doc:update deploy doc

docs/conf.py

@@ -30,10 +30,24 @@ extensions = [
     "myst_nb",
     "sphinx_copybutton",
     "sphinx_panels",
+    "sphinx_tabs.tabs",
     "IPython.sphinxext.ipython_console_highlighting",
+    'sphinx.ext.autosectionlabel'
 ]
 source_suffix = [".ipynb", ".html", ".md", ".rst"]
 
+
+myst_enable_extensions = [
+    "dollarmath",
+    "amsmath",
+    "deflist",
+    "html_admonition",
+    "html_image",
+    "colon_fence",
+    "smartquotes",
+    "replacements",
+]
+
 # autodoc_pydantic_model_show_json = False
 # autodoc_pydantic_field_list_validators = False
 # autodoc_pydantic_config_members = False
@@ -56,5 +70,7 @@ gettext_uuid = True
 # -- Options for HTML output -------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
 
-html_theme = "furo"
+html_theme = "sphinx_book_theme"
+
+
 html_static_path = ["_static"]

docs/getting_started/install.rst

@@ -18,7 +18,7 @@ DB-GPT product is a Web application that you can chat database, chat knowledge,
    :name: deploy
    :hidden:
 
-   ./install/deploy/deploy.md
+   ./install/deploy.rst
    ./install/docker/docker.md
    ./install/docker_compose/docker_compose.md
    ./install/cluster/cluster.rst

