https://github.com/trending The most popular GitHub repositories today for typescript. Mon, 09 Feb 2026 00:08:28 GMT https://validator.w3.org/feed/docs/rss2.html GitHub Trending RSS Generator en All rights reserved 2026, GitHub https://github.com/KeygraphHQ/shannon https://github.com/KeygraphHQ/shannon Mon, 09 Feb 2026 00:08:28 GMT KeygraphHQ/shannon

Fully autonomous AI hacker to find actual exploits in your web apps. Shannon has achieved a 96.15% success rate on the hint-free, source-aware XBOW Benchmark.

Language: TypeScript

Stars: 13,100

Forks: 1,531

Stars today: 3,479 stars today

README

> [!NOTE]
> **[Shannon Lite achieves a 96.15% success rate on a hint-free, source-aware XBOW benchmark. →](https://github.com/KeygraphHQ/shannon/tree/main/xben-benchmark-results/README.md)**


<div align="center">

<a href="https://trendshift.io/repositories/15604" target="_blank"><img src="https://trendshift.io/api/badge/repositories/15604" alt="KeygraphHQ%2Fshannon | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>

<img src="./assets/shannon-screen.png?v=2" alt="Shannon Screen" width="100%">

# Shannon is your fully autonomous AI pentester.

Shannon’s job is simple: break your web app before anyone else does. <br />
The Red Team to your vibe-coding Blue team. <br />
Every Claude (coder) deserves their Shannon.

---

[Website](https://keygraph.io) • [Discord](https://discord.gg/KAqzSHHpRt)

---
</div>

## 🎯 What is Shannon?

Shannon is an AI pentester that delivers actual exploits, not just alerts.

Shannon's goal is to break your web app before someone else does. It autonomously hunts for attack vectors in your code, then uses its built-in browser to execute real exploits, such as injection attacks, and auth bypass, to prove the vulnerability is actually exploitable.

**What Problem Does Shannon Solve?**

Thanks to tools like Claude Code and Cursor, your team ships code non-stop. But your penetration test? That happens once a year. This creates a *massive* security gap. For the other 364 days, you could be unknowingly shipping vulnerabilities to production.

Shannon closes this gap by acting as your on-demand whitebox pentester. It doesn't just find potential issues. It executes real exploits, providing concrete proof of vulnerabilities. This lets you ship with confidence, knowing every build can be secured.

> [!NOTE]
> **From Autonomous Pentesting to Automated Compliance**
>
> Shannon is a core component of the **Keygraph Security and Compliance Platform**.
>
> While Shannon automates the critical task of penetration testing for your application, our broader platform automates your entire compliance journey—from evidence collection to audit readiness. We're building the "Rippling for Cybersecurity," a single platform to manage your security posture and streamline compliance frameworks like SOC 2 and HIPAA.
>
> ➡️ **[Learn more about the Keygraph Platform](https://keygraph.io)**

## 🎬 See Shannon in Action

**Real Results**: Shannon discovered 20+ critical vulnerabilities in OWASP Juice Shop, including complete auth bypass and database exfiltration. [See full report →](sample-reports/shannon-report-juice-shop.md)

![Demo](assets/shannon-action.gif)

## ✨ Features

- **Fully Autonomous Operation**: Launch the pentest with a single command. The AI handles everything from advanced 2FA/TOTP logins (including sign in with Google) and browser navigation to the final report with zero intervention.
- **Pentester-Grade Reports with Reproducible Exploits**: Delivers a final report focused on proven, exploitable findings, complete with copy-and-paste Proof-of-Concepts to eliminate false positives and provide actionable results.
- **Critical OWASP Vulnerability Coverage**: Currently identifies and validates the following critical vulnerabilities: Injection, XSS, SSRF, and Broken Authentication/Authorization, with more types in development.
- **Code-Aware Dynamic Testing**: Analyzes your source code to intelligently guide its attack strategy, then performs live, browser and command line based exploits on the running application to confirm real-world risk.
- **Powered by Integrated Security Tools**: Enhances its discovery phase by leveraging leading reconnaissance and testing tools—including **Nmap, Subfinder, WhatWeb, and Schemathesis**—for deep analysis of the target environment.
- **Parallel Processing for Faster Results**: Get your report faster. The system parallelizes the most time-intensive phases, running analysis and exploitation for all vulnerability types concurrently.

## 📦 Product Line

Shannon is available in two editions:

| Edition | License | Best For |
|---------|---------|----------|
| **Shannon Lite** | AGPL-3.0 | Security teams, independent researchers, testing your own applications |
| **Shannon Pro** | Commercial | Enterprises requiring advanced features, CI/CD integration, and dedicated support |

> **This repository contains Shannon Lite,** which utilizes our core autonomous AI pentesting framework. **Shannon Pro** enhances this foundation with an advanced, LLM-powered data flow analysis engine (inspired by the [LLMDFA paper](https://arxiv.org/abs/2402.10754)) for enterprise-grade code analysis and deeper vulnerability detection.

> [!IMPORTANT]
> **White-box only.** Shannon Lite is designed for **white-box (source-available)** application security testing.  
> It expects access to your application's source code and repository layout.

[See feature comparison](./SHANNON-PRO.md)
## 📑 Table of Contents

- [What is Shannon?](#-what-is-shannon)
- [See Shannon in Action](#-see-shannon-in-action)
- [Features](#-features)
- [Product Line](#-product-line)
- [Setup & Usage Instructions](#-setup--usage-instructions)
  - [Prerequisites](#prerequisites)
  - [Quick Start](#quick-start)
  - [Monitoring Progress](#monitoring-progress)
  - [Stopping Shannon](#stopping-shannon)
  - [Usage Examples](#usage-examples)
  - [Configuration (Optional)](#configuration-optional)
  - [[EXPERIMENTAL - UNSUPPORTED] Router Mode (Alternative Providers)](#experimental---unsupported-router-mode-alternative-providers)
  - [Output and Results](#output-and-results)
- [Sample Reports](#-sample-reports)
- [Architecture](#️-architecture)
- [Coverage and Roadmap](#-coverage-and-roadmap)
- [Disclaimers](#️-disclaimers)
- [License](#-license)
- [Community & Support](#-community--support)
- [Get in Touch](#-get-in-touch)

---

## 🚀 Setup & Usage Instructions

### Prerequisites

- **Docker** - Container runtime ([Install Docker](https://docs.docker.com/get-docker/))
- **AI Provider Credentials** (choose one):
  - **Anthropic API key** (recommended) - Get from [Anthropic Console](https://console.anthropic.com)
  - **Claude Code OAuth token**
  - **[EXPERIMENTAL - UNSUPPORTED] Alternative providers via Router Mode** - OpenAI or Google Gemini via OpenRouter (see [Router Mode](#experimental---unsupported-router-mode-alternative-providers))

### Quick Start

```bash
# 1. Clone Shannon
git clone https://github.com/KeygraphHQ/shannon.git
cd shannon

# 2. Configure credentials (choose one method)

# Option A: Export environment variables
export ANTHROPIC_API_KEY="your-api-key"              # or CLAUDE_CODE_OAUTH_TOKEN
export CLAUDE_CODE_MAX_OUTPUT_TOKENS=64000           # recommended

# Option B: Create a .env file
cat > .env << 'EOF'
ANTHROPIC_API_KEY=your-api-key
CLAUDE_CODE_MAX_OUTPUT_TOKENS=64000
EOF

# 3. Run a pentest
./shannon start URL=https://your-app.com REPO=/path/to/your/repo
```

Shannon will build the containers, start the workflow, and return a workflow ID. The pentest runs in the background.

### Monitoring Progress

```bash
# View real-time worker logs
./shannon logs

# Query a specific workflow's progress
./shannon query ID=shannon-1234567890

# Open the Temporal Web UI for detailed monitoring
open http://localhost:8233
```

### Stopping Shannon

```bash
# Stop all containers (preserves workflow data)
./shannon stop

# Full cleanup (removes all data)
./shannon stop CLEAN=true
```

### Usage Examples

```bash
# Basic pentest
./shannon start URL=https://example.com REPO=/path/to/repo

# With a configuration file
./shannon start URL=https://example.com REPO=/path/to/repo CONFIG=./configs/my-config.yaml

# Custom output directory
./shannon start URL=https://example.com REPO=/path/to/repo OUTPUT=./my-reports
```

### Prepare Your Repository

Shannon is designed for **web application security testing** and expects all application code to be available in a single directory structure. This works well for:

- **Monorepos** - Single repository containing all components
- **Consolidated setups** - Multiple repositories organized in a shared folder

**For monorepos:**

```bash
git clone https://github.com/your-org/your-monorepo.git /path/to/your-app
```

**For multi-repository applications** (e.g., separate frontend/backend):

```bash
mkdir /path/to/your-app
cd /path/to/your-app
git clone https://github.com/your-org/frontend.git
git clone https://github.com/your-org/backend.git
git clone https://github.com/your-org/api.git
```

### Platform-Specific Instructions

**For Linux (Native Docker):**

You may need to run commands with `sudo` depending on your Docker setup. If you encounter permission issues with output files, ensure your user has access to the Docker socket.

**For macOS:**

Works out of the box with Docker Desktop installed.

**Testing Local Applications:**

Docker containers cannot reach `localhost` on your host machine. Use `host.docker.internal` in place of `localhost`:

```bash
./shannon start URL=http://host.docker.internal:3000 REPO=/path/to/repo
```

### Configuration (Optional)

While you can run without a config file, creating one enables authenticated testing and customized analysis.

#### Create Configuration File

Copy and modify the example configuration:

```bash
cp configs/example-config.yaml configs/my-app-config.yaml
```

#### Basic Configuration Structure

```yaml
authentication:
  login_type: form
  login_url: "https://your-app.com/login"
  credentials:
    username: "test@example.com"
    password: "yourpassword"
    totp_secret: "LB2E2RX7XFHSTGCK"  # Optional for 2FA

  login_flow:
    - "Type $username into the email field"
    - "Type $password into the password field"
    - "Click the 'Sign In' button"

  success_condition:
    type: url_contains
    value: "/dashboard"

rules:
  avoid:
    - description: "AI should avoid testing logout functionality"
      type: path
      url_path: "/logout"

  focus:
    - description: "AI should emphasize testing API endpoints"
      type: path
      url_path: "/api"
```

#### TOTP Setup for 2FA

If your application uses two-factor authentication, simply add the TOTP secret to your config file. The AI will automatically generate the required codes during testing.

### [EXPERIMENTAL - UNSUPPORTED] Router Mode (Alternative Providers)

Shannon can experimentally route requests through alternative AI providers using claude-code-router. This mode is not officially supported and is intended primarily for:

* **Model experimentation** — try Shannon with GPT-5.2 or Gemini 3–family models

#### Quick Setup

1. Add your provider API key to `.env`:

```bash
# Choose one provider:
OPENAI_API_KEY=sk-...
# OR
OPENROUTER_API_KEY=sk-or-...

# Set default model:
ROUTER_DEFAULT=openai,gpt-5.2  # provider,model format
```

2. Run with `ROUTER=true`:

```bash
./shannon start URL=https://example.com REPO=/path/to/repo ROUTER=true
```

#### Experimental Models

| Provider | Models |
|----------|--------|
| OpenAI | gpt-5.2, gpt-5-mini |
| OpenRouter | google/gemini-3-flash-preview |

#### Disclaimer

This feature is experimental and unsupported. Output quality depends heavily on the model. Shannon is built on top of the Anthropic Agent SDK and is optimized and primarily tested with Anthropic Claude models. Alternative providers may produce inconsistent results (including failing early phases like Recon) depending on the model and routing setup.

### Output and Results

All results are saved to `./audit-logs/{hostname}_{sessionId}/` by default. Use `--output <path>` to specify a custom directory.

Output structure:
```
audit-logs/{hostname}_{sessionId}/
├── session.json          # Metrics and session data
├── agents/               # Per-agent execution logs
├── prompts/              # Prompt snapshots for reproducibility
└── deliverables/
    └── comprehensive_security_assessment_report.md   # Final comprehensive security report
```

---

## 📊 Sample Reports

> **Looking for quantitative benchmarks?** [See full benchmark methodology and results →](./xben-benchmark-results/README.md)

See Shannon's capabilities in action with penetration test results from industry-standard vulnerable applications:

#### 🧃 **OWASP Juice Shop** • [GitHub](https://github.com/juice-shop/juice-shop)

*A notoriously insecure web application maintained by OWASP, designed to test a tool's ability to uncover a wide range of modern vulnerabilities.*

**Performance**: Identified **over 20 high-impact vulnerabilities** across targeted OWASP categories in a single automated run.

**Key Accomplishments**:

- **Achieved complete authentication bypass** and exfiltrated the entire user database via Injection attack
- **Executed a full privilege escalation** by creating a new administrator account through a registration workflow bypass
- **Identified and exploited systemic authorization flaws (IDOR)** to access and modify any user's private data and shopping cart
- **Discovered a Server-Side Request Forgery (SSRF)** vulnerability, enabling internal network reconnaissance

📄 **[View Complete Report →](sample-reports/shannon-report-juice-shop.md)**

---

#### 🔗 **c{api}tal API** • [GitHub](https://github.com/Checkmarx/capital)

*An intentionally vulnerable API from Checkmarx, designed to test a tool's ability to uncover the OWASP API Security Top 10.*

**Performance**: Identified **nearly 15 critical and high-severity vulnerabilities**, leading to full application compromise.

**Key Accomplishments**:

- **Executed a root-level Injection attack** by bypassing a denylist via command chaining in a hidden debug endpoint
- **Achieved complete authentication bypass** by discovering and targeting a legacy, unpatched v1 API endpoint
- **Escalated a regular user to full administrator privileges** by exploiting a Mass Assignment vulnerability in the user profile update function
- **Demonstrated high accuracy** by correctly confirming the application's robust XSS defenses, reporting zero false positives

📄 **[View Complete Report →](sample-reports/shannon-report-capital-api.md)**

---

#### 🚗 **OWASP crAPI** • [GitHub](https://github.com/OWASP/crAPI)

*A modern, intentionally vulnerable API from OWASP, designed to benchmark a tool's effectiveness against the OWASP API Security Top 10.*

**Performance**: Identified **over 15 critical and high-severity vulnerabilities**, achieving full application compromise.

