Merge remote-tracking branch 'origin/main' into feat_llm_manage

pilot/component.py

@@ -46,6 +46,7 @@ class ComponentType(str, Enum):
     WORKER_MANAGER = "dbgpt_worker_manager"
     WORKER_MANAGER_FACTORY = "dbgpt_worker_manager_factory"
     MODEL_CONTROLLER = "dbgpt_model_controller"
+    EXECUTOR_DEFAULT = "dbgpt_thread_pool_default"
 
 
 class BaseComponent(LifeCycle, ABC):

pilot/configs/config.py

@@ -141,6 +141,7 @@ class Config(metaclass=Singleton):
         self.LOCAL_DB_PORT = int(os.getenv("LOCAL_DB_PORT", 3306))
         self.LOCAL_DB_USER = os.getenv("LOCAL_DB_USER", "root")
         self.LOCAL_DB_PASSWORD = os.getenv("LOCAL_DB_PASSWORD", "aa123456")
+        self.LOCAL_DB_POOL_SIZE = int(os.getenv("LOCAL_DB_POOL_SIZE", 10))
 
         self.LOCAL_DB_MANAGE = None
 

pilot/connections/manages/connection_manager.py

@@ -4,7 +4,9 @@ import asyncio
 from pilot.configs.config import Config
 from pilot.connections.manages.connect_storage_duckdb import DuckdbConnectConfig
 from pilot.common.schema import DBType
-from pilot.component import SystemApp
+from pilot.component import SystemApp, ComponentType
+from pilot.utils.executor_utils import ExecutorFactory
+
 from pilot.connections.rdbms.conn_mysql import MySQLConnect
 from pilot.connections.base import BaseConnect
 
@@ -76,7 +78,11 @@ class ConnectManager:
                     + CFG.LOCAL_DB_HOST
                     + ":"
                     + str(CFG.LOCAL_DB_PORT),
-                    engine_args={"pool_size": 10, "pool_recycle": 3600, "echo": True},
+                    engine_args={
+                        "pool_size": CFG.LOCAL_DB_POOL_SIZE,
+                        "pool_recycle": 3600,
+                        "echo": True,
+                    },
                 )
                 # default_mysql = MySQLConnect.from_uri(
                 #     "mysql+pymysql://"
@@ -208,13 +214,15 @@ class ConnectManager:
                     db_info.comment,
                 )
             # async embedding
-            thread = threading.Thread(
-                target=self.db_summary_client.db_summary_embedding(
-                    db_info.db_name, db_info.db_type
+            executor = CFG.SYSTEM_APP.get_component(
+                ComponentType.EXECUTOR_DEFAULT, ExecutorFactory
+            ).create()
+            executor.submit(
+                self.db_summary_client.db_summary_embedding,
+                db_info.db_name,
+                db_info.db_type,
             )
-            )
-            thread.start()
         except Exception as e:
-            raise ValueError("Add db connect info error！" + str(e))
+            raise ValueError("Add db connect info error!" + str(e))
 
         return True

pilot/model/cluster/worker/manager.py

@@ -1,17 +1,18 @@
 import asyncio
 import itertools
 import json
-import os
-import sys
-import random
-import time
 import logging
+import os
+import random
+import sys
+import time
 from concurrent.futures import ThreadPoolExecutor
 from dataclasses import asdict
 from typing import Awaitable, Callable, Dict, Iterator, List, Optional
 
 from fastapi import APIRouter, FastAPI
 from fastapi.responses import StreamingResponse
+
 from pilot.component import SystemApp
 from pilot.model.base import (
     ModelInstance,
@@ -20,16 +21,16 @@ from pilot.model.base import (
     WorkerApplyType,
     WorkerSupportedModel,
 )
-from pilot.model.cluster.registry import ModelRegistry
-from pilot.model.llm_utils import list_supported_models
-from pilot.model.parameter import ModelParameters, ModelWorkerParameters, WorkerType
-from pilot.model.cluster.worker_base import ModelWorker
+from pilot.model.cluster.base import *
 from pilot.model.cluster.manager_base import (
     WorkerManager,
-    WorkerRunData,
     WorkerManagerFactory,
+    WorkerRunData,
 )
-from pilot.model.cluster.base import *
+from pilot.model.cluster.registry import ModelRegistry
+from pilot.model.cluster.worker_base import ModelWorker
+from pilot.model.llm_utils import list_supported_models
+from pilot.model.parameter import ModelParameters, ModelWorkerParameters, WorkerType
 from pilot.utils.parameter_utils import (
     EnvArgumentParser,
     ParameterDescription,
@@ -639,6 +640,10 @@ def _setup_fastapi(worker_params: ModelWorkerParameters, app=None):
         )
 
         if not worker_params.controller_addr:
+            # if we have http_proxy or https_proxy in env, the server can not start
+            # so set it to empty here
+            os.environ["http_proxy"] = ""
+            os.environ["https_proxy"] = ""
             worker_params.controller_addr = f"http://127.0.0.1:{worker_params.port}"
         logger.info(
             f"Run WorkerManager with standalone mode, controller_addr: {worker_params.controller_addr}"

pilot/model/parameter.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+import os
 from dataclasses import dataclass, field
 from enum import Enum
 from typing import Dict, Optional
@@ -246,6 +247,11 @@ class ProxyModelParameters(BaseModelParameters):
     proxy_api_key: str = field(
         metadata={"tags": "privacy", "help": "The api key of current proxy LLM"},
     )
+    http_proxy: Optional[str] = field(
+        default=os.environ.get("http_proxy") or os.environ.get("https_proxy"),
+        metadata={"help": "The http or https proxy to use openai"},
+    )
+
     proxyllm_backend: Optional[str] = field(
         default=None,
         metadata={

pilot/server/component_configs.py

@@ -4,6 +4,7 @@ import logging
 from typing import TYPE_CHECKING, Any, Type
 
 from pilot.component import ComponentType, SystemApp
+from pilot.utils.executor_utils import DefaultExecutorFactory
 from pilot.embedding_engine.embedding_factory import EmbeddingFactory
 from pilot.server.base import WebWerverParameters
 
