feat(core): Multi-module dependency splitting

.github/release-drafter.yml

@@ -76,6 +76,16 @@ autolabeler:
       # feat(connection): Support xxxx
       # fix(connection): Fix xxx
       - '/^(build|chore|ci|depr|docs|feat|fix|perf|refactor|release|test)\(.*connection.*\)/'
+  - label: core
+    title:
+      # feat(core): Support xxxx
+      # fix(core): Fix xxx
+      - '/^(build|chore|ci|depr|docs|feat|fix|perf|refactor|release|test)\(.*core.*\)/'
+  - label: web
+    title:
+      # feat(web): Support xxxx
+      # fix(web): Fix xxx
+      - '/^(build|chore|ci|depr|docs|feat|fix|perf|refactor|release|test)\(.*web.*\)/'
   - label: build
     title:
       - '/^build/'

.gitignore

@@ -28,6 +28,8 @@ sdist/
 var/
 wheels/
 models/
+# Soft link
+models
 plugins/
 
 pip-wheel-metadata/

README.md

@@ -86,7 +86,7 @@ Currently, we have released multiple key features, which are listed below to dem
 - Unified vector storage/indexing of knowledge base
   - Support for unstructured data such as PDF, TXT, Markdown, CSV, DOC, PPT, and WebURL
 - Multi LLMs Support, Supports multiple large language models, currently supporting
-  - 🔥 InternLM(7b)
+  - 🔥 InternLM(7b,20b)
   - 🔥 Baichuan2(7b,13b)
   - 🔥 Vicuna-v1.5(7b,13b)
   - 🔥 llama-2(7b,13b,70b)

README.zh.md

@@ -119,7 +119,7 @@ DB-GPT 是一个开源的以数据库为基础的GPT实验项目，使用本地
   - 非结构化数据支持包括PDF、MarkDown、CSV、WebURL
 - 多模型支持
   - 支持多种大语言模型, 当前已支持如下模型: 
-  - 🔥 InternLM(7b)
+  - 🔥 InternLM(7b,20b)
   - 🔥 Baichuan2(7b,13b)
   - 🔥 Vicuna-v1.5(7b,13b)
   - 🔥 llama-2(7b,13b,70b)

docker/base/Dockerfile

@@ -11,10 +11,12 @@ ARG LANGUAGE="en"
 ARG PIP_INDEX_URL="https://pypi.org/simple"
 ENV PIP_INDEX_URL=$PIP_INDEX_URL
 
+ARG DB_GPT_INSTALL_MODEL="default"
+ENV DB_GPT_INSTALL_MODEL=$DB_GPT_INSTALL_MODEL
+
 RUN mkdir -p /app
 
 # COPY only requirements.txt first to leverage Docker cache
-COPY ./requirements.txt /app/requirements.txt
 COPY ./setup.py /app/setup.py
 COPY ./README.md /app/README.md
 
@@ -26,9 +28,9 @@ WORKDIR /app
 # RUN pip3 install -i $PIP_INDEX_URL ".[all]"
 
 RUN pip3 install --upgrade pip -i $PIP_INDEX_URL \
-    && pip3 install -i $PIP_INDEX_URL . \
-    # && pip3 install -i $PIP_INDEX_URL ".[llama_cpp]" \
-    && (if [ "${LANGUAGE}" = "zh" ]; \
+    && pip3 install -i $PIP_INDEX_URL ".[$DB_GPT_INSTALL_MODEL]"
+
+RUN (if [ "${LANGUAGE}" = "zh" ]; \
         # language is zh, download zh_core_web_sm from github
         then wget https://github.com/explosion/spacy-models/releases/download/zh_core_web_sm-3.5.0/zh_core_web_sm-3.5.0-py3-none-any.whl -O /tmp/zh_core_web_sm-3.5.0-py3-none-any.whl \
         && pip3 install /tmp/zh_core_web_sm-3.5.0-py3-none-any.whl -i $PIP_INDEX_URL \
@@ -58,4 +60,4 @@ RUN (if [ "${LOAD_EXAMPLES}" = "true" ]; \
 ENV PYTHONPATH "/app:$PYTHONPATH"
 EXPOSE 5000
 