docs/getting_started/install/deploy.rst

@@ -0,0 +1,438 @@
+.. _installation:
+
+Installation From Source
+==============
+
+To get started, install DB-GPT with the following steps.
+
+DB-GPT can be deployed on servers with low hardware requirements or on servers with high hardware requirements.
+You can install DB-GPT by Using third-part LLM REST API Service OpenAI, Azure.
+
+And you can also install DB-GPT by deploy LLM Service by download LLM model.
+
+
+1.Preparation
+-----------------
+**Download DB-GPT**
+
+.. code-block:: shell
+
+    git clone https://github.com/eosphoros-ai/DB-GPT.git
+
+**Install Miniconda**
+
+We use Sqlite as default database, so there is no need for database installation.  If you choose to connect to other databases, you can follow our tutorial for installation and configuration.
+For the entire installation process of DB-GPT, we use the miniconda3 virtual environment. Create a virtual environment and install the Python dependencies.
+:ref: `https://docs.conda.io/en/latest/miniconda.html<How to install Miniconda>`
+
+.. code-block:: shell
+
+    python>=3.10
+    conda create -n dbgpt_env python=3.10
+    conda activate dbgpt_env
+    # it will take some minutes
+    pip install -e ".[default]"
+
+.. code-block:: shell
+
+    cp .env.template .env
+
+2.Deploy LLM Service
+-----------------
+DB-GPT can be deployed on servers with low hardware requirements or on servers with high hardware requirements.
+
+If you are low hardware requirements you can install DB-GPT by Using third-part LLM REST API Service OpenAI, Azure, tongyi.
+
+.. tabs::
+
+    .. tab:: OpenAI
+
+        Download embedding model
+
+        .. code-block:: shell
+
+            cd DB-GPT
+            mkdir models and cd models
+
+            #### embedding model
+            git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
+            or
+            git clone https://huggingface.co/moka-ai/m3e-large
+
+        Configure LLM_MODEL and PROXY_API_URL and API_KEY in `.env` file
+
+        .. code-block:: shell
+
+            LLM_MODEL=chatgpt_proxyllm
+            PROXY_API_KEY={your-openai-sk}
+            PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
+
+        .. tip::
+
+            Make sure your .env configuration is not overwritten
+
+
+    .. tab:: Vicuna
+        ([Vicuna-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5) based on llama-2 has been released, we recommend you set `LLM_MODEL=vicuna-13b-v1.5` to try this model)
+
+        .. list-table:: vicuna-v1.5 hardware requirements
+            :widths: 50 50 50
+            :header-rows: 1
+
+            * - Model
+              - Quantize
+              - VRAM Size
+            * - vicuna-7b-v1.5
+              - 4-bit
+              - 8 GB
+            * - vicuna-7b-v1.5
+              - 8-bit
+              - 12 GB
+            * - vicuna-13b-v1.5
+              - 4-bit
+              - 12 GB
+            * - vicuna-13b-v1.5
+              - 8-bit
+              - 20 GB
+
+
+        .. note::
+
+          Notice make sure you have install git-lfs
+
+          centos:yum install git-lfs
+
+          ubuntu:apt-get install git-lfs
+
+          macos:brew install git-lfs
+
+
+        .. code-block:: shell
+
+            cd DB-GPT
+            mkdir models and cd models
+
+            #### embedding model
+            git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
+            or
+            git clone https://huggingface.co/moka-ai/m3e-large
+
+            #### llm model, if you use openai or Azure or tongyi llm api service, you don't need to download llm model
+            git clone https://huggingface.co/lmsys/vicuna-13b-v1.5
+
+        The model files are large and will take a long time to download.
+
+        **Configure LLM_MODEL in `.env` file**
+
+
+        .. code-block:: shell
+
+            LLM_MODEL=vicuna-13b-v1.5
+
+    .. tab:: Baichuan
+
+        .. list-table:: Baichuan hardware requirements
+            :widths: 50 50 50
+            :header-rows: 1
+
+            * - Model
+              - Quantize
+              - VRAM Size
+            * - baichuan-7b
+              - 4-bit
+              - 8 GB
+            * - baichuan-7b
+              - 8-bit
+              - 12 GB
+            * - baichuan-13b
+              - 4-bit
+              - 12 GB
+            * - baichuan-13b
+              - 8-bit
+              - 20 GB
+
+        .. note::
+
+          Notice make sure you have install git-lfs
+
+          centos:yum install git-lfs
+
+          ubuntu:apt-get install git-lfs
+
+          macos:brew install git-lfs
+
+
+        .. code-block:: shell
+
+            cd DB-GPT
+            mkdir models and cd models
+
+            #### embedding model
+            git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
+            or
+            git clone https://huggingface.co/moka-ai/m3e-large
+
+            #### llm model
+            git clone https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat
+            or
+            git clone https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat
+
+        The model files are large and will take a long time to download.
+
+        **Configure LLM_MODEL in `.env` file**
+
+        please rename Baichuan path to "baichuan2-13b" or "baichuan2-7b"
+
+        .. code-block:: shell
+
+            LLM_MODEL=baichuan2-13b
+
+    .. tab:: ChatGLM
+
+        .. note::
+
+          Notice make sure you have install git-lfs
+
+          centos:yum install git-lfs
+
+          ubuntu:apt-get install git-lfs
+
+          macos:brew install git-lfs
+
+
+        .. code-block:: shell
+
+            cd DB-GPT
+            mkdir models and cd models
+
+            #### embedding model
+            git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
+            or
+            git clone https://huggingface.co/moka-ai/m3e-large
+
+            #### llm model
+            git clone https://huggingface.co/THUDM/chatglm2-6b
+
+        The model files are large and will take a long time to download.
+
+        **Configure LLM_MODEL in `.env` file**
+
+        please rename chatglm model path to "chatglm2-6b"
+
+        .. code-block:: shell
+
+            LLM_MODEL=chatglm2-6b
+
+    .. tab:: Other LLM API
+
+        Download embedding model
+
+        .. code-block:: shell
+
+            cd DB-GPT
+            mkdir models and cd models
+
+            #### embedding model
+            git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
+            or
+            git clone https://huggingface.co/moka-ai/m3e-large
+
+        .. note::
+
+            * OpenAI
+            * Azure
+            * Aliyun tongyi
+            * Baidu wenxin
+            * Zhipu
+            * Baichuan
+            * Bard
+
+        Configure LLM_MODEL and PROXY_API_URL and API_KEY in `.env` file
+
+        .. code-block:: shell
+
+            #OpenAI
+            LLM_MODEL=chatgpt_proxyllm
+            PROXY_API_KEY={your-openai-sk}
+            PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
+
+            #Azure
+            LLM_MODEL=chatgpt_proxyllm
+            PROXY_API_KEY={your-azure-sk}
+            PROXY_API_BASE=https://{your domain}.openai.azure.com/
+            PROXY_API_TYPE=azure
+            PROXY_SERVER_URL=xxxx
+            PROXY_API_VERSION=2023-05-15
+            PROXYLLM_BACKEND=gpt-35-turbo
+
+            #Aliyun tongyi
+            LLM_MODEL=tongyi_proxyllm
+            TONGYI_PROXY_API_KEY={your-tongyi-sk}
+            PROXY_SERVER_URL={your_service_url}
+
+            ## Baidu wenxin
+            LLM_MODEL=wenxin_proxyllm
+            PROXY_SERVER_URL={your_service_url}
+            WEN_XIN_MODEL_VERSION={version}
+            WEN_XIN_API_KEY={your-wenxin-sk}
+            WEN_XIN_SECRET_KEY={your-wenxin-sct}
+
+            ## Zhipu
+            LLM_MODEL=zhipu_proxyllm
+            PROXY_SERVER_URL={your_service_url}
+            ZHIPU_MODEL_VERSION={version}
+            ZHIPU_PROXY_API_KEY={your-zhipu-sk}
+
+            ## Baichuan
+            LLM_MODEL=bc_proxyllm
+            PROXY_SERVER_URL={your_service_url}
+            BAICHUN_MODEL_NAME={version}
+            BAICHUAN_PROXY_API_KEY={your-baichuan-sk}
+            BAICHUAN_PROXY_API_SECRET={your-baichuan-sct}
+
+            ## bard
+            LLM_MODEL=bard_proxyllm
+            PROXY_SERVER_URL={your_service_url}
+            # from https://bard.google.com/     f12-> application-> __Secure-1PSID
+            BARD_PROXY_API_KEY={your-bard-token}
+
+        .. tip::
+
+            Make sure your .env configuration is not overwritten
+
+    .. tab:: llama.cpp
+
+        DB-GPT already supports [llama.cpp](https://github.com/ggerganov/llama.cpp) via [llama-cpp-python](https://github.com/abetlen/llama-cpp-python).
+
+        **Preparing Model Files**
+
+        To use llama.cpp, you need to prepare a gguf format model file, and there are two common ways to obtain it, you can choose either:
+
+        **1. Download a pre-converted model file.**
+
+        Suppose you want to use [Vicuna 13B v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5), you can download the file already converted from [TheBloke/vicuna-13B-v1.5-GGUF](https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF), only one file is needed. Download it to the `models` directory and rename it to `ggml-model-q4_0.gguf`.
+
+        .. code-block::
+
+          wget https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF/resolve/main/vicuna-13b-v1.5.Q4_K_M.gguf -O models/ggml-model-q4_0.gguf
+
+        **2. Convert It Yourself**
+
+        You can convert the model file yourself according to the instructions in [llama.cpp#prepare-data--run](https://github.com/ggerganov/llama.cpp#prepare-data--run), and put the converted file in the models directory and rename it to `ggml-model-q4_0.gguf`.
+
+        **Installing Dependencies**
+
+        llama.cpp is an optional dependency in DB-GPT, and you can manually install it using the following command:
+
+        .. code-block::
+
+            pip install -e ".[llama_cpp]"
+
+
+        **3.Modifying the Configuration File**
+
+        Next, you can directly modify your `.env` file to enable llama.cpp.
+
+        .. code-block::
+
+            LLM_MODEL=llama-cpp
+            llama_cpp_prompt_template=vicuna_v1.1
+
+        Then you can run it according to [Run](https://db-gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html#run).
+
+
+        **More Configurations**
+
+        In DB-GPT, the model configuration can be done through  `{model name}_{config key}`.
+
+        .. list-table:: More Configurations
+            :widths: 50 50 50
+            :header-rows: 1
+
+            * - Environment Variable Key
+              - Default
+              - Description
+            * - llama_cpp_prompt_template
+              - None
+              - Prompt template name, now support: zero_shot, vicuna_v1.1,alpaca,llama-2,baichuan-chat,internlm-chat, If None, the prompt template is automatically determined from model path。
+            * - llama_cpp_model_path
+              - None
+              - Model path
+            * - llama_cpp_n_gpu_layers
+              - 1000000000
+              - Number of layers to offload to the GPU, Set this to 1000000000 to offload all layers to the GPU. If your GPU VRAM is not enough, you can set a low number, eg: 10
+            * - llama_cpp_n_threads
+              - None
+              - Number of threads to use. If None, the number of threads is automatically determined
+            * - llama_cpp_n_batch
+              - 512
+              - Maximum number of prompt tokens to batch together when calling llama_eval
+            * - llama_cpp_n_gqa
+              - None
+              - Grouped-query attention. Must be 8 for llama-2 70b.
+            * - llama_cpp_rms_norm_eps
+              - 5e-06
+              - 5e-6 is a good value for llama-2 models.
+            * - llama_cpp_cache_capacity
+              - None
+              - Maximum cache capacity. Examples: 2000MiB, 2GiB
+            * - llama_cpp_prefer_cpu
+              - False
+              - If a GPU is available, it will be preferred by default, unless prefer_cpu=False is configured.
+
+
+    .. tab:: vllm
+
+        vLLM is a fast and easy-to-use library for LLM inference and serving.
+
+        **Running vLLM**
+
+        **1.Installing Dependencies**
+
+        vLLM is an optional dependency in DB-GPT, and you can manually install it using the following command:
+
+        .. code-block::
+
+          pip install -e ".[vllm]"
+
+        **2.Modifying the Configuration File**
+
+        Next, you can directly modify your .env file to enable vllm.
+
+        .. code-block::
+
+            LLM_MODEL=vicuna-13b-v1.5
+            MODEL_TYPE=vllm
+
+
+
+
+
+
+
+
+3.Prepare sql example(Optional)
+-----------------
+**(Optional) load examples into SQLite**
+
+        .. code-block:: shell
+
+            bash ./scripts/examples/load_examples.sh
+
+
+        On windows platform:
+
+        .. code-block:: shell
+
+            .\scripts\examples\load_examples.bat
+
+4.Run db-gpt server
+-----------------
+
+        .. code-block:: shell
+
+
+            python pilot/server/dbgpt_server.py
+
+**Open http://localhost:5000 with your browser to see the product.**
+