@@ -22,6 +23,9 @@ def initialize_components(
 ):
     from pilot.model.cluster.controller.controller import controller
 
+    # Register global default executor factory first
+    system_app.register(DefaultExecutorFactory)
+
     system_app.register_instance(controller)
 
     _initialize_embedding_model(

pilot/server/knowledge/_cli/knowledge_client.py

@@ -124,12 +124,13 @@ def knowledge_init(
     def upload(filename: str):
         try:
             logger.info(f"Begin upload document: {filename} to {space.name}")
-            return client.document_upload(
+            doc_id = client.document_upload(
                 space.name, filename, KnowledgeType.DOCUMENT.value, filename
             )
+            client.document_sync(space.name, DocumentSyncRequest(doc_ids=[doc_id]))
         except Exception as e:
             if skip_wrong_doc:
-                logger.warn(f"Warning: {str(e)}")
+                logger.warn(f"Upload {filename} to {space.name} failed: {str(e)}")
             else:
                 raise e
 
@@ -144,5 +145,3 @@ def knowledge_init(
         if not doc_ids:
             logger.warn("Warning: no document to sync")
             return
-        logger.info(f"Begin sync document: {doc_ids}")
-        client.document_sync(space.name, DocumentSyncRequest(doc_ids=doc_ids))

pilot/server/knowledge/service.py

@@ -9,6 +9,9 @@ from pilot.configs.model_config import (
     EMBEDDING_MODEL_CONFIG,
     KNOWLEDGE_UPLOAD_ROOT_PATH,
 )
+from pilot.component import ComponentType
+from pilot.utils.executor_utils import ExecutorFactory
+
 from pilot.logs import logger
 from pilot.server.knowledge.chunk_db import (
     DocumentChunkEntity,
@@ -227,10 +230,15 @@ class KnowledgeService:
             doc.gmt_modified = datetime.now()
             knowledge_document_dao.update_knowledge_document(doc)
             # async doc embeddings
-            thread = threading.Thread(
-                target=self.async_doc_embedding, args=(client, chunk_docs, doc)
-            )
-            thread.start()
+            # thread = threading.Thread(
+            #     target=self.async_doc_embedding, args=(client, chunk_docs, doc)
+            # )
+            # thread.start()
+            executor = CFG.SYSTEM_APP.get_component(
+                ComponentType.EXECUTOR_DEFAULT, ExecutorFactory
+            ).create()
+            executor.submit(self.async_doc_embedding, client, chunk_docs, doc)
+
             logger.info(f"begin save document chunks, doc:{doc.doc_name}")
             # save chunk details
             chunk_entities = [

pilot/utils/executor_utils.py

@@ -0,0 +1,26 @@
+from abc import ABC, abstractmethod
+from concurrent.futures import Executor, ThreadPoolExecutor
+
+from pilot.component import BaseComponent, ComponentType, SystemApp
+
+
+class ExecutorFactory(BaseComponent, ABC):
+    name = ComponentType.EXECUTOR_DEFAULT.value
+
+    @abstractmethod
+    def create(self) -> "Executor":
+        """Create executor"""
+
+
+class DefaultExecutorFactory(ExecutorFactory):
+    def __init__(self, system_app: SystemApp | None = None, max_workers=None):
+        super().__init__(system_app)
+        self._executor = ThreadPoolExecutor(
+            max_workers=max_workers, thread_name_prefix=self.name
+        )
+
+    def init_app(self, system_app: SystemApp):
+        pass
+
+    def create(self) -> Executor:
+        return self._executor

setup.py

@@ -8,7 +8,6 @@ from enum import Enum
 import urllib.request
 from urllib.parse import urlparse, quote
 import re
-from pip._internal.utils.appdirs import user_cache_dir
 import shutil
 from setuptools import find_packages
 
@@ -67,6 +66,9 @@ def cache_package(package_url: str, package_name: str, is_windows: bool = False)
     safe_url, parsed_url = encode_url(package_url)
     if BUILD_NO_CACHE:
         return safe_url
+
+    from pip._internal.utils.appdirs import user_cache_dir
+
     filename = os.path.basename(parsed_url)
     cache_dir = os.path.join(user_cache_dir("pip"), "http", "wheels", package_name)
     os.makedirs(cache_dir, exist_ok=True)
@@ -279,7 +281,7 @@ def core_requires():
         "importlib-resources==5.12.0",
         "psutil==5.9.4",
         "python-dotenv==1.0.0",
-        "colorama",
+        "colorama==0.4.10",
         "prettytable",
         "cachetools",
     ]