[AZ-172] Update documentation for distributed architecture, add Update Docs step to workflow

- Update module docs: main, inference, ai_config, loader_http_client
- Add new module doc: media_hash
- Update component docs: inference_pipeline, api
- Update system-flows (F2, F3) and data_parameters
- Add Task Mode to document skill for incremental doc updates
- Insert Step 11 (Update Docs) in existing-code flow, renumber 11-13 to 12-14

Made-with: Cursor

_docs/02_document/modules/media_hash.md

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+# Module: media_hash
+
+## Purpose
+
+Content-based hashing for media files using XxHash64 with a deterministic sampling algorithm. Produces a stable, unique ID for any media file based on its content.
+
+## Public Interface
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `compute_media_content_hash` | `(data: bytes, virtual: bool = False) -> str` | Returns hex XxHash64 digest of sampled content. If `virtual=True`, prefixes with "V". |
+
+## Internal Logic
+
+### Sampling Algorithm (`_sampling_payload`)
+
+- **Small files** (< 3072 bytes): uses entire content
+- **Large files** (≥ 3072 bytes): samples 3 × 1024-byte windows: first 1024, middle 1024, last 1024
+- All payloads are prefixed with the 8-byte little-endian file size for collision resistance
+
+The sampling avoids reading the full file through the hash function while still providing high uniqueness — the head, middle, and tail capture format headers, content, and EOF markers.
+
+## Dependencies
+
+- **External**: `xxhash` (pinned at 3.5.0 in requirements.txt)
+- **Internal**: none (leaf module)
+
+## Consumers
+
+- `main` — computes content hash for uploaded media in `POST /detect` to use as the media record ID and storage filename
+
+## Data Models
+
+None.
+
+## Configuration
+
+None.
+
+## External Integrations
+
+None.
+
+## Security
+
+None. The hash is non-cryptographic (fast, not tamper-resistant).
+
+## Tests
+
+- `tests/test_media_hash.py` — covers small files, large files, and virtual prefix behavior