Files
ragflow/rag/llm/ocr_model.py
Xavierando 08332501a8 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)
2026-07-24 21:07:48 +08:00

398 lines
17 KiB
Python

#
# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import json
import logging
import os
from typing import Any, Optional
from deepdoc.parser.mineru_parser import MinerUParser
from deepdoc.parser.mistral_parser import MistralParser
from deepdoc.parser.opendataloader_parser import OpenDataLoaderParser
from deepdoc.parser.paddleocr_parser import PaddleOCRParser
from deepdoc.parser.pdf_parser import MAXIMUM_PAGE_NUMBER
from deepdoc.parser.somark_parser import SoMarkParser
class Base:
def __init__(self, key: str | dict, model_name: str, **kwargs):
self.model_name = model_name
def parse_pdf(self, filepath: str, binary=None, **kwargs) -> tuple[Any, Any]:
raise NotImplementedError("Please implement parse_pdf!")
class MinerUOcrModel(Base, MinerUParser):
_FACTORY_NAME = "MinerU"
def __init__(self, key: str | dict, model_name: str, **kwargs):
Base.__init__(self, key, model_name, **kwargs)
raw_config = {}
if key:
try:
raw_config = json.loads(key)
except Exception:
raw_config = {}
# nested {"api_key": {...}} from UI
# flat {"MINERU_*": "..."} payload auto-provisioned from env vars
config = raw_config.get("api_key", raw_config)
if not isinstance(config, dict):
config = {}
def _resolve_config(key: str, env_key: str, default=""):
# lower-case keys (UI), upper-case MINERU_* (env auto-provision), env vars
return config.get(key, config.get(env_key, os.environ.get(env_key, default)))
self.mineru_api = _resolve_config("mineru_apiserver", "MINERU_APISERVER", "")
self.mineru_output_dir = _resolve_config("mineru_output_dir", "MINERU_OUTPUT_DIR", "")
self.mineru_backend = _resolve_config("mineru_backend", "MINERU_BACKEND", "pipeline")
self.mineru_server_url = _resolve_config("mineru_server_url", "MINERU_SERVER_URL", "")
self.mineru_delete_output = bool(int(_resolve_config("mineru_delete_output", "MINERU_DELETE_OUTPUT", 1)))
# Redact sensitive config keys before logging
redacted_config = {}
for k, v in config.items():
if any(sensitive_word in k.lower() for sensitive_word in ("key", "password", "token", "secret")):
redacted_config[k] = "[REDACTED]"
else:
redacted_config[k] = v
logging.info(f"Parsed MinerU config (sensitive fields redacted): {redacted_config}")
MinerUParser.__init__(self, mineru_api=self.mineru_api, mineru_server_url=self.mineru_server_url)
def check_available(self, backend: Optional[str] = None, server_url: Optional[str] = None) -> tuple[bool, str]:
backend = backend or self.mineru_backend
server_url = server_url or self.mineru_server_url
return self.check_installation(backend=backend, server_url=server_url)
def parse_pdf(self, filepath: str, binary=None, callback=None, parse_method: str = "raw", **kwargs):
ok, reason = self.check_available()
if not ok:
raise RuntimeError(f"MinerU server not accessible: {reason}")
sections, tables = MinerUParser.parse_pdf(
self,
filepath=filepath,
binary=binary,
callback=callback,
output_dir=self.mineru_output_dir,
backend=self.mineru_backend,
server_url=self.mineru_server_url,
delete_output=self.mineru_delete_output,
parse_method=parse_method,
**kwargs,
)
return sections, tables
class PaddleOCROcrModel(Base, PaddleOCRParser):
_FACTORY_NAME = "PaddleOCR"
def __init__(self, key: str | dict, model_name: str, **kwargs):
Base.__init__(self, key, model_name, **kwargs)
raw_config = {}
if key:
try:
raw_config = json.loads(key)
except Exception:
raw_config = {}
# nested {"api_key": {...}} from UI
# flat {"PADDLEOCR_*": "..."} payload auto-provisioned from env vars
config = raw_config.get("api_key", raw_config)
if not isinstance(config, dict):
config = {}
def _resolve_config(key: str, env_key: str, default=""):
