chore(core.provider): 🚨 修正实现错误Lint

2026-07-19 18:47:41 +08:00 · 2025-10-31 19:13:47 +08:00
parent 918960a7ef
commit 339f9042b7
17 changed files with 99 additions and 54 deletions
--- a/astrbot/core/provider/sources/azure_tts_source.py
+++ b/astrbot/core/provider/sources/azure_tts_source.py
@@ -6,6 +6,7 @@ import re
 import time
 import uuid
 from pathlib import Path
+from typing import cast
 from xml.sax.saxutils import escape

 from httpx import AsyncClient, Timeout
@@ -41,7 +42,7 @@ class OTTSProvider:

    async def _sync_time(self):
        try:
-            response = await self.client.get(self.auth_time_url)
+            response = await cast(AsyncClient, self.client).get(self.auth_time_url)
            response.raise_for_status()
            server_time = int(response.json()["timestamp"])
            local_time = int(time.time())
@@ -63,7 +64,7 @@ class OTTSProvider:
        signature = await self._generate_signature()
        for attempt in range(self.retry_count):
            try:
-                response = await self.client.post(
+                response = await cast(AsyncClient, self.client).post(
                    f"{self.api_url}?sign={signature}",
                    data={
                        "text": text,
@@ -88,6 +89,7 @@ class OTTSProvider:
                if attempt == self.retry_count - 1:
                    raise RuntimeError(f"OTTS请求失败: {e!s}") from e
                await asyncio.sleep(0.5 * (attempt + 1))
+        raise RuntimeError("OTTS未返回音频文件")


 class AzureNativeProvider(TTSProvider):
@@ -132,7 +134,7 @@ class AzureNativeProvider(TTSProvider):
        token_url = (
            f"https://{self.region}.api.cognitive.microsoft.com/sts/v1.0/issuetoken"
        )
-        response = await self.client.post(
+        response = await cast(AsyncClient, self.client).post(
            token_url,
            headers={"Ocp-Apim-Subscription-Key": self.subscription_key},
        )
@@ -156,7 +158,7 @@ class AzureNativeProvider(TTSProvider):
                </mstts:express-as>
            </voice>
        </speak>"""
-        response = await self.client.post(
+        response = await cast(AsyncClient, self.client).post(
            self.endpoint,
            content=ssml,
            headers={
@@ -179,8 +181,11 @@ class AzureTTSProvider(TTSProvider):
        key_value = provider_config.get("azure_tts_subscription_key", "")
        self.provider = self._parse_provider(key_value, provider_config)

-    def _parse_provider(self, key_value: str, config: dict) -> TTSProvider:
+    def _parse_provider(
+        self, key_value: str, config: dict
+    ) -> OTTSProvider | AzureNativeProvider:
        if key_value.lower().startswith("other["):
+            json_str = ""
            try:
                match = re.match(r"other\[(.*)\]", key_value, re.DOTALL)
                if not match:
--- a/astrbot/core/provider/sources/coze_source.py
+++ b/astrbot/core/provider/sources/coze_source.py
@@ -27,7 +27,7 @@ class ProviderCoze(Provider):
            provider_settings,
            default_persona,
        )
-        self.api_key = provider_config.get("coze_api_key", "")
+        self.api_key: str = provider_config.get("coze_api_key", "")
        if not self.api_key:
            raise Exception("Coze API Key 不能为空。")
        self.bot_id = provider_config.get("bot_id", "")
@@ -65,8 +65,8 @@ class ProviderCoze(Provider):
        """
        try:
            if is_base64 and data.startswith("data:image/"):
+                header, encoded = data.split(",", 1)
                try:
-                    header, encoded = data.split(",", 1)
                    image_bytes = base64.b64decode(encoded)
                    cache_key = hashlib.md5(image_bytes).hexdigest()
                    return cache_key
@@ -579,11 +579,11 @@ class ProviderCoze(Provider):
            logger.error(f"清空 Coze 会话失败: {e!s}")
            return False

-    async def get_current_key(self):
+    def get_current_key(self):
        """获取当前API Key"""
        return self.api_key

-    async def set_key(self, key: str):
+    def set_key(self, key: str):
        """设置新的API Key"""
        raise NotImplementedError("Coze 适配器不支持设置 API Key。")

@@ -595,12 +595,12 @@ class ProviderCoze(Provider):
        """获取当前模型"""
        return f"bot_{self.bot_id}"