docs/locales/zh_CN/LC_MESSAGES/getting_started/install/environment/environment.po

@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: DB-GPT 👏👏 0.3.5\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2023-08-17 13:07+0800\n"
+"POT-Creation-Date: 2023-11-02 10:10+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language: zh_CN\n"
@@ -20,290 +20,292 @@ msgstr ""
 "Generated-By: Babel 2.12.1\n"
 
 #: ../../getting_started/install/environment/environment.md:1
-#: be341d16f7b24bf4ad123ab78a6d855a
+#: 28d2f84fc8884e78afad8118cd59c654
 #, fuzzy
 msgid "Environment Parameter"
 msgstr "环境变量说明"
 
 #: ../../getting_started/install/environment/environment.md:4
-#: 46eddb27c90f41548ea9a724bbcebd37
+#: c83fbb5e1aa643cdb09fffe7f3d1a3c5
 msgid "LLM MODEL Config"
 msgstr "模型配置"
 
 #: ../../getting_started/install/environment/environment.md:5
-#: 7deaa85df4a04fb098f5994547a8724f
+#: eb675965ae57407e8d8bf90fed8e9e2a
 msgid "LLM Model Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG"
 msgstr "LLM Model Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG"
 
 #: ../../getting_started/install/environment/environment.md:6
-#: 3902801c546547b3a4009df681ef7d52
+#: 5d28d35126d849ea9b0d963fd1ba8699
 msgid "LLM_MODEL=vicuna-13b"
 msgstr "LLM_MODEL=vicuna-13b"
 
 #: ../../getting_started/install/environment/environment.md:8
-#: 84b0fdbfa1544ec28751e9b69b00cc02
+#: 01955b2d0fbe4d94939ebf2cbb380bdd
 msgid "MODEL_SERVER_ADDRESS"
 msgstr "MODEL_SERVER_ADDRESS"
 
 #: ../../getting_started/install/environment/environment.md:9
-#: 0b430bfab77d405989470d00ca3f6fe0
+#: 4eaaa9ab59854c0386b28b3111c82784
 msgid "MODEL_SERVER=http://127.0.0.1:8000  LIMIT_MODEL_CONCURRENCY"
 msgstr "MODEL_SERVER=http://127.0.0.1:8000  LIMIT_MODEL_CONCURRENCY"
 
 #: ../../getting_started/install/environment/environment.md:12
-#: b477a25586c546729a93fb6785b7b2ec
+#: 5c2dd05e16834443b7451c2541b59757
 msgid "LIMIT_MODEL_CONCURRENCY=5"
 msgstr "LIMIT_MODEL_CONCURRENCY=5"
 
 #: ../../getting_started/install/environment/environment.md:14
-#: 1d6ea800af384fff9c265610f71cc94e
+#: 7707836c2fb04e7da13d2d59b5f9566f
 msgid "MAX_POSITION_EMBEDDINGS"
 msgstr "MAX_POSITION_EMBEDDINGS"
 
 #: ../../getting_started/install/environment/environment.md:16
-#: 388e758ce4ea4692a4c34294cebce7f2
+#: ee24a7d3d8384e61b715ef3bd362b965
 msgid "MAX_POSITION_EMBEDDINGS=4096"
 msgstr "MAX_POSITION_EMBEDDINGS=4096"
 
 #: ../../getting_started/install/environment/environment.md:18
-#: 16a307dce1294ceba892ff93ae4e81c0
+#: 90b51aa4e46b4d1298c672e0052c2f68
 msgid "QUANTIZE_QLORA"
 msgstr "QUANTIZE_QLORA"
 
 #: ../../getting_started/install/environment/environment.md:20
-#: 93ceb2b2fcd5454b82eefb0ae8c7ae77
+#: 7de7a8eb431e4973ae00f68ca0686281
 msgid "QUANTIZE_QLORA=True"
 msgstr "QUANTIZE_QLORA=True"
 
 #: ../../getting_started/install/environment/environment.md:22
-#: 15ffa35d023a4530b02a85ee6168dd4b
+#: e331ca016a474f4aa4e9182165a2693a
 msgid "QUANTIZE_8bit"
 msgstr "QUANTIZE_8bit"
 
 #: ../../getting_started/install/environment/environment.md:24
-#: 81df248ac5cb4ab0b13a711505f6a177
+#: 519ccce5a0884778be2719c437a17bd4
 msgid "QUANTIZE_8bit=True"
 msgstr "QUANTIZE_8bit=True"
 
 #: ../../getting_started/install/environment/environment.md:27
-#: 15cc7b7d41ad44f0891c1189709f00f1
+#: 1c0586d070f046de8d0f9f94a6b508b4
 msgid "LLM PROXY Settings"
 msgstr "LLM PROXY Settings"
 
 #: ../../getting_started/install/environment/environment.md:28
-#: e6c1115a39404f11b193a1593bc51a22
+#: c208c3f4b13f4b39962de814e5be6ab9
 msgid "OPENAI Key"
 msgstr "OPENAI Key"
 
 #: ../../getting_started/install/environment/environment.md:30
-#: 8157e0a831fe4506a426822b7565e4f6
+#: 9228bbee2faa4467b1d24f1125faaac8
 msgid "PROXY_API_KEY={your-openai-sk}"
 msgstr "PROXY_API_KEY={your-openai-sk}"
 
