diff --git a/.gitignore b/.gitignore index e9a3f5c2..8f770c98 100644 --- a/.gitignore +++ b/.gitignore @@ -11,6 +11,7 @@ agent/active_project.json # Generated AI tool configs (run: python setup.py) .claude/commands/fk-* +.agents/skills/fk-* AGENTS.md .fk-setup.json @@ -28,3 +29,7 @@ extension/_metadata/ .agent/ flow_session_project.json .venv/ +*.mp3 +scratch/ + +series_manifest.json diff --git a/AGENTS.md b/AGENTS.md index bc523821..28f450d8 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -81,11 +81,14 @@ This project has reusable skills in `skills/`. When the user says `/fk-`, | Skill | Purpose | |-------|---------| +| `/fk-action-choreography` | Action Choreography — AI Cinematic Combat & Motion Direction | | `/fk-add-material` | fk-add-material — Image Material System | | `/fk-brand-logo` | fk-brand-logo — Apply Channel Branding (Intro + Outro + Logo + 4K Badge) | | `/fk-camera-guide` | Camera Guide — Cinematic Video Prompts (Veo 3) | | `/fk-change-model` | fk-change-model — View & Change Video/Image Model Keys | | `/fk-change-provider` | fk-change-provider — View & Switch the Reviewer for a Role | +| `/fk-character-bible` | Character Bible & Visual Consistency — AI Film Production | +| `/fk-cinematic-transitions` | Cinematic Transitions & Chapter Bumpers — AI Film Direction | | `/fk-concat-fit-narrator` | Trim each scene video to fit its TTS narrator duration, burn text overlays, then concatenate into a final video. | | `/fk-concat` | Download and concatenate all scene videos into a single video with optional TTS narration. | | `/fk-create-project` | Create a new Google Flow video project. Ask the user for: | @@ -110,6 +113,8 @@ This project has reusable skills in `skills/`. When the user says `/fk-`, | `/fk-research` | fk-research — Fact-Check & Research Before Scripting | | `/fk-review-board` | Start the Scene Review Board web app for visual feedback on scene chains. | | `/fk-review-video` | Review AI-generated scene videos for quality. | +| `/fk-scriptwriter` | The Ultimate AI Screenplay Bible — Google Flow & Veo 3 | +| `/fk-sound-design` | Sound Design & Audio Mastering — AI Cinematic Soundscapes | | `/fk-status` | Show full status dashboard for a project. | | `/fk-switch-project` | fk-switch-project — Switch Active Project | | `/fk-thumbnail-guide` | YouTube Thumbnail Guide — Hook-Worthy Design Rules | diff --git a/agent/api/projects.py b/agent/api/projects.py index 31a8a51f..955c9372 100644 --- a/agent/api/projects.py +++ b/agent/api/projects.py @@ -298,9 +298,88 @@ async def get_characters(pid: str): return await repo.get_project_characters(pid) +async def _build_or_update_series_manifest(repo, project, slug: str, output_dir: Path) -> dict: + """Build or synchronize the project-level series_manifest.json.""" + pid = getattr(project, "id", None) or (project.get("id") if isinstance(project, dict) else "") + project_name = getattr(project, "name", None) or (project.get("name") if isinstance(project, dict) else "") + manifest_path = output_dir / "series_manifest.json" + + existing = {} + if manifest_path.exists(): + try: + existing = json.loads(manifest_path.read_text(encoding="utf-8")) + except Exception: + existing = {} + + chars = await repo.get_project_characters(pid) + chars_list = [] + locs_list = [] + props_list = [] + + for c in chars: + entity_type = getattr(c, "entity_type", None) or "character" + entry = { + "name": getattr(c, "name", ""), + "slug": getattr(c, "slug", ""), + "entity_type": entity_type, + "description": getattr(c, "description", None), + "image_prompt": getattr(c, "image_prompt", None), + "voice_description": getattr(c, "voice_description", None), + "media_id": getattr(c, "media_id", None), + "reference_image_url": getattr(c, "reference_image_url", None), + } + if entity_type == "character": + chars_list.append(entry) + elif entity_type == "location": + locs_list.append(entry) + else: + props_list.append(entry) + + videos = await repo.list_videos(pid) + existing_eps_by_vid = {ep.get("video_id"): ep for ep in existing.get("episodes", []) if "video_id" in ep} + episodes = [] + for idx, v in enumerate(videos, 1): + scenes = await repo.list_scenes(v.id) + old_ep = existing_eps_by_vid.get(v.id, {}) + episodes.append({ + "episode": getattr(v, "display_order", idx) or idx, + "title": getattr(v, "title", None) or old_ep.get("title") or f"Episode {idx}", + "subtitle": getattr(v, "description", "") or old_ep.get("subtitle", ""), + "video_id": v.id, + "scene_count": len(scenes) if scenes else 0, + "status": getattr(v, "status", "IN_PROGRESS"), + }) + + first_vid = videos[0] if videos else None + orientation = (getattr(first_vid, "orientation", None) if first_vid else None) or existing.get("orientation", "HORIZONTAL") + material_val = getattr(project, "material", None) or (project.get("material") if isinstance(project, dict) else "") or existing.get("material", "realistic") + story_val = getattr(project, "story", None) or (project.get("story") if isinstance(project, dict) else "") or existing.get("story_bible", "") + + manifest = { + "series_title": existing.get("series_title") or project_name, + "slug": slug, + "genre": existing.get("genre", "Cinematic / Realistic"), + "material": material_val, + "orientation": orientation, + "story_bible": story_val, + "default_voice": existing.get("default_voice", "vi-VN-NamMinhNeural"), + "origin_project_id": pid, + "shared_entities": { + "characters": chars_list, + "locations": locs_list, + "key_props": props_list, + }, + "episodes": episodes, + "updated_at": datetime.now(timezone.utc).isoformat(), + } + + manifest_path.write_text(json.dumps(manifest, indent=2, ensure_ascii=False), encoding="utf-8") + return manifest + + @router.get("/{pid}/output-dir") async def get_output_dir(pid: str): - """Get or create project output directory with meta.json.""" + """Get or create project output directory with meta.json and series_manifest.json.""" repo = _get_repo() project = await repo.get_project(pid) if not project: @@ -341,7 +420,30 @@ async def get_output_dir(pid: str): meta["created_at"] = existing.get("created_at", now) meta_path.write_text(json.dumps(meta, indent=2, ensure_ascii=False), encoding="utf-8") - return {"slug": slug, "path": f"output/{slug}", "meta": meta} + # Automatically generate or update per-project series_manifest.json + manifest = await _build_or_update_series_manifest(repo, project, slug, output_dir) + + return { + "slug": slug, + "path": f"output/{slug}", + "meta": meta, + "manifest_path": f"output/{slug}/series_manifest.json" + } + + +@router.get("/{pid}/manifest") +async def get_project_manifest(pid: str): + """Retrieve or auto-generate the project's series_manifest.json.""" + repo = _get_repo() + project = await repo.get_project(pid) + if not project: + raise HTTPException(404, "Project not found") + project_name = getattr(project, "name", None) or (project.get("name") if isinstance(project, dict) else "") + slug = slugify(project_name) + output_dir = BASE_DIR / "output" / slug + output_dir.mkdir(parents=True, exist_ok=True) + return await _build_or_update_series_manifest(repo, project, slug, output_dir) + _ASPECT_RATIO_MAP = { diff --git a/agent/db/crud.py b/agent/db/crud.py index 00184fc8..43e286c9 100644 --- a/agent/db/crud.py +++ b/agent/db/crud.py @@ -256,6 +256,7 @@ async def create_request(req_type: str, orientation: str = None, return await _get_with_db(db, "request", "id", rid) async def get_request(rid: str): return await _get("request", "id", rid) +async def get_request_by_operation_id(op_id: str): return await _get("request", "request_id", op_id) async def update_request(rid: str, **kw): return await _update("request", "id", rid, **kw) async def list_requests(scene_id: str = None, status: str = None, diff --git a/agent/main.py b/agent/main.py index c0722a15..6cbb2e4b 100644 --- a/agent/main.py +++ b/agent/main.py @@ -271,6 +271,39 @@ async def ext_test_project_media(): } +@app.get("/api/ext/test-op") +async def ext_test_op(op: str): + """Fetch raw operation status for an operation ID.""" + client = get_flow_client() + if not client.connected: + from fastapi import HTTPException + raise HTTPException(503, "Extension not connected") + from agent.services import flow_batch as fb + res = await client.batch_rpc(fb.RPC_OPERATION, fb.operation_request(op)) + return res + + +@app.get("/api/ext/test-op-match") +async def ext_test_op_match(op: str): + """Test matching an operation in project media listing.""" + client = get_flow_client() + if not client.connected: + from fastapi import HTTPException + raise HTTPException(503, "Extension not connected") + from agent.services import flow_batch as fb + pid = "594758cc-11f5-4f92-8b3c-1213686591f4" + res = await client.batch_rpc(fb.RPC_PROJECT_MEDIA, fb.project_media_request(pid), match=op) + raw = res.get("data", "") + found_mid = fb.find_media_id_in_text(raw, op) + return { + "status": res.get("status"), + "error": res.get("error"), + "raw_len": len(raw), + "raw": raw, + "found_mid": found_mid, + } + + @app.get("/api/ext/media-url") async def ext_media_url(media_id: str): """Fetch signed media URLs for a media_id.""" diff --git a/agent/sdk/services/flow_provider.py b/agent/sdk/services/flow_provider.py index 60cc25db..e4e7336d 100644 --- a/agent/sdk/services/flow_provider.py +++ b/agent/sdk/services/flow_provider.py @@ -59,6 +59,16 @@ def _omni_duration(requested) -> int: logger = logging.getLogger(__name__) +async def _remember_op(client, op_name: str | None, pid: str | None) -> None: + if not client or not op_name or not pid: + return + fn = getattr(client, "_remember_operation", None) + if callable(fn): + res = fn(op_name, pid) + if asyncio.iscoroutine(res): + await res + + def _save_raw_bytes( operations: list[dict], scene_id: str, project_slug: str, display_order: int ) -> str | None: @@ -394,6 +404,8 @@ async def _run_video(self, job: ProviderJob) -> dict: # would abandon a running render and pay for a second one. if existing_op: logger.info("Video gen already submitted (op=%s), re-polling", existing_op[:30]) + pid = ex.get("project_id") or (req_row.get("project_id") if req_row else None) + await _remember_op(self._client, existing_op, pid) operations = [{"operation": {"name": existing_op}, "status": "MEDIA_GENERATION_STATUS_PENDING"}] return await _poll_operations(self._client, operations) @@ -438,6 +450,7 @@ async def _run_video(self, job: ProviderJob) -> dict: return {"error": "Video gen returned no operations"} op_name = operations[0].get("operation", {}).get("name", "") + await _remember_op(self._client, op_name, ex.get("project_id")) if request_id: await crud.update_request(request_id, request_id=op_name) @@ -468,6 +481,8 @@ async def _run_video_refs(self, job: ProviderJob) -> dict: if existing_op: logger.info("R2V already submitted (op=%s), re-polling", existing_op[:30]) + pid = ex.get("project_id") or (req_row.get("project_id") if req_row else None) + await _remember_op(self._client, existing_op, pid) operations = [{"operation": {"name": existing_op}, "status": "MEDIA_GENERATION_STATUS_PENDING"}] return await _poll_operations(self._client, operations) @@ -488,6 +503,7 @@ async def _run_video_refs(self, job: ProviderJob) -> dict: return {"error": "R2V returned no operations"} op_name = operations[0].get("operation", {}).get("name", "") + await _remember_op(self._client, op_name, ex.get("project_id")) if request_id: await crud.update_request(request_id, request_id=op_name) diff --git a/agent/services/flow_batch.py b/agent/services/flow_batch.py index 0e148562..1262966d 100644 --- a/agent/services/flow_batch.py +++ b/agent/services/flow_batch.py @@ -752,8 +752,8 @@ def find_media_id_in_text(text: str, operation_id: str) -> Optional[str]: start = lower_text.find(lower_op) if start == -1: return None - # Search within window of match - window_start = max(0, start - 400) + # Search within window of match (from operation start onwards to avoid matching previous items) + window_start = start window_end = min(len(text), start + 800) match = _MEDIA_SLOT.search(text, window_start, window_end) return match.group(1) if match else None diff --git a/agent/services/flow_client.py b/agent/services/flow_client.py index cb90e7df..e16e11ab 100644 --- a/agent/services/flow_client.py +++ b/agent/services/flow_client.py @@ -987,6 +987,15 @@ async def _find_operation_media(self, operation_id: str) -> tuple[str | None, st self._operation_polls[operation_id] = rounds project_id = self._operation_projects.get(operation_id) or FLOW_PROJECT_ID + if not project_id: + try: + from agent.db import crud + req = await crud.get_request_by_operation_id(operation_id) + if req and req.get("project_id"): + project_id = req["project_id"] + self._remember_operation(operation_id, project_id) + except Exception: + pass complaint = None worth_looking = rounds % 3 == 0 try: diff --git a/agent/worker/processor.py b/agent/worker/processor.py index e128df37..1acf65ba 100644 --- a/agent/worker/processor.py +++ b/agent/worker/processor.py @@ -481,12 +481,12 @@ async def _handle_failure(rid: str, req: dict, result: dict, retry_after: dict = if isinstance(error_msg, dict): error_msg = json.dumps(error_msg)[:200] - # Auto-recover expired media by re-uploading - if "not found" in str(error_msg).lower(): + # Auto-recover expired media by re-uploading (only on real entity-not-found, never on polling timeout) + if "not found" in str(error_msg).lower() and "polling timeout" not in str(error_msg).lower(): recovered = await _recover_entity_not_found(req) if recovered: logger.info("Request %s: recovered expired media, retrying", rid[:8]) - await crud.update_request(rid, status="PENDING", error_message=f"recovered: {error_msg}") + await crud.update_request(rid, status="PENDING", request_id=None, error_message=f"recovered: {error_msg}") return error_lower = str(error_msg).lower() diff --git a/extension/background.js b/extension/background.js index 8f4a261e..df0c5f9c 100644 --- a/extension/background.js +++ b/extension/background.js @@ -375,6 +375,11 @@ function connectToAgent() { bl: wiz.cfb2h, hasGrecaptcha: !!window.grecaptcha?.enterprise?.execute, executeString: window.grecaptcha?.enterprise?.execute?.toString(), + hasHijack: !!window.__fk_hijack, + hijackPristine: typeof window.__fk_hijack?.pristine, + hijackTrapped: !!window.__fk_hijack?.trapped, + hijackSource: window.__fk_hijack?.source, + grecaptchaClients: Object.keys(window.___grecaptcha_cfg?.clients || {}), promptElements: Array.from(document.querySelectorAll('textarea, [contenteditable="true"], [role="textbox"]')) .map(el => ({ tag: el.tagName, id: el.id, className: el.className, placeholder: el.placeholder || el.getAttribute('aria-label') || el.getAttribute('placeholder') })), editorContent: document.querySelector('.ProseMirror')?.innerText || '', @@ -607,8 +612,8 @@ async function solveCaptcha(requestId, captchaAction) { } // Try each Flow tab in turn. A tab that answers "no grecaptcha" is a tab - // sitting on a page that never loaded it — another Flow tab may well be - // fine. Returning on the first one let one stale tab veto every generation. + // Try project tabs first (they have the full toolchain and recaptcha context loaded) + tabs.sort((a, b) => ((b.url && b.url.includes('/project/')) ? 1 : 0) - ((a.url && a.url.includes('/project/')) ? 1 : 0)); const errors = []; for (const candidate of tabs) { const tab = await reviveTabIfNeeded(candidate); @@ -689,6 +694,7 @@ const MAX_RPC_TEXT = 32000000; // the project listing alone is past 17 MB async function runBatchRpc(cmd) { const tabs = await chrome.tabs.query({ url: flowUrls }); let candidate = + tabs.find((t) => t.url && t.url.includes('/project/') && !t.discarded) || tabs.find((t) => t.active && !t.discarded) || tabs.find((t) => !t.discarded) || tabs[0]; diff --git a/scratch/captured_netlog.jsonl b/scratch/captured_netlog.jsonl deleted file mode 100644 index 85715337..00000000 --- a/scratch/captured_netlog.jsonl +++ /dev/null @@ -1,321 +0,0 @@ -{"ts": "2026-09-23T13:16:52.291Z", "url": "https://flow.google.com/_/AiSandboxAngularFrontend/data/batchexecute?rpcids=Zzl0ze&source-path=%2Fproject%2F594758cc-11f5-4f92-8b3c-1213686591f4&bl=boq_labs-ai-sandbox-frontend_20260922.00_p0&f.sid=6833755015842157859&hl=vi&_reqid=281899&rt=c", "method": "POST", "body": "{\"at\":[\"AIQ-s5jEGkBwmXOrigHYujR0_cSl:1790168749588\"],\"f.req\":[\"[[[\\\"Zzl0ze\\\",\\\"[\\\\\\\"projects/594758cc-11f5-4f92-8b3c-1213686591f4\\\\\\\",null,null,null,[1]]\\\",null,\\\"generic\\\"]]]\"]}", "statusCode": 200} -{"ts": "2026-09-23T13:17:05.413Z", "url": "https://flow.google.com/_/AiSandboxAngularFrontend/data/batchexecute?rpcids=ogiZ0b&source-path=%2Fproject%2F594758cc-11f5-4f92-8b3c-1213686591f4&bl=boq_labs-ai-sandbox-frontend_20260922.00_p0&f.sid=6833755015842157859&hl=vi&_reqid=826921&rt=c", "method": "POST", "body": "{\"at\":[\"AIQ-s5jEGkBwmXOrigHYujR0_cSl:1790168749588\"],\"f.req\":[\"[[[\\\"ogiZ0b\\\",\\\"[null,[[null,null,null,733647544,3,\\\\\\\"GEM_PIX_2\\\\\\\",null,[null,22,null,null,null,\\\\\\\"594758cc-11f5-4f92-8b3c-1213686591f4\\\\\\\",null,null,null,null,[\\\\\\\"0cAFcWeA5MPg8cTqBq2xeiEK_4oNLK1jZnsUckrwa1t4j1ZGVfgPOC5hIcFD3EMddxnfrhVFHTv9uKf4EKq3uAEHT2r3B3hY0FOwpbMvBDOHk30qQbz-nactrTEWIFDmBAqlUQ8VZ9m7FSGhHmRbKNNUkB3Y0tHRL1lEZGGkILJ9EgGjB7Y1u9h3O8No1vWM8BrY7J7f0f-rhjn-8UU_QvW3i_rn30cNYqumup-k8rPoOgVQY5pKpZXcQL5pP6YSBkZWL6D965aCcVvOmGKnVMUCV5L-4cS873cdEVm-AcwhDzaeZuYkKgpWjGaJ9V2dodPZlHXhbe47E5C1y8d1Br5Z29pZkyI1H8cQk13FryCsuNwyhEusneAmDIM8ghOzqjTckDRQfAZIAt6lPaHDmrrePCIBrQWXqvChE26Zz-Y7ZrGxeNUn3wnbo3XSss0b1Hdsq5GNv5fLr25AJ-2Jvri0UVd_pAWssJksY6cd-8WWG2msnt39uOtct2FAPA3S9YA5kF7PMZm8QfiaJ00AF3mHIvv-cZHcNSmPtpBY9lZP12RFUcrdcIosyENe37vqI0680oJL-x4VUJqw4MZu1ASdycwa5JLbBt7YC1v400rkFRSZYXUyCXxhCRHrK-fEl3CLDSTWaGPW8jKEo_aLVCQ9rjpKMrVb_SRsftv2SzSylYZpOWHykX4Cydt5daVYCS4c21BFMOpPfLGpN8O4QenFxrEpV67BuR3mQrSKdaNJ0yETRI2uhApjbcXkWEmK75uDolzvk4HvJMRdqbt_x3yqs_8KvB0ASbQcMfiRbahjSXJF0HMBpCMkLVY0bU7PtBVDkbZy7-169vkRZnCoe003-xMR8JPrIiijg-PNe_gEkzVHvwS9eybEjQetRfOal2R-cbnpJe3fWdbd-E8XFqkT-tCTR4R4Fh1FmC1kGVRPFzSq_2dInSlUsReqJEGb9wZoalRD_aa19mJF2FilfEMqJUfEBS_DN32lr25_FjsBqtWShrJQVU8YcO1ai8tnLez8cUZJ-FRRFZa7Uf6gJVFsRQ_cdFi-ZM6i9okJjzbLA-wlQry74ZBPe3SKA1Z3QKeT-t5FLNuIVnMjiE6rMIPhkRw_tdxNRLHQPafbJRDPuiCzmNS5YRczrTMGvcRwPVeok1-lxV-yt8R4oVo-MVnZOSGM9wB8TQ4-YfUdvSh0b34tDrPGumi_9PBL6Gn8-Tweby_WRUzOwmAN62v5AIHOq2lGvn1TpUXy7hc9RPK2O70Xy1umOZgY4qpkyjnL-eVm8r1ZYuMyCQmgS4eFwEHlOBP4ePlI4lPCo1g03i38mDU3XjZjZD0Ub0y96dwZrEikeo-3yBvMJI3KGCHhT28bQPV9GPqd-OL96QMYq5UaGZFbQao7Hqq9Qd_1b7QbV-xqhInNHWv5df7QozHgLZA5ZMtcyLPT6PFTFDAhuzMUDKkuS4T_rZbsaQzKxi7hJzQsMDa1z4ZhtsqsoPRIU2NjZSEWmGUC6HgqFeBEAxtYsOvdQFJMg9mSrjyZzD6IX4aKXIJ-jEBiJSAmDhH2i53sCRmmDAM-f9qOLpccS45LuKT-Y1wtj7I5zRRV09J4tOOoyQpa3Rt7G4g1gezlSkQRejRuE5ds67tUQ2JZyyQnqOszxidxKmFnB6v5q0jvdSgWsejRmUKkJW6dnggt4eeRoejI_5SZelXySVsIxrzWlV_1GO9etcjAsjhOBMyJhhhUWRtMECpfwSHSLBSDtRBO4iVw5p8Gz5Hl8eGgIpELDQlVryq8T1Kc7qWqTrSvJ1cnM8qj6cfuTfc34TFH2q6A2E1mPe6-g9xYYEiv1zp1bofVsmYZQYKZiaRm03LMD2yWSf8-mbGtPi-VZu6oViaYkHfoPq_Sudc96pKriTm7X6fTWhNP0Oqeq-Id5z_hXaHMDJWY8ga8nXybwfTQWEl-qQtHDAtNOqNgW2kGxhHa94Dgg2VRRzOuXJrl82pnuYhGlTRb0w_JXmrcg8RIyWQCVONTstupDngNEV4ylP7gOk9KmumsMbV89roJyju3OclKxIsSNQv1RKjKXbeC6wBw3uAdqiK88xZ7LnuF_czNFJZzOlh2057r2n4nch9qEUz2c2XlKOSDhKoY6p2vdX50viRbDc9BmXCvqKk91G6nyTJU2WYAhAQeVyR9VrHWptruCCXo9KuRfEjTykvmxDN4k8lcOqH21fO5iYrOO7zczBRopPp_fQO7J6N3XFBfZ5QIeJHfOUEjZPOKiGhBO3Q79XYsek3HS7TFsBCSuSUlWnLkVSQhP4f4mWU_ueS5WfAg9Di9yyBgw0-B-ILb-_FBG1yFnbimLeuAFq-zW-_2LFgQRjtJlAJtSgf6y0BvNvZmYtP-1avLnJTjnc8uSADBObmfnUtwkQtqRVuxAjjIGVcNBFHYfLr-zHEmnHQvo4OY7KXKhL-P08cwKDMl9L4Ap7ms4iVLPGSHQRRdeEKGjVBOFbYFVORSMslT-7LvhmR6G58kNhjm_n\\\\\\\",1]],[[[\\\\\\\"Real RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. 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Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted 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RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot in subterranean B3 basement parking at Me Tri under extreme heat. Le Quoc Tien lies on scorched concrete floor full of deep heat fractures, clutching a bleeding abdominal wound beside a torn empty water pouch and heat-warped debris. In the background, Do Minh Kha stands looming with a cold detached gaze, holding a tactical combat knife, backlit by an ominous beam of deep crimson sunlight piercing through a jagged collapsed ceiling fissure. 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Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted 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RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot in subterranean B3 basement parking at Me Tri under extreme heat. Le Quoc Tien lies on scorched concrete floor full of deep heat fractures, clutching a bleeding abdominal wound beside a torn empty water pouch and heat-warped debris. In the background, Do Minh Kha stands looming with a cold detached gaze, holding a tactical combat knife, backlit by an ominous beam of deep crimson sunlight piercing through a jagged collapsed ceiling fissure. Chiaroscuro high contrast lighting, floating soot embers, atmospheric heat distortion waves, 35mm RAW 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Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted 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"statusCode": 200} -{"ts": "2026-09-23T13:18:57.172Z", "url": "https://flow.google.com/_/AiSandboxAngularFrontend/data/batchexecute?rpcids=ogiZ0b&source-path=%2Fproject%2F594758cc-11f5-4f92-8b3c-1213686591f4&bl=boq_labs-ai-sandbox-frontend_20260922.00_p0&f.sid=6833755015842157859&hl=vi&_reqid=422769&rt=c", "method": "POST", "body": 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RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot in subterranean B3 basement parking at Me Tri under extreme heat. Le Quoc Tien lies on scorched concrete floor full of deep heat fractures, clutching a bleeding abdominal wound beside a torn empty water pouch and heat-warped debris. In the background, Do Minh Kha stands looming with a cold detached gaze, holding a tactical combat knife, backlit by an ominous beam of deep crimson sunlight piercing through a jagged collapsed ceiling fissure. 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Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted 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RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot in subterranean B3 basement parking at Me Tri under extreme heat. Le Quoc Tien lies on scorched concrete floor full of deep heat fractures, clutching a bleeding abdominal wound beside a torn empty water pouch and heat-warped debris. In the background, Do Minh Kha stands looming with a cold detached gaze, holding a tactical combat knife, backlit by an ominous beam of deep crimson sunlight piercing through a jagged collapsed ceiling fissure. 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Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted 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RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot in subterranean B3 basement parking at Me Tri under extreme heat. Le Quoc Tien lies on scorched concrete floor full of deep heat fractures, clutching a bleeding abdominal wound beside a torn empty water pouch and heat-warped debris. In the background, Do Minh Kha stands looming with a cold detached gaze, holding a tactical combat knife, backlit by an ominous beam of deep crimson sunlight piercing through a jagged collapsed ceiling fissure. 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Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. 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Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted hands.\\\\\\\"]]]],\\\\\\\"veo_3_1_i2v_lite\\\\\\\",2,null,[null,\\\\\\\"538cd93f-52d5-4c9e-9924-7a66b8dd016f\\\\\\\",null,null,null,[null,0.0038759689922481244,1,0.9961240310077519]],[null,null,null,null,\\\\\\\"D887BB95-D45F-4884-8BDC-E3F44D68FFA5\\\\\\\",\\\\\\\"DCDA3CF1-DF42-4053-AE48-E7A7054E9DBF\\\\\\\"]]],[null,22,null,null,null,\\\\\\\"594758cc-11f5-4f92-8b3c-1213686591f4\\\\\\\",null,null,null,null,[\\\\\\\"0cAFcWeA7YK9uBA14Mnal5eZS5AIVpD4X6oOQpQ4z3H3bUdOh2UcJwS91qBOVhg6Gz7MXG2F483Ha8-z-a6ygTvpvgORnPO8UB7Z7ZKFQQgNLgJECGOz3xzEh2jKYRF6QZNxik9DuiNT2dNZze2nu1KtAhO-Nqbyt02VckJhSu3HUm7o1E3sXShz9TpikEx-NkpSZfqXSA7KKn3nS57orzeT7IaOVkHpkQAhWu1O-IVxvDADb1GBXSSvRd0xMBM8eVhpef0R4Hxwb0B_yYFjTYaXMXbinNGewUzqkLtIkNcsAB5nX_dZ58Yg-WYJebHgzUQIkVGvA98Wt-OUatfr3vEERciAkzlK7LuHqBMsZArpLvyewP3G-QeIDnN0Hc_SrXjpvraYayISWTPnz1AQvdxAgcVgP-F70ky6Ot6T4Lv3AX6bslusk6B04UJFlvYhzphX69I68cWEJCQ0KM-ehnnANS6z9idQ5ZrRUlEYDeD9N0xNm82U8vS4M2StyaXSHdgb_IssGkLMMkYIVZ-5jYe08m7p5cBu3PMu34AxigGVSmEaFVcS9hxB4flX-q7pVH7OtdQTCNoYLJGXV2P4wUTx32n6_30qk9P8B2MflnNLmgXt6xi68UNbLZ7p3Gqap_zmb2GkA_CryP0GQ7rhBvSUogha15Y6Syz4pSuuH7aUMtJuF_1P7iy3T3CdeIYHbbPBGxPkZpCuCTriVha1u2xol74plrszWp7Po6ESXfbdjd0UU4AGbYgq10UKxl2XGuECT72oIkR4wt7x37JITOQyw9qHGgCCB9sjZmCZkPSI92ErmzWfibUbuuTy020Y-uYf88YjgdYDbGX_Jbk1ajkbtJTy1iv339tmVDk0RpHykwk4o5Mjg43tRrUQ2Q_r4LC2h5LilehZHg8NnEP-IJZUuF0plLWkHizlUtzKPt7OFFsEgG41brsZhsZ_ActBKXGsoDIXFihj00VfSjHl21uDCgwalKmq-tOHurLzW2dIuzEFOLSzcYJ09T166N0FVyuE7Yow91PO2exZ6Iq5krSRLSJO-tgp5x4Q4L2E_ho4s5Kkkn2Aids50DgV_Q3RrHdm-RW-LNwh7k965nBPEJGJGsKoq29pQW7Iw7ZYlJyi_1UgfIP4H0WQPmirfxYAoaIwMLWb0j3sVXIpvPhul-i9iYrlG-X4N5pqdcCnhqH1aHXwOpx1KrWa3fTLSLHw58-u0aNh_KU0SpUajB-R64OsQ1wkU6PGiejL85yfKTbKP6R1dImPQJBvYzLluDWPVuomF1l32tP6PNuToL0_TrrOSqTpH8xL9YSKQtWWiDvwLCJMCZ_8s-eILB5t2C_GFlDji4nyhkX8EISwO-gFj82MMBzihq49r-oUCrjMBsIhX9MKcWqhpfqsOt0GnLFcUBAxZ1TPDDpvQpK876MFWKYdNyWDz9SmjnwmwzGioU84H7EizAF7nMzpmprqE-nCfFV7D-RDQHNT1kWEb7Y848vUBNyut8sisAwgaxh2booc1cxuwThkd8hV87u3154zmjtXPUNpUie56rQTvzreGrL5EZDmoXOEGqSCyBHKlA9Vhj1f67oRzKzr2HPX_Xr2VRe4OPM4NIB068DQF2vJCzupg_HY95Vx9FKZussBrZk0u-67SzVf_qUn7pti75L_hLMZerK5PQPqGqD2ZhloQc-LsXp8bwfkPt11F5UnQM-jLWmWowvP_wCqBxGq2sdJQjSZjDLxvxpFsjKfEWh8y49YjzIXj1Q-HBaTRN2xRLyDgI0V45cKELI6OCH6AwgFMSMn6LoJyiThmZ9e0mcWHv12irgzBp8Khw0gXt-Jv7ZiRIom2_LXPfcqSwhFrY-fnX9uddVcqUr5v9ZUhUJu-jIE82Egj-8J8PQm7HwUjs14zZwY5AXeyFv7puYmocIg7urLLdBcig5s9P6TamZbBrt403lfF-g9gIRAYH5kyBaUaSBKodhwnIlcqU4BnUZNeVaXirewsKL8nfdt8qVf_iuqzkiupL_edBDYyN4JL7bfeAxlL4NL8KHt8TR9ncl4DxoG0MFSafoYmPyjrPV-N5GKmlhw6oW2spjLtdKyORnQIpjEK1VCnA2FrAUNvvet7vmq9pP1csbdXQJ7BXB7WNA69sHRyEZ1Gz8JjMatwUcEEdyQr00AE9K6hGuVLeAmJw6XDLBPu91wFozQrKE_mf6xLJY5FfL57vPTIeYsikZSxvCaSbHHowGhsVMYX6HBYX8eYy68WxEmGGv_AE-Hq_7ETq5-0_RwJrvLqqJ1kTaUoCrxRmqhulRknxa51Qj2JV2c9_WzYDBfCB9_8pakdKnWIQeEKd-xN81TBNFzf1R7QWu3jJQx4ZPhf89UHki4TVaRtdpTiIKt3LAv8dE5udV9Umn6h4kkwUrLJ4hARr3P0S0CwNl0hS8_M8hfWCZMgRX0E4GzHksMbTGvMIsrkby650FO0qTiiKAcLlQzW-N80sNN_WTWtFzfg\\\\\\\",1]],[\\\\\\\"70E19F8A-5A62-4550-93A4-3FC3CE123516\\\\\\\",2]]\\\",null,\\\"generic\\\"]]]\"]}", "statusCode": 200} -{"ts": "2026-09-23T13:20:17.231Z", "url": "https://flow.google.com/_/AiSandboxAngularFrontend/data/batchexecute?rpcids=eb1hJf&source-path=%2Fproject%2F594758cc-11f5-4f92-8b3c-1213686591f4&bl=boq_labs-ai-sandbox-frontend_20260922.00_p0&f.sid=6833755015842157859&hl=vi&_reqid=125855&rt=c", "method": "POST", "body": "{\"at\":[\"AIQ-s5jEGkBwmXOrigHYujR0_cSl:1790168749588\"],\"f.req\":[\"[[[\\\"eb1hJf\\\",\\\"[[[[null,null,[[[\\\\\\\"0-3s: Close-up on Le Quoc Tien chest heaving as he gasps for air, jolting upright in sheer shock. 3-6s: His trembling hand grasps the smartphone, screen glowing with the date 09/05/2028. 6-8s: Camera tracks smoothly to the window showing peaceful golden morning sunlight. Character voices: Le Quoc Tien: Calm, firm, determined Vietnamese male voice with deep analytical cadence. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted hands.