# lower-case keys (UI), upper-case PADDLEOCR_* (env auto-provision), env vars
return config.get(key, config.get(env_key, os.environ.get(env_key, default)))
self.paddleocr_base_url = _resolve_config("paddleocr_base_url", "PADDLEOCR_BASE_URL", "") or _resolve_config("paddleocr_api_url", "PADDLEOCR_API_URL", "")
self.paddleocr_algorithm = _resolve_config("paddleocr_algorithm", "PADDLEOCR_ALGORITHM", "PaddleOCR-VL")
self.paddleocr_access_token = _resolve_config("paddleocr_access_token", "PADDLEOCR_ACCESS_TOKEN", None)
# Redact sensitive config keys before logging
redacted_config = {}
for k, v in config.items():
if any(sensitive_word in k.lower() for sensitive_word in ("key", "password", "token", "secret")):
redacted_config[k] = "[REDACTED]"
else:
redacted_config[k] = v
logging.info(f"Parsed PaddleOCR config (sensitive fields redacted): {redacted_config}")
PaddleOCRParser.__init__(
self,
base_url=self.paddleocr_base_url or None,
access_token=self.paddleocr_access_token,
algorithm=self.paddleocr_algorithm,
)
def check_available(self) -> tuple[bool, str]:
return self.check_installation()
def parse_pdf(self, filepath: str, binary=None, callback=None, parse_method: str = "raw", **kwargs):
ok, reason = self.check_available()
if not ok:
raise RuntimeError(f"PaddleOCR server not accessible: {reason}")
sections, tables = PaddleOCRParser.parse_pdf(self, filepath=filepath, binary=binary, callback=callback, parse_method=parse_method, **kwargs)
return sections, tables
def parse_image(self, filepath: str, binary=None, callback=None, **kwargs) -> str:
ok, reason = self.check_available()
if not ok:
raise RuntimeError(f"PaddleOCR server not accessible: {reason}")
logging.info(f"PaddleOCR parse_image start: {filepath}")
result = PaddleOCRParser.parse_image(self, filepath=filepath, binary=binary, callback=callback, **kwargs)
logging.info(f"PaddleOCR parse_image done: {filepath}, text length: {len(result)}")
return result
class OpenDataLoaderOcrModel(Base, OpenDataLoaderParser):
_FACTORY_NAME = "OpenDataLoader"
def __init__(self, key: str | dict, model_name: str, **kwargs):
Base.__init__(self, key, model_name, **kwargs)
raw_config = {}
if key:
try:
raw_config = json.loads(key)
except Exception:
raw_config = {}
config = raw_config.get("api_key", raw_config)
if not isinstance(config, dict):
config = {}
def _resolve_config(key: str, env_key: str, default=""):
return config.get(key, config.get(env_key, os.environ.get(env_key, default)))
redacted_config = {}
for k, v in config.items():
if any(s in k.lower() for s in ("key", "password", "token", "secret")):
redacted_config[k] = "[REDACTED]"
else:
redacted_config[k] = v
logging.info(f"Parsed OpenDataLoader config (sensitive fields redacted): {redacted_config}")
OpenDataLoaderParser.__init__(self)
self.api_url = _resolve_config("opendataloader_apiserver", "OPENDATALOADER_APISERVER", "").rstrip("/")
self.api_key = _resolve_config("opendataloader_api_key", "OPENDATALOADER_API_KEY", "").strip()
timeout_val = _resolve_config("opendataloader_timeout", "OPENDATALOADER_TIMEOUT", "600") or "600"
try:
self.timeout = int(timeout_val)
except (TypeError, ValueError):
self.timeout = 600
def check_available(self) -> tuple[bool, str]:
ok = self.check_installation()
return ok, "" if ok else "OpenDataLoader service not reachable"
def parse_pdf(self, filepath: str, binary=None, callback=None, parse_method: str = "raw", **kwargs):
ok, reason = self.check_available()
if not ok:
raise RuntimeError(f"OpenDataLoader service not accessible: {reason}")
sections, tables = OpenDataLoaderParser.parse_pdf(
self,
filepath=filepath,
binary=binary,
callback=callback,
parse_method=parse_method,
**kwargs,
)
return sections, tables
class SoMarkOcrModel(Base, SoMarkParser):
_FACTORY_NAME = "SoMark"
def __init__(self, key: str | dict, model_name: str, **kwargs):
Base.__init__(self, key, model_name, **kwargs)
raw_config: dict = {}
if isinstance(key, dict):
