Files
ragflow/rag/llm/__init__.py
wdeveloper16 14c0985182 feat: bump Python minimum from 3.12 to 3.13, drop strenum backport (#14767)
Closes #14753

## What changed

| File | Change |
|---|---|
| `pyproject.toml` | `requires-python` → `>=3.13,<3.15`; remove
`strenum==0.4.15` |
| `Dockerfile` | `uv python install 3.13`, `uv sync --python 3.13` |
| `.github/workflows/tests.yml` | `uv sync --python 3.13` on both matrix
legs |
| `CLAUDE.md` | dev setup command + requirements note updated |
| `deepdoc/parser/mineru_parser.py` | `from strenum import StrEnum` →
`from enum import StrEnum` |
| `agent/tools/code_exec.py` | same |

`StrEnum` has been in the stdlib since Python 3.11 — the `strenum`
backport package is no longer needed once the floor is 3.13.

## Why uv.lock is not regenerated

`uv lock --python 3.13` fails because:

1. The infiniflow/graspologic fork pins `numpy>=1.26.4,<2.0.0`
2. `tensorflow-cpu>=2.20.0` (the first release with cp313 wheels)
depends on `ml-dtypes>=0.5.1`, which requires `numpy>=2.1.0`
3. These two constraints are irreconcilable on Python 3.13

The lockfile regeneration requires loosening the `numpy` upper bound in
the `infiniflow/graspologic` fork. Once that fork commit is updated and
the SHA in `pyproject.toml:49` is bumped, `uv lock --python 3.13` will
succeed.

## RFC corrections

Two claims in the original RFC (#14753) did not hold up under code
review:

- **"graspologic hard-blocks 3.13"** — the infiniflow fork at the pinned
commit has no `<3.13` Python constraint. The blocker is the transitive
`numpy<2.0.0` conflict with tensorflow-cpu's test dependency, not a
direct Python version cap.
- **"free-threading throughput gains for I/O-bound workload"** — Python
3.13 free-threading requires a special `--disable-gil` build and
provides no benefit for async I/O code (the GIL is already released
during I/O). The real motivation is forward compatibility and improved
error messages.
2026-05-15 14:40:53 +08:00