**Key Accomplishments**:

- **Bypassed authentication using multiple advanced JWT attacks**, including Algorithm Confusion, alg:none, and weak key (kid) injection
- **Achieved full database compromise via Injection attacks**, exfiltrating user credentials from the PostgreSQL database
- **Executed a critical Server-Side Request Forgery (SSRF) attack** that successfully forwarded internal authentication tokens to an external service
- **Demonstrated high accuracy** by correctly identifying the application's robust XSS defenses, reporting zero false positives

📄 **[View Complete Report →](sample-reports/shannon-report-crapi.md)**

---

*These results demonstrate Shannon's ability to move beyond simple scanning, performing deep contextual exploitation with minimal false positives and actionable proof-of-concepts.*

---

## 🏗️ Architecture

Shannon emulates a human penetration tester's methodology using a sophisticated multi-agent architecture. It combines white-box source code analysis with black-box dynamic exploitation across four distinct phases:

```
                    ┌──────────────────────┐
                    │    Reconnaissance    │
                    └──────────┬───────────┘
                               │
                               ▼
                    ┌──────────┴───────────┐
                    │          │           │
                    ▼          ▼           ▼
        ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
        │ Vuln Analysis   │ │ Vuln Analysis   │ │      ...        │
        │  (Injection)    │ │     (XSS)       │ │                 │
        └─────────┬───────┘ └─────────┬───────┘ └─────────┬───────┘
                  │                   │                   │
                  ▼                   ▼                   ▼
        ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
        │  Exploitation   │ │  Exploitation   │ │      ...        │
        │  (Injection)    │ │     (XSS)       │ │                 │
        └─────────┬───────┘ └─────────┬───────┘ └─────────┬───────┘
                  │                   │                   │
                  └─────────┬─────────┴───────────────────┘
                            │
                            ▼
                    ┌──────────────────────┐
                    │      Reporting       │
                    └──────────────────────┘
```

### Architectural Overview

Shannon is engineered to emulate the methodology of a human penetration tester. It leverages Anthropic's Claude Agent SDK as its core reasoning engine, but its true strength lies in the sophisticated multi-agent architecture built around it. This architecture combines the deep context of **white-box source code analysis** with the real-world validation of **black-box dynamic exploitation**, managed by an orchestrator through four distinct phases to ensure a focus on minimal false positives and intelligent context management.

---

#### **Phase 1: Reconnaissance**

The first phase builds a comprehensive map of the application's attack surface. Shannon analyzes the source code and integrates with tools like Nmap and Subfinder to understand the tech stack and infrastructure. Simultaneously, it performs live application exploration via browser automation to correlate code-level insights with real-world behavior, producing a detailed map of all entry points, API endpoints, and authentication mechanisms for the next phase.

#### **Phase 2: Vulnerability Analysis**

To maximize efficiency, this phase operates in parallel. Using the reconnaissance data, specialized agents for each OWASP category hunt for potential flaws in parallel. For vulnerabilities like Injection and SSRF, agents perform a structured data flow analysis, tracing user input to dangerous sinks. This phase produces a key deliverable: a list of **hypothesized exploitable paths** that are passed on for validation.

#### **Phase 3: Exploitation**

Continuing the parallel workflow to maintain speed, this phase is dedicated entirely to turning hypotheses into proof. Dedicated exploit agents receive the hypothesized paths and attempt to execute real-world attacks using browser automation, command-line tools, and custom scripts. This phase enforces a strict **"No Exploit, No Report"** policy: if a hypothesis cannot be successfully exploited to demonstrate impact, it is discarded as a false positive.

#### **Phase 4: Reporting**

The final phase compiles all validated findings into a professional, actionable report. An agent consolidates the reconnaissance data and the successful exploit evidence, cleaning up any noise or hallucinated artifacts. Only verified vulnerabilities are included, complete with **reproducible, copy-and-paste Proof-of-Concepts**, delivering a final pentest-grade report focused exclusively on proven risks.


## 📋 Coverage and Roadmap

For detailed information about Shannon's security testing coverage and development roadmap, see our [Coverage and Roadmap](./COVERAGE.md) documentation.

## ⚠️ Disclaimers

### Important Usage Guidelines & Disclaimers

Please review the following guidelines carefully before using Shannon (Lite). As a user, you are responsible for your actions and assume all liability.

#### **1. Potential for Mutative Effects & Environment Selection**

This is not a passive scanner. The exploitation agents are designed to **actively execute attacks** to confirm vulnerabilities. This process can have mutative effects on the target application and its data.

> [!WARNING]
> **⚠️ DO NOT run Shannon on production environments.**
>
> - It is

... [README content truncated due to size. Visit the repository for the complete README] ...

]]> TypeScript https://github.com/virattt/dexter https://github.com/virattt/dexter Mon, 09 Feb 2026 00:08:27 GMT virattt/dexter

An autonomous agent for deep financial research

Language: TypeScript

Stars: 12,613

Forks: 1,522

Stars today: 1,039 stars today

README

# Dexter 🤖

Dexter is an autonomous financial research agent that thinks, plans, and learns as it works. It performs analysis using task planning, self-reflection, and real-time market data. Think Claude Code, but built specifically for financial research.

<img width="1098" height="659" alt="Screenshot 2026-01-21 at 5 25 10 PM" src="https://github.com/user-attachments/assets/3bcc3a7f-b68a-4f5e-8735-9d22196ff76e" />

## Table of Contents

- [👋 Overview](#-overview)
- [✅ Prerequisites](#-prerequisites)
- [💻 How to Install](#-how-to-install)
- [🚀 How to Run](#-how-to-run)
- [📊 How to Evaluate](#-how-to-evaluate)
- [🐛 How to Debug](#-how-to-debug)
- [🤝 How to Contribute](#-how-to-contribute)
- [📄 License](#-license)


## 👋 Overview

Dexter takes complex financial questions and turns them into clear, step-by-step research plans. It runs those tasks using live market data, checks its own work, and refines the results until it has a confident, data-backed answer.  

**Key Capabilities:**
- **Intelligent Task Planning**: Automatically decomposes complex queries into structured research steps
- **Autonomous Execution**: Selects and executes the right tools to gather financial data
- **Self-Validation**: Checks its own work and iterates until tasks are complete
- **Real-Time Financial Data**: Access to income statements, balance sheets, and cash flow statements
- **Safety Features**: Built-in loop detection and step limits to prevent runaway execution

[![Twitter Follow](https://img.shields.io/twitter/follow/virattt?style=social)](https://twitter.com/virattt)

<img width="875" height="558" alt="Screenshot 2026-01-21 at 5 22 19 PM" src="https://github.com/user-attachments/assets/72d28363-69ea-4c74-a297-dfa60aa347f7" />


## ✅ Prerequisites

- [Bun](https://bun.com) runtime (v1.0 or higher)
- OpenAI API key (get [here](https://platform.openai.com/api-keys))
- Financial Datasets API key (get [here](https://financialdatasets.ai))
- Exa API key (get [here](https://exa.ai)) - optional, for web search

#### Installing Bun

If you don't have Bun installed, you can install it using curl:

**macOS/Linux:**
```bash
curl -fsSL https://bun.com/install | bash
```

**Windows:**
```bash
powershell -c "irm bun.sh/install.ps1|iex"
```

After installation, restart your terminal and verify Bun is installed:
```bash
bun --version
```

## 💻 How to Install

1. Clone the repository:
```bash
git clone https://github.com/virattt/dexter.git
cd dexter
```

2. Install dependencies with Bun:
```bash
bun install
```

3. Set up your environment variables:
```bash
# Copy the example environment file
cp env.example .env

# Edit .env and add your API keys (if using cloud providers)
# OPENAI_API_KEY=your-openai-api-key
# ANTHROPIC_API_KEY=your-anthropic-api-key (optional)
# GOOGLE_API_KEY=your-google-api-key (optional)
# XAI_API_KEY=your-xai-api-key (optional)
# OPENROUTER_API_KEY=your-openrouter-api-key (optional)

# (Optional) If using Ollama locally
# OLLAMA_BASE_URL=http://127.0.0.1:11434

# Other required keys
# FINANCIAL_DATASETS_API_KEY=your-financial-datasets-api-key

# Web Search (Exa preferred, Tavily fallback)
# EXASEARCH_API_KEY=your-exa-api-key
# TAVILY_API_KEY=your-tavily-api-key
```

## 🚀 How to Run

Run Dexter in interactive mode:
```bash
bun start
```

Or with watch mode for development:
```bash
bun dev
```

## 📊 How to Evaluate

Dexter includes an evaluation suite that tests the agent against a dataset of financial questions. Evals use LangSmith for tracking and an LLM-as-judge approach for scoring correctness.

**Run on all questions:**
```bash
bun run src/evals/run.ts
```

**Run on a random sample of data:**
```bash
bun run src/evals/run.ts --sample 10
```

The eval runner displays a real-time UI showing progress, current question, and running accuracy statistics. Results are logged to LangSmith for analysis.

## 🐛 How to Debug

Dexter logs all tool calls to a scratchpad file for debugging and history tracking. Each query creates a new JSONL file in `.dexter/scratchpad/`.

**Scratchpad location:**
```
.dexter/scratchpad/
├── 2026-01-30-111400_9a8f10723f79.jsonl
├── 2026-01-30-143022_a1b2c3d4e5f6.jsonl
└── ...
```

Each file contains newline-delimited JSON entries tracking:
- **init**: The original query
- **tool_result**: Each tool call with arguments, raw result, and LLM summary
- **thinking**: Agent reasoning steps

**Example scratchpad entry:**
```json
{"type":"tool_result","timestamp":"2026-01-30T11:14:05.123Z","toolName":"get_income_statements","args":{"ticker":"AAPL","period":"annual","limit":5},"result":{...},"llmSummary":"Retrieved 5 years of Apple annual income statements showing revenue growth from $274B to $394B"}
```

This makes it easy to inspect exactly what data the agent gathered and how it interpreted results.

## 🤝 How to Contribute

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

**Important**: Please keep your pull requests small and focused.  This will make it easier to review and merge.


## 📄 License

This project is licensed under the MIT License.

]]> TypeScript https://github.com/likec4/likec4 https://github.com/likec4/likec4 Mon, 09 Feb 2026 00:08:26 GMT likec4/likec4

Visualize, collaborate, and evolve the software architecture with always actual and live diagrams from your code

Language: TypeScript

Stars: 2,340

Forks: 158

Stars today: 271 stars today

README

# Architecture as a code

Visualize, collaborate on, and evolve your software architecture with always up-to-date, live diagrams generated from your code.

[docs](https://likec4.dev/) - [playground](https://playground.likec4.dev/) - [demo](https://template.likec4.dev/view/index)

<a href="https://www.npmjs.com/package/likec4" target="_blank"> ![NPM Version](https://img.shields.io/npm/v/likec4) </a>
<a href="https://www.npmjs.com/package/likec4" target="_blank">![NPM Downloads](https://img.shields.io/npm/dm/likec4)</a>
<a href="https://marketplace.visualstudio.com/items?itemName=likec4.likec4-vscode" target="_blank">![VSCode Installs](https://img.shields.io/visual-studio-marketplace/azure-devops/installs/total/likec4.likec4-vscode?label=vscode%20installs)</a>
<a href="https://open-vsx.org/extension/likec4/likec4-vscode" target="_blank">![Open VSX Installs](https://img.shields.io/open-vsx/dt/likec4/likec4-vscode?label=open-vsx&color=%23A60EE5)</a>

![vscode extension](https://github.com/likec4/likec4/assets/824903/d6994540-55d1-4167-b66b-45056754cc29)

## What is LikeC4? Why "like"?

LikeC4 is a modeling language for describing software architecture and tools to generate diagrams from the model.

LikeC4 is inspired by [C4 Model](https://c4model.com/) and [Structurizr DSL](https://github.com/structurizr/dsl), but provides some flexibility.
You customize or define your own notation, element types, and any number of nested levels in architecture model.\
Perfectly tailored to your needs.

## What does LikeC4 look like?

LikeC4 source:

<div align="center">
  <img src="https://github.com/likec4/.github/assets/824903/c0f22106-dba6-469e-ab47-85e7b8565513" width="675px">
</div>

Run [CLI](./packages/likec4/README.md) to preview:

```sh
npx likec4 start
```

And result:

<div align="center">
  <img src="https://github.com/likec4/likec4/assets/824903/27eabe54-7d97-47a8-a7e4-1bb44a8e03e5" width="984px">
</div>

Template repository - [likec4/template](https://github.com/likec4/template)\
Deployed - [https://template.likec4.dev](https://template.likec4.dev/view/index)

[![Open in StackBlitz](https://developer.stackblitz.com/img/open_in_stackblitz.svg)](https://stackblitz.com/~/github.com/likec4/template)

Check [Tutorial](https://likec4.dev/tutorial/) - for a quick overview of LikeC4.

## Getting help

We are always happy to help you get started:

- [Join Discord community](https://discord.gg/86ZSpjKAdA) – it is the easiest way to get help
- [GitHub Discussions](https://github.com/likec4/likec4/discussions) – ask anything about the project or give feedback

## Contributors

<a href="https://github.com/likec4/likec4/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=likec4/likec4" />
</a>

[Become a contributor](./CONTRIBUTING.md)

## Support development

LikeC4 is a MIT-licensed open source project with its ongoing development made possible entirely by your support.\
If you like the project, please consider contributing financially to help grow and improve it.\
You can support us via [OpenCollective](https://opencollective.com/likec4) or [GitHub Sponsors](https://github.com/sponsors/likec4).

## License

This project is released under the [MIT License](LICENSE)

]]> TypeScript https://github.com/iOfficeAI/AionUi https://github.com/iOfficeAI/AionUi Mon, 09 Feb 2026 00:08:25 GMT iOfficeAI/AionUi

Free, local, open-source 24/7 Cowork and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Language: TypeScript

Stars: 13,152

Forks: 1,010

Stars today: 335 stars today

README

README not available. Either the repository does not have a README or it could not be accessed.