# API verify path passes the form dict directly; no JSON to parse.
raw_config = key
elif key:
try:
raw_config = json.loads(key)
except Exception:
raw_config = {}
# nested {"api_key": {...}} from UI
# flat {"SOMARK_*": "..."} payload auto-provisioned from env vars
config = raw_config.get("api_key", raw_config)
if not isinstance(config, dict):
config = {}
key_as_secret = key if isinstance(key, str) and key and not key.lstrip().startswith("{") else ""
def _resolve(ui_key: str, env_key: str, default=""):
return config.get(
ui_key,
config.get(
env_key,
kwargs.get(
ui_key,
kwargs.get(env_key, os.environ.get(env_key, default)),
),
),
)
def _resolve_bool(ui_key: str, env_key: str, default: bool) -> bool:
raw = _resolve(ui_key, env_key, int(default))
if isinstance(raw, bool):
return raw
if isinstance(raw, (int, float)):
return bool(raw)
return str(raw).strip().lower() in {"1", "true", "yes", "on"}
base_url = _resolve(
"somark_base_url",
"SOMARK_BASE_URL",
kwargs.get("base_url", "https://somark.cn/api/v1"),
)
api_key = _resolve("api_key", "SOMARK_API_KEY", key_as_secret)
image_format = _resolve("somark_image_format", "SOMARK_IMAGE_FORMAT", "url")
formula_format = _resolve("somark_formula_format", "SOMARK_FORMULA_FORMAT", "latex")
table_format = _resolve("somark_table_format", "SOMARK_TABLE_FORMAT", "html")
cs_format = _resolve("somark_cs_format", "SOMARK_CS_FORMAT", "image")
enable_text_cross_page = _resolve_bool("somark_enable_text_cross_page", "SOMARK_ENABLE_TEXT_CROSS_PAGE", False)
enable_table_cross_page = _resolve_bool("somark_enable_table_cross_page", "SOMARK_ENABLE_TABLE_CROSS_PAGE", False)
enable_title_level_recognition = _resolve_bool("somark_enable_title_level_recognition", "SOMARK_ENABLE_TITLE_LEVEL_RECOGNITION", False)
enable_inline_image = _resolve_bool("somark_enable_inline_image", "SOMARK_ENABLE_INLINE_IMAGE", True)
enable_table_image = _resolve_bool("somark_enable_table_image", "SOMARK_ENABLE_TABLE_IMAGE", True)
enable_image_understanding = _resolve_bool("somark_enable_image_understanding", "SOMARK_ENABLE_IMAGE_UNDERSTANDING", True)
keep_header_footer = _resolve_bool("somark_keep_header_footer", "SOMARK_KEEP_HEADER_FOOTER", False)
# Redact sensitive config keys before logging
redacted_config = {}
for k, v in config.items():
if any(s in k.lower() for s in ("key", "password", "token", "secret")):
redacted_config[k] = "[REDACTED]"
else:
redacted_config[k] = v
logging.info(f"Parsed SoMark config (sensitive fields redacted): {redacted_config}")
self.base_url = base_url
self.api_key = api_key
SoMarkParser.__init__(
self,
base_url=base_url,
api_key=api_key,
image_format=image_format,
formula_format=formula_format,
table_format=table_format,
cs_format=cs_format,
enable_text_cross_page=enable_text_cross_page,
enable_table_cross_page=enable_table_cross_page,
enable_title_level_recognition=enable_title_level_recognition,
enable_inline_image=enable_inline_image,
enable_table_image=enable_table_image,
enable_image_understanding=enable_image_understanding,
keep_header_footer=keep_header_footer,
)
def check_available(self) -> tuple[bool, str]:
return self.check_installation()
def parse_pdf(self, filepath: str, binary=None, callback=None, parse_method: str = "raw", **kwargs):
ok, reason = self.check_available()
if not ok:
raise RuntimeError(f"SoMark service not accessible: {reason}")
