Thor

Thor(雷神托尔) 是一款强大的人工智能模型管理工具，其主要目的是为了实现多种AI模型的统一管理和使用。通过Thor(雷神托尔)，用户可以轻松地管理和使用众多AI模型，而且Thor(雷神托尔)兼容OpenAI的接口格式，使得使用更加方便。

Stars: 131

Visit

Thor is a powerful AI model management tool designed for unified management and usage of various AI models. It offers features such as user, channel, and token management, data statistics preview, log viewing, system settings, external chat link integration, and Alipay account balance purchase. Thor supports multiple AI models including OpenAI, Kimi, Starfire, Claudia, Zhilu AI, Ollama, Tongyi Qianwen, AzureOpenAI, and Tencent Hybrid models. It also supports various databases like SqlServer, PostgreSql, Sqlite, and MySql, allowing users to choose the appropriate database based on their needs.

README:

Thor(雷神托尔)

Thor(雷神托尔),一个AI大模型管理网关。

Changelog · Report Bug · Request Feature

Thor(雷神托尔)

Thor(雷神托尔)提供了丰富的功能：

管理功能：支持用户管理，渠道管理以及token管理，简化了管理流程。
数据统计预览：可以清晰地看到各种数据的统计情况，帮助用户更好地了解使用情况。
日志查看：支持日志查看，方便用户跟踪和解决问题。
系统设置：可以根据需要进行各种系统设置。
外部Chat链接接入：支持接入外部Chat链接，提升交互体验。
支付宝购买账号余额：提供支付宝购买账号余额的功能，方便用户进行充值。

此外，Thor(雷神托尔)还支持多种AI大模型，包括OpenAI、星火大模型、Claudia、智谱AI、Ollama、通义千问（阿里云）、AzureOpenAI以及腾讯混元大模型，满足了用户对各种AI模型的需求。

Thor(雷神托尔)还支持多种数据库，包括SqlServer、PostgreSql、Sqlite以及MySql，用户可以根据自己的需要选择合适的数据库。

功能实现

[x] 支持用户管理
[x] 支持渠道管理
[x] 支持token管理
[x] 提供数据统计预览
[x] 支持日志查看
[x] 支持系统设置
[x] 支持接入外部Chat链接
[x] 支持支付宝购买账号余额
[x] 支持Rabbit消费日志（默认情况下使用本地事件）
[x] 支持分布式多级缓存

AI大模型支持列表

[x] OpenAI （支持function）
[x] Kimi（月之暗面）（支持function）
[x] 星火大模型（支持function）
[x] Claudia (非Stream支持function)
[x] 智谱AI (支持function)
[x] AzureOpenAI（支持function）
[x] Ollama（支持function）
[x] 通义千问（阿里云）（支持function）
[x] 腾讯混元大模型
[x] 支持百度大模型(ErnieBot)
[x] Gitee AI

支持数据库

[x] SqlServer 配置类型[sqlserver,mssql]
[x] PostgreSql 配置类型[postgresql,pgsql]
[x] Sqlite 配置类型[sqlite,默认]
[x] MySql 配置类型[mysql]
[x] 达梦数据库配置类型[dm]

修改appsettings.json的ConnectionStrings:DBType配置项即可切换数据库类型。请注意切换数据库不会迁移数据。

graph LR
    A(用户)
    A --->|使用 Thor 分发的 key 进行请求| B(Thor)
    B -->|中继请求| C(OpenAI)
    B -->|中继请求| D(Azure)
    B -->|中继请求| E(其他 OpenAI API 格式下游渠道)
    B -->|中继并修改请求体和返回体| F(非 OpenAI API 格式下游渠道)

简单使用

默认账号密码 admin admin

注意事项

需要注意的是，如果克隆项目后，项目根目录缺少data时，需要手动创建，docker compose up 时，需要挂载本地目录data。

环境变量

DBType sqlite | [postgresql,pgsql] | [sqlserver,mssql] | mysql
ConnectionStrings:DefaultConnection 主数据库连接字符串
ConnectionStrings:LoggerConnection 日志数据连接字符串
CACHE_TYPE 缓存类型 Memory|Redis
CACHE_CONNECTION_STRING 缓存连接字符串如果是Redis则为Redis连接字符串，Memory则为空
HttpClientPoolSize HttpClient连接池大小
RunMigrationsAtStartup 是否在启动时运行迁移如果是首次启动则需要设置为true