]]> TypeScript https://github.com/linshenkx/prompt-optimizer https://github.com/linshenkx/prompt-optimizer Mon, 09 Feb 2026 00:08:24 GMT linshenkx/prompt-optimizer

一款提示词优化器，助力于编写高质量的提示词

Language: TypeScript

Stars: 20,022

Forks: 2,471

Stars today: 152 stars today

README

# Prompt Optimizer (提示词优化器) 🚀

<div align="center">

[English](README_EN.md) | [中文](README.md)

[![GitHub stars](https://img.shields.io/github/stars/linshenkx/prompt-optimizer)](https://github.com/linshenkx/prompt-optimizer/stargazers)
![Chrome Web Store Users](https://img.shields.io/chrome-web-store/users/cakkkhboolfnadechdlgdcnjammejlna?style=flat&label=Chrome%20Users&link=https%3A%2F%2Fchromewebstore.google.com%2Fdetail%2F%25E6%258F%2590%25E7%25A4%25BA%25E8%25AF%258D%25E4%25BC%2598%25E5%258C%2596%25E5%2599%25A8%2Fcakkkhboolfnadechdlgdcnjammejlna)

<a href="https://trendshift.io/repositories/13813" target="_blank"><img src="https://trendshift.io/api/badge/repositories/13813" alt="linshenkx%2Fprompt-optimizer | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>

[![License](https://img.shields.io/badge/license-AGPL--3.0-blue.svg)](LICENSE)
[![Docker Pulls](https://img.shields.io/docker/pulls/linshen/prompt-optimizer)](https://hub.docker.com/r/linshen/prompt-optimizer)
![GitHub forks](https://img.shields.io/github/forks/linshenkx/prompt-optimizer?style=flat)
[![Deploy with Vercel](https://img.shields.io/badge/Vercel-indigo?style=flat&logo=vercel)](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2Flinshenkx%2Fprompt-optimizer)

[在线体验](https://prompt.always200.com) | [快速开始](#快速开始) | [常见问题](#常见问题) | [Chrome插件](https://chromewebstore.google.com/detail/prompt-optimizer/cakkkhboolfnadechdlgdcnjammejlna) | [💖赞助支持](images/other/sponsor_wx.jpg)

[开发文档](dev.md) | [Vercel部署指南](docs/user/deployment/vercel.md) | [MCP部署使用说明](docs/user/mcp-server.md) | [DeepWiki文档](https://deepwiki.com/linshenkx/prompt-optimizer) | [ZRead文档](https://zread.ai/linshenkx/prompt-optimizer)

</div>

## 📖 项目简介

Prompt Optimizer是一个强大的AI提示词优化工具，帮助你编写更好的AI提示词，提升AI输出质量。支持Web应用、桌面应用、Chrome插件和Docker部署四种使用方式。

### 🎥 功能演示

<div align="center">
  <p><b>1. 角色扮演对话：激发小模型潜力</b></p>
  <p>在追求成本效益的生产或注重隐私的本地化场景中，结构化的提示词能让小模型稳定地进入角色，提供沉浸式、高一致性的角色扮演体验，有效激发其潜力。</p>
  <img src="images/demo/cat-maid-roleplay.png" alt="猫女仆角色扮演演示" width="85%">
  <br>
  <p><b>2. 知识图谱提取：保障生产环境的稳定性</b></p>
  <p>在需要程序化处理的生产环境中，高质量的提示词能显著降低对模型智能程度的要求，使得更经济的小模型也能稳定输出可靠的指定格式。本工具旨在辅助开发者快速达到此目的，从而加速开发、保障稳定，实现降本增效。</p>
  <img src="images/demo/knowledge-graph-extractor.png" alt="知识图谱提取演示" width="85%">
  <br>
  <p><b>3. 诗歌写作：辅助创意探索与需求定制</b></p>
  <p>当面对一个强大的AI，我们的目标不只是得到一个“好”答案，而是得到一个“我们想要的”独特答案。本工具能帮助用户将一个模糊的灵感（如“写首诗”）细化为具体的需求（关于什么主题、何种意象、何种情感），辅助您探索、发掘并精确表达自己的创意，与AI共创独一无二的作品。</p>
  <img src="images/demo/poetry-writing.png" alt="诗歌创作演示" width="85%">
</div>

## ✨ 核心特性

- 🎯 **智能优化**：一键优化提示词，支持多轮迭代改进，提升AI回复准确度
- 📝 **双模式优化**：支持系统提示词优化和用户提示词优化，满足不同使用场景
- 🔄 **对比测试**：支持原始提示词和优化后提示词的实时对比，直观展示优化效果
- 🤖 **多模型集成**：支持OpenAI、Gemini、DeepSeek、智谱AI、SiliconFlow等主流AI模型
- 🖼️ **图像生成**：支持文生图（T2I）和图生图（I2I），集成Gemini、Seedream等图像模型
- 📊 **高级测试模式**：上下文变量管理、多轮会话测试、工具调用（Function Calling）支持
- 🔒 **安全架构**：纯客户端处理，数据直接与AI服务商交互，不经过中间服务器
- 📱 **多端支持**：同时提供Web应用、桌面应用、Chrome插件和Docker部署四种使用方式
- 🔐 **访问控制**：支持密码保护功能，保障部署安全
- 🧩 **MCP协议支持**：支持Model Context Protocol (MCP) 协议，可与Claude Desktop等MCP兼容应用集成

## 🚀 高级功能

### 图像生成模式
- 🖼️ **文生图（T2I）**：通过文本提示词生成图像
- 🎨 **图生图（I2I）**：基于本地图片进行图像变换和优化
- 🔌 **多模型支持**：集成Gemini、Seedream等主流图像生成模型
- ⚙️ **模型参数**：支持各模型特有参数配置（如尺寸、风格等）
- 📥 **预览与下载**：实时预览生成结果，支持下载保存

### 高级测试模式
- 📊 **上下文变量管理**：自定义变量、批量替换、变量预览
- 💬 **多轮会话测试**：模拟真实对话场景，测试提示词在多轮交互中的表现
- 🛠️ **工具调用支持**：Function Calling集成，支持OpenAI和Gemini工具调用
- 🎯 **灵活调试**：更强大的提示词测试和调试能力

详细使用说明请查看 [图像模式文档](docs/image-mode.md)

## 快速开始

### 1. 使用在线版本（推荐）

直接访问：[https://prompt.always200.com](https://prompt.always200.com)

项目是纯前端项目，所有数据只存储在浏览器本地，不会上传至任何服务器，因此直接使用在线版本也是安全可靠的

### 2. Vercel部署
方式1：一键部署到自己的Vercel(方便，但后续无法自动更新)：
   [![部署到 Vercel](https://vercel.com/button)](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2Flinshenkx%2Fprompt-optimizer)

方式2: Fork项目后在Vercel中导入（推荐，但需参考部署文档进行手动设置）：
   - 先Fork项目到自己的GitHub
   - 然后在Vercel中导入该项目
   - 可跟踪源项目更新，便于同步最新功能和修复
- 配置环境变量：
  - `ACCESS_PASSWORD`：设置访问密码，启用访问限制
  - `VITE_OPENAI_API_KEY`等：配置各AI服务商的API密钥

更多详细的部署步骤和注意事项，请查看：
- [Vercel部署指南](docs/user/deployment/vercel.md)

### 3. 下载桌面应用
从 [GitHub Releases](https://github.com/linshenkx/prompt-optimizer/releases) 下载最新版本。我们为各平台提供**安装程序**和**压缩包**两种格式。

- **安装程序 (推荐)**: 如 `*.exe`, `*.dmg`, `*.AppImage` 等。**强烈推荐使用此方式，因为它支持自动更新**。
- **压缩包**: 如 `*.zip`。解压即用，但无法自动更新。

**桌面应用核心优势**:
- ✅ **无跨域限制**：作为原生桌面应用，它能彻底摆脱浏览器跨域（CORS）问题的困扰。这意味着您可以直接连接任何AI服务提供商的API，包括本地部署的Ollama或有严格安全策略的商业API，获得最完整、最稳定的功能体验。
- ✅ **自动更新**：通过安装程序（如 `.exe`, `.dmg`）安装的版本，能够自动检查并更新到最新版。
- ✅ **独立运行**：无需依赖浏览器，提供更快的响应和更佳的性能。

### 4. 安装Chrome插件
1. 从Chrome商店安装（由于审批较慢，可能不是最新的）：[Chrome商店地址](https://chromewebstore.google.com/detail/prompt-optimizer/cakkkhboolfnadechdlgdcnjammejlna)
2. 点击图标即可打开提示词优化器

### 5. Docker部署
<details>
<summary>点击查看 Docker 部署命令</summary>

```bash
# 运行容器（默认配置）
docker run -d -p 8081:80 --restart unless-stopped --name prompt-optimizer linshen/prompt-optimizer

# 运行容器（配置API密钥和访问密码）
docker run -d -p 8081:80 \
  -e VITE_OPENAI_API_KEY=your_key \
  -e ACCESS_USERNAME=your_username \  # 可选，默认为"admin"
  -e ACCESS_PASSWORD=your_password \  # 设置访问密码
  --restart unless-stopped \
  --name prompt-optimizer \
  linshen/prompt-optimizer
```
</details>

> **国内镜像**: 如果Docker Hub访问较慢，可以将上述命令中的 `linshen/prompt-optimizer` 替换为 `registry.cn-guangzhou.aliyuncs.com/prompt-optimizer/prompt-optimizer`

### 6. Docker Compose部署
<details>
<summary>点击查看 Docker Compose 部署步骤</summary>

```bash
# 1. 克隆仓库
git clone https://github.com/linshenkx/prompt-optimizer.git
cd prompt-optimizer

# 2. 可选：创建.env文件配置API密钥和访问认证
cp env.local.example .env
# 编辑 .env 文件，填入实际的 API 密钥和配置

# 3. 启动服务
docker compose up -d

# 4. 查看日志
docker compose logs -f

# 5. 访问服务
Web 界面：http://localhost:8081
MCP 服务器：http://localhost:8081/mcp
```
</details>

你还可以直接编辑docker-compose.yml文件，自定义配置：
<details>
<summary>点击查看 docker-compose.yml 示例</summary>

```yaml
services:
  prompt-optimizer:
    # 使用Docker Hub镜像
    image: linshen/prompt-optimizer:latest
    # 或使用阿里云镜像（国内用户推荐）
    # image: registry.cn-guangzhou.aliyuncs.com/prompt-optimizer/prompt-optimizer:latest
    container_name: prompt-optimizer
    restart: unless-stopped
    ports:
      - "8081:80"  # Web应用端口（包含MCP服务器，通过/mcp路径访问）
    environment:
      # API密钥配置
      - VITE_OPENAI_API_KEY=your_openai_key
      - VITE_GEMINI_API_KEY=your_gemini_key
      # 访问控制（可选）
      - ACCESS_USERNAME=admin
      - ACCESS_PASSWORD=your_password
```
</details>

### 7. MCP Server 使用说明
<details>
<summary>点击查看 MCP Server 使用说明</summary>

Prompt Optimizer 现在支持 Model Context Protocol (MCP) 协议，可以与 Claude Desktop 等支持 MCP 的 AI 应用集成。

当通过 Docker 运行时，MCP Server 会自动启动，并可通过 `http://ip:port/mcp` 访问。

#### 环境变量配置

MCP Server 需要配置 API 密钥才能正常工作。主要的 MCP 专属配置：

```bash
# MCP 服务器配置
MCP_DEFAULT_MODEL_PROVIDER=openai  # 可选值：openai, gemini, deepseek, siliconflow, zhipu, custom
MCP_LOG_LEVEL=info                 # 日志级别
```

#### Docker 环境下使用 MCP

在 Docker 环境中，MCP Server 会与 Web 应用一起运行，您可以通过 Web 应用的相同端口访问 MCP 服务，路径为 `/mcp`。

例如，如果您将容器的 80 端口映射到主机的 8081 端口：
```bash
docker run -d -p 8081:80 \
  -e VITE_OPENAI_API_KEY=your-openai-key \
  -e MCP_DEFAULT_MODEL_PROVIDER=openai \
  --name prompt-optimizer \
  linshen/prompt-optimizer
```

那么 MCP Server 将可以通过 `http://localhost:8081/mcp` 访问。

#### Claude Desktop 集成示例

要在 Claude Desktop 中使用 Prompt Optimizer，您需要在 Claude Desktop 的配置文件中添加服务配置。

1. 找到 Claude Desktop 的配置目录：
   - Windows: `%APPDATA%\Claude\services`
   - macOS: `~/Library/Application Support/Claude/services`
   - Linux: `~/.config/Claude/services`

2. 编辑或创建 `services.json` 文件，添加以下内容：

```json
{
  "services": [
    {
      "name": "Prompt Optimizer",
      "url": "http://localhost:8081/mcp"
    }
  ]
}
```

请确保将 `localhost:8081` 替换为您实际部署 Prompt Optimizer 的地址和端口。

#### 可用工具

- **optimize-user-prompt**: 优化用户提示词以提高 LLM 性能
- **optimize-system-prompt**: 优化系统提示词以提高 LLM 性能
- **iterate-prompt**: 对已经成熟/完善的提示词进行定向迭代优化

更多详细信息，请查看 [MCP 服务器用户指南](docs/user/mcp-server.md)。
</details>

## ⚙️ API密钥配置

<details>
<summary>点击查看API密钥配置方法</summary>

### 方式一：通过界面配置（推荐）
1. 点击界面右上角的"⚙️设置"按钮
2. 选择"模型管理"选项卡
3. 点击需要配置的模型（如OpenAI、Gemini、DeepSeek等）
4. 在弹出的配置框中输入对应的API密钥
5. 点击"保存"即可

支持的模型：OpenAI、Gemini、DeepSeek、Zhipu智谱、SiliconFlow、自定义API（OpenAI兼容接口）

除了API密钥，您还可以在模型配置界面为每个模型单独设置高级LLM参数。这些参数通过一个名为 `llmParams` 的字段进行配置，它允许您以键值对的形式指定LLM SDK支持的任何参数，从而更精细地控制模型行为。

**高级LLM参数配置示例：**
- **OpenAI/兼容API**: `{"temperature": 0.7, "max_tokens": 4096, "timeout": 60000}`
- **Gemini**: `{"temperature": 0.8, "maxOutputTokens": 2048, "topP": 0.95}`
- **DeepSeek**: `{"temperature": 0.5, "top_p": 0.9, "frequency_penalty": 0.1}`

有关 `llmParams` 的更详细说明和配置指南，请参阅 [LLM参数配置指南](docs/developer/llm-params-guide.md)。

### 方式二：通过环境变量配置
Docker部署时通过 `-e` 参数配置环境变量：

```bash
-e VITE_OPENAI_API_KEY=your_key
-e VITE_GEMINI_API_KEY=your_key
-e VITE_DEEPSEEK_API_KEY=your_key
-e VITE_ZHIPU_API_KEY=your_key
-e VITE_SILICONFLOW_API_KEY=your_key

# 多自定义模型配置（支持无限数量）
-e VITE_CUSTOM_API_KEY_ollama=dummy_key
-e VITE_CUSTOM_API_BASE_URL_ollama=http://localhost:11434/v1
-e VITE_CUSTOM_API_MODEL_ollama=qwen2.5:7b
```

> 📖 **详细配置指南**: 查看 [多自定义模型配置文档](./docs/user/multi-custom-models.md) 了解完整的配置方法和高级用法

</details>

## 本地开发
详细文档可查看 [开发文档](dev.md)

<details>
<summary>点击查看本地开发命令</summary>

```bash
# 1. 克隆项目
git clone https://github.com/linshenkx/prompt-optimizer.git
cd prompt-optimizer

# 2. 安装依赖
pnpm install

# 3. 启动开发服务
pnpm dev               # 主开发命令：构建core/ui并运行web应用
pnpm dev:web          # 仅运行web应用
pnpm dev:fresh        # 完整重置并重新启动开发环境
```
</details>

## 🗺️ 开发路线

- [x] 基础功能开发
- [x] Web应用发布
- [x] Chrome插件发布
- [x] 国际化支持
- [x] 支持系统提示词优化和用户提示词优化
- [x] 桌面应用发布
- [x] MCP服务发布
- [x] 高级模式：变量管理、上下文测试、工具调用
- [x] 图像生成：文生图（T2I）和图生图（I2I）支持
- [ ] 支持工作区/项目管理
- [ ] 支持提示词收藏和模板管理

详细的项目状态可查看 [项目状态文档](docs/project-status.md)

## 📖 相关文档

- [文档索引](docs/README.md) - 所有文档的索引
- [技术开发指南](docs/developer/technical-development-guide.md) - 技术栈和开发规范
- [LLM参数配置指南](docs/developer/llm-params-guide.md) - 高级LLM参数配置详细说明
- [项目结构](docs/developer/project-structure.md) - 详细的项目结构说明
- [项目状态](docs/project/project-status.md) - 当前进度和计划
- [产品需求](docs/project/prd.md) - 产品需求文档
- [Vercel部署指南](docs/user/deployment/vercel.md) - Vercel部署详细说明


## Star History

<a href="https://star-history.com/#linshenkx/prompt-optimizer&Date">
 <picture>
   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=linshenkx/prompt-optimizer&type=Date&theme=dark" />
   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=linshenkx/prompt-optimizer&type=Date" />
   <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=linshenkx/prompt-optimizer&type=Date" />
 </picture>
</a>

