feat(v0.7.2): data-flow correctness — fix the 27K→35 dashboard gap

Gradata/examples/basic_usage.py

@@ -1,5 +1,7 @@
 """Basic Gradata usage — learn from corrections in 10 lines."""
+
 from pathlib import Path
+
 from gradata.brain import Brain
 
 # Create a brain (or open existing)

Gradata/examples/domain-profiles/sales_profile.py

@@ -26,15 +26,16 @@
 from __future__ import annotations
 
 from collections import defaultdict
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from datetime import datetime
 
 
 @dataclass
 class OutreachEvent:
     """A single outreach attempt."""
-    channel: str           # email, call, linkedin, etc.
-    timestamp: str         # ISO 8601
+
+    channel: str  # email, call, linkedin, etc.
+    timestamp: str  # ISO 8601
     prospect: str = ""
     replied: bool = False
     reply_sentiment: str = ""  # positive, neutral, negative
@@ -43,6 +44,7 @@ class OutreachEvent:
 @dataclass
 class FollowupEvent:
     """A follow-up in a sequence."""
+
     prospect: str
     touch_number: int
     days_since_last: int
@@ -53,20 +55,21 @@ class FollowupEvent:
 @dataclass
 class SalesProfileReport:
     """Aggregated sales behavioral metrics."""
+
     # Timing
-    best_send_hours: list[int]           # Hours (0-23) with highest reply rates
-    best_send_days: list[str]            # Days of week with highest reply rates
-    avg_response_time_hours: float       # Average time to reply after outreach
+    best_send_hours: list[int]  # Hours (0-23) with highest reply rates
+    best_send_days: list[str]  # Days of week with highest reply rates
+    avg_response_time_hours: float  # Average time to reply after outreach
 
     # Cadence
     avg_days_between_touches: float
-    cadence_compliance: float            # 0-1, how close to optimal cadence
-    touches_before_reply: float          # Average touches before first reply
-    drop_off_touch: int                  # Touch number where most sequences die
+    cadence_compliance: float  # 0-1, how close to optimal cadence
+    touches_before_reply: float  # Average touches before first reply
+    drop_off_touch: int  # Touch number where most sequences die
 
     # Multi-threading
-    avg_contacts_per_deal: float         # Gong: 2x contacts = higher win rate
-    deals_with_single_contact: int       # Risk indicator
+    avg_contacts_per_deal: float  # Gong: 2x contacts = higher win rate
+    deals_with_single_contact: int  # Risk indicator
     deals_with_multithread: int
 
     # Volume
@@ -92,13 +95,15 @@ def log_outreach(
         reply_sentiment: str = "",
     ) -> None:
         """Log an outreach attempt."""
-        self._outreach.append(OutreachEvent(
-            channel=channel,
-            timestamp=timestamp,
-            prospect=prospect,
-            replied=replied,
-            reply_sentiment=reply_sentiment,
-        ))
+        self._outreach.append(
+            OutreachEvent(
+                channel=channel,
+                timestamp=timestamp,
+                prospect=prospect,
+                replied=replied,
+                reply_sentiment=reply_sentiment,
+            )
+        )
 
     def log_followup(
         self,
@@ -109,13 +114,15 @@ def log_followup(
         replied: bool = False,
     ) -> None:
         """Log a follow-up touch in a sequence."""
-        self._followups.append(FollowupEvent(
-            prospect=prospect,
-            touch_number=touch_number,
-            days_since_last=days_since_last,
-            channel=channel,
-            replied=replied,
-        ))
+        self._followups.append(
+            FollowupEvent(
+                prospect=prospect,
+                touch_number=touch_number,
+                days_since_last=days_since_last,
+                channel=channel,
+                replied=replied,
+            )
+        )
 
     def log_deal_contact(self, deal: str, contact_role: str) -> None:
         """Log a contact associated with a deal (multi-threading tracking)."""
@@ -147,9 +154,7 @@ def compute(self) -> SalesProfileReport:
 
         # Best days by reply rate
         day_rates = {
-            d: sum(replies) / len(replies)
-            for d, replies in reply_days.items()
-            if len(replies) >= 3
+            d: sum(replies) / len(replies) for d, replies in reply_days.items() if len(replies) >= 3
         }
         best_days = sorted(day_rates, key=day_rates.get, reverse=True)[:3]
 
@@ -159,7 +164,8 @@ def compute(self) -> SalesProfileReport:
             replied_followups = [f for f in self._followups if f.replied]
             touches_before = (
                 sum(f.touch_number for f in replied_followups) / len(replied_followups)
-                if replied_followups else 0.0
+                if replied_followups
+                else 0.0
             )
             # Find drop-off: touch number with most non-replied sequences
             touch_counts: dict[int, int] = defaultdict(int)
@@ -178,7 +184,7 @@ def compute(self) -> SalesProfileReport:
                 if gaps:
                     deviations = [
                         abs(a - o) / max(o, 1)
-                        for a, o in zip(gaps[:5], optimal_gaps[:len(gaps)])
+                        for a, o in zip(gaps[:5], optimal_gaps[: len(gaps)], strict=False)
                     ]
                     compliances.append(max(0.0, 1.0 - sum(deviations) / len(deviations)))
             compliance = sum(compliances) / len(compliances) if compliances else 0.0
@@ -194,7 +200,8 @@ def compute(self) -> SalesProfileReport:
         multi = sum(1 for contacts in self._deal_contacts.values() if len(contacts) > 1)
         avg_contacts = (
             sum(len(c) for c in self._deal_contacts.values()) / deal_count
-            if deal_count > 0 else 0.0
+            if deal_count > 0
+            else 0.0
         )
 
