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## Add Astraflow Provider Support This PR integrates [Astraflow](https://astraflow.ucloud.cn/) (by UCloud / 优刻得) as a new AI model provider in RAGFlow, with support for both global and China endpoints. ### About Astraflow Astraflow is an OpenAI-compatible AI model aggregation platform supporting 200+ models from major providers including DeepSeek, Qwen, GPT, Claude, Gemini, Llama, Mistral, and more. | Variant | Factory Name | Endpoint | Env Var | |---------|-------------|----------|---------| | Global | `Astraflow` | `https://api-us-ca.umodelverse.ai/v1` | `ASTRAFLOW_API_KEY` | | China | `Astraflow-CN` | `https://api.modelverse.cn/v1` | `ASTRAFLOW_CN_API_KEY` | - **API key signup**: https://astraflow.ucloud.cn/ --- ### Files Changed | File | Change | |------|--------| | `rag/llm/__init__.py` | Register `Astraflow` and `Astraflow-CN` in `SupportedLiteLLMProvider` enum, `FACTORY_DEFAULT_BASE_URL`, and `LITELLM_PROVIDER_PREFIX` | | `rag/llm/chat_model.py` | Add `AstraflowChat` and `AstraflowCNChat` (OpenAI-compatible `Base` subclass) | | `rag/llm/embedding_model.py` | Add `AstraflowEmbed` and `AstraflowCNEmbed` (subclasses of `OpenAIEmbed`) | | `rag/llm/rerank_model.py` | Add `AstraflowRerank` and `AstraflowCNRerank` (subclasses of `OpenAI_APIRerank`) | | `rag/llm/cv_model.py` | Add `AstraflowCV` and `AstraflowCNCV` (subclasses of `GptV4`) | | `rag/llm/tts_model.py` | Add `AstraflowTTS` and `AstraflowCNTTS` (subclasses of `OpenAITTS`) | | `rag/llm/sequence2txt_model.py` | Add `AstraflowSeq2txt` and `AstraflowCNSeq2txt` (subclasses of `GPTSeq2txt`) | | `conf/llm_factories.json` | Register `Astraflow` and `Astraflow-CN` factories with a curated list of popular models | --- ### Supported Model Types - ✅ **Chat / LLM** — DeepSeek-V3/R1, Qwen3, GPT-4o/4.1, Claude 3.5/3.7, Gemini 2.0/2.5 Flash, Llama 3.3/4, Mistral, and 200+ more - ✅ **Text Embedding** — text-embedding-3-small/large - ✅ **Image / Vision (IMAGE2TEXT)** — GPT-4o, GPT-4.1, Claude, Gemini, Llama-4, etc. - ✅ **Text Re-Rank** - ✅ **TTS** — tts-1 - ✅ **Speech-to-Text (SPEECH2TEXT)** — whisper-1 ### Implementation Notes - Uses the `openai/` LiteLLM prefix — consistent with other OpenAI-compatible aggregation platforms (SILICONFLOW, DeerAPI, CometAPI, OpenRouter, n1n, Avian, etc.) - `Astraflow` (global, rank 250) and `Astraflow-CN` (China, rank 249) are separate factory entries, allowing users to choose the optimal endpoint based on their region. - All model classes cleanly subclass existing base classes (`Base`, `OpenAIEmbed`, `OpenAI_APIRerank`, `GptV4`, `OpenAITTS`, `GPTSeq2txt`) with no custom logic needed — the provider is fully OpenAI-compatible. --------- Co-authored-by: user <user@xzaaaMacBook-Air.local>
198 lines
7.6 KiB
Python
198 lines
7.6 KiB
Python
#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# AFTER UPDATING THIS FILE, PLEASE ENSURE THAT docs/references/supported_models.mdx IS ALSO UPDATED for consistency!