-CMD ["python3", "pilot/server/dbgpt_server.py"]
+CMD ["dbgpt", "start", "webserver"]

docker/base/build_image.sh

@@ -4,14 +4,21 @@ SCRIPT_LOCATION=$0
 cd "$(dirname "$SCRIPT_LOCATION")"
 WORK_DIR=$(pwd)
 
-BASE_IMAGE="nvidia/cuda:11.8.0-runtime-ubuntu22.04"
+BASE_IMAGE_DEFAULT="nvidia/cuda:11.8.0-runtime-ubuntu22.04"
+BASE_IMAGE_DEFAULT_CPU="ubuntu:22.04"
+
+BASE_IMAGE=$BASE_IMAGE_DEFAULT
 IMAGE_NAME="eosphorosai/dbgpt"
+IMAGE_NAME_ARGS=""
+
 # zh: https://pypi.tuna.tsinghua.edu.cn/simple
 PIP_INDEX_URL="https://pypi.org/simple"
 # en or zh
 LANGUAGE="en"
 BUILD_LOCAL_CODE="false"
 LOAD_EXAMPLES="true"
+BUILD_NETWORK=""
+DB_GPT_INSTALL_MODEL="default"
 
 usage () {
     echo "USAGE: $0 [--base-image nvidia/cuda:11.8.0-runtime-ubuntu22.04] [--image-name db-gpt]"
@@ -21,6 +28,8 @@ usage () {
     echo "  [--language en or zh] You language, default: en"
     echo "  [--build-local-code true or false] Whether to use the local project code to package the image, default: false"
     echo "  [--load-examples true or false] Whether to load examples to default database default: true"
+    echo "  [--network network name] The network of docker build"
+    echo "  [--install-mode mode name] Installation mode name, default: default, If you completely use openai's service, you can set the mode name to 'openai'"
     echo "  [-h|--help] Usage message"
 }
 
@@ -33,7 +42,7 @@ while [[ $# -gt 0 ]]; do
         shift # past value
         ;;
         -n|--image-name)
-        IMAGE_NAME="$2"
+        IMAGE_NAME_ARGS="$2"
         shift # past argument
         shift # past value
         ;;
@@ -57,6 +66,20 @@ while [[ $# -gt 0 ]]; do
         shift
         shift
         ;;
+        --network)
+        BUILD_NETWORK=" --network $2 "
+        shift # past argument
+        shift # past value
+        ;;
+        -h|--help)
+        help="true"
+        shift
+        ;;
+        --install-mode)
+        DB_GPT_INSTALL_MODEL="$2"
+        shift # past argument
+        shift # past value
+        ;;
         -h|--help)
         help="true"
         shift
@@ -73,11 +96,29 @@ if [[ $help ]]; then
     exit 0
 fi
 
-docker build \
+if [ "$DB_GPT_INSTALL_MODEL" != "default" ]; then
+    IMAGE_NAME="$IMAGE_NAME-$DB_GPT_INSTALL_MODEL"
+    echo "install mode is not 'default', set image name to: ${IMAGE_NAME}"
+fi
+
+if [ -z "$IMAGE_NAME_ARGS" ]; then
+    if [ "$DB_GPT_INSTALL_MODEL" == "openai" ]; then 
+        # Use cpu image
+        BASE_IMAGE=$BASE_IMAGE_DEFAULT_CPU
+    fi
+else
+    # User input image is not empty
+    BASE_IMAGE=$IMAGE_NAME_ARGS
+fi
+
+echo "Begin build docker image, base image: ${BASE_IMAGE}, target image name: ${IMAGE_NAME}"
+
+docker build $BUILD_NETWORK \
     --build-arg BASE_IMAGE=$BASE_IMAGE \
     --build-arg PIP_INDEX_URL=$PIP_INDEX_URL \
     --build-arg LANGUAGE=$LANGUAGE \
     --build-arg BUILD_LOCAL_CODE=$BUILD_LOCAL_CODE \
     --build-arg LOAD_EXAMPLES=$LOAD_EXAMPLES \
+    --build-arg DB_GPT_INSTALL_MODEL=$DB_GPT_INSTALL_MODEL \
     -f Dockerfile \
     -t $IMAGE_NAME $WORK_DIR/../../

docs/getting_started/install/cluster/vms/index.md

@@ -6,7 +6,7 @@ Local cluster deployment
 
 **Installing Command-Line Tool**
 
-All operations below are performed using the `dbgpt` command. To use the `dbgpt` command, you need to install the DB-GPT project with `pip install -e .`. Alternatively, you can use `python pilot/scripts/cli_scripts.py` as a substitute for the `dbgpt` command.
+All operations below are performed using the `dbgpt` command. To use the `dbgpt` command, you need to install the DB-GPT project with `pip install -e ".[default]"`. Alternatively, you can use `python pilot/scripts/cli_scripts.py` as a substitute for the `dbgpt` command.
 