# parse_method selects the output tuple shape (see SoMarkParser._transfer_to_sections):
# manual/pipeline -> typed 3-tuples for the rag/flow DAG; raw/other -> 2-tuples
# for naive.py chunking. Thread it through like MinerU rather than dropping it.
sections, tables = SoMarkParser.parse_pdf(
self,
filepath=filepath,
binary=binary,
callback=callback,
parse_method=parse_method,
**kwargs,
)
return sections, tables
class MistralOcrModel(Base, MistralParser):
_FACTORY_NAME = "Mistral OCR"
def __init__(self, key: str | dict, model_name: str, **kwargs):
Base.__init__(self, key, model_name, **kwargs)
raw_config: dict = {}
if isinstance(key, dict):
raw_config = key
elif key:
try:
raw_config = json.loads(key)
except Exception:
raw_config = {}
# Only unwrap a nested {"api_key": {...}} config object; a flat config
# whose "api_key" is a string must be preserved so the key is not lost.
nested_config = raw_config.get("api_key") if isinstance(raw_config, dict) else None
config = nested_config if isinstance(nested_config, dict) else raw_config
if not isinstance(config, dict):
config = {}
key_as_secret = key if isinstance(key, str) and key and not key.lstrip().startswith("{") else ""
def _resolve(ui_key: str, env_key: str, default=""):
return config.get(ui_key, config.get(env_key, kwargs.get(ui_key, kwargs.get(env_key, os.environ.get(env_key, default)))))
base_url = _resolve("mistral_ocr_base_url", "MISTRAL_OCR_BASE_URL", kwargs.get("base_url") or "https://api.mistral.ai/v1")
api_key = _resolve("api_key", "MISTRAL_OCR_API_KEY", key_as_secret)
table_format = _resolve("mistral_ocr_table_format", "MISTRAL_OCR_TABLE_FORMAT", "html")
keep_hf = _resolve("mistral_ocr_keep_header_footer", "MISTRAL_OCR_KEEP_HEADER_FOOTER", 0)
# Redact sensitive config keys before logging
redacted_config = {}
for k, v in config.items():
if any(s in k.lower() for s in ("key", "password", "token", "secret")):
redacted_config[k] = "[REDACTED]"
else:
redacted_config[k] = v
logging.info(f"Parsed Mistral OCR config (sensitive fields redacted): {redacted_config}")
MistralParser.__init__(
self,
base_url=base_url,
api_key=api_key,
model=model_name,
table_format=table_format,
keep_header_footer=str(keep_hf).strip().lower() in {"1", "true", "yes", "on"},
)
def check_available(self) -> tuple[bool, str]:
return self.check_installation()
def parse_pdf(self, filepath, binary=None, callback=None, parse_method: str = "raw", from_page: int = 0, to_page: int = MAXIMUM_PAGE_NUMBER, **kwargs):
ok, reason = self.check_available()
if not ok:
raise RuntimeError(f"Mistral OCR not accessible: {reason}")
return MistralParser.parse_pdf(
self,
filepath=filepath,
binary=binary,
callback=callback,
parse_method=parse_method,
from_page=from_page,
to_page=to_page,
**kwargs,
)