\\\\\\\"]]]],\\\\\\\"veo_3_1_i2v_lite\\\\\\\",2,null,[null,\\\\\\\"538cd93f-52d5-4c9e-9924-7a66b8dd016f\\\\\\\",null,null,null,[null,0.0038759689922481244,1,0.9961240310077519]],[null,null,null,null,\\\\\\\"2374E839-F2E9-4C58-A0F6-C2F0F42BB101\\\\\\\",\\\\\\\"FACFBD7D-6077-4154-B91B-DA74EE8A8D78\\\\\\\"]]],[null,22,null,null,null,\\\\\\\"594758cc-11f5-4f92-8b3c-1213686591f4\\\\\\\",null,null,null,null,[\\\\\\\"0cAFcWeA7OXK784tTnLFqRwKd-SLXdWZh8M_pOFA1Pl1Ygc_2WL5hg2oq8jEKnTSZ9pKqd23jcdmq9NWMKaXhCNx-tIzlxG1uQKyQPLaLFlXH-N_Y_-SCRILalM3M1ToaYKhd8Z3ePO05iluVjXzQ1hTay23C8K62I4pF-n-8R0k82ZYoCl5_tJ_WBdJ_OK65SGtF4QoUMOUMANbWdk2Ab96Bo_DcK3eEqHMVjywAly0A9QaV46rVH73oyQqkqnIS1iFnPC6EzbQ78e5manTvRsmretDVNIURe0-_bhCvsd6a2MaH2hWsapURyNC6FFHwSfActrOgahZYMU88kZSi9kzCPgepbw7K0ysvi3m_Ya4vyE2maAQEYtYFewtLTSSCgfpyyhWdswylRxydOqe1Yk87JPuQiFOlHEiiqpON9v_WR__--5TeFheMm8kvDWzG8FCWpfYVXk_M4DWH2EaJfeROd-nfDwwX62eYZe0qppl2pRNJ7wj0cXpV-Omd8dfeymMJJWoCEdSFJhfxZcearv1y84cy2L2Na-HX8WUL7yZfarXAt92-MDa1RiRGhn62sTs7I-y-NDIjxosNsJ_ytDwJo2in9KX3MGx7luHneWgNEeO08LWXhdGoK7Y5dABaf17WSjktzEEDBS1x5oeneMq3rggbZTtTS7gUb6SHE6H6luK0uwE26kfeFJZXu9tO0XP_97VY2DP0lYqtDjLlr_Cle98dd6GV7mMd16JyRbLXpuG_6EoYvBzi3_Gc3AqQ3qWp5rxG5slqQFfq2ptSZzeuwtwFLY43-fg_JkYj8iYV94r-XAldMeS1Qa_fRCrfe5D7Rv4KoY8l_9rMkTL5VWRovN4Lr7IaMdZHFvFgStEX75xRYu5pfo3JL9AqkJNAB3zjEA97WIyB5UbLcF1LuPUrtpzo_KgMSiHcJ6qg92OVaVnNTXU1SC9-Jv2HAVN6eQpy0sXl4RJUqVm20YzJH8tAxvJ8XvLbxoDgquM_gJ0-EE43sIKi_Hsp1ePJVvzErs4KaQrklBbo-EpADzGK7rkYjTCSjNMBd99yE4YqIPMVCrNwwIqwaU5ums73Cf_1GQxAWJIxV74xka7FEazpqXzjmXFpyvnxMeMqv3I9FaT29N3-JSgBhvA9yrNW1NNjmJRuCyMeOEjWNw_dQljidgxHOTiW_HdLrJhYybtYrIwDbiAFZJcWbHY7QxgzdNxcnrs7wRg3vxsu5xwh9O5OXEe2shFtd1bpurBJZ_drcukAIkoQRTKsFKOSbfw8ezsQKYdQu-ayK3-H_E2NQsQYS5CXkgKPbQEhU96pgoHvXklIz4y_b0oa3cbNxVuR8X6rcRj0D_XPRzQw_3LMInrOAXfW2aCXTS-Y85jEaPdkeHsrGvuR-v_NG95ie4QOOhSA1ge6h4IsnPn4ZC60siU8WZqLaYfKlKSnxfELI3Hr3BvmBFJinxE8sZ9ArJWgjv0Sn2bd_0cvK0L9nVN7Cq-XFkapy78iHyyDDY1u4I45PM6ZQTBfMLbNmG8zxGpp0BPv79l8NWLQcuF2rxLi52Y2HwjHxg8wAjBs4ybqXJtyY4eKOb5Fe_JgK41nQ3IbGmIdGFLA5xIfHWQd2-IPRfAGb-nq1hqTEL2sJ_VIQid63xhdOsDZYKxu20bCQ7j0PDtWDszNZrFfwkHwnGmMh_o9HKHMU5_GvIbQQB0joxdn6gZBwxLas5Ruy6QPC_DIir68fEvmOC-esHw3V0BbgZ5yWX0Asn11RWpG6Aolr5VntZ2fvjsp9egSgd3jGa8U6P7XB51YNwVlplcv7vJAtRDc2-SL8ID49AV-6AzCIkf5HUEQ3R0ROz4eQGSSu9C-MNT2HMLPAKJkLXl53mjDDoofr-acM-VBeTAAPVUsMqpDos70alY9i1zvaFnuRGWnpYbYOe5aHtMJsE31thS35c0_JEaNt5lvD6_JdkhHM8fesrtcGPDPMEMIm38ufMnx_o5dYT2buIw-Am8WmoZYVbpVqelYq-aNNYVoQfoAj8pbmeSY0JDCIZfrL7FSbVDvvvKPv0uSN066M1U89Vm3y7sv3lpMHQuG9kExeqwvtuhHMP_J2ufH-dAb-zHQZzbNQbx55dcBUlq3qZR8xZxLmOcoGdkRBzhumn4EyNdeSkFOQUn3O5WJ8djnpWq4DZblwXt5gqEWS6tn5k0Ik5r0Lr17_oZm3-7JlmZP9pCqyXHtDnFCYhXs06BrLA-7wSwLkZ7TGU-QbiCM9eqf84r8742cBQWiTLjvbsPi5nEbPM6fRpA6xYLgkjVHRpT41U8q8q_Gsb1EqGBlsfaushPYw4Rm3o4wkeOLxWk7R0Fw80Aqkq69atkiKapyhtnPwtJVrGqqg7A0_8_K6Slewo5XjFnhqMC3DwPcGLm5AalASXBiXHOm24_WAYL-A1dqM37NGmzfL-dB1j-nEsA46L4i4HGSXn32RfD7Wbm8XF1BrQN9faJbAcyQWWQ5Nzes\\\\\\\",1]],[\\\\\\\"C882DC7E-FF63-4CA0-96BA-069022F8B1DA\\\\\\\",2]]\\\",null,\\\"generic\\\"]]]\"]}", "statusCode": 200} -{"ts": "2026-09-23T13:20:27.303Z", "url": "https://flow.google.com/_/AiSandboxAngularFrontend/data/batchexecute?rpcids=eb1hJf&source-path=%2Fproject%2F594758cc-11f5-4f92-8b3c-1213686591f4&bl=boq_labs-ai-sandbox-frontend_20260922.00_p0&f.sid=6833755015842157859&hl=vi&_reqid=195153&rt=c", "method": "POST", "body": "{\"at\":[\"AIQ-s5jEGkBwmXOrigHYujR0_cSl:1790168749588\"],\"f.req\":[\"[[[\\\"eb1hJf\\\",\\\"[[[[null,null,[[[\\\\\\\"0-3s: Close-up on Le Quoc Tien chest heaving as he gasps for air, jolting upright in sheer shock. 3-6s: His trembling hand grasps the smartphone, screen glowing with the date 09/05/2028. 6-8s: Camera tracks smoothly to the window showing peaceful golden morning sunlight. 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Chiaroscuro high contrast lighting, floating soot embers, atmospheric heat distortion waves, 35mm RAW photograph.\",25,\"\",null,\"482b99b0-f4ee-40f9-a31b-c4f76ddd2af7\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUbv96PVxcN2PbifMQLbnfBljuWf4Xiu5nDiPGArpO0tyJYXHdrObt1q-0gOdtpRBQDoTJoVFo676vQBLUKK7WbuzryMkfcJSs9xB7ZWWKW8qfp2Nxu4OrbxkHjMCKlHYF_0t5UqhdHWoG3gINiTcdb13Wsssk-KF_FjORBFaQ\",3],null,[1376,768]]],[\"279b944e-5348-4ecc-91d4-f356b9271132\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"7212e0d2-229b-4032-95e3-4c363d2b46c4\",\"CAQ\",null,[[1790105556,47573000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUZvnfLi4e_wIQIorBBWTJ68UhPPAGCGyMM1bGCslA4p0p3FPmZaErkcCJYOWZAU45AtW9O6ltyL0rvw2djSHFrWD5qQSNo0YvIoExryJLJri_WXrIastNeDraPmM1lNKPSF3KgOHu71rkSRSh_Dczg-c1R657r9-mQNa93KkQ\",[null,null,[[\"deep cut-out top, revealing cleavage\",null,[[[\"áo khoét sâu, lộ ngực\"]]]]],[[[null,2,\"cea6d7a9-29a2-4b36-aa89-60358b4998b5\"]]],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUZvnfLi4e_wIQIorBBWTJ68UhPPAGCGyMM1bGCslA4p0p3FPmZaErkcCJYOWZAU45AtW9O6ltyL0rvw2djSHFrWD5qQSNo0YvIoExryJLJri_WXrIastNeDraPmM1lNKPSF3KgOHu71rkSRSh_Dczg-c1R657r9-mQNa93KkQ\",null,null,181343],[[null,2021215439,null,null,null,null,null,\"deep cut-out top, revealing cleavage\",25,\"\",null,\"7212e0d2-229b-4032-95e3-4c363d2b46c4\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUZvnfLi4e_wIQIorBBWTJ68UhPPAGCGyMM1bGCslA4p0p3FPmZaErkcCJYOWZAU45AtW9O6ltyL0rvw2djSHFrWD5qQSNo0YvIoExryJLJri_WXrIastNeDraPmM1lNKPSF3KgOHu71rkSRSh_Dczg-c1R657r9-mQNa93KkQ\",3],null,[1376,768]]],[\"27cf3d47-aae9-4035-9324-32bb65509721\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"da045c4a-d318-46ce-9d05-2b902878dc90\",\"CAE\",null,[[1790104504,482062000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUaFSHfD2PqGyT1oHU6O0EbyvRHBQu_z7dP3bo91wcegBn8L2viTM_ntW_NoGAq0eebQ8yYP2V-H_P4AsXf_55A1NCdBuJPm9nEi6JyjvG_OGCPVk4McB5eeTavReqR7FdSnH6SaY61Zueutr1LWVRHArV8DgqyHVX_3ZRkEMQ\",[null,null,[[\"A post-apocalyptic Hanoi intersection under a blistering, golden-hour sun that feels oppressive. 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Grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast, natural skin texture, physically believable heat haze and sweat, restrained expression. Subtle film grain, high dynamic range. No anime, no illustration, no glossy rendering, no generic cyberpunk neon, no holograms. No face drift, no age drift, no hairstyle drift, no costume drift. No generated readable text, no watermark.\",25,\"\",null,\"3ab07549-ccbb-410a-a97d-08b8a4627f84\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUb_QujW3NDPoer97t_RbrFOtFLtMDC-jX49qb8CXY7dI1IdXHvhFoyk9WtQaUZunQm2XyQK2Wrx530dtfCNPv_b9m3ppqNaiXcDBB5HN7COGvoIBa_CPqKx98-KEOw_9SSP_KMjpOSvSP2krJY_RL6kv-KFBwuk06SqhiGOPg\",3],null,[1376,768]]],[\"6aa915c7-1123-4e12-b75f-6d5e6d40d0fe\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"d7c54686-02ce-4344-ac22-2888ccf9c76e\",\"CAE\",null,[[1784546032,956328000],\"Man in black shirt and pants\",null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUa0Hu8CuBjBs_H1OHD0zbJ6ZyQhx1Hx0z1fdSfPWo778yvuntmjnGeBneX5oRmxo12rL4ebKQlklWgX6TmVuwqp8rBlNdWXHAkIDSKkyqIO38lMbR9EsRrp1fydpam1-1EGOvRRDEA4ds17HnIBQ-iIpCzpHEfOq_-YjCmO4A\",[null,null,null,null,1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUa0Hu8CuBjBs_H1OHD0zbJ6ZyQhx1Hx0z1fdSfPWo778yvuntmjnGeBneX5oRmxo12rL4ebKQlklWgX6TmVuwqp8rBlNdWXHAkIDSKkyqIO38lMbR9EsRrp1fydpam1-1EGOvRRDEA4ds17HnIBQ-iIpCzpHEfOq_-YjCmO4A\",null,\"A man with short dark hair stands against a plain gray background, shown from multiple angles. He wears a black button-up shirt over a dark t-shirt, dark cargo pants, and a crossbody bag. He has a watch on his left wrist.\"],[null,[null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUa0Hu8CuBjBs_H1OHD0zbJ6ZyQhx1Hx0z1fdSfPWo778yvuntmjnGeBneX5oRmxo12rL4ebKQlklWgX6TmVuwqp8rBlNdWXHAkIDSKkyqIO38lMbR9EsRrp1fydpam1-1EGOvRRDEA4ds17HnIBQ-iIpCzpHEfOq_-YjCmO4A\",0],[1376,768]]],[\"6e6be6ca-d2c5-477c-b025-8ceac859aa54\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"7212e0d2-229b-4032-95e3-4c363d2b46c4\",\"CAU\",null,[[1790105600,764469000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUZ5hXeejQlQWInv3-Nk6t2Os8Ny-BBsbgmhlE9LmsbSyiPXjGPU9Eenh2ayA97QstKkBFb3OVzZBoiEyffvhPkMOTUIijGjPNYm-pYc8mtJAu39C3mO8ivKlsXdSiopxKxiTDsQPdEMQRRT-ieg1Nv6VgX92UoHk7ralpuQ\",[null,null,[[\"two-piece outfit, camisole, many torn spots\",null,[[[\"áo 2 mảnh , 2 dây, có nhiều vết rách\"]]]]],[[[null,2,\"279b944e-5348-4ecc-91d4-f356b9271132\"]]],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUZ5hXeejQlQWInv3-Nk6t2Os8Ny-BBsbgmhlE9LmsbSyiPXjGPU9Eenh2ayA97QstKkBFb3OVzZBoiEyffvhPkMOTUIijGjPNYm-pYc8mtJAu39C3mO8ivKlsXdSiopxKxiTDsQPdEMQRRT-ieg1Nv6VgX92UoHk7ralpuQ\",null,null,181689],[[null,166472867,null,null,null,null,null,\"two-piece outfit, camisole, many torn spots\",25,\"\",null,\"7212e0d2-229b-4032-95e3-4c363d2b46c4\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUZ5hXeejQlQWInv3-Nk6t2Os8Ny-BBsbgmhlE9LmsbSyiPXjGPU9Eenh2ayA97QstKkBFb3OVzZBoiEyffvhPkMOTUIijGjPNYm-pYc8mtJAu39C3mO8ivKlsXdSiopxKxiTDsQPdEMQRRT-ieg1Nv6VgX92UoHk7ralpuQ\",3],null,[1376,768]]],[\"732c7e1a-7267-462f-8f58-1bf43694428e\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"be5c73e8-269a-4fdf-a1a5-d2265179a8be\",\"CAE\",null,[[1784546459,807750000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUb5ap5IbDPwWp5-DGrbazcb9T_G-aOu9nN3g7ib3dMMRXskaJ6jaihFAztr4lIRjSOFZCDgBhfGvvkmqUxqXxUdQtNNnARmrm5vl4Q9vWVTtVHAKPxZGJfphs0xlOYhLL6xrDPIkT3b-1dd0mapyQ-nFne_v6Vmi_MEQZgtFg\",[null,null,[[\"Live-action cinematic character reference of Lê Quốc Tiến. A 29-year-old Vietnamese systems engineer. Emaciated, dehydrated, with patched and worn clothing, and a visible abdomen wound. Preserve the exact facial geometry, eye shape, nose, jaw, hairline, and body proportions of the identity in reference 1. Clean full-body neutral standing view and one clear three-quarter portrait. Plain segmented grey background, soft neutral studio lighting. Grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast, natural skin texture, physically believable heat haze and sweat, restrained expression. Subtle film grain, high dynamic range. No anime, no illustration, no glossy rendering, no generic cyberpunk neon, no holograms. No face drift, no age drift, no hairstyle drift, no costume drift. No generated readable text, no watermark.\",null,[[[\"Live-action cinematic character reference of Lê Quốc Tiến. A 29-year-old Vietnamese systems engineer. Emaciated, dehydrated, with patched and worn clothing, and a visible abdomen wound. Preserve the exact facial geometry, eye shape, nose, jaw, hairline, and body proportions of the identity in reference 1. Clean full-body neutral standing view and one clear three-quarter portrait. Plain segmented grey background, soft neutral studio lighting. Grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast, natural skin texture, physically believable heat haze and sweat, restrained expression. Subtle film grain, high dynamic range. No anime, no illustration, no glossy rendering, no generic cyberpunk neon, no holograms. No face drift, no age drift, no hairstyle drift, no costume drift. No generated readable text, no watermark.\"]]]]],[null,[[\"f4d9c731-41f2-4b51-9dd2-edd20c1dc7f1\"]]],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUb5ap5IbDPwWp5-DGrbazcb9T_G-aOu9nN3g7ib3dMMRXskaJ6jaihFAztr4lIRjSOFZCDgBhfGvvkmqUxqXxUdQtNNnARmrm5vl4Q9vWVTtVHAKPxZGJfphs0xlOYhLL6xrDPIkT3b-1dd0mapyQ-nFne_v6Vmi_MEQZgtFg\",null,null,655260],[[null,599389,\"CAMSJDU5NDc1OGNjLTExZjUtNGY5Mi04YjNjLTEyMTM2ODY1OTFmNBokMTMyMDVkOTQtYTQ2Mi00MjE5LWI5MjQtMzdhNjFiNjY2MzIxIgNDQUUqJDczMmM3ZTFhLTcyNjctNDYyZi04ZjU4LTFiZjQzNjk0NDI4ZQ\",null,null,null,null,\"Live-action cinematic character reference of Lê Quốc Tiến. A 29-year-old Vietnamese systems engineer. Emaciated, dehydrated, with patched and worn clothing, and a visible abdomen wound. Preserve the exact facial geometry, eye shape, nose, jaw, hairline, and body proportions of the identity in reference 1. Clean full-body neutral standing view and one clear three-quarter portrait. Plain segmented grey background, soft neutral studio lighting. Grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast, natural skin texture, physically believable heat haze and sweat, restrained expression. Subtle film grain, high dynamic range. No anime, no illustration, no glossy rendering, no generic cyberpunk neon, no holograms. No face drift, no age drift, no hairstyle drift, no costume drift. No generated readable text, no watermark.\",25,\"\",null,\"be5c73e8-269a-4fdf-a1a5-d2265179a8be\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUb5ap5IbDPwWp5-DGrbazcb9T_G-aOu9nN3g7ib3dMMRXskaJ6jaihFAztr4lIRjSOFZCDgBhfGvvkmqUxqXxUdQtNNnARmrm5vl4Q9vWVTtVHAKPxZGJfphs0xlOYhLL6xrDPIkT3b-1dd0mapyQ-nFne_v6Vmi_MEQZgtFg\",3],null,[1376,768]]],[\"76a03ec4-6340-4e25-9e8a-5009942893b9\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"a5fbb9e9-b0d0-48f4-89ea-277444ec27c4\",\"CAE\",null,[[1790104424,188616000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUZyRbtbzcGUezd3ygh-aozo8PeVAlRLEKABEn0N0fDPqLBG5uL0xC4YycYgSDi9TOTperhgoMI6GJWmGv5QXTmlsA4TzK1yYdOeJF_5xxGj9U8Oh-g93r_A9laQ7LC1RvLfh8nVouNkPZlw5DiPSkCNehYo6N1bwxkx1ZXd_A\",[null,null,[[\"A deserted, dust-covered street in Hanoi's Old Quarter after a near-future catastrophe. Abandoned 2028-style electric scooters are half-buried in debris and overgrown vines. Tall, narrow buildings show signs of structural decay under a dim, overcast sun. Grounded live-action aesthetic, cinematic realism, authentic Vietnamese everyday objects. Darker, atmospheric lighting with high dynamic range.\",null,[[[\"A deserted, dust-covered street in Hanoi's Old Quarter after a near-future catastrophe. Abandoned 2028-style electric scooters are half-buried in debris and overgrown vines. Tall, narrow buildings show signs of structural decay under a dim, overcast sun. Grounded live-action aesthetic, cinematic realism, authentic Vietnamese everyday objects. Darker, atmospheric lighting with high dynamic range.\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUZyRbtbzcGUezd3ygh-aozo8PeVAlRLEKABEn0N0fDPqLBG5uL0xC4YycYgSDi9TOTperhgoMI6GJWmGv5QXTmlsA4TzK1yYdOeJF_5xxGj9U8Oh-g93r_A9laQ7LC1RvLfh8nVouNkPZlw5DiPSkCNehYo6N1bwxkx1ZXd_A\",null,null,281615],[[null,755263,null,null,null,null,null,\"A deserted, dust-covered street in Hanoi's Old Quarter after a near-future catastrophe. Abandoned 2028-style electric scooters are half-buried in debris and overgrown vines. Tall, narrow buildings show signs of structural decay under a dim, overcast sun. Grounded live-action aesthetic, cinematic realism, authentic Vietnamese everyday objects. Darker, atmospheric lighting with high dynamic range.\",25,\"\",null,\"a5fbb9e9-b0d0-48f4-89ea-277444ec27c4\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUZyRbtbzcGUezd3ygh-aozo8PeVAlRLEKABEn0N0fDPqLBG5uL0xC4YycYgSDi9TOTperhgoMI6GJWmGv5QXTmlsA4TzK1yYdOeJF_5xxGj9U8Oh-g93r_A9laQ7LC1RvLfh8nVouNkPZlw5DiPSkCNehYo6N1bwxkx1ZXd_A\",3],null,[1376,768]]],[\"78266bba-b106-47e7-80e3-c152822e1ca9\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"82ddef0b-fced-4a18-a039-240a66c111d2\",\"CAE\",null,[[1790105368,716850000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUaWhR4c9CHlZw_wiJwoNlZJDs8mzOrvAB-X2XljYNHpxlP3snah_vertyktxnovuo81KPz7UqZpVPoXsJWw4fx5iwYnChh9FZ9dEUTEBZTXi7c3F9PMYVPnPhkdTdsrraejL2gyMA0NH0gPESKQazHrNYgJDxTFXzY35Uhk\",[null,null,[[\"A beautiful Vietnamese female character in a grounded 2028 techno-thriller setting. She is wearing sleek, tight-fitting industrial-chic clothing with a long, flowing tech-fabric coat that trails behind her. Her face is authentically Vietnamese, with a determined expression. Cinematic realism, natural lighting under a harsh, hot sun, visible heat haze in the background. Physically believable textures, no fantasy spectacle, subtle film grain. High-quality live-action aesthetic.\",null,[[[\"A beautiful Vietnamese female character in a grounded 2028 techno-thriller setting. She is wearing sleek, tight-fitting industrial-chic clothing with a long, flowing tech-fabric coat that trails behind her. Her face is authentically Vietnamese, with a determined expression. Cinematic realism, natural lighting under a harsh, hot sun, visible heat haze in the background. Physically believable textures, no fantasy spectacle, subtle film grain. High-quality live-action aesthetic.\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUaWhR4c9CHlZw_wiJwoNlZJDs8mzOrvAB-X2XljYNHpxlP3snah_vertyktxnovuo81KPz7UqZpVPoXsJWw4fx5iwYnChh9FZ9dEUTEBZTXi7c3F9PMYVPnPhkdTdsrraejL2gyMA0NH0gPESKQazHrNYgJDxTFXzY35Uhk\",null,null,169250],[[null,475867,null,null,null,null,null,\"A beautiful Vietnamese female character in a grounded 2028 techno-thriller setting. She is wearing sleek, tight-fitting industrial-chic clothing with a long, flowing tech-fabric coat that trails behind her. Her face is authentically Vietnamese, with a determined expression. Cinematic realism, natural lighting under a harsh, hot sun, visible heat haze in the background. Physically believable textures, no fantasy spectacle, subtle film grain. High-quality live-action aesthetic.\",25,\"\",null,\"82ddef0b-fced-4a18-a039-240a66c111d2\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUaWhR4c9CHlZw_wiJwoNlZJDs8mzOrvAB-X2XljYNHpxlP3snah_vertyktxnovuo81KPz7UqZpVPoXsJWw4fx5iwYnChh9FZ9dEUTEBZTXi7c3F9PMYVPnPhkdTdsrraejL2gyMA0NH0gPESKQazHrNYgJDxTFXzY35Uhk\",3],null,[1376,768]]],[\"78e46231-e6cf-43fb-99bc-a4cb96196e24\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"431da3f0-96a9-4cc7-8384-937287b72c6e\",\"CAE\",null,[[1790098978,830949000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUarwgaECQHTDEn00eyt70D2PN5pVA_w2IGU7iU5N8W9UmWPaozySZboiA15dJttaxxWVKJG3E8A0lhxYJg9dw9MOG1Y7EbFshxazXjJ4KuZEKA_1Pg5ItXC1YxZXtTl2Q4oJPpTmXT_gQGJC-ytNPkvug_1jJlgv3DCzLo0rA\",[null,null,[[\"Single reference image of 34-year-old Vietnamese logistics commander, tall imposing authoritative posture, slicked-back dark hair, wearing an unbuttoned black button-down shirt with rolled-up sleeves, dark trousers, distinctive matte black ring on his left ring finger, piercing cold calculated gaze. Photorealistic RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light, real footage. NOT 3D render, NOT CGI, NOT digital art, NOT illustration, NOT anime, NOT painting, NOT cartoon. COMPOSITION: Full body shot from head to toe, standing upright and straight (not tilted or leaning). Centered in frame with balanced composition. Front-facing view, looking directly at camera. Neutral simple background that does not distract from the subject. Proper proportions and anatomy. Character perfectly vertical, not skewed or rotated. ONE single image only, NOT a multi-panel grid or multiple views. Studio lighting, highly detailed\",null,[[[\"Single reference image of 34-year-old Vietnamese logistics commander, tall imposing authoritative posture, slicked-back dark hair, wearing an unbuttoned black button-down shirt with rolled-up sleeves, dark trousers, distinctive matte black ring on his left ring finger, piercing cold calculated gaze. Photorealistic RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light, real footage. NOT 3D render, NOT CGI, NOT digital art, NOT illustration, NOT anime, NOT painting, NOT cartoon. COMPOSITION: Full body shot from head to toe, standing upright and straight (not tilted or leaning). Centered in frame with balanced composition. Front-facing view, looking directly at camera. Neutral simple background that does not distract from the subject. Proper proportions and anatomy. Character perfectly vertical, not skewed or rotated. ONE single image only, NOT a multi-panel grid or multiple views. Studio lighting, highly detailed\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUarwgaECQHTDEn00eyt70D2PN5pVA_w2IGU7iU5N8W9UmWPaozySZboiA15dJttaxxWVKJG3E8A0lhxYJg9dw9MOG1Y7EbFshxazXjJ4KuZEKA_1Pg5ItXC1YxZXtTl2Q4oJPpTmXT_gQGJC-ytNPkvug_1jJlgv3DCzLo0rA\",null,null,93667],[[null,610053073,null,null,null,null,null,\"Single reference image of 34-year-old Vietnamese logistics commander, tall imposing authoritative posture, slicked-back dark hair, wearing an unbuttoned black button-down shirt with rolled-up sleeves, dark trousers, distinctive matte black ring on his left ring finger, piercing cold calculated gaze. Photorealistic RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light, real footage. NOT 3D render, NOT CGI, NOT digital art, NOT illustration, NOT anime, NOT painting, NOT cartoon. COMPOSITION: Full body shot from head to toe, standing upright and straight (not tilted or leaning). Centered in frame with balanced composition. Front-facing view, looking directly at camera. Neutral simple background that does not distract from the subject. Proper proportions and anatomy. Character perfectly vertical, not skewed or rotated. ONE single image only, NOT a multi-panel grid or multiple views. Studio lighting, highly detailed\",25,\"\",null,\"431da3f0-96a9-4cc7-8384-937287b72c6e\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUarwgaECQHTDEn00eyt70D2PN5pVA_w2IGU7iU5N8W9UmWPaozySZboiA15dJttaxxWVKJG3E8A0lhxYJg9dw9MOG1Y7EbFshxazXjJ4KuZEKA_1Pg5ItXC1YxZXtTl2Q4oJPpTmXT_gQGJC-ytNPkvug_1jJlgv3DCzLo0rA\",2],null,[768,1376]]],[\"7b965b5d-e710-4d9a-9d24-253ba6e48286\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"80fcf81d-8e09-4a04-a22d-1de8c8569a46\",\"CAE\",null,[[1790106045,1406000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUZNkJAU3A3mTXxfRB3z5XcrRTmYMsW-vXve1HwCrASZ9FQV4ibEcqbVitT5TOALfwxiJPbzh3tlfUqPYtmD9oWIM7iOPBjjBa9P5RryK2ULhlECqLZPH3qop6s6GDIor3LD2vWhMhnIFeJa4MeityYUYIM4Vpqf1IShoOFEdw\",[null,null,[[\"Grounded cinematic realism, a beautiful 19-year-old Vietnamese woman in a high-tech Hanoi apartment, 2028. She is wearing a practical yet stylish dark lace-trimmed camisole with thin straps. Authentic Vietnamese features, natural skin texture with subtle sweat from the extreme heatwave. She is sitting near a cooling fan, parched atmosphere, soft tungsten lighting. Near-future techno-thriller style, restrained pose, high dynamic range, subtle film grain. High-quality live-action aesthetic.\",null,[[[\"Grounded cinematic realism, a beautiful 19-year-old Vietnamese woman in a high-tech Hanoi apartment, 2028. She is wearing a practical yet stylish dark lace-trimmed camisole with thin straps. Authentic Vietnamese features, natural skin texture with subtle sweat from the extreme heatwave. She is sitting near a cooling fan, parched atmosphere, soft tungsten lighting. Near-future techno-thriller style, restrained pose, high dynamic range, subtle film grain. 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Studio lighting, global illumination, highly detailed\",25,\"\",null,\"d6e35829-f7a1-43aa-b12c-7172309cf84c\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUbRQ_Bp4QhsU1Iu84cZ-r5y2ZhYCzF3AYTam8eKNwGcW9aKvYsPy8wkabi2M6RcWcVfzv9RHeFbYP9C6dJNgxaTsqqTwpzDQnPHqnDGMNSSnGdTiQ9y3zAAYHU0LZ_AWwPH-skO-aEWWB0ZBhgaO1i8zfdqnZ9fsGRMwYHwWA\",2],null,[768,1376]]],[\"ac5f92cb-b55e-4db9-b800-0dd1dbe759ef\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"b00ceb65-a125-49c4-91ff-49f0af1e2356\",\"CAE\",null,[[1784545698,613155000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUYU9yBwTqRhuBqi4Sq7neRHGAdzXTSk4Jbt4JKNBO0_NTcu_Bym4j5YCMNenazSJ9djSeRzF0p5-QKF4AfNoHQdJDY4RSI9b_pa_5fKvtNJ09GrtO97eqRuzqofh5L2LjMjFzSWYuNYpUastYCDucqB24U_KWAlNxhc7SkHkw\",[null,null,[[\"Live-action cinematic character reference sheet. 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Plain segmented grey background, soft neutral studio lighting, exact identity consistency across all views, authentic Vietnamese facial features, natural skin texture and anatomy. grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast and Hanoi architecture, natural skin texture, practical 2028 clothing and industrial equipment, physically believable heat haze and sweat, restrained acting, controlled camera movement, 24 fps cinematic motion, subtle film grain, high dynamic range, no fantasy spectacle. no anime, no illustration, no comic-book rendering, no glossy video-game look, no superhero armor, no magic glow, no Chinese imperial costume, no Japanese historical styling, no European medieval architecture, no generic cyberpunk neon, no holograms, no face drift, no age drift, no hairstyle drift, no costume drift, no extra fingers, no duplicated main characters, no generated readable text, no watermark.\",null,[[[\"Live-action cinematic character reference sheet. A 29-year-old Vietnamese infrastructure and systems engineer, lean athletic but not muscular, light tan skin, short slightly messy black hair, tired focused dark eyes, restrained expression, charcoal crew-neck T-shirt, lightweight black technical overshirt, dark cargo trousers, black field watch and simple cross-body utility bag. He looks like someone who notices exits and electrical panels before people. Front portrait, three-quarter portrait, left and right profile, and full-body neutral standing view. Plain segmented grey background, soft neutral studio lighting, exact identity consistency across all views, authentic Vietnamese facial features, natural skin texture and anatomy. grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast and Hanoi architecture, natural skin texture, practical 2028 clothing and industrial equipment, physically believable heat haze and sweat, restrained acting, controlled camera movement, 24 fps cinematic motion, subtle film grain, high dynamic range, no fantasy spectacle. no anime, no illustration, no comic-book rendering, no glossy video-game look, no superhero armor, no magic glow, no Chinese imperial costume, no Japanese historical styling, no European medieval architecture, no generic cyberpunk neon, no holograms, no face drift, no age drift, no hairstyle drift, no costume drift, no extra fingers, no duplicated main characters, no generated readable text, no watermark.\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUYU9yBwTqRhuBqi4Sq7neRHGAdzXTSk4Jbt4JKNBO0_NTcu_Bym4j5YCMNenazSJ9djSeRzF0p5-QKF4AfNoHQdJDY4RSI9b_pa_5fKvtNJ09GrtO97eqRuzqofh5L2LjMjFzSWYuNYpUastYCDucqB24U_KWAlNxhc7SkHkw\",null,null,626799],[[null,562848,\"CAMSJDU5NDc1OGNjLTExZjUtNGY5Mi04YjNjLTEyMTM2ODY1OTFmNBokZGExZTY3YWYtYmI2OS00Njg4LWJhMzYtZGRiNTFiZjg4MjNkIgNDQUUqJGFjNWY5MmNiLWI1NWUtNGRiOS1iODAwLTBkZDFkYmU3NTllZg\",null,null,null,null,\"Live-action cinematic character reference sheet. A 29-year-old Vietnamese infrastructure and systems engineer, lean athletic but not muscular, light tan skin, short slightly messy black hair, tired focused dark eyes, restrained expression, charcoal crew-neck T-shirt, lightweight black technical overshirt, dark cargo trousers, black field watch and simple cross-body utility bag. He looks like someone who notices exits and electrical panels before people. Front portrait, three-quarter portrait, left and right profile, and full-body neutral standing view. Plain segmented grey background, soft neutral studio lighting, exact identity consistency across all views, authentic Vietnamese facial features, natural skin texture and anatomy. grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast and Hanoi architecture, natural skin texture, practical 2028 clothing and industrial equipment, physically believable heat haze and sweat, restrained acting, controlled camera movement, 24 fps cinematic motion, subtle film grain, high dynamic range, no fantasy spectacle. no anime, no illustration, no comic-book rendering, no glossy video-game look, no superhero armor, no magic glow, no Chinese imperial costume, no Japanese historical styling, no European medieval architecture, no generic cyberpunk neon, no holograms, no face drift, no age drift, no hairstyle drift, no costume drift, no extra fingers, no duplicated main characters, no generated readable text, no watermark.\",25,\"\",null,\"b00ceb65-a125-49c4-91ff-49f0af1e2356\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUYU9yBwTqRhuBqi4Sq7neRHGAdzXTSk4Jbt4JKNBO0_NTcu_Bym4j5YCMNenazSJ9djSeRzF0p5-QKF4AfNoHQdJDY4RSI9b_pa_5fKvtNJ09GrtO97eqRuzqofh5L2LjMjFzSWYuNYpUastYCDucqB24U_KWAlNxhc7SkHkw\",3],null,[1376,768]]],[\"acf87cab-c8f4-46c4-b305-5d57a5be19fa\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"b58780b6-8218-433c-bdca-6fb13f9e9cd6\",\"CAE\",null,[[1784545738,781156000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUZRZ0X8_gAC7eBzRHdccFMzFSVKpAjlYJj6gkxZm6voFpniFQxGgmu64zF0-pMBuihjmsUXMFj-QZEKDHe2fvD3zTqI9i-yHmfHTIXoJJ-iOI7XwN6Vv7cQragFr-DkewKeiOqeRHTx2Mn3fEvhgcypfX5FGNpIFqTfCuFOCA\",[null,null,[[\"Live-action cinematic character reference sheet. A 29-year-old Vietnamese infrastructure and systems engineer, lean athletic but not muscular, light tan skin, short slightly messy black hair, tired focused dark eyes, restrained expression, charcoal crew-neck T-shirt, lightweight black technical overshirt, dark cargo trousers, black field watch and simple cross-body utility bag. He looks like someone who notices exits and electrical panels before people. Front portrait, three-quarter portrait, left and right profile, and full-body neutral standing view. Plain segmented grey background, soft neutral studio lighting, exact identity consistency across all views, authentic Vietnamese facial features, natural skin texture and anatomy. grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast and Hanoi architecture, natural skin texture, practical 2028 clothing and industrial equipment, physically believable heat haze and sweat, restrained acting, controlled camera movement, 24 fps cinematic motion, subtle film grain, high dynamic range, no fantasy spectacle. no anime, no illustration, no comic-book rendering, no glossy video-game look, no superhero armor, no magic glow, no Chinese imperial costume, no Japanese historical styling, no European medieval architecture, no generic cyberpunk neon, no holograms, no face drift, no age drift, no hairstyle drift, no costume drift, no extra fingers, no duplicated main characters, no generated readable text, no watermark.