## 常见问题

<details>
<summary>点击查看常见问题解答</summary>

### API连接问题

#### Q1: 为什么配置好API密钥后仍然无法连接到模型服务？
**A**: 大多数连接失败是由**跨域问题**（CORS）导致的。由于本项目是纯前端应用，浏览器出于安全考虑会阻止直接访问不同源的API服务。模型服务如未正确配置CORS策略，会拒绝来自浏览器的直接请求。

#### Q2: 如何解决本地Ollama的连接问题？
**A**: Ollama完全支持OpenAI标准接口，只需配置正确的跨域策略：
1. 设置环境变量 `OLLAMA_ORIGINS=*` 允许任意来源的请求
2. 如仍有问题，设置 `OLLAMA_HOST=0.0.0.0:11434` 监听任意IP地址

#### Q3: 如何解决商业API（如Nvidia的DS API、字节跳动的火山API）的跨域问题？
**A**: 这些平台通常有严格的跨域限制，推荐以下解决方案：

1. **使用桌面版应用**（最推荐）
   - 桌面应用作为原生应用，完全没有跨域限制
   - 可以直接连接任何API服务，包括本地部署的模型
   - 提供最完整、最稳定的功能体验
   - 从 [GitHub Releases](https://github.com/linshenkx/prompt-optimizer/releases) 下载

2. **使用自部署的API中转服务**（专业方案）
   - 部署如OneAPI、NewAPI等开源API聚合/代理工具
   - 在设置中配置为自定义API端点
   - 请求流向：浏览器→中转服务→模型服务提供商
   - 完全控制安全策略和访问权限

**注意**：Web版（包括在线版、Vercel部署、Docker部署）都是纯前端应用，都会受到浏览器CORS限制。只有桌面版或使用API中转服务才能解决跨域问题。

#### Q4: 我已正确配置本地模型（如Ollama）的跨域策略，为什么使用在线版依然无法连接？
**A**: 这是由浏览器的**混合内容（Mixed Content）安全策略**导致的。出于安全考虑，浏览器会阻止安全的HTTPS页面（如在线版）向不安全的HTTP地址（如您的本地Ollama服务）发送请求。

**解决方案**：
为了绕过此限制，您需要让应用和API处于同一种协议下（例如，都是HTTP）。推荐以下方式：
1. **使用桌面版**：桌面应用没有浏览器限制，是连接本地模型最稳定可靠的方式
2. **使用Docker部署（HTTP）**：通过 `http://localhost:8081` 访问，与本地Ollama都是HTTP
3. **使用Chrome插件**：插件在某些情况下也可以绕过部分安全限制

### macOS 桌面应用问题

#### Q5: macOS 打开应用时提示「已损坏」或「无法验证开发者」怎么办？
**A**: 这是因为应用未经过 Apple 签名认证。由于 Apple 开发者账号费用较高，目前桌面应用暂未进行签名。

**解决方案**：
在终端中执行以下命令移除安全隔离属性：

```bash
# 对于已安装的应用
xattr -rd com.apple.quarantine /Applications/PromptOptimizer.app

# 对于下载的 .dmg 文件（安装前执行）
xattr -rd com.apple.quarantine ~/Downloads/PromptOptimizer-*.dmg
```

执行后重新打开应用即可正常使用。

</details>


## 🤝 参与贡献

<details>
<summary>点击查看贡献指南</summary>

1. Fork 本仓库
2. 创建特性分支 (`git checkout -b feature/AmazingFeature`)
3. 提交更改 (`git commit -m '添加某个特性'`)
4. 推送到分支 (`git push origin feature/AmazingFeature`)
5. 提交 Pull Request

提示：使用cursor工具开发时，建议在提交前:
1. 使用"code_review"规则进行代码审查
2. 按照审查报告格式检查:
   - 变更的整体一致性
   - 代码质量和实现方式
   - 测试覆盖情况
   - 文档完善程度
3. 根据审查结果进行优化后再提交

</details>

## 👏 贡献者名单

感谢所有为项目做出贡献的开发者！

<a href="https://github.com/linshenkx/prompt-optimizer/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=linshenkx/prompt-optimizer" alt="贡献者" />
</a>

## 📄 开源协议

本项目采用 [AGPL-3.0](LICENSE) 协议开源。

**简单来说**：你可以自由使用、修改和商用本项目，但如果你把它做成网站或服务给别人用，需要公开你的源代码。

<details>
<summary>👉 点击查看详细说明</summary>

**允许做什么：**
- ✅ 个人使用、学习、研究
- ✅ 公司内部使用（不对外提供服务）
- ✅ 修改代码并用于商业项目
- ✅ 收费销售或提供服务

**需要做什么：**
- 📖 如果分发软件或提供网络服务，必须公开源代码
- 📝 保留原作者的版权声明

**一句话核心**：可以商用，但不能闭源。

</details>

---

如果这个项目对你有帮助，请考虑给它一个 Star ⭐️

## 👥 联系我们

- 提交 Issue
- 发起 Pull Request
- 加入讨论组

]]> TypeScript https://github.com/actualbudget/actual https://github.com/actualbudget/actual Mon, 09 Feb 2026 00:08:23 GMT actualbudget/actual

A local-first personal finance app

Language: TypeScript

Stars: 24,829

Forks: 2,144

Stars today: 49 stars today

README

<p align="center">
  <img src="/demo.png" alt="Actualbudget" />
</p>

## Getting Started

Actual is a local-first personal finance tool. It is 100% free and open-source, written in NodeJS, it has a synchronization element so that all your changes can move between devices without any heavy lifting.

If you are interested in contributing, or want to know how development works, see our [contributing](https://actualbudget.org/docs/contributing/) document we would love to have you.

Want to say thanks? Click the ⭐ at the top of the page.

## Key Links

- Actual [discord](https://discord.gg/pRYNYr4W5A) community.
- Actual [Community Documentation](https://actualbudget.org/docs)
- [Frequently asked questions](https://actualbudget.org/docs/faq)

## Installation

There are four ways to deploy Actual:

1. One-click deployment [via PikaPods](https://www.pikapods.com/pods?run=actual) (~1.40 $/month) - recommended for non-technical users
1. Managed hosting [via Fly.io](https://actualbudget.org/docs/install/fly) (~1.50 $/month)
1. Self-hosted by using [a Docker image](https://actualbudget.org/docs/install/docker)
1. Local-only apps - [downloadable Windows, Mac and Linux apps](https://actualbudget.org/download/) you can run on your device

Learn more in the [installation instructions docs](https://actualbudget.org/docs/install/).

## Ready to Start Budgeting?

Read about [Envelope budgeting](https://actualbudget.org/docs/getting-started/envelope-budgeting) to know more about the idea behind Actual Budget.

### Are you new to budgeting or want to start fresh?

Check out the community's [Starting Fresh](https://actualbudget.org/docs/getting-started/starting-fresh) guide so you can quickly get up and running!

### Are you migrating from other budgeting apps?

Check out the community's [Migration](https://actualbudget.org/docs/migration/) guide to start jumping on the Actual Budget train!

## Documentation

We have a wide range of documentation on how to use Actual, this is all available in our [Community Documentation](https://actualbudget.org/docs), this includes topics on Budgeting, Account Management, Tips & Tricks and some documentation for developers.

## Contributing

Actual is a community driven product. Learn more about [contributing to Actual](https://actualbudget.org/docs/contributing/).

### Code structure

The Actual app is split up into a few packages:

- loot-core - The core application that runs on any platform
- desktop-client - The desktop UI
- desktop-electron - The desktop app

More information on the project structure is available in our [community documentation](https://actualbudget.org/docs/contributing/project-details).

### Feature Requests

Current feature requests can be seen [here](https://github.com/actualbudget/actual/issues?q=is%3Aissue+label%3A%22needs+votes%22+sort%3Areactions-%2B1-desc).
Vote for your favorite requests by reacting :+1: to the top comment of the request.

To add new feature requests, open a new Issue of the "Feature Request" type.

### Translation

Make Actual Budget accessible to more people by helping with the [Internationalization](https://actualbudget.org/docs/contributing/i18n/) of Actual. We are using a crowd sourcing tool to manage the translations, see our [Weblate Project](https://hosted.weblate.org/projects/actualbudget/). Weblate proudly supports open-source software projects through their [Libre plan](https://weblate.org/en/hosting/#libre).

<a href="https://hosted.weblate.org/engage/actualbudget/">
<img src="https://hosted.weblate.org/widget/actualbudget/actual/287x66-grey.png" alt="Translation status" />
</a>

## Repo Activity

![Alt](https://repobeats.axiom.co/api/embed/e20537dd8b74956f86736726ccfbc6f0565bec22.svg 'Repobeats analytics image')

## Sponsors

Thanks to our wonderful sponsors who make Actual Budget possible!

<a href="https://www.netlify.com"> <img src="https://www.netlify.com/v3/img/components/netlify-color-accent.svg" alt="Deploys by Netlify" /> </a>

]]> TypeScript https://github.com/fosrl/pangolin https://github.com/fosrl/pangolin Mon, 09 Feb 2026 00:08:22 GMT fosrl/pangolin

Identity-aware VPN and proxy for remote access to anything, anywhere.

Language: TypeScript

Stars: 18,704

Forks: 559

Stars today: 64 stars today

README

<div align="center">
    <h2>
    <a href="https://pangolin.net/">
        <picture>
            <source media="(prefers-color-scheme: dark)" srcset="public/logo/word_mark_white.png">
            <img alt="Pangolin Logo" src="public/logo/word_mark_black.png" width="350">
        </picture>
    </a>
    </h2>
</div>

<div align="center">
  <h5>
      <a href="https://pangolin.net/">
        Website
      </a>
      <span> | </span>
      <a href="https://docs.pangolin.net/">
        Documentation
      </a>
      <span> | </span>
      <a href="mailto:contact@pangolin.net">
        Contact Us
      </a>
  </h5>
</div>

<div align="center">

[![Discord](https://img.shields.io/discord/1325658630518865980?logo=discord&style=flat-square)](https://discord.gg/HCJR8Xhme4)
[![Slack](https://img.shields.io/badge/chat-slack-yellow?style=flat-square&logo=slack)](https://pangolin.net/slack)
[![Docker](https://img.shields.io/docker/pulls/fosrl/pangolin?style=flat-square)](https://hub.docker.com/r/fosrl/pangolin)
![Stars](https://img.shields.io/github/stars/fosrl/pangolin?style=flat-square)
[![YouTube](https://img.shields.io/badge/YouTube-red?logo=youtube&logoColor=white&style=flat-square)](https://www.youtube.com/@pangolin-net)

</div>

<p align="center">
    <a href="https://docs.pangolin.net/careers/join-us">
        <img src="https://img.shields.io/badge/🚀_We're_Hiring!-Join_Our_Team-brightgreen?style=for-the-badge" alt="We're Hiring!" />
    </a>
</p>

<p align="center">
    <strong>
        Start testing Pangolin at <a href="https://app.pangolin.net/auth/signup">app.pangolin.net</a>
    </strong>
</p>

Pangolin is an open-source, identity-based remote access platform built on WireGuard that enables secure, seamless connectivity to private and public resources. Pangolin combines reverse proxy and VPN capabilities into one platform, providing browser-based access to web applications and client-based access to any private resources, all with zero-trust security and granular access control.

## Installation

- Check out the [quick install guide](https://docs.pangolin.net/self-host/quick-install) for how to install and set up Pangolin.
- Install from the [DigitalOcean marketplace](https://marketplace.digitalocean.com/apps/pangolin-ce-1?refcode=edf0480eeb81) for a one-click pre-configured installer.

<img src="public/screenshots/hero.png" />

## Deployment Options

| <img width=500 /> | Description |
|-----------------|--------------|
| **Self-Host: Community Edition** | Free, open source, and licensed under AGPL-3. |
| **Self-Host: Enterprise Edition** | Licensed under Fossorial Commercial License. Free for personal and hobbyist use, and for businesses earning under \$100K USD annually. |
| **Pangolin Cloud** | Fully managed service with instant setup and pay-as-you-go pricing — no infrastructure required. Or, self-host your own [remote node](https://docs.pangolin.net/manage/remote-node/nodes) and connect to our control plane. |

## Key Features

| <img width=500 />                                                                                                                                                                                                                                                                                                                                                                | <img width=500 />                                                  |
|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------|
| **Connect remote networks with sites**<br /><br />Pangolin's lightweight site connectors create secure tunnels from remote networks without requiring public IP addresses or open ports. Sites make any network anywhere available for authorized access.                                                                                                                                                                                   | <img src="public/screenshots/sites.png" width=500 /><tr></tr>               |
| **Browser-based reverse proxy access**<br /><br />Expose web applications through identity and context-aware tunneled reverse proxies. Pangolin handles routing, load balancing, health checking, and automatic SSL certificates without exposing your network directly to the internet. Users access applications through any web browser with authentication and granular access control.                                                                                                  | <img src="public/clip.gif" width=500 /><tr></tr>          |
| **Client-based private resource access**<br /><br />Access private resources like SSH servers, databases, RDP, and entire network ranges through Pangolin clients. Intelligent NAT traversal enables connections even through restrictive firewalls, while DNS aliases provide friendly names and fast connections to resources across all your sites.                                                                                                                                                                                                | <img src="public/screenshots/private-resources.png" width=500 /><tr></tr>               |
| **Zero-trust granular access**<br /><br />Grant users access to specific resources, not entire networks. Unlike traditional VPNs that expose full network access, Pangolin's zero-trust model ensures users can only reach the applications and services you explicitly define, reducing security risk and attack surface.                                                                                                                                                                                    | <img src="public/screenshots/user-devices.png" width=500 /><tr></tr> |

## Download Clients

Download the Pangolin client for your platform:

- [Mac](https://pangolin.net/downloads/mac)
- [Windows](https://pangolin.net/downloads/windows)
- [Linux](https://pangolin.net/downloads/linux)
- [iOS](https://pangolin.net/downloads/ios)
- [Android](https://pangolin.net/downloads/android)

## Get Started

### Check out the docs

We encourage everyone to read the full documentation first, which is
available at [docs.pangolin.net](https://docs.pangolin.net). This README provides only a very brief subset of
the docs to illustrate some basic ideas.

### Sign up and try now

For Pangolin's managed service, you will first need to create an account at
[app.pangolin.net](https://app.pangolin.net). We have a generous free tier to get started.

## Licensing

Pangolin is dual licensed under the AGPL-3 and the [Fossorial Commercial License](https://pangolin.net/fcl.html). For inquiries about commercial licensing, please contact us at [contact@pangolin.net](mailto:contact@pangolin.net).

## Contributions

Please see [CONTRIBUTING](./CONTRIBUTING.md) in the repository for guidelines and best practices.

---

WireGuard® is a registered trademark of Jason A. Donenfeld.

]]> TypeScript https://github.com/eigent-ai/eigent https://github.com/eigent-ai/eigent Mon, 09 Feb 2026 00:08:21 GMT eigent-ai/eigent

Eigent: The Open Source Cowork Desktop to Unlock Your Exceptional Productivity.