 ### Launch Model Controller
 

docs/getting_started/install/deploy/deploy.md

@@ -49,7 +49,7 @@ For the entire installation process of DB-GPT, we use the miniconda3 virtual env
 python>=3.10
 conda create -n dbgpt_env python=3.10
 conda activate dbgpt_env
-pip install -e .
+pip install -e ".[default]"
 ```
 Before use DB-GPT Knowledge
 ```bash

docs/getting_started/install/llm/llm.rst

@@ -6,7 +6,7 @@ DB-GPT provides a management and deployment solution for multiple models. This c
 
 
 Multi LLMs Support, Supports multiple large language models, currently supporting
-  - 🔥 InternLM(7b)
+  - 🔥 InternLM(7b,20b)
   - 🔥 Baichuan2(7b,13b)
   - 🔥 Vicuna-v1.5(7b,13b)
   - 🔥 llama-2(7b,13b,70b)

pilot/common/plugins.py

@@ -1,4 +1,5 @@
 """加载组件"""
+from __future__ import annotations
 
 import json
 import os
@@ -8,17 +9,19 @@ import requests
 import threading
 import datetime
 from pathlib import Path
-from typing import List
+from typing import List, TYPE_CHECKING
 from urllib.parse import urlparse
 from zipimport import zipimporter
 
 import requests
-from auto_gpt_plugin_template import AutoGPTPluginTemplate
 
 from pilot.configs.config import Config
 from pilot.configs.model_config import PLUGINS_DIR
 from pilot.logs import logger
 
+if TYPE_CHECKING:
+    from auto_gpt_plugin_template import AutoGPTPluginTemplate
+
 
 def inspect_zip_for_modules(zip_path: str, debug: bool = False) -> list[str]:
     """
@@ -115,7 +118,7 @@ def load_native_plugins(cfg: Config):
     t.start()
 
 
-def scan_plugins(cfg: Config, debug: bool = False) -> List[AutoGPTPluginTemplate]:
+def scan_plugins(cfg: Config, debug: bool = False) -> List["AutoGPTPluginTemplate"]:
     """Scan the plugins directory for plugins and loads them.
 
     Args:

pilot/configs/config.py

@@ -1,11 +1,16 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
+from __future__ import annotations
 
 import os
-from typing import List
+from typing import List, Optional, TYPE_CHECKING
 
 from pilot.singleton import Singleton
 
+if TYPE_CHECKING:
+    from auto_gpt_plugin_template import AutoGPTPluginTemplate
+    from pilot.component import SystemApp
+
 
 class Config(metaclass=Singleton):
     """Configuration class to store the state of bools for different scripts access"""
@@ -99,9 +104,8 @@ class Config(metaclass=Singleton):
         self.message_dir = os.getenv("MESSAGE_HISTORY_DIR", "../../message")
 
         ### The associated configuration parameters of the plug-in control the loading and use of the plug-in
-        from auto_gpt_plugin_template import AutoGPTPluginTemplate
 
-        self.plugins: List[AutoGPTPluginTemplate] = []
+        self.plugins: List["AutoGPTPluginTemplate"] = []
         self.plugins_openai = []
         self.plugins_auto_load = os.getenv("AUTO_LOAD_PLUGIN", "True") == "True"
 
@@ -189,9 +193,7 @@ class Config(metaclass=Singleton):
         ### Log level
         self.DBGPT_LOG_LEVEL = os.getenv("DBGPT_LOG_LEVEL", "INFO")
 