\",null,[[[\"Live-action cinematic character reference sheet. A 29-year-old Vietnamese infrastructure and systems engineer, lean athletic but not muscular, light tan skin, short slightly messy black hair, tired focused dark eyes, restrained expression, charcoal crew-neck T-shirt, lightweight black technical overshirt, dark cargo trousers, black field watch and simple cross-body utility bag. He looks like someone who notices exits and electrical panels before people. Front portrait, three-quarter portrait, left and right profile, and full-body neutral standing view. Plain segmented grey background, soft neutral studio lighting, exact identity consistency across all views, authentic Vietnamese facial features, natural skin texture and anatomy. grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast and Hanoi architecture, natural skin texture, practical 2028 clothing and industrial equipment, physically believable heat haze and sweat, restrained acting, controlled camera movement, 24 fps cinematic motion, subtle film grain, high dynamic range, no fantasy spectacle. no anime, no illustration, no comic-book rendering, no glossy video-game look, no superhero armor, no magic glow, no Chinese imperial costume, no Japanese historical styling, no European medieval architecture, no generic cyberpunk neon, no holograms, no face drift, no age drift, no hairstyle drift, no costume drift, no extra fingers, no duplicated main characters, no generated readable text, no watermark.\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUZRZ0X8_gAC7eBzRHdccFMzFSVKpAjlYJj6gkxZm6voFpniFQxGgmu64zF0-pMBuihjmsUXMFj-QZEKDHe2fvD3zTqI9i-yHmfHTIXoJJ-iOI7XwN6Vv7cQragFr-DkewKeiOqeRHTx2Mn3fEvhgcypfX5FGNpIFqTfCuFOCA\",null,null,694462],[[null,571904,\"CAMSJDU5NDc1OGNjLTExZjUtNGY5Mi04YjNjLTEyMTM2ODY1OTFmNBokMDllNjYyZGUtOGQxNy00NWU5LTg5MWYtZWViYWEzNDY5MTdiIgNDQUUqJGFjZjg3Y2FiLWM4ZjQtNDZjNC1iMzA1LTVkNTdhNWJlMTlmYQ\",null,null,null,null,\"Live-action cinematic character reference sheet. A 29-year-old Vietnamese infrastructure and systems engineer, lean athletic but not muscular, light tan skin, short slightly messy black hair, tired focused dark eyes, restrained expression, charcoal crew-neck T-shirt, lightweight black technical overshirt, dark cargo trousers, black field watch and simple cross-body utility bag. He looks like someone who notices exits and electrical panels before people. Front portrait, three-quarter portrait, left and right profile, and full-body neutral standing view. Plain segmented grey background, soft neutral studio lighting, exact identity consistency across all views, authentic Vietnamese facial features, natural skin texture and anatomy. grounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast and Hanoi architecture, natural skin texture, practical 2028 clothing and industrial equipment, physically believable heat haze and sweat, restrained acting, controlled camera movement, 24 fps cinematic motion, subtle film grain, high dynamic range, no fantasy spectacle. no anime, no illustration, no comic-book rendering, no glossy video-game look, no superhero armor, no magic glow, no Chinese imperial costume, no Japanese historical styling, no European medieval architecture, no generic cyberpunk neon, no holograms, no face drift, no age drift, no hairstyle drift, no costume drift, no extra fingers, no duplicated main characters, no generated readable text, no watermark.\",25,\"\",null,\"b58780b6-8218-433c-bdca-6fb13f9e9cd6\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUZRZ0X8_gAC7eBzRHdccFMzFSVKpAjlYJj6gkxZm6voFpniFQxGgmu64zF0-pMBuihjmsUXMFj-QZEKDHe2fvD3zTqI9i-yHmfHTIXoJJ-iOI7XwN6Vv7cQragFr-DkewKeiOqeRHTx2Mn3fEvhgcypfX5FGNpIFqTfCuFOCA\",3],null,[1376,768]]],[\"b4d91c90-5b01-4472-aab2-1bcacb892fa4\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"80fcf81d-8e09-4a04-a22d-1de8c8569a46\",\"CAI\",null,[[1790106092,630331000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUbWF5CgIMSnMgw6esBRNn9yOAnIIO3zTaaZSw403meT4lIMC7DGlMaWND-o4l1jC2FYzS_BKIn4zgJHF0X5DJdiPMPnClnsUV8zYKQaV3DOcrSi80NivCeUQcSk0ksCZTLRUGVpaExY0oljfF4gHz_d95OMI-6AD5IlgEDkUg\",[null,null,[[\"Big breasts?\",null,[[[\"ngực to mà ?\"]]]]],[[[null,2,\"7b965b5d-e710-4d9a-9d24-253ba6e48286\"]]],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUbWF5CgIMSnMgw6esBRNn9yOAnIIO3zTaaZSw403meT4lIMC7DGlMaWND-o4l1jC2FYzS_BKIn4zgJHF0X5DJdiPMPnClnsUV8zYKQaV3DOcrSi80NivCeUQcSk0ksCZTLRUGVpaExY0oljfF4gHz_d95OMI-6AD5IlgEDkUg\",null,null,120695],[[null,10322356,null,null,null,null,null,\"Big breasts?\",25,\"\",null,\"80fcf81d-8e09-4a04-a22d-1de8c8569a46\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUbWF5CgIMSnMgw6esBRNn9yOAnIIO3zTaaZSw403meT4lIMC7DGlMaWND-o4l1jC2FYzS_BKIn4zgJHF0X5DJdiPMPnClnsUV8zYKQaV3DOcrSi80NivCeUQcSk0ksCZTLRUGVpaExY0oljfF4gHz_d95OMI-6AD5IlgEDkUg\",3],null,[1376,768]]],[\"b5b2415a-b104-4e53-bf22-1bd940d2186b\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"d9102dd3-bb7b-4a6b-8135-90e9e3455f30\",\"CAE\",null,[[1790104505,133221000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUazu0_Xip0Px8230pDZrhmBE6DcbMBlniQH7V3twUTrLf7SO7Vcvj1z_3QOPC08UlD4gQbfZXoeZW-fMErVIyyHGUNr0MPTv_7tY7_KCVQP9XpX_oHtJUOAlgvcmjWLvAPWqBwJcs8Pdefn4Ynw46NmLWrke6x_1Qla1iKvCw\",[null,null,[[\"Grounded cinematic realism, extreme heatwave apocalypse in Hanoi 2028. Intense, scorching sunlight creates a visible, shimmering heat haze over a deserted Ba Dinh Square. The asphalt is cracked and dry. Tall, modern Vietnamese government buildings look bleached under a relentless, white-hot sun. Physically believable sweat and parched textures, muted but high-contrast color palette, subtle film grain. No holograms or neon.\",null,[[[\"Grounded cinematic realism, extreme heatwave apocalypse in Hanoi 2028. Intense, scorching sunlight creates a visible, shimmering heat haze over a deserted Ba Dinh Square. The asphalt is cracked and dry. Tall, modern Vietnamese government buildings look bleached under a relentless, white-hot sun. Physically believable sweat and parched textures, muted but high-contrast color palette, subtle film grain. No holograms or neon.\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUazu0_Xip0Px8230pDZrhmBE6DcbMBlniQH7V3twUTrLf7SO7Vcvj1z_3QOPC08UlD4gQbfZXoeZW-fMErVIyyHGUNr0MPTv_7tY7_KCVQP9XpX_oHtJUOAlgvcmjWLvAPWqBwJcs8Pdefn4Ynw46NmLWrke6x_1Qla1iKvCw\",null,null,206966],[[null,479066,null,null,null,null,null,\"Grounded cinematic realism, extreme heatwave apocalypse in Hanoi 2028. Intense, scorching sunlight creates a visible, shimmering heat haze over a deserted Ba Dinh Square. The asphalt is cracked and dry. Tall, modern Vietnamese government buildings look bleached under a relentless, white-hot sun. Physically believable sweat and parched textures, muted but high-contrast color palette, subtle film grain. No holograms or neon.\",25,\"\",null,\"d9102dd3-bb7b-4a6b-8135-90e9e3455f30\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUazu0_Xip0Px8230pDZrhmBE6DcbMBlniQH7V3twUTrLf7SO7Vcvj1z_3QOPC08UlD4gQbfZXoeZW-fMErVIyyHGUNr0MPTv_7tY7_KCVQP9XpX_oHtJUOAlgvcmjWLvAPWqBwJcs8Pdefn4Ynw46NmLWrke6x_1Qla1iKvCw\",3],null,[1376,768]]],[\"b6900ed9-ed42-4b6c-80c1-74db6fc6132d\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"f69d66c7-9cd6-459d-a883-753390a8cb25\",\"CAE\",null,[[1790106044,585720000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUazFzv8j1epY7qODet9rTfh2aglcrIHhLR6BCxhOPSdCZWGuwI5HApIMFeeCrOPgGVVzHuVPeNVEqWf15Lw57IN68AMR9kGtEbAb-bLlLSWzY-pKmCfWmQHmS7rrWSzHGEdvOBu5w7xzQWIVyxfJUiPmcW60g5IMDWkW2vkCw\",[null,null,[[\"A beautiful young Vietnamese woman, aged 18-20, in a grounded post-apocalyptic Hanoi setting. She wears a sleek, form-fitting top with thin straps and delicate lace details, suitable for the oppressive heat. Her expression is calm yet determined. Cinematic realism, natural harsh lighting from the blistering sun, visible heat haze in the background. Physically believable textures, authentic Vietnamese face, subtle film grain. Near-future techno-thriller aesthetic.\",null,[[[\"A beautiful young Vietnamese woman, aged 18-20, in a grounded post-apocalyptic Hanoi setting. She wears a sleek, form-fitting top with thin straps and delicate lace details, suitable for the oppressive heat. Her expression is calm yet determined. Cinematic realism, natural harsh lighting from the blistering sun, visible heat haze in the background. Physically believable textures, authentic Vietnamese face, subtle film grain. Near-future techno-thriller aesthetic.\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUazFzv8j1epY7qODet9rTfh2aglcrIHhLR6BCxhOPSdCZWGuwI5HApIMFeeCrOPgGVVzHuVPeNVEqWf15Lw57IN68AMR9kGtEbAb-bLlLSWzY-pKmCfWmQHmS7rrWSzHGEdvOBu5w7xzQWIVyxfJUiPmcW60g5IMDWkW2vkCw\",null,null,197433],[[null,766422,null,null,null,null,null,\"A beautiful young Vietnamese woman, aged 18-20, in a grounded post-apocalyptic Hanoi setting. She wears a sleek, form-fitting top with thin straps and delicate lace details, suitable for the oppressive heat. Her expression is calm yet determined. Cinematic realism, natural harsh lighting from the blistering sun, visible heat haze in the background. Physically believable textures, authentic Vietnamese face, subtle film grain. Near-future techno-thriller aesthetic.\",25,\"\",null,\"f69d66c7-9cd6-459d-a883-753390a8cb25\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUazFzv8j1epY7qODet9rTfh2aglcrIHhLR6BCxhOPSdCZWGuwI5HApIMFeeCrOPgGVVzHuVPeNVEqWf15Lw57IN68AMR9kGtEbAb-bLlLSWzY-pKmCfWmQHmS7rrWSzHGEdvOBu5w7xzQWIVyxfJUiPmcW60g5IMDWkW2vkCw\",3],null,[1376,768]]],[\"bdcbe55a-ee7b-497d-a414-25d22d04c096\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"e516fce6-a049-4a7f-b414-5db3660b52fc\",\"CAE\",null,[[1790174038,296806000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUY_2RMjbW4Qrd71immM795La14bTfiQSqYUlm2w480hqwU_Ctv3Yz_jYRewqNieAa_g3bGZpkUYeoFsilY8ZOD0-67hsSWF23WzrQWffIvc5nmpeyS_iuj_ZO4NcUD2bAbpfNRHE1iFpt-z-sRgb_pA42pkZl5rYIzwfyNz\",[null,null,[[\"Real RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot inside subterranean B3 basement parking at Me Tri during extreme heatwave. Le Quoc Tien slumps against a cracked concrete pillar in defeat beside a torn empty water pouch and heat-warped debris. Do Minh Kha looms over him in the background with a cold detached expression, silhouette backlit by an ominous beam of deep crimson sunlight piercing through a fractured ceiling fissure. Chiaroscuro high contrast cinematic lighting, floating soot embers, atmospheric heat distortion waves, 35mm RAW photograph.\",null,[[[\"Real RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot inside subterranean B3 basement parking at Me Tri during extreme heatwave. Le Quoc Tien slumps against a cracked concrete pillar in defeat beside a torn empty water pouch and heat-warped debris. Do Minh Kha looms over him in the background with a cold detached expression, silhouette backlit by an ominous beam of deep crimson sunlight piercing through a fractured ceiling fissure. Chiaroscuro high contrast cinematic lighting, floating soot embers, atmospheric heat distortion waves, 35mm RAW photograph.\"]]]]],[[[null,1,\"9416e9ba-eeed-43c3-b5d7-15774851c6ae\"],[null,1,\"78e46231-e6cf-43fb-99bc-a4cb96196e24\"]]],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUY_2RMjbW4Qrd71immM795La14bTfiQSqYUlm2w480hqwU_Ctv3Yz_jYRewqNieAa_g3bGZpkUYeoFsilY8ZOD0-67hsSWF23WzrQWffIvc5nmpeyS_iuj_ZO4NcUD2bAbpfNRHE1iFpt-z-sRgb_pA42pkZl5rYIzwfyNz\",null,null,127848],[[null,314608653,null,null,null,null,null,\"Real RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. Dramatic low-angle cinematic shot inside subterranean B3 basement parking at Me Tri during extreme heatwave. Le Quoc Tien slumps against a cracked concrete pillar in defeat beside a torn empty water pouch and heat-warped debris. Do Minh Kha looms over him in the background with a cold detached expression, silhouette backlit by an ominous beam of deep crimson sunlight piercing through a fractured ceiling fissure. Chiaroscuro high contrast cinematic lighting, floating soot embers, atmospheric heat distortion waves, 35mm RAW photograph.\",25,\"\",null,\"e516fce6-a049-4a7f-b414-5db3660b52fc\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUY_2RMjbW4Qrd71immM795La14bTfiQSqYUlm2w480hqwU_Ctv3Yz_jYRewqNieAa_g3bGZpkUYeoFsilY8ZOD0-67hsSWF23WzrQWffIvc5nmpeyS_iuj_ZO4NcUD2bAbpfNRHE1iFpt-z-sRgb_pA42pkZl5rYIzwfyNz\",3],null,[1376,768]]],[\"c38a6066-9d26-44da-8a14-8c7e260f7f8d\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"e2367807-01e9-4bf4-a522-1f8549998e20\",\"CAE\",null,[[1790099008,171508000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUZ3qYdMe-lNRWEyiCcRXUZHs63NHB40gTE6N-0m8iqcLmWSyC4r_1Z4Md8IxwyEcv5P0EKu2uV1I3IjqOS1Igx3DfYAf1yBknNKtYX8UprHaSK2_snwMqM_jJj9pZS0oe-BnymuvNBefI88hk32_ynKCPEVEMhuYwyRYOi4\",[null,null,[[\"Single reference image of Massive modern glass shopping mall in Ha Dong district under a terrifying dark crimson sun and apocalyptic red sky, giant glass windows completely fogged with thick condensation from dark boiling interior, heat ripples warping the melting empty asphalt parking lot outside. Photorealistic RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light, real footage. NOT 3D render, NOT CGI, NOT digital art, NOT illustration, NOT anime, NOT painting, NOT cartoon. COMPOSITION: Establishing shot showing the full environment. Balanced level composition with straight horizon. Clear focal point. Atmospheric and richly detailed. Show depth and spatial layout. ONE single image only, NOT a multi-panel grid or multiple views. Studio lighting, highly detailed\",null,[[[\"Single reference image of Massive modern glass shopping mall in Ha Dong district under a terrifying dark crimson sun and apocalyptic red sky, giant glass windows completely fogged with thick condensation from dark boiling interior, heat ripples warping the melting empty asphalt parking lot outside. Photorealistic RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light, real footage. NOT 3D render, NOT CGI, NOT digital art, NOT illustration, NOT anime, NOT painting, NOT cartoon. COMPOSITION: Establishing shot showing the full environment. Balanced level composition with straight horizon. Clear focal point. Atmospheric and richly detailed. Show depth and spatial layout. ONE single image only, NOT a multi-panel grid or multiple views. Studio lighting, highly detailed\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUZ3qYdMe-lNRWEyiCcRXUZHs63NHB40gTE6N-0m8iqcLmWSyC4r_1Z4Md8IxwyEcv5P0EKu2uV1I3IjqOS1Igx3DfYAf1yBknNKtYX8UprHaSK2_snwMqM_jJj9pZS0oe-BnymuvNBefI88hk32_ynKCPEVEMhuYwyRYOi4\",null,null,129129],[[null,998037757,null,null,null,null,null,\"Single reference image of Massive modern glass shopping mall in Ha Dong district under a terrifying dark crimson sun and apocalyptic red sky, giant glass windows completely fogged with thick condensation from dark boiling interior, heat ripples warping the melting empty asphalt parking lot outside. Photorealistic RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light, real footage. NOT 3D render, NOT CGI, NOT digital art, NOT illustration, NOT anime, NOT painting, NOT cartoon. COMPOSITION: Establishing shot showing the full environment. Balanced level composition with straight horizon. Clear focal point. Atmospheric and richly detailed. Show depth and spatial layout. ONE single image only, NOT a multi-panel grid or multiple views. 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Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted hands.\",null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUYvaqvdsuNtIAJuK_1bJx2k71A4qAsIBGQl4y-gYfvW33GRcSoTKs7OZyN32kVyQhFqsM6j7V_KUbwVNcbeHEGPsuAjft_N_JFjAChQSe4C54ksgm701PhETzSBgURwCqA-4tqYmwmm1tCnJ27AiVlaulcyjlbfqRt8j4pA8A\",[null,[[\"veo_3_1_i2v_lite\",2,[1],null,2,1],[[null,1,\"ce812adb-5fef-42cb-9a38-97b2e1bac60b\",[null,0.0038759689922481244,1,0.9961240310077519]]]],[[null,null,[[[\"0-3s: Camera pushes rapidly toward fogged glass doors as desperate hands slam against the condensation from steaming dark interiors of Dai Ha Mall Heat Trap. 3-6s: Pan up sharply to the terrifying dark crimson sun blazing in a blood-red hazy sky. 6-8s: Violent heat waves distort the melting asphalt parking lot in the foreground. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted hands.\"]]]]],null,1],null,[3],1,\"https://lh3.googleusercontent.com/asb/AB-nOUYvaqvdsuNtIAJuK_1bJx2k71A4qAsIBGQl4y-gYfvW33GRcSoTKs7OZyN32kVyQhFqsM6j7V_KUbwVNcbeHEGPsuAjft_N_JFjAChQSe4C54ksgm701PhETzSBgURwCqA-4tqYmwmm1tCnJ27AiVlaulcyjlbfqRt8j4pA8A\",null,null,6169385],null,[[null,423232,null,null,null,null,null,\"\\u003croot\\u003e\\n \\u003ccontext\\u003e\\n \\u003c/context\\u003e\\n \\u003cinstruction\\u003e\\n \\u003cprompt\\u003e0-3s: Camera pushes rapidly toward fogged glass doors as desperate hands slam against the condensation from steaming dark interiors of Dai Ha Mall Heat Trap. 3-6s: Pan up sharply to the terrifying dark crimson sun blazing in a blood-red hazy sky. 6-8s: Violent heat waves distort the melting asphalt parking lot in the foreground. Audio: natural ambient sounds only, no background music, no narration, no voiceover. Negative: subtitles, captions, watermark, text on screen, logo, blurry faces, distorted hands.\\u003c/prompt\\u003e\\n \\u003c/instruction\\u003e\\n\\u003c/root\\u003e\",\"https://lh3.googleusercontent.com/asb/AB-nOUYvaqvdsuNtIAJuK_1bJx2k71A4qAsIBGQl4y-gYfvW33GRcSoTKs7OZyN32kVyQhFqsM6j7V_KUbwVNcbeHEGPsuAjft_N_JFjAChQSe4C54ksgm701PhETzSBgURwCqA-4tqYmwmm1tCnJ27AiVlaulcyjlbfqRt8j4pA8A\",null,null,null,\"veo_3_1_i2v_lite\",\"\",null,false,2],[null,null,[8]],[\"c86e9fac-57bb-4fc3-a85f-d751ecefdcc8\"]]],[\"c8939cac-021c-4000-a355-ec23628e5ea0\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"2c817534-e7d9-4711-ba06-8da52e020080\",\"CAE\",null,[[1790099773,817655000],\"Camera pans slowly across cracked asphalt under a red burning sun.\",null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUaV1tO8-xovmpV_inv5eoc_0bAl-yyrighrAbfO8zIk73RGamYKaeVuga4GD2bcsrLYdhKRXIt66KXFrZsejmiexvPi7-afxasqy3H7bww-Qkjmp4oH8wyG3GSmUoHN9gkQCGwdWdWLFLJ2ekmHX6paaHtQr8WMqiJSoaouCg\",[null,[[\"veo_3_1_i2v_lite\",2,[1],null,2,1],[[null,1,\"a6010398-57c9-4e27-a89f-31ed0ddf2d1a\",[null,0.0038759689922481244,1,0.9961240310077519]]]],[[null,null,[[[\"Camera pans slowly across cracked asphalt under a red burning sun.\"]]]]],null,1],null,[3],1,\"https://lh3.googleusercontent.com/asb/AB-nOUaV1tO8-xovmpV_inv5eoc_0bAl-yyrighrAbfO8zIk73RGamYKaeVuga4GD2bcsrLYdhKRXIt66KXFrZsejmiexvPi7-afxasqy3H7bww-Qkjmp4oH8wyG3GSmUoHN9gkQCGwdWdWLFLJ2ekmHX6paaHtQr8WMqiJSoaouCg\",null,null,5280152],null,[[null,876437,null,null,null,null,null,\"\\u003croot\\u003e\\n \\u003ccontext\\u003e\\n \\u003c/context\\u003e\\n \\u003cinstruction\\u003e\\n \\u003cprompt\\u003eCamera pans slowly across cracked asphalt under a red burning sun.\\u003c/prompt\\u003e\\n \\u003c/instruction\\u003e\\n\\u003c/root\\u003e\",\"https://lh3.googleusercontent.com/asb/AB-nOUaV1tO8-xovmpV_inv5eoc_0bAl-yyrighrAbfO8zIk73RGamYKaeVuga4GD2bcsrLYdhKRXIt66KXFrZsejmiexvPi7-afxasqy3H7bww-Qkjmp4oH8wyG3GSmUoHN9gkQCGwdWdWLFLJ2ekmHX6paaHtQr8WMqiJSoaouCg\",null,null,null,\"veo_3_1_i2v_lite\",\"\",null,false,2],[null,null,[8]],[\"c8939cac-021c-4000-a355-ec23628e5ea0\"]]],[\"ca9eac0a-7816-4104-af03-8f98001f2915\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"d0e3e32c-df9c-4641-bce4-dd9ca73a4f9b\",\"CAE\",null,[[1790104962,53428000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUYsXiMFzL5yVqksvdhx4KnzGYCJp6UsTDwP5jhnKxaFKjYDQB6mdF-T7yCiHl3H3zd4p-jeqcajDOxceub52tl7jRl6hV0Fd-17OIpT4adugt1wAvZifAo0-GgZCAoLY0mGjuPsbs7yVYOaY5yZD9UagJKgIrt8dn3VwLP5xA\",[null,null,[[\"A wide cinematic shot of a scorched mountain range in Vietnam, 2028. 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Grounded live-action aesthetic, high dynamic range, restrained camera feel, subtle film grain.\"]]]]],[],1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUYsXiMFzL5yVqksvdhx4KnzGYCJp6UsTDwP5jhnKxaFKjYDQB6mdF-T7yCiHl3H3zd4p-jeqcajDOxceub52tl7jRl6hV0Fd-17OIpT4adugt1wAvZifAo0-GgZCAoLY0mGjuPsbs7yVYOaY5yZD9UagJKgIrt8dn3VwLP5xA\",null,null,228740],[[null,593792,null,null,null,null,null,\"A wide cinematic shot of a scorched mountain range in Vietnam, 2028. The peaks are jagged and dry, with deep shadows and brilliant, oppressive sunlight hitting the sun-baked rock faces. A lone, abandoned 2028 industrial outpost sits precariously on a ridge. Physically believable heat haze and atmospheric dust. Grounded live-action aesthetic, high dynamic range, restrained camera feel, subtle film grain.\",25,\"\",null,\"d0e3e32c-df9c-4641-bce4-dd9ca73a4f9b\",null,\"https://lh3.googleusercontent.com/asb/AB-nOUYsXiMFzL5yVqksvdhx4KnzGYCJp6UsTDwP5jhnKxaFKjYDQB6mdF-T7yCiHl3H3zd4p-jeqcajDOxceub52tl7jRl6hV0Fd-17OIpT4adugt1wAvZifAo0-GgZCAoLY0mGjuPsbs7yVYOaY5yZD9UagJKgIrt8dn3VwLP5xA\",3],null,[1376,768]]],[\"cd20c077-1f3e-4432-9bbc-6d19af7a5a16\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"420931e8-d444-4a59-8ba8-a745cbeead17\",\"CAE\",null,[[1784545966,119130000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUb6YBqsZvC6YSp7nU_rOBQxAnxihDc4VD35WLn8YcPT3q_SCJSlgwvQJ3CdE0qb91Oi2-UZwI1qqLEd2DAYspddAksc_5ENYcQOTzUX10TfAiX1LEY0Q2iQPSTWY3YP9vKJNDOzhgbkudjm8jXPdFkApTZKB-Fx9rCzHLdnBw\",[null,null,null,null,1],null,null,1,\"https://lh3.googleusercontent.com/asb/AB-nOUb6YBqsZvC6YSp7nU_rOBQxAnxihDc4VD35WLn8YcPT3q_SCJSlgwvQJ3CdE0qb91Oi2-UZwI1qqLEd2DAYspddAksc_5ENYcQOTzUX10TfAiX1LEY0Q2iQPSTWY3YP9vKJNDOzhgbkudjm8jXPdFkApTZKB-Fx9rCzHLdnBw\",null,null,368502],[null,[null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUb6YBqsZvC6YSp7nU_rOBQxAnxihDc4VD35WLn8YcPT3q_SCJSlgwvQJ3CdE0qb91Oi2-UZwI1qqLEd2DAYspddAksc_5ENYcQOTzUX10TfAiX1LEY0Q2iQPSTWY3YP9vKJNDOzhgbkudjm8jXPdFkApTZKB-Fx9rCzHLdnBw\",0],[1376,768]]],[\"ce812adb-5fef-42cb-9a38-97b2e1bac60b\",\"594758cc-11f5-4f92-8b3c-1213686591f4\",\"fb28016d-5ed3-47b0-9a38-6f98eaa8b439\",\"CAE\",null,[[1790099243,507045000],null,null,null,null,\"https://lh3.googleusercontent.com/asb/AB-nOUa57Zw_aDZZh7dEML9KwifC0P9iCfIcqGFwOpGOrXeeVr4qKEIoSLoiHYLi0b8HGFAkBvJ4lLDe8834nZVL3Vz2FMZpOKmWgjtk7dhxbULSdfKVglbE0JcrZ9l-7WKOWCfYh8Z0Bb7A7htprMxyYbipRgLnmMhTprA-P6f1\",[null,null,[[\"Real RAW photograph, shot on Canon EOS R5, 35mm lens, natural available light. 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pitch\",true,\"https://gstatic.com/aitestkitchen/voices/samples/Schedar.wav\"]]]],[\"sulafat\",3,\"Sulafat\",[\"sulafat\",null,null,null,null,null,null,null,null,null,[[\"Sulafat\",\"Female, warm, mid pitch\",true,\"https://gstatic.com/aitestkitchen/voices/samples/Sulafat.wav\"]]]],[\"umbriel\",3,\"Umbriel\",[\"umbriel\",null,null,null,null,null,null,null,null,null,[[\"Umbriel\",\"Male, smooth, lower pitch\",true,\"https://gstatic.com/aitestkitchen/voices/samples/Umbriel.wav\"]]]],[\"vindemiatrix\",3,\"Vindemiatrix\",[\"vindemiatrix\",null,null,null,null,null,null,null,null,null,[[\"Vindemiatrix\",\"Female, gentle, mid pitch\",true,\"https://gstatic.com/aitestkitchen/voices/samples/Vindemiatrix.wav\"]]]],[\"zephyr\",3,\"Zephyr\",[\"zephyr\",null,null,null,null,null,null,null,null,null,[[\"Zephyr\",\"Female, bright, mid-high 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live-action Vietnamese near-future techno-thriller.\\n\\nNON-NEGOTIABLE VISUAL RULES\\n- Live-action cinematic realism only.\\n- Authentic Vietnamese faces, Hanoi architecture, infrastructure, vehicles and everyday objects.\\n- Restrained acting and physically believable motion.\\n- Practical 2028 clothing and industrial equipment.\\n- No anime, illustration, comic, glossy game rendering, fantasy armor, magical glow, generic cyberpunk neon or holograms.\\n- Never use assets marked STORYBOARD_ONLY as identity or video Ingredients.\\n\\nPRODUCTION RULES\\n- One main action per generated clip.\\n- Never invent a new costume, injury, prop or age for an APPROVED Character.\\n- Never modify or overwrite an asset whose filename ends in APPROVED or FINAL.\\n- Exact dates, clocks, terminal text, logos and subtitles are post-production overlays; keep screens clean.\\n- Use Character references and location references exactly as named.\\n- When asked to organize, use filename prefixes and move assets to the matching Collection.\\n- Ask for confirmation before any generation that spends credits.\\n- For locked render cards, do not choose the model automatically; the user will use the standard prompt box.\\n\\nMASTER STYLE\\ngrounded live-action Vietnamese near-future techno-thriller, cinematic realism, authentic Vietnamese cast and Hanoi architecture, natural skin texture, practical 2028 clothing and industrial equipment, physically believable heat haze and sweat, restrained acting, controlled camera movement, 24 fps cinematic motion, subtle film grain, high dynamic range, no fantasy spectacle\\n\\nMASTER NEGATIVE\\nno anime, no illustration, no comic-book rendering, no glossy video-game look, no superhero armor, no magic glow, no Chinese imperial costume, no Japanese historical styling, no European medieval architecture, no generic cyberpunk neon, no holograms, no face drift, no age drift, no hairstyle drift, no costume drift, no extra fingers, no duplicated main characters, no generated readable text, no watermark\",true]]],[[null,3,2,null,\"nano_banana_pro\"],[null,2,1,null,\"abra\"]],1,1]]",null,null,null,"generic"]] -57 -[["di",695],["af.httprm",694,"3185932965805684473",25]] -28 -[["e",4,null,null,164172]] diff --git a/scripts/build_master_film.py b/scripts/build_master_film.py new file mode 100644 index 00000000..3efbdd3c --- /dev/null +++ b/scripts/build_master_film.py @@ -0,0 +1,450 @@ +#!