使用docker compose启动服务：

version: '3.8'

services:
  thor:
    image: aidotnet/thor:latest
    ports:
      - 18080:8080
    container_name: thor
    volumes:
      - ./data:/data
    environment:
      - TZ=Asia/Shanghai
      - DBType=sqlite # sqlite | [postgresql,pgsql] | [sqlserver,mssql] | mysql
      - ConnectionStrings:DefaultConnection=data source=/data/token.db
      - ConnectionStrings:LoggerConnection=data source=/data/logger.db
      - RunMigrationsAtStartup=true

使用docker run启动服务

docker run -d -p 18080:8080 --name thor --network=gateway -v $PWD/data:/data -e Theme=lobe -e TZ=Asia/Shanghai -e DBType=sqlite -e ConnectionStrings:ConnectionString="data source=/data/token.db" -e RunMigrationsAtStartup=true -e ConnectionStrings:LoggerConnectionString="data source=/data/logger.db" aidotnet/thor:latest

Sqlite构建

docker compose版本

项目根目录创建docker-compose.yml文件，内容如下：

version: '3.8'

services:
  thor:
    image: aidotnet/thor:latest
    container_name: thor
    ports:
      - 18080:8080
    volumes:
      - ./data:/data
    environment:
      - TZ=Asia/Shanghai
      - DBType=sqlite
      - ConnectionStrings:DefaultConnection=data source=/data/token.db
      - ConnectionStrings:LoggerConnection=data source=/data/logger.db
      - RunMigrationsAtStartup=true

执行如下命令打包镜像

sudo docker compose build

执行以下命令启动服务

sudo docker compose up -d

docker run版本

docker run -d -p 18080:8080 --name ai-dotnet-api-service -v $(pwd)/data:/data -e RunMigrationsAtStartup=true  -e Theme=lobe -e TZ=Asia/Shanghai -e DBType=sqlite -e ConnectionStrings:DefaultConnection=data source=/data/token.db -e ConnectionStrings:LoggerConnection=data source=/data/logger.db aidotnet/thor:latest

然后访问 http://localhost:18080 即可看到服务启动成功。

PostgreSql构建

docker compose版本

项目根目录创建docker-compose.yml文件，内容如下：

version: '3.8'

services:
  thor:
    image: aidotnet/thor:latest
    container_name: thor
    ports:
      - 18080:8080
    volumes:
      - ./data:/data
    environment:
      - TZ=Asia/Shanghai
      - DBType=postgresql
      - ConnectionStrings:DefaultConnection=Host=127.0.0.1;Port=5432;Database=token;Username=token;Password=dd666666
      - ConnectionStrings:LoggerConnection=Host=127.0.0.1;Port=5432;Database=logger;Username=token;Password=dd666666
      - RunMigrationsAtStartup=true

执行如下命令打包镜像

sudo docker compose build

执行以下命令启动服务

sudo docker compose up -d

docker run版本

docker run -d \
  --name thor \
  -p 18080:8080 \
  -v $(pwd)/data:/data \
  -e TZ=Asia/Shanghai \
  -e DBType=postgresql \
  -e RunMigrationsAtStartup=true \
  -e ConnectionStrings:DefaultConnection=Host=127.0.0.1;Port=5432;Database=token;Username=token;Password=dd666666 \
  -e ConnectionStrings:LoggerConnection=Host=127.0.0.1;Port=5432;Database=logger;Username=token;Password=dd666666 \
  aidotnet/thor:latest

然后访问 http://localhost:18080 即可看到服务启动成功。

SqlServer构建

docker compose版本

项目根目录创建docker-compose.yml文件，内容如下：

version: '3.8'

services:
  thor:
    image: aidotnet/thor:latest
    container_name: thor
    ports:
      - 18080:8080
    volumes:
      - ./data:/data
    environment:
      - TZ=Asia/Shanghai
      - DBType=sqlserver
      - ConnectionStrings:DefaultConnection=Server=127.0.0.1;Database=token;User Id=sa;Password=dd666666;
      - ConnectionStrings:LoggerConnection=Server=127.0.0.1;Database=logger;User Id=sa;Password=dd666666;
      - RunMigrationsAtStartup=true