-        from pilot.component import SystemApp
-
-        self.SYSTEM_APP: SystemApp = None
+        self.SYSTEM_APP: Optional["SystemApp"] = None
 
     def set_debug_mode(self, value: bool) -> None:
         """Set the debug mode value"""

pilot/configs/model_config.py

@@ -23,15 +23,18 @@ os.chdir(new_directory)
 
 
 def get_device() -> str:
-    import torch
+    try:
+        import torch
 
-    return (
-        "cuda"
-        if torch.cuda.is_available()
-        else "mps"
-        if torch.backends.mps.is_available()
-        else "cpu"
-    )
+        return (
+            "cuda"
+            if torch.cuda.is_available()
+            else "mps"
+            if torch.backends.mps.is_available()
+            else "cpu"
+        )
+    except ModuleNotFoundError:
+        return "cpu"
 
 
 LLM_MODEL_CONFIG = {
@@ -70,8 +73,9 @@ LLM_MODEL_CONFIG = {
     "wizardlm-13b": os.path.join(MODEL_PATH, "WizardLM-13B-V1.2"),
     "llama-cpp": os.path.join(MODEL_PATH, "ggml-model-q4_0.bin"),
     # https://huggingface.co/internlm/internlm-chat-7b-v1_1, 7b vs 7b-v1.1: https://github.com/InternLM/InternLM/issues/288
-    "internlm-7b": os.path.join(MODEL_PATH, "internlm-chat-7b-v1_1"),
+    "internlm-7b": os.path.join(MODEL_PATH, "internlm-chat-7b"),
     "internlm-7b-8k": os.path.join(MODEL_PATH, "internlm-chat-7b-8k"),
+    "internlm-20b": os.path.join(MODEL_PATH, "internlm-20b-chat"),
 }
 
 EMBEDDING_MODEL_CONFIG = {

pilot/embedding_engine/embedding_engine.py

@@ -1,6 +1,5 @@
 from typing import Optional
 
-from chromadb.errors import NotEnoughElementsException
 from langchain.text_splitter import TextSplitter
 
 from pilot.embedding_engine.embedding_factory import (
@@ -69,10 +68,10 @@ class EmbeddingEngine:
         vector_client = VectorStoreConnector(
             self.vector_store_config["vector_store_type"], self.vector_store_config
         )
-        try:
-            ans = vector_client.similar_search(text, topk)
-        except NotEnoughElementsException:
-            ans = vector_client.similar_search(text, 1)
+        # https://github.com/chroma-core/chroma/issues/657
+        ans = vector_client.similar_search(text, topk)
+        # except NotEnoughElementsException:
+        # ans = vector_client.similar_search(text, 1)
         return ans
 
     def vector_exist(self):

pilot/embedding_engine/markdown_embedding.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
-import os
 from typing import List, Optional
 
 import markdown

pilot/embedding_engine/source_embedding.py

@@ -3,7 +3,6 @@
 from abc import ABC, abstractmethod
 from typing import Dict, List, Optional
 
-from chromadb.errors import NotEnoughElementsException
 from langchain.text_splitter import TextSplitter
 
 from pilot.vector_store.connector import VectorStoreConnector
@@ -71,10 +70,9 @@ class SourceEmbedding(ABC):
         self.vector_client = VectorStoreConnector(
             self.vector_store_config["vector_store_type"], self.vector_store_config
         )
-        try:
-            ans = self.vector_client.similar_search(doc, topk)
-        except NotEnoughElementsException:
-            ans = self.vector_client.similar_search(doc, 1)
+        # https://github.com/chroma-core/chroma/issues/657
+        ans = self.vector_client.similar_search(doc, topk)
+        # ans = self.vector_client.similar_search(doc, 1)
         return ans
 
     def vector_name_exist(self):

pilot/model/cluster/worker/default_worker.py

@@ -1,5 +1,4 @@
 import logging
-import platform
 from typing import Dict, Iterator, List
 
 from pilot.configs.model_config import get_device
@@ -12,7 +11,7 @@ from pilot.server.chat_adapter import get_llm_chat_adapter, BaseChatAdpter
 from pilot.utils.model_utils import _clear_torch_cache
 from pilot.utils.parameter_utils import EnvArgumentParser
 
-logger = logging.getLogger("model_worker")
+logger = logging.getLogger(__name__)
 
 
 class DefaultModelWorker(ModelWorker):
@@ -91,8 +90,13 @@ class DefaultModelWorker(ModelWorker):
         _clear_torch_cache(self._model_params.device)
 
     def generate_stream(self, params: Dict) -> Iterator[ModelOutput]:
-        import torch
+        torch_imported = False
+        try:
+            import torch
 