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#
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import importlib
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import inspect
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from strenum import StrEnum
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class SupportedLiteLLMProvider(StrEnum):
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Tongyi_Qianwen = "Tongyi-Qianwen"
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Dashscope = "Dashscope"
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Bedrock = "Bedrock"
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Moonshot = "Moonshot"
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xAI = "xAI"
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DeepInfra = "DeepInfra"
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Groq = "Groq"
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Cohere = "Cohere"
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Gemini = "Gemini"
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DeepSeek = "DeepSeek"
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Nvidia = "NVIDIA"
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TogetherAI = "TogetherAI"
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Anthropic = "Anthropic"
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Ollama = "Ollama"
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LongCat = "LongCat"
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CometAPI = "CometAPI"
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SILICONFLOW = "SILICONFLOW"
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OpenRouter = "OpenRouter"
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StepFun = "StepFun"
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PPIO = "PPIO"
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PerfXCloud = "PerfXCloud"
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Upstage = "Upstage"
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NovitaAI = "NovitaAI"
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Lingyi_AI = "01.AI"
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GiteeAI = "GiteeAI"
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AI_302 = "302.AI"
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JiekouAI = "Jiekou.AI"
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ZHIPU_AI = "ZHIPU-AI"
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MiniMax = "MiniMax"
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DeerAPI = "DeerAPI"
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GPUStack = "GPUStack"
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OpenAI = "OpenAI"
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Azure_OpenAI = "Azure-OpenAI"
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n1n = "n1n"
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HunYuan = "Tencent Hunyuan"
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Avian = "Avian"
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Astraflow = "Astraflow"
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Astraflow_CN = "Astraflow-CN"
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FACTORY_DEFAULT_BASE_URL = {
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SupportedLiteLLMProvider.Tongyi_Qianwen: "https://dashscope.aliyuncs.com/compatible-mode/v1",
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SupportedLiteLLMProvider.Dashscope: "https://dashscope.aliyuncs.com/compatible-mode/v1",
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SupportedLiteLLMProvider.Moonshot: "https://api.moonshot.cn/v1",
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SupportedLiteLLMProvider.Ollama: "",
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SupportedLiteLLMProvider.LongCat: "https://api.longcat.chat/openai",
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SupportedLiteLLMProvider.CometAPI: "https://api.cometapi.com/v1",
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SupportedLiteLLMProvider.SILICONFLOW: "https://api.siliconflow.cn/v1",
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SupportedLiteLLMProvider.OpenRouter: "https://openrouter.ai/api/v1",
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SupportedLiteLLMProvider.StepFun: "https://api.stepfun.com/v1",
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SupportedLiteLLMProvider.PPIO: "https://api.ppinfra.com/v3/openai",
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SupportedLiteLLMProvider.PerfXCloud: "https://cloud.perfxlab.cn/v1",
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SupportedLiteLLMProvider.Upstage: "https://api.upstage.ai/v1/solar",
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SupportedLiteLLMProvider.NovitaAI: "https://api.novita.ai/v3/openai",
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SupportedLiteLLMProvider.Lingyi_AI: "https://api.lingyiwanwu.com/v1",
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SupportedLiteLLMProvider.GiteeAI: "https://ai.gitee.com/v1/",
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SupportedLiteLLMProvider.AI_302: "https://api.302.ai/v1",
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SupportedLiteLLMProvider.Anthropic: "https://api.anthropic.com/",
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SupportedLiteLLMProvider.JiekouAI: "https://api.jiekou.ai/openai",
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SupportedLiteLLMProvider.ZHIPU_AI: "https://open.bigmodel.cn/api/paas/v4",
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SupportedLiteLLMProvider.MiniMax: "https://api.minimaxi.com/v1",
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SupportedLiteLLMProvider.DeerAPI: "https://api.deerapi.com/v1",
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SupportedLiteLLMProvider.OpenAI: "https://api.openai.com/v1",
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SupportedLiteLLMProvider.n1n: "https://api.n1n.ai/v1",
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SupportedLiteLLMProvider.HunYuan: "https://api.hunyuan.cloud.tencent.com/v1",
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SupportedLiteLLMProvider.Avian: "https://api.avian.io/v1",
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SupportedLiteLLMProvider.Astraflow: "https://api-us-ca.umodelverse.ai/v1",
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SupportedLiteLLMProvider.Astraflow_CN: "https://api.modelverse.cn/v1",
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}
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LITELLM_PROVIDER_PREFIX = {
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SupportedLiteLLMProvider.Tongyi_Qianwen: "dashscope/",
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SupportedLiteLLMProvider.Dashscope: "dashscope/",
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SupportedLiteLLMProvider.Bedrock: "bedrock/",
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SupportedLiteLLMProvider.Moonshot: "moonshot/",
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SupportedLiteLLMProvider.xAI: "xai/",
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SupportedLiteLLMProvider.DeepInfra: "deepinfra/",
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SupportedLiteLLMProvider.Groq: "groq/",
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SupportedLiteLLMProvider.Cohere: "", # don't need a prefix