 #: ../../getting_started/install/environment/environment.md:31
-#: 89b34d00bdb64e738bd9bc8c086b1f02
+#: 759ae581883348019c1ba79e8954728a
 msgid "PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions"
 msgstr "PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions"
 
 #: ../../getting_started/install/environment/environment.md:33
-#: 7a97df730aeb484daf19c8172e61a290
+#: 83f3952917d34aab80bd34119f7d1e20
 msgid "from https://bard.google.com/     f12-> application-> __Secure-1PSID"
 msgstr "from https://bard.google.com/     f12-> application-> __Secure-1PSID"
 
 #: ../../getting_started/install/environment/environment.md:35
-#: d430ddf726a049c0a9e0a9bfd5a6fe0e
+#: 1d70707ca82749bb90b2bed1aee44d62
 msgid "BARD_PROXY_API_KEY={your-bard-token}"
 msgstr "BARD_PROXY_API_KEY={your-bard-token}"
 
 #: ../../getting_started/install/environment/environment.md:38
-#: 23d6b0da3e7042abb55f6181c4a382d2
+#: 38a2091fa223493ea23cb9bbb33cf58e
 msgid "DATABASE SETTINGS"
 msgstr "DATABASE SETTINGS"
 
 #: ../../getting_started/install/environment/environment.md:39
-#: dbae0a2d847f41f5be9396a160ef88d0
+#: 5134180d7a5945b48b072a1eb92b27ba
 msgid "SQLite database (Current default database)"
 msgstr "SQLite database (Current default database)"
 
 #: ../../getting_started/install/environment/environment.md:40
-#: bdb55b7280c341a981e9d338cce53345
+#: 6875e2300e094668a45fa4f2551e0d30
 msgid "LOCAL_DB_PATH=data/default_sqlite.db"
 msgstr "LOCAL_DB_PATH=data/default_sqlite.db"
 
 #: ../../getting_started/install/environment/environment.md:41
-#: 739d67927a9d46b28500deba1917916b
+#: 034e8f06f24f44af9d8184563f99b4b3
 msgid "LOCAL_DB_TYPE=sqlite # Database Type default:sqlite"
 msgstr "LOCAL_DB_TYPE=sqlite # Database Type default:sqlite"
 
 #: ../../getting_started/install/environment/environment.md:43
-#: eb4717bce6a6483b86d9780d924c5ff1
+#: f688149a97f740269f80b79775236ce9
 msgid "MYSQL database"
 msgstr "MYSQL database"
 
 #: ../../getting_started/install/environment/environment.md:44
-#: 0f4cdf0ff5dd4ff0b397dfa88541a2e1
+#: 6db0b305137d45a3aa036e4f2262f460
 msgid "LOCAL_DB_TYPE=mysql"
 msgstr "LOCAL_DB_TYPE=mysql"
 
 #: ../../getting_started/install/environment/environment.md:45
-#: c971ead492c34487bd766300730a9cba
+#: b6d662ce8d5f44f0b54a7f6e7c66f5a5
 msgid "LOCAL_DB_USER=root"
 msgstr "LOCAL_DB_USER=root"
 
 #: ../../getting_started/install/environment/environment.md:46
-#: 02828b29ad044eeab890a2f8af0e5907
+#: cd7493d61ac9415283640dc6c018d2f4
 msgid "LOCAL_DB_PASSWORD=aa12345678"
 msgstr "LOCAL_DB_PASSWORD=aa12345678"
 
 #: ../../getting_started/install/environment/environment.md:47
-#: 53dc7f15b3934987b1f4c2e2d0b11299
+#: 4ea2a622b23f4342a4c2ab7f8d9c4e8d
 msgid "LOCAL_DB_HOST=127.0.0.1"
 msgstr "LOCAL_DB_HOST=127.0.0.1"
 
 #: ../../getting_started/install/environment/environment.md:48
-#: 1ac95fc482934247a118bab8dcebeb57
+#: 936db95a0ab246098028f4dbb596cd17
 msgid "LOCAL_DB_PORT=3306"
 msgstr "LOCAL_DB_PORT=3306"
 
 #: ../../getting_started/install/environment/environment.md:51
-#: 34e46aa926844be19c7196759b03af63
+#: d9255f25989840ea9c9e7b34f3947c87
 msgid "EMBEDDING SETTINGS"
 msgstr "EMBEDDING SETTINGS"
 
 #: ../../getting_started/install/environment/environment.md:52
-#: 2b5aa08cc995495e85a1f7dc4f97b5d7
+#: b09291d32aca43928a981e873476a985
 msgid "EMBEDDING MODEL Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG"
 msgstr "EMBEDDING模型, 参考see /pilot/configs/model_config.LLM_MODEL_CONFIG"
 
 #: ../../getting_started/install/environment/environment.md:53
-#: 0de0ca551ed040248406f848feca541d
+#: 63de573b03a54413b997f18a1ccee279
 msgid "EMBEDDING_MODEL=text2vec"
 msgstr "EMBEDDING_MODEL=text2vec"
 
 #: ../../getting_started/install/environment/environment.md:55
-#: 43019fb570904c9981eb68f33e64569c
+#: 0ef8defbab544bd0b9475a036f278489
 msgid "Embedding Chunk size, default 500"
 msgstr "Embedding 切片大小, 默认500"
 
 #: ../../getting_started/install/environment/environment.md:57
-#: 7e3f93854873461286e96887e04167aa
+#: 33dbc7941d054baa8c6ecfc0bf1ce271
 msgid "KNOWLEDGE_CHUNK_SIZE=500"
 msgstr "KNOWLEDGE_CHUNK_SIZE=500"
 
 #: ../../getting_started/install/environment/environment.md:59
-#: 9504f4a59ae74352a524b7741113e2d6
+#: e6ee9f2620ab45ecbc8e9c0642f5ca42
 msgid "Embedding Chunk Overlap, default 100"
 msgstr "Embedding chunk Overlap, 文本块之间的最大重叠量。保留一些重叠可以保持文本块之间的连续性（例如使用滑动窗口）,默认100"
 
 #: ../../getting_started/install/environment/environment.md:60
-#: 24e6119c2051479bbd9dba71a9c23dbe
+#: fcddf64340a04df4ab95176fc2fc67a6
 msgid "KNOWLEDGE_CHUNK_OVERLAP=100"
 msgstr "KNOWLEDGE_CHUNK_OVERLAP=100"
 