+            torch_imported = True
+        except ImportError:
+            pass
         try:
             # params adaptation
             params, model_context = self.llm_chat_adapter.model_adaptation(
@@ -117,16 +121,17 @@ class DefaultModelWorker(ModelWorker):
                 )
                 yield model_output
             print(f"\n\nfull stream output:\n{previous_response}")
-        except torch.cuda.CudaError:
-            model_output = ModelOutput(
-                text="**GPU OutOfMemory, Please Refresh.**", error_code=0
-            )
-            yield model_output
         except Exception as e:
-            model_output = ModelOutput(
-                text=f"**LLMServer Generate Error, Please CheckErrorInfo.**: {e}",
-                error_code=0,
-            )
+            # Check if the exception is a torch.cuda.CudaError and if torch was imported.
+            if torch_imported and isinstance(e, torch.cuda.CudaError):
+                model_output = ModelOutput(
+                    text="**GPU OutOfMemory, Please Refresh.**", error_code=0
+                )
+            else:
+                model_output = ModelOutput(
+                    text=f"**LLMServer Generate Error, Please CheckErrorInfo.**: {e}",
+                    error_code=0,
+                )
             yield model_output
 
     def generate(self, params: Dict) -> ModelOutput:

pilot/model/cluster/worker/manager.py

@@ -5,6 +5,7 @@ import os
 import sys
 import random
 import time
+import logging
 from concurrent.futures import ThreadPoolExecutor
 from dataclasses import asdict
 from typing import Awaitable, Callable, Dict, Iterator, List, Optional
@@ -12,7 +13,6 @@ 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.configs.model_config import LOGDIR
 from pilot.model.base import (
     ModelInstance,
     ModelOutput,
@@ -30,15 +30,13 @@ from pilot.model.cluster.manager_base import (
     WorkerManagerFactory,
 )
 from pilot.model.cluster.base import *
-from pilot.utils import build_logger
 from pilot.utils.parameter_utils import (
     EnvArgumentParser,
     ParameterDescription,
     _dict_to_command_args,
 )
 
-logger = build_logger("model_worker", LOGDIR + "/model_worker.log")
-
+logger = logging.getLogger(__name__)
 
 RegisterFunc = Callable[[WorkerRunData], Awaitable[None]]
 DeregisterFunc = Callable[[WorkerRunData], Awaitable[None]]

pilot/model/proxy/llms/bard.py

@@ -1,4 +1,3 @@
-import bardapi
 import requests
 from typing import List
 from pilot.scene.base_message import ModelMessage, ModelMessageRoleType
@@ -52,6 +51,8 @@ def bard_generate_stream(
         else:
             yield f"bard proxy url request failed!, response = {str(response)}"
     else:
+        import bardapi
+
         response = bardapi.core.Bard(proxy_api_key).get_answer("\n".join(msgs))
 
         if response is not None and response.get("content") is not None:

pilot/scene/chat_data/chat_excel/excel_learning/chat.py

@@ -10,9 +10,6 @@ from pilot.scene.base_chat import BaseChat
 from pilot.scene.base import ChatScene
 from pilot.common.sql_database import Database
 from pilot.configs.config import Config
-from pilot.common.markdown_text import (
-    generate_htm_table,
-)
 from pilot.scene.chat_data.chat_excel.excel_learning.prompt import prompt
 from pilot.scene.chat_data.chat_excel.excel_reader import ExcelReader
 from pilot.json_utils.utilities import DateTimeEncoder

pilot/scene/chat_knowledge/v1/chat.py

@@ -1,7 +1,5 @@
 from typing import Dict
 
-from chromadb.errors import NoIndexException
-
 from pilot.scene.base_chat import BaseChat
 from pilot.scene.base import ChatScene
 from pilot.configs.config import Config
@@ -59,22 +57,19 @@ class ChatKnowledge(BaseChat):
         )
 
