chore: Add PyPI package support for uvx/pip installation (#1764)

* Initial plan * Add package structure and resource path utilities - Created langbot/ package with __init__.py and __main__.py entry point - Added paths utility to find frontend and resource files from package installation - Updated config loading to use resource paths - Updated frontend serving to use resource paths - Added MANIFEST.in for package data inclusion - Updated pyproject.toml with build system and entry points Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * Add PyPI publishing workflow and update license - Created GitHub Actions workflow to build frontend and publish to PyPI - Added license field to pyproject.toml to fix deprecation warning - Updated .gitignore to exclude build artifacts - Tested package building successfully Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * Add PyPI installation documentation - Created PYPI_INSTALLATION.md with detailed installation and usage instructions - Updated README.md to feature uvx/pip installation as recommended method - Updated README_EN.md with same changes for English documentation Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * Address code review feedback - Made package-data configuration more specific to langbot package only - Improved path detection with caching to avoid repeated file I/O - Removed sys.path searching which was incorrect for package data - Removed interactive input() call for non-interactive environment compatibility - Simplified error messages for version check Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * Fix code review issues - Use specific exception types instead of bare except - Fix misleading comments about directory levels - Remove redundant existence check before makedirs with exist_ok=True - Use context manager for file opening to ensure proper cleanup Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * Simplify package configuration and document behavioral differences - Removed redundant package-data configuration, relying on MANIFEST.in - Added documentation about behavioral differences between package and source installation - Clarified that include-package-data=true uses MANIFEST.in for data files Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * chore: update pyproject.toml * chore: try pack templates in langbot/ * chore: update * chore: update * chore: update * chore: update * chore: update * chore: adjust dir structure * chore: fix imports * fix: read default-pipeline-config.json * fix: read default-pipeline-config.json * fix: tests * ci: publish pypi * chore: bump version 4.6.0-beta.1 for testing * chore: add templates/** * fix: send adapters and requesters icons * chore: bump version 4.6.0b2 for testing * chore: add platform field for docker-compose.yaml --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> Co-authored-by: Junyan Qin <rockchinq@gmail.com>
2026-06-13 01:06:03 +00:00 · 2025-11-16 19:53:01 +08:00
parent 6a24c951e0
commit e642ffa5b3
477 changed files with 1001 additions and 1002 deletions
--- a/src/langbot/pkg/provider/modelmgr/modelmgr.py
+++ b/src/langbot/pkg/provider/modelmgr/modelmgr.py
@@ -0,0 +1,202 @@
+from __future__ import annotations
+
+import sqlalchemy
+import traceback
+
+from . import requester
+from ...core import app
+from ...discover import engine
+from . import token
+from ...entity.persistence import model as persistence_model
+from ...entity.errors import provider as provider_errors
+
+FETCH_MODEL_LIST_URL = 'https://api.qchatgpt.rockchin.top/api/v2/fetch/model_list'
+
+
+class ModelManager:
+    """模型管理器"""
+
+    ap: app.Application
+
+    llm_models: list[requester.RuntimeLLMModel]
+
+    embedding_models: list[requester.RuntimeEmbeddingModel]
+
+    requester_components: list[engine.Component]
+
+    requester_dict: dict[str, type[requester.ProviderAPIRequester]]  # cache
+
+    def __init__(self, ap: app.Application):
+        self.ap = ap
+        self.llm_models = []
+        self.embedding_models = []
+        self.requester_components = []
+        self.requester_dict = {}
+
+    async def initialize(self):
+        self.requester_components = self.ap.discover.get_components_by_kind('LLMAPIRequester')
+
+        # forge requester class dict
+        requester_dict: dict[str, type[requester.ProviderAPIRequester]] = {}
+        for component in self.requester_components:
+            requester_dict[component.metadata.name] = component.get_python_component_class()
+
+        self.requester_dict = requester_dict
+
+        await self.load_models_from_db()
+
+    async def load_models_from_db(self):
+        """从数据库加载模型"""
+        self.ap.logger.info('Loading models from db...')
