+# If you want tracing, create a LangSmith or Traceloop account.
+# For Traceloop: set TRACELOOP_API_KEY=<your_key> in Space → Settings → Variables.
+try:
+    if os.getenv("TRACELOOP_API_KEY"):
+        from traceloop.sdk import Traceloop
+        from traceloop.sdk.decorators import workflow
+        Traceloop.init(app_name="ssra-auditor")
+        TRACING = True
+    else:
+        TRACING = False
+except Exception:
+    TRACING = False
 
-# Guardrails AI: schema + semantic guardrails
+# --- Guardrails schema guard (semantic validators are optional) ---
 from guardrails import Guard
-from guardrails.validators import ValidLength  # example semantic validator
 
 app = FastAPI()
 
@@ -39,24 +45,17 @@ AUDIT_SCHEMA = {
   },
   "required": ["decision","metrics","deltas"]
 }
-
-# Example: cap deltas to 10 items (semantic-ish)
-guard = Guard().configure(
-  output_schema=AUDIT_SCHEMA,
-  validators={ "deltas": [ValidLength(min=0, max=10)] }
-)
+guard = Guard().configure(output_schema=AUDIT_SCHEMA)
+# Guardrails: schema + optional semantic validators; see docs & hub for options. :contentReference[oaicite:1]{index=1}
 
 @app.get("/health")
 def health():
-    return {"ok": True, "service": "auditor", "ts": datetime.utcnow().isoformat()}
+    return {"ok": True, "service": "auditor", "ts": datetime.utcnow().isoformat(), "tracing": TRACING}
 
-@workflow(name="audit_workflow")   # shows up as a workflow in traces
-@app.post("/audit", response_model=AuditResult)
-def audit(payload: Dict[str, Any]):
+def _audit_logic(payload: Dict[str, Any]) -> AuditResult:
     bundle = payload.get("bundle", {}) or {}
     m_in   = payload.get("metrics", {}) or {}
 
-    # start from inbound metrics
     m = {
       "TCS": float(m_in.get("TCS", 0.0)),
       "HDI": float(m_in.get("HDI", 0.0)),
@@ -70,7 +69,6 @@ def audit(payload: Dict[str, Any]):
     regions = len((bundle.get("regions",{}).get("data") or {}).get("regions_ranked",[]) or [])
     lit_ok  = bool(bundle.get("literature"))
 
-    # recompute (simple heuristics)
     m["TCS"] = min(1.0, (1 if edges>0 else 0) + (1 if regions>0 else 0) + (1 if lit_ok else 0)) * 0.9
     m["HDI"] = 1.2 if regions>8 else (1.0 if regions>4 else 0.8)
     m["EVI"] = (1 if edges>0 else 0) + (1 if regions>0 else 0) + (1 if lit_ok else 0)
@@ -85,7 +83,18 @@ def audit(payload: Dict[str, Any]):
         if m["EVI"] < 3:   deltas.append("Add one more evidence type (review/trials).")
         if m["CBS"] > 0.6: deltas.append("Surface/address contrary findings explicitly.")
 
-    # Guardrails validate & auto-repair minor schema issues
     out_raw = {"metrics": m, "decision": decision, "deltas": deltas}
     _, validated, *_ = guard.parse(out_raw)
     return AuditResult(**validated)
+
+# Route with or without Traceloop @workflow
+if TRACING:
+    from traceloop.sdk.decorators import workflow
+    @workflow(name="audit_workflow")
+    @app.post("/audit", response_model=AuditResult)
+    def audit(payload: Dict[str, Any]):
+        return _audit_logic(payload)
+else:
+    @app.post("/audit", response_model=AuditResult)
+    def audit(payload: Dict[str, Any]):
+        return _audit_logic(payload)