     def generate_input_values(self):
-        try:
-            if self.space_context:
-                self.prompt_template.template_define = self.space_context["prompt"][
-                    "scene"
-                ]
-                self.prompt_template.template = self.space_context["prompt"]["template"]
-            docs = self.knowledge_embedding_client.similar_search(
-                self.current_user_input, self.top_k
-            )
-            context = [d.page_content for d in docs]
-            context = context[: self.max_token]
-            input_values = {"context": context, "question": self.current_user_input}
-        except NoIndexException:
+        if self.space_context:
+            self.prompt_template.template_define = self.space_context["prompt"]["scene"]
+            self.prompt_template.template = self.space_context["prompt"]["template"]
+        docs = self.knowledge_embedding_client.similar_search(
+            self.current_user_input, self.top_k
+        )
+        if not docs:
             raise ValueError(
                 "you have no knowledge space, please add your knowledge space"
             )
+        context = [d.page_content for d in docs]
+        context = context[: self.max_token]
+        input_values = {"context": context, "question": self.current_user_input}
         return input_values
 
     @property

pilot/server/knowledge/_cli/knowledge_cli.py

@@ -71,7 +71,7 @@ def load(
     skip_wrong_doc: bool,
     max_workers: int,
 ):
-    """Load you local knowledge to DB-GPT"""
+    """Load your local knowledge to DB-GPT"""
     from pilot.server.knowledge._cli.knowledge_client import knowledge_init
 
     knowledge_init(

pilot/summary/db_summary_client.py

@@ -170,8 +170,9 @@ class DBSummaryClient:
     def init_db_profile(self, db_summary_client, dbname, embeddings):
         from pilot.embedding_engine.string_embedding import StringEmbedding
 
+        vector_store_name = dbname + "_profile"
         profile_store_config = {
-            "vector_store_name": dbname + "_profile",
+            "vector_store_name": vector_store_name,
             "chroma_persist_path": KNOWLEDGE_UPLOAD_ROOT_PATH,
             "vector_store_type": CFG.VECTOR_STORE_TYPE,
             "embeddings": embeddings,
@@ -190,6 +191,8 @@ class DBSummaryClient:
                 )
                 docs.extend(embedding.read_batch())
             embedding.index_to_store(docs)
+        else:
+            logger.info(f"Vector store name {vector_store_name} exist")
         logger.info("init db profile success...")
 
 

pilot/vector_store/chroma_store.py

@@ -2,6 +2,7 @@ import os
 from typing import Any
 
 from chromadb.config import Settings
+from chromadb import PersistentClient
 from pilot.logs import logger
 from pilot.vector_store.base import VectorStoreBase
 
@@ -18,15 +19,18 @@ class ChromaStore(VectorStoreBase):
             ctx["chroma_persist_path"], ctx["vector_store_name"] + ".vectordb"
         )
         chroma_settings = Settings(
-            chroma_db_impl="duckdb+parquet",
+            # chroma_db_impl="duckdb+parquet", => deprecated configuration of Chroma
             persist_directory=self.persist_dir,
             anonymized_telemetry=False,
         )
+        client = PersistentClient(path=self.persist_dir, settings=chroma_settings)
+
         collection_metadata = {"hnsw:space": "cosine"}
         self.vector_store_client = Chroma(
             persist_directory=self.persist_dir,
             embedding_function=self.embeddings,
-            client_settings=chroma_settings,
+            # client_settings=chroma_settings,
+            client=client,
             collection_metadata=collection_metadata,
         )
 
@@ -35,9 +39,13 @@ class ChromaStore(VectorStoreBase):
         return self.vector_store_client.similarity_search(text, topk)
 
     def vector_name_exists(self):
-        return (
-            os.path.exists(self.persist_dir) and len(os.listdir(self.persist_dir)) > 0
-        )
+        logger.info(f"Check persist_dir: {self.persist_dir}")
+        if not os.path.exists(self.persist_dir):
+            return False
+        files = os.listdir(self.persist_dir)
+        # Skip default file: chroma.sqlite3
+        files = list(filter(lambda f: f != "chroma.sqlite3", files))
+        return len(files) > 0
 
     def load_document(self, documents):
         logger.info("ChromaStore load document")

