Merge branch 'main' into anydoc-support

Conflicts, and how each was taken:

- application/core/settings.py — ours. The renamed OCR_ENABLED /
  OCR_ATTACHMENTS_ENABLED / OCR_MIN_CHARS_PER_PAGE accept main's
  DOCLING_OCR_* spellings as AliasChoices, so nothing is dropped.
- application/Dockerfile — both. Main's install layers plus the
  INSTALL_DOCLING build arg.
- application/parser/file/constants.py — both imports.
- deployment/docker-compose.yaml — both. The INSTALL_DOCLING /
  INSTALL_TESSERACT build args on backend and worker, and main's
  -Q docsgpt,parsing,embeddings, which query embedding needs.
- tests/conftest.py — theirs. Both sides fixed the same pytest-postgresql
  9.0.0 autocommit= breakage; main's spelling is the one already on main.
- application/requirements.txt — the comments claimed different reasons
  torch is in core. Main's is the true one now: it removed
  sentence-transformers, so docling is torch's only remaining consumer.

Two things the merge broke without conflicting:

- onnxruntime. This branch moved it out of core into the docling extra;
  main meanwhile made it the runtime local embeddings execute on
  (fastembed). Git took the deletion, leaving fastembed with no pinned
  runtime in a repo that pins everything. Restored to core, and no longer
  pinned twice from the extra.
- The frontend copy of ATTACHMENT_PARSER_EXTENSIONS. The backend list is
  derived and picked up the anydoc suffixes; the hand-kept frontend mirror
  did not, so the composer would refuse files the API accepts.
  tests/parser/file/test_constants.py is what caught it.

ruff, pytest (9897 passed), frontend build and docs build all pass. The
image build is unverified: no Docker daemon on this machine.

docs/content/Deploying/Development-Environment.mdx

@@ -76,18 +76,16 @@ To run the DocsGPT backend locally, you'll need to set up a Python environment a
          venv/Scripts/activate
         ```
 
-3.  **Download Embedding Model:**
+3.  **Embedding Model (no action needed):**
 
-    The backend requires an embedding model. Download the `mpnet-base-v2` model and place it in the `models/` directory within the project root. You can use the following script:
+    The embedding model is downloaded automatically the first time you ingest a document, and cached for subsequent runs. Set `EMBEDDINGS_CACHE_DIR` to control where.
+
+    For an offline or air-gapped machine, fetch it ahead of time instead:
 
     ```bash
-    wget https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip
-    unzip mpnet-base-v2.zip -d model
-    rm mpnet-base-v2.zip
+    python -m application.scripts.prefetch_models
     ```
 
-    Alternatively, you can manually download the zip file from [here](https://d3dg1063dc54p9.cloudfront.net/models/embeddings/mpnet-base-v2.zip), unzip it, and place the extracted folder in `models/`.
-
 4.  **Install Backend Dependencies:**
 
     Navigate to the root of your DocsGPT repository and install the required Python packages: