dphn/Dolphin3.0-Mistral-24B is the ungated mirror of the Dolphin 3.0 Mistral 24B — exactly what you asked for. It's ~48GB fp16, which needs GPU+CPU split (device_map="auto" with 32GB on GPU, ~16GB in RAM). Let me kick off the download and update the service in parallel.

tour-comfy/edit_api.py

@@ -2362,7 +2362,8 @@ def _make_side_by_side(img1: Image.Image, img2: Image.Image,
 
 
 def _scenery_worker(job_id: str, model_filename: str, scene_pil: Image.Image,
-                    prompt: str, seed: int, extra_pils: list | None = None):
+                    prompt: str, seed: int, extra_pils: list | None = None,
+                    scene_video: str | None = None, extra_filename: str | None = None):
     output_dir = _load_output_dir()
     try:
         model_path = os.path.join(output_dir, model_filename)
@@ -2390,10 +2391,16 @@ def _scenery_worker(job_id: str, model_filename: str, scene_pil: Image.Image,
         try:
             embedding  = embeddings.generate_embedding(out_path)
             next_order = database.get_next_sort_order(group_id)
+            # Store all source references: person image, background video (if any), extra ref (if any)
+            refs = [model_filename]
+            if scene_video:
+                refs.append(f"video:{scene_video}")
+            if extra_filename:
+                refs.append(extra_filename)
             database.upsert_person(out_name, filepath=out_path, embedding=embedding,
                                    group_id=group_id, prompt=prompt,
                                    sort_order=next_order,
-                                   source_refs=json.dumps([model_filename]))
+                                   source_refs=json.dumps(refs))
         except Exception as db_err:
             print(f"[scenery] DB error: {db_err}")
         jobs[job_id]["status"] = "done"
@@ -2455,11 +2462,50 @@ def generate_scenery(req: SceneryRequest):
     threading.Thread(
         target=_scenery_worker,
         args=(job_id, req.model_filename, scene_pil, prompt, req.seed, extra_pils),
+        kwargs={"scene_video": req.scene_video if req.scene_video else None,
+                "extra_filename": req.extra_filename},
         daemon=True,
     ).start()
     return {"job_id": job_id, "model": req.model_filename}
 
 
+@app.get("/scenery/library")
+def scenery_library():
+    """Return all scenery images grouped by source video reference."""
+    conn = database.get_db_connection()
+    cur = conn.cursor()
+    try:
+        cur.execute("""
+            SELECT filename, group_id, source_refs
+            FROM person
+            WHERE archived IS NOT TRUE
+              AND filename LIKE '%_sc_%'
+              AND source_refs IS NOT NULL
+            ORDER BY filename DESC
+        """)
+        rows = cur.fetchall()
+    finally:
+        cur.close()
+        database._put_db_connection(conn)
+
+    by_video: dict[str, list] = {}
+    ungrouped: list = []
+    for filename, group_id, source_refs_raw in rows:
+        try:
+            refs = json.loads(source_refs_raw) if source_refs_raw else []
+        except Exception:
+            refs = []
+        video = next((r[len("video:"):] for r in refs if r.startswith("video:")), None)
+        entry = {"filename": filename, "group_id": group_id, "refs": refs}
+        if video:
+            by_video.setdefault(video, []).append(entry)
+        else:
+            ungrouped.append(entry)
+
+    groups = [{"video": v, "items": items} for v, items in by_video.items()]
+    return {"groups": groups, "ungrouped": ungrouped}
+
+
 # --- SAM2 background removal --------------------------------------------------
 
 _sam2_predictor      = None