-    def set_model(self, model: str):
+    def set_model(self, model_name: str):
        """设置模型（在Coze中是Bot ID）"""
-        if model.startswith("bot_"):
-            self.bot_id = model[4:]
+        if model_name.startswith("bot_"):
+            self.bot_id = model_name[4:]
        else:
-            self.bot_id = model
+            self.bot_id = model_name

    async def get_human_readable_context(
        self,
--- a/astrbot/core/provider/sources/dashscope_source.py
+++ b/astrbot/core/provider/sources/dashscope_source.py
@@ -28,7 +28,7 @@ class ProviderDashscope(ProviderOpenAIOfficial):
            provider_settings,
            default_persona,
        )
-        self.api_key = provider_config.get("dashscope_api_key", "")
+        self.api_key: str = provider_config.get("dashscope_api_key", "")
        if not self.api_key:
            raise Exception("阿里云百炼 API Key 不能为空。")
        self.app_id = provider_config.get("dashscope_app_id", "")
@@ -70,6 +70,7 @@ class ProviderDashscope(ProviderOpenAIOfficial):
        func_tool=None,
        contexts=None,
        system_prompt=None,
+        tool_calls_result=None,
        model=None,
        **kwargs,
    ) -> LLMResponse:
@@ -79,6 +80,8 @@ class ProviderDashscope(ProviderOpenAIOfficial):
        payload_vars = self.variables.copy()
        # 动态变量
        session_var = await sp.session_get(session_id, "session_variables", default={})
+        if not isinstance(session_var, dict):
+            session_var = {}
        payload_vars.update(session_var)

        if (
@@ -163,9 +166,9 @@ class ProviderDashscope(ProviderOpenAIOfficial):
        self,
        prompt,
        session_id=None,
-        image_urls=...,
+        image_urls=None,
        func_tool=None,
-        contexts=...,
+        contexts=None,
        system_prompt=None,
        tool_calls_result=None,
        model=None,
@@ -190,10 +193,10 @@ class ProviderDashscope(ProviderOpenAIOfficial):
    async def forget(self, session_id):
        return True

-    async def get_current_key(self):
+    def get_current_key(self):
        return self.api_key

-    async def set_key(self, key):
+    def set_key(self, key):
        raise Exception("阿里云百炼 适配器不支持设置 API Key。")

    async def get_models(self):
--- a/astrbot/core/provider/sources/dashscope_tts.py
+++ b/astrbot/core/provider/sources/dashscope_tts.py
@@ -36,7 +36,7 @@ class ProviderDashscopeTTSAPI(TTSProvider):
        super().__init__(provider_config, provider_settings)
        self.chosen_api_key: str = provider_config.get("api_key", "")
        self.voice: str = provider_config.get("dashscope_tts_voice", "loongstella")
-        self.set_model(provider_config.get("model"))
+        self.set_model(provider_config["model"])
        self.timeout_ms = float(provider_config.get("timeout", 20)) * 1000
        dashscope.api_key = self.chosen_api_key

@@ -71,9 +71,10 @@ class ProviderDashscopeTTSAPI(TTSProvider):

        kwargs = {
            "model": model,
-            "text": text,
+            "messages": None,
            "api_key": self.chosen_api_key,
            "voice": self.voice or "Cherry",
+            "text": text,
        }
        if not self.voice:
            logging.warning(
--- a/astrbot/core/provider/sources/dify_source.py
+++ b/astrbot/core/provider/sources/dify_source.py
@@ -101,6 +101,8 @@ class ProviderDify(Provider):
        payload_vars = self.variables.copy()
        # 动态变量
        session_var = await sp.session_get(session_id, "session_variables", default={})
+        if not isinstance(session_var, dict):
+            session_var = {}
        payload_vars.update(session_var)
        payload_vars["system_prompt"] = system_prompt

@@ -271,10 +273,10 @@ class ProviderDify(Provider):
        self.conversation_ids[session_id] = ""
        return True

-    async def get_current_key(self):
+    def get_current_key(self):
        return self.api_key

-    async def set_key(self, key):
+    def set_key(self, key):
        raise Exception("Dify 适配器不支持设置 API Key。")

    async def get_models(self):
--- a/astrbot/core/provider/sources/edge_tts_source.py
+++ b/astrbot/core/provider/sources/edge_tts_source.py
@@ -67,7 +67,7 @@ class ProviderEdgeTTS(TTSProvider):
                from pyffmpeg import FFmpeg

                ff = FFmpeg()
-                ff.convert(input=mp3_path, output=wav_path)
+                ff.convert(input_file=mp3_path, output_file=wav_path)
            except Exception as e:
                logger.debug(f"pyffmpeg 转换失败: {e}, 尝试使用 ffmpeg 命令行进行转换")
                # use ffmpeg command line
--- a/astrbot/core/provider/sources/fishaudio_tts_api_source.py
+++ b/astrbot/core/provider/sources/fishaudio_tts_api_source.py
@@ -59,9 +59,9 @@ class ProviderFishAudioTTSAPI(TTSProvider):
        self.headers = {
            "Authorization": f"Bearer {self.chosen_api_key}",
        }
-        self.set_model(provider_config.get("model"))
+        self.set_model(provider_config["model"])