         # Reply rates

Gradata/examples/with_claude_code.py

@@ -13,6 +13,7 @@
 
 See also: .claude-plugin/README.md for the zero-code install flow.
 """
+
 from pathlib import Path
 
 from gradata.brain import Brain

Gradata/examples/with_openai.py

@@ -7,6 +7,7 @@
 
 Requires:  pip install gradata openai
 """
+
 from pathlib import Path
 
 from openai import OpenAI

Gradata/scripts/migrate_legacy_scopes.py

@@ -118,9 +118,7 @@ def load_domain_set(
             if isinstance(data, list):
                 return {str(d).strip().lower() for d in data if str(d).strip()}
         except ImportError:
-            logger.warning(
-                "PyYAML not installed; falling back to inferred domain set."
-            )
+            logger.warning("PyYAML not installed; falling back to inferred domain set.")
         except Exception as exc:  # pragma: no cover - defensive
             logger.warning("Could not parse %s: %s", domains_file, exc)
 

Gradata/src/gradata/_config.py

@@ -79,6 +79,11 @@ class BrainConfig:
     max_recall_tokens: int = 2000
     ranker: RecallRanker = "hybrid"
 
+    @classmethod
+    def load(cls, brain_dir: str | Path | None = None) -> BrainConfig:
+        """Load runtime config from ``<brain_dir>/brain-config.json``."""
+        return _load_brain_config(brain_dir)
+
 
 BRAIN_CONFIG = BrainConfig()
 

Gradata/src/gradata/_context_packet.py

@@ -382,6 +382,7 @@ def build_packet(
     packet = {}
     if session is None:
         session = _detect_session()
+    session = session or 0
 
     if task_type in ("prospecting", "meeting_prep"):
         packet["user_scope"] = _load_user_scope(ctx=ctx)

Gradata/src/gradata/_core.py

@@ -1231,11 +1231,15 @@ def _cloud_sync_session(
     """Best-effort cloud sync at session end. Never raises, never blocks."""
     try:
         import hashlib
-        import os
         from pathlib import Path
 
-        # 1. Resolve cloud credentials: ~/.gradata/config.toml or env var
-        api_key = os.environ.get("GRADATA_API_KEY", "")
+        # 1. Resolve cloud credentials: per-brain cloud-config.json, keyfile,
+        # legacy ~/.gradata/config.toml, or env var.
+        from gradata.cloud import _credentials as _cloud_creds
+        from gradata.cloud.sync import load_config as _load_cloud_config
+
+        brain_cloud_cfg = _load_cloud_config(brain.dir)
+        api_key = _cloud_creds.resolve_credential(fallback=brain_cloud_cfg.token)
         api_url = ""
         brain_id_from_config = ""
 
@@ -1249,6 +1253,7 @@ def _cloud_sync_session(
             except Exception as e:
                 _log.debug("cloud config parse failed: %s", e)
 
+        api_url = _cloud_creds.resolve_endpoint(api_url, fallback=brain_cloud_cfg.api_base)
         if not api_key:
             return  # No cloud credentials — nothing to sync
 
@@ -1337,17 +1342,15 @@ def _cloud_sync_session(
         sync_client.sync_metrics(payload)
         _log.debug("Cloud telemetry synced for session %d", session)
 
-        # Finding 11: respect sync_mode — default is metrics_only.
-        # Only sync full events/corrections if explicitly opted in via config.
-        sync_mode = "metrics_only"
+        sync_mode = getattr(brain_cloud_cfg, "sync_mode", "full") or "full"
         try:
             cfg = _parse_toml_cloud(config_path)
-            sync_mode = cfg.get("sync_mode", "metrics_only")
+            sync_mode = cfg.get("sync_mode", sync_mode)
         except Exception:
             pass
 
         if sync_mode == "full":
-            # 4. Sync events/corrections via the full cloud client (opt-in only)
+            # 4. Sync events/corrections via the full cloud client.
             try:
                 from gradata.cloud.client import CloudClient
 
@@ -1361,9 +1364,14 @@ def _cloud_sync_session(
                     _log.debug("Cloud event sync completed for session %d", session)
             except Exception as e:
                 _log.debug("Cloud event sync failed (non-fatal): %s", e)
+        elif sync_mode == "metrics_only":
+            _log.warning(
+                "Skipping event/correction sync (sync_mode=metrics_only) — dashboard will "
+                "not show corrections. Run `gradata sync --full` to backfill."
+            )
         else:
-            _log.debug(
-                "Cloud sync_mode=%s — skipping event/correction sync for session %d",
+            _log.warning(
+                "Unknown cloud sync_mode=%s — skipping event/correction sync for session %d",
                 sync_mode,
                 session,
             )