 #: ../../getting_started/install/environment/environment.md:62
-#: 0d180d7f2230442abee901c19526e442
+#: 61272200194b4461a921581feb1273da
-msgid "embeding recall top k,5"
+#, fuzzy
+msgid "embedding recall top k,5"
 msgstr "embedding 召回topk, 默认5"
 
 #: ../../getting_started/install/environment/environment.md:64
-#: a5bb9ab2ba50411cbbe87f7836bfbb6d
+#: b433091f055542b1b89ff2d525ac99e4
 msgid "KNOWLEDGE_SEARCH_TOP_SIZE=5"
 msgstr "KNOWLEDGE_SEARCH_TOP_SIZE=5"
 
 #: ../../getting_started/install/environment/environment.md:66
-#: 183b8dd78cba4ae19bd2e08d69d21e0b
+#: 1db0de41aebd4caa8cc2eaecb4cacd6a
-msgid "embeding recall max token ,2000"
+#, fuzzy
+msgid "embedding recall max token ,2000"
 msgstr "embedding向量召回最大token, 默认2000"
 
 #: ../../getting_started/install/environment/environment.md:68
-#: ce0c711febcb44c18ae0fc858c3718d1
+#: 81b9d862e58941a4b09680a7520cdabe
 msgid "KNOWLEDGE_SEARCH_MAX_TOKEN=5"
 msgstr "KNOWLEDGE_SEARCH_MAX_TOKEN=5"
 
 #: ../../getting_started/install/environment/environment.md:71
 #: ../../getting_started/install/environment/environment.md:87
-#: 4cab1f399cc245b4a1a1976d2c4fc926 ec9cec667a1c4473bf9a796a26e1ce20
+#: cac73575d54544778bdee09b18532fd9 f78a509949a64f03aa330f31901e2e7a
 msgid "Vector Store SETTINGS"
 msgstr "Vector Store SETTINGS"
 
 #: ../../getting_started/install/environment/environment.md:72
 #: ../../getting_started/install/environment/environment.md:88
-#: 4dd04aadd46948a5b1dcf01fdb0ef074 bab7d512f33e40cf9e10f0da67e699c8
+#: 5ebba1cb047b4b09849000244237dfbb 7e9285e91bcb4b2d9413909c0d0a06a7
 msgid "Chroma"
 msgstr "Chroma"
 
 #: ../../getting_started/install/environment/environment.md:73
 #: ../../getting_started/install/environment/environment.md:89
-#: 13eec36741b14e028e2d3859a320826e ab3ffbcf9358401993af636ba9ab2e2d
+#: 05625cfcc23c4745ae1fa0d94ce5450c 3a8615f1507f4fc49d1adda5100a4edf
 msgid "VECTOR_STORE_TYPE=Chroma"
 msgstr "VECTOR_STORE_TYPE=Chroma"
 
 #: ../../getting_started/install/environment/environment.md:74
 #: ../../getting_started/install/environment/environment.md:90
-#: d15b91e2a2884f23a1dd2d54783b0638 d1f856d571b547098bb0c2a18f9f1979
+#: 5b559376aea44f159262e6d4b75c7ec1 e954782861404b10b4e893e01cf74452
 msgid "MILVUS"
 msgstr "MILVUS"
 
 #: ../../getting_started/install/environment/environment.md:75
 #: ../../getting_started/install/environment/environment.md:91
-#: 1e165f6c934343c7808459cc7a65bc70 985dd60c2b7d4baaa6601a810a6522d7
+#: 55ee8199c97a4929aeefd32370f2b92d 8f40c02543ea4a2ca9632dd9e8a08c2e
 msgid "VECTOR_STORE_TYPE=Milvus"
 msgstr "VECTOR_STORE_TYPE=Milvus"
 
 #: ../../getting_started/install/environment/environment.md:76
 #: ../../getting_started/install/environment/environment.md:92
-#: a1a53f051cee40ed886346a94babd75a d263e8eaee684935a58f0a4fe61c6f0e
+#: 528a01d25720491c8e086bf43a62ad92 ba1386d551d7494a85681a2803081a6f
 msgid "MILVUS_URL=127.0.0.1"
 msgstr "MILVUS_URL=127.0.0.1"
 
 #: ../../getting_started/install/environment/environment.md:77
 #: ../../getting_started/install/environment/environment.md:93
-#: 2741a312db1a4c6a8a1c1d62415c5fba d03bbf921ddd4f4bb715fe5610c3d0aa
+#: b031950dafcd4d4783c120dc933c4178 c2e9c8cdd41741e3aba01e59a6ef245d
 msgid "MILVUS_PORT=19530"
 msgstr "MILVUS_PORT=19530"
 
 #: ../../getting_started/install/environment/environment.md:78
 #: ../../getting_started/install/environment/environment.md:94
-#: d0786490d38c4e4f971cc14f62fe1fc8 e9e0854873dc4c209861ee4eb77d25cd
+#: 27b0a64af6434cb2840373e2b38c9bd5 d0e4d79af7954b129ffff7303a1ec3ce
 msgid "MILVUS_USERNAME"
 msgstr "MILVUS_USERNAME"
 
 #: ../../getting_started/install/environment/environment.md:79
 #: ../../getting_started/install/environment/environment.md:95
-#: 9a82d07153cc432ebe754b5bc02fde0d a6485c1cfa7d4069a6894c43674c8c2b
+#: 27aa1a5b61e64dd6bfe29124e274809e 5c58892498ce4f46a59f54b2887822d4
 msgid "MILVUS_PASSWORD"
 msgstr "MILVUS_PASSWORD"
 
 #: ../../getting_started/install/environment/environment.md:80
 #: ../../getting_started/install/environment/environment.md:96
-#: 2f233f32b8ba408a9fbadb21fabb99ec 809b3219dd824485bc2cfc898530d708
+#: 009e57d4acc5434da2146f0545911c85 bac8888dcbff47fbb0ea8ae685445aac
 msgid "MILVUS_SECURE="
 msgstr "MILVUS_SECURE="
 
 #: ../../getting_started/install/environment/environment.md:82
 #: ../../getting_started/install/environment/environment.md:98
-#: f00603661f2b42e1bd2bca74ad1e3c31 f378e16fdec44c559e34c6929de812e8
+#: a6eeb16ab5274045bee88ecc3d93e09e eb341774403d47658b9b7e94c4c16d5c
 msgid "WEAVIATE"
 msgstr "WEAVIATE"
 