-    async def _get_reference_id_by_character(self, character: str) -> str:
+    async def _get_reference_id_by_character(self, character: str) -> str | None:
        """获取角色的reference_id

        Args:
@@ -128,7 +128,7 @@ class ProviderFishAudioTTSAPI(TTSProvider):
            text=text,
            format="wav",
            reference_id=reference_id,
-        )
+        ).model_dump()

    async def get_audio(self, text: str) -> str:
        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
@@ -146,5 +146,6 @@ class ProviderFishAudioTTSAPI(TTSProvider):
                    async for chunk in response.aiter_bytes():
                        f.write(chunk)
                return path
-            text = await response.aread()
+            body = await response.aread()
+            text = body.decode("utf-8", errors="replace")
            raise Exception(f"Fish Audio API请求失败: {text}")
--- a/astrbot/core/provider/sources/gemini_embedding_source.py
+++ b/astrbot/core/provider/sources/gemini_embedding_source.py
@@ -1,3 +1,5 @@
+from typing import cast
+
 from google import genai
 from google.genai import types
 from google.genai.errors import APIError
@@ -18,8 +20,8 @@ class GeminiEmbeddingProvider(EmbeddingProvider):
        self.provider_config = provider_config
        self.provider_settings = provider_settings

-        api_key: str = provider_config.get("embedding_api_key")
-        api_base: str = provider_config.get("embedding_api_base")
+        api_key: str = provider_config["embedding_api_key"]
+        api_base: str = provider_config["embedding_api_base"]
        timeout: int = int(provider_config.get("timeout", 20))

        http_options = types.HttpOptions(timeout=timeout * 1000)
@@ -41,18 +43,26 @@ class GeminiEmbeddingProvider(EmbeddingProvider):
                model=self.model,
                contents=text,
            )
+            assert result.embeddings is not None
+            assert result.embeddings[0].values is not None
            return result.embeddings[0].values
        except APIError as e:
            raise Exception(f"Gemini Embedding API请求失败: {e.message}")

-    async def get_embeddings(self, texts: list[str]) -> list[list[float]]:
+    async def get_embeddings(self, text: list[str]) -> list[list[float]]:
        """批量获取文本的嵌入"""
        try:
            result = await self.client.models.embed_content(
                model=self.model,
-                contents=texts,
+                contents=cast(types.ContentListUnion, text),
            )
-            return [embedding.values for embedding in result.embeddings]
+            assert result.embeddings is not None
+
+            embeddings: list[list[float]] = []
+            for embedding in result.embeddings:
+                assert embedding.values is not None
+                embeddings.append(embedding.values)
+            return embeddings
        except APIError as e:
            raise Exception(f"Gemini Embedding API批量请求失败: {e.message}")

--- a/astrbot/core/provider/sources/gemini_source.py
+++ b/astrbot/core/provider/sources/gemini_source.py
@@ -4,6 +4,7 @@ import json
 import logging
 import random
 from collections.abc import AsyncGenerator
+from typing import cast

 from google import genai
 from google.genai import types
@@ -138,7 +139,7 @@ class ProviderGoogleGenAI(Provider):
            logger.warning("流式输出不支持图片模态，已自动降级为文本模态")
            modalities = ["Text"]

-        tool_list = []
+        tool_list: list[types.Tool] | None = []
        model_name = self.get_model()
        native_coderunner = self.provider_config.get("gm_native_coderunner", False)
        native_search = self.provider_config.get("gm_native_search", False)
@@ -215,7 +216,7 @@ class ProviderGoogleGenAI(Provider):
            logprobs=payloads.get("logprobs"),
            seed=payloads.get("seed"),
            response_modalities=modalities,
-            tools=tool_list,
+            tools=cast(types.ToolListUnion | None, tool_list),
            safety_settings=self.safety_settings if self.safety_settings else None,
            thinking_config=(
                types.ThinkingConfig(
@@ -259,6 +260,7 @@ class ProviderGoogleGenAI(Provider):
            content_cls: type[types.Content],
        ) -> None:
            if contents and isinstance(contents[-1], content_cls):
+                assert contents[-1].parts is not None
                contents[-1].parts.extend(part)
            else:
                contents.append(content_cls(parts=part))
@@ -419,7 +421,7 @@ class ProviderGoogleGenAI(Provider):
                )
                result = await self.client.models.generate_content(
                    model=self.get_model(),
-                    contents=conversation,
+                    contents=cast(types.ContentListUnion, conversation),
                    config=config,
                )