requirements.txt

@@ -1,84 +0,0 @@
-# torch==2.0.0
-aiohttp==3.8.4
-aiosignal==1.3.1
-async-timeout==4.0.2
-attrs==22.2.0
-cchardet==2.1.7
-chardet==5.1.0
-# contourpy==1.0.7
-# cycler==0.11.0
-filelock==3.9.0
-fonttools==4.38.0
-frozenlist==1.3.3
-huggingface-hub==0.14.1
-importlib-resources==5.12.0
-
-sqlparse==0.4.4
-# kiwisolver==1.4.4
-# matplotlib==3.7.1
-multidict==6.0.4
-packaging==23.0
-psutil==5.9.4
-# pycocotools==2.0.6
-# pyparsing==3.0.9
-python-dateutil==2.8.2
-pyyaml==6.0
-tokenizers==0.13.2
-tqdm==4.64.1
-transformers>=4.31.0
-transformers_stream_generator
-# timm==0.6.13
-spacy==3.5.3
-webdataset==0.2.48
-yarl==1.8.2
-zipp==3.14.0
-omegaconf==2.3.0
-opencv-python==4.7.0.72
-iopath==0.1.10
-tenacity==8.2.2
-peft
-# TODO remove pycocoevalcap
-pycocoevalcap
-cpm_kernels
-umap-learn
-# notebook
-gradio==3.23
-gradio-client==0.0.8
-# wandb
-# llama-index==0.5.27
-
-# TODO move bitsandbytes to optional
-# bitsandbytes
-accelerate>=0.20.3
-
-unstructured==0.6.3
-gpt4all==0.3.0
-diskcache==5.6.1
-seaborn
-auto-gpt-plugin-template
-pymdown-extensions
-gTTS==2.3.1
-langchain>=0.0.286
-nltk
-python-dotenv==1.0.0
-
-vcrpy
-chromadb==0.3.22
-markdown2
-colorama
-playsound
-distro
-pypdf
-weaviate-client
-bardapi==0.1.29
-
-# database
-
-# TODO moved to optional dependencies
-pymysql
-duckdb
-duckdb-engine
-
-# cli
-prettytable
-cachetools

requirements/dev-requirements.txt

@@ -1,4 +1,4 @@
-# Testing dependencies
+# Testing and dev dependencies
 pytest
 asynctest
 pytest-asyncio
@@ -7,4 +7,6 @@ pytest-cov
 pytest-integration
 pytest-mock
 pytest-recording
-pytesseract==0.3.10
+pytesseract==0.3.10
+# python code format
+black

setup.py

@@ -10,7 +10,6 @@ from urllib.parse import urlparse, quote
 import re
 from pip._internal.utils.appdirs import user_cache_dir
 import shutil
-import tempfile
 from setuptools import find_packages
 
 with open("README.md", mode="r", encoding="utf-8") as fh:
@@ -74,7 +73,6 @@ def cache_package(package_url: str, package_name: str, is_windows: bool = False)
 
     local_path = os.path.join(cache_dir, filename)
     if not os.path.exists(local_path):
-        # temp_file, temp_path = tempfile.mkstemp()
         temp_path = local_path + ".tmp"
         if os.path.exists(temp_path):
             os.remove(temp_path)
@@ -204,23 +202,16 @@ def torch_requires(
     torchvision_version: str = "0.15.1",
     torchaudio_version: str = "2.0.1",
 ):
-    torch_pkgs = []
+    torch_pkgs = [
+        f"torch=={torch_version}",
+        f"torchvision=={torchvision_version}",
+        f"torchaudio=={torchaudio_version}",
+    ]
+    torch_cuda_pkgs = []
     os_type, _ = get_cpu_avx_support()
-    if os_type == OSType.DARWIN:
-        torch_pkgs = [
-            f"torch=={torch_version}",
-            f"torchvision=={torchvision_version}",
-            f"torchaudio=={torchaudio_version}",
-        ]
-    else:
+    if os_type != OSType.DARWIN:
         cuda_version = get_cuda_version()
-        if not cuda_version:
-            torch_pkgs = [
-                f"torch=={torch_version}",
-                f"torchvision=={torchvision_version}",
-                f"torchaudio=={torchaudio_version}",
-            ]
-        else:
+        if cuda_version:
             supported_versions = ["11.7", "11.8"]
             if cuda_version not in supported_versions:
                 print(
@@ -238,12 +229,16 @@ def torch_requires(
             torchvision_url_cached = cache_package(
                 torchvision_url, "torchvision", os_type == OSType.WINDOWS
             )
-            torch_pkgs = [
+
+            torch_cuda_pkgs = [
                 f"torch @ {torch_url_cached}",
                 f"torchvision @ {torchvision_url_cached}",
                 f"torchaudio=={torchaudio_version}",
             ]
+
     setup_spec.extras["torch"] = torch_pkgs
+    setup_spec.extras["torch_cpu"] = torch_pkgs
+    setup_spec.extras["torch_cuda"] = torch_cuda_pkgs
 
 
 def llama_cpp_python_cuda_requires():
@@ -274,6 +269,57 @@ def llama_cpp_python_cuda_requires():
     setup_spec.extras["llama_cpp"].append(f"llama_cpp_python_cuda @ {extra_index_url}")
 