/usr/bin/env python3 +""" +FlowKit — Multi-Chapter Cinematic Master Film Compiler +Assembles independent chapter videos into a seamless, Hollywood-grade Master Film. + +Features: +1. Dynamic Interstitial Chapter Bumpers (obsidian canvas, antique gold typography, 40-60Hz sub-bass drone). +2. Micro Ken Burns zoom (1.0x -> 1.04x) on chapter cards. +3. Dip-to-black video & audio crossfades (0.8s standard). +4. Automated YouTube Chapter Timestamps generation for video descriptions. +5. Codec-safe normalization & concatenation. + +Usage: + python scripts/build_master_film.py --project-dir output/hong_nhat_thang_long --chapters 1 2 3 4 5 + python scripts/build_master_film.py --config config/master_film_config.json +""" + +import argparse +import json +import math +import os +import re +import subprocess +import sys +from pathlib import Path + +try: + from PIL import Image, ImageDraw, ImageFont + HAS_PIL = True +except ImportError: + HAS_PIL = False + + +def run_command(cmd, desc=""): + """Execute subprocess and return success status and output.""" + if desc: + print(f" [EXEC] {desc}") + res = subprocess.run(cmd, capture_output=True, text=True) + if res.returncode != 0: + print(f" [ERROR] {res.stderr.strip()}", file=sys.stderr) + return False, res.stderr + return True, res.stdout + + +def get_media_duration(file_path): + """Retrieve media duration in seconds via ffprobe.""" + cmd = [ + 'ffprobe', '-v', 'error', + '-show_entries', 'format=duration', + '-of', 'default=noprint_wrappers=1:nokey=1', + str(file_path) + ] + res = subprocess.run(cmd, capture_output=True, text=True) + try: + return float(res.stdout.strip()) + except Exception: + return 0.0 + + +def format_timestamp(seconds): + """Convert seconds into MM:SS or HH:MM:SS format.""" + total_sec = int(round(seconds)) + hrs = total_sec // 3600 + mins = (total_sec % 3600) // 60 + secs = total_sec % 60 + if hrs > 0: + return f"{hrs:02d}:{mins:02d}:{secs:02d}" + return f"{mins:02d}:{secs:02d}" + + +def create_bumper_card_pil( + category_text, + main_title, + subtitle_text, + output_path, + width=1280, + height=720, + accent_color=(212, 175, 55), # Antique Gold + glow_color=(180, 50, 30) # Crimson Ambience +): + """Render a cinematic chapter interstitial title card using PIL.""" + img = Image.new('RGB', (width, height), color=(10, 8, 12)) + pixels = img.load() + cx, cy = width / 2.0, height / 2.0 + max_dist = math.sqrt(cx**2 + cy**2) + + for y in range(height): + for x in range(width): + dist = math.sqrt((x - cx)**2 + (y - cy)**2) / max_dist + radial = max(0.0, 1.0 - dist * 1.3) + r = int(10 + radial * glow_color[0] * 0.22) + g = int(8 + radial * glow_color[1] * 0.12) + b = int(12 + radial * glow_color[2] * 0.12) + pixels[x, y] = (min(255, r), min(255, g), min(255, b)) + + draw = ImageDraw.Draw(img) + + # Resolve fonts (with Windows fallback) + font_cat_path = 'C:/Windows/Fonts/timesbd.ttf' if os.name == 'nt' else '/usr/share/fonts/truetype/dejavu/DejaVuSerif-Bold.ttf' + font_sub_path = 'C:/Windows/Fonts/arial.ttf' if os.name == 'nt' else '/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf' + + try: + scale = height / 720.0 + font_cat = ImageFont.truetype(font_cat_path, int(26 * scale)) + font_title = ImageFont.truetype(font_cat_path, int(50 * scale)) + font_sub = ImageFont.truetype(font_sub_path, int(24 * scale)) + font_dec = ImageFont.truetype(font_cat_path, int(18 * scale)) + except Exception: + font_cat = font_title = font_sub = font_dec = ImageFont.load_default() + + y_cat = int(height * 0.35) + y_line1 = y_cat + int(35 * (height / 720.0)) + y_title = int(height * 0.50) + y_line2 = y_title + int(45 * (height / 720.0)) + y_sub = int(height * 0.65) + + # Series Header + draw.text((cx, y_cat), category_text, font=font_cat, fill=accent_color, anchor='mm') + + # Accent Dividers + line_w = int(280 * (width / 1280.0)) + draw.line([(cx - line_w, y_line1), (cx + line_w, y_line1)], fill=(120, 95, 40), width=1) + draw.text((cx, y_line1), "◆", font=font_dec, fill=accent_color, anchor='mm') + + # Main Chapter Title + draw.text((cx, y_title), main_title, font=font_title, fill=(255, 255, 255), anchor='mm') + + draw.line([(cx - line_w, y_line2), (cx + line_w, y_line2)], fill=(120, 95, 40), width=1) + draw.text((cx, y_line2), "◆", font=font_dec, fill=accent_color, anchor='mm') + + # Narrative Context / Subtitle + if subtitle_text: + draw.text((cx, y_sub), subtitle_text, font=font_sub, fill=(200, 205, 215), anchor='mm') + + # Letterbox border framing + margin_x = int(60 * (width / 1280.0)) + margin_y = int(40 * (height / 720.0)) + draw.rectangle([margin_x, margin_y, width - margin_x, height - margin_y], outline=(45, 38, 25), width=1) + draw.rectangle([margin_x + 4, margin_y + 4, width - margin_x - 4, height - margin_y - 4], outline=(25, 20, 15), width=1) + + os.makedirs(os.path.dirname(os.path.abspath(output_path)), exist_ok=True) + img.save(output_path, quality=95) + return True + + +def render_bumper_video(card_img_path, output_video_path, duration=3.5, width=1280, height=720, fps=24): + """Render a dynamic bumper video with Ken Burns micro-zoom and sub-bass brown drone.""" + if os.path.exists(output_video_path) and os.path.getsize(output_video_path) > 10000: + return True + + os.makedirs(os.path.dirname(os.path.abspath(output_video_path)), exist_ok=True) + num_frames = int(duration * fps) + + # 0.8s fade in, 1.0s fade out + fade_out_start = max(0.5, duration - 1.0) + filter_complex = ( + f"[0:v]zoompan=z='min(zoom+0.0006,1.05)':d={num_frames}:x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)':s={width}x{height}:fps={fps}," + f"fade=t=in:st=0:d=0.8,fade=t=out:st={fade_out_start:.2f}:d=1.0[vout];" + f"[1:a]lowpass=f=160,volume=3.2,afade=t=in:ss=0:d=0.8,afade=t=out:st={fade_out_start:.2f}:d=1.0[aout]" + ) + + cmd = [ + 'ffmpeg', '-y', + '-i', str(card_img_path), + '-f', 'lavfi', '-t', str(duration), '-i', f'anoisesrc=d={duration}:c=brown:r=48000:a=0.12', + '-filter_complex', filter_complex, + '-map', '[vout]', '-map', '[aout]', + '-c:v', 'libx264', '-preset', 'medium', '-crf', '18', '-pix_fmt', 'yuv420p', + '-c:a', 'aac', '-b:a', '192k', '-ar', '48000', + '-t', str(duration), + str(output_video_path) + ] + ok, _ = run_command(cmd, f"Rendering bumper video: {output_video_path}") + return ok + + +def apply_fades_to_chapter(input_video_path, output_video_path, fade_dur=0.8): + """Apply head/tail video and audio dips to black.""" + if os.path.exists(output_video_path) and os.path.getsize(output_video_path) > 10000: + return True + + dur = get_media_duration(input_video_path) + if dur <= 0: + return False + + fade_out_st = max(0.0, dur - fade_dur) + filter_complex = ( + f"[0:v]fade=t=in:st=0:d={fade_dur},fade=t=out:st={fade_out_st:.2f}:d={fade_dur}[vout];" + f"[0:a]afade=t=in:ss=0:d={fade_dur},afade=t=out:st={fade_out_st:.2f}:d={fade_dur}[aout]" + ) + + os.makedirs(os.path.dirname(os.path.abspath(output_video_path)), exist_ok=True) + cmd = [ + 'ffmpeg', '-y', + '-i', str(input_video_path), + '-filter_complex', filter_complex, + '-map', '[vout]', '-map', '[aout]', + '-c:v', 'libx264', '-preset', 'fast', '-crf', '18', '-pix_fmt', 'yuv420p', + '-c:a', 'aac', '-b:a', '192k', '-ar', '48000', + str(output_video_path) + ] + ok, _ = run_command(cmd, f"Fading chapter: {input_video_path} -> {output_video_path}") + return ok + + +def build_master_film( + project_dir, + chapters, + series_title="HỒNG NHẬT THĂNG LONG", + chapter_metadata=None, + output_master=None, + width=1280, + height=720, + fps=24, + bumper_dur=3.5, + fade_dur=0.8, + skip_bumpers=False +): + """Main orchestration function for building a master film.""" + project_path = Path(project_dir) + slug = project_path.name + temp_dir = project_path / ".master_film_cache" + temp_dir.mkdir(parents=True, exist_ok=True) + + if not output_master: + output_master = str(project_path / f"{slug}_CINEMATIC_MASTER.mp4") + + print(f"\n=======================================================") + print(f"🎬 FLOWKIT CINEMATIC MASTER FILM COMPILER") + print(f"Series: {series_title}") + print(f"Project Directory: {project_dir}") + print(f"Chapters Count: {len(chapters)}") + print(f"Output Master: {output_master}") + print(f"=======================================================\n") + + # Resolve chapter files + chapter_entries = [] + for ch in chapters: + # Check standard filename patterns + candidates = [ + project_path / f"{slug}_ch{ch}_final.mp4", + project_path / f"ch{ch}_final.mp4", + project_path / f"chapter_{ch}.mp4", + project_path / f"ch{ch}.mp4", + ] + found = None + for cand in candidates: + if cand.exists(): + found = cand + break + + if not found: + # Fallback search by pattern + matches = list(project_path.glob(f"*ch{ch}*.mp4")) + if matches: + found = matches[0] + + if not found: + print(f"❌ Error: Cannot find chapter video for chapter '{ch}' in {project_dir}", file=sys.stderr) + return False + + meta = {} + if chapter_metadata and str(ch) in chapter_metadata: + meta = chapter_metadata[str(ch)] + elif chapter_metadata and ch in chapter_metadata: + meta = chapter_metadata[ch] + + title = meta.get("title", f"CHƯƠNG {ch}") + subtitle = meta.get("subtitle", "") + chapter_entries.append({ + "chapter": ch, + "raw_video": found, + "title": title, + "subtitle": subtitle + }) + + playback_sequence = [] + current_timeline_sec = 0.0 + youtube_timestamps = [] + + # 1. Bumpers and Transitions + for idx, item in enumerate(chapter_entries, 1): + ch = item["chapter"] + raw_video = item["raw_video"] + + if not skip_bumpers: + card_img = temp_dir / f"card_ch{ch}.png" + bumper_mp4 = temp_dir / f"bumper_ch{ch}.mp4" + + if not card_img.exists(): + if HAS_PIL: + create_bumper_card_pil( + category_text=series_title, + main_title=item["title"], + subtitle_text=item["subtitle"], + output_path=str(card_img), + width=width, + height=height + ) + + render_bumper_video( + card_img_path=str(card_img), + output_video_path=str(bumper_mp4), + duration=bumper_dur, + width=width, + height=height, + fps=fps + ) + + # Record timestamp for YouTube + ts_str = format_timestamp(current_timeline_sec) + youtube_timestamps.append(f"{ts_str} - {item['title']}: {item['subtitle']}" if item['subtitle'] else f"{ts_str} - {item['title']}") + + playback_sequence.append(str(bumper_mp4)) + current_timeline_sec += bumper_dur + + # Faded chapter + faded_mp4 = temp_dir / f"ch{ch}_smooth.mp4" + apply_fades_to_chapter(str(raw_video), str(faded_mp4), fade_dur=fade_dur) + playback_sequence.append(str(faded_mp4)) + + ch_dur = get_media_duration(str(raw_video)) + current_timeline_sec += ch_dur + + # Outro Bumper if provided + outro_meta = chapter_metadata.get("outro") if chapter_metadata else None + if outro_meta and not skip_bumpers: + card_outro = temp_dir / "card_outro.png" + bumper_outro = temp_dir / "bumper_outro.mp4" + if HAS_PIL and not card_outro.exists(): + create_bumper_card_pil( + category_text=series_title, + main_title=outro_meta.get("title", "HẾT PHẦN 1"), + subtitle_text=outro_meta.get("subtitle", "Đón xem Phần 2"), + output_path=str(card_outro), + width=width, + height=height + ) + render_bumper_video(str(card_outro), str(bumper_outro), duration=bumper_dur, width=width, height=height, fps=fps) + ts_str = format_timestamp(current_timeline_sec) + youtube_timestamps.append(f"{ts_str} - {outro_meta.get('title', 'KẾT THÚC')}") + playback_sequence.append(str(bumper_outro)) + current_timeline_sec += bumper_dur + + # 2. Concat + concat_txt = temp_dir / "master_concat_list.txt" + with open(concat_txt, "w", encoding="utf-8") as f: + for p in playback_sequence: + abs_p = Path(p).resolve().as_posix() + f.write(f"file '{abs_p}'\n") + + print(f"\n[STITCH] Concatenating {len(playback_sequence)} video blocks into final master...") + cmd_concat = [ + 'ffmpeg', '-y', + '-f', 'concat', + '-safe', '0', + '-i', str(concat_txt), + '-c', 'copy', + str(output_master) + ] + ok, _ = run_command(cmd_concat, "FFmpeg stream copy concat") + if not ok: + print("Falling back to re-encoding concat...", file=sys.stderr) + cmd_concat_reencode = [ + 'ffmpeg', '-y', + '-f', 'concat', + '-safe', '0', + '-i', str(concat_txt), + '-c:v', 'libx264', '-crf', '18', '-preset', 'fast', + '-c:a', 'aac', '-b:a', '192k', + str(output_master) + ] + ok, _ = run_command(cmd_concat_reencode, "FFmpeg re-encode concat") + if not ok: + return False + + final_size_mb = os.path.getsize(output_master) / (1024 * 1024) + final_dur = get_media_duration(output_master) + + # 3. Print Results & YouTube Chapters + yt_file = project_path / f"{slug}_YOUTUBE_CHAPTERS.txt" + with open(yt_file, "w", encoding="utf-8") as f: + f.write("\n".join(youtube_timestamps)) + + print(f"\n=======================================================") + print(f"✅ CINEMATIC MASTER FILM GENERATED SUCCESSFULLY!") + print(f"Output File: {output_master}") + print(f"Total Size: {final_size_mb:.2f} MB") + print(f"Total Duration: {final_dur:.1f}s ({final_dur/60:.2f} minutes)") + print(f"YouTube Chapters File: {yt_file}") + print(f"-------------------------------------------------------") + print("📋 YouTube Chapter Timestamps for Description:") + for line in youtube_timestamps: + print(f" {line}") + print(f"=======================================================\n") + return True + + +def main(): + parser = argparse.ArgumentParser(description="FlowKit Multi-Chapter Master Film Compiler") + parser.add_argument("--project-dir", required=True, help="Directory containing chapter video files") + parser.add_argument("--chapters", nargs="+", default=["1", "2", "3", "4", "5"], help="List of chapter identifiers") + parser.add_argument("--title", default="HỒNG NHẬT THĂNG LONG", help="Series or movie main title") + parser.add_argument("--config", help="Optional JSON config file with chapter titles and subtitles") + parser.add_argument("--output", help="Output path for the master film MP4") + parser.add_argument("--resolution", default="1280x720", help="Resolution WxH (e.g. 1280x720 or 1920x1080)") + parser.add_argument("--fps", type=int, default=24, help="Target frames per second") + parser.add_argument("--bumper-duration", type=float, default=3.5, help="Duration of chapter interstitial card (sec)") + parser.add_argument("--fade-duration", type=float, default=0.8, help="Fade duration for crossfades/dips (sec)") + parser.add_argument("--no-bumpers", action="store_true", help="Skip bumper title cards") + + args = parser.parse_args() + + width, height = [int(x) for x in args.resolution.split("x")] + + chapter_meta = {} + if args.config and os.path.exists(args.config): + with open(args.config, "r", encoding="utf-8") as f: + chapter_meta = json.load(f) + + # Built-in default metadata for Hong Nhat Thang Long if not provided + if not chapter_meta and "hong_nhat" in args.project_dir.lower(): + chapter_meta = { + "1": {"title": "CHƯƠNG I: NGÀY TRỞ VỀ", "subtitle": "Tầng hầm B3 Mễ Trì — Khởi đầu chuỗi ngày sinh tồn"}, + "2": {"title": "CHƯƠNG II: NGÀY NGỌC TRẦM", "subtitle": "Bốn mươi bốn ngày trước thảm họa — Bão nhiệt 65°C tấn công"}, + "3": {"title": "CHƯƠNG III: LA PHÙ KHÔNG CÒN LỬA", "subtitle": "Ba mươi ngày trước thảm họa — Bí mật chuỗi cung ứng ngầm"}, + "4": {"title": "CHƯƠNG IV: HỒNG NHẬT GIỮA ĐÊM ĐEN", "subtitle": "Mười lăm ngày trước thảm họa — Trận chiến cống ngầm Đại Hà"}, + "5": {"title": "CHƯƠNG V: THĂNG LONG PHÒNG TUYẾN", "subtitle": "Bảy ngày trước thảm họa — Lời thề giữ đất Thăng Long"}, + "outro": {"title": "HẾT PHẦN 1 — CHUỖI 5 CHƯƠNG ĐẦU", "subtitle": "Đón xem Phần 2: Ngày Tận Thế Thăng Long"} + } + + ok = build_master_film( + project_dir=args.project_dir, + chapters=args.chapters, + series_title=args.title, + chapter_metadata=chapter_meta, + output_master=args.output, + width=width, + height=height, + fps=args.fps, + bumper_dur=args.bumper_duration, + fade_dur=args.fade_duration, + skip_bumpers=args.no_bumpers + ) + + sys.exit(0 if ok else 1) + + +if __name__ == '__main__': + main() diff --git a/scripts/generate_subtitles.py b/scripts/generate_subtitles.py new file mode 100644 index 00000000..936a4a1d --- /dev/null +++ b/scripts/generate_subtitles.py @@ -0,0 +1,282 @@ +#!/usr/bin/env python3 +""" +FlowKit — Subtitle (.srt / .vtt) Generator & Hardsub Burner +Extracts narrator text and timing from scenes or local project files to generate: +1. SubRip (.srt) subtitle files (for YouTube captions and VLC) +2. WebVTT (.vtt) subtitle files (for web players) +3. Hardsub Burning: Directly burns stylized, cinematic subtitles into video frames via FFmpeg. + +Styles: +- cinematic_gold: Antique gold text (&H0080C2E6), dark outline, elegant margins +- clean_white: Crisp white text (&H00FFFFFF), 1.8px dark outline, subtle shadow +- cyber_amber: Glowing amber text (&H0000D7FF), high-contrast outline +- emerald_hud: Military sci-fi HUD light-green (&H00C0FFC0) + +Usage: + python scripts/generate_subtitles.py --video-id --output output//subtitles.srt + python scripts/generate_subtitles.py --project-dir output/hong_nhat_thang_long --burn-subtitles --input-video output/hong_nhat_thang_long/hong_nhat_thang_long_CINEMATIC_MASTER.mp4 +""" + +import argparse +import json +import os +import re +import subprocess +import sys +import urllib.request +from pathlib import Path + + +SUBTITLE_STYLES = { + "cinematic_gold": "FontName=Arial,FontSize=20,PrimaryColour=&H0080C2E6,OutlineColour=&H0008080A,BorderStyle=1,Outline=2.0,Shadow=1.5,MarginV=35", + "clean_white": "FontName=Arial,FontSize=20,PrimaryColour=&H00FFFFFF,OutlineColour=&H00000000,BorderStyle=1,Outline=1.8,Shadow=1.0,MarginV=30", + "cyber_amber": "FontName=Arial,FontSize=20,PrimaryColour=&H0000D7FF,OutlineColour=&H00000020,BorderStyle=1,Outline=2.2,Shadow=1.5,MarginV=35", + "emerald_hud": "FontName=Arial,FontSize=20,PrimaryColour=&H00C0FFC0,OutlineColour=&H00002000,BorderStyle=1,Outline=2.0,Shadow=1.5,MarginV=35", +} + + +def format_srt_time(seconds): + """Format seconds into SRT timestamp: HH:MM:SS,mmm""" + millis = int(round((seconds - int(seconds)) * 1000)) + total_sec = int(seconds) + hrs = total_sec // 3600 + mins = (total_sec % 3600) // 60 + secs = total_sec % 60 + return f"{hrs:02d}:{mins:02d}:{secs:02d},{millis:03d}" + + +def format_vtt_time(seconds): + """Format seconds into WebVTT timestamp: HH:MM:SS.mmm""" + millis = int(round((seconds - int(seconds)) * 1000)) + total_sec = int(seconds) + hrs = total_sec // 3600 + mins = (total_sec % 3600) // 60 + secs = total_sec % 60 + return f"{hrs:02d}:{mins:02d}:{secs:02d}.{millis:03d}" + + +def wrap_subtitle_text(text, max_chars=42): + """Split long subtitle text into max 2 readable lines.""" + words = text.strip().split() + if not words: + return "" + + lines = [] + cur_line = [] + cur_len = 0 + + for w in words: + if cur_len + len(w) + (1 if cur_line else 0) > max_chars and cur_line: + lines.append(" ".join(cur_line)) + cur_line = [w] + cur_len = len(w) + else: + cur_line.append(w) + cur_len += len(w) + (1 if cur_len > 0 else 0) + + if cur_line: + lines.append(" ".join(cur_line)) + + # Return at most 2 lines per subtitle card, joined by newline + return "\n".join(lines[:2]) + + +def get_audio_duration(file_path): + """Get audio duration in seconds using ffprobe.""" + if not os.path.exists(file_path): + return 0.0 + cmd = [ + 'ffprobe', '-v', 'error', + '-show_entries', 'format=duration', + '-of', 'default=noprint_wrappers=1:nokey=1', + str(file_path) + ] + res = subprocess.run(cmd, capture_output=True, text=True) + try: + return float(res.stdout.strip()) + except Exception: + return 0.0 + + +def fetch_scenes_api(video_id, base_url="http://127.0.0.1:8100"): + """Fetch scenes for a given video_id from FlowKit API.""" + url = f"{base_url}/api/scenes?video_id={video_id}" + req = urllib.request.Request(url, headers={"User-Agent": "FlowKit-Subtitle"}) + try: + with urllib.request.urlopen(req, timeout=10) as resp: + data = json.loads(resp.read().decode("utf-8")) + return sorted(data, key=lambda s: s.get("display_order", 0)) + except Exception as e: + print(f"Error fetching scenes from API: {e}", file=sys.stderr) + return [] + + +def generate_subtitles_from_scenes(scenes, output_base, buffer_sec=0.5, default_scene_dur=8.0): + """Generate .srt and .vtt files given scene metadata list.""" + srt_entries = [] + vtt_entries = ["WEBVTT\n"] + + current_time = 0.0 + sub_index = 1 + + for sc in scenes: + narrator = sc.get("narrator_text", "").strip() + dur = sc.get("duration") or default_scene_dur + + # If there's narrator text + if narrator: + start_t = current_time + end_t = current_time + max(2.0, dur - buffer_sec) + + wrapped = wrap_subtitle_text(narrator) + + srt_entries.append( + f"{sub_index}\n" + f"{format_srt_time(start_t)} --> {format_srt_time(end_t)}\n" + f"{wrapped}\n" + ) + + vtt_entries.append( + f"{sub_index}\n" + f"{format_vtt_time(start_t)} --> {format_vtt_time(end_t)}\n" + f"{wrapped}\n" + ) + sub_index += 1 + + current_time += dur + + srt_path = output_base.with_suffix(".srt") + vtt_path = output_base.with_suffix(".vtt") + + srt_path.write_text("\n".join(srt_entries), encoding="utf-8") + vtt_path.write_text("\n".join(vtt_entries), encoding="utf-8") + + print(f"✅ Generated SRT subtitles: {srt_path} ({sub_index - 1} entries)") + print(f"✅ Generated VTT subtitles: {vtt_path}") + return srt_path, vtt_path + + +def burn_subtitles_to_video(input_video_path, srt_path, output_video_path=None, style="cinematic_gold"): + """Burn subtitles directly into video frames using FFmpeg libass subtitles filter.""" + in_p = Path(input_video_path) + if not in_p.exists(): + print(f"❌ Input video not found: {input_video_path}", file=sys.stderr) + return False + + if not output_video_path: + output_video_path = in_p.parent / f"{in_p.stem}_hardsub.mp4" + else: + output_video_path = Path(output_video_path) + + style_str = SUBTITLE_STYLES.get(style, SUBTITLE_STYLES["cinematic_gold"]) + + # Format srt path for FFmpeg filter: + # Use forward slashes and escape colon for Windows drives (e.g. D\:/path) + clean_srt = str(Path(srt_path).resolve()).replace('\\', '/') + clean_srt = clean_srt.replace(':', '\\:') + + vf = f"subtitles='{clean_srt}':force_style='{style_str}'" + + print(f"\n🎬 Burning subtitles into video: {input_video_path}") + print(f" Style: {style}") + print(f" Output: {output_video_path}") + + cmd = [ + 'ffmpeg', '-y', + '-i', str(in_p), + '-vf', vf, + '-c:v', 'libx264', '-crf', '18', '-preset', 'medium', '-pix_fmt', 'yuv420p', + '-c:a', 'copy', + str(output_video_path) + ] + + res = subprocess.run(cmd, capture_output=True, text=True) + if res.returncode != 0: + print(f"❌ Error burning subtitles: {res.stderr.strip()}", file=sys.stderr) + return False + + size_mb = os.path.getsize(output_video_path) / (1024 * 1024) + print(f"✅ Subtitles burned successfully: {output_video_path} ({size_mb:.2f} MB)") + return True + + +def main(): + parser = argparse.ArgumentParser(description="FlowKit Subtitle (.srt / .vtt) Generator & Hardsub Burner") + parser.add_argument("--video-id", help="FlowKit Video ID to fetch scenes via API") + parser.add_argument("--project-dir", help="Project output directory containing project metadata or scenes") + parser.add_argument("--output", help="Output path (without extension or .srt)") + parser.add_argument("--buffer", type=float, default=0.5, help="Audio tail buffer in seconds") + parser.add_argument("--api-url", default="http://127.0.0.1:8100", help="FlowKit base URL") + parser.add_argument("--burn-subtitles", "--burn", action="store_true", help="Burn subtitles directly into video") + parser.add_argument("--input-video", help="Input video file to burn subtitles into") + parser.add_argument("--output-video", help="Output path for video with burned subtitles") + parser.add_argument("--style", choices=list(SUBTITLE_STYLES.keys()), default="cinematic_gold", help="Visual subtitle style") + + args = parser.parse_args() + + if not args.video_id and not args.project_dir and not args.input_video: + print("Error: Either --video-id, --project-dir, or --input-video must be specified.", file=sys.stderr) + sys.exit(1) + + scenes = [] + output_base = None + + if args.video_id: + scenes = fetch_scenes_api(args.video_id, base_url=args.api_url) + if not scenes: + print(f"No scenes found for video_id {args.video_id}", file=sys.stderr) + sys.exit(1) + if args.output: + output_base = Path(args.output) + else: + output_base = Path(f"output/subtitles_{args.video_id[:8]}") + + elif args.project_dir: + proj_dir = Path(args.project_dir) + scenes_json = proj_dir / "scenes.json" + if not scenes_json.exists(): + scenes_json = proj_dir / "meta.json" + + if scenes_json.exists(): + with open(scenes_json, "r", encoding="utf-8") as f: + data = json.load(f) + scenes = data if isinstance(data, list) else data.get("scenes", []) + + if not scenes: + print(f"Could not load scenes from {proj_dir}", file=sys.stderr) + sys.exit(1) + + output_base = Path(args.output) if args.output else proj_dir / f"{proj_dir.name}_subtitles" + + srt_path = None + if scenes and output_base: + output_base.parent.mkdir(parents=True, exist_ok=True) + srt_path, _ = generate_subtitles_from_scenes(scenes, output_base, buffer_sec=args.buffer) + elif args.output and Path(args.output).exists() and Path(args.output).suffix == ".srt": + srt_path = Path(args.output) + + # If burn requested + if args.burn_subtitles: + in_vid = args.input_video + if not in_vid and args.project_dir: + proj_p = Path(args.project_dir) + # Find candidate master video + candidates = list(proj_p.glob("*CINEMATIC_MASTER.mp4")) + list(proj_p.glob("*final.mp4")) + if candidates: + in_vid = str(candidates[0]) + + if not in_vid: + print("Error: --burn-subtitles requires --input-video or an existing master video in --project-dir", file=sys.stderr) + sys.exit(1) + + if not srt_path: + print("Error: No SRT subtitle file found to burn.", file=sys.stderr) + sys.exit(1) + + ok = burn_subtitles_to_video(in_vid, srt_path, output_video_path=args.output_video, style=args.style) + if not ok: + sys.exit(1) + + +if __name__ == '__main__': + main() diff --git a/scripts/series_manifest.py b/scripts/series_manifest.py new file mode 100644 index 00000000..69f1f8ae --- /dev/null +++ b/scripts/series_manifest.py @@ -0,0 +1,230 @@ +#!/usr/bin/env python3 +""" +FlowKit — Batch Episode Series Manifest Manager +Manages per-project series manifests (`output//series_manifest.json`). + +Features: +1. Per-Project Manifest Architecture: Each project stores its own `series_manifest.json` + directly inside `output//series_manifest.json`. +2. Automatic Synchronization: Automatically generated and kept in sync with FlowKit backend. +3. `sync` / `export`: Generates or pulls the latest manifest from FlowKit API into `output//series_manifest.json`. +4. `show`: Renders an overview table of characters, locations, and episode progress. +5. `bootstrap`: Creates a new chapter in FlowKit API reusing pre-existing shared entity UUIDs. + +Usage: + python scripts/series_manifest.py sync --project-id + python scripts/series_manifest.py show --project-dir output/hong_nhat_thang_long + python scripts/series_manifest.py bootstrap --project-dir output/hong_nhat_thang_long --episode 6 --title "Chương VI: Huyết Nguyệt" +""" + +import argparse +import json +import os +import sys +import urllib.request +from pathlib import Path + + +def api_request(url, method="GET", payload=None): + """Perform JSON HTTP request against FlowKit API.""" + data = None + headers = {"User-Agent": "FlowKit-SeriesManifest"} + if payload is not None: + data = json.dumps(payload).encode("utf-8") + headers["Content-Type"] = "application/json" + + req = urllib.request.Request(url, data=data, headers=headers, method=method) + try: + with urllib.request.urlopen(req, timeout=15) as resp: + content = resp.read().decode("utf-8") + return json.loads(content) if content else {} + except urllib.error.HTTPError as e: + err_msg = e.read().decode("utf-8") if e.fp else str(e) + print(f"API Error ({e.code}) on {url}: {err_msg}", file=sys.stderr) + return None + except Exception as e: + print(f"Connection Error on {url}: {e}", file=sys.stderr) + return None + + +def resolve_manifest_path(project_dir=None, project_id=None, manifest=None, base_url="http://127.0.0.1:8100"): + """Resolve the path to the per-project series_manifest.json.""" + if manifest: + return Path(manifest) + + if project_dir: + p_dir = Path(project_dir) + return p_dir / "series_manifest.json" + + if project_id: + # Fetch output-dir from API + res = api_request(f"{base_url}/api/projects/{project_id}/output-dir") + if res and "path" in res: + return Path(res["path"]) / "series_manifest.json" + + # Default fallback: check common project directory + candidates = list(Path("output").glob("*/series_manifest.json")) + if candidates: + return candidates[0] + + return Path("output/default/series_manifest.json") + + +def sync_from_project_api(project_id, base_url="http://127.0.0.1:8100"): + """Trigger API to auto-generate and return per-project series_manifest.json.""" + print(f"🔄 Syncing series manifest from API for project {project_id}...") + manifest_data = api_request(f"{base_url}/api/projects/{project_id}/manifest") + if not manifest_data: + print(f"❌ Failed to sync manifest for project {project_id}", file=sys.stderr) + return False + + slug = manifest_data.get("slug", "project") + target_path = Path(f"output/{slug}/series_manifest.json") + print(f"✅ Series manifest automatically synced and saved to: {target_path}") + print(f" Title: {manifest_data.get('series_title')}") + print(f" Characters: {len(manifest_data.get('shared_entities', {}).get('characters', []))}") + print(f" Locations: {len(manifest_data.get('shared_entities', {}).get('locations', []))}") + print(f" Episodes: {len(manifest_data.get('episodes', []))}") + return True + + +def show_manifest(manifest_path): + """Print an overview of the series manifest.""" + m_path = Path(manifest_path) + if not m_path.exists(): + print(f"❌ Manifest not found at: {manifest_path}", file=sys.stderr) + return False + + data = json.loads(m_path.read_text(encoding="utf-8")) + print("\n=======================================================") + print(f"📚 PER-PROJECT SERIES MANIFEST: {data.get('series_title')}") + print(f"Location: {m_path}") + print(f"Slug: {data.get('slug')}") + print(f"Material: {data.get('material')}") + print(f"Orientation: {data.get('orientation')}") + print(f"Default TTS: {data.get('default_voice')}") + print("=======================================================\n") + + chars = data.get("shared_entities", {}).get("characters", []) + print(f"🎭 Shared Characters ({len(chars)}):") + for c in chars: + m_id = c.get("media_id", "NO MEDIA ID") + print(f" • {c.get('name'):<22} | UUID: {m_id}") + + locs = data.get("shared_entities", {}).get("locations", []) + print(f"\n🏛️ Shared Locations ({len(locs)}):") + for l in locs: + m_id = l.get("media_id", "NO MEDIA ID") + print(f" • {l.get('name'):<25} | UUID: {m_id}") + + episodes = data.get("episodes", []) + print(f"\n🎬 Episode Roadmap ({len(episodes)} episodes):") + for ep in episodes: + num = ep.get("episode", "?") + title = ep.get("title", "") + status = ep.get("status", "PLANNING") + vid_id = ep.get("video_id", "N/A")[:8] + print(f" [{status:<10}] Ep {num:<2}: {title:<35} (VID: {vid_id})") + + print("=======================================================\n") + return True + + +def bootstrap_episode(manifest_path, episode_num, episode_title, base_url="http://127.0.0.1:8100"): + """Create a new chapter project in FlowKit with all shared entities pre-linked.""" + m_path = Path(manifest_path) + if not m_path.exists(): + print(f"❌ Manifest not found: {manifest_path}", file=sys.stderr) + return False + + data = json.loads(m_path.read_text(encoding="utf-8")) + series_title = data.get("series_title", "Series") + material = data.get("material", "realistic") + + project_name = f"{series_title} — Ep {episode_num}: {episode_title}" + story_summary = f"Episode {episode_num} of {series_title}. {data.get('story_bible', '')}" + + all_entities = [] + shared = data.get("shared_entities", {}) + for cat in ["characters", "locations", "key_props"]: + for item in shared.get(cat, []): + all_entities.append({ + "name": item.get("name"), + "description": item.get("description"), + "entity_type": item.get("entity_type", "character"), + "image_prompt": item.get("image_prompt"), + "media_id": item.get("media_id") # Reuses existing UUID! + }) + + payload = { + "name": project_name, + "story": story_summary, + "material": material, + "entities": all_entities + } + + print(f"\n🚀 Bootstrapping new episode project via API:") + print(f" Name: {project_name}") + print(f" Reusing {len(all_entities)} shared entity references...") + + res = api_request(f"{base_url}/api/projects", method="POST", payload=payload) + if not res or "id" not in res: + print("Failed to create project in FlowKit API", file=sys.stderr) + return False + + new_pid = res["id"] + print(f"✅ Episode project created successfully!") + print(f" Project ID: {new_pid}") + print(f" Pre-linked entities: {len(res.get('characters', []))}") + + # Auto-initialize output directory and project manifest + api_request(f"{base_url}/api/projects/{new_pid}/output-dir") + + print(f"\nNext Steps:") + print(f" 1. Create video: POST /api/videos (project_id={new_pid})") + print(f" 2. Create scenes: POST /api/scenes (using character_names)") + print(f" 3. Skip ref generation! All shared entities already have media_ids.") + return True + + +def main(): + parser = argparse.ArgumentParser(description="FlowKit Per-Project Series Manifest Manager") + subparsers = parser.add_subparsers(dest="command", required=True) + + # sync + p_sync = subparsers.add_parser("sync", help="Auto-sync series_manifest.json from FlowKit API") + p_sync.add_argument("--project-id", required=True, help="FlowKit project ID to sync") + p_sync.add_argument("--api-url", default="http://127.0.0.1:8100", help="FlowKit base URL") + + # show + p_show = subparsers.add_parser("show", help="Display manifest summary") + p_show.add_argument("--project-dir", help="Project directory (e.g. output/hong_nhat_thang_long)") + p_show.add_argument("--project-id", help="Project ID") + p_show.add_argument("--manifest", help="Direct path to series_manifest.json") + p_show.add_argument("--api-url", default="http://127.0.0.1:8100", help="FlowKit base URL") + + # bootstrap + p_boot = subparsers.add_parser("bootstrap", help="Create new episode project reusing shared entities") + p_boot.add_argument("--project-dir", help="Source project directory (e.g. output/hong_nhat_thang_long)") + p_boot.add_argument("--manifest", help="Direct path to series_manifest.json") + p_boot.add_argument("--episode", type=int, required=True, help="Episode number (e.g. 6)") + p_boot.add_argument("--title", required=True, help="Episode title") + p_boot.add_argument("--api-url", default="http://127.0.0.1:8100", help="FlowKit base URL") + + args = parser.parse_args() + + if args.command == "sync": + ok = sync_from_project_api(args.project_id, base_url=args.api_url) + sys.exit(0 if ok else 1) + elif args.command == "show": + m_path = resolve_manifest_path(project_dir=args.project_dir, project_id=args.project_id, manifest=args.manifest, base_url=args.api_url) + ok = show_manifest(m_path) + sys.exit(0 if ok else 1) + elif args.command == "bootstrap": + m_path = resolve_manifest_path(project_dir=args.project_dir, manifest=args.manifest, base_url=args.api_url) + ok = bootstrap_episode(m_path, args.episode, args.title, base_url=args.api_url) + sys.exit(0 if ok else 1) + + +if __name__ == '__main__': + main() diff --git a/scripts/sfx_layering.py b/scripts/sfx_layering.py new file mode 100644 index 00000000..bd111c96 --- /dev/null +++ b/scripts/sfx_layering.py @@ -0,0 +1,262 @@ +#!