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fix(backend): 修复 DeepSeek 模型列表为空 & whisper 下载不走代理 (#417)
问题1 — DeepSeek 模型下拉为空:
provider 的 /models 调用失败时,get_model_list 吞掉异常返回 [],
get_all_models_by_id 再对 [] 取 .data 触发 AttributeError 又被吞,
最终接口返回 {"code":0,"msg":"success","data":[]},把失败伪装成空成功,
用户看不到任何原因。
- 捕获并回传真实错误,不再二次吞
- 新增 model_fallback.normalize_models 兼容 SyncPage/list/dict,绝不再 .data 崩
- 内置供应商提供已知模型兜底清单(DeepSeek→deepseek-chat/deepseek-reasoner,
Qwen→qwen-plus 等),动态拿不到时回退,保证下拉非空;动态可用时仍以动态为准
问题2 — whisper 模型下载不走代理(Docker 里代理没生效):
snapshot_download 既不读 UI 配的代理,HF_ENDPOINT 又固定 hf-mirror.com。
- ProxyConfigManager.apply_to_env() 把生效代理 export 到 HTTP(S)_PROXY/ALL_PROXY,
huggingface_hub 即可复用;在每次下载前与启动时应用(覆盖转写按需下载)
- 网络类下载报错翻译成可操作提示(配代理 / 改 HF_ENDPOINT / 检查容器外网)
- .env.example 补充 HF_ENDPOINT 与代理覆盖说明
新增 tests/test_model_fallback.py、tests/test_proxy_apply_env.py(14 用例)
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
co-authored by
Claude Opus 4.8
parent
6a43043874
commit
bebf2e8c61
@@ -13,7 +13,8 @@
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"type": "built-in",
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"logo": "DeepSeek",
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"api_key": "",
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"base_url": "https://api.deepseek.com"
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"base_url": "https://api.deepseek.com",
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"models": ["deepseek-chat", "deepseek-reasoner"]
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},
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{
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"id": "qwen",
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@@ -21,7 +22,8 @@
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"type": "built-in",
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"logo": "Qwen",
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"api_key": "",
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"base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1"
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"base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
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"models": ["qwen-plus", "qwen-turbo", "qwen-max", "qwen-long"]
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},
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{
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"id": "Claude",
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@@ -240,6 +240,38 @@ class ModelDownloadRequest(BaseModel):
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transcriber_type: str = "fast-whisper" # "fast-whisper" 或 "mlx-whisper"
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def _friendly_download_error(e: Exception) -> str:
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"""把 HuggingFace 的网络类报错翻译成用户能照着做的提示(issue #417)。
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典型原文:'An error happened while trying to locate the file on the Hub and we
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cannot find the requested files in the local cache...' —— 本质是连不上 Hub。
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用户大概率不知道:默认走 hf-mirror.com 镜像,可配代理或改 HF_ENDPOINT。
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"""
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raw = str(e)
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lowered = raw.lower()
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network_markers = (
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"locate the file on the hub",
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"couldn't connect",
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"connection error",
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"connecttimeout",
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"read timed out",
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"max retries exceeded",
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"failed to establish",
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"name or service not known",
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"temporary failure in name resolution",
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)
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if any(m in lowered for m in network_markers):
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endpoint = os.getenv("HF_ENDPOINT", "https://huggingface.co")
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return (
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f"{raw}\n"
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f"——连不上模型仓库(当前 HF_ENDPOINT={endpoint})。可尝试:"
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f"1) 在「设置」里配置可用代理;"
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f"2) 设置环境变量 HF_ENDPOINT 切换镜像(国内可用 https://hf-mirror.com);"
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f"3) 确认容器能访问外网/镜像站后重试。"
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)
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return raw
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def _do_download_whisper(model_size: str):
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"""后台下载 faster-whisper 模型(支持内置 size / 自定义 repo_id / 本地路径)。
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@@ -250,9 +282,14 @@ def _do_download_whisper(model_size: str):
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"""
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from huggingface_hub import snapshot_download
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from app.transcriber.whisper_models import resolve_whisper_model, is_local_target
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from app.services.proxy_config_manager import ProxyConfigManager
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try:
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dl_state.mark_downloading(model_size)
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# 让 UI 配的代理对 HuggingFace 下载也生效(issue #417:容器里代理没生效)
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proxy = ProxyConfigManager().apply_to_env()
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if proxy:
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logger.info(f"whisper 下载走代理: {proxy}")
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model_dir = get_model_dir("whisper")
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# 已经下好就不重复下
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@@ -289,8 +326,9 @@ def _do_download_whisper(model_size: str):
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logger.info(f"whisper 模型下载完成: {model_size}")
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dl_state.mark_done(model_size)
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except Exception as e:
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msg = _friendly_download_error(e)
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logger.error(f"whisper 模型下载失败: {model_size}, {e}")
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dl_state.mark_failed(model_size, str(e))
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dl_state.mark_failed(model_size, msg)
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def _do_download_mlx_whisper(model_size: str):
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@@ -300,6 +338,12 @@ def _do_download_mlx_whisper(model_size: str):