Language: TypeScript

Stars: 12,133

Forks: 1,396

Stars today: 69 stars today

README

<div align="center"><a name="readme-top"></a>

[![][image-head]][eigent-site]

[![][image-seperator]][eigent-site]

### Eigent: The Open Source Cowork Desktop to Unlock Your Exceptional Productivity

<!-- SHIELD GROUP -->

[![][download-shield]][eigent-download]
[![][github-star]][eigent-github]
[![][social-x-shield]][social-x-link]
[![][discord-image]][discord-url]<br>
[![Reddit][reddit-image]][reddit-url]
[![Wechat][wechat-image]][wechat-url]
[![][sponsor-shield]][sponsor-link]
[![][built-with-camel]][camel-github]
[![][join-us-image]][join-us]

</div>

<hr/>
<div align="center">

**English** · [Português](./README_PT-BR.md) · [简体中文](./README_CN.md) · [日本語](./README_JA.md) · [Official Site][eigent-site] · [Documents][docs-site] · [Feedback][github-issue-link]

</div>
<br/>

**Eigent** is the open source Cowork desktop application, empowering you to build, manage, and deploy a custom AI workforce that can turn your most complex workflows into automated tasks. As a leading open-source Cowork product, Eigent brings together the best of open-source collaboration and AI-powered automation.

Built on [CAMEL-AI][camel-site]'s acclaimed open-source project, our system introduces a **Multi-Agent Workforce** that **boosts productivity** through parallel execution, customization, and privacy protection.

### ⭐ 100% Open Source - 🥇 Local Deployment - 🏆 MCP Integration

- ✅ **Zero Setup** - No technical configuration required
- ✅ **Multi-Agent Coordination** - Handle complex multi-agent workflows
- ✅ **Enterprise Feature** - SSO/Access control
- ✅ **Local Deploymen**t
- ✅ **Open Source**
- ✅ **Custom Model Support**
- ✅ **MCP Integration**

<br/>

[![][image-join-us]][join-us]

<details>
<summary><kbd>Table of contents</kbd></summary>

#### TOC

- [🚀 Getting Started with Open Source Cowork](#-getting-started-with-open-source-Cowork)
  - [🏠 Local Deployment (Recommended)](#-local-deployment-recommended)
  - [⚡ Quick Start (Cloud-Connected)](#-quick-start-cloud-connected)
  - [🏢 Enterprise](#-enterprise)
  - [☁️ Cloud Version](#%EF%B8%8F-cloud-version)
- [✨ Key features - Open Source Cowork](#-key-features---open-source-Cowork)
  - [🏭 Workforce](#-workforce)
  - [🧠 Comprehensive Model Support](#-comprehensive-model-support)
  - [🔌 MCP Tools Integration (MCP)](#-mcp-tools-integration-mcp)
  - [✋ Human-in-the-Loop](#-human-in-the-loop)
  - [👐 100% Open Source](#-100-open-source)
- [🧩 Use Cases - Open Source Cowork](#-use-cases---open-source-Cowork)
- [🛠️ Tech Stack](#-tech-stack)
  - [Backend](#backend)
  - [Frontend](#frontend)
- [🌟 Staying ahead - Open Source Cowork](#-staying-ahead---open-source-Cowork)
- [🗺️ Roadmap - Open Source Cowork](#%EF%B8%8F-roadmap---open-source-Cowork)
- [📖 Contributing](#-contributing)
  - [Main Contributors](#main-contributors)
  - [Distinguished amabssador](#distinguished-amabssador)
- [Ecosystem](#ecosystem)
- [📄 Open Source License](#-open-source-license)
- [🌐 Community & contact](#-community--contact)

#### 

<br/>

</details>

## **🚀 Getting Started with Open Source Cowork**

> **🔓 Build in Public** — Eigent is **100% open source** from day one. Every feature, every commit, every decision is transparent. We believe the best AI tools should be built openly with the community, not behind closed doors.

### 🏠 Local Deployment (Recommended)

The recommended way to run Eigent — fully standalone with complete control over your data, no cloud account required.

👉 **[Full Local Deployment Guide](./server/README_EN.md)**

This setup includes:

- Local backend server with full API
- Local model integration (vLLM, Ollama, LM Studio, etc.)
- Complete isolation from cloud services
- Zero external dependencies

### ⚡ Quick Start (Cloud-Connected)

For a quick preview using our cloud backend — get started in seconds:

#### Prerequisites

- Node.js (version 18-22) and npm

#### Steps

```bash
git clone https://github.com/eigent-ai/eigent.git
cd eigent
npm install
npm run dev
```

> Note: This mode connects to Eigent cloud services and requires account registration. For a fully standalone experience, use [Local Deployment](#-local-deployment-recommended) instead.

#### Updating Dependencies

After pulling new code (`git pull`), update both frontend and backend dependencies:

```bash
# 1. Update frontend dependencies (in project root)
npm install

# 2. Update backend/Python dependencies (in backend directory)
cd backend
uv sync
```

### 🏢 Enterprise

For organizations requiring maximum security, customization, and control:

- **Exclusive Features** (like SSO & custom development)
- **Scalable Enterprise Deployment**
- **Negotiated SLAs** & implementation services

📧 For further details, please contact us at [info@eigent.ai](mailto:info@eigent.ai).

### ☁️ Cloud Version

For teams who prefer managed infrastructure, we also offer a cloud platform. The fastest way to experience Eigent's multi-agent AI capabilities without setup complexity. We'll host the models, APIs, and cloud storage, ensuring Eigent runs flawlessly.

- **Instant Access** - Start building multi-agent workflows in minutes.
- **Managed Infrastructure** - We handle scaling, updates, and maintenance.
- **Premium Support** - Subscribe and get priority assistance from our engineering team.

<br/>

[![image-public-beta]][eigent-download]

<div align="right">
<a href="https://www.eigent.ai/download">Get started at Eigent.ai →</a>
</div>

## **✨ Key features - Open Source Cowork**

Unlock the full potential of exceptional productivity with Eigent's open-source Cowork powerful features — built for seamless integration, smarter task execution, and boundless automation.

### 🏭 Workforce

Employs a team of specialized AI agents that collaborate to solve complex tasks. Eigent's open-source Cowork dynamically breaks down tasks and activates multiple agents to work **in parallel.**

Eigent pre-defined the following agent workers:

- **Developer Agent:** Writes and executes code, runs terminal commands.
- **Browser Agent:** Searches the web and extracts content.
- **Document Agent:** Creates and manages documents.
- **Multi-Modal Agent:** Processes images and audio.

![Workforce](https://eigent-ai.github.io/.github/assets/gif/feature_dynamic_workforce.gif)

<br/>

### 🧠 Comprehensive Model Support

Deploy the Eigent open-source Cowork desktop locally with your preferred models.

![Model](https://eigent-ai.github.io/.github/assets/gif/feature_local_model.gif)

<br/>

### 🔌 MCP Tools Integration (MCP)

Eigent comes with massive built-in **Model Context Protocol (MCP)** tools (for web browsing, code execution, Notion, Google suite, Slack etc.), and also lets you **install your own tools**. Equip agents with exactly the right tools for your scenarios – even integrate internal APIs or custom functions – to enhance their capabilities.

![MCP](https://eigent-ai.github.io/.github/assets/gif/feature_add_mcps.gif)

<br/>

### ✋ Human-in-the-Loop

If a task gets stuck or encounters uncertainty, Eigent will automatically request human input.

![Human-in-the-loop](https://eigent-ai.github.io/.github/assets/gif/feature_human_in_the_loop.gif)

<br/>

### 👐 100% Open Source

Eigent is completely open-sourced. You can download, inspect, and modify the code, ensuring transparency and fostering a community-driven ecosystem for multi-agent innovation.

![Opensource][image-opensource]

<br/>

## 🧩 Use Cases - Open Source Cowork

Discover how developers worldwide leverage Eigent's open-source Cowork capabilities to automate complex workflows and boost productivity across diverse industries.

### 1. Palm Springs Tennis Trip Itinerary with Slack Summary [Replay ▶️](https://www.eigent.ai/download?share_token=IjE3NTM0MzUxNTEzMzctNzExMyI.aIeysw.MUeG6ZcBxI1GqvPDvn4dcv-CDWw__1753435151337-7113)

<details>
<summary><strong>Prompt:</strong> <kbd>We are two tennis fans and want to go see the tennis tournament ... <kbd></summary>
<br>
We are two tennis fans and want to go see the tennis tournament in Palm Springs 2026. I live in SF - please prepare a detailed itinerary with flights, hotels, things to do for 3 days - around the time semifinal/finals are happening. We like hiking, vegan food and spas. Our budget is $5K. The itinerary should be a detailed timeline of time, activity, cost, other details and if applicable a link to buy tickets/make reservations etc. for the item. Some preferences .Spa access would be nice but not necessary. When you finish this task, please generate a html report about this trip; write a summary of this plan and send text summary and report html link to slack #tennis-trip-sf channel.
</details>

<br>

### 2. Generate Q2 Report from CSV Bank Data [Replay ▶️](https://www.eigent.ai/download?share_token=IjE3NTM1MjY4OTE4MDgtODczOSI.aIjJmQ.WTdoX9mATwrcBr_w53BmGEHPo8U__1753526891808-8739)

<details>
<summary><strong>Prompt:</strong> <kbd>Please help me prepare a Q2 financial statement based on my bank ... <kbd></summary>
<br>
Please help me prepare a Q2 financial statement based on my bank transfer record file bank_transacation.csv in my desktop to a html report with chart to investors how much we have spent.
</details>

<br>

### 3. UK Healthcare Market Research Report Automation [Replay ▶️](https://www.eigent.ai/download?share_token=IjE3NTMzOTM1NTg3OTctODcwNyI.aIey-Q.Jh9QXzYrRYarY0kz_qsgoj3ewX0__1753393558797-8707)

<details>
<summary><strong>Prompt:</strong> <kbd>Analyze the UK healthcare industry to support the planning ... <kbd></summary>
<br>
Analyze the UK healthcare industry to support the planning of my next company. Provide a comprehensive market overview, including current trends, growth projections, and relevant regulations. Identify the top 5–10 major opportunities, gaps, or underserved segments within the market. Present all findings in a well-structured, professional HTML report. Then send a message to slack #eigentr-product-test channel when this task is done to align the report content with my teammates.
</details>

<br>

### 4. German Electric Skateboard Market Feasibility [Replay ▶️](https://www.eigent.ai/download?share_token=IjE3NTM2NTI4MjY3ODctNjk2Ig.aIjGiA.t-qIXxk_BZ4ENqa-yVIm0wMVyXU__1753652826787-696)

<details>
<summary><strong>Prompt:</strong> <kbd>We are a company that produces high-end electric skateboards ... <kbd></summary>
<br>
We are a company that produces high-end electric skateboards, and we are considering entering the German market. Please prepare a detailed market entry feasibility report for me. The report needs to cover the following aspects:
1. Market Size & Regulations: Research the market size, annual growth rate, key players, and market share for Personal Light Electric Vehicles (PLEVs) in Germany. Simultaneously, provide a detailed breakdown and summary of German laws and regulations concerning the use of electric skateboards on public roads, including certification requirements (such as ABE certification) and insurance policies.
2. Consumer Profile: Analyze the profile of potential German consumers, including their age, income level, primary usage scenarios (commuting, recreation), key purchasing decision drivers (price, performance, brand, design), and the channels they typically use to gather information (forums, social media, offline retail stores).
3. Channels & Distribution: Investigate Germany’s mainstream online electronics sales platforms (e.g., Amazon.de, MediaMarkt.de) and high-end sporting goods offline retail chains. List the top 5 potential online and offline distribution partners and find the contact information for their purchasing departments, if possible.
4. Costing & Pricing: Based on the product cost structure in my Product_Cost.csv file on my desktop, and taking into account German customs duties, Value Added Tax (VAT), logistics and warehousing costs, and potential marketing expenses, estimate a Manufacturer’s Suggested Retail Price (MSRP) and analyze its competitiveness in the market.
5. Comprehensive Report & Presentation: Summarize all research findings into an HTML report file. The content should include data charts, key findings, and a final market entry strategy recommendation (Recommended / Not Recommended / Recommended with Conditions).
</details>

<br>

### 5. SEO Audit for Workforce Multiagent Launch [Replay ▶️](https://www.eigent.ai/download?share_token=IjE3NTM2OTk5NzExNDQtNTY5NiI.aIex0w.jc_NIPmfIf9e3zGt-oG9fbMi3K4__1753699971144-5696)

<details>
<summary><strong>Prompt:</strong> <kbd>To support the launch of our new Workforce Multiagent product ... <kbd></summary>
<br>
To support the launch of our new Workforce Multiagent product, please run a thorough SEO audit on our official website (https://www.camel-ai.org/) and deliver a detailed optimization report with actionable recommendations.
</details>

<br>

### 6. Identify Duplicate Files in Downloads [Replay ▶️](https://www.eigent.ai/download?share_token=IjE3NTM3NjAzODgxNzEtMjQ4Ig.aIhKLQ.epOG--0Nj0o4Bqjtdqm9OZdaqRQ__1753760388171-248)

<details>
<summary><strong>Prompt:</strong> <kbd>I have a folder named mydocs inside my Documents directory ... <kbd></summary>
<br>
I have a folder named mydocs inside my Documents directory. Please scan it and identify all files that are exact or near duplicates — including those with identical content, file size, or format (even if file names or extensions differ). List them clearly, grouped by similarity.
</details>

<br>

### 7. Add Signature to PDF [Replay ▶️](https://www.eigent.ai/download?share_token=IjE3NTQwOTU0ODM0NTItNTY2MSI.aJCHrA.Mg5yPOFqj86H_GQvvRNditzepXc__1754095483452-5661)

<details>
<summary><strong>Prompt:</strong> <kbd>Please add this signature image to the Signature Areas in the PDF ... <kbd></summary>
<br>
Please add this signature image to the Signature Areas in the PDF. You could install the CLI tool ‘tesseract’ (needed for reliable location of ‘Signature Areas’ via OCR) to help finish this task.
</details>

<br>

## 🛠️ Tech Stack

Eigent open-source Cowork desktop is built on modern, reliable technologies that ensure scalability, performance, and extensibility.