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SupportedLiteLLMProvider.Gemini: "gemini/",
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SupportedLiteLLMProvider.DeepSeek: "deepseek/",
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SupportedLiteLLMProvider.Nvidia: "nvidia_nim/",
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SupportedLiteLLMProvider.TogetherAI: "together_ai/",
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SupportedLiteLLMProvider.Anthropic: "", # don't need a prefix
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SupportedLiteLLMProvider.Ollama: "ollama_chat/",
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SupportedLiteLLMProvider.LongCat: "openai/",
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SupportedLiteLLMProvider.CometAPI: "openai/",
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SupportedLiteLLMProvider.SILICONFLOW: "openai/",
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SupportedLiteLLMProvider.OpenRouter: "openai/",
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SupportedLiteLLMProvider.StepFun: "openai/",
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SupportedLiteLLMProvider.PPIO: "openai/",
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SupportedLiteLLMProvider.PerfXCloud: "openai/",
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SupportedLiteLLMProvider.Upstage: "openai/",
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SupportedLiteLLMProvider.NovitaAI: "openai/",
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SupportedLiteLLMProvider.Lingyi_AI: "openai/",
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SupportedLiteLLMProvider.GiteeAI: "openai/",
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SupportedLiteLLMProvider.AI_302: "openai/",
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SupportedLiteLLMProvider.JiekouAI: "openai/",
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SupportedLiteLLMProvider.ZHIPU_AI: "openai/",
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SupportedLiteLLMProvider.MiniMax: "openai/",
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SupportedLiteLLMProvider.DeerAPI: "openai/",
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SupportedLiteLLMProvider.GPUStack: "openai/",
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SupportedLiteLLMProvider.OpenAI: "openai/",
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SupportedLiteLLMProvider.Azure_OpenAI: "azure/",
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SupportedLiteLLMProvider.n1n: "openai/",
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SupportedLiteLLMProvider.HunYuan: "openai/",
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SupportedLiteLLMProvider.Avian: "openai/",
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SupportedLiteLLMProvider.Astraflow: "openai/",
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SupportedLiteLLMProvider.Astraflow_CN: "openai/",
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}
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ChatModel = globals().get("ChatModel", {})
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CvModel = globals().get("CvModel", {})
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EmbeddingModel = globals().get("EmbeddingModel", {})
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RerankModel = globals().get("RerankModel", {})
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Seq2txtModel = globals().get("Seq2txtModel", {})
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TTSModel = globals().get("TTSModel", {})
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OcrModel = globals().get("OcrModel", {})
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MODULE_MAPPING = {
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"chat_model": ChatModel,
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"cv_model": CvModel,
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"embedding_model": EmbeddingModel,
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"rerank_model": RerankModel,
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"sequence2txt_model": Seq2txtModel,
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"tts_model": TTSModel,
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"ocr_model": OcrModel,
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}
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package_name = __name__
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for module_name, mapping_dict in MODULE_MAPPING.items():
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full_module_name = f"{package_name}.{module_name}"
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module = importlib.import_module(full_module_name)
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base_class = None
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lite_llm_base_class = None
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for name, obj in inspect.getmembers(module):
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if inspect.isclass(obj):
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if name == "Base":
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base_class = obj
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elif name == "LiteLLMBase":
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lite_llm_base_class = obj
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assert hasattr(obj, "_FACTORY_NAME"), "LiteLLMbase should have _FACTORY_NAME field."
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if hasattr(obj, "_FACTORY_NAME"):
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if isinstance(obj._FACTORY_NAME, list):
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for factory_name in obj._FACTORY_NAME:
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mapping_dict[factory_name] = obj
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else:
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mapping_dict[obj._FACTORY_NAME] = obj
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if base_class is not None:
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for _, obj in inspect.getmembers(module):
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if inspect.isclass(obj) and issubclass(obj, base_class) and obj is not base_class and hasattr(obj, "_FACTORY_NAME"):
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if isinstance(obj._FACTORY_NAME, list):
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for factory_name in obj._FACTORY_NAME:
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mapping_dict[factory_name] = obj
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else:
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mapping_dict[obj._FACTORY_NAME] = obj
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__all__ = [
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"ChatModel",
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"CvModel",
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"EmbeddingModel",
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"RerankModel",
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"Seq2txtModel",
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"TTSModel",
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"OcrModel",
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]
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