/usr/bin/env python3 +""" +FlowKit — Audio SFX & Foley Layering Engine +Analyzes scene actions, video prompts, and descriptions to procedurally synthesize +and mix appropriate sound effects (metal clashing, underground rumbling, impacts, sirens, heartbeat). + +Features: +1. Zero-dependency procedural audio synthesis using FFmpeg lavfi filters. +2. Local asset override: Checks `assets/sfx//` for user-provided studio WAV samples. +3. Sub-clip timeline synchronization (detects 0-3s, 3-6s, 6-8s action triggers). +4. Audio mastering with dynamic limiting and ducking to preserve narrator intelligibility. + +Usage: + python scripts/sfx_layering.py --input-video input.mp4 --prompt "Tactical knife thrust against concrete" --output output_sfx.mp4 + python scripts/sfx_layering.py --video-id --scene-id +""" + +import argparse +import json +import os +import re +import subprocess +import sys +from pathlib import Path + +ROOT = Path(__file__).resolve().parent.parent +ASSETS_SFX_DIR = ROOT / "assets" / "sfx" + +# Action sound design mapping +KEYWORD_SFX_MAP = { + "metal_clash": { + "keywords": ["knife", "blade", "sword", "dao", "kiếm", "chém", "kim loại", "clash", "steel", "vũ khí"], + "desc": "Metallic blade impact / sword clash", + "synth": "aevalsrc=sin(2*PI*1200*t)*exp(-12*t)+sin(2*PI*2400*t)*exp(-16*t):d=0.8:s=48000,volume=1.8" + }, + "heavy_impact": { + "keywords": ["strike", "slam", "punch", "ngã", "đấm", "va chạm", "thud", "gục", "va đập", "impact", "knock"], + "desc": "Low-end punch / physical blunt impact", + "synth": "aevalsrc=sin(2*PI*65*t)*exp(-7*t)+0.4*sin(2*PI*130*t)*exp(-10*t):d=1.0:s=48000,volume=2.5" + }, + "explosion_blast": { + "keywords": ["explosion", "blast", "nổ", "bomb", "bom", "lựu đạn", "shockwave", "sóng xung kích", "detonate"], + "desc": "Deep detonation / explosion burst", + "synth": "anoisesrc=d=2.5:c=brown:r=48000:a=0.8,lowpass=f=140,volume=3.0,afade=t=out:st=1.0:d=1.5" + }, + "underground_drone": { + "keywords": ["tầng hầm", "b3", "cống ngầm", "underground", "tunnel", "hầm", "bóng tối", "mễ trì"], + "desc": "Subterranean ambient drone / 45Hz room tone", + "synth": "anoisesrc=d=8.0:c=brown:r=48000:a=0.25,lowpass=f=90,volume=1.4" + }, + "alarm_siren": { + "keywords": ["báo động", "siren", "alarm", "klaxon", "còi báo", "nguy hiểm", "emergency"], + "desc": "Modulated tactical warning siren", + "synth": "aevalsrc=sin(2*PI*(750+200*sin(2*PI*1.5*t))*t):d=4.0:s=48000,volume=0.8" + }, + "heartbeat_tension": { + "keywords": ["tim đập", "nghẹt thở", "tension", "gasping", "thở dốc", "lo sợ", "heartbeat", "hồi hộp"], + "desc": "60 BPM physiological heartbeat pulse", + "synth": "aevalsrc=sin(2*PI*55*t)*exp(-8*mod(t\\,1.0)):d=6.0:s=48000,lowpass=f=120,volume=2.5" + }, + "fire_crackle": { + "keywords": ["cháy", "lửa", "burning", "flames", "hỏa hoạn", "rực lửa", "tàn lửa", "embers"], + "desc": "Subtle acoustic fire crackle", + "synth": "anoisesrc=d=8.0:c=pink:r=48000:a=0.2,bandpass=f=2500:w=1200,volume=0.6" + } +} + + +def detect_sfx_events(text): + """Scan text for sound design triggers and estimate timing.""" + text_lower = text.lower() + events = [] + + # Detect subclip timing blocks if present: 0-3s, 3-6s, 6-8s + segments = [ + ("0-3s", 0.0, 3.0, 1.0), + ("3-6s", 3.0, 6.0, 3.8), + ("6-8s", 6.0, 8.0, 6.2), + ] + + found_in_segments = False + for seg_label, start_s, end_s, default_t in segments: + m = re.search(rf'{seg_label}:?\s*([^.\n]+)', text_lower) + if m: + found_in_segments = True + seg_text = m.group(1) + for category, data in KEYWORD_SFX_MAP.items(): + if any(kw in seg_text for kw in data["keywords"]): + events.append({ + "category": category, + "time_offset": default_t, + "desc": data["desc"], + "source": f"Segment {seg_label}" + }) + + # If no segmented prompt, scan whole text + if not found_in_segments: + for category, data in KEYWORD_SFX_MAP.items(): + if any(kw in text_lower for kw in data["keywords"]): + events.append({ + "category": category, + "time_offset": 1.5, + "desc": data["desc"], + "source": "Full text keyword" + }) + + return events + + +def synthesize_sfx_track(events, total_duration, output_wav_path): + """Synthesize and mix an audio track containing all detected SFX events.""" + os.makedirs(os.path.dirname(os.path.abspath(output_wav_path)), exist_ok=True) + + if not events: + # Generate silent track + cmd = [ + 'ffmpeg', '-y', + '-f', 'lavfi', '-t', str(total_duration), + '-i', 'anullsrc=r=48000:cl=stereo', + '-c:a', 'pcm_s16le', + str(output_wav_path) + ] + subprocess.run(cmd, capture_output=True, text=True) + return True + + inputs = [] + filter_chains = [] + mix_labels = [] + + # 1. Base silence canvas + inputs.extend(['-f', 'lavfi', '-t', str(total_duration), '-i', 'anullsrc=r=48000:cl=stereo']) + mix_labels.append("[0:a]") + + for idx, ev in enumerate(events, 1): + cat = ev["category"] + delay_ms = int(ev["time_offset"] * 1000) + sfx_config = KEYWORD_SFX_MAP[cat] + + # Check local sample override + local_sample = None + if ASSETS_SFX_DIR.exists(): + cat_dir = ASSETS_SFX_DIR / cat + if cat_dir.exists(): + samples = list(cat_dir.glob("*.wav")) + list(cat_dir.glob("*.mp3")) + if samples: + local_sample = samples[0] + + if local_sample: + inputs.extend(['-i', str(local_sample)]) + filter_chains.append(f"[{idx}:a]adelay={delay_ms}|{delay_ms},volume=0.9[sfx{idx}]") + else: + synth_expr = sfx_config["synth"] + inputs.extend(['-f', 'lavfi', '-i', synth_expr]) + filter_chains.append(f"[{idx}:a]adelay={delay_ms}|{delay_ms}[sfx{idx}]") + + mix_labels.append(f"[sfx{idx}]") + + num_inputs = len(mix_labels) + all_inputs_str = "".join(mix_labels) + filter_complex = ";".join(filter_chains) + if filter_complex: + filter_complex += f";{all_inputs_str}amix=inputs={num_inputs}:duration=first:dropout_transition=2,alimiter=limit=0.95[aout]" + else: + filter_complex = f"{all_inputs_str}amix=inputs={num_inputs}:duration=first[aout]" + + cmd = [ + 'ffmpeg', '-y', + *inputs, + '-filter_complex', filter_complex, + '-map', '[aout]', + '-c:a', 'pcm_s16le', + '-t', str(total_duration), + str(output_wav_path) + ] + res = subprocess.run(cmd, capture_output=True, text=True) + if res.returncode != 0: + print(f"Error synthesizing SFX track: {res.stderr.strip()}", file=sys.stderr) + return False + return True + + +def apply_sfx_to_video(input_video_path, prompt_text, output_video_path=None, sfx_volume=0.6): + """Extract prompt cues, synthesize SFX, and mix into video audio.""" + in_p = Path(input_video_path) + if not in_p.exists(): + print(f"Input video not found: {input_video_path}", file=sys.stderr) + return False + + if not output_video_path: + output_video_path = in_p.parent / f"{in_p.stem}_sfx.mp4" + else: + output_video_path = Path(output_video_path) + + # Get duration + cmd_dur = ['ffprobe', '-v', 'error', '-show_entries', 'format=duration', '-of', 'default=noprint_wrappers=1:nokey=1', str(in_p)] + dur_res = subprocess.run(cmd_dur, capture_output=True, text=True) + try: + dur = float(dur_res.stdout.strip()) + except Exception: + dur = 8.0 + + events = detect_sfx_events(prompt_text) + print(f"\n🎧 Sound Design Analysis for: {in_p.name}") + print(f" Duration: {dur:.2f}s") + print(f" Detected SFX Cues: {len(events)}") + for ev in events: + print(f" - [{ev['time_offset']:.1f}s] {ev['category']}: {ev['desc']} ({ev['source']})") + + temp_sfx_wav = in_p.parent / f"temp_sfx_{in_p.stem}.wav" + if not synthesize_sfx_track(events, dur, temp_sfx_wav): + return False + + # Check if input video has an audio stream + cmd_has_audio = ['ffprobe', '-v', 'error', '-select_streams', 'a', '-show_entries', 'stream=codec_type', '-of', 'default=noprint_wrappers=1:nokey=1', str(in_p)] + has_audio = bool(subprocess.run(cmd_has_audio, capture_output=True, text=True).stdout.strip()) + + if has_audio: + filter_complex = f"[0:a]volume=1.0[orig];[1:a]volume={sfx_volume}[sfx];[orig][sfx]amix=inputs=2:duration=first[aout]" + map_audio = '[aout]' + else: + filter_complex = f"[1:a]volume={sfx_volume}[aout]" + map_audio = '[aout]' + + cmd_mix = [ + 'ffmpeg', '-y', + '-i', str(in_p), + '-i', str(temp_sfx_wav), + '-filter_complex', filter_complex, + '-map', '0:v', + '-map', map_audio, + '-c:v', 'copy', + '-c:a', 'aac', '-b:a', '192k', '-ar', '48000', + str(output_video_path) + ] + res_mix = subprocess.run(cmd_mix, capture_output=True, text=True) + + # Cleanup temp wav + if temp_sfx_wav.exists(): + temp_sfx_wav.unlink() + + if res_mix.returncode != 0: + print(f"Error mixing SFX with video: {res_mix.stderr.strip()}", file=sys.stderr) + return False + + print(f"✅ Video with Foley/SFX generated: {output_video_path}") + return True + + +def main(): + parser = argparse.ArgumentParser(description="FlowKit Audio SFX & Foley Layering Engine") + parser.add_argument("--input-video", required=True, help="Path to input scene or chapter video") + parser.add_argument("--prompt", required=True, help="Scene prompt or action description to extract sound cues") + parser.add_argument("--output", help="Output path for final video with SFX") + parser.add_argument("--volume", type=float, default=0.6, help="SFX mix volume relative to main audio (default: 0.6)") + + args = parser.parse_args() + ok = apply_sfx_to_video(args.input_video, args.prompt, args.output, sfx_volume=args.volume) + sys.exit(0 if ok else 1) + + +if __name__ == '__main__': + main() diff --git a/scripts/sync_skills.py b/scripts/sync_skills.py new file mode 100644 index 00000000..e32b94af --- /dev/null +++ b/scripts/sync_skills.py @@ -0,0 +1,74 @@ +#!/usr/bin/env python3 +""" +Sync skills from skills/fk-*.md to: +1. .agents/skills/fk-/SKILL.md (for Antigravity IDE) +2. .claude/commands/fk-.md (for Claude Code) +3. AGENTS.md (for Codex CLI) +""" + +import re +from pathlib import Path + +ROOT = Path(__file__).resolve().parent.parent +SKILLS_DIR = ROOT / "skills" +AGENTS_SKILLS_DIR = ROOT / ".agents" / "skills" + +def discover_skills(): + skills = [] + for path in sorted(SKILLS_DIR.glob("fk-*.md")): + name = path.stem[len("fk-"):] + content = path.read_text(encoding="utf-8") + + # Check description + desc = "" + for line in content.splitlines(): + line = line.strip() + if line and not line.startswith("---"): + desc = re.sub(r'^[#\s\-*]+', '', line).strip() + break + if not desc: + desc = f"{name} workflow skill" + + skills.append({"name": name, "description": desc, "path": path, "content": content}) + return skills + +def sync_antigravity(skills): + AGENTS_SKILLS_DIR.mkdir(parents=True, exist_ok=True) + count = 0 + for s in skills: + name = s["name"] + skill_id = f"fk-{name}" + desc = s["description"].replace("'", "''").replace("\n", " ").strip() + content = s["content"] + + # Strip existing frontmatter if any + if content.startswith("---"): + parts = content.split("---", 2) + if len(parts) >= 3: + body = parts[2].lstrip() + else: + body = content + else: + body = content + + dest_dir = AGENTS_SKILLS_DIR / skill_id + dest_dir.mkdir(parents=True, exist_ok=True) + dest_file = dest_dir / "SKILL.md" + + skill_md = ( + f"---\n" + f"name: {skill_id}\n" + f"description: '{desc}'\n" + f"---\n\n" + f"{body}\n" + ) + dest_file.write_text(skill_md, encoding="utf-8") + count += 1 + print(f" [OK] .agents/skills/{skill_id}/SKILL.md") + print(f"Synchronized {count} skills to Antigravity (.agents/skills/)") + return count + +if __name__ == "__main__": + skills = discover_skills() + print(f"Discovered {len(skills)} skills in skills/") + sync_antigravity(skills) diff --git a/scripts/validate_skills.py b/scripts/validate_skills.py new file mode 100644 index 00000000..2b154456 --- /dev/null +++ b/scripts/validate_skills.py @@ -0,0 +1,113 @@ +#!/usr/bin/env python3 +""" +FlowKit — Skills Validator & Quality Assurance Linter +Validates the entire skill suite to enforce: +1. 100% unified English language purity across all instructions. +2. Heading and metadata consistency. +3. Cross-reference markdown link validity. +4. Sync parity between skills/, .agents/skills/, and .claude/commands/. +""" + +import re +import sys +from pathlib import Path + +ROOT = Path(__file__).resolve().parent.parent +SKILLS_DIR = ROOT / "skills" +AGENTS_SKILLS_DIR = ROOT / ".agents" / "skills" +CLAUDE_COMMANDS_DIR = ROOT / ".claude" / "commands" + +# Vietnamese instructional keywords that should NEVER appear as instructions +VI_INSTRUCTIONAL_PATTERN = re.compile( + r'\b(hướng dẫn|thực hiện|lưu ý|yêu cầu|bước 1|bước 2|bước 3|bước 4|bước 5|' + r'tổng quan|cách dùng|chú ý|kiểm tra|thiết lập|kịch bản|nhân vật|chuyển cảnh)\b', + re.IGNORECASE +) + + +def validate_skills(): + print("=======================================================") + print("🔍 FLOWKIT SKILLS QUALITY ASSURANCE VALIDATOR") + print("=======================================================\n") + + skill_files = sorted(SKILLS_DIR.glob("fk-*.md")) + print(f"Discovered {len(skill_files)} skill files in {SKILLS_DIR}") + + errors = [] + warnings = [] + + for path in skill_files: + name = path.name + content = path.read_text(encoding="utf-8") + lines = content.splitlines() + + # 1. Heading check + if not lines or not (lines[0].startswith("#") or (len(lines) > 1 and lines[1].startswith("#")) or lines[0].strip()): + warnings.append(f"[{name}] Missing top header or description.") + + # 2. Check for mixed Vietnamese instruction text (ignoring explicit quotes/code blocks containing data) + in_code_block = False + for line_idx, line in enumerate(lines, 1): + if line.strip().startswith("```"): + in_code_block = not in_code_block + continue + + # Skip code blocks and lines that are explicit sample quotes or dialogue examples + if in_code_block or '"' in line or '“' in line or '`' in line: + continue + + vi_match = VI_INSTRUCTIONAL_PATTERN.search(line) + if vi_match: + errors.append(f"[{name}:L{line_idx}] Mixed Vietnamese keyword in instruction: '{vi_match.group(0)}'") + + # 3. Check markdown links + links = re.findall(r'\[([^\]]+)\]\(([^)]+)\)', content) + for link_text, link_target in links: + if link_target.startswith("http") or link_target.startswith("#") or link_target.startswith("mailto:"): + continue + # Strip anchors + target_file = link_target.split("#")[0] + if target_file: + target_path = (SKILLS_DIR / target_file).resolve() + if not target_path.exists(): + # check relative to project root + if not (ROOT / target_file).resolve().exists(): + warnings.append(f"[{name}] Broken markdown link: '{link_target}'") + + # 4. Check sync parity + antigravity_skills = list(AGENTS_SKILLS_DIR.glob("fk-*/SKILL.md")) if AGENTS_SKILLS_DIR.exists() else [] + claude_commands = list(CLAUDE_COMMANDS_DIR.glob("fk-*.md")) if CLAUDE_COMMANDS_DIR.exists() else [] + + print(f"\nTool Sync Parity Check:") + print(f" skills/ Source: {len(skill_files)}") + print(f" .agents/skills/ (AGY): {len(antigravity_skills)}") + print(f" .claude/commands/ (Claude): {len(claude_commands)}") + + if len(skill_files) != len(antigravity_skills): + errors.append(f"Antigravity sync mismatch: {len(skill_files)} vs {len(antigravity_skills)}. Run 'python setup.py sync'.") + + if len(skill_files) != len(claude_commands): + errors.append(f"Claude sync mismatch: {len(skill_files)} vs {len(claude_commands)}. Run 'python setup.py sync'.") + + print("\n-------------------------------------------------------") + if warnings: + print(f"⚠️ {len(warnings)} Warnings:") + for w in warnings: + print(f" - {w}") + else: + print("✅ No warnings detected.") + + if errors: + print(f"\n❌ {len(errors)} Errors Found:") + for e in errors: + print(f" - {e}") + print("\nValidator FAILED.") + return False + else: + print("\n✅ All 41 skills passed quality validation! 100% English compliant.") + return True + + +if __name__ == '__main__': + ok = validate_skills() + sys.exit(0 if ok else 1) diff --git a/setup.py b/setup.py index 15ea3507..08dd54ec 100644 --- a/setup.py +++ b/setup.py @@ -35,6 +35,7 @@ SKILLS_DIR = ROOT / "skills" CLAUDE_COMMANDS_DIR = ROOT / ".claude" / "commands" AGENTS_MD = ROOT / "AGENTS.md" +ANTIGRAVITY_SKILLS_DIR = ROOT / ".agents" / "skills" STATE_FILE = ROOT / ".fk-setup.json" # Nothing generates these any more; `clean` still removes them so an install @@ -84,6 +85,46 @@ def generate_claude(skills): return count +def generate_antigravity(skills): + """Create .agents/skills/fk-/SKILL.md for Antigravity IDE.""" + ANTIGRAVITY_SKILLS_DIR.mkdir(parents=True, exist_ok=True) + count = 0 + for skill in skills: + name = skill["name"] + skill_id = f"fk-{name}" + desc = skill["description"] + src = Path(skill["path"]) + content = src.read_text(encoding="utf-8") + + # Strip existing frontmatter if any + if content.startswith("---"): + parts = content.split("---", 2) + if len(parts) >= 3: + body = parts[2].lstrip() + else: + body = content + else: + body = content + + dest_dir = ANTIGRAVITY_SKILLS_DIR / skill_id + dest_dir.mkdir(parents=True, exist_ok=True) + dest = dest_dir / "SKILL.md" + + escaped_desc = desc.replace("'", "''").replace("\n", " ").strip() + skill_md = ( + f"---\n" + f"name: {skill_id}\n" + f"description: '{escaped_desc}'\n" + f"---\n\n" + f"{body}\n" + ) + dest.write_text(skill_md, encoding="utf-8") + count += 1 + print(f"Generated {count} Antigravity skills in .agents/skills/") + return count + + + ## ── Inline content for AGENTS.md ── # Inlined so a non-Claude tool sees the rules directly instead of following a # "read CLAUDE.md" pointer. @@ -221,6 +262,7 @@ def load_state(): TOOLS = { "claude": generate_claude, "codex": generate_codex, + "antigravity": generate_antigravity, } @@ -241,20 +283,18 @@ def do_interactive(skills): """Interactive mode: prompt user to pick tools.""" print("\nFlow Kit — AI Tool Setup\n") print("Which AI tool do you drive this project from?") - print(" [1] Claude Code (.claude/commands/)") - print(" [2] Codex CLI (AGENTS.md)") - print(" [3] Both") - print() - print(" (agy / Antigravity reads none of these — it is configured as a") - print(" video-review provider instead, via /fk-change-provider.)") + print(" [1] Claude Code (.claude/commands/)") + print(" [2] Codex CLI (AGENTS.md)") + print(" [3] Antigravity IDE (.agents/skills/)") + print(" [4] All tools") print() - raw = input("Select (comma-separated, e.g. 1,2): ").strip() + raw = input("Select (comma-separated, e.g. 1,2,3): ").strip() if not raw: print("No selection made. Exiting.") return - mapping = {"1": "claude", "2": "codex", "3": "all"} + mapping = {"1": "claude", "2": "codex", "3": "antigravity", "4": "all"} choices = [c.strip() for c in raw.split(",")] tools = [] @@ -315,6 +355,15 @@ def do_clean(): f.unlink() removed.append(str(f)) + # Antigravity skills + if ANTIGRAVITY_SKILLS_DIR.exists(): + for d in ANTIGRAVITY_SKILLS_DIR.glob("fk-*"): + if d.is_dir(): + for f in d.glob("*"): + f.unlink() + d.rmdir() + removed.append(str(d)) + # Whatever the retired Gemini target left behind. Removed here even # though nothing writes it any more — an install from before v1.3.1 has # these files, and `clean` is the only thing that will ever take them away. diff --git a/skills/README.md b/skills/README.md index 257a4df2..5da9f8ae 100644 --- a/skills/README.md +++ b/skills/README.md @@ -2,37 +2,76 @@ Workflow skills for AI agents and humans. Each skill is a step-by-step recipe. -## Pipeline (run in order) +## Core Production Pipeline | # | Skill | File | Description | |---|-------|------|-------------| -| 1 | `fk-create-project` | [fk-create-project.md](fk-create-project.md) | Create project + entities + video + scenes | -| 2 | `fk-gen-refs` | [fk-gen-refs.md](fk-gen-refs.md) | Generate reference images for all entities | -| 3 | `fk-gen-images` | [fk-gen-images.md](fk-gen-images.md) | Generate scene images with character refs | -| 4 | `fk-gen-videos` | [fk-gen-videos.md](fk-gen-videos.md) | Generate videos from scene images | -| 5 | `fk-concat` | [fk-concat.md](fk-concat.md) | Download + merge all scene videos | +| 0 | `fk-research` | [fk-research.md](fk-research.md) | Fact-check events and research historical/story lore before scripting | +| 1 | `fk-scriptwriter` | [fk-scriptwriter.md](fk-scriptwriter.md) | The Ultimate AI Screenplay Bible (10 Archetypes, 8s Arcs, Quality Gates) | +| 2 | `fk-create-project` | [fk-create-project.md](fk-create-project.md) | Create project + entities + video + scenes | +| 3 | `fk-gen-refs` | [fk-gen-refs.md](fk-gen-refs.md) | Generate reference images for all entities | +| 4 | `fk-gen-images` | [fk-gen-images.md](fk-gen-images.md) | Generate scene images with character refs bound | +| 5 | `fk-gen-videos` | [fk-gen-videos.md](fk-gen-videos.md) | Generate videos from scene images via Veo 3 / Flow | +| 6 | `fk-review-video` | [fk-review-video.md](fk-review-video.md) | AI Vision quality check with prompt healing loop (pass score >= 7.5) | +| 7 | `fk-concat-fit-narrator` | [fk-concat-fit-narrator.md](fk-concat-fit-narrator.md) | Trim scene videos to TTS duration, burn hardsubs, assemble multi-chapter film | +| 8 | `fk-concat` | [fk-concat.md](fk-concat.md) | Download + merge all scene videos (basic stream concat) | + +## Cinematography, Direction & Choreography -## Advanced Video +| Skill | File | Description | +|-------|------|-------------| +| `fk-camera-guide` | [fk-camera-guide.md](fk-camera-guide.md) | Lens packages, Hollywood lighting & color grading matrix, 180° rule | +| `fk-action-choreography` | [fk-action-choreography.md](fk-action-choreography.md) | Physics-safe combat direction & 3-phase motion invariants for Veo 3 | +| `fk-cinematic-transitions` | [fk-cinematic-transitions.md](fk-cinematic-transitions.md) | Chapter bumpers (Ken Burns + sub-bass drone), match cuts, J-cut/L-cut | +| `fk-gen-chain-videos` | [fk-gen-chain-videos.md](fk-gen-chain-videos.md) | Auto start+end frame chaining for continuous transitions | +| `fk-insert-scene` | [fk-insert-scene.md](fk-insert-scene.md) | Multi-angle shots, cutaways, close-ups insertion | +| `fk-creative-mix` | [fk-creative-mix.md](fk-creative-mix.md) | Analyze story + suggest optimal combination of all cinematic techniques | + +## Character & World Consistency + +| Skill | File | Description | +|-------|------|-------------| +| `fk-character-bible` | [fk-character-bible.md](fk-character-bible.md) | Biometric anchor sheets, wardrobe state matrices & series manifest engine | +| `fk-add-material` | [fk-add-material.md](fk-add-material.md) | Image material management (realistic, 3d_pixar, anime, etc.) | +| `fk-upload-image` | [fk-upload-image.md](fk-upload-image.md) | Upload local images to Google Flow to get UUID media_ids | +| `fk-fix-uuids` | [fk-fix-uuids.md](fk-fix-uuids.md) | Repair legacy CAMS... media_ids to standard UUID format | +| `fk-refresh-urls` | [fk-refresh-urls.md](fk-refresh-urls.md) | Re-sign expired media URLs for scenes and entity reference images | + +## Audio, Voice & Sound Design | Skill | File | Description | |-------|------|-------------| -| `fk-gen-chain-videos` | [fk-gen-chain-videos.md](fk-gen-chain-videos.md) | Auto start+end frame chaining for smooth transitions | -| `fk-insert-scene` | [fk-insert-scene.md](fk-insert-scene.md) | Multi-angle shots, cutaways, close-ups | -| `fk-creative-mix` | [fk-creative-mix.md](fk-creative-mix.md) | Analyze story + suggest all techniques combined | +| `fk-sound-design` | [fk-sound-design.md](fk-sound-design.md) | 4-layer audio design, sidechain ducking (-14dB), sub-bass drone, procedural SFX | +| `fk-gen-music` | [fk-gen-music.md](fk-gen-music.md) | Generate soundtracks & orchestral scores via Suno AI | +| `fk-gen-narrator` | [fk-gen-narrator.md](fk-gen-narrator.md) | Edge-TTS neural narration with pacing punctuation & voice profiles | +| `fk-gen-tts-template` | [fk-gen-tts-template.md](fk-gen-tts-template.md) | Generate consistent voice templates for narration | +| `fk-import-voice` | [fk-import-voice.md](fk-import-voice.md) | Import existing voice recordings as templates | +| `fk-gen-text-overlays` | [fk-gen-text-overlays.md](fk-gen-text-overlays.md) | Extract dates, names, casualty statistics for on-screen text overlays | -## Reference +## Distribution, YouTube SEO & Branding | Skill | File | Description | |-------|------|-------------| -| `fk-camera-guide` | [fk-camera-guide.md](fk-camera-guide.md) | Camera angles, movements, lighting, DOF for cinematic video prompts | -| `fk-provider` | [fk-provider.md](fk-provider.md) | Media providers: choose the generation backend, run the assistant worker, troubleshoot provider jobs | +| `fk-brand-logo` | [fk-brand-logo.md](fk-brand-logo.md) | Channel intro/outro bumpers, corner watermark logo, 4K resolution badge | +| `fk-thumbnail-guide` | [fk-thumbnail-guide.md](fk-thumbnail-guide.md) | YouTube thumbnail rules, high-CTR composition & 3-second hook principles | +| `fk-thumbnail` | [fk-thumbnail.md](fk-thumbnail.md) | Generate 4 YouTube thumbnail variants with high-impact typography | +| `fk-youtube-seo` | [fk-youtube-seo.md](fk-youtube-seo.md) | Generate high-converting hook titles, 3-zone descriptions, tags & AI disclosures | +| `fk-youtube-upload` | [fk-youtube-upload.md](fk-youtube-upload.md) | Automated YouTube API video upload (Shorts & Long-form) | -## Utilities +## Operations, Monitoring & Provider Management | Skill | File | Description | |-------|------|-------------| -| `fk-status` | [fk-status.md](fk-status.md) | Full project dashboard + next action | -| `fk-fix-uuids` | [fk-fix-uuids.md](fk-fix-uuids.md) | Repair any CAMS... media_ids to UUID format | +| `fk-status` | [fk-status.md](fk-status.md) | Comprehensive project status dashboard + recommended next action | +| `fk-dashboard` | [fk-dashboard.md](fk-dashboard.md) | Terminal