执行如下命令打包镜像

sudo docker compose build

执行以下命令启动服务

sudo docker compose up -d

docker run版本

docker run -d \
  --name thor \
  -p 18080:8080 \
  -v $(pwd)/data:/data \
  -e TZ=Asia/Shanghai \
  -e RunMigrationsAtStartup=true \
  -e DBType=sqlserver \
  -e ConnectionStrings:DefaultConnection=Server=127.0.0.1;Database=token;User Id=sa;Password=dd666666; \
  -e ConnectionStrings:LoggerConnection=Server=127.0.0.1;Database=logger;User Id=sa;Password=dd666666; \
  aidotnet/thor:latest

然后访问 http://localhost:18080 即可看到服务启动成功。

MySql构建

docker compose版本

项目根目录创建docker-compose.yml文件，内容如下：

version: '3.8'

services:
  thor:
    image: aidotnet/thor:latest
    container_name: thor
    ports:
      - 18080:8080
    volumes:
      - ./data:/data
    environment:
      - TZ=Asia/Shanghai
      - DBType=mysql
      - "ConnectionStrings:DefaultConnection=mysql://root:dd666666@localhost:3306/token"
      - "ConnectionStrings:LoggerConnection=mysql://root:dd666666@localhost:3306/logger"
      - RunMigrationsAtStartup=true

执行如下命令打包镜像

sudo docker compose build

执行以下命令启动服务

sudo docker compose up -d

docker run版本

docker run -d \
  --name thor \
  -p 18080:8080 \
  -v $(pwd)/data:/data \
  -e TZ=Asia/Shanghai \
  -e DBType=mysql \
  -e "ConnectionStrings:DefaultConnection=mysql://root:dd666666@localhost:3306/token" \
  -e "ConnectionStrings:LoggerConnection=mysql://root:dd666666@localhost:3306/logger" \
  -e RunMigrationsAtStartup=true \
  aidotnet/thor:latest

然后访问 http://localhost:18080 即可看到服务启动成功。

For Tasks:

Click tags to check more tools for each tasks

manage ai models view data statistics integrate external chat links purchase account balance switch databases

For Jobs:

ai model manager data scientist machine learning engineer ai solutions architect ai project manager

Alternative AI tools for Thor

Similar Open Source Tools

Thor

github

: 131

VoAPI

VoAPI is a new high-value/high-performance AI model interface management and distribution system. It is a closed-source tool for personal learning use only, not for commercial purposes. Users must comply with upstream AI model service providers and legal regulations. The system offers a visually appealing interface with features such as independent development documentation page support, service monitoring page configuration support, and third-party login support. Users can manage user registration time, optimize interface elements, and support features like online recharge, model pricing display, and sensitive word filtering. VoAPI also provides support for various AI models and platforms, with the ability to configure homepage templates, model information, and manufacturer information.

github

: 383

VoAPI

VoAPI is a new high-value/high-performance AI model interface management and distribution system. It is a closed-source tool for personal learning use only, not for commercial purposes. Users must comply with upstream AI model service providers and legal regulations. The system offers a visually appealing interface, independent development documentation page support, service monitoring page configuration support, and third-party login support. It also optimizes interface elements, user registration time support, data operation button positioning, and more.

github

: 89

bce-qianfan-sdk

The Qianfan SDK provides best practices for large model toolchains, allowing AI workflows and AI-native applications to access the Qianfan large model platform elegantly and conveniently. The core capabilities of the SDK include three parts: large model reasoning, large model training, and general and extension: * `Large model reasoning`: Implements interface encapsulation for reasoning of Yuyan (ERNIE-Bot) series, open source large models, etc., supporting dialogue, completion, Embedding, etc. * `Large model training`: Based on platform capabilities, it supports end-to-end large model training process, including training data, fine-tuning/pre-training, and model services. * `General and extension`: General capabilities include common AI development tools such as Prompt/Debug/Client. The extension capability is based on the characteristics of Qianfan to adapt to common middleware frameworks.

github

: 342

AMchat

AMchat is a large language model that integrates advanced math concepts, exercises, and solutions. The model is based on the InternLM2-Math-7B model and is specifically designed to answer advanced math problems. It provides a comprehensive dataset that combines Math and advanced math exercises and solutions. Users can download the model from ModelScope or OpenXLab, deploy it locally or using Docker, and even retrain it using XTuner for fine-tuning. The tool also supports LMDeploy for quantization, OpenCompass for evaluation, and various other features for model deployment and evaluation. The project contributors have provided detailed documentation and guides for users to utilize the tool effectively.

