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

.dockerignore

@@ -2,4 +2,10 @@ models/
 plugins/
 pilot/data
 pilot/message
-logs/
+logs/
+venv/
+web/node_modules/
+docs/node_modules/
+build/
+docs/build/
+docs/Dockerfile-deploy

.github/workflows/doc-image-publish.yml

@@ -0,0 +1,39 @@
+name: Build and push docs image
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'docs/**'
+  release:
+    types: [published]
+  workflow_dispatch: 
+
+permissions:
+  contents: read
+
+jobs:
+  build-image:
+    runs-on: ubuntu-latest
+    # run unless event type is pull_request
+    if: github.event_name != 'pull_request'
+    steps:
+      - uses: actions/checkout@v3
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v2
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+      - name: Login to Docker Hub
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+      - name: Build and push
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          file: ./docs/Dockerfile-deploy
+          platforms: linux/amd64
+          push: true
+          tags: eosphorosai/dbgpt-docs:${{ github.ref_name }},eosphorosai/dbgpt-docs:latest

README.ja.md

@@ -154,6 +154,9 @@ DB-GPTのアーキテクチャは以下の図に示されています：
   私たちは、LLaMA/LLaMA2、Baichuan、ChatGLM、Wenxin、Tongyi、Zhipuなど、オープンソースおよびAPIエージェントからの数十の大規模言語モデル（LLM）を含む幅広いモデルをサポートしています。
 
   - ニュース
+    - 🔥🔥🔥  [Meta-Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct)
+    - 🔥🔥🔥  [Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct)
+    - 🔥🔥🔥  [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)
     - 🔥🔥🔥  [gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it)
     - 🔥🔥🔥  [gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)
     - 🔥🔥🔥  [DeepSeek-Coder-V2-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct)

README.md

@@ -158,6 +158,9 @@ At present, we have introduced several key features to showcase our current capa
   We offer extensive model support, including dozens of large language models (LLMs) from both open-source and API agents, such as LLaMA/LLaMA2, Baichuan, ChatGLM, Wenxin, Tongyi, Zhipu, and many more. 
 
   - News
+    - 🔥🔥🔥  [Meta-Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct)
+    - 🔥🔥🔥  [Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct)
+    - 🔥🔥🔥  [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)
     - 🔥🔥🔥  [gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it)
     - 🔥🔥🔥  [gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)
     - 🔥🔥🔥  [DeepSeek-Coder-V2-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct)

README.zh.md

@@ -152,6 +152,9 @@
   海量模型支持，包括开源、API代理等几十种大语言模型。如LLaMA/LLaMA2、Baichuan、ChatGLM、文心、通义、智谱等。当前已支持如下模型: 
 
   - 新增支持模型
+    - 🔥🔥🔥  [Meta-Llama-3.1-405B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-405B-Instruct)
+    - 🔥🔥🔥  [Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct)
+    - 🔥🔥🔥  [Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)
     - 🔥🔥🔥  [gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it)
     - 🔥🔥🔥  [gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)
     - 🔥🔥🔥  [DeepSeek-Coder-V2-Instruct](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Instruct)

dbgpt/agent/expand/resources/search_tool.py

@@ -38,6 +38,7 @@ def baidu_search(
         "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:112.0) "
         "Gecko/20100101 Firefox/112.0"
     }
+    num_results = int(num_results)
     if num_results < 8:
         num_results = 8
     url = f"https://www.baidu.com/s?wd={query}&rn={num_results}"

dbgpt/app/knowledge/service.py

@@ -1,5 +1,6 @@
 import json
 import logging
+import re
 from datetime import datetime
 
 from dbgpt._private.config import Config
@@ -80,6 +81,10 @@ def create_knowledge_space(self, request: KnowledgeSpaceRequest):
         )
         if request.vector_type == "VectorStore":
             request.vector_type = CFG.VECTOR_STORE_TYPE
+        if request.vector_type == "KnowledgeGraph":
+            knowledge_space_name_pattern = r"^[a-zA-Z0-9\u4e00-\u9fa5]+$"
+            if not re.match(knowledge_space_name_pattern, request.name):
+                raise Exception(f"space name:{request.name} invalid")
         spaces = knowledge_space_dao.get_knowledge_space(query)
         if len(spaces) > 0:
             raise Exception(f"space name:{request.name} have already named")