@@ -494,7 +496,7 @@ class ProviderGoogleGenAI(Provider):
                )
                result = await self.client.models.generate_content_stream(
                    model=self.get_model(),
-                    contents=conversation,
+                    contents=cast(types.ContentListUnion, conversation),
                    config=config,
                )
                break
--- a/astrbot/core/provider/sources/minimax_tts_api_source.py
+++ b/astrbot/core/provider/sources/minimax_tts_api_source.py
@@ -87,7 +87,7 @@ class ProviderMiniMaxTTSAPI(TTSProvider):

        return json.dumps(dict_body)

-    async def _call_tts_stream(self, text: str) -> AsyncIterator[bytes]:
+    async def _call_tts_stream(self, text: str) -> AsyncIterator[str]:
        """进行流式请求"""
        try:
            async with (
@@ -117,7 +117,9 @@ class ProviderMiniMaxTTSAPI(TTSProvider):
                                    data = json.loads(message[6:])
                                    if "extra_info" in data:
                                        continue
-                                    audio = data.get("data", {}).get("audio")
+                                    audio: str | None = data.get("data", {}).get(
+                                        "audio"
+                                    )
                                    if audio is not None:
                                        yield audio
                                except json.JSONDecodeError:
--- a/astrbot/core/provider/sources/openai_embedding_source.py
+++ b/astrbot/core/provider/sources/openai_embedding_source.py
@@ -30,9 +30,9 @@ class OpenAIEmbeddingProvider(EmbeddingProvider):
        embedding = await self.client.embeddings.create(input=text, model=self.model)
        return embedding.data[0].embedding

-    async def get_embeddings(self, texts: list[str]) -> list[list[float]]:
+    async def get_embeddings(self, text: list[str]) -> list[list[float]]:
        """批量获取文本的嵌入"""
-        embeddings = await self.client.embeddings.create(input=texts, model=self.model)
+        embeddings = await self.client.embeddings.create(input=text, model=self.model)
        return [item.embedding for item in embeddings.data]

    def get_dim(self) -> int:
--- a/astrbot/core/provider/sources/openai_source.py
+++ b/astrbot/core/provider/sources/openai_source.py
@@ -102,7 +102,7 @@ class ProviderOpenAIOfficial(Provider):
        except NotFoundError as e:
            raise Exception(f"获取模型列表失败：{e}")

-    async def _query(self, payloads: dict, tools: ToolSet) -> LLMResponse:
+    async def _query(self, payloads: dict, tools: ToolSet | None) -> LLMResponse:
        if tools:
            model = payloads.get("model", "").lower()
            omit_empty_param_field = "gemini" in model
@@ -151,9 +151,7 @@ class ProviderOpenAIOfficial(Provider):
        return llm_response

    async def _query_stream(
-        self,
-        payloads: dict,
-        tools: ToolSet,
+        self, payloads: dict, tools: ToolSet | None
    ) -> AsyncGenerator[LLMResponse, None]:
        """流式查询API，逐步返回结果"""
        if tools:
@@ -212,7 +210,9 @@ class ProviderOpenAIOfficial(Provider):

        yield llm_response

-    async def parse_openai_completion(self, completion: ChatCompletion, tools: ToolSet):
+    async def parse_openai_completion(
+        self, completion: ChatCompletion, tools: ToolSet | None
+    ):
        """解析 OpenAI 的 ChatCompletion 响应"""
        llm_response = LLMResponse("assistant")