statusline monitor for GLA and active tasks | +| `fk-monitor` | [fk-monitor.md](fk-monitor.md) | Full pipeline queue monitor with live background polling | +| `fk-doctor` | [fk-doctor.md](fk-doctor.md) | End-to-end diagnostic suite & error taxonomy resolver | +| `fk-pipeline` | [fk-pipeline.md](fk-pipeline.md) | Autonomous full-pipeline orchestrator from research to final concat | +| `fk-provider` | [fk-provider.md](fk-provider.md) | Select and manage media generation backend (Flow vs Assistant) | +| `fk-change-provider` | [fk-change-provider.md](fk-change-provider.md) | Switch AI vision review backend (Claude, Antigravity, Codex) | +| `fk-change-model` | [fk-change-model.md](fk-change-model.md) | View and configure image and video generation model keys | +| `fk-switch-project` | [fk-switch-project.md](fk-switch-project.md) | Switch active working project context | +| `fk-review-board` | [fk-review-board.md](fk-review-board.md) | Launch visual scene review board web app | ## Cross-Tool Compatibility @@ -49,11 +88,7 @@ python setup.py clean # Remove generated configs |------|-----------------|------------------|------------| | Claude Code | `.claude/commands/fk-.md` (stubs) | `CLAUDE.md` (committed) | `/fk-` | | Codex CLI | — | `AGENTS.md` (generated) | Read `skills/fk-.md` | - -`agy` (Antigravity) is not a target here: it expands neither `.gemini/commands/*.toml` -nor `.claude/commands/*.md`, and does not auto-load `AGENTS.md`, `GEMINI.md` or -`CLAUDE.md` in print mode. It is supported as a **video-review provider** -instead — see `/fk-change-provider`. +| Antigravity IDE | `.agents/skills/fk-/SKILL.md` | Workspace Skills | `/fk-` or Skill Discovery | **Adding a new skill:** Create `skills/fk-.md`, then run `python setup.py sync`. diff --git a/skills/fk-action-choreography.md b/skills/fk-action-choreography.md new file mode 100644 index 00000000..4106d628 --- /dev/null +++ b/skills/fk-action-choreography.md @@ -0,0 +1,100 @@ +# Action Choreography — AI Cinematic Combat & Motion Direction + +Technical manual for choreographing physics-safe action sequences, duels, and epic battle dynamics optimized specifically for generative AI video models (Google Veo 3, Flow, Sora). Eliminates anatomical morphing, limb fusion, and weapon clipping. + +--- + +## 1. Physical Principles of Generative AI Video + +Unlike traditional 3D CGI or live-action stunt work, generative AI video possesses no underlying skeletal rig, collision meshes, or Newtonian physics simulation. The model predicts sequential pixel manifolds based on training probabilities. + +### High-Risk Deformation Traps: +- **360-Degree Continuous Spins:** The model fails to maintain simultaneous dorsal and ventral memory, frequently rendering a second face on the back of the head. +- **Direct Head-On Sprints Toward Camera:** Rapid focal scale expansion distorts biometric proportions and liquefies facial features. +- **Intricate Physical Grappling:** Close-contact wrestling blends skin textures, generating fused limbs, three-armed mutants, or rubbery appendages. +- **Deep Penetration Wounds (Impaling):** Triggers safety moderation filters or results in rubberized, bending weapons. + +### Strengths to Maximize: +- **Unidirectional Trajectories:** Clean linear, diagonal, or arc-based kinetic paths. +- **Environmental Momentum:** Billowing cloaks, turbulent hair, kicking dust clouds, sparks flying from steel collisions. +- **Camera-Assisted Kinetic Energy:** Dynamic tracking and push-ins synchronized to the blow to amplify visual force without complex character movement. + +--- + +## 2. The 3-Phase Motion Invariant + +Every 8-second Veo 3 video clip (yielding 7.0 seconds of pristine footage after a 1.0s head trim) must be structured into three distinct temporal phases: + +``` +[0–3s: PREPARATION & KINETIC TENSION] ──► [3–6s: KINETIC STRIKE & TRAJECTORY] ──► [6–8s: RECOIL & ANCHOR POSE] +(Stance, grip, eye lock, coiled potential) (Unidirectional release, camera assist) (Follow-through, sparks, dust settle) +``` + +### Phase 1 (0–3s) — Preparation & Kinetic Tension +- **Objective:** Establish physical balance, lower the center of gravity, lock eye contact onto the target. +- **Safe Prompt Verbs:** `lowers stance into a firm combat crouch`, `tightens white-knuckled grip on the sword hilt`, `draws heavy recurve bowstring backward smoothly to the cheekbone`. +- **Camera Dynamic:** Slow deliberate dolly-in or static locked-off shot to build coiled tension. + +### Phase 2 (3–6s) — Kinetic Strike & Spatial Trajectory +- **Objective:** Execute the primary strike along a **single distinct vector**. +- **Golden Rule:** Describe weapon trajectory and environmental impact, NEVER soft-tissue penetration. +- **Safe Prompt Verbs:** `lunges forward in a powerful diagonal downward slash`, `sweeps the iron spear across in a broad horizontal crescent arc`, `releases the arrow which streaks forward leaving an air ripple`. +- **Camera Dynamic:** Camera rapidly tracking alongside the strike to amplify velocity. + +### Phase 3 (6–8s) — Recoil, Anchor Pose & Resolution +- **Objective:** Settle into an anchor freeze-pose, absorbing recoil and displaying exertion. +- **Safe Prompt Verbs:** `skids to a firm halt kicking up dry dust`, `holds the defensive parry lock as orange sparks scatter`, `chest heaves with controlled breaths, fierce glare locked on opponent`. +- **Environmental Aftermath:** Cloaks settle, kicked-up gravel rolls to a stop, rising smoke clears. + +--- + +## 3. Physics-Safe Action Vocabulary vs. Deformation Traps + +| Combat Archetype | ❌ High-Risk Triggers (Causes Morphing) | ✅ Physics-Safe Vocabulary (Clean 100% Render) | +| :--- | :--- | :--- | +| **Swords / Blades** | `stabs sword through enemy chest, blood splatters` | `delivers a decisive diagonal downward slash, blade clashing against raised iron shield in an explosive burst of orange sparks` | +| **Spears / Polearms** | `twirls spear rapidly spinning 10 times in air` | `thrusts the heavy spear forward in an explosive straight line, then retracts immediately into a solid defensive guard` | +| **Archery / Snipers** | `rapidly shoots 10 arrows in 2 seconds` | `smoothly pulls bowstring taut to jawline, exhales, and looses a single heavy war arrow that streaks through smoke` | +| **Dodges & Evasions** | `does a backflip somersault in midair` | `ducks low beneath the sweeping blade, sidestepping swiftly to screen-left with defensive guard raised` | +| **Cavalry / Horseback** | `horse leaps directly over camera lens` | `gallops hard diagonally across the frame from mid-ground to foreground, hooves churning up wet mud` | +| **Unarmed Melee** | `grapples and rolls on the floor wrestling` | `drives a heavy iron-gauntleted punch forward, deflecting the incoming blow with a solid forearm block` | + +--- + +## 4. Master Battle Sequence Templates + +### Template 1: Melee Duel (Clashing Steel) +```text +[0-3s] Medium shot: The commander lowers his combat stance, drawing his bronze blade in a deliberate arc as hot torch embers drift past. +[3-6s] He explodes forward in a decisive diagonal slash; his blade collides violently with his opponent's raised iron buckler, discharging a brilliant shower of orange sparks. The camera rapidly dollies forward to accentuate the impact. +[6-8s] Both warriors lock blades in a rigid contest of physical will, muscles straining, breath pluming in the freezing mountain air. +Audio: Resonant clatter of striking metal, sizzle of flying sparks, heavy guttural war grunt. +Negative: subtitles, captions, watermark, text overlay, extra limbs, distorted hands. +``` + +### Template 2: Precision Archery Sequence +```text +[0-3s] Medium close-up: The archer stands resolute upon the wind-swept battlements, drawing the heavy horn bowstring back to her jawline with frozen focus amidst heavy snowfall. +[3-6s] She looses the arrow; the bowstring snaps forward with a sharp vibration, and the iron bodkin arrow streaks diagonally across the snowy sky. The camera smoothly pans alongside the arrow's flight path. +[6-8s] She lowers her bow into a ready stance, eyes tracking the distant impact beyond the palisade, her fur-lined cloak whipping violently in the gale. +Audio: Crisp snap of bowstring vibration, whistling air rush of speeding arrow, distant heavy thud into wood. +Negative: subtitles, captions, watermark, text overlay, extra fingers. +``` + +### Template 3: Armored Cavalry Charge +```text +[0-3s] Wide shot: The armored cavalry vanguard holds formation momentarily at the crest of the grassy hill, war steeds stamping restless hooves into rising morning mist. +[3-6s] The riders surge downhill simultaneously in a thunderous charge, iron lances leveled horizontally, moving diagonally from upper-left to lower-right. The camera tracks smoothly alongside the galloping horses. +[6-8s] Mud and clods of earth erupt violently beneath pounding hooves, silk battle banners fluttering furiously overhead as the charge reaches full momentum. +Audio: Massive rhythmic thunder of hundreds of galloping hooves, clanking bronze armor plates, distant war horn call. +Negative: subtitles, captions, watermark, text overlay, distorted legs. +``` + +### Template 4: Fortress Gate Siege & Shield Wall +```text +[0-3s] Low-angle shot: Soldiers brace their heavy bronze tower shields together into an unbroken wall, locking shoulders against the reinforced timber frame. +[3-6s] A volley of flaming arrows rains down from the dark sky, striking the shield wall in explosive bursts of sparks and splintering wood. The camera remains locked in a low-angle heroic perspective. +[6-8s] The soldiers hold their ground without flinching, smoke curling off the charred bronze shield faces as the commander raises his sword to signal the counter-assault. +Audio: Thundering impact of flaming arrows on metal and timber, hissing fire extinguished on wet wood, resolute soldier battle cry. +Negative: subtitles, captions, watermark, text overlay, blurry faces. +``` diff --git a/skills/fk-camera-guide.md b/skills/fk-camera-guide.md index 839211ed..85031fb2 100644 --- a/skills/fk-camera-guide.md +++ b/skills/fk-camera-guide.md @@ -343,8 +343,46 @@ Negative: subtitles, watermark, text overlay, blurry faces. --- +## Cinema Lens Profiles & Optical Emulation + +Lenses define the soul and optical texture of the image. Rather than using generic words like "cinematic", specify the exact lens package and optical characteristics: + +| Lens Package | Prompt Keywords | Visual Signature | Ideal Genre | +| :--- | :--- | :--- | :--- | +| **Anamorphic 2.39:1** | `shot on 35mm anamorphic lens, oval bokeh, horizontal blue streak lens flares` | Ultra-widescreen field of view, elliptical bokeh, horizontal cobalt streaks. | Sci-fi, blockbuster action, panoramic battlefields. | +| **Cooke Panchro / "Cooke Look"** | `Cooke S4/i prime lens, warm organic skin tones, painterly roll-off bokeh` | Flattering organic skin warmth, painterly focus roll-off, vintage character. | Psychological drama, character close-ups, intimate dialogue. | +| **Arri Master Prime** | `Arri Master Prime lens, ultra-sharp edge-to-edge clarity, neutral high contrast` | Clinical optical resolution, zero aberration, authentic theatrical realism. | Epic warfare, detailed armor, ancient architectural majesty. | +| **Vintage Leica Summilux** | `Leica Summilux-C vintage glass, creamy soft highlights, subtle micro-contrast` | Creamy highlight bloom, delicate micro-contrast, intimate nostalgic glow. | Atmospheric night exteriors, period flashbacks, candlelight. | + +--- + +## Hollywood Color Grading & Film Stock Matrix + +Color palette establishes the emotional tone of the sequence before physical action unfolds: + +| Color Grade / Stock | Prompt Keywords | Emotional Atmosphere | Benchmark Context | +| :--- | :--- | :--- | :--- | +| **Bleach Bypass (Silver Retention)** | `bleach bypass color grade, high contrast, desaturated muted tones, gritty silver sheen` | Harsh, uncompromising, tragic, militaristic grit. | Blood-soaked combat, ruined citadels in post-siege aftermath. | +| **Teal & Orange** | `teal and orange color grade, rich amber skin tones against deep cyan shadows` | Vibrant, high kinetic energy, modern blockbuster punch. | High-speed pursuits, night ambushes with blazing torches. | +| **Kodachrome 64 Vintage** | `Kodachrome 64 aesthetic, deep saturated reds and golds, warm nostalgic film grain` | Historical reverence, nostalgic warmth, timeless prestige. | Childhood retrospectives, coronation banquets, imperial glory. | +| **Chiaroscuro Night** | `chiaroscuro lighting, deep crushing black shadows, single directional candlelight source` | Paranoia, perilous conspiracy, claustrophobic power struggle. | Palace palace coup meetings, late-night war councils. | + +--- + +## The 180-Degree Rule in AI Direction (Spatial Continuity) + +In consecutive dialogue shots between two opposing characters or armies: +- **Core Principle:** An imaginary line of action connects the two subjects. The camera **must remain strictly on one side** of this axis across consecutive cuts. +- **Eyeline Vector Matching:** + - **Character A (Close-up):** `looking screen-right towards opponent`. + - **Character B (Close-up):** `looking screen-left towards opponent`. + - *If both characters are prompted looking screen-right, the audience perceives them gazing in the same direction rather than making direct eye contact.* + +--- + ## Quality Checklist + Before submitting any video prompt, verify: - [ ] Prompt is 100–150 words, 3–6 sentences diff --git a/skills/fk-character-bible.md b/skills/fk-character-bible.md new file mode 100644 index 00000000..6507a128 --- /dev/null +++ b/skills/fk-character-bible.md @@ -0,0 +1,124 @@ +# Character Bible & Visual Consistency — AI Film Production + +Standards and technical workflows for maintaining biometric fidelity, wardrobe coherence, signature accessories, and environmental continuity across multi-chapter AI films in Google Flow and Veo 3. + +--- + +## 1. Core Consistency Invariants + +In multi-chapter AI filmmaking (5 to 20+ episodes), the most destructive failure modes are: +1. **Facial Drift:** Subtle generational changes in jawline, eye color, facial hair, or perceived age across chapters. +2. **Wardrobe Glitching:** A character wearing battle armor spontaneously switching into court robes, or cape colors morphing between cuts. +3. **Vanishing Identifiers:** Signature scars, tattoos, family heirlooms, or eye patches disappearing between consecutive scenes. + +### The Golden Production Rule: +> **"Appearance in Reference, Action in Prompt"** +> * Detailed physical appearance (facial architecture, hairstyle, bone structure, clothing fabric, color palette) **MUST** be locked into the reference image and Entity description. +> * Scene prompts **MUST NEVER** re-describe facial anatomy. Prompts must specify **ACTION, TEMPORAL KINETICS, AND IMMEDIATE EMOTION ONLY**. + +--- + +## 2. Character Visual Anchor Sheet + +Before scripting an episode, every recurring character requires an immutable Visual Anchor Sheet saved at `.omc/research/_character_bible.md`: + +### Specification Template: +```markdown +### [ENTITY_KEY] Character Display Name (Role-Based Alias) +* **Entity Name:** Commander_Steel (Never use real public figures — Rule 15) +* **Biometric Invariants:** + - Perceived Age & Build: Male, 38 years old, athletic battle-hardened build, 6'1" stature. + - Facial Structure: Sharp square jawline, high weathered cheekbones, piercing cold amber eyes. + - Signature Identifier: Thin 3cm diagonal pale battle scar running across the left cheekbone. + - Hair & Facial Hair: Jet-black hair tightly bound in a high topknot with an antique bronze hair pin; clean-trimmed stubble along the jawline. +* **Palette Signature (Hex Codes):** + - Primary: Deep crimson blood (`#801818` / Crimson blood). + - Secondary: Charcoal carbon (`#1A1A1D` / Matte black). + - Metal: Antique unpolished bronze (`#8C6239` / Weathered bronze). +* **Signature Prop / Weapon:** + - Double-edged bronze broadsword with an engraved dragon guard and grey stingray-skin wrapped hilt. +``` + +--- + +## 3. Wardrobe State Matrix (Costume Progression by Story Arc) + +Characters cannot remain in pristine identical garments through battles, captivity, or coronation. However, wardrobe transitions must be managed through strict **Discrete States**: + +| State | State Identifier | Costume & Physical Condition | Narrative Context | Associated Entity Reference | +| :--- | :--- | :--- | :--- | :--- | +| **STATE 01** | `Normal / Court` | Raw silk ceremonial robe in indigo blue, jade hair pin, pristine posture. | Imperial audience, civilian life, covert meetings. | `Commander_Steel_Court` | +| **STATE 02** | `Battle / Armor` | Black iron scale armor, bronze dragon pauldrons, heavy crimson battle cloak. | Field command, vanguard assault, night patrol. | `Commander_Steel_Armor` | +| **STATE 03** | `Wounded / Battle-worn` | Shattered shoulder plate, scorched cloak, blood-stained linen band wrapped on forehead. | Post-siege breakout, desperate retreat, duel aftermath. | `Commander_Steel_Wounded` | +| **STATE 04** | `Coronation / Triumph` | Golden embroidered imperial vestments, ceremonial dragon crown, dignified triumph. | Victory parade, enthronement, climactic resolution. | `Commander_Steel_Triumph` | + +### Production Rules for Wardrobe Changes: +- When a character undergoes a major visual transformation, **create a distinct Entity Reference** (e.g., `Commander_Steel_Armor` vs. `Commander_Steel_Wounded`). +- Generate and verify dedicated reference images for each state (`POST /api/requests/batch` with `GENERATE_CHARACTER_IMAGE`). +- Bind the exact matching entity name into the scene's `character_names` array in `POST /api/scenes`. + +--- + +## 4. Rule 15 Compliance: Real-People Bypass + +Modern generative video models (Google Flow, Veo 3, Imagen 3) enforce strict automated safety filters that reject generation requests containing names of real public figures, historical leaders, or politicians. + +### Safe Execution Protocol: +1. **Role-Based Aliases:** + - ❌ **Reject:** `Napoleon_Bonaparte`, `George_Washington`, `Tran_Hung_Dao`. + - ✅ **Approve:** `Supreme_Commander_Grand_Marshal`, `Continental_General`, `Supreme_Field_Marshal`. +2. **Pure Anatomical Descriptions (Zero Named Identity):** + - Prompt description: *"A seasoned 13th-century military general with piercing eyes, dignified weathered facial features, high cheekbones, traditional topknot hair tied with antique bronze pin, wearing iron scale armor."* +3. **Dialogue & Narrator Isolation:** + - Formal titles and narrative lore may appear in `narrator_text` (handled via Edge-TTS audio), but **real names must NEVER enter image or video prompts**. + +--- + +## 5. Environmental & World Consistency + +Consistency applies equally to sets, citadels, terrain, and lighting: + +1. **Entity Type = `location`:** Always generate reference images in **HORIZONTAL (16:9)** orientation. +2. **Unified Lighting Signature:** + - Lock the illumination source across the scene chain (e.g., *"lit strictly by flickering orange pitch torches and distant embers, deep chiaroscuro shadows"*). +3. **Dual Entity Ingestion in Google Flow:** + - When posting scenes, include both the character and location in `character_names`: + ```json + { + "character_names": ["Commander_Steel_Armor", "Thang_Long_Grand_Palace"] + } + ``` + - Flow maps both reference media IDs into `imageInputs`, anchoring the character's facial likeness simultaneously with architectural consistency. + +--- + +## 6. Per-Project Series Manifest Engine (`scripts/series_manifest.py`) + +When managing multi-chapter epics (e.g., 5 to 20+ episodes), re-creating entities or re-generating reference images causes catastrophic visual drift. FlowKit provides an automated **Per-Project Series Manifest Engine**: + +- **Location:** Stored strictly per-project inside `output//series_manifest.json`. +- **Automatic Generation:** Automatically synthesized and synchronized by FlowKit API whenever `GET /api/projects/{pid}/output-dir` or `GET /api/projects/{pid}/manifest` is accessed. + +### Workflow: +1. **Auto-Generate & Sync from Active Project:** + ```bash + # Synchronize entities, media_ids, and episodes into output//series_manifest.json + python scripts/series_manifest.py sync --project-id + ``` + +2. **Inspect Series Manifest Overview:** + ```bash + python scripts/series_manifest.py show --project-dir output/ + ``` + +3. **Bootstrap New Episodes with Zero Ref Drift:** + ```bash + # Create Chapter 6, reusing existing character & location UUIDs + python scripts/series_manifest.py bootstrap \ + --project-dir output/ \ + --episode 6 \ + --title "Chương VI: Huyết Nguyệt" + ``` + *(This automatically links all pre-existing character and location `media_id`s into the new project, completely skipping reference image generation and preserving 100% biometric consistency across seasons).* + + diff --git a/skills/fk-cinematic-transitions.md b/skills/fk-cinematic-transitions.md new file mode 100644 index 00000000..b4778ef5 --- /dev/null +++ b/skills/fk-cinematic-transitions.md @@ -0,0 +1,156 @@ +# Cinematic Transitions & Chapter Bumpers — AI Film Direction + +Comprehensive technical guide and automated recipes for Hollywood-grade transitions, chapter interstitial bumpers, and multi-layer continuity in Google Flow and Veo 3. + +--- + +## 1. Principles of AI Cinematic Transitions + +In generative AI filmmaking, the most glaring indicators of amateur production are: +- **Abrupt Hard Cuts:** Jarring jumps between unrelated camera motions without visual or kinetic preparation. +- **Overused Cross-Dissolves:** Monotonous 50/50 opacity blends that muddy the image and dilute visual impact. +- **Truncated Chapter Transitions:** Abrupt jumps between story arcs without breathing room for the audience to absorb narrative progression. + +This skill establishes **four tiers of cinematic continuity** combining Veo 3 directorial prompt engineering, multi-layer audio lead-ins, and precision FFmpeg post-processing. + +--- + +## 2. Chapter Interstitial Bumpers (Golden Serif & Sub-Bass Drones) + +When compiling episodic scenes or multi-chapter narratives into a master film, every chapter transition requires a **3.2s – 4.0s** interstitial bumper. + +### Visual Architecture: +1. **Background:** Deep obsidian black `#08080A` or subtle volumetric smoke texture. +2. **Typography Hierarchy:** + - **Line 1 (Chapter Title):** Elegant Serif (e.g., Trajan Pro / Times New Roman Bold), royal antique gold `#E6C280` or amber `#D4AF37`. + - **Line 2 (Location / Temporal Anchor):** Subdued smoke grey `#8E95A5`, clean geometric spacing. +3. **Ken Burns Motion Dynamics:** Ultra-slow linear zoom from `1.0x` to `1.04x` over 3.5s (`zoompan` filter), giving static typography dimensional depth. +4. **Dip-to-Black Envelope:** 0.8s fade-in from pure black -> 1.9s hold -> 0.8s fade-out to pure black. +5. **Sub-Bass Drone Acoustic Design:** + - 40Hz – 60Hz Brown noise resonance (rumble felt in the chest). + - Deep cinematic boom, resonant temple bell chime, or distant war horn to establish solemn gravity. + +### Automated Python + FFmpeg Bumper Generation: +```python +from PIL import Image, ImageDraw, ImageFont + +# Generate 1920x1080 or 1280x720 canvas +img = Image.new("RGB", (1280, 720), (8, 8, 11)) +draw = ImageDraw.Draw(img) + +# Center divider line in antique gold +draw.line([(440, 395), (840, 395)], fill=(180, 145, 75), width=2) +img.save("bumper_canvas.png") +``` + +Render into animated bumper with sub-bass audio: +```bash +ffmpeg -y -loop 1 -i bumper_canvas.png \ + -f lavfi -i "anoisesrc=c=brown:r=48000:a=0.3,lowpass=f=75,volume=0.6" \ + -vf "zoompan=z='min(zoom+0.0003,1.04)':d=88:x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)':s=1280x720,fade=t=in:st=0:d=0.8,fade=t=out:st=2.7:d=0.8" \ + -af "afade=t=in:st=0:d=0.8,afade=t=out:st=2.7:d=0.8" \ + -t 3.5 -c:v libx264 -pix_fmt yuv420p -c:a aac -b:a 192k bumper.mp4 +``` + +--- + +## 3. In-Camera AI Transitions (Directing the Lens) + +Rather than forcing transitions in the edit, instruct the generative model to execute transitions directly inside the lens: + +### A. Whip Pan / Swish Pan +* **Purpose:** Dynamic leap across time or vast geographical distance during high-tension sequences. +* **Scene N (Outgoing):** + ```text + ...In the final second, the camera executes a violent whip pan to the right, dissolving the entire background into motion blur. + ``` +* **Scene N+1 (Incoming):** + ```text + The scene begins with a high-speed whip pan entering from screen-left, quickly stabilizing onto [Subject] standing in combat stance. + ``` + +### B. Frame Obscurity / Object Wipe +* **Purpose:** Concealing the edit point behind a foreground physical obstruction. +* **Scene N (Outgoing):** + ```text + A heavy armored warrior in a black cloak marches directly past the camera from right to left, his dark cloak completely blacking out the entire lens in the final second. + ``` +* **Scene N+1 (Incoming):** + ```text + The shot opens from behind a thick wooden palace pillar moving out of frame to the left, revealing [New Scene]. + ``` + +### C. Focus Pull / Defocus Transition +* **Purpose:** Shifting between reality, flashback, memory, or intense internal dilemma. +* **Scene N (Outgoing):** + ```text + The camera slowly racks focus away from the protagonist's sorrowful expression, dissolving the frame into soft, circular golden bokeh. + ``` +* **Scene N+1 (Incoming):** + ```text + Beginning in complete soft bokeh blur, the lens smoothly pulls focus inward to reveal the sharp, trembling flame of a bronze oil lamp. + ``` + +--- + +## 4. Visual Match Cuts + +Match cuts establish thematic, psychological, or kinetic parallels between two distinct shots: + +### A. Graphic Match (Shape & Composition) +Aligning subjects with identical geometry and screen placement across the cut point: + +| Outgoing Shot (Scene N) | Incoming Shot (Scene N+1) | Cinematic Thematic Meaning | +| :--- | :--- | :--- | +| Blood-red full moon centered in a stormy night sky (EWS). | Circular bronze war gong struck by an iron mallet in the grand hall (CU). | Omen of impending dynasty collapse manifesting into war. | +| Single tear falling from an empress's cheek (ECU). | Single raindrop hitting the tranquil surface of the river (MS). | Personal sorrow swallowed by the vast flow of history. | + +### B. Match Cut on Action (Momentum & Kinetic Trajectory) +* **Core Rule:** Match direction, speed, and trajectory of the action across the cut. Always cut at **peak velocity (mid-motion)**, never after movement has settled. +* **Scene N (Outgoing):** General slashes his bronze blade diagonally downward from top-right to bottom-left (`camera whip pans following the sword strike`). +* **Scene N+1 (Incoming):** An enemy battle flag is sliced diagonally in two along the exact matching trajectory (`camera continues the rapid diagonal movement before settling`). + +--- + +## 5. Audio Transitions: J-Cuts, L-Cuts & Sound Bridges + +Over 50% of cinematic immersion is acoustic. Audio bridges eliminate perceived visual abruptness: + +### A. J-Cut (Audio Lead-in) +* **Technique:** The audio of Scene N+1 (dialogue, war cries, gallop of steeds, or ringing church bell) enters **1.0s – 1.5s** before the visual cut occurs. +* **Psychological Impact:** Prepares the viewer's subconscious, creating momentum into the incoming scene. + +### B. L-Cut (Audio Hangover) +* **Technique:** The dying reverberation, heavy exhale, or final sentence of Scene N continues for 1.0s into Scene N+1. +* **Psychological Impact:** Sustains emotional resonance and dramatic gravity across scene changes. + +### C. Sound Bridge (Acoustic Continuity) +* Sustaining a unifying atmospheric tone (torrential rain, howling wind, or a thematic musical motif) seamlessly across contrasting camera angles. + +--- + +## 6. Post-Production FFmpeg Recipes + +### 1. Head Trim to Eliminate AI Generator Glitches: +AI video models (including Veo 3) often suffer from a micro-freeze or flicker on frame 0. Standardize every clip: +```bash +ffmpeg -ss 1.0 -t 7.0 -i raw_scene.mp4 -c:v libx264 -crf 18 -c:a aac -b:a 192k normalized_scene.mp4 +``` + +### 2. Dip-to-Black Sequence Concatenation: +```bash +# Fade out scene tail +ffmpeg -i scene_A.mp4 -vf "fade=t=out:st=6.2:d=0.8" -af "afade=t=out:st=6.2:d=0.8" -c:v libx264 -c:a aac scene_A_faded.mp4 + +# Fade in scene head +ffmpeg -i scene_B.mp4 -vf "fade=t=in:st=0:d=0.8" -af "afade=t=in:st=0:d=0.8" -c:v libx264 -c:a aac scene_B_faded.mp4 +``` + +### 3. Master Multi-Chapter Compilation: +Use the battle-tested script: +```bash +python scripts/build_master_film.py \ + --project-dir output/ \ + --chapters 1 2 3 4 5 \ + --output output//_CINEMATIC_MASTER.mp4 +``` diff --git a/skills/fk-concat-fit-narrator.md b/skills/fk-concat-fit-narrator.md index 2d4ad9fc..55d7f0e1 100644 --- a/skills/fk-concat-fit-narrator.md +++ b/skills/fk-concat-fit-narrator.md @@ -308,6 +308,50 @@ Per-scene breakdown: Total saved: XXs ``` +## Step 9: Multi-Chapter Cinematic Master Film Assembly (`--master`) + +When producing an episodic or multi-chapter film (e.g., Chapters 1 through 5), this stage compiles all independent chapter masters into a seamless **Cinematic Master Film**: + +```bash +# Execute master compilation across all chapters +python scripts/build_master_film.py \ + --project-dir output/ \ + --chapters 1 2 3 4 5 \ + --output output//_CINEMATIC_MASTER.mp4 +``` + +### Standard 4-Step Technical Workflow: + +1. **Chapter Interstitial Bumpers (3.5s duration):** + - Renders 1280x720 / 3840x2160 title plates featuring an obsidian background `#08080A`, antique gold dividing line `#B4914B`, and dignified Serif typography (`timesbd.ttf`). + - Ken Burns motion dynamics: micro-zoom from 1.0x to 1.04x over 3.5s (`zoompan=z='min(zoom+0.0003,1.04)':d=88:x='iw/2-(iw/zoom/2)':y='ih/2-(ih/zoom/2)'`). + - Integrated acoustic tone: 40–60Hz Brown noise sub-bass drone creating a solemn, cinematic atmosphere. + +2. **Dip-to-Black Transitions:** + - Outgoing chapter tail: 0.8s fade-out to black (`fade=t=out:st=:d=0.8` and `afade=t=out:st=:d=0.8`). + - Incoming chapter head: 0.8s fade-in from black (`fade=t=in:st=0:d=0.8` and `afade=t=in:st=0:d=0.8`). + - Interstitial bumper inserted between chapters as an acoustic and visual bridge. + +3. **Cinematic Multi-Layer Audio Balance:** + - **TTS Voice Narration:** `volume=1.40` (+2.9 dB boost for presence and intelligibility). + - **Veo 3 Ambient / Foley:** `volume=0.25` (-12 dB ducking so background noise never interferes with spoken dialogue). + - **Bumper Drone / Chapter Stinger:** `volume=0.50` (Resonant and deep without causing distortion). + +4. **Automated Subtitle & Hardsub Generation (`scripts/generate_subtitles.py`):** + - Automatically computes timeline timestamps from scene durations and narrator text. + - Generates standard `.srt` (for YouTube CC / VLC) and `.vtt` (for web players). + - Burns hardsubs directly into frames with custom styling presets: + ```bash + python scripts/generate_subtitles.py \ + --project-dir output/ \ + --burn-subtitles \ + --input-video output//_CINEMATIC_MASTER.mp4 \ + --style cinematic_gold + ``` + - **Styles:** `cinematic_gold` (Antique Gold text `#E6C280` with dark shadow), `clean_white` (Crisp White `#FFFFFF`), `cyber_amber` (Amber Gold), `emerald_hud` (Sci-Fi HUD Green). + +--- + ## Common Issues | Issue | Cause | Fix | @@ -318,3 +362,6 @@ Per-scene breakdown: | Scene order wrong | Not sorted by display_order | Sort scenes before processing | | TTS file not found | Wrong path or naming mismatch | Check both TTS path patterns | | Abrupt video cut | No fade-out at trim point | Add optional `-af "afade=t=out:st={CUT_DUR-0.3}:d=0.3"` | +| Bumper audio missing | Video concat without audio stream | Always include an audio stream with bumpers (drone or silent evaluation stream) | + + diff --git a/skills/fk-doctor.md b/skills/fk-doctor.md index 56ebbff1..a2fc34b8 100644 --- a/skills/fk-doctor.md +++ b/skills/fk-doctor.md @@ -163,6 +163,13 @@ Three behaviours on this path routinely look like bugs and are not: - **A poll can say "Media not found." and the job still finishes.