+
+        self.llm_models = []
+        self.embedding_models = []
+
+        # llm models
+        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel))
+        llm_models = result.all()
+        for llm_model in llm_models:
+            try:
+                await self.load_llm_model(llm_model)
+            except provider_errors.RequesterNotFoundError as e:
+                self.ap.logger.warning(f'Requester {e.requester_name} not found, skipping llm model {llm_model.uuid}')
+            except Exception as e:
+                self.ap.logger.error(f'Failed to load model {llm_model.uuid}: {e}\n{traceback.format_exc()}')
+
+        # embedding models
+        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.EmbeddingModel))
+        embedding_models = result.all()
+        for embedding_model in embedding_models:
+            try:
+                await self.load_embedding_model(embedding_model)
+            except provider_errors.RequesterNotFoundError as e:
+                self.ap.logger.warning(
+                    f'Requester {e.requester_name} not found, skipping embedding model {embedding_model.uuid}'
+                )
+            except Exception as e:
+                self.ap.logger.error(f'Failed to load model {embedding_model.uuid}: {e}\n{traceback.format_exc()}')
+
+    async def init_runtime_llm_model(
+        self,
+        model_info: persistence_model.LLMModel | sqlalchemy.Row[persistence_model.LLMModel] | dict,
+    ):
+        """初始化运行时 LLM 模型"""
+        if isinstance(model_info, sqlalchemy.Row):
+            model_info = persistence_model.LLMModel(**model_info._mapping)
+        elif isinstance(model_info, dict):
+            model_info = persistence_model.LLMModel(**model_info)
+
+        if model_info.requester not in self.requester_dict:
+            raise provider_errors.RequesterNotFoundError(model_info.requester)
+
+        requester_inst = self.requester_dict[model_info.requester](ap=self.ap, config=model_info.requester_config)
+
+        await requester_inst.initialize()
+
+        runtime_llm_model = requester.RuntimeLLMModel(
+            model_entity=model_info,
+            token_mgr=token.TokenManager(
+                name=model_info.uuid,
+                tokens=model_info.api_keys,
+            ),
+            requester=requester_inst,
+        )
+
+        return runtime_llm_model
+
+    async def init_runtime_embedding_model(
+        self,
+        model_info: persistence_model.EmbeddingModel | sqlalchemy.Row[persistence_model.EmbeddingModel] | dict,
+    ):
+        """初始化运行时 Embedding 模型"""
+        if isinstance(model_info, sqlalchemy.Row):
+            model_info = persistence_model.EmbeddingModel(**model_info._mapping)
+        elif isinstance(model_info, dict):
+            model_info = persistence_model.EmbeddingModel(**model_info)
+
+        if model_info.requester not in self.requester_dict:
+            raise provider_errors.RequesterNotFoundError(model_info.requester)
+
+        requester_inst = self.requester_dict[model_info.requester](ap=self.ap, config=model_info.requester_config)
+
+        await requester_inst.initialize()
+
+        runtime_embedding_model = requester.RuntimeEmbeddingModel(
+            model_entity=model_info,
+            token_mgr=token.TokenManager(
+                name=model_info.uuid,
+                tokens=model_info.api_keys,
+            ),
+            requester=requester_inst,
+        )
+
+        return runtime_embedding_model
+
+    async def load_llm_model(
+        self,
+        model_info: persistence_model.LLMModel | sqlalchemy.Row[persistence_model.LLMModel] | dict,
+    ):
+        """加载 LLM 模型"""
+        runtime_llm_model = await self.init_runtime_llm_model(model_info)
+        self.llm_models.append(runtime_llm_model)
+
+    async def load_embedding_model(
+        self,
+        model_info: persistence_model.EmbeddingModel | sqlalchemy.Row[persistence_model.EmbeddingModel] | dict,
+    ):
+        """加载 Embedding 模型"""
+        runtime_embedding_model = await self.init_runtime_embedding_model(model_info)
+        self.embedding_models.append(runtime_embedding_model)
+
+    async def get_model_by_uuid(self, uuid: str) -> requester.RuntimeLLMModel:
+        """通过uuid获取 LLM 模型"""
+        for model in self.llm_models:
+            if model.model_entity.uuid == uuid:
+                return model
+        raise ValueError(f'LLM model {uuid} not found')
+
+    async def get_embedding_model_by_uuid(self, uuid: str) -> requester.RuntimeEmbeddingModel:
+        """通过uuid获取 Embedding 模型"""
+        for model in self.embedding_models:
+            if model.model_entity.uuid == uuid:
+                return model
+        raise ValueError(f'Embedding model {uuid} not found')
+
+    async def remove_llm_model(self, model_uuid: str):
+        """移除 LLM 模型"""
+        for model in self.llm_models:
+            if model.model_entity.uuid == model_uuid:
+                self.llm_models.remove(model)
+                return
+
+    async def remove_embedding_model(self, model_uuid: str):
+        """移除 Embedding 模型"""
+        for model in self.embedding_models:
+            if model.model_entity.uuid == model_uuid:
+                self.embedding_models.remove(model)
+                return
+
+    def get_available_requesters_info(self, model_type: str) -> list[dict]:
+        """获取所有可用的请求器"""
+        if model_type != '':
+            return [
+                component.to_plain_dict()
+                for component in self.requester_components
+                if model_type in component.spec['support_type']
+            ]
+        else:
+            return [component.to_plain_dict() for component in self.requester_components]
+
+    def get_available_requester_info_by_name(self, name: str) -> dict | None:
+        """通过名称获取请求器信息"""
+        for component in self.requester_components:
+            if component.metadata.name == name:
+                return component.to_plain_dict()
+        return None
+
+    def get_available_requester_manifest_by_name(self, name: str) -> engine.Component | None:
+        """通过名称获取请求器清单"""
+        for component in self.requester_components:
+            if component.metadata.name == name:
+                return component
+        return None