201 lines
7.8 KiB
Python

#
# Copyright 2024 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.
#
# AFTER UPDATING THIS FILE, PLEASE ENSURE THAT docs/references/supported_models.mdx IS ALSO UPDATED for consistency!
#
import importlib
import inspect
from enum import StrEnum
class SupportedLiteLLMProvider(StrEnum):
Tongyi_Qianwen = "Tongyi-Qianwen"
Dashscope = "Dashscope"
Bedrock = "Bedrock"
Moonshot = "Moonshot"
xAI = "xAI"
DeepInfra = "DeepInfra"
Groq = "Groq"
Cohere = "Cohere"
Gemini = "Gemini"
DeepSeek = "DeepSeek"
Nvidia = "NVIDIA"
TogetherAI = "TogetherAI"
Anthropic = "Anthropic"
Ollama = "Ollama"
LongCat = "LongCat"
CometAPI = "CometAPI"
SILICONFLOW = "SILICONFLOW"
OpenRouter = "OpenRouter"
StepFun = "StepFun"
PPIO = "PPIO"
PerfXCloud = "PerfXCloud"
Upstage = "Upstage"
NovitaAI = "NovitaAI"
Lingyi_AI = "01.AI"
GiteeAI = "GiteeAI"
AI_302 = "302.AI"
JiekouAI = "Jiekou.AI"
ZHIPU_AI = "ZHIPU-AI"
MiniMax = "MiniMax"
DeerAPI = "DeerAPI"
GPUStack = "GPUStack"
OpenAI = "OpenAI"
Azure_OpenAI = "Azure-OpenAI"
n1n = "n1n"
HunYuan = "Tencent Hunyuan"
Avian = "Avian"
Astraflow = "Astraflow"
Astraflow_CN = "Astraflow-CN"
FuturMix = "FuturMix"
FACTORY_DEFAULT_BASE_URL = {
SupportedLiteLLMProvider.Tongyi_Qianwen: "https://dashscope.aliyuncs.com/compatible-mode/v1",
SupportedLiteLLMProvider.Dashscope: "https://dashscope.aliyuncs.com/compatible-mode/v1",
SupportedLiteLLMProvider.Moonshot: "https://api.moonshot.cn/v1",
SupportedLiteLLMProvider.Ollama: "",
SupportedLiteLLMProvider.LongCat: "https://api.longcat.chat/openai",
SupportedLiteLLMProvider.CometAPI: "https://api.cometapi.com/v1",
SupportedLiteLLMProvider.SILICONFLOW: "https://api.siliconflow.cn/v1",
SupportedLiteLLMProvider.OpenRouter: "https://openrouter.ai/api/v1",
SupportedLiteLLMProvider.StepFun: "https://api.stepfun.com/v1",
SupportedLiteLLMProvider.PPIO: "https://api.ppinfra.com/v3/openai",
SupportedLiteLLMProvider.PerfXCloud: "https://cloud.perfxlab.cn/v1",
SupportedLiteLLMProvider.Upstage: "https://api.upstage.ai/v1/solar",
SupportedLiteLLMProvider.NovitaAI: "https://api.novita.ai/v3/openai",
SupportedLiteLLMProvider.Lingyi_AI: "https://api.lingyiwanwu.com/v1",
SupportedLiteLLMProvider.GiteeAI: "https://ai.gitee.com/v1/",
SupportedLiteLLMProvider.AI_302: "https://api.302.ai/v1",
SupportedLiteLLMProvider.Anthropic: "https://api.anthropic.com/",
SupportedLiteLLMProvider.JiekouAI: "https://api.jiekou.ai/openai",
SupportedLiteLLMProvider.ZHIPU_AI: "https://open.bigmodel.cn/api/paas/v4",
SupportedLiteLLMProvider.MiniMax: "https://api.minimaxi.com/v1",
SupportedLiteLLMProvider.DeerAPI: "https://api.deerapi.com/v1",
SupportedLiteLLMProvider.OpenAI: "https://api.openai.com/v1",
SupportedLiteLLMProvider.n1n: "https://api.n1n.ai/v1",
SupportedLiteLLMProvider.HunYuan: "https://api.hunyuan.cloud.tencent.com/v1",
SupportedLiteLLMProvider.Avian: "https://api.avian.io/v1",
SupportedLiteLLMProvider.Astraflow: "https://api-us-ca.umodelverse.ai/v1",
SupportedLiteLLMProvider.Astraflow_CN: "https://api.modelverse.cn/v1",
SupportedLiteLLMProvider.FuturMix: "https://futurmix.ai/v1",
}
LITELLM_PROVIDER_PREFIX = {
SupportedLiteLLMProvider.Tongyi_Qianwen: "dashscope/",
SupportedLiteLLMProvider.Dashscope: "dashscope/",
SupportedLiteLLMProvider.Bedrock: "bedrock/",
SupportedLiteLLMProvider.Moonshot: "moonshot/",
SupportedLiteLLMProvider.xAI: "xai/",
SupportedLiteLLMProvider.DeepInfra: "deepinfra/",
SupportedLiteLLMProvider.Groq: "groq/",
SupportedLiteLLMProvider.Cohere: "", # don't need a prefix
SupportedLiteLLMProvider.Gemini: "gemini/",
SupportedLiteLLMProvider.DeepSeek: "deepseek/",
SupportedLiteLLMProvider.Nvidia: "nvidia_nim/",
SupportedLiteLLMProvider.TogetherAI: "together_ai/",
SupportedLiteLLMProvider.Anthropic: "", # don't need a prefix
SupportedLiteLLMProvider.Ollama: "ollama_chat/",
SupportedLiteLLMProvider.LongCat: "openai/",
SupportedLiteLLMProvider.CometAPI: "openai/",
SupportedLiteLLMProvider.SILICONFLOW: "openai/",
SupportedLiteLLMProvider.OpenRouter: "openai/",
SupportedLiteLLMProvider.StepFun: "openai/",
SupportedLiteLLMProvider.PPIO: "openai/",
SupportedLiteLLMProvider.PerfXCloud: "openai/",
SupportedLiteLLMProvider.Upstage: "openai/",
SupportedLiteLLMProvider.NovitaAI: "openai/",
SupportedLiteLLMProvider.Lingyi_AI: "openai/",
SupportedLiteLLMProvider.GiteeAI: "openai/",
SupportedLiteLLMProvider.AI_302: "openai/",
SupportedLiteLLMProvider.JiekouAI: "openai/",
SupportedLiteLLMProvider.ZHIPU_AI: "openai/",
SupportedLiteLLMProvider.MiniMax: "openai/",
SupportedLiteLLMProvider.DeerAPI: "openai/",
SupportedLiteLLMProvider.GPUStack: "openai/",
SupportedLiteLLMProvider.OpenAI: "openai/",
SupportedLiteLLMProvider.Azure_OpenAI: "azure/",
SupportedLiteLLMProvider.n1n: "openai/",
SupportedLiteLLMProvider.HunYuan: "openai/",
SupportedLiteLLMProvider.Avian: "openai/",
SupportedLiteLLMProvider.Astraflow: "openai/",
SupportedLiteLLMProvider.Astraflow_CN: "openai/",
SupportedLiteLLMProvider.FuturMix: "openai/",
}
ChatModel = globals().get("ChatModel", {})
CvModel = globals().get("CvModel", {})
EmbeddingModel = globals().get("EmbeddingModel", {})
RerankModel = globals().get("RerankModel", {})
Seq2txtModel = globals().get("Seq2txtModel", {})
TTSModel = globals().get("TTSModel", {})
OcrModel = globals().get("OcrModel", {})
MODULE_MAPPING = {
"chat_model": ChatModel,
"cv_model": CvModel,
"embedding_model": EmbeddingModel,
"rerank_model": RerankModel,
"sequence2txt_model": Seq2txtModel,
"tts_model": TTSModel,
"ocr_model": OcrModel,
}
package_name = __name__
for module_name, mapping_dict in MODULE_MAPPING.items():
full_module_name = f"{package_name}.{module_name}"
module = importlib.import_module(full_module_name)
base_class = None
lite_llm_base_class = None
for name, obj in inspect.getmembers(module):
if inspect.isclass(obj):
if name == "Base":
base_class = obj
elif name == "LiteLLMBase":
lite_llm_base_class = obj
assert hasattr(obj, "_FACTORY_NAME"), "LiteLLMbase should have _FACTORY_NAME field."
if hasattr(obj, "_FACTORY_NAME"):
if isinstance(obj._FACTORY_NAME, list):
for factory_name in obj._FACTORY_NAME:
mapping_dict[factory_name] = obj
else:
mapping_dict[obj._FACTORY_NAME] = obj
if base_class is not None:
for _, obj in inspect.getmembers(module):
if inspect.isclass(obj) and issubclass(obj, base_class) and obj is not base_class and hasattr(obj, "_FACTORY_NAME"):
if isinstance(obj._FACTORY_NAME, list):
for factory_name in obj._FACTORY_NAME:
mapping_dict[factory_name] = obj
else:
mapping_dict[obj._FACTORY_NAME] = obj
__all__ = [
"ChatModel",
"CvModel",
"EmbeddingModel",
"RerankModel",
"Seq2txtModel",
"TTSModel",
"OcrModel",
]