github

: 153

midjourney-proxy

Midjourney-proxy is a proxy for the Discord channel of MidJourney, enabling API-based calls for AI drawing. It supports Imagine instructions, adding image base64 as a placeholder, Blend and Describe commands, real-time progress tracking, Chinese prompt translation, prompt sensitive word pre-detection, user-token connection to WSS, multi-account configuration, and more. For more advanced features, consider using midjourney-proxy-plus, which includes Shorten, focus shifting, image zooming, local redrawing, nearly all associated button actions, Remix mode, seed value retrieval, account pool persistence, dynamic maintenance, /info and /settings retrieval, account settings configuration, Niji bot robot, InsightFace face replacement robot, and an embedded management dashboard.

github

: 4.9k

ddddocr

ddddocr is a Rust version of a simple OCR API server that provides easy deployment for captcha recognition without relying on the OpenCV library. It offers a user-friendly general-purpose captcha recognition Rust library. The tool supports recognizing various types of captchas, including single-line text, transparent black PNG images, target detection, and slider matching algorithms. Users can also import custom OCR training models and utilize the OCR API server for flexible OCR result control and range limitation. The tool is cross-platform and can be easily deployed.

github

: 80

aiges

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.

github

: 275

meet-libai

The 'meet-libai' project aims to promote and popularize the cultural heritage of the Chinese poet Li Bai by constructing a knowledge graph of Li Bai and training a professional AI intelligent body using large models. The project includes features such as data preprocessing, knowledge graph construction, question-answering system development, and visualization exploration of the graph structure. It also provides code implementations for large models and RAG retrieval enhancement.

github

: 1.1k

YesImBot

YesImBot, also known as Athena, is a Koishi plugin designed to allow large AI models to participate in group chat discussions. It offers easy customization of the bot's name, personality, emotions, and other messages. The plugin supports load balancing multiple API interfaces for large models, provides immersive context awareness, blocks potentially harmful messages, and automatically fetches high-quality prompts. Users can adjust various settings for the bot and customize system prompt words. The ultimate goal is to seamlessly integrate the bot into group chats without detection, with ongoing improvements and features like message recognition, emoji sending, multimodal image support, and more.

github

: 52

FastGPT

FastGPT is a knowledge base Q&A system based on the LLM large language model, providing out-of-the-box data processing, model calling and other capabilities. At the same time, you can use Flow to visually arrange workflows to achieve complex Q&A scenarios!

github

: 19.7k

Tianji

Tianji is a free, non-commercial artificial intelligence system developed by SocialAI for tasks involving worldly wisdom, such as etiquette, hospitality, gifting, wishes, communication, awkwardness resolution, and conflict handling. It includes four main technical routes: pure prompt, Agent architecture, knowledge base, and model training. Users can find corresponding source code for these routes in the tianji directory to replicate their own vertical domain AI applications. The project aims to accelerate the penetration of AI into various fields and enhance AI's core competencies.

github

: 1.0k

CareGPT

CareGPT is a medical large language model (LLM) that explores medical data, training, and deployment related research work. It integrates resources, open-source models, rich data, and efficient deployment methods. It supports various medical tasks, including patient diagnosis, medical dialogue, and medical knowledge integration. The model has been fine-tuned on diverse medical datasets to enhance its performance in the healthcare domain.

github

: 508

evalplus

EvalPlus is a rigorous evaluation framework for LLM4Code, providing HumanEval+ and MBPP+ tests to evaluate large language models on code generation tasks. It offers precise evaluation and ranking, coding rigorousness analysis, and pre-generated code samples. Users can use EvalPlus to generate code solutions, post-process code, and evaluate code quality. The tool includes tools for code generation and test input generation using various backends.

github

: 1.3k

ChatPilot

ChatPilot is a chat agent tool that enables AgentChat conversations, supports Google search, URL conversation (RAG), and code interpreter functionality, replicates Kimi Chat (file, drag and drop; URL, send out), and supports OpenAI/Azure API. It is based on LangChain and implements ReAct and OpenAI Function Call for agent Q&A dialogue. The tool supports various automatic tools such as online search using Google Search API, URL parsing tool, Python code interpreter, and enhanced RAG file Q&A with query rewriting support. It also allows front-end and back-end service separation using Svelte and FastAPI, respectively. Additionally, it supports voice input/output, image generation, user management, permission control, and chat record import/export.