 #: ../../getting_started/install/environment/environment.md:83
-#: da2049ebc6874cf0a6b562e0e2fd9ec7
+#: fbd97522d8da4824b41b99298fd41069
 msgid "VECTOR_STORE_TYPE=Weaviate"
 msgstr "VECTOR_STORE_TYPE=Weaviate"
 
 #: ../../getting_started/install/environment/environment.md:84
 #: ../../getting_started/install/environment/environment.md:99
-#: 25f1246629934289aad7ef01c7304097 c9fe0e413d9a4fc8abf86b3ed99e0581
+#: 341785b4abfe42b5af1c2e04497261f4 a81cc2aabc8240f3ac1f674d9350bff4
 msgid "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network"
 msgstr "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network"
 
 #: ../../getting_started/install/environment/environment.md:102
-#: ba7c9e707f6a4cd6b99e52b58da3ab2d
+#: 5bb9e5daa36241d499089c1b1910f729
 msgid "Multi-GPU Setting"
 msgstr "Multi-GPU Setting"
 
 #: ../../getting_started/install/environment/environment.md:103
-#: 5ca75fdf2c264b2c844d77f659b4f0b3
+#: 30df45b7f1f7423c9f18c6360f0b7600
 msgid ""
 "See https://developer.nvidia.com/blog/cuda-pro-tip-control-gpu-"
 "visibility-cuda_visible_devices/ If CUDA_VISIBLE_DEVICES is not "
@@ -313,49 +315,49 @@ msgstr ""
 "cuda_visible_devices/ 如果 CUDA_VISIBLE_DEVICES没有设置, 会使用所有可用的gpu"
 
 #: ../../getting_started/install/environment/environment.md:106
-#: de92eb310aff43fbbbf3c5a116c3b2c6
+#: 8631ea968dfb4d90a7ae6bdb2acdfdce
 msgid "CUDA_VISIBLE_DEVICES=0"
 msgstr "CUDA_VISIBLE_DEVICES=0"
 
 #: ../../getting_started/install/environment/environment.md:108
-#: d2641df6123a442b8e4444ad5f01a9aa
+#: 0010422280dd4fe79326ebceb2a66f0e
 msgid ""
 "Optionally, you can also specify the gpu ID to use before the starting "
 "command"
 msgstr "你也可以通过启动命令设置gpu ID"
 
 #: ../../getting_started/install/environment/environment.md:110
-#: 76c66179d11a4e5fa369421378609aae
+#: 00106f7341304fbd9425721ea8e6a261
 msgid "CUDA_VISIBLE_DEVICES=3,4,5,6"
 msgstr "CUDA_VISIBLE_DEVICES=3,4,5,6"
 
 #: ../../getting_started/install/environment/environment.md:112
-#: 29bd0f01fdf540ad98385ea8473f7647
+#: 720aa8b3478744d78e4b10dfeccb50b4
 msgid "You can configure the maximum memory used by each GPU."
 msgstr "可以设置GPU的最大内存"
 
 #: ../../getting_started/install/environment/environment.md:114
-#: 31e5e23838734ba7a2810e2387e6d6a0
+#: f9639ac96a244296832c75bbcbdae2af
 msgid "MAX_GPU_MEMORY=16Gib"
 msgstr "MAX_GPU_MEMORY=16Gib"
 
 #: ../../getting_started/install/environment/environment.md:117
-#: 99aa63ab1ae049d9b94536d6a96f3443
+#: fc4d955fdb3e4256af5c8f29b042dcd6
 msgid "Other Setting"
 msgstr "Other Setting"
 
 #: ../../getting_started/install/environment/environment.md:118
-#: 3168732183874bffb59a3575d3473d62
+#: 66b14a834e884339be2d48392e884933
 msgid "Language Settings(influence prompt language)"
 msgstr "Language Settings(涉及prompt语言以及知识切片方式)"
 
 #: ../../getting_started/install/environment/environment.md:119
-#: 73eb0a96f29b4739bd456faa9cb5033d
+#: 5c9f05174eb84edd9e1316cc0721a840
 msgid "LANGUAGE=en"
 msgstr "LANGUAGE=en"
 
 #: ../../getting_started/install/environment/environment.md:120
-#: c6646b78c6cf4d25a13108232f5b2046
+#: 7f6d62117d024c51bba9255fa4fcf151
 msgid "LANGUAGE=zh"
 msgstr "LANGUAGE=zh"
 

docs/locales/zh_CN/LC_MESSAGES/modules/knowledge.po

@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: DB-GPT 0.3.0\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2023-07-13 15:39+0800\n"
+"POT-Creation-Date: 2023-11-02 10:10+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language: zh_CN\n"
@@ -19,103 +19,84 @@ msgstr ""
 "Content-Transfer-Encoding: 8bit\n"
 "Generated-By: Babel 2.12.1\n"
 
-#: ../../modules/knowledge.rst:2 ../../modules/knowledge.rst:136
+#: ../../modules/knowledge.md:1 436b94d3a8374ed18feb5c14893a84e6
-#: 3cc8fa6e9fbd4d889603d99424e9529a
 msgid "Knowledge"
 msgstr "知识"
 
-#: ../../modules/knowledge.rst:4 0465a393d9d541958c39c1d07c885d1f
+#: ../../modules/knowledge.md:3 918a3747cbed42d18b8c9c4547e67b14
 #, fuzzy
 msgid ""
 "As the knowledge base is currently the most significant user demand "
 "scenario, we natively support the construction and processing of "
 "knowledge bases. At the same time, we also provide multiple knowledge "
-"base management strategies in this project, such as pdf knowledge,md "
+"base management strategies in this project, such as:"
-"knowledge, txt knowledge, word knowledge, ppt knowledge:"
 msgstr ""
 "由于知识库是当前用户需求最显著的场景，我们原生支持知识库的构建和处理。同时，我们还在本项目中提供了多种知识库管理策略，如:pdf,md , "
 "txt, word, ppt"
 
-#: ../../modules/knowledge.rst:6 e670cbe14d8e4da88ba935e4120c31e0
+#: ../../modules/knowledge.md:4 d4d4b5d57918485aafa457bb9fdcf626
-msgid ""
+msgid "Default built-in knowledge base"
-"We currently support many document formats: raw text, txt, pdf, md, html,"
-" doc, ppt, and url. In the future, we will continue to support more types"
-" of knowledge, including audio, video, various databases, and big data "
-"sources. Of course, we look forward to your active participation in "
-"contributing code."
 msgstr ""
 
