LOT 1 - Optimizare script build -Instalare mono comanda

ai_platform/modules/video-analysis/INDEX.md

@@ -4,8 +4,8 @@ Video analysis service for DIDI. Performs deepfake detection and semantic tempor
 
 - **Stack:** Python 3.11+, FastAPI, uvicorn, OpenCV (headless), Pillow, NumPy, httpx/requests, ffmpeg toolchain (via OpenCV), pydantic-settings + YAML
 - **URL (Dev):** `http://10.11.10.12:54600`
-- **Container:** runs on GPU host (`network_mode: host` in `deploy/docker-compose.yml`); the service itself is CPU-only — GPU is consumed by the upstream vLLM server
-- **Vision backend:** external vLLM server (default: BusterX 7B @ port `54500`); same endpoint also drives semantic analysis. Optional alternative: Qwen3-VL-30B @ port `14002` for richer semantic narratives. The wider DIDI vision cascade (Qwen Vision local → Gemini Flash → GPT-4o) lives in `agent-v3`; this service only talks to one vLLM at a time.
+- **Container:** runs on GPU host, attached to the external bridge network `didi-network` (see `deploy/docker-compose.yml`); the service itself is CPU-only — GPU is consumed by the upstream vLLM server
+- **Vision backend:** external vLLM server (BusterX 7B @ port `54500`); the **same** BusterX endpoint drives both deepfake detection and semantic per-chunk analysis. Semantic narratives are produced by aggregating the per-chunk descriptions with the DIDI text LLM (Qwen3.5) via `http://didiAI-llm-api:14011`. The wider DIDI vision cascade (Qwen Vision local → Gemini Flash → GPT-4o) lives in `agent-v3`; this service talks only to the BusterX vLLM.
 
 ## Ce face
 
@@ -50,8 +50,8 @@ Auth: none (called over private network / through Kong upstream by agent-v3).
 
 This service does **not** implement a multi-provider cascade. It is a thin client over a single vLLM endpoint configured at startup:
 
-- **Primary (deepfake):** BusterX (Qwen2.5-VL-7B fine-tune, `l8cv/BusterX_plusplus`) at `VIDEO_ANALYSIS_VLLM_BASE_URL` — typically `http://didiAI-video-vllm-buster:54500` on the GPU host
-- **Optional (semantic):** Qwen3-VL-30B at `http://didiAI-llm-vllm-vision:14002` — swap by editing `deploy/.env` and rebuilding
+- **Deepfake + semantic (vision):** BusterX (Qwen2.5-VL-7B fine-tune, `l8cv/BusterX_plusplus`, served as `busterx`) at `VIDEO_ANALYSIS_VLLM_BASE_URL` — typically `http://didiAI-video-vllm-buster:54500` on the GPU host. The same endpoint handles both the deepfake verdict and the per-chunk semantic descriptions. BusterX is self-contained (Qwen2.5-VL is bundled inside the fine-tune) — it does not load a separate Qwen base model.
+- **Semantic aggregation (text):** per-chunk descriptions are merged into a narrative `final_summary` by the DIDI text LLM (Qwen3.5) via `http://didiAI-llm-api:14011` — set through `VIDEO_ANALYSIS_SEMANTIC_LLM_BASE_URL`.
 - **DIDI-wide cascade** (Qwen Vision local → OpenRouter Gemini Flash → GPT-4o) is implemented in agent-v3, NOT here. This service is a leaf node in that chain — agent-v3 calls it as one of several vision options.
 - Service refuses to start if `VIDEO_ANALYSIS_VLLM_BASE_URL` is not set or the vLLM endpoint is unreachable (see `buster_client.py`, `settings.py`).
 
@@ -62,7 +62,7 @@ Env vars (prefix `VIDEO_ANALYSIS_`), loaded from `deploy/.env`:
 | Variable | Required | Description |
 |---|---|---|
 | `VIDEO_ANALYSIS_VLLM_BASE_URL` | yes | Upstream vLLM server URL |
-| `VIDEO_ANALYSIS_VLLM_MODEL` | yes | Model name passed to vLLM (`busterx`, `qwen3-vl`, `l8cv/BusterX_plusplus`, …) |
+| `VIDEO_ANALYSIS_VLLM_MODEL` | yes | Served model name passed to vLLM (`busterx`; underlying weights `l8cv/BusterX_plusplus`) |
 | `VIDEO_ANALYSIS_RUNS_DIR` | yes | Where to drop per-request artifacts (default `/app/runs` in container) |
 | `VIDEO_ANALYSIS_EXTERNAL_URL` | yes | External URL embedded in the OpenAPI spec |
 | `HF_TOKEN`, `HF_CACHE_DIR` | yes (when running bundled vLLM) | HuggingFace creds + shared cache for the vLLM container |
@@ -74,7 +74,7 @@ Env vars (prefix `VIDEO_ANALYSIS_`), loaded from `deploy/.env`:
 | `VIDEO_ANALYSIS_REPETITION_PENALTY` | no (default 1.05) | Repetition penalty |
 | `NGINX_CONNECT_TIMEOUT` / `_SEND_TIMEOUT` / `_READ_TIMEOUT` | no | nginx upstream timeouts (only `api-nginx` profile) |
 
-Tuning defaults live in `deploy/config.yaml`; env vars override YAML.
+Tuning defaults are baked into `settings.py` and overridden via the `VIDEO_ANALYSIS_*` env vars above (a `deploy/config.yaml` may optionally be supplied to override defaults, but none ships with the module).
 
 ## Deployment
 
@@ -93,8 +93,8 @@ Tuning defaults live in `deploy/config.yaml`; env vars override YAML.
 ## Related
 
 - **agent-v3 video pipeline** — `/home/admin365/didi_mono/backend/services/orchestration-layer/agent-v3` is the consumer; orchestrates async video sessions and merges this service's verdict into `ai_tampered` + `techniques` results
-- **BusterX vLLM** (port `54500`) — sibling service in the AI platform; the actual GPU-backed model that this service queries (referenced in main `CLAUDE.md` ports section)
-- **Qwen3-VL vision vLLM** (port `14002`) — alternative semantic backend (`didiAI-llm-vllm-vision`)
+- **BusterX vLLM** (port `54500`) — sibling service in the AI platform; the actual GPU-backed model that this service queries for both deepfake and semantic chunks (referenced in main `CLAUDE.md` ports section)
+- **DIDI text LLM API** (`http://didiAI-llm-api:14011`) — Qwen3.5 endpoint used to aggregate semantic chunk descriptions into the final narrative
 - **AI platform shared assets** — `../../README.md`, `../../ruff.toml`
 - **Internal package layout:** `src/video_analysis/{app.py, buster_client.py, schemas.py, settings.py, video_sampling.py}`
 - **Sibling docs:** `README.md`, `API.md`, `TESTING.md` in this folder