dbgpt/configs/model_config.py

@@ -85,6 +85,15 @@ def get_device() -> str:
     "meta-llama-3-8b-instruct": os.path.join(MODEL_PATH, "Meta-Llama-3-8B-Instruct"),
     # https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct
     "meta-llama-3-70b-instruct": os.path.join(MODEL_PATH, "Meta-Llama-3-70B-Instruct"),
+    "meta-llama-3.1-8b-instruct": os.path.join(
+        MODEL_PATH, "Meta-Llama-3.1-8B-Instruct"
+    ),
+    "meta-llama-3.1-70b-instruct": os.path.join(
+        MODEL_PATH, "Meta-Llama-3.1-70B-Instruct"
+    ),
+    "meta-llama-3.1-405b-instruct": os.path.join(
+        MODEL_PATH, "Meta-Llama-3.1-405B-Instruct"
+    ),
     "baichuan-13b": os.path.join(MODEL_PATH, "Baichuan-13B-Chat"),
     # please rename "fireballoon/baichuan-vicuna-chinese-7b" to "baichuan-7b"
     "baichuan-7b": os.path.join(MODEL_PATH, "baichuan-7b"),

dbgpt/model/adapter/hf_adapter.py

@@ -403,7 +403,12 @@ class Llama3Adapter(NewHFChatModelAdapter):
     support_8bit: bool = True
 
     def do_match(self, lower_model_name_or_path: Optional[str] = None):
-        return lower_model_name_or_path and "llama-3" in lower_model_name_or_path
+        return (
+            lower_model_name_or_path
+            and "llama-3" in lower_model_name_or_path
+            and "instruct" in lower_model_name_or_path
+            and "3.1" not in lower_model_name_or_path
+        )
 
     def get_str_prompt(
         self,
@@ -431,6 +436,22 @@ def get_str_prompt(
         return str_prompt
 
 
+class Llama31Adapter(Llama3Adapter):
+    def check_transformer_version(self, current_version: str) -> None:
+        logger.info(f"Checking transformers version: Current version {current_version}")
+        if not current_version >= "4.43.0":
+            raise ValueError(
+                "Llama-3.1 require transformers.__version__>=4.43.0, please upgrade your transformers package."
+            )
+
+    def do_match(self, lower_model_name_or_path: Optional[str] = None):
+        return (
+            lower_model_name_or_path
+            and "llama-3.1" in lower_model_name_or_path
+            and "instruct" in lower_model_name_or_path
+        )
+
+
 class DeepseekV2Adapter(NewHFChatModelAdapter):
     support_4bit: bool = False
     support_8bit: bool = False
@@ -613,6 +634,7 @@ def load(self, model_path: str, from_pretrained_kwargs: dict):
 register_model_adapter(QwenAdapter)
 register_model_adapter(QwenMoeAdapter)
 register_model_adapter(Llama3Adapter)
+register_model_adapter(Llama31Adapter)
 register_model_adapter(DeepseekV2Adapter)
 register_model_adapter(DeepseekCoderV2Adapter)
 register_model_adapter(SailorAdapter)