github

: 523

ap-plugin

AP-PLUGIN is an AI drawing plugin for the Yunzai series robot framework, allowing you to have a convenient AI drawing experience in the input box. It uses the open source Stable Diffusion web UI as the backend, deploys it for free, and generates a variety of images with richer functions.

github

: 103

For similar tasks

Thor

github

: 131

griptape

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.

github

: 2.1k

tts-generation-webui

TTS Generation WebUI is a comprehensive tool that provides a user-friendly interface for text-to-speech and voice cloning tasks. It integrates various AI models such as Bark, MusicGen, AudioGen, Tortoise, RVC, Vocos, Demucs, SeamlessM4T, and MAGNeT. The tool offers one-click installers, Google Colab demo, videos for guidance, and extra voices for Bark. Users can generate audio outputs, manage models, caches, and system space for AI projects. The project is open-source and emphasizes ethical and responsible use of AI technology.

github

: 1.6k

VoAPI

VoAPI is a new high-value/high-performance AI model interface management and distribution system. It is a closed-source tool for personal learning use only, not for commercial purposes. Users must comply with upstream AI model service providers and legal regulations. The system offers a visually appealing interface, independent development documentation page support, service monitoring page configuration support, and third-party login support. It also optimizes interface elements, user registration time support, data operation button positioning, and more.

github

: 89

VoAPI

github

: 383

aigcpanel

AigcPanel is a simple and easy-to-use all-in-one AI digital human system that even beginners can use. It supports video synthesis, voice synthesis, voice cloning, simplifies local model management, and allows one-click import and use of AI models. It prohibits the use of this product for illegal activities and users must comply with the laws and regulations of the People's Republic of China.

github

: 635

For similar jobs

Thor

github

: 131

aigcpanel

github

: 635

redbox

Redbox is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License. Security measures are in place to ensure user data privacy and considerations are being made to make the core-api secure.

github

: 99

WilmerAI

WilmerAI is a middleware system designed to process prompts before sending them to Large Language Models (LLMs). It categorizes prompts, routes them to appropriate workflows, and generates manageable prompts for local models. It acts as an intermediary between the user interface and LLM APIs, supporting multiple backend LLMs simultaneously. WilmerAI provides API endpoints compatible with OpenAI API, supports prompt templates, and offers flexible connections to various LLM APIs. The project is under heavy development and may contain bugs or incomplete code.

github

: 109

MLE-agent

MLE-Agent is an intelligent companion designed for machine learning engineers and researchers. It features autonomous baseline creation, integration with Arxiv and Papers with Code, smart debugging, file system organization, comprehensive tools integration, and an interactive CLI chat interface for seamless AI engineering and research workflows.

github

: 1.1k

LynxHub

LynxHub is a platform that allows users to seamlessly install, configure, launch, and manage all their AI interfaces from a single, intuitive dashboard. It offers features like AI interface management, arguments manager, custom run commands, pre-launch actions, extension management, in-app tools like terminal and web browser, AI information dashboard, Discord integration, and additional features like theme options and favorite interface pinning. The platform supports modular design for custom AI modules and upcoming extensions system for complete customization. LynxHub aims to streamline AI workflow and enhance user experience with a user-friendly interface and comprehensive functionalities.

github

: 144

ChatGPT-Next-Web-Pro

ChatGPT-Next-Web-Pro is a tool that provides an enhanced version of ChatGPT-Next-Web with additional features and functionalities. It offers complete ChatGPT-Next-Web functionality, file uploading and storage capabilities, drawing and video support, multi-modal support, reverse model support, knowledge base integration, translation, customizations, and more. The tool can be deployed with or without a backend, allowing users to interact with AI models, manage accounts, create models, manage API keys, handle orders, manage memberships, and more. It supports various cloud services like Aliyun OSS, Tencent COS, and Minio for file storage, and integrates with external APIs like Azure, Google Gemini Pro, and Luma. The tool also provides options for customizing website titles, subtitles, icons, and plugin buttons, and offers features like voice input, file uploading, real-time token count display, and more.

github

: 625

agentneo

AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

github

: 293