 
+def core_requires():
+    """
+    pip install db-gpt or pip install "db-gpt[core]"
+    """
+    setup_spec.extras["core"] = [
+        "aiohttp==3.8.4",
+        "chardet==5.1.0",
+        "importlib-resources==5.12.0",
+        "psutil==5.9.4",
+        "python-dotenv==1.0.0",
+        "colorama",
+        "prettytable",
+        "cachetools",
+    ]
+
+    setup_spec.extras["framework"] = [
+        "httpx",
+        "sqlparse==0.4.4",
+        "seaborn",
+        # https://github.com/eosphoros-ai/DB-GPT/issues/551
+        "pandas==2.0.3",
+        "auto-gpt-plugin-template",
+        "gTTS==2.3.1",
+        "langchain>=0.0.286",
+        "SQLAlchemy",
+        "pymysql",
+        "duckdb",
+        "duckdb-engine",
+        "jsonschema",
+        # TODO move transformers to default
+        "transformers>=4.31.0",
+    ]
+
+
+def knowledge_requires():
+    """
+    pip install "db-gpt[knowledge]"
+    """
+    setup_spec.extras["knowledge"] = [
+        "spacy==3.5.3",
+        # "chromadb==0.3.22",
+        "chromadb",
+        "markdown",
+        "bs4",
+        "python-pptx",
+        "python-docx",
+        "pypdf",
+        "python-multipart",
+    ]
+
+
 def llama_cpp_requires():
     """
     pip install "db-gpt[llama_cpp]"
@@ -309,6 +355,7 @@ def all_vector_store_requires():
     setup_spec.extras["vstore"] = [
         "grpcio==1.47.5",  # maybe delete it
         "pymilvus==2.2.1",
+        "weaviate-client",
     ]
 
 
@@ -324,6 +371,31 @@ def openai_requires():
     pip install "db-gpt[openai]"
     """
     setup_spec.extras["openai"] = ["openai", "tiktoken"]
+    setup_spec.extras["openai"] += setup_spec.extras["framework"]
+    setup_spec.extras["openai"] += setup_spec.extras["knowledge"]
+
+
+def gpt4all_requires():
+    """
+    pip install "db-gpt[gpt4all]"
+    """
+    setup_spec.extras["gpt4all"] = ["gpt4all"]
+
+
+def default_requires():
+    """
+    pip install "db-gpt[default]"
+    """
+    setup_spec.extras["default"] = [
+        "tokenizers==0.13.2",
+        "accelerate>=0.20.3",
+        "sentence-transformers",
+        "protobuf==3.20.3",
+    ]
+    setup_spec.extras["default"] += setup_spec.extras["framework"]
+    setup_spec.extras["default"] += setup_spec.extras["knowledge"]
+    setup_spec.extras["default"] += setup_spec.extras["torch"]
+    setup_spec.extras["default"] += setup_spec.extras["quantization"]
 
 
 def all_requires():
@@ -335,20 +407,23 @@ def all_requires():
 
 
 def init_install_requires():
-    setup_spec.install_requires += parse_requirements("requirements.txt")
-    setup_spec.install_requires += setup_spec.extras["torch"]
-    setup_spec.install_requires += setup_spec.extras["quantization"]
+    setup_spec.install_requires += setup_spec.extras["core"]
     print(f"Install requires: \n{','.join(setup_spec.install_requires)}")
 
 
+core_requires()
 torch_requires()
+knowledge_requires()
 llama_cpp_requires()
 quantization_requires()
+
 all_vector_store_requires()
 all_datasource_requires()
 openai_requires()
+gpt4all_requires()
 
 # must be last
+default_requires()
 all_requires()
 init_install_requires()