### Backend

- **Framework:** FastAPI
- **Package Manager:** uv
- **Async Server:** Uvicorn
- **Authentication:** OAuth 2.0, Passlib.
- **Multi-agent framework:** CAMEL

### Frontend

- **Framework:** React
- **Desktop App Framework:** Electron
- **Language:** TypeScript
- **UI:** Tailwind CSS, Radix UI, Lucide React, Framer Motion
- **State Management:** Zustand
- **Flow Editor:** React Flow

## 🌟 Staying ahead - Open Source Cowork

> [!IMPORTANT]
>
> **Star Eigent**, You will receive all release notifications from GitHub without any delay ~ ⭐️

![][image-star-us]

## 🗺️ Roadmap - Open Source Cowork

Our open-source Cowork continues to evolve with input from the community. Here's what's coming next:

| Topics                      | Issues                                                                                                                         | Discord Channel                                             |
| --------------------------- | ------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------- |
| **Context Engineering**     | - Prompt caching<br> - System prompt optimize<br> - Toolkit docstring optimize<br> - Context compression                       | [**Join Discord →**](https://discord.com/invite/CNcNpquyDc) |
| **Multi-modal Enhancement** | - More accurate image understanding when using browser<br> - Advanced video generation                                         | [**Join Discord →**](https://discord.com/invite/CNcNpquyDc) |
| **Multi-agent system**      | - Workforce support fixed workflow<br> - Workforce support multi-round conversion                                              | [**Join Discord →**](https://discord.com/invite/CNcNpquyDc) |
| **Browser Toolkit**         | - BrowseComp integration<br> - Benchmark improvement<br> - Forbid repeated page visiting<br> - Automatic cache button clicking | [**Join Discord →**](https://discord.com/invite/CNcNpquyDc) |
| **Document Toolkit**        | - Support dynamic file editing                                                                                                 | [**Join Discord →**](https://discord.com/invite/CNcNpquyDc) |
| **Terminal Toolkit**        | - Benchmark improvement<br> - Terminal-Bench integration                                                                       | [**Join Discord →**](https://discord.com/invite/CNcNpquyDc) |
| **Environment & RL**        | - Environment design<br> - Data-generation<br> - RL framework integration (VERL, TRL, OpenRLHF)                                | [**Join Discord →**](https://discord.com/invite/CNcNpquyDc) |

## [🤝 Contributing][contribution-link]

We believe in building trust and embracing all forms of open-source collaborations. Your creative contributions help drive the innovation of `Eigent`. Explore our GitHub issues and projects to dive in and show us what you’ve got 🤝❤️ [Contribution Guideline][contribution-link]

## Contributors

<a href="https://github.com/eigent-ai/eigent/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=eigent-ai/eigent" />
</a>

Made with [contrib.rocks](https://contrib.rocks).

<br>

## [❤️ Sponsor][sponsor-link]

Eigent is built on top of [CAMEL-AI.org][camel-ai-org-github]'s research and infrastructures. [Sponsoring CAMEL-AI.org][sponsor-link] will make `Eigent` better.

## **📄 Open Source License**

This repository is licensed under the [Apache License 2.0](LICENSE).

## 🌐 Community & Contact

For more information please contact info@eigent.ai

- **GitHub Issues:** Report bugs, request features, and track development. [Submit an issue][github-issue-link]

- **Discord:** Get real-time support, chat with the community, and stay updated. [Join us](https://discord.com/invite/CNcNpquyDc)

- **X (Twitter):** Follow for updates, AI insights, and key announcements. [Follow us][social-x-link]

- **WeChat Community:** Scan the QR code below to add our WeChat assistant, and join our WeChat community group.

<div align="center">
  <img src="./src/assets/wechat_qr.jpg" width="200" style="display: inline-block; margin: 10px;">
</div>

<!-- LINK GROUP -->

<!-- Social -->

<!-- camel & eigent -->

<!-- marketing -->

<!-- feature -->

[built-with-camel]: https://img.shields.io/badge/-Built--with--CAMEL-4C19E8.svg?logo=data:image/svg+xml;base64,PHN2ZyB3aWR0aD0iMjQ4IiBoZWlnaHQ9IjI3MiIgdmlld0JveD0iMCAwIDI0OCAyNzIiIGZpbGw9Im5vbmUiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyI+CjxwYXRoIGQ9Ik04LjgzMTE3IDE4LjU4NjVMMCAzMC44MjY3QzUuNDY2OTIgMzUuMDQzMiAxNS4xMzkxIDM4LjgyNTggMjQuODExNCAzNi4yOTU5QzMwLjY5ODggNDAuOTM0MSAzOS42NzAyIDQwLjIzMTMgNDQuMTU1OSA0MC4wOTA4QzQzLjQ1NSA0Ny4zOTk0IDQyLjQ3MzcgNzAuOTU1OCA0NC4xNTU5IDEwNi43MTJDNDUuODM4IDE0Mi40NjggNzEuNzcwOCAxNjYuODY4IDg0LjUyNjkgMTc0LjU5OEw3Ni4wMDAyIDIyMEw4NC41MjY5IDI3MkgxMDguOTE4TDk4LjAwMDIgMjIwTDEwOC45MTggMTc0LjU5OEwxMjkuOTQ0IDI3MkgxNTQuNzU2TDEzNC4xNSAxNzQuNTk4SDE4Ny4xMzdMMTY2LjUzMSAyNzJIMTkxLjc2M0wyMTIuMzY5IDE3NC41OThMMjI2IDIyMEwyMTIuMzY5IDI3MkgyMzcuNjAxTDI0OC4wMDEgMjIwTDIzNy4xOCAxNzQuNTk4QzIzOS4yODMgMTY5LjExNyAyNDAuNDAxIDE2Ni45NzYgMjQxLjgwNiAxNjEuMTA1QzI0OS4zNzUgMTI5LjQ4MSAyMzUuMDc3IDEwMy45MDEgMjI2LjY2NyA5NC40ODRMMjA2LjQ4MSA3My44MjNDMTk3LjY1IDY0Ljk2ODMgMTgyLjUxMSA2NC41NDY3IDE3Mi44MzkgNzIuNTU4MUMxNjUuNzI4IDc4LjQ0NzcgMTYxLjcwMSA3OC43NzI3IDE1NC43NTYgNzIuNTU4MUMxNTEuODEyIDcwLjAyODEgMTQ0LjUzNSA2MS40ODg5IDEzNC45OTEgNTMuNTgzN0MxMjUuMzE5IDQ1LjU3MjMgMTA4LjQ5NyA0OC45NDU1IDEwMi4xODkgNTUuNjkxOUw3My41OTMxIDg0LjM2NDRWNy42MjM0OUw3OS4xMjczIDBDNjAuOTA0MiAzLjY1NDMzIDIzLjgwMjEgOS41NjMwOSAxOS43NjUgMTAuNTc1MUMxNS43Mjc5IDExLjU4NyAxMC43OTM3IDE2LjMzNzcgOC44MzExNyAxOC41ODY1WiIgZmlsbD0id2hpdGUiLz4KPHBhdGggZD0iTTQzLjIwMzggMTguNzE4N0w0OS4wOTEyIDEzLjA0OTNMNTQuOTc4NyAxOC43MTg3TDQ5LjA5MTIgMjQuODI0Mkw0My4yMDM4IDE4LjcxODdaIiBmaWxsPSIjNEMxOUU4Ii8+Cjwvc3ZnPgo=
[camel-ai-org-github]: https://github.com

... [README content truncated due to size. Visit the repository for the complete README] ...

]]> TypeScript https://github.com/bluesky-social/social-app https://github.com/bluesky-social/social-app Mon, 09 Feb 2026 00:08:20 GMT bluesky-social/social-app

The Bluesky Social application for Web, iOS, and Android

Language: TypeScript

Stars: 17,672

Forks: 2,614

Stars today: 9 stars today

README

# Bluesky Social App

Welcome friends! This is the codebase for the Bluesky Social app.

Get the app itself:

- **Web: [bsky.app](https://bsky.app)**
- **iOS: [App Store](https://apps.apple.com/us/app/bluesky-social/id6444370199)**
- **Android: [Play Store](https://play.google.com/store/apps/details?id=xyz.blueskyweb.app)**

## Development Resources

This is a [React Native](https://reactnative.dev/) application, written in the TypeScript programming language. It builds on the `atproto` TypeScript packages (like [`@atproto/api`](https://www.npmjs.com/package/@atproto/api)), which are also open source, but in [a different git repository](https://github.com/bluesky-social/atproto).

There is a small amount of Go language source code (in `./bskyweb/`), for a web service that returns the React Native Web application.

The [Build Instructions](./docs/build.md) are a good place to get started with the app itself.

The Authenticated Transfer Protocol ("AT Protocol" or "atproto") is a decentralized social media protocol. You don't *need* to understand AT Protocol to work with this application, but it can help. Learn more at:

- [Overview and Guides](https://atproto.com/guides/overview)
- [GitHub Discussions](https://github.com/bluesky-social/atproto/discussions) 👈 Great place to ask questions
- [Protocol Specifications](https://atproto.com/specs/atp)
- [Blogpost on self-authenticating data structures](https://bsky.social/about/blog/3-6-2022-a-self-authenticating-social-protocol)

The Bluesky Social application encompasses a set of schemas and APIs built in the overall AT Protocol framework. The namespace for these "Lexicons" is `app.bsky.*`.

## Contributions

> [!NOTE]
> While we do accept contributions, we prioritize high quality issues and pull requests. Adhering to the below guidelines will ensure a more timely review.

**Rules:**

- We may not respond to your issue or PR.
- We may close an issue or PR without much feedback.
- We may lock discussions or contributions if our attention is getting DDOSed.
- We're not going to provide support for build issues.

**Guidelines:**

- Check for existing issues before filing a new one please.
- Open an issue and give some time for discussion before submitting a PR.
- Stay away from PRs like...
  - Changing "Post" to "Skeet."
  - Refactoring the codebase, e.g., to replace React Query with Redux Toolkit or something.
  - Adding entirely new features without prior discussion. 

Remember, we serve a wide community of users. Our day-to-day involves us constantly asking "which top priority is our top priority." If you submit well-written PRs that solve problems concisely, that's an awesome contribution. Otherwise, as much as we'd love to accept your ideas and contributions, we really don't have the bandwidth. That's what forking is for!

## Forking guidelines

You have our blessing 🪄✨ to fork this application! However, it's very important to be clear to users when you're giving them a fork.

Please be sure to:

- Change all branding in the repository and UI to clearly differentiate from Bluesky.
- Change any support links (feedback, email, terms of service, etc) to your own systems.
- Replace any analytics or error-collection systems with your own so we don't get super confused.

## Security disclosures

If you discover any security issues, please send an email to security@bsky.app. The email is automatically CC'd to the entire team and we'll respond promptly.

## Are you a developer interested in building on atproto?

Bluesky is an open social network built on the AT Protocol, a flexible technology that will never lock developers out of the ecosystems that they help build. With atproto, third-party integration can be as seamless as first-party through custom feeds, federated services, clients, and more.

## License (MIT)

See [./LICENSE](./LICENSE) for the full license.

Bluesky Social PBC has committed to a software patent non-aggression pledge. For details see [the original announcement](https://bsky.social/about/blog/10-01-2025-patent-pledge).

## P.S.

We ❤️ you and all of the ways you support us. Thank you for making Bluesky a great place!

]]> TypeScript https://github.com/memodb-io/Acontext https://github.com/memodb-io/Acontext Mon, 09 Feb 2026 00:08:19 GMT memodb-io/Acontext

Context Data Platform for AI Agents

Language: TypeScript

Stars: 2,897

Forks: 265

Stars today: 8 stars today

README

<div align="center">
  <a href="https://discord.acontext.io">
      <img alt="Acontext - Simple Context Storage for Cloud Agents" src="./assets/Acontext-header-banner.png">
  </a>
 	<p align="center">
 	  	<a href="https://acontext.io">🌐 Website</a>
      |
 	  	<a href="https://docs.acontext.io">📚 Document</a>
  </p>
  <p align="center">
    <a href="https://pypi.org/project/acontext/"><img src="https://img.shields.io/pypi/v/acontext.svg"></a>
    <a href="https://www.npmjs.com/package/@acontext/acontext"><img src="https://img.shields.io/npm/v/@acontext/acontext.svg?logo=npm&logoColor=fff&style=flat&labelColor=2C2C2C&color=28CF8D"></a>
    <a href="https://github.com/memodb-io/acontext/actions/workflows/core-test.yaml"><img src="https://github.com/memodb-io/acontext/actions/workflows/core-test.yaml/badge.svg"></a>
    <a href="https://github.com/memodb-io/acontext/actions/workflows/api-test.yaml"><img src="https://github.com/memodb-io/acontext/actions/workflows/api-test.yaml/badge.svg"></a>
    <a href="https://github.com/memodb-io/acontext/actions/workflows/cli-test.yaml"><img src="https://github.com/memodb-io/acontext/actions/workflows/cli-test.yaml/badge.svg"></a>
  </p>
<p align="center">
 	  	<a href="https://x.com/acontext_io"><img src="https://img.shields.io/twitter/follow/acontext_io?style=social" alt="Twitter Follow"></a>
    <a href="https://discord.acontext.io"><img src="https://img.shields.io/badge/dynamic/json?label=Acontext&style=flat&query=approximate_member_count&url=https%3A%2F%2Fdiscord.com%2Fapi%2Fv10%2Finvites%2FSG9xJcqVBu%3Fwith_counts%3Dtrue&logo=discord&logoColor=white&suffix=+members&color=36393f&labelColor=5765F2" alt="Acontext Discord"></a>
  </p>
</div>




Acontext is a context data platform for production AI agents. Think of it as Supabase, but purpose-built for agent context.

We help agents scale from local demos to production without rebuilding context infrastructure — giving you unified storage, built-in context engineering, and context observability out of the box.



# ❓ Why use Acontext

#### Challenges in Building Agents

- Context data like **llm messages, files, and skills are scattered** across different storages
- **Long-running agents need context management**, and you have to build it yourself
- **Tracking states from multi-modal, multi-llm Agents is a nightmare**, how you know your agent is great?

#### How Acontext Solves It

- **One unified storage** for messages, files, skills, and more. Integrated with Claude Agent SDK, AI-SDK, OpenAI SDK...
- **Built-in context management** methods — just one argument, zero code
- **Replay** agent trajectory in Dashboard
- **Observe** agent with background monitor to estimate success rate

<div align="center">
      <img alt="Acontext - Simple Context Storage for Cloud Agents" src="./assets/acontext-components.png">  
</div>


# 💡 Core Features

- **Context Storage**
  - [Session](https://docs.acontext.io/store/messages/multi-provider): save agent history from any llm, any modal.
    - [Context Editing](https://docs.acontext.io/engineering/editing) - edit context window in one api.
  - [Disk](https://docs.acontext.io/store/disk): virtual, persistent filesystem,
  - [Agent Skills](https://docs.acontext.io/store/skill) - manage skills in server-side.
  - [Sandbox](https://docs.acontext.io/store/sandbox) - run code, analyze data, export artifacts.


- **Context Observability**
  - [Session Summary](https://docs.acontext.io/observe/agent_tasks): asynchronously summarize agent's progress and user feedback.
  - [State Tracking](https://docs.acontext.io/observe/agent_tasks): collect agent's working status in near real-time.
- **View everything in one [dashboard](https://docs.acontext.io/observe/dashboard)**

<div align="center">
    <picture>
      <img alt="Dashboard" src="./docs/images/dashboard/BI.png" width="80%">
    </picture>
  <p>Dashboard of Agent Success Rate and Other Metrics</p>
</div>





# 🚀 Step-by-step Quickstart

### Connect to Acontext

1. Go to [Acontext.io](https://acontext.io), claim your free credits.
2. Go through a one-click onboarding to get your API Key (starts with `sk-ac`)

<div align="center">
    <picture>
      <img alt="Dashboard" src="./assets/onboard.png" width="80%">
    </picture>
</div>




<details>
<summary>💻 Self-host Acontext</summary>

We have an `acontext-cli` to help you do quick proof-of-concept. Download it first in your terminal:

```bash
curl -fsSL https://install.acontext.io | sh
```

You should have [docker](https://www.docker.com/get-started/) installed and an OpenAI API Key to start an Acontext backend on your computer:

```bash
mkdir acontext_server && cd acontext_server
acontext server up
```

> Make sure your LLM has the ability to [call tools](https://platform.openai.com/docs/guides/function-calling). By default, Acontext will use `gpt-4.1`.