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dl_state.mark_downloading(key)
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from huggingface_hub import snapshot_download as hf_download
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from app.transcriber.mlx_whisper_transcriber import resolve_mlx_repo_id
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from app.services.proxy_config_manager import ProxyConfigManager
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# 让 UI 配的代理对 HuggingFace 下载也生效(issue #417)
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proxy = ProxyConfigManager().apply_to_env()
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if proxy:
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logger.info(f"mlx-whisper 下载走代理: {proxy}")
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try:
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repo_id = resolve_mlx_repo_id(model_size)
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@@ -319,8 +363,9 @@ def _do_download_mlx_whisper(model_size: str):
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logger.info(f"mlx-whisper 模型下载完成: {model_size}")
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dl_state.mark_done(key)
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except Exception as e:
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msg = _friendly_download_error(e)
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logger.error(f"mlx-whisper 模型下载失败: {model_size}, {e}")
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dl_state.mark_failed(key, str(e))
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dl_state.mark_failed(key, msg)
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@router.post("/transcriber_download")
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@@ -83,22 +83,56 @@ class ModelService:
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return enabled_models
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@staticmethod
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def get_all_models_by_id(provider_id: str, verbose: bool = False):
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"""拉取某供应商的可选模型列表,用于设置页下拉。
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历史坑(issue #417):旧实现对 get_model_list 的返回值直接取 `.data`,但
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get_model_list 在 /models 调用失败时会吞掉异常返回 `[]`,于是 `[].data`
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触发 AttributeError,又被这里的 except 吞成 `[]` —— 最终接口返回
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`{"code":0,"msg":"success","data":[]}`,把「DeepSeek /models 取不到」伪装成
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成功的空列表,用户完全看不到原因。
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现在:
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1. 直接捕获 /models 的真实异常(不再二次吞);
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2. normalize_models 兼容 SyncPage / list / dict,绝不再 `.data` 崩;
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3. 动态拿不到(失败或空)时退回内置已知清单,保证下拉非空;
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4. 仍然为空且确有报错时,把报错带回去(前端可提示,不再假装成功)。
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"""
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from app.services.model_fallback import (
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builtin_fallback_models,
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normalize_models,
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as_model_dicts,
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)
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provider = ProviderService.get_provider_by_id(provider_id)
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if not provider:
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logger.warning(f"[{provider_id}] 供应商不存在")
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return {"models": []}
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models: list = []
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error: str | None = None
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try:
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provider = ProviderService.get_provider_by_id(provider_id)
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models = ModelService.get_model_list(provider["id"], verbose=verbose)
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print(type(models))
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serializable_models = [m.dict() for m in models.data]
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model_list = {
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"models": serializable_models
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}
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logger.info(f"[{provider['name']}] 获取模型成功")
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return model_list
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config = ModelService._build_model_config(provider)
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gpt = GPTFactory().from_config(config)
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models = normalize_models(gpt.list_models())
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if verbose:
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print(f"[{provider['name']}] 动态模型列表: {models}")
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except Exception as e:
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# print(f"[{provider_id}] 获取模型失败: {e}")
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logger.error(f"[{provider_id}] 获取模型失败: {e}")
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return []
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error = str(e)
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logger.warning(f"[{provider['name']}] 动态获取模型失败,尝试回退内置清单: {e}")
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if not models:
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fallback = builtin_fallback_models(provider)
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if fallback:
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logger.info(f"[{provider['name']}] /models 为空,回退内置清单: {fallback}")
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models = as_model_dicts(fallback, owned_by=provider.get("name", ""))
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result = {"models": models}
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if not models and error:
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# 既没动态结果也没兜底清单:把真实报错带回去,别再伪装成功
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result["error"] = error
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else:
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logger.info(f"[{provider['name']}] 获取模型成功,共 {len(models)} 个")
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return result
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@staticmethod
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def connect_test(id: str, model: str | None = None) -> bool:
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"""连通性测试:发一条最小化 chat completion。
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@@ -0,0 +1,86 @@
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"""内置供应商的回退模型清单 + 模型对象归一化(issue #417)。
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背景:设置页的「模型下拉」依赖 provider 的 `/v1/models` 动态列表。但这个接口