docs/Dockerfile-deploy

@@ -0,0 +1,95 @@
+FROM node:lts-alpine as build
+
+RUN apk add --no-cache git
+
+ARG NPM_REGISTRY=https://registry.npmjs.org
+ENV NPM_REGISTRY=$NPM_REGISTRY
+
+# Set github CI environment variable
+ARG CI=true
+ENV CI=$CI
+
+WORKDIR /app
+
+# Copy package.json and package-lock.json to a separate build directory
+COPY docs/package*.json /app-build/docs/
+
+# Install dependencies in the separate build directory
+RUN cd /app-build/docs && \
+    npm config set registry $NPM_REGISTRY && \
+    npm ci
+
+# Copy the rest of the application to /app and /app-build
+COPY . /app-build
+COPY . /app
+
+# Make sure we have the latest version of the repository
+RUN if [ "$CI" = "true" ]; then \
+        git fetch --prune --unshallow; \
+    fi
+
+ARG NUM_VERSION=2
+ENV NUM_VERSION=$NUM_VERSION
+
+# Commit the changes to the repository, just for local testing
+# Sometimes, we just want to test the changes in the Dockerfile
+RUN git config --global user.email "[email protected]" && \
+    git config --global user.name "DB-GPT" && \
+    git add . && git commit --no-verify -m "Commit message"
+
+# New logic for building versions directly in Dockerfile
+RUN git config --global --add safe.directory /app && \
+    # Record the current position
+    CURRENT_POSITION=$(git rev-parse --abbrev-ref HEAD) && \
+    # Get the latest tags
+    TAGS=$(git tag --sort=-creatordate | head -n $NUM_VERSION | tac) && \
+    # If there are no tags, get the latest commits
+    if [ -z "$TAGS" ]; then \
+        TAGS=$(git log --format="%h" -n $NUM_VERSION | tac); \
+    fi && \
+    for TAG in $TAGS; do \
+        echo "Creating version $TAG"; \
+        cd /app/docs && git checkout $TAG; \
+        echo "Checked out to tag: $TAG"; \
+        # Copy the necessary files to the build directory for each tag
+        rm -rf /app-build/docs/docs /app-build/docs/sidebars.js /app-build/docs/static /app-build/docs/src && \
+        cp -r /app/docs/docs /app-build/docs/ && \
+        cp /app/docs/sidebars.js /app-build/docs/ && \
+        cp -r /app/docs/static /app-build/docs/ && \
+        cp -r /app/docs/src /app-build/docs/; \
+        # Create a new version
+        cd /app-build/docs && npm run docusaurus docs:version $TAG || exit 1; \
+    done && \
+    # Return to the original position, build dev version
+    cd /app/docs && git checkout $CURRENT_POSITION && \
+    rm -rf /app-build/docs/docs /app-build/docs/sidebars.js /app-build/docs/static /app-build/docs/src && \
+    cp -r /app/docs/docs /app-build/docs/ && \
+    cp /app/docs/sidebars.js /app-build/docs/ && \
+    cp -r /app/docs/static /app-build/docs/ && \
+    cp -r /app/docs/src /app-build/docs/; \
+    cd /app-build/docs && npm run build && \
+    echo $TAGS | tr ' ' '\n' | tac > /app-build/docs/build/versions.txt && \
+    echo "latest" >> /app-build/docs/build/versions.txt && \
+    echo "Built versions:" && \
+    cat /app-build/docs/build/versions.txt
+
+# For production
+FROM nginx:alpine
+
+# Copy the nginx configuration file
+# COPY nginx.conf /etc/nginx/nginx.conf
+
+# Copy the build output to replace the default nginx contents.
+COPY --from=build /app-build/docs/build /usr/share/nginx/html
+COPY --from=build /app-build/docs/versioned_docs/ /usr/share/nginx/html/versioned_docs/
+COPY --from=build /app-build/docs/versioned_sidebars/ /usr/share/nginx/html/versioned_sidebars/
+
+RUN echo '#!/bin/sh' > /usr/share/nginx/html/versions.sh && \
+    echo 'echo "Available versions:"' >> /usr/share/nginx/html/versions.sh && \
+    echo 'cat /usr/share/nginx/html/versions.txt' >> /usr/share/nginx/html/versions.sh && \
+    chmod +x /usr/share/nginx/html/versions.sh
+
+EXPOSE 80
+
+# Start Nginx server
+CMD ["nginx", "-g", "daemon off;"]

docs/README.md

@@ -17,3 +17,33 @@ yarn start
 
 The default service starts on port `3000`, visit `localhost:3000`
 
+## Deploy Multi-Version Documentation
+
+We can deploy multiple versions of the documentation by docker.
+
+### Build Docker Image
+
+Firstly, build the docker image in `DB-GPT` project root directory.
+
+```bash
+# Use the default NPM_REGISTRY=https://registry.npmjs.org
+# Use https://www.npmmirror.com/
+NPM_REGISTRY=https://registry.npmmirror.com
+docker build -f docs/Dockerfile-deploy \
+-t eosphorosai/dbgpt-docs \
+--build-arg NPM_REGISTRY=$NPM_REGISTRY \
+--build-arg CI=false \
+--build-arg NUM_VERSION=2 .
+```
+
+### Run Docker Container
+
+Run the docker container with the following command:
+```bash
+docker run -it --rm -p 8089:8089 \
+--name my-dbgpt-docs \
+-v $(pwd)/docs/nginx/nginx-docs.conf:/etc/nginx/nginx.conf \
+eosphorosai/dbgpt-docs
+```
+
+Open the browser and visit `localhost:8089` to see the documentation.