`acontext server up` will create/use  `.env` and `config.yaml` for Acontext, and create a `db` folder to persist data.



Once it's done, you can access the following endpoints:

- Acontext API Base URL: http://localhost:8029/api/v1
- Acontext Dashboard: http://localhost:3000/

</details>



### Install SDKs

We're maintaining Python [![pypi](https://img.shields.io/pypi/v/acontext.svg)](https://pypi.org/project/acontext/) and Typescript [![npm](https://img.shields.io/npm/v/@acontext/acontext.svg?logo=npm&logoColor=fff&style=flat&labelColor=2C2C2C&color=28CF8D)](https://www.npmjs.com/package/@acontext/acontext) SDKs. The snippets below are using Python.

> Click the doc link to see TS SDK Quickstart.

```bash
pip install acontext
```


### Initialize Client

```python
import os
from acontext import AcontextClient

# For cloud:
client = AcontextClient(
    api_key=os.getenv("ACONTEXT_API_KEY"),
)

# For self-hosted:
client = AcontextClient(
    base_url="http://localhost:8029/api/v1",
    api_key="sk-ac-your-root-api-bearer-token",
)
```



### Store & Get Messages

> [Docs](https://docs.acontext.io/store/messages/multi-provider)

Store messages in OpenAI, Anthropic, or Gemini format. Auto-converts on retrieval.

```python
# Create session and store messages
session = client.sessions.create()

# Store text, image, file, etc.
client.sessions.store_message(
    session_id=session.id,
    blob={"role": "user", "content": "Hello!"},
    format="openai"
)

# Retrieve in any format (auto-converts)
result = client.sessions.get_messages(session_id=session.id, format="anthropic")
```

### Context Engineering

> [Session Summary](https://docs.acontext.io/engineering/session_summary) | [Context Editing](https://docs.acontext.io/engineering/editing)

Compress context with summaries and edit strategies. Original messages unchanged.

```python
# Session summary for prompt injection
summary = client.sessions.get_session_summary(session_id)
system_prompt = f"Previous tasks:\n{summary}\n\nContinue helping."

# Context editing - limit tokens on retrieval
result = client.sessions.get_messages(
    session_id=session_id,
    edit_strategies=[
        {"type": "remove_tool_result", "params": {"keep_recent_n_tool_results": 3}},
        {"type": "token_limit", "params": {"limit_tokens": 30000}}
    ]
)
```

### Agent Storage Tools
<details>
<summary>Disk Tool</summary>



> [Tool Docs](https://docs.acontext.io/tool/disk_tools) | [SDK Docs](https://docs.acontext.io/store/disk)
> 
Persistent file storage for agents. Supports read, write, grep, glob.

```python
from acontext.agent.disk import DISK_TOOLS
from openai import OpenAI

disk = client.disks.create()
ctx = DISK_TOOLS.format_context(client, disk.id)

# Pass to LLM
response = OpenAI().chat.completions.create(
    model="gpt-4.1",
    messages=[
        {"role": "system", "content": f"You have disk access.\n\n{ctx.get_context_prompt()}"},
        {"role": "user", "content": "Create a todo.md with 3 tasks"}
    ],
    tools=DISK_TOOLS.to_openai_tool_schema()
)

# Execute tool calls
for tc in response.choices[0].message.tool_calls:
    result = DISK_TOOLS.execute_tool(ctx, tc.function.name, json.loads(tc.function.arguments))
```

</details>


<details>
<summary>Sandbox Tool</summary>


> [Tool Docs](https://docs.acontext.io/tool/bash_tools) | [SDK Docs](https://docs.acontext.io/store/sandbox)
>
> Isolated code execution environment with bash, Python, and common tools.

```python
from acontext.agent.sandbox import SANDBOX_TOOLS
from openai import OpenAI

sandbox = client.sandboxes.create()
disk = client.disks.create()
ctx = SANDBOX_TOOLS.format_context(client, sandbox.sandbox_id, disk.id)

# Pass to LLM
response = OpenAI().chat.completions.create(
    model="gpt-4.1",
    messages=[
        {"role": "system", "content": f"You have sandbox access.\n\n{ctx.get_context_prompt()}"},
        {"role": "user", "content": "Run a Python hello world script"}
    ],
    tools=SANDBOX_TOOLS.to_openai_tool_schema()
)

# Execute tool calls
for tc in response.choices[0].message.tool_calls:
    result = SANDBOX_TOOLS.execute_tool(ctx, tc.function.name, json.loads(tc.function.arguments))
```

</details>

<details>
<summary>Sandbox with Skills</summary>



> [Tool Docs](https://docs.acontext.io/tool/bash_tools#mounting-skills-in-sandbox) | [SDK Docs](https://docs.acontext.io/store/skill)
>
> Mount reusable Agent Skills into sandbox at `/skills/{name}/`. [Download xlsx skill](https://github.com/memodb-io/Acontext-Examples/raw/refs/heads/main/python/interactive-agent-skill/xlsx.zip).

```python
from acontext import FileUpload

# Upload a skill ZIP (e.g., xlsx.zip)
with open("web-artifacts-builder.zip", "rb") as f:
    skill = client.skills.create(file=FileUpload(filename="xlsx.zip", content=f.read()))

# Mount into sandbox
ctx = SANDBOX_TOOLS.format_context(
    client, sandbox.sandbox_id, disk.id,
    mount_skills=[skill.id]  # Available at /skills/{skill.name}/
)

# Context prompt includes skill instructions
response = OpenAI().chat.completions.create(
    model="gpt-4.1",
    messages=[
        {"role": "system", "content": f"You have sandbox access.\n\n{ctx.get_context_prompt()}"},
        {"role": "user", "content": "Create an Excel file with a simple budget spreadsheet and export it"}
    ],
    tools=SANDBOX_TOOLS.to_openai_tool_schema()
)

# Execute tool calls
for tc in response.choices[0].message.tool_calls:
    result = SANDBOX_TOOLS.execute_tool(ctx, tc.function.name, json.loads(tc.function.arguments))
```

You can download a full skill interactive demo with `acontext-cli`:

```shell
acontext create my-skill --template-path "python/interactive-agent-skill"
```



</details>





# 🧐 Use Acontext to build Agent

Download end-to-end scripts with `acontext`:

**Python**

```bash
acontext create my-proj --template-path "python/openai-basic"
```

More examples on Python:

- `python/openai-agent-basic`: openai agent sdk template
- `python/openai-agent-artifacts`: agent can edit and download artifacts
- `python/claude-agent-sdk`: claude agent sdk with `ClaudeAgentStorage`
- `python/agno-basic`: agno framework template
- `python/smolagents-basic`: smolagents (huggingface) template
- `python/interactive-agent-skill`: interactive sandbox with mountable agent skills

**Typescript**

```bash
acontext create my-proj --template-path "typescript/openai-basic"
```

More examples on Typescript:
- `typescript/vercel-ai-basic`: agent in @vercel/ai-sdk
- `typescript/claude-agent-sdk`: claude agent sdk with `ClaudeAgentStorage`
- `typescript/interactive-agent-skill`: interactive sandbox with mountable agent skills



> [!NOTE]
>
> Check our example repo for more templates: [Acontext-Examples](https://github.com/memodb-io/Acontext-Examples).
>
> We're cooking more full-stack Agent Applications! [Tell us what you want!](https://discord.acontext.io)





# 🔍 Document

To understand what Acontext can do better, please view [our docs](https://docs.acontext.io/)



# ❤️ Stay Updated

Star Acontext on Github to support and receive instant notifications 

![click_star](./assets/star_acontext.gif)



# 🏗️ Architecture

<details>
<summary>click to open</summary>

```mermaid
graph TB
    subgraph "Client Layer"
        PY["pip install acontext"]
        TS["npm i @acontext/acontext"]
    end
    
    subgraph "Acontext Backend"
      subgraph " "
          API["API<br/>localhost:8029"]
          CORE["Core"]
          API -->|FastAPI & MQ| CORE
      end
      
      subgraph " "
          Infrastructure["Infrastructures"]
          PG["PostgreSQL"]
          S3["S3"]
          REDIS["Redis"]
          MQ["RabbitMQ"]
      end
    end
    
    subgraph "Dashboard"
        UI["Web Dashboard<br/>localhost:3000"]
    end
    
    PY -->|RESTFUL API| API
    TS -->|RESTFUL API| API
    UI -->|RESTFUL API| API
    API --> Infrastructure
    CORE --> Infrastructure

    Infrastructure --> PG
    Infrastructure --> S3
    Infrastructure --> REDIS
    Infrastructure --> MQ
    
    
    style PY fill:#3776ab,stroke:#fff,stroke-width:2px,color:#fff
    style TS fill:#3178c6,stroke:#fff,stroke-width:2px,color:#fff
    style API fill:#00add8,stroke:#fff,stroke-width:2px,color:#fff
    style CORE fill:#ffd43b,stroke:#333,stroke-width:2px,color:#333
    style UI fill:#000,stroke:#fff,stroke-width:2px,color:#fff
    style PG fill:#336791,stroke:#fff,stroke-width:2px,color:#fff
    style S3 fill:#ff9900,stroke:#fff,stroke-width:2px,color:#fff
    style REDIS fill:#dc382d,stroke:#fff,stroke-width:2px,color:#fff
    style MQ fill:#ff6600,stroke:#fff,stroke-width:2px,color:#fff
```

</details>

# 🤝 Stay Together

Join the community for support and discussions:

-   [Discuss with Builders on Acontext Discord](https://discord.acontext.io) 👻 
-  [Follow Acontext on X](https://x.com/acontext_io) 𝕏 



# 🌟 Contributing

- Check our [roadmap.md](./ROADMAP.md) first.
- Read [contributing.md](./CONTRIBUTING.md)



# 🥇 Badges

![Made with Acontext](./assets/badge-made-with-acontext.svg) ![Made with Acontext (dark)](./assets/badge-made-with-acontext-dark.svg)

```md
[![Made with Acontext](https://assets.memodb.io/Acontext/badge-made-with-acontext.svg)](https://acontext.io)

[![Made with Acontext](https://assets.memodb.io/Acontext/badge-made-with-acontext-dark.svg)](https://acontext.io)
```





# 📑 LICENSE

This project is currently licensed under [Apache License 2.0](LICENSE).

]]> TypeScript https://github.com/CodeWithCJ/SparkyFitness https://github.com/CodeWithCJ/SparkyFitness Mon, 09 Feb 2026 00:08:18 GMT CodeWithCJ/SparkyFitness

SparkyFitness: Built for Families. Powered by AI. Track food, fitness, water, and health — together.

Language: TypeScript

Stars: 2,200

Forks: 100

Stars today: 39 stars today

README

<div align="right">
  <details>
    <summary >🌐 Language</summary>
    <div>
      <div align="right">
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=en">English</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=zh-CN">简体中文</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=zh-TW">繁體中文</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=ja">日本語</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=ko">한국어</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=hi">हिन्दी</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=th">ไทย</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=fr">Français</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=de">Deutsch</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=es">Español</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=it">Italiano</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=ru">Русский</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=pt">Português</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=nl">Nederlands</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=pl">Polski</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=ar">العربية</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=fa">فارسی</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=tr">Türkçe</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=vi">Tiếng Việt</a></p>
        <p><a href="https://openaitx.github.io/view.html?user=CodeWithCJ&project=SparkyFitness&lang=id">Bahasa Indonesia</a></p>
      </div>
    </div>
  </details>
</div>

# SparkyFitness

A self-hosted, privacy-first alternative to MyFitnessPal. Track nutrition, exercise, body metrics, and health data while keeping full control of your data.


![Screenshot](docs/public/web_screenshot.png)


SparkyFitness is a self-hosted fitness tracking platform made up of:

- A backend server (API + data storage)
- A web-based frontend
- Native mobile apps for iOS and Android

It stores and manages health data on infrastructure you control, without relying on third party services.

## Core Features

- Nutrition, exercise, hydration, and body measurement tracking
- Goal setting and daily check-ins
- Interactive charts and long-term reports
- Multiple user profiles and family access
- Light and dark themes

## Health & Device Integrations

SparkyFitness can sync data from multiple health and fitness platforms:

- **Apple Health** (iOS)
- **Google Health Connect** (Android)
- **Fitbit**
- **Garmin Connect**
- **Withings**

Integrations automatically sync activity data such as steps, workouts, and sleep, along with health metrics like weight and body measurements, to your SparkyFitness server.

## Optional AI Features (Beta)

SparkyAI provides a conversational interface for logging data and reviewing progress.

- Log food, exercise, body stats, and steps via chat
- Upload food images for automatic meal logging
- Retains conversation history for follow ups

Note: AI features are currently in beta.


## Quick Start (Server)

Get a SparkyFitness server running in minutes using Docker Compose.

```bash
# 1. Create a new folder
mkdir sparkyfitness && cd sparkyfitness

# 2. Download Docker files only
curl -o docker-compose.yml https://github.com/CodeWithCJ/SparkyFitness/releases/latest/download/docker-compose.prod.yml
curl -L -o .env https://github.com/CodeWithCJ/SparkyFitness/releases/latest/download/default.env.example

# 3. (Optional) Edit .env to customize database credentials, ports, etc.

# 4. Start the app
docker compose pull && docker compose up -d

# Access application at http://localhost:8080
```

## Documentation

For full installation guides, configuration options, and development docs, please visit our [Documentation Site](https://codewithcj.github.io/SparkyFitness/).

### Quick Links

- **[Installation Guide](https://codewithcj.github.io/SparkyFitness/install/docker-compose)** - Deployment and configurations
- **[Features Overview](https://codewithcj.github.io/SparkyFitness/features)** - Complete feature documentation
- **[Development Workflow](https://codewithcj.github.io/SparkyFitness/developer/getting-started)** - Developer guide and contribution process
- **[iOS App Info](https://github.com/CodeWithCJ/SparkyFitness/wiki/Apple-Health-Integration)** and **[Android App Info](https://github.com/CodeWithCJ/SparkyFitness/wiki/Android-Mobile-App)**

### Need Help?

- **[Join our Discord](https://discord.gg/vcnMT5cPEA)**

## Star History

<a href="https://star-history.com/#CodeWithCJ/SparkyFitness&Date">
  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=CodeWithCJ/SparkyFitness&type=Date&theme=dark" />
    <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=CodeWithCJ/SparkyFitness&type=Date" />
    <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=CodeWithCJ/SparkyFitness&type=Date" width="100%" />
  </picture>
</a>

## Translations

**[Weblate Translations](https://hosted.weblate.org/engage/sparkyfitness)**

<a href="https://hosted.weblate.org/engage/sparkyfitness/">
<img src="https://hosted.weblate.org/widget/sparkyfitness/sparkyfitness-translations/multi-auto.svg" alt="Translation status" />
</a>

## Repository activity

![Alt](https://repobeats.axiom.co/api/embed/828203d3070ff56c8873c727b6873b684c4ed399.svg "Repobeats analytics image")

## Contributors

<a href="https://github.com/CodeWithCJ/SparkyFitness/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=CodeWithCJ/SparkyFitness" width="100%"/>
</a>

## ⚠️ Known Issues / Beta Features ⚠️

SparkyFitness is under active development.
Breaking changes may occur between releases.