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并不可靠——
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- DeepSeek 的 `/models` 在部分账号/网络下取不到,下拉直接空白;
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- 不少自建 OpenAI 兼容网关压根不实现 `/models`;
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- key 没有 inference 权限时也可能返回异常。
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(`OpenAI_compatible_provider.test_connection` 的注释里已经记录过这个不可靠性。)
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所以对**内置供应商**额外维护一份已知可用清单兜底:动态拿不到时退回这份清单,
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保证下拉永远有内容,用户不至于卡在空列表。清单数据写在
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`app/db/builtin_providers.json` 的 `models` 字段里,单一数据源,方便维护。
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本模块只依赖标准库,便于单测隔离加载(不触发 app 包的重依赖导入链)。
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"""
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import json
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from pathlib import Path
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from typing import Any, List, Optional
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# builtin_providers.json 与本文件同属 backend/app 下:app/services/ -> app/db/
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_BUILTIN_JSON = Path(__file__).resolve().parent.parent / "db" / "builtin_providers.json"
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def _load_builtin() -> List[dict]:
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try:
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return json.loads(_BUILTIN_JSON.read_text(encoding="utf-8"))
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except Exception:
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return []
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def builtin_fallback_models(provider: Optional[dict]) -> List[str]:
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"""按 provider 的 id 或 name(忽略大小写)匹配内置清单里的 models 字段。
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自定义供应商(DB 里 id 是 uuid)通常 name 也对得上内置名,所以 id / name 都试。
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匹配不到或没配 models 返回空列表。
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"""
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if not provider:
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return []
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keys = {str(provider.get("id", "")).strip().lower(), str(provider.get("name", "")).strip().lower()}
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keys.discard("")
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if not keys:
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return []
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for p in _load_builtin():
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candidate = {str(p.get("id", "")).strip().lower(), str(p.get("name", "")).strip().lower()}
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if keys & candidate:
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models = p.get("models") or []
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return [str(m) for m in models if m]
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return []
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def normalize_models(raw: Any) -> List[dict]:
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"""把 SDK 返回值统一成 [{'id', 'object', 'owned_by', ...}] 列表。
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兼容三种形态:
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- openai SDK 的 SyncPage(取 .data)
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- 普通 list(含旧代码失败时返回的 [],绝不能再 .data)
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- list 里既可能是 pydantic Model 也可能是 dict
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"""
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if raw is None:
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return []
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data = getattr(raw, "data", raw) # SyncPage -> .data;list/tuple 原样
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if not isinstance(data, (list, tuple)):
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return []
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out: List[dict] = []
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for m in data:
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if isinstance(m, dict):
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d = m
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elif hasattr(m, "model_dump"):
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d = m.model_dump()
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elif hasattr(m, "dict"):
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d = m.dict()
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else:
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d = {"id": getattr(m, "id", None)}
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if d.get("id"):
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out.append(d)
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return out
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def as_model_dicts(model_ids: List[str], owned_by: str = "") -> List[dict]:
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"""把模型名列表包成与 SDK Model 一致的 dict,前端下拉直接复用同一套渲染。"""
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return [
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{"id": mid, "object": "model", "created": None, "owned_by": owned_by}
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for mid in model_ids
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]
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@@ -58,3 +58,22 @@ class ProxyConfigManager:
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if val:
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return val
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return None
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def apply_to_env(self) -> Optional[str]:
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"""把当前生效的代理 URL 写进进程环境变量,返回生效的 url(无则 None)。
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为什么需要(issue #417):huggingface_hub / requests 这类库**只认**环境变量
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HTTP_PROXY / HTTPS_PROXY / ALL_PROXY,不读我们 UI 配置文件。whisper 模型用
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snapshot_download 从 HuggingFace 拉取,如果用户只在设置页填了代理,下载根本
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不走代理 —— 就是用户说的「Docker 容器里代理没生效」。在下载前/启动时调用本
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方法,把 UI 配的代理 export 到环境变量,HF 下载就能复用同一个代理。
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大小写别名都写,覆盖不同库的读取习惯。
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"""
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url = self.get_proxy_url()
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if not url:
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return None
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for key in ("HTTP_PROXY", "HTTPS_PROXY", "ALL_PROXY",
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"http_proxy", "https_proxy", "all_proxy"):
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os.environ[key] = url
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return url
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