docs/blog/2024-07-24-db-gpt-llama-3.1-support.md

@@ -0,0 +1,66 @@
+---
+slug: db-gpt-llama-3.1-support
+title: DB-GPT Now Supports Meta Llama 3.1 Series Models
+authors: fangyinc
+tags: [llama, LLM]
+---
+
+We are thrilled to announce that DB-GPT now supports inference with the Meta Llama 3.1 series models!
+
+## Introducing Meta Llama 3.1
+
+Meta Llama 3.1 is a state-of-the-art series of language models developed by Meta AI. Designed with cutting-edge techniques, the Llama 3.1 models offer unparalleled performance and versatility. Here are some of the key highlights:
+
+- **Variety of Models**: Meta Llama 3.1 is available in 8B, 70B, and 405B versions, each with both instruction-tuned and base models, supporting contexts up to 128k tokens.
+- **Multilingual Support**: Supports 8 languages, including English, German, and French.
+- **Extensive Training**: Trained on over 1.5 trillion tokens, utilizing 250 million human and synthetic samples for fine-tuning.
+- **Flexible Licensing**: Permissive model output usage allows for adaptation into other large language models (LLMs).
+- **Quantization Support**: Available in FP8, AWQ, and GPTQ quantized versions for efficient inference.
+- **Performance**: The Llama 3 405B version has outperformed GPT-4 in several benchmarks.
+- **Enhanced Efficiency**: The 8B and 70B models have seen a 12% improvement in coding and instruction-following capabilities.
+- **Tool and Function Call Support**: Supports tool usage and function calling.
+
+## How to Access Meta Llama 3.1
+
+Your can access the Meta Llama 3.1 models according to [Access to Hugging Face](https://github.com/meta-llama/llama-models?tab=readme-ov-file#access-to-hugging-face).
+
+For comprehensive documentation and additional details, please refer to the [model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/MODEL_CARD.md).
+
+## Using Meta Llama 3.1 in DB-GPT
+
+Please read the [Source Code Deployment](../docs/installation/sourcecode) to learn how to install DB-GPT from source code.
+
+Llama 3.1 needs upgrade your transformers >= 4.43.0, please upgrade your transformers:
+```bash
+pip install --upgrade "transformers>=4.43.0"
+```
+
+Please cd to the DB-GPT root directory:
+```bash
+cd DB-GPT
+```
+
+We assume that your models are stored in the `models` directory, e.g., `models/Meta-Llama-3.1-8B-Instruct`.
+
+Then modify your `.env` file:
+```env
+LLM_MODEL=meta-llama-3.1-8b-instruct
+# LLM_MODEL=meta-llama-3.1-70b-instruct
+# LLM_MODEL=meta-llama-3.1-405b-instruct
+## you can also specify the model path
+# LLM_MODEL_PATH=models/Meta-Llama-3.1-8B-Instruct
+## Quantization settings
+# QUANTIZE_8bit=False
+# QUANTIZE_4bit=True
+## You can configure the maximum memory used by each GPU.
+# MAX_GPU_MEMORY=16Gib
+```
+
+Then you can run the following command to start the server:
+```bash
+dbgpt start webserver
+```
+
+Open your browser and visit `http://localhost:5670` to use the Meta Llama 3.1 models in DB-GPT.
+
+Enjoy the power of Meta Llama 3.1 in DB-GPT!

docs/blog/authors.yml

@@ -0,0 +1,5 @@
+fangyinc:
+  name: Fangyin Cheng
+  title: DB-GPT Core Team
+  url: https://github.com/fangyinc
+  image_url: https://avatars.githubusercontent.com/u/22972572?v=4

docs/blog/tags.yml

@@ -0,0 +1,8 @@
+llama:
+  label: LLama
+  permalink: /llama
+  description: A series of language models developed by Meta AI 
+LLM:
+  label: LLM
+  permalink: /llm
+  description: Large Language Models

docs/docs/agents/introduction/tools.md

@@ -178,4 +178,4 @@ In the above code, we use the `ToolAssistantAgent` to select and call the approp
 In the above code, we use the `tool` decorator to define the tool function. It will wrap the function to a 
 `FunctionTool` object. And `FunctionTool` is a subclass of `BaseTool`, which is a base class of all tools.
 
-Actually, **tool** is a special **resource** in the `DB-GPT` agent. You will see more details in the [Resource](./resource.md) section.
+Actually, **tool** is a special **resource** in the `DB-GPT` agent. You will see more details in the [Resource](../modules/resource/resource.md) section.