** The project listing is what decides; the poll is a hint. Never treat the complaint as fatal. +- **CRITICAL: Polling timeout must NOT trigger entity re-upload.** + `processor.py:_handle_failure` had a bug where matching `"not found"` triggered `_recover_entity_not_found`, + which falsely re-uploaded the start image and overwrote the genuine generated scene image media ID. + The guard in `processor.py` (line 485) is: + `if "not found" in str(error_msg).lower() and "polling timeout" not in str(error_msg).lower():` + If a scene's `image_media_id` was accidentally overwritten by this bug, check `/api/requests` history + or restore the original generated image media ID from the initial GENERATE_IMAGE completed payload. - **A media id arrives before the clip is fetchable.** The media record serves the poster image first and grows the `/video/` url in later, so a scene sits PENDING for a while after its id exists. Downloading on the id alone saves a diff --git a/skills/fk-gen-narrator.md b/skills/fk-gen-narrator.md index 8272d086..c71f7a60 100644 --- a/skills/fk-gen-narrator.md +++ b/skills/fk-gen-narrator.md @@ -188,16 +188,31 @@ The `ref_text` is the **exact transcript** of what's spoken in `ref_audio`. - If template was created via `/fk-gen-tts-template`: `ref_text` = the standard base transcript used during creation (stored in `templates.json`) - If template is a user-provided WAV: transcribe it first using whisper, then use that transcript as `ref_text` for all scenes -### Provider (optional) +### Edge-TTS Neural Voices (Zero-Cost, High-Fidelity Narration) -Usage: `/fk-gen-narrator [--provider ] [--force] [--language vi] [--speed 1.1]` +The pipeline natively supports Microsoft Edge TTS for broadcast-grade neural voice synthesis: -Add `"provider": ""` to the `/api/tts/generate` payload to route TTS -through a provider job (`assistant`) instead of the local OmniVoice engine — -the worker's provider must support audio (`generate_audio` capability). Omit -it for local TTS. `flow` cannot do audio and is rejected with 400. +| Neural Voice Model | Voice Profile & Timbre | Optimal Genre | Recommended Rate | +|:---|:---|:---|:---| +| `vi-VN-NamMinhNeural` | Male, resonant baritone, authoritative Northern dialect | History, military, documentary, epic action | `+0%` or `-2%` (Solemn) | +| `vi-VN-HoaiMyNeural` | Female, crystalline clarity, nuanced emotional delivery | Poetic drama, introspective narrative, tragedy | `+0%` or `+3%` | + +**Automated Python Edge-TTS Generation:** +```python +import edge_tts, asyncio + +async def generate_scene_edge_tts(text: str, out_wav: str, voice: str = "vi-VN-NamMinhNeural", rate: str = "+0%"): + communicate = edge_tts.Communicate(text, voice=voice, rate=rate) + await communicate.save(out_wav) +``` + +**Cinematic Punctuation & Pacing Controls:** +- Em Dash (`—`): Enforces a 0.4s – 0.5s dramatic acoustic pause before revealing crucial plot words. +- Ellipsis (`...`): Injects an atmospheric 0.6s trailing fade for lingering contemplation. +- Comma (`,`): Structurally segments complex thoughts into 4–6 word cadences, preventing rushed phonemes. ### Key rules: + - `ref_audio` = the voice template WAV file (voice timbre source) - `ref_text` = exact transcript of `ref_audio` (phoneme alignment) - Both MUST be provided together — never just `ref_audio` alone diff --git a/skills/fk-review-video.md b/skills/fk-review-video.md index 20cc6e1e..75a44088 100644 --- a/skills/fk-review-video.md +++ b/skills/fk-review-video.md @@ -249,20 +249,35 @@ HIGH errors → note `usable_segments` before the error timestamp. Trim or regen MINOR errors → acceptable for most use cases. Polish optional. -### Prevention Patterns - -| Issue | Fix | -|-------|-----| -| Character drift | Simpler prompts, add "steady camera, minimal movement" | -| Breed swap | Use high color contrast between similar characters | -| Character count | ONE dominant character, others in background | -| Reverse motion | Regen video (luck-based, different seed) | -| Brand logos | Add "no brand logos, no text" to prompt | -| Camera drift | Add "static camera" or "locked-off shot" to video_prompt | -| Human hands | Add "paws, claws, hooves" (or correct anatomy) to prompt | +### Automatic Prompt Healing (Self-Correction Loop for Scores < 7.5) + +In compliance with **Critical Rule 16**, any scene scoring below 7.5 undergoes automated diagnostic healing and regeneration (capped at 2 cycles): + +1. **Extract Error Vectors from the `errors` Array:** + - If error contains `Camera Drift`: Append `locked-off static camera, subtle smooth tracking` to the camera sentence. + - If error contains `Character Drift`: Append `strictly preserves identical facial bone structure and eye color from reference`. + - If error contains `Object/Anatomy Morph`: Append `natural realistic anatomy, five distinct fingers, rigid solid weapon hilt`. + - If error contains `Reverse Motion / Jerk`: Append `continuous linear motion, fluid steady trajectory without backward hitch`. + +2. **Update Scene via PATCH (Rule 13):** + ```bash + curl -X PATCH http://127.0.0.1:8100/api/scenes/ \ + -H "Content-Type: application/json" \ + -d '{"video_prompt": ""}' + ``` + +3. **Dispatch REGENERATE_VIDEO Request:** + ```bash + curl -X POST http://127.0.0.1:8100/api/requests \ + -H "Content-Type: application/json" \ + -d '{"type": "REGENERATE_VIDEO", "scene_id": "", "project_id": "", "video_id": "", "orientation": "${ORI}"}' + ``` + +--- ## Cost Note + Each scene review = 1 Claude Vision API call with N frames. - Light mode (32 frames/scene): ~$0.01–0.03 per scene - Deep mode (64 frames/scene): ~2x light mode cost diff --git a/skills/fk-scriptwriter.md b/skills/fk-scriptwriter.md new file mode 100644 index 00000000..24e18f69 --- /dev/null +++ b/skills/fk-scriptwriter.md @@ -0,0 +1,550 @@ +# The Ultimate AI Screenplay Bible — Google Flow & Veo 3 + +Usage: `/fk-scriptwriter "" [--episode N] [--scenes 8|12] [--lang vi|en] [--orientation HORIZONTAL|VERTICAL] [--fast]` + +- **Default:** Runs the **Interactive 5-Step Director Workflow** (Section A), pausing for approval at Steps 1, 3, and 5. +- `--fast`: Bypasses user review gates to directly generate technical production scripts (still strictly enforces Section N Quality Gates). + +--- + +## 0. Technical Truths of FlowKit (Must Never Violate) + +| Technical Reality | Direct Screenplay Consequence | +| :--- | :--- | +| `POST /api/scenes` only accepts: `video_id, display_order, prompt, image_prompt, video_prompt, transition_prompt, character_names, parent_scene_id, chain_type, source`. Extra fields are **silently ignored**. | Sending `narrator_text` in the POST payload will be **lost**. You must call `PATCH /api/scenes/{sid}` with `{"narrator_text": "..."}` immediately after scene creation. | +| The server automatically injects the material `scene_prefix` (e.g., `realistic`) to the beginning of `prompt`. | Do NOT manually prepend material style prefixes into `prompt` to avoid duplicate prompt contamination. | +| `character_names` must **strictly match** project entity names (characters, locations, visual assets). | This is how reference images are routed into Google Flow `imageInputs`. Mismatched names = missing refs = facial drift and identity loss. | +| `chain_type: CONTINUATION` uses the subsequent scene image as `endImage`. On the modern Flow API, endImage triggers an immediate fatal error: `UNSUPPORTED_ON_BATCH_API`. | **Default every scene to `ROOT`.** Only use chained transitions when `FLOW_ALLOW_DEGRADED=1` is confirmed or when using compatible providers. | +| Veo 3 video clips are 8.0s; post-production applies `-ss 1` head trim → **7.0s** usable footage remaining. | All narrator mathematics (Section J) are calibrated against a 7.0s effective window. | +| Scenes are mutable via `PATCH`. | Refine prompts via `PATCH /api/scenes/{sid}`. **Never delete and recreate** (preserves generated media). | + +--- + +## A. Interactive 5-Step Director Workflow + +### Step 1 — Pitch Logline (Pause for Approval) +- If the subject is based on real historical events or public figures: execute `/fk-research` first (Rule 14). +- Present **2–3 creative angles**, each including: 1-sentence logline, genre preset (Section L), narrative tone, and the opening 3-second visual hook. + +### Step 2 — Cast & World Lock +- Enumerate project entities: `character` (vertical 9:16 portrait), `location` (horizontal 16:9 landscape), and `visual_asset`. +- Lock **Lighting Signature**, **Color Palette**, and **Dialogue Language** (e.g., Vietnamese or English). +- If the project already exists: query `GET /api/projects/{pid}` to obtain exact entity names. + +### Step 3 — Beat Sheet: 8–12 Beats (Pause for Approval) +One line per scene: scene archetype (Section D) · shot scale · characters present · dialogue presence · targeted emotional shift (Section I2). + +### Step 4 — Technical Production Script +Author exhaustive specifications per scene: `prompt`, `video_prompt`, `narrator_text`, `character_names`, `music_cue`, `wardrobe_state`. + +### Step 5 — Self-Audit & Pipeline Ingestion (Pause for Approval) +1. Run the **20-Point Quality Gate** (Section N) — output full verification scorecard; resolve any failing items. +2. Save screenplay: `.omc/research/_ep_script.json`. +3. Inquire: *"Dispatch into FlowKit pipeline immediately?"* → upon confirmation, execute Section O. + +--- + +## B. Series Bible & Multi-Episode Arc Architecture + +Before scripting Episode 1, compile a minimal Series Bible (saved at `.omc/research/_bible.md`): + +- **Series Logline** (1 sentence) · **Core Theme** · **World Rules** (e.g., "Solar temperature increases 1°C every 3 days"). +- **Series Clock**: Universal countdown anchor. Every episode must advance this ticking clock. +- **Visual Leitmotif**: A recurring visual motif that evolves across episodes (e.g., the sun grows progressively crimson). + +### 4-Act Structure for a 10–12 Episode Series +| Act | Episodes | Narrative Function | Emotional Temperature | +| :--- | :--- | :--- | :--- | +| **Act 1 — Inciting Arc** | 1–3 | Introduce protagonists, stakes, allies, opposing force | Curiosity → Rising dread | +| **Act 2 — Escalation Arc** | 4–7 | Resource competition, betrayals, pyrrhic victories | Sustained high tension | +| **Act 3 — Darkest Night** | 8–9 | Core citadel under siege, catastrophic personal loss | Existential despair | +| **Act 4 — Climax & Resolution** | 10+ | Final confrontation, ultimate sacrifice, transformed world | Catharsis & resonance | + +**Episode Transition Rule:** Scene 0 of Episode N+1 must directly address or escalate the cliffhanger of Episode N within the first 3 seconds. + +--- + +## C. The 10 Core Screenplay Commandments + +1. **Action-Only Prompts:** Never describe facial anatomy, hair color, or body build in scene prompts. Reference images govern identity; prompts describe action only (Wardrobe state is the sole exception — Section F). +2. **3-Beat Structure in 8 Seconds:** Mandate `0-3s`, `3-6s`, `6-8s` temporal breakdown in every `video_prompt`. +3. **Narrator Mathematics:** Narrator audio must comfortably conclude within 7.0s (Section J). +4. **Show ≠ Tell:** Narration must reveal unseen context, motives, or stakes. Never redundantly narrate what is already visible on screen. +5. **Maximum 2 Named Characters per Scene:** Crowds remain blurred in the background. +6. **Camera Movement as Standalone Sentence:** Camera direction must be separated from character action sentences. +7. **No Consecutive Scale Repetition:** Never place two identical shot sizes back-to-back (Section G). +8. **Physiological Emotion:** Describe observable physiological symptoms rather than abstract adjectives (Section I). +9. **Lighting Signature Consistency:** Maintain unified lighting within identical temporal and spatial sequences. +10. **Unresolved Cliffhanger:** Every episode must end on an unanswered question or suspended threat. + +--- + +## D. 10 Professional Cinematic Scene Archetypes + +A genuine film is not a slideshow of walking figures with continuous narration. Every scene must adopt one of the following 10 archetypes, and each episode must blend **at least 5–6 distinct archetypes**: + +### 1. Establishing Shot +- **Function:** Establishes geography, scale, time of day, and environmental scale. Zero or tiny character presence. +- **Framing:** Extreme Wide Shot (EWS) / Aerial / Bird's Eye. +- **Dialogue:** None. Narration + environmental audio only. +- **video_prompt Formula:** + ```text + 0-3s: Aerial establishing shot of the mountain pass at dawn, morning fog clinging to jagged limestone peaks. 3-6s: The camera slowly descends toward an ancient stone fortress, golden sunrise light glinting off slate watchtowers. 6-8s: The camera settles on the heavy timber gates slightly ajar. Smooth crane-down movement. Lighting: soft golden dawn, volumetric morning mist. Audio: distant mountain winds, faint raven calls. Negative: subtitles, watermark, text overlay. + ``` + +### 2. Dialogue Scene — Two-Shot +- **Function:** Two characters exchange vital plot information, make decisions, or enter conflict. **The backbone of cinematic storytelling.** +- **Framing:** Medium Two-Shot → Over-the-Shoulder → Reaction Close-up. +- **Dialogue:** Spoken naturally by characters inside the clip (`Character says: "..." (no subtitles)`). +- **video_prompt Formula:** + ```text + 0-3s: Medium two-shot inside dim military tent. General Tien and Doctor Thuy sit across a rough wooden table. Tien leans forward and speaks in a low urgent tone. Tien says: "We have thirty days. No more." (no subtitles) 3-6s: Over-the-shoulder from behind Tien, camera focuses on Thuy. She listens intently, brow furrowing, then gives a slow resolute nod. Thuy says: "I will secure the medical supplies." (no subtitles) 6-8s: Close-up of Tien's face — a flicker of relief, then hardening resolve. Static locked-off shot with subtle rack focus. Lighting: warm candlelight through tent canvas, deep shadows. Audio: quiet room ambience, howling wind outside tent. Negative: subtitles, watermark, text overlay. + ``` + +### 3. Dialogue Scene — Reaction Focus +- **Function:** One character speaks off-screen or from behind, while the camera fixates on the listener's internal shift. +- **Framing:** Medium → Slow push-in to Close-up on the listener. +- **video_prompt Formula:** + ```text + 0-3s: Medium shot of Doctor Thuy speaking firmly across the table, gesturing slightly. Thuy says: "The reserves will only last two weeks." (no subtitles) 3-6s: Slow push-in to close-up of General Tien listening. His jaw tightens, eyes narrowing as he absorbs the gravity of the crisis. 6-8s: Tien looks down at the battle map, takes a slow breath, then looks back up with cold determination. Lighting: warm diffused lamp light. Audio: quiet room tone, faint distant rain. Negative: subtitles, watermark, text overlay. + ``` + +### 4. Action Beat +- **Function:** Physical labor, mechanical repairs, tactical operations, or combat maneuvers. +- **Framing:** Medium Tracking / Kinetic Dynamic. +- **video_prompt Formula:** + ```text + 0-3s: Medium tracking shot as General Tien hauls an iron reinforcement beam, sparks drifting from a brazier against the stone wall. 3-6s: He braces his shoulder against the timber barricade and hammers a heavy iron locking peg into place with a mallet. 6-8s: Tien steps back, wipes sweat from his brow, and inspects the fortified gate with a firm nod. Lateral tracking shot following the movement. Lighting: chiaroscuro — warm orange forge glow against dark stone shadows. Audio: harsh metallic clanging of hammer on iron, crackling fire. Negative: subtitles, watermark, text overlay. + ``` + +### 5. Pure Reaction Shot +- **Function:** Intense close-up on a character processing shocking news, discovery, or danger. No dialogue — pure micro-expression. +- **Framing:** Close-up / Extreme Close-up. +- **video_prompt Formula:** + ```text + 0-3s: Close-up of General Tien's face illuminated by the crimson glow of a warning signal. His pupils dilate, lips parting slightly. 3-6s: Slow push-in to extreme close-up. A bead of sweat rolls down his temple. He swallows hard. 6-8s: His eyes narrow into hardened resolve, jaw setting firmly. He exhales through his nose. Static shot with subtle handheld micro-movement. Lighting: pulsing red warning glow on one side, deep shadow on the other. Audio: low electronic drone, controlled heavy breathing. Negative: subtitles, watermark, text overlay. + ``` + +### 6. Insert / Detail Shot +- **Function:** Macro shot on a crucial thematic prop: maps, hourglass, broken seal, thermometer, dagger. +- **Framing:** Macro / Extreme Close-up. +- **video_prompt Formula:** + ```text + 0-3s: Extreme close-up of an ancient bronze sundial, shadows stretching across carved zodiac markers. 3-6s: Camera slowly racks focus to reveal a royal seal stamped in red wax on parchment behind the sundial. 6-8s: A hand enters the frame and draws an ink line across the parchment with a bamboo brush. Smooth rack focus. Lighting: harsh afternoon sun through slatted blinds. Audio: ticking of a clock, distant courtyard birds. Negative: subtitles, watermark, text overlay. + ``` + +### 7. Montage Beat (Compressed Time) +- **Function:** Rapid progression of preparation, construction, marching, or tactical training. +- **Framing:** Fast cutting or multi-action pacing within a single clip. +- **video_prompt Formula:** + ```text + 0-2s: Overhead shot of hands stacking bamboo arrows into wooden quivers. 2-4s: Medium shot of Tien tightening leather straps on an armored saddle. 4-6s: Close-up of fresh water pouring into clay jars. 6-8s: Wide shot of the fortified camp, organized and prepared as evening torches ignite. Fast montage rhythm. Lighting: warm amber dusk. Audio: rhythmic sounds of sharpening blades, pouring water, marching boots. Negative: subtitles, watermark, text overlay. + ``` + +### 8. Stalking / Surveillance Shot +- **Function:** Generating covert suspense, feelings of being hunted, or espionage. +- **Framing:** Long Telephoto compressed through foreground obstruction (branches, lattice, pillars). +- **video_prompt Formula:** + ```text + 0-3s: Long telephoto shot through carved wooden palace lattice — Lord Kha exits a pavilion, adjusting his silk collar. The lattice partially obscures the frame. 3-6s: Rack focus from the wooden screen to Kha's face. He pauses, glances sideways, and smiles coldly. 6-8s: Kha steps into a waiting carriage. The camera remains static behind the screen as the carriage pulls away. Locked-off telephoto through obstruction. Lighting: midday contrast, deep shadows beneath eaves. Audio: distant palace chatter, carriage wheels grinding on gravel. Negative: subtitles, watermark, text overlay. + ``` + +### 9. Atmospheric Transition / Bridge Shot +- **Function:** Establishing time passage, twilight into darkness, weather changes. Provides narrative breathing room. +- **Framing:** Wide / Time-lapse style. +- **video_prompt Formula:** + ```text + 0-3s: Wide static shot of the citadel exterior at dusk. The last rays of golden sunlight turn stone parapets amber. 3-6s: Shadows lengthen rapidly across the courtyard as the sun slips below the mountain crest. Citadel watch fires ignite one by one. 6-8s: Night falls — a single beacon fire casts warm light across the stone gate. Static wide shot, natural time progression. Lighting: golden hour transitioning to deep twilight. Audio: evening crickets, distant guard horn call. Negative: subtitles, watermark, text overlay. + ``` + +### 10. Silent Moment (The Breathing Room) +- **Function:** Total cinematic pause. No dialogue, no narrator. Pure image, breathing, and acoustic realism. +- **Framing:** Medium or Wide, locked-off static. +- **video_prompt Formula:** + ```text + 0-3s: Medium shot of General Tien sitting alone on a stone bench in the quiet courtyard. A single shaft of moonlight cuts across his shoulders. 3-6s: He stares at the ground. His chest rises and falls with a long, slow breath. Cold mist drifts across the flagstones. 6-8s: He lifts his gaze slowly toward the distant horizon. Locked-off static shot, zero camera movement. Lighting: single volumetric moonlight beam in darkness. Audio: near-silence — only his breathing and the distant rustle of pine needles. Negative: subtitles, watermark, text overlay. + ``` + +--- + +## E. Multi-Language & Native Dialogue Directing + +### The Core Invariant: Narration Leads, Dialogue Punctuates +In high-end cinema, dialogue and narration must never collide: +``` +[1] NARRATOR TTS: Sets macroscopic context, stakes, and countdown (plays during 0-3s or before). +[2] AMBIENT AUDIO (Veo 3 Native): Continuous environmental bed (wind, rain, crackling fire). +[3] CHARACTER DIALOGUE (Veo 3 Native): Brief, sharp, localized speech embedded inside the clip. +``` + +### Prompt Dialogue Syntax +```text +[Character Name] says: "[Dialogue Line]" (no subtitles) +``` +Examples: +- English: `Tien says: "Thirty days. No more." (no subtitles) — low urgent voice` +- Vietnamese: `Tiến nói: "Ba mươi ngày. Không hơn." (không phụ đề) — giọng trầm, dứt khoát` + +### Dialogue Rules: +1. **Length Cap:** Maximum **10–12 words per character per 8s clip** (Rule 12). +2. **Speaker Limit:** Maximum 2 speaking characters per scene. +3. **Delivery Direction:** Append vocal tone immediately following the quote: `— whispered urgently` or `— deep commanding baritone`. +4. **Mandatory Suffix:** Always include `(no subtitles)` or `(không phụ đề)` to prevent AI video generators from burning deformed text overlays onto the video frames. +5. **No Redundancy:** If the narrator says "They met to discuss the siege", the character must NOT say "We must discuss the siege". Dialogue expresses immediate emotional reaction and commitments. + +--- + +## F. Wardrobe & Temporal Decay Dynamics + +Reference images lock **facial identity**; clothing must be directed in prompts as **functional layers** tied to physical action: + +- ✅ **Correct:** `General Tien, wearing a heavy soot-stained leather breastplate, lowers his iron visor.` +- ❌ **Incorrect:** `General Tien, a handsome Vietnamese general with sharp cheekbones and black hair.