feat: add Mistral OCR (/v1/ocr) as a document parser; fix "Can't find model" mis-tag (#5782, #7075) (#17057)

### What problem does this PR solve?

Adds first-class support for **Mistral OCR** (`POST /v1/ocr`) as a
document parser, and fixes the long-standing bug where selecting
`mistral-ocr-latest` fails with `Can't find model for
<tenant>/image2text/mistral-ocr-latest`.

`mistral-ocr-latest` is Mistral's dedicated document-OCR endpoint, not a
vision-chat (`image2text`) model, but the catalog tagged it `image2text`
— so it resolved to the `CvModel` registry, which has no `Mistral`
entry, and there was no `OcrModel` entry either. This PR registers it
correctly and wires it end to end.

Closes #17056
Closes #5782
Closes #7075

**What it does**

1. **`MistralParser` + `MistralOcrModel`**
(`deepdoc/parser/mistral_parser.py`, `rag/llm/ocr_model.py`) — a proper
`OcrModel` factory `Mistral OCR`, mirroring the SoMark cloud-OCR
template. Tables stay inline as HTML; the page range maps to Mistral's
native `pages` selector (absolute page indices, billed per selected
page, so multi-task documents do not re-OCR the whole file); documents
over the inline limit go through the `/v1/files` signed-URL flow with
cleanup.
2. **Removes the `image2text` mis-tag** for `mistral-ocr-latest` from
the `Mistral` factory in `conf/llm_factories.json` (it now lives only in
the `Mistral OCR` factory, typed `ocr`). This is what closes the `Can't
find model` path.
3. **`MistralCV`** (`rag/llm/cv_model.py`) — a thin `GptV4` subclass
over Mistral's OpenAI-compatible endpoint, registering a `Mistral` entry
in the `CvModel` registry so Mistral vision models (`pixtral-*`) become
usable as `image2text` at all.
4. **Figure description** — Mistral-OCR-extracted figures are captioned
using the tenant's configured `image2text` model (any provider),
matching MinerU/deepdoc behaviour.
5. **Wires the parser into every chunking method** (`naive`, `paper`,
`book`, `laws`, `manual`, `one`, `presentation`) and the `rag/flow` DAG
path. This also fixes a related latent gap where those chunkers
forwarded only `mineru_llm_name`, so any model-based OCR provider
selected on a non-`naive` method silently fell through.

**Notes on the API contract** (verified against the live Mistral API):
`pages` is a selector (returns absolute `index`, bills only the
requested pages); `include_blocks: true` returns per-block bounding
boxes usable for chunk highlighting and figure cropping; large files use
`POST /v1/files` → signed URL → OCR → `DELETE`.

**Testing**: new unit tests cover the response→sections contract (both
the 2-tuple `naive` path and the typed 3-tuple DAG path), the
position-tag rescale, the HTTP client incl. upload failure/cleanup
paths, `parse_pdf` page-range threading, registry registration, env
config, the suffix normalization, the factory catalog entry, `MistralCV`
registration, and figure-description injection. Verified end to end
against the live Mistral API on real PDFs (table extraction,
page-selector cost avoidance, figure captioning).

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)

api/apps/services/provider_api_service.py

@@ -83,7 +83,7 @@ def list_providers(tenant_id: str, all_available: bool = False):
             if factory_info["name"] in ["Youdao", "FastEmbed", "BAAI", "Builtin", "siliconflow_intl"]:
                 continue
             model_types = sorted(set(model_type for llm in factory_info.get("llm", []) for model_type in _factory_model_types(llm))) if factory_info.get("llm", []) else []
-            if factory_info["name"] in ["MinerU", "PaddleOCR", "OpenDataLoader"]:
+            if factory_info["name"] in ["MinerU", "PaddleOCR", "OpenDataLoader", "Mistral OCR"]:
                 model_types.append("ocr")
             provider = {"model_types": model_types, "name": factory_info["name"], "url": {"default": factory_info.get("url", "")}}
             if factory_info["name"].lower() == "siliconflow":
@@ -105,7 +105,7 @@ def list_providers(tenant_id: str, all_available: bool = False):
             provider_obj = TenantModelProviderService.get_by_tenant_id_and_provider_name(tenant_id, name)
             has_instance = bool(provider_obj and TenantModelInstanceService.get_all_by_provider_id(provider_obj.id))
             model_types = sorted(set(model_type for llm in factory_info.get("llm", []) for model_type in _factory_model_types(llm))) if factory_info.get("llm", []) else []
-            if name in ["MinerU", "PaddleOCR", "OpenDataLoader"]:
+            if name in ["MinerU", "PaddleOCR", "OpenDataLoader", "Mistral OCR"]:
                 model_types.append("ocr")
 
             provider = {"has_instance": has_instance, "model_types": model_types, "name": factory_info["name"], "url": {"default": factory_info.get("url", "")}}