-#: ../../modules/knowledge.rst:9 e0bf601a1a0c458297306db6ff79f931
+#: ../../modules/knowledge.md:5 d4d4b5d57918485aafa457bb9fdcf626
-msgid "**Create your own knowledge repository**"
+msgid "Custom addition of knowledge bases"
+msgstr ""
+
+#: ../../modules/knowledge.md:6 984361ce835c4c3492e29e1fb897348a
+msgid ""
+"Various usage scenarios such as constructing knowledge bases through "
+"plugin capabilities and web crawling. Users only need to organize the "
+"knowledge documents, and they can use our existing capabilities to build "
+"the knowledge base required for the large model."
+msgstr ""
+
+#: ../../modules/knowledge.md:9 746e4fbd3212460198be51b90caee2c8
+#, fuzzy
+msgid "Create your own knowledge repository"
 msgstr "创建你自己的知识库"
 
-#: ../../modules/knowledge.rst:11 bb26708135d44615be3c1824668010f6
+#: ../../modules/knowledge.md:11 1c46b33b0532417c824efbaa3e687c3f
-msgid "1.prepare"
+msgid ""
-msgstr "准备"
+"1.Place personal knowledge files or folders in the pilot/datasets "
+"directory."
+msgstr ""
 
-#: ../../modules/knowledge.rst:13 c150a0378f3e4625908fa0d8a25860e9
+#: ../../modules/knowledge.md:13 3b16f387b5354947a89d6df77bd65bdb
 #, fuzzy
 msgid ""
-"We currently support many document formats: TEXT(raw text), "
+"We currently support many document formats: txt, pdf, md, html, doc, ppt,"
-"DOCUMENT(.txt, .pdf, .md, .doc, .ppt, .html), and URL."
+" and url."
 msgstr "当前支持txt, pdf, md, html, doc, ppt, url文档格式"
 
-#: ../../modules/knowledge.rst:15 7f9f02a93d5d4325b3d2d976f4bb28a0
+#: ../../modules/knowledge.md:15 09ec337d7da4418db854e58afb6c0980
 msgid "before execution:"
 msgstr "开始前"
 
-#: ../../modules/knowledge.rst:24 59699a8385e04982a992cf0d71f6dcd5
+#: ../../modules/knowledge.md:22 c09b3decb018485f8e56830ddc156194
-#, fuzzy
 msgid ""
-"2.prepare embedding model, you can download from https://huggingface.co/."
+"2.Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma "
-" Notice you have installed git-lfs."
+"(now only support Chroma and Milvus, if you set Milvus, please set "
+"MILVUS_URL and MILVUS_PORT)"
 msgstr ""
-"提前准备Embedding Model, 你可以在https://huggingface.co/进行下载，注意：你需要先安装git-lfs.eg:"
-" git clone https://huggingface.co/THUDM/chatglm2-6b"
 
-#: ../../modules/knowledge.rst:27 2be1a17d0b54476b9dea080d244fd747
+#: ../../modules/knowledge.md:25 74460ec7709441d5945ce9f745a26d20
-msgid ""
+msgid "2.Run the knowledge repository initialization command"
-"eg: git clone https://huggingface.co/sentence-transformers/all-"
-"MiniLM-L6-v2"
-msgstr "eg: git clone https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2"
-
-#: ../../modules/knowledge.rst:33 d328f6e243624c9488ebd27c9324621b
-msgid ""
-"3.prepare vector_store instance and vector store config, now we support "
-"Chroma, Milvus and Weaviate."
-msgstr "提前准备向量数据库环境，目前支持Chroma, Milvus and Weaviate向量数据库"
-
-#: ../../modules/knowledge.rst:63 44f97154eff647d399fd30b6f9e3b867
-msgid ""
-"3.init Url Type EmbeddingEngine api and embedding your document into "
-"vector store in your code."
-msgstr "初始化 Url类型 EmbeddingEngine api， 将url文档embedding向量化到向量数据库 "
-
-#: ../../modules/knowledge.rst:75 e2581b414f0148bca88253c7af9cd591
-msgid "If you want to add your source_reader or text_splitter, do this:"
-msgstr "如果你想手动添加你自定义的source_reader和text_splitter, 请参考:"
-
-#: ../../modules/knowledge.rst:95 74c110414f924bbfa3d512e45ba2f30f
-#, fuzzy
-msgid ""
-"4.init Document Type EmbeddingEngine api and embedding your document into"
-" vector store in your code. Document type can be .txt, .pdf, .md, .doc, "
-".ppt."
 msgstr ""
-"初始化 文档型类型 EmbeddingEngine api， 将文档embedding向量化到向量数据库(文档可以是.txt, .pdf, "
-".md, .html, .doc, .ppt)"
 
-#: ../../modules/knowledge.rst:108 0afd40098d5f4dfd9e44fe1d8004da25
+#: ../../modules/knowledge.md:31 4498ec4e46ff4e24b45dd855e829bd32
 msgid ""
-"5.init TEXT Type EmbeddingEngine api and embedding your document into "
+"Optionally, you can run `dbgpt knowledge load --help` command to see more"
-"vector store in your code."
+" usage."
-msgstr "初始化TEXT类型 EmbeddingEngine api， 将文档embedding向量化到向量数据库"
+msgstr ""
 
-#: ../../modules/knowledge.rst:120 a66961bf3efd41fa8ea938129446f5a5
+#: ../../modules/knowledge.md:33 5048ac3289e540f2a2b5fd0e5ed043f5
-msgid "4.similar search based on your knowledge base. ::"
+msgid ""
-msgstr "在知识库进行相似性搜索"
+"3.Add the knowledge repository in the interface by entering the name of "
+"your knowledge repository (if not specified, enter \"default\") so you "
+"can use it for Q&A based on your knowledge base."
+msgstr ""
 
-#: ../../modules/knowledge.rst:126 b7066f408378450db26770f83fbd2716
+#: ../../modules/knowledge.md:35 deeccff20f7f453dad0881b63dae2a18
 msgid ""
 "Note that the default vector model used is text2vec-large-chinese (which "
 "is a large model, so if your personal computer configuration is not "
@@ -125,48 +106,6 @@ msgstr ""
 "注意，这里默认向量模型是text2vec-large-chinese(模型比较大，如果个人电脑配置不够建议采用text2vec-base-"
 "chinese),因此确保需要将模型download下来放到models目录中。"
 
