Refine GPT enrichment logic, add relevance badges to UI, and fix minor model/logging issues

app.py

@@ -112,6 +112,15 @@ async def _enrich_first_frame_gpt(
             gpt_dets = [d for d in detections if d.get("mission_relevant", True)]
 
         if not gpt_dets:
+            # All detections filtered as not relevant — mark ASSESSED and persist
+            for det in detections:
+                det["assessment_status"] = "ASSESSED"
+            storage = get_job_storage()
+            storage.update(
+                job_id,
+                first_frame_detections=detections,
+            )
+            logging.info("All detections non-relevant for job %s; marked ASSESSED", job_id)
             return
 
         # GPT threat assessment
@@ -131,8 +140,9 @@ async def _enrich_first_frame_gpt(
                 info = gpt_results[obj_id]
                 det.update(info)
                 det["gpt_raw"] = info
-                det["assessment_frame_index"] = 0
-                det["assessment_status"] = "ASSESSED"
+            # Mark ASSESSED regardless of whether GPT returned data for this object
+            det["assessment_frame_index"] = 0
+            det["assessment_status"] = "ASSESSED"
 
         for det in detections:
             if "assessment_status" not in det:

frontend/js/api/client.js

@@ -161,18 +161,36 @@ APP.api.client.pollAsyncJob = async function () {
 
                     // Check if GPT enrichment has updated first-frame detections
                     if (status.first_frame_detections && status.first_frame_detections.length > 0) {
-                        const hasGpt = status.first_frame_detections.some(d => d.assessment_status === "ASSESSED");
-                        const alreadyEnriched = state.hf._gptEnriched;
-                        if (hasGpt && !alreadyEnriched) {
+                        const rawDets = status.first_frame_detections;
+                        let needsRender = false;
+
+                        // Phase A: Always sync assessment status fields (not gated on gpt_raw)
+                        for (const rd of rawDets) {
+                            const tid = rd.track_id || `T${String(rawDets.indexOf(rd) + 1).padStart(2, "0")}`;
+                            const existing = (state.detections || []).find(d => d.id === tid);
+                            if (existing) {
+                                if (rd.assessment_status && existing.assessment_status !== rd.assessment_status) {
+                                    existing.assessment_status = rd.assessment_status;
+                                    needsRender = true;
+                                }
+                                if (rd.mission_relevant !== undefined && rd.mission_relevant !== null) {
+                                    existing.mission_relevant = rd.mission_relevant;
+                                }
+                                if (rd.relevance_reason) {
+                                    existing.relevance_reason = rd.relevance_reason;
+                                }
+                            }
+                        }
+
+                        // Phase B: One-shot GPT feature merge (gated on gpt_raw + _gptEnriched flag)
+                        const hasGptData = rawDets.some(d => d.gpt_raw);
+                        if (hasGptData && !state.hf._gptEnriched) {
                             state.hf._gptEnriched = true;
-                            state.hf.firstFrameDetections = status.first_frame_detections;
-                            // Merge GPT data into existing state.detections (preserve bbox/aim/etc)
-                            const rawDets = status.first_frame_detections;
+                            state.hf.firstFrameDetections = rawDets;
                             for (const rd of rawDets) {
                                 const tid = rd.track_id || `T${String(rawDets.indexOf(rd) + 1).padStart(2, "0")}`;
                                 const existing = (state.detections || []).find(d => d.id === tid);
                                 if (existing && rd.gpt_raw) {
-                                    existing.features = {};
                                     const g = rd.gpt_raw;
                                     const rangeStr = g.range_estimate && g.range_estimate !== "Unknown"
                                         ? g.range_estimate + " (est.)" : "Unknown";
@@ -197,16 +215,17 @@ APP.api.client.pollAsyncJob = async function () {
                                     existing.threat_level_score = rd.threat_level_score || g.threat_level_score || 0;
                                     existing.threat_classification = rd.threat_classification || g.threat_classification || "Unknown";
                                     existing.weapon_readiness = rd.weapon_readiness || g.weapon_readiness || "Unknown";
-                                    existing.assessment_status = rd.assessment_status || "ASSESSED";
                                     existing.gpt_distance_m = rd.gpt_distance_m || null;
                                     existing.gpt_direction = rd.gpt_direction || null;
+                                    needsRender = true;
                                 }
                             }
-                            if (APP.ui && APP.ui.cards && APP.ui.cards.renderFrameTrackList) {
-                                APP.ui.cards.renderFrameTrackList();
-                            }
                             log("Track cards updated with GPT assessment", "g");
                         }
+
+                        if (needsRender && APP.ui && APP.ui.cards && APP.ui.cards.renderFrameTrackList) {
+                            APP.ui.cards.renderFrameTrackList();
+                        }
                     }
                 }
 

frontend/js/ui/cards.js

@@ -97,7 +97,12 @@ APP.ui.cards.renderFrameTrackList = function () {
                 <span>${id} · ${det.label}</span>
                 <div style="display:flex; gap:4px; align-items:center">
                     ${statusBadge}
-                    <span class="badgemini" style="background:rgba(255,255,255,.08); color:rgba(255,255,255,.7)">${(det.score * 100).toFixed(0)}%</span>
+                    ${det.mission_relevant === true
+                        ? '<span class="badgemini" style="background:#28a745; color:white">RELEVANT</span>'
+                        : det.mission_relevant === false
+                            ? '<span class="badgemini" style="background:#6c757d; color:white">N/R</span>'
+                            : `<span class="badgemini" style="background:rgba(255,255,255,.08); color:rgba(255,255,255,.7)">${(det.score * 100).toFixed(0)}%</span>`
+                    }
                 </div>
             </div>
             <div class="track-card-meta">

models/detectors/grounding_dino.py

@@ -23,7 +23,10 @@ class GroundingDinoDetector(ObjectDetector):
             self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         logging.info("Loading %s onto %s", self.MODEL_NAME, self.device)
         self.processor = GroundingDinoProcessor.from_pretrained(self.MODEL_NAME)
-        self.model = GroundingDinoForObjectDetection.from_pretrained(self.MODEL_NAME)
+        self.model = GroundingDinoForObjectDetection.from_pretrained(
+            self.MODEL_NAME,
+            low_cpu_mem_usage=False,
+        )
         self.model.to(self.device)
         self.model.eval()
 

utils/gpt_reasoning.py

@@ -141,7 +141,7 @@ def estimate_threat_gpt(
 
     api_key = os.environ.get("OPENAI_API_KEY")
     if not api_key:
-        logger.warning("OPENAI_API_KEY not set. Skipping GPT threat assessment.")
+        logger.error("OPENAI_API_KEY not set. Skipping GPT threat assessment.")
         return {}
 
     # 1. Prepare detections summary for prompt
@@ -271,5 +271,5 @@ def estimate_threat_gpt(
         return objects
 
     except Exception as e:
-        logger.error(f"GPT API call failed: {e}")
+        logger.error("GPT API call failed: %s", e, exc_info=True)
         return {}