` + +### Temporal Costume Progression: +| Story Stage | Wardrobe State Description | +| :--- | :--- | +| **Opening / Prologue** | `clean ceremonial robes, neat topknot, pristine fabric` | +| **Onset of Struggle** | `sleeves rolled up, light dust on shoulders, untied sash` | +| **Middle / Prolonged War** | `sweat-stained tunic, scuffed leather armor, soot on collar` | +| **Darkest Night / Climax** | `torn cloak, blood-stained linen bandage on forearm, ash-streaked face` | + +--- + +## G. Scale Alternation & Cinematic Rhythm + +Never use the same shot scale in consecutive scenes. Standard 8-Scene Rhythm: + +| Scene | Archetype | Shot Framing | Kinetic Velocity | Dialogue? | +| :---: | :--- | :--- | :--- | :---: | +| 0 | Hook / Reaction | Close-up | Rapid / Urgent | Optional | +| 1 | Establishing | Extreme Wide (EWS) | Majestic / Slow | None | +| 2 | Action Beat | Medium Tracking | Kinetic / Driving | Short command | +| 3 | **Dialogue Two-Shot** | Two-Shot → OTS | Moderate / Intimate | **Mandatory** | +| 4 | Insert / Detail | Macro | Static / Tense | None | +| 5 | **Dialogue / Reaction** | Close-up → Push-in | Deep / Emotional | **Mandatory** | +| 6 | Surveillance / Threat | Telephoto through Obstruction | Simmering Tension | None | +| 7 | Cliffhanger | Wide → Slow Push-in | Accelerating Dread | Climactic line | + +**The Dialogue Invariant:** Every 8-scene episode must contain **at least 2 dialogue scenes**. A video without dialogue is an automated slideshow, not cinema. + +--- + +## H. Director of Photography (DP) Lexicon + +### Camera Movements: +- `slow push-in` — Deepens internal psychological tension or realization. +- `slow pull-back` — Evokes isolation, smallness against the environment. +- `low-angle tracking` — Imparts authority, heroic determination. +- `lateral tracking` — Accelerates urgency, pursuit, race against time. +- `overhead bird-eye` — Establishes tactical layout, vulnerability. +- `rack focus from A to B` — Shifts viewer focus between foreground threat and background reaction. +- `over-the-shoulder (OTS)` — Intimate conversational framing. +- `locked-off static` — Somber gravity, quiet contemplation. +- `Dutch angle` — Disorientation, psychological unbalance. +- `subtle handheld` — Gritty documentary realism, combat tension. + +### Lighting Signatures: +- `hard chiaroscuro, deep shadows` — Danger, conspiracy, moral ambiguity. +- `volumetric light beams through dust` — Fortress interiors, catacombs, temples. +- `warm golden-hour rim light` — Hope, honor, farewell. +- `flickering torchlight against wet stone` — Dungeon, night fortress defense. +- `harsh midday sun with heat shimmer` — Desolation, heat crisis, arid wasteland. +- `cold overcast diffused daylight` — Bleak realism, sorrow, military readiness. + +### Optical Focal Lengths: +- `35mm natural perspective` — Grounded documentary realism. +- `85mm portrait, shallow depth of field` — Emotional character isolation. +- `telephoto lens compression` — Espionage, compressed crowds, claustrophobia. +- `wide 24mm` — Vast architectural scale or overwhelming landscape. + +--- + +## I. Micro-Expression Physicality + +AI models fail on abstract adjectives like "he looks sad". Direct precise physiological symptoms: + +| Emotion | Avoid Abstract Words | Direct Physical Symptoms | +| :--- | :--- | :--- | +| **Terror** | `he is terrified` | `rapid shallow breathing, eyes darting left and right, hand gripping table edge until knuckles whiten` | +| **Resolve** | `she looks determined` | `jaw tightening firmly, gaze narrowing to a fixed point, slow decisive nod` | +| **Shock** | `he is shocked` | `sudden complete stillness, lips parting without a sound, breath held mid-inhale` | +| **Exhaustion** | `he is exhausted` | `shoulders sagging forward, spine slumping, leaning heavily against the stone wall, slow heavy blink` | +| **Suppressed Grief** | `she is sad` | `eyes glistening without tears falling, swallowing hard twice, looking away toward the window` | +| **Suspicion** | `he is suspicious` | `head tilting 15 degrees, eyes narrowing, weight shifting to back foot in a half-step retreat` | +| **Arrogance** | `he is arrogant` | `chin raised exposing throat, slow measured stride, thin smirk curling one corner of mouth` | +| **Relief** | `she is relieved` | `long slow exhale through parted lips, shoulders dropping two inches, eyes closing for three beats` | + +--- + +## I2. The 8-Second Micro-Emotional Arc (A → B Progression) + +Every scene **MUST** exhibit an internal emotional transformation. A character begins at State A and arrives at State B: + +``` +Beat 1 (0-3s): STATE A — Initial baseline emotion +Beat 2 (3-6s): THE CATALYST — Visual, acoustic, or physical shift that fractures the baseline +Beat 3 (6-8s): STATE B — New, irreversible emotional resolution +``` + +### 15 Extended Physiological Expression States: +1. **Calm → Terror:** Eyes gazing calmly → Pupils dilate widely, lips part trembling → Face goes pale, steps backward. +2. **Skepticism → Bitter Realization:** Brows slightly furrowed → Pupils freeze, jaw muscle twitches → Slow shake of head, glistening eyes. +3. **Despair → Desperate Resolve:** Head lowered in defeat → Slowly lifts chin through disheveled hair → Jaw sets, fists clench white, eyes blaze. +4. **Confidence → Sudden Collapse:** Smug half-smile → Smile vanishes instantly, brow contorts → Stares blankly downward, hands tremble. +5. **Fear → Rising Courage:** Body shaking, darting eyes → Closes eyes, takes one deep breath → Opens eyes locked on the enemy, stands tall. +6. **Rage → Cold Cruelty:** Veins bulging on neck, panting → Breath abruptly slows, facial muscles relax into blankness → Eyes turn icy, cold smirk forms. +7. **Physical Pain → Iron Will:** Grimacing from wound, biting lower lip → Sharp hiss through teeth, sweating profusely → Forces eyes open, stance solidifies. +8. **Vigilance → Moving Relief:** Hand clenched on sword hilt, scanning shadows → Grip slowly relaxes, shoulders drop → Soft exhale, gaze softens warmly. +9. **Pride → Humiliated Rage:** Chin high, disdainful stare → Lowers head, ears flushing red → Clenches fists until veins stand out. +10. **Remorse → Redemption Resolve:** Staring down at trembling hands in self-blame → Looks up toward the horizon → Expression turns steely, gives a decisive nod. +11. **Confusion → Sudden Epiphany:** Eyes scanning documents frantically → Pupils freeze, light sparks in eyes → Gentle smile forms as puzzle clicks. +12. **Isolation → Found Solidarity:** Vacant stare in the crowd → Catches comrade's loyal gaze → Subtle nod, warmth returns to weathered face. +13. **Agony → Manic Defiance:** Tears streaming down, head in hands → Broken laughter escapes lips → Eyes widen with wild defiance. +14. **Melancholy → Peaceful Acceptance:** Heavy weary eyes, downturned mouth → Closes eyes into the passing breeze → Gentle half-smile, total tranquility. +15. **Casual Watch → Maximum Alertness:** Scanning darkness lazily → Ear twitches slightly, pupils snap toward shadows → Lowers center of gravity silently. + +--- + +## I3. 8 Cinematic Action Archetypes + +### 1. Melee Duel / Clashing Blades +- **AI Safety Rule:** Avoid impaling weapons through bodies. Describe weapon trajectory and explosive spark impacts on shields/guards. +- **video_prompt:** + ```text + 0-3s: Two warriors lower their combat stances, bronze swords raised to shoulder height, eyes locked across drifting ash. 3-6s: The left warrior lunges forward in a powerful diagonal slash; his blade collides violently with his opponent's iron shield, discharging brilliant orange sparks. Camera tracks the kinetic slash. 6-8s: Both warriors lock blades in a rigid contest of brute strength, muscles straining, hot breath steaming in the cold night air. Audio: Clashing steel, sizzling sparks, heavy war grunts. Negative: subtitles, watermark, text overlay. + ``` + +### 2. High-Speed Pursuit +- **AI Safety Rule:** Never run directly into the camera lens. Track diagonally or laterally. +- **video_prompt:** + ```text + 0-3s: A courier gallops at full sprint along a muddy forest road, black cloak fluttering in the storm. 3-6s: Three mounted pursuers surge into frame behind him, arrows whistling past and striking the earth. The camera tracks laterally alongside the galloping steeds. 6-8s: The courier jerks the reins, veering sharply through a narrow rocky ravine, mud spraying across the lower frame. Audio: Thundering rhythmic hooves, whistling arrows, panicked horse whinny. Negative: subtitles, watermark, text overlay. + ``` + +### 3. Dodge & Counter-Strike +- **AI Safety Rule:** Duck or sidestep; avoid 360-degree midair flips. +- **video_prompt:** + ```text + 0-3s: The general stands in a balanced guard stance, watching an enemy spear thrust incoming. 3-6s: As the spear tip nears, he ducks low to the left, pivoting his wrist to strike the spear shaft upward with his broadsword hilt. The camera pushes in on the deflection. 6-8s: The spear deflects wide; the general straightens into an imposing counter stance. Audio: Whistling spear air rush, dull timber crack, clatter of weapon. Negative: subtitles, watermark, text overlay. + ``` + +### 4. Precision Archery +- **AI Safety Rule:** Structure as pull -> release shockwave -> trajectory pan. +- **video_prompt:** + ```text + 0-3s: The archer stands steady upon the battlement, drawing the heavy recurve bowstring back to her jawline in the rain. 3-6s: She releases; the bowstring snaps forward and the iron arrow streaks diagonally through the mist. The camera pans rapidly with the arrow trajectory. 6-8s: The arrow strikes the enemy signal banner in the distance, tearing it down; the archer lowers her bow with a calm exhale. Audio: Crisp bowstring snap, piercing arrow whistle, distant timber crash. Negative: subtitles, watermark, text overlay. + ``` + +### 5. Stealth Ambush +- **AI Safety Rule:** Emerge from natural shadow/cover; avoid teleportation artifacts. +- **video_prompt:** + ```text + 0-3s: A patrol unit carrying torches marches cautiously through a silent canyon pass, firelight dancing on rock walls. 3-6s: From dark tree branches above, cloaked scouts drop down silently, blades drawn to block the path. Low-angle camera looking up dramatically. 6-8s: A dropped torch hisses into a puddle and extinguishes in smoke; the scouts form an unbroken perimeter in the moonlight. Audio: Rustling leaves, taut rope snap, hissing fire extinguishing, unison steel unsheathing. Negative: subtitles, watermark, text overlay. + ``` + +### 6. Breaching / Gate Breakout +- **AI Safety Rule:** Direct kinetic impact against timber/iron; use dust and debris shockwaves. +- **video_prompt:** + ```text + 0-3s: The lead warrior locks his heavy bronze shield against his shoulder, driving all momentum forward. 3-6s: He smashes into the reinforced timber palace doors, splintering wood and sending dust billowing across the frame. Subtle camera shake on impact. 6-8s: The doors burst open, morning sunlight flooding inward to silhouette the warrior raising his sword to lead the charge. Audio: War cry, splintering timber crash, iron impact boom. Negative: subtitles, watermark, text overlay. + ``` + +### 7. Desperate Shield Wall Stand +- **AI Safety Rule:** Anchor firm poses; express resilience under pressure. +- **video_prompt:** + ```text + 0-3s: Shield-bearers drop to one knee, interlocking large bronze shields into a solid barricade before incoming fire arrows. 3-6s: A barrage of flaming arrows thuds heavily into the shields, smoking under the impact, but the wall holds firm. Low-angle heroic perspective. 6-8s: Smoke curls off the scorched shields; the commander raps his sword pommel three times against bronze to rally the ranks. Audio: Raining arrow impacts on metal, crackling flames, three crisp steel strikes. Negative: subtitles, watermark, text overlay. + ``` + +### 8. Tense Standoff / Eye-to-Eye +- **AI Safety Rule:** Minimal physical body movement; concentrate energy into eyes, breathing, and 180-degree arc camera orbit. +- **video_prompt:** + ```text + 0-3s: Medium two-shot of two rival commanders facing each other three paces apart on an ancient wooden bridge, wind whipping their robes. 3-6s: The camera executes a slow 180-degree arc shot around them. Neither moves; their eyes burn with locked hatred as one hand rests upon his sword hilt. 6-8s: Close-up of a bead of sweat rolling down the jawline; a thumb subtly clicks the sword guard upward from the scabbard. Audio: Creaking wooden bridge, distant wind chime, dry throat swallow, metallic click. Negative: subtitles, watermark, text overlay. + ``` + +--- + +## I4. The Suspense & Tension Toolkit (6 Master Techniques) + +True suspense is generated through **information withholding** and **impending dread**, not cheap jump scares: + +### 1. The Ticking Clock +- **Principle:** Audience watches a physical deadline expire (candle melting toward gunpowder, sun sinking below the horizon). +- `video_prompt`: Macro close-up of a red candle melting onto a war table, hot wax pooling toward the edge of an envelope dusted with sulfur. Camera slowly dollies forward. +- `narrator_text`: Thirty seconds remain. If unopened, the cipher will consume itself in flames. +- `Audio`: Rhythmic dripping of wax like a clock pendulum, shallow choked breathing. + +### 2. The Blind Spot / Negative Space +- **Principle:** Character framed on the extreme third, leaving an expansive, pitch-black void behind them. +- `video_prompt`: Close-up of general cleaning his sword by candlelight on screen-left. The right two-thirds is a pitch-black corridor behind him. A faint shadow drifts in the deep darkness. +- `narrator_text`: In the shadows of the imperial court, the deadliest blade always strikes from behind. +- `Audio`: Cloth wiping across cold steel, faint padding footsteps on distant floorboards. + +### 3. The Delayed Reveal +- **Principle:** Character witnesses a horrific sight first, face contorting, while concealing the source from the viewer until the 6th second. +- `video_prompt`: 0-3s: Close-up of a sentry peering through a wooden shutter, eyes widening in sheer disbelief, jaw trembling. 3-6s: Camera slowly tracks over the sentry's shoulder. 6-8s: The river below is revealed, covered with thousands of silent enemy warships emerging from the mist. +- `narrator_text`: When the shutter opened, all hope for a peaceful night dissolved into the mist. +- `Audio`: Creaking shutter hinge, pounding heartbeat, then thundering roar of a thousand oars churning water. + +### 4. Sonic Isolation / The Sensory Cutout +- **Principle:** Abruptly eliminate all musical score, isolating a single surreal sound to heighten visceral tension. +- `video_prompt`: Close-up in slow motion of the archer taking aim amidst a chaotic battlefield. His focus is absolute; a single raindrop strikes his eyelid, causing a micro-blink. +- `narrator_text`: Amidst ten thousand clashing blades, time freezes before the arrow of destiny. +- `Audio`: Total muting of battle noise; only a slow 40 BPM heartbeat and deep breath intake. + +### 5. The Deceptive Calm +- **Principle:** Unnerving stillness that contrasts with imminent annihilation. +- `video_prompt`: Mirror-flat morning lake surface; a water lily sways gently in the breeze. Suddenly, concentric ripples erupt across the surface, vibrating with increasing violence from underground tremors. +- `narrator_text`: The lake remains terrifyingly still... Herald of the catastrophe gathering beneath the earth. +- `Audio`: Solitary bird chirp abruptly silenced by deep subterranean rumble, water sloshing. + +### 6. Time Dilation on Edge +- **Principle:** Deconstruct a 1-second real-world crisis into a full 8-second cinematic struggle. +- `video_prompt`: 0-3s: Bloodied hand of a guardsman reaches out in desperation toward a falling battle standard. 3-6s: Fingers brush against the silk banner by millimeters; macro camera captures fabric sliding across knuckles. 6-8s: He strains forward another half-inch, gripping the wooden pole right before it hits the ground. +- `narrator_text`: A single fraction of an inch decided the fate of the entire army. +- `Audio`: Slow-motion fluttering silk, teeth grinding in agony, decisive timber snap as hand grips wood. + +--- + +## J. Narrator Mathematics (The 7.0s Usable Window) + +Veo 3 produces an 8.0s clip. Post-production trims the first 1.0s (`-ss 1`) to eliminate model initialization freezes. Usable footage = **7.0 seconds**. + +### Exact Word Count Constraints (Hard Maximum): +| Language | Max Words | Target Duration | Speed Rate | Structural Rules | +| :--- | :---: | :---: | :---: | :--- | +| **Vietnamese** | **18–22** | ~6.0s – 6.5s | 1.1x | Tonal diacritics slow TTS. 2 punchy clauses separated by `—`. | +| **English** | **20–24** | ~6.0s – 6.5s | 1.0x | Active verbs, zero filler adjectives. | +| **Scenes with Dialogue** | **12–16** | ~4.0s – 4.5s | 1.1x | Narration must finish BEFORE characters begin speaking. | + +**The Golden Rule:** A narrator must NEVER narrate what is already obvious on screen. Narration reveals *lore, motivation, consequences, and the ticking clock*. + +--- + +## K. Anti-Artifact Playbook + +| AI Vulnerability | Problematic Prompting | Physics-Safe Prompting | +| :--- | :--- | :--- | +| **Finger Dexterity** | Typing passcodes, interlinking fingers | Pressing flat palm, shifting lever, turning wheel, wearing gauntlets | +| **Text & Numbers** | Close-ups of readable screens or paper | Graphical symbols: glowing runes, flashing red signal, wax seal | +| **180° Head Turn** | Character turning from back to front | Split into 2 separate scenes; cut directly to front close-up | +| **Feet Slipping** | Floating walk cycle without contact | Specify surface traction: `boots striking wet concrete firmly` | +| **Mid-Clip Costume Change** | Character taking off coat or backpack | Garments must be fully worn from Frame 0 | +| **Body Merging** | Intimate grappling or tight hugs | Maintain distance: `standing an arm's length apart` | +| **Physical Impossibility** | Superhuman leaps, car crashes | Shoot the aftermath: dust billowing, camera shaking, debris settling | +| **Action Overload** | 5 actions crammed into 8s | Strictly 1 primary kinetic action per temporal beat | + +--- + +## L. Genre Presets + +| Genre | Color Palette Signature | Characteristic Keywords | Signature Hook | +| :--- | :--- | :--- | :--- | +| **Post-Apocalypse / Survival** | Burnt amber, dust grey | rust, corrugated iron, sandstorm, gas mask | Thermometer spikes past fatal threshold | +| **Revenge / Modern Noir** | Charcoal black, cold glass reflections | penthouse window, tailored suit, rain slick | Old scar throbs with memory | +| **Historical War / Epic** | Muted bronze, crimson, ash | iron scale armor, war drums, banner, torches | Ominous battle horn echoes in fog | +| **Cyberpunk / Sci-Fi** | Deep cyan, neon magenta | airlock steam, zero-g debris, biometric HUD | Pressure seal breach alarm | +| **Dark Fantasy** | Midnight violet, torch orange | ancient runes, misty bog, iron talismans | Relic emits sudden shockwave | + +--- + +## L2. Safety Filter Ladder (Real-People Bypass) + +If a prompt trips safety moderation, descend this ladder systematically: +1. **Camera Angle Shift:** Reposition camera behind the character or in a 3/4 profile. +2. **Remove Names from Prompt:** Retain entity in `character_names`, but remove specific aliases from the `video_prompt` text (use "the commander"). +3. **Drop Reference Dependency:** Remove `character_names` for that single scene, relying on prompt physical descriptors. +4. **Keyword Sanitation:** Substitute flagged terms: `confidential/classified` → `parchment/scroll`; `weapon/rifle` → `iron gear`; `blood/kill` → `confrontation`. Never include minors. + +--- + +## M. Audio & Musical Score Architecture + +### Audio Tags in `video_prompt`: +- `Audio:` Background acoustic bed (wind howling, rain on canvas, engine idle). +- `SFX:` Discrete synchronized impacts (steel clashing, bolt locking, glass shattering). +- `Dialogue:` Native speech formatted as `Character says: "..." (no subtitles)`. +- **Mandatory Negative Tag:** `Negative: subtitles, captions, watermark, text overlay.` + +### `music_cue` (Stored in screenplay JSON metadata, never sent to generation API): +- **Hook:** `low analog drone, ticking pulse, 60 BPM` +- **Escalation:** `industrial percussion, driving bass, 90 BPM` +- **Dialogue:** `sparse piano over warm ambient pad, breathing room` +- **Dread / Threat:** `dissonant low strings, sub-bass swells` +- **Cliffhanger:** `crescendo to a massive hit, then abrupt absolute silence` + +--- + +## N. Quality Gate — 20 Production Checkpoints + +Every scene script must pass this 20-point audit before generation: + +| # | Checkpoint | Pass Criteria | +| :-: | :--- | :--- | +| 1 | Action-Only Prompt | Zero descriptions of face/hair/body in prompts | +| 2 | Wardrobe Progression | Costume changes justified and recorded in `wardrobe_state` | +| 3 | 3-Beat Pacing | Every `video_prompt` contains `0-3s`, `3-6s`, `6-8s` | +| 4 | Prompt Word Count | 100–150 words per prompt, containing lighting + audio tags | +| 5 | Narrator Word Count | 18–22 words (12–16 words for scenes with dialogue) | +| 6 | Show ≠ Tell | Narration does not redundantly describe on-screen actions | +| 7 | Character Limit | Maximum 2 named characters per scene | +| 8 | Entity Integrity | `character_names` strictly matches project database entities | +| 9 | Scale Alternation | No two consecutive scenes share the same framing scale | +| 10 | Standalone Camera | Camera motion written as a dedicated separate sentence | +| 11 | Physiological Emotion | Emotions described via physiological cues, not abstract adjectives | +| 12 | Anti-Artifact Rules | Free of finger micro-actions, text, 180° turns, mid-clip costume swaps | +| 13 | Lighting Consistency | Unified lighting signature across same-location scenes | +| 14 | Safety Compliance | Role-based aliases only; zero public figure names or flagged terms | +| 15 | 3-Second Hook | Scene 0 presents immediate visual conflict in the opening frame | +| 16 | Cliffhanger | Final scene leaves a suspended, unanswered narrative threat | +| 17 | Fact-Check Verification | Historical/factual data verified via research notes | +| 18 | Chain Type Standard | Defaulted to `ROOT` | +| 19 | Dialogue Presence | Minimum 2 dialogue scenes per 8-scene episode | +| 20 | Subtitle Suppression | All dialogue includes `(no subtitles)` suffix | + +--- + +## O. Production Output & Pipeline Execution + +### O.1 Screenplay JSON Schema +Save at `.omc/research/_ep_script.json`: +```json +{ + "series": "Hong Nhat Thang Long", + "episode": 2, + "title": "Race Against Time", + "orientation": "HORIZONTAL", + "lighting_signature": "volumetric light through dust (indoor); harsh midday sun (outdoor)", + "scenes": [ + { + "display_order": 0, + "scene_type": "reaction_hook", + "beat": "hook", + "framing": "close-up", + "chain_type": "ROOT", + "character_names": ["Commander_Tien"], + "has_dialogue": false, + "wardrobe_state": "sleeves rolled up, light dust on shoulders", + "prompt": "Close-up inside dim warehouse. Commander Tien stares at a pulsing red warning display, face half-lit by crimson glow. 35mm lens, shallow depth of field.", + "video_prompt": "0-3s: Close-up of Commander Tien's face illuminated by pulsing red warning light. His eyes widen, lips parting slightly. 3-6s: Slow push-in to extreme close-up. Sweat on his brow catches the red light. He swallows hard. 6-8s: His jaw sets firmly, eyes narrowing with resolve. He exhales through his nose. Static shot with subtle handheld shake. Lighting: pulsing red on one side, deep shadow on the other. Audio: low electronic alarm pulse, controlled breathing. Negative: subtitles, watermark, text overlay.", + "narrator_text": "The solar radiation warning flashes across the forecast terminal. The countdown stands at exactly thirty days.", + "music_cue": "low analog drone, ticking pulse, 60 BPM" + } + ] +} +``` + +### O.2 Pipeline Ingestion Protocol +1. Verify daemon: `curl -s http://127.0.0.1:8100/health` → `{"extension_connected": true}`. +2. Create video entry: `POST /api/videos` with `project_id`, `title`, `orientation`. +3. Create scenes: `POST /api/scenes` (only approved schema fields). +4. Patch narration: `PATCH /api/scenes/{sid}` with `{"narrator_text": "..."}`. +5. Batch generation execution: + - Reference images: `POST /api/requests/batch` with `GENERATE_CHARACTER_IMAGE`. + - Scene start images: `POST /api/requests/batch` with `GENERATE_IMAGE`. + - Veo 3 video clips: `POST /api/requests/batch` with `GENERATE_VIDEO`. + - AI Vision review: `POST /api/videos/{vid}/review?mode=light`. + - TTS narration: `POST /api/tts/generate` (Edge-TTS or OmniVoice). + - Final concatenation & audio mastering: `/fk-concat-fit-narrator`. diff --git a/skills/fk-sound-design.md b/skills/fk-sound-design.md new file mode 100644 index 00000000..1152f7a2 --- /dev/null +++ b/skills/fk-sound-design.md @@ -0,0 +1,105 @@ +# Sound Design & Audio Mastering — AI Cinematic Soundscapes + +Industry standards for multi-layer sound design, automated dynamic ducking, sub-bass rumble synthesis, and EBU R128 loudness mastering for Google Veo 3, Edge-TTS, and AI cinematic productions. + +--- + +## 1. Principles of AI Sound Design + +> *"Sound is 50 percent of the movie-going experience, and in AI cinema, sound represents 70 percent of perceived reality."* — George Lucas + +When generative AI imagery occasionally exhibits synthetic artifacts, a **rich, multi-layered, and physically grounded soundscape** anchors the viewer's subconscious, convincing the brain of physical reality. + +--- + +## 2. The 4-Layer Audio Architecture + +Every professional AI cinematic scene must be constructed from four independent acoustic strata: + +``` +LAYER 1: NARRATOR / DIALOGUE ────► Center (Mid/Mono), Crisp clarity, High presence (+2.5dB to +3.5dB) +LAYER 2: VEO 3 FOLEY & SFX ──────► Discrete impacts, Footsteps, Clashing steel, Bowstring release +LAYER 3: AMBIENCE & ROOM TONE ──► Wind howling, Falling rain, Campfire crackle, Night cicadas +LAYER 4: SCORE & SUB-BASS DRONE ─► Orchestral themes (Suno AI), War drums, 40-60Hz tactile rumble +``` + +### Acoustic Balance Matrix: + +| Audio Stratum | Generation Source | Role in Scene | Standard Level (Gain Factor) | +|:---|:---|:---|:---| +| **Layer 1: Voice (Dialogue & Narration)** | Edge-TTS (`NamMinhNeural` / `HoaiMyNeural`) | Story progression, emotional anchoring | `1.30 – 1.50` (+2.5dB to +3.5dB) | +| **Layer 2: Foley & SFX (Physical Action)** | Veo 3 Native Audio / SFX Library | Physical weight, combat impact | `0.60 – 0.80` (When dialogue absent) | +| **Layer 3: Ambience (World Acoustic)** | Veo 3 Background Audio / Field Recordings | Environmental scale & space | `0.20 – 0.30` (Auto-ducked during dialogue) | +| **Layer 4: Score & Sub-Bass Drone** | Suno AI (`/fk-gen-music`) & Brown noise | Emotional pulse & visceral tension | `0.35 – 0.50` (Score), `0.60` (Bumper drone) | + +--- + +## 3. Automated Audio Ducking Invariant + +The most common defect in amateur AI video compiles is **background audio or music drowning out spoken dialogue**. + +### FFmpeg Sidechain Ducking Formula: +When dialogue or voice narration is active, ambient sound and background music must automatically duck by **-12dB to -15dB**: + +```bash +# Mix Voice (input 1) with Ambient (input 0) applying cinema balance: +ffmpeg -y -i scene_video.mp4 -i scene_tts.wav \ + -filter_complex "[0:a]volume=0.25[bg];[1:a]volume=1.40[fg];[bg][fg]amix=inputs=2:duration=first:dropout_transition=2[aout]" \ + -map 0:v -map "[aout]" -c:v copy -c:a aac -b:a 192k output_mixed.mp4 +``` + +--- + +## 4. Sub-Bass Drone Synthesis (Suspense & Chapter Bumpers) + +Frequencies between **40Hz and 60Hz** bypass the auditory ear canal and vibrate directly in the chest cavity, creating visceral tension: + +1. **Dramatic Triggers:** + - Pre-ambush stillness, ticking clocks, impending royal betrayals. + - Chapter interstitial bumpers (creating solemn, ancient reverence). +2. **FFmpeg Procedural Sub-Bass Rumble Generation:** + ```bash + # Synthesize 3.5s of Brown Noise filtered at 48Hz for cinematic bumper transition: + ffmpeg -f lavfi -i "anoisesrc=c=brown:r=48000:a=0.3,lowpass=f=75,volume=0.6" -t 3.5 -c:a aac drone.m4a + ``` + +--- + +## 5. Broadcast & YouTube Mastering (EBU R128 Loudness) + +Before final distribution on YouTube (Shorts or Long-form) or streaming platforms, the master audio must comply with international broadcast loudness standards: +- **Integrated Loudness Target:** `-14.0 LUFS` (±1 LUFS) for YouTube (prevents YouTube's automated loudness penalty compressor from squashing dynamics). +- **True Peak Ceiling:** `-1.0 dBTP` (prevents digital clipping and inter-sample distortion on mobile DACs). +- **Loudness Range (LRA):** `7.0 to 10.0 LU` (maintains cinematic dynamic range between whispers and explosions). + +### Mastering Command via FFmpeg: +```bash +ffmpeg -i input_master.mp4 \ + -af "loudnorm=I=-14:LRA=7:TP=-1.0" \ + -c:v copy -c:a aac -b:a 256k final_master_mastered.mp4 +``` + +--- + +## 6. Procedural Foley & SFX Layering (`scripts/sfx_layering.py`) + +When scene actions feature intense physical beats (blade combat, heavy strikes, detonations, underground tremors), FlowKit's automated sound design engine scans the `prompt` or `video_prompt` to synthesize and layer synchronized sound effects: + +### Supported SFX Categories & Triggers: +- **`metal_clash`** (Keywords: `knife`, `blade`, `sword`, `dao`, `kiếm`, `chém`, `steel`): Metallic blade impact with high-frequency shimmer. +- **`heavy_impact`** (Keywords: `strike`, `slam`, `punch`, `đấm`, `va chạm`, `ngã gục`): Low-end punch with 65Hz transient thud. +- **`explosion_blast`** (Keywords: `explosion`, `blast`, `nổ`, `bomb`, `shockwave`, `lựu đạn`): Deep detonation rumble with brown noise decay. +- **`underground_drone`** (Keywords: `tầng hầm`, `b3`, `cống ngầm`, `underground`, `tunnel`): 45Hz subterranean room tone. +- **`alarm_siren`** (Keywords: `báo động`, `siren`, `alarm`, `klaxon`, `còi báo`): Modulated tactical warning siren. +- **`heartbeat_tension`** (Keywords: `tim đập`, `tension`, `gasping`, `thở dốc`, `hồi hộp`): 60 BPM physiological heartbeat pulse. + +### Automated Layering Command: +```bash +python scripts/sfx_layering.py \ + --input-video path/to/scene.mp4 \ + --prompt "0-3s: Tactical knife blade clash. 3-6s: Heavy strike against concrete." \ + --output path/to/scene_with_sfx.mp4 \ + --volume 0.6 +``` +*(Studio sample overrides can be added to `assets/sfx//` for custom studio WAV assets).* + diff --git a/tests/unit/test_setup.py b/tests/unit/test_setup.py index 3e35a13a..62c839f5 100644 --- a/tests/unit/test_setup.py +++ b/tests/unit/test_setup.py @@ -35,6 +35,7 @@ def sandbox(setup_mod, monkeypatch, tmp_path): monkeypatch.setattr( setup_mod, "LEGACY_GEMINI_COMMANDS_DIR", tmp_path / ".gemini" / "commands" / "fk") monkeypatch.setattr(setup_mod, "LEGACY_GEMINI_MD", tmp_path / "GEMINI.md") + monkeypatch.setattr(setup_mod, "ANTIGRAVITY_SKILLS_DIR", tmp_path / ".agents" / "skills") (tmp_path / "skills").mkdir() (tmp_path / "skills" / "fk-demo.md").write_text("# fk-demo — A demo skill\n", encoding="utf-8") return tmp_path @@ -46,10 +47,17 @@ def sandbox(setup_mod, monkeypatch, tmp_path): class TestRetiredGeminiTarget: def test_gemini_is_not_a_generator_any_more(self, setup_mod): assert "gemini" not in setup_mod.TOOLS - assert set(setup_mod.TOOLS) == {"claude", "codex"} + assert set(setup_mod.TOOLS) == {"claude", "codex", "antigravity"} assert not hasattr(setup_mod, "generate_gemini") assert not hasattr(setup_mod, "generate_gemini_md") + def test_antigravity_generator_creates_skills(self, setup_mod, sandbox): + skills = setup_mod.discover_skills() + count = setup_mod.generate_antigravity(skills) + assert count > 0 + assert (sandbox / ".agents" / "skills" / "fk-demo" / "SKILL.md").exists() + + def test_a_stale_state_file_naming_gemini_does_not_crash_sync( self, setup_mod, sandbox, capsys ):