-#: ../../modules/knowledge.rst:128 58481d55cab74936b6e84b24c39b1674
-#, fuzzy
-msgid ""
-"`pdf_embedding <./knowledge/pdf/pdf_embedding.html>`_: supported pdf "
-"embedding."
-msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
-
-#: ../../modules/knowledge.rst:129 fbb013c4f1bc46af910c91292f6690cf
-#, fuzzy
-msgid ""
-"`markdown_embedding <./knowledge/markdown/markdown_embedding.html>`_: "
-"supported markdown embedding."
-msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
-
-#: ../../modules/knowledge.rst:130 59d45732f4914d16b4e01aee0992edf7
-#, fuzzy
-msgid ""
-"`word_embedding <./knowledge/word/word_embedding.html>`_: supported word "
-"embedding."
-msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
-
-#: ../../modules/knowledge.rst:131 df0e6f311861423e885b38e020a7c0f0
-#, fuzzy
-msgid ""
-"`url_embedding <./knowledge/url/url_embedding.html>`_: supported url "
-"embedding."
-msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
-
-#: ../../modules/knowledge.rst:132 7c550c1f5bc34fe9986731fb465e12cd
-#, fuzzy
-msgid ""
-"`ppt_embedding <./knowledge/ppt/ppt_embedding.html>`_: supported ppt "
-"embedding."
-msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
-
-#: ../../modules/knowledge.rst:133 8648684cb191476faeeb548389f79050
-#, fuzzy
-msgid ""
-"`string_embedding <./knowledge/string/string_embedding.html>`_: supported"
-" raw text embedding."
-msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
-
 #~ msgid "before execution:  python -m spacy download zh_core_web_sm"
 #~ msgstr "在执行之前请先执行python -m spacy download zh_core_web_sm"
 
@@ -201,3 +140,112 @@ msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embeddin
 #~ "and MILVUS_PORT)"
 #~ msgstr "2.更新你的.env，设置你的向量存储类型，VECTOR_STORE_TYPE=Chroma(现在只支持Chroma和Milvus，如果你设置了Milvus，请设置MILVUS_URL和MILVUS_PORT)"
 
+#~ msgid ""
+#~ "We currently support many document "
+#~ "formats: raw text, txt, pdf, md, "
+#~ "html, doc, ppt, and url. In the"
+#~ " future, we will continue to support"
+#~ " more types of knowledge, including "
+#~ "audio, video, various databases, and big"
+#~ " data sources. Of course, we look "
+#~ "forward to your active participation in"
+#~ " contributing code."
+#~ msgstr ""
+
+#~ msgid "1.prepare"
+#~ msgstr "准备"
+
+#~ msgid ""
+#~ "2.prepare embedding model, you can "
+#~ "download from https://huggingface.co/. Notice "
+#~ "you have installed git-lfs."
+#~ msgstr ""
+#~ "提前准备Embedding Model, 你可以在https://huggingface.co/进行下载，注意"
+#~ "：你需要先安装git-lfs.eg: git clone "
+#~ "https://huggingface.co/THUDM/chatglm2-6b"
+
+#~ msgid ""
+#~ "eg: git clone https://huggingface.co/sentence-"
+#~ "transformers/all-MiniLM-L6-v2"
+#~ msgstr ""
+#~ "eg: git clone https://huggingface.co/sentence-"
+#~ "transformers/all-MiniLM-L6-v2"
+
+#~ msgid ""
+#~ "3.prepare vector_store instance and vector "
+#~ "store config, now we support Chroma, "
+#~ "Milvus and Weaviate."
+#~ msgstr "提前准备向量数据库环境，目前支持Chroma, Milvus and Weaviate向量数据库"
+
+#~ msgid ""
+#~ "3.init Url Type EmbeddingEngine api and"
+#~ " embedding your document into vector "
+#~ "store in your code."
+#~ msgstr "初始化 Url类型 EmbeddingEngine api， 将url文档embedding向量化到向量数据库 "
+
+#~ msgid "If you want to add your source_reader or text_splitter, do this:"
+#~ msgstr "如果你想手动添加你自定义的source_reader和text_splitter, 请参考:"
+
+#~ msgid ""
+#~ "4.init Document Type EmbeddingEngine api "
+#~ "and embedding your document into vector"
+#~ " store in your code. Document type"
+#~ " can be .txt, .pdf, .md, .doc, "
+#~ ".ppt."
+#~ msgstr ""
+#~ "初始化 文档型类型 EmbeddingEngine api， "
+#~ "将文档embedding向量化到向量数据库(文档可以是.txt, .pdf, .md, .html,"
+#~ " .doc, .ppt)"
+
+#~ msgid ""
+#~ "5.init TEXT Type EmbeddingEngine api and"
+#~ " embedding your document into vector "
+#~ "store in your code."
+#~ msgstr "初始化TEXT类型 EmbeddingEngine api， 将文档embedding向量化到向量数据库"
+
+#~ msgid "4.similar search based on your knowledge base. ::"
+#~ msgstr "在知识库进行相似性搜索"
+
+#~ msgid ""
+#~ "`pdf_embedding <./knowledge/pdf/pdf_embedding.html>`_: "
+#~ "supported pdf embedding."
+#~ msgstr ""
+#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: "
+#~ "supported pdf embedding."
+
+#~ msgid ""
+#~ "`markdown_embedding "
+#~ "<./knowledge/markdown/markdown_embedding.html>`_: supported "
+#~ "markdown embedding."
+#~ msgstr ""
+#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: "
+#~ "supported pdf embedding."
+
+#~ msgid ""
+#~ "`word_embedding <./knowledge/word/word_embedding.html>`_: "
+#~ "supported word embedding."
+#~ msgstr ""
+#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: "
+#~ "supported pdf embedding."
+
+#~ msgid ""
+#~ "`url_embedding <./knowledge/url/url_embedding.html>`_: "
+#~ "supported url embedding."
+#~ msgstr ""
+#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: "
+#~ "supported pdf embedding."
+
+#~ msgid ""
+#~ "`ppt_embedding <./knowledge/ppt/ppt_embedding.html>`_: "
+#~ "supported ppt embedding."
+#~ msgstr ""
+#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: "
+#~ "supported pdf embedding."
+
+#~ msgid ""
+#~ "`string_embedding <./knowledge/string/string_embedding.html>`_:"
+#~ " supported raw text embedding."
+#~ msgstr ""
+#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: "
+#~ "supported pdf embedding."
+

docs/requirements.txt

@@ -9,9 +9,9 @@ sphinx_book_theme
 sphinx_rtd_theme==1.0.0
 sphinx-typlog-theme==0.8.0
 sphinx-panels
+sphinx-tabs==3.4.0
 toml
 myst_nb
 sphinx_copybutton
 pydata-sphinx-theme==0.13.1
-pydantic-settings
 furo