@@ -234,6 +234,10 @@ class ProviderOpenAIOfficial(Provider):
                if isinstance(tool_call, str):
                    # workaround for #1359
                    tool_call = json.loads(tool_call)
+                if tools is None:
+                    # 工具集未提供
+                    # Should be unreachable
+                    raise Exception("工具集未提供")
                for tool in tools.func_list:
                    if (
                        tool_call.type == "function"
@@ -310,7 +314,7 @@ class ProviderOpenAIOfficial(Provider):
        e: Exception,
        payloads: dict,
        context_query: list,
-        func_tool: ToolSet,
+        func_tool: ToolSet | None,
        chosen_key: str,
        available_api_keys: list[str],
        retry_cnt: int,
--- a/astrbot/core/provider/sources/sensevoice_selfhosted_source.py
+++ b/astrbot/core/provider/sources/sensevoice_selfhosted_source.py
@@ -7,6 +7,7 @@ import asyncio
 import os
 import re
 from datetime import datetime
+from typing import cast

 from funasr_onnx import SenseVoiceSmall
 from funasr_onnx.utils.postprocess_utils import rich_transcription_postprocess
@@ -32,7 +33,7 @@ class ProviderSenseVoiceSTTSelfHost(STTProvider):
        provider_settings: dict,
    ) -> None:
        super().__init__(provider_config, provider_settings)
-        self.set_model(provider_config.get("stt_model"))
+        self.set_model(provider_config["stt_model"])
        self.model = None
        self.is_emotion = provider_config.get("is_emotion", False)

@@ -86,7 +87,9 @@ class ProviderSenseVoiceSTTSelfHost(STTProvider):
            loop = asyncio.get_event_loop()
            res = await loop.run_in_executor(
                None,  # 使用默认的线程池
-                lambda: self.model(audio_url, language="auto", use_itn=True),
+                lambda: cast(SenseVoiceSmall, self.model)(
+                    audio_url, language="auto", use_itn=True
+                ),
            )

            # res = self.model(audio_url, language="auto", use_itn=True)
--- a/astrbot/core/provider/sources/vllm_rerank_source.py
+++ b/astrbot/core/provider/sources/vllm_rerank_source.py
@@ -44,6 +44,7 @@ class VLLMRerankProvider(RerankProvider):
        }
        if top_n is not None:
            payload["top_n"] = top_n
+        assert self.client is not None
        async with self.client.post(
            f"{self.base_url}/v1/rerank",
            json=payload,
--- a/astrbot/core/provider/sources/whisper_api_source.py
+++ b/astrbot/core/provider/sources/whisper_api_source.py
@@ -33,7 +33,7 @@ class ProviderOpenAIWhisperAPI(STTProvider):
            timeout=provider_config.get("timeout", NOT_GIVEN),
        )

-        self.set_model(provider_config.get("model"))
+        self.set_model(provider_config["model"])

    async def _is_silk_file(self, file_path):
        silk_header = b"SILK"
--- a/astrbot/core/provider/sources/whisper_selfhosted_source.py
+++ b/astrbot/core/provider/sources/whisper_selfhosted_source.py
@@ -1,6 +1,7 @@
 import asyncio
 import os
 import uuid
+from typing import cast

 import whisper

@@ -26,7 +27,7 @@ class ProviderOpenAIWhisperSelfHost(STTProvider):
        provider_settings: dict,
    ) -> None:
        super().__init__(provider_config, provider_settings)
-        self.set_model(provider_config.get("model"))
+        self.set_model(provider_config["model"])
        self.model = None

    async def initialize(self):
@@ -75,5 +76,7 @@ class ProviderOpenAIWhisperSelfHost(STTProvider):
                await tencent_silk_to_wav(audio_url, output_path)
                audio_url = output_path

-        result = await loop.run_in_executor(None, self.model.transcribe, audio_url)
-        return result["text"]
+        result = await loop.run_in_executor(
+            None, cast(whisper.Whisper, self.model).transcribe, audio_url
+        )
+        return cast(str, result["text"])
--- a/astrbot/core/provider/sources/xinference_rerank_source.py
+++ b/astrbot/core/provider/sources/xinference_rerank_source.py
@@ -1,6 +1,11 @@
+from typing import cast
+
 from xinference_client.client.restful.async_restful_client import (
    AsyncClient as Client,
 )
+from xinference_client.client.restful.async_restful_client import (
+    AsyncRESTfulRerankModelHandle,
+)

 from astrbot import logger

@@ -29,7 +34,7 @@ class XinferenceRerankProvider(RerankProvider):
            False,
        )
        self.client = None
-        self.model = None
+        self.model: AsyncRESTfulRerankModelHandle | None = None
        self.model_uid = None

    async def initialize(self):
@@ -65,7 +70,10 @@ class XinferenceRerankProvider(RerankProvider):
                    return

            if self.model_uid:
-                self.model = await self.client.get_model(self.model_uid)
+                self.model = cast(
+                    AsyncRESTfulRerankModelHandle,
+                    await self.client.get_model(self.model_uid),
+                )

        except Exception as e:
            logger.error(f"Failed to initialize Xinference model: {e}")