- Auto-updating containers is not recommended
- Always review release notes before upgrading

The following features are currently in beta and may not have been thoroughly tested. Expect potential bugs or incomplete functionality:

- AI Chatbot
- Family & Friends access
- API documentation

]]> TypeScript https://github.com/moeru-ai/airi https://github.com/moeru-ai/airi Mon, 09 Feb 2026 00:08:17 GMT moeru-ai/airi

💖🧸 Self hosted, you owned Grok Companion, a container of souls of waifu, cyber livings to bring them into our worlds, wishing to achieve Neuro-sama's altitude. Capable of realtime voice chat, Minecraft, Factorio playing. Web / macOS / Windows supported.

Language: TypeScript

Stars: 17,374

Forks: 1,684

Stars today: 22 stars today

README

<picture>
  <source
    width="100%"
    srcset="./docs/content/public/banner-dark-1280x640.avif"
    media="(prefers-color-scheme: dark)"
  />
  <source
    width="100%"
    srcset="./docs/content/public/banner-light-1280x640.avif"
    media="(prefers-color-scheme: light), (prefers-color-scheme: no-preference)"
  />
  <img width="250" src="./docs/content/public/banner-light-1280x640.avif" />
</picture>

<h1 align="center">Project AIRI</h1>

<p align="center">Re-creating Neuro-sama, a soul container of AI waifu / virtual characters to bring them into our world.</p>

<p align="center">
  [<a href="https://discord.gg/TgQ3Cu2F7A">Join Discord Server</a>] [<a href="https://airi.moeru.ai">Try it</a>] [<a href="https://github.com/moeru-ai/airi/blob/main/docs/README.zh-CN.md">简体中文</a>] [<a href="https://github.com/moeru-ai/airi/blob/main/docs/README.ja-JP.md">日本語</a>] [<a href="https://github.com/moeru-ai/airi/blob/main/docs/README.ru-RU.md">Русский</a>] [<a href="https://github.com/moeru-ai/airi/blob/main/docs/README.vi.md">Tiếng Việt</a>] [<a href="https://github.com/moeru-ai/airi/blob/main/docs/README.fr.md">Français</a>]
</p>

<p align="center">
  <a href="https://deepwiki.com/moeru-ai/airi"><img src="https://deepwiki.com/badge.svg"></a>
  <a href="https://github.com/moeru-ai/airi/blob/main/LICENSE"><img src="https://img.shields.io/github/license/moeru-ai/airi.svg?style=flat&colorA=080f12&colorB=1fa669"></a>
  <a href="https://discord.gg/TgQ3Cu2F7A"><img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2FTgQ3Cu2F7A%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&suffix=%20members&logo=discord&logoColor=white&label=%20&color=7389D8&labelColor=6A7EC2"></a>
  <a href="https://x.com/proj_airi"><img src="https://img.shields.io/badge/%40proj__airi-black?style=flat&logo=x&labelColor=%23101419&color=%232d2e30"></a>
  <a href="https://t.me/+7M_ZKO3zUHFlOThh"><img src="https://img.shields.io/badge/Telegram-%235AA9E6?logo=telegram&labelColor=FFFFFF"></a>
  <a href="./docs/wechat.md"><img src="https://img.shields.io/badge/WeChat-%2307C160?logo=wechat&logoColor=%2307C160&labelColor=FFFFFF"></a>
  <a href="https://qun.qq.com/universal-share/share?ac=1&authKey=9g00d%2BZS7nORzcJugNNddJ7rCghZTIR7fhXabGwch2S%2BG%2BKGIKwlN1N2nIqkh2jg&busi_data=eyJncm91cENvZGUiOiIxMDU4MTU2Njk3IiwidG9rZW4iOiJmcnkra1hWNFIxNytEcG0zcHRUdVJIaldlRDFxN0dzK080QWtvTEdOQjJkNEY2eUFta1g1clNpbkxSMS9FQWFYIiwidWluIjoiMTI2MDkwNzMzNSJ9&data=b1eJrwn3GVOUh7YIxZ7l9vHQo99HPmRxKPpMKlDCmfzx8Y57IXb2EZCMaOC9rVTd2U558qpNjwUYUWlPHxVHvg&svctype=4&tempid=h5_group_info"><img src="https://img.shields.io/badge/QQ-%2312B7F5?logo=qq&labelColor=FFFFFF"></a>
</p>

<p align="center">
  <a href="https://www.producthunt.com/products/airi?embed=true&utm_source=badge-featured&utm_medium=badge&utm_source=badge-airi" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/featured.svg?post_id=993524&theme=neutral&t=1752696535380" alt="AIRI - A&#0032;container&#0032;of&#0032;cyber&#0032;living&#0032;souls&#0044;&#0032;re&#0045;creation&#0032;of&#0032;Neuro&#0045;sama | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
  <a href="https://trendshift.io/repositories/14636" target="_blank"><img src="https://trendshift.io/api/badge/repositories/14636" alt="moeru-ai%2Fairi | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>

> Heavily inspired by [Neuro-sama](https://www.youtube.com/@Neurosama)

> [!WARNING]
> **Attention:** We **do not** have any officially minted cryptocurrency or token associated with this project. Please check the information and proceed with caution.

> [!NOTE]
>
> We've got a whole dedicated organization [@proj-airi](https://github.com/proj-airi) for all the sub-projects born from Project AIRI. Check it out!
>
> RAG, memory system, embedded database, icons, Live2D utilities, and more!

> [!TIP]
> We have a translation project on [Crowdin](https://crowdin.com/project/proj-airi). If you find any inaccurate translations, feel free to contribute improvements there.
> <a href="https://crowdin.com/project/proj-airi" target="_blank" rel="nofollow"><img style="width: 140px; height: 40px;" src="https://badges.crowdin.net/badge/light/crowdin-on-dark.png" srcset="https://badges.crowdin.net/badge/light/crowdin-on-dark.png 1x, https://badges.crowdin.net/badge/light/crowdin-on-dark@2x.png 2x" alt="Crowdin | Agile localization for tech companies" width="140" height="40" /></a>

Have you dreamed about having a cyber living being (cyber waifu, digital pet) or digital companion that could play with and talk to you?

With the power of modern large language models like [ChatGPT](https://chatgpt.com) and famous [Claude](https://claude.ai), asking a virtual being to roleplay and chat with us is already easy enough for everyone. Platforms like [Character.ai (a.k.a. c.ai)](https://character.ai) and [JanitorAI](https://janitorai.com/) as well as local playgrounds like [SillyTavern](https://github.com/SillyTavern/SillyTavern) are already good-enough solutions for a chat based or visual adventure game like experience.

> But, what about the abilities to play games? And see what you are coding at? Chatting while playing games, watching videos, and is capable of doing many other things.

Perhaps you know [Neuro-sama](https://www.youtube.com/@Neurosama) already. She is currently the best virtual streamer capable of playing games, chatting, and interacting with you and the participants. Some also call this kind of being "digital human." **Sadly, as it's not open sourced, you cannot interact with her after her live streams go offline**.

Therefore, this project, AIRI, offers another possibility here: **let you own your digital life, cyber living, easily, anywhere, anytime**.

## DevLogs We Posted & Recent Updates

- [DevLog @ 2026.01.01](https://airi.moeru.ai/docs/en/blog/DevLog-2026.01.01/) on January 1, 2026
- [DevLog @ 2025.10.20](https://airi.moeru.ai/docs/en/blog/DevLog-2025.10.20/) on October 20, 2025
- [DevLog @ 2025.08.05](https://airi.moeru.ai/docs/en/blog/DevLog-2025.08.05/) on August 5, 2025
- [DevLog @ 2025.08.01](https://airi.moeru.ai/docs/en/blog/DevLog-2025.08.01/) on August 1, 2025
- [DevLog @ 2025.07.18](https://airi.moeru.ai/docs/en/blog/DevLog-2025.07.18/) on July 18, 2025
- [DreamLog 0x1](https://airi.moeru.ai/docs/en/blog/dreamlog-0x1/) on June 16, 2025
- ...more on [documentation site](https://airi.moeru.ai/docs/en/)

## What's So Special About This Project?

Unlike the other AI driven VTuber open source projects, アイリ was built with support of many Web technologies such as [WebGPU](https://www.w3.org/TR/webgpu/), [WebAudio](https://developer.mozilla.org/en-US/docs/Web/API/Web_Audio_API), [Web Workers](https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers), [WebAssembly](https://webassembly.org/), [WebSocket](https://developer.mozilla.org/en-US/docs/Web/API/WebSocket), etc. from the first day.

> [!TIP]
> Worrying about the performance drop since we are using Web related technologies?
>
> Don't worry, while Web browser version is meant to give an insight about how much we can push and do inside browsers, and webviews, we will never fully rely on this, the desktop version of AIRI is capable of using native [NVIDIA CUDA](https://developer.nvidia.com/cuda-toolkit) and [Apple Metal](https://developer.apple.com/metal/) by default (thanks to HuggingFace & beloved [candle](https://github.com/huggingface/candle) project), without any complex dependency managements, considering the tradeoff, it was partially powered by Web technologies for graphics, layouts, animations, and the WIP plugin systems for everyone to integrate things.

This means that **アイリ is capable of running on modern browsers and devices** and even on mobile devices (already done with PWA support). This brings a lot of possibilities for us (the developers) to build and extend the power of アイリ VTuber to the next level, while still leaving the flexibilities for users to enable features that requires TCP connections or other non-Web technologies such as connecting to a Discord voice channel or playing Minecraft and Factorio with friends.

> [!NOTE]
>
> We are still in the early stage of development where we are seeking out talented developers to join us and help us to make アイリ a reality.
>
> It's ok if you are not familiar with Vue.js, TypeScript, and devtools required for this project, you can join us as an artist, designer, or even help us to launch our first live stream.
>
> Even if you are a big fan of React, Svelte or even Solid, we welcome you. You can open a sub-directory to add features that you want to see in アイリ, or would like to experiment with.
>
> Fields (and related projects) that we are looking for:
>
> - Live2D modeller
> - VRM modeller
> - VRChat avatar designer
> - Computer Vision
> - Reinforcement Learning
> - Speech Recognition
> - Speech Synthesis
> - ONNX Runtime
> - Transformers.js
> - vLLM
> - WebGPU
> - Three.js
> - WebXR ([checkout the another project](https://github.com/moeru-ai/chat) we have under the @moeru-ai organization)
>
> **If you are interested, why not introduce yourself here? [Would like to join part of us to build AIRI?](https://github.com/moeru-ai/airi/discussions/33)**

## Current Progress

Capable of

- [x] Brain
  - [x] Play [Minecraft](https://www.minecraft.net)
  - [x] Play [Factorio](https://www.factorio.com) (WIP, but [PoC and demo available](https://github.com/moeru-ai/airi-factorio))
  - [x] Chat in [Telegram](https://telegram.org)
  - [x] Chat in [Discord](https://discord.com)
  - [ ] Memory
    - [x] Pure in-browser database support (DuckDB WASM | `pglite`)
    - [ ] Memory Alaya (WIP)
  - [ ] Pure in-browser local (WebGPU) inference
- [x] Ears
  - [x] Audio input from browser
  - [x] Audio input from [Discord](https://discord.com)
  - [x] Client side speech recognition
  - [x] Client side talking detection
- [x] Mouth
  - [x] [ElevenLabs](https://elevenlabs.io/) voice synthesis
- [x] Body
  - [x] VRM support
    - [x] Control VRM model
  - [x] VRM model animations
    - [x] Auto blink
    - [x] Auto look at
    - [x] Idle eye movement
  - [x] Live2D support
    - [x] Control Live2D model
  - [x] Live2D model animations
    - [x] Auto blink
    - [x] Auto look at
    - [x] Idle eye movement

## Development

> For detailed instructions to develop this project, follow [CONTRIBUTING.md](./.github/CONTRIBUTING.md)

> [!NOTE]
> By default, `pnpm dev` will start the development server for the Stage Web (browser version). If you would
> like to try developing the desktop version, please make sure you read [CONTRIBUTING.md](./.github/CONTRIBUTING.md)
> to setup the environment correctly.

```shell
pnpm i
pnpm dev
```

### Stage Web (Browser Version at [airi.moeru.ai](https://airi.moeru.ai))

```shell
pnpm dev
```

### Stage Tamagotchi (Desktop Version)

```shell
pnpm dev:tamagotchi
```

A Nix package for Tamagotchi is included. To run airi with Nix, first make sure to enable flakes, then run:

```shell
nix run github:moeru-ai/airi
```

### Stage Pocket (Mobile Version)

Start the development server for the capacitor web version:

```shell
pnpm dev:pocket
```

Check your IP address in the output of the command above:

```shell
  ROLLDOWN-VITE v7.3.0  ready in 1073 ms

  ➜  Local:   https://localhost:5273/
  ➜  Network: https://<ip-will-be-here>:5273/
  ➜  Vue DevTools: Open https://localhost:5273/__devtools__/ as a separate window
  ➜  Vue DevTools: Press Option(⌥)+Shift(⇧)+D in App to toggle the Vue DevTools
  ➜  UnoCSS Inspector: https://localhost:5273/__unocss/
```

Open the Xcode project:

```shell
CAPACITOR_DEV_SERVER_URL=https://<your-ip-address>:5273 pnpm open:ios
```

Then Xcode will open and you can click the "Run" button to run the app on your iPhone.

If you need to connect server channel on pocket in wireless mode, you need to start tamagotchi as root:

```shell
sudo pnpm dev:tamagotchi
```

Then enable secure websocket in tamagotchi `settings/system/general`.

### Documentation Site

```shell
pnpm dev:docs
```

### Publish

Please update the version in `Cargo.toml` after running `bumpp`:

```shell
npx bumpp --no-commit --no-tag
```

## Support of LLM API Providers (powered by [xsai](https://github.com/moeru-ai/xsai))

- [x] [302.AI (sponsored)](https://share.302.ai/514k2v)
- [x] [OpenRouter](https://openrouter.ai/)
- [x] [vLLM](https://github.com/vllm-project/vllm)
- [x] [SGLang](https://github.com/sgl-project/sglang)
- [x] [Ollama](https://github.com/ollama/ollama)
- [x] [Google Gemini](https://developers.generativeai.google)
- [x] [OpenAI](https://platform.openai.com/docs/guides/gpt/chat-completions-api)
  - [ ] [Azure OpenAI API](https://learn.microsoft.com/en-us/azure/ai-services/openai/reference) (PR welcome)
- [x] [Anthropic Claude](https://anthropic.com)
  - [ ] [AWS Claude](https://docs.anthropic.com/en/api/claude-on-amazon-bedrock) (PR welcome)
- [x] [DeepSeek](https://www.deepseek.com/)
- [x] [Qwen](https://help.aliyun.com/document_detail/2400395.html)
- [x] [xAI](https://x.ai/)
- [x] [Groq](https://wow.groq.com/)
- [x] [Mistral](https://mistral.ai/)
- [x] [Cloudflare Workers AI](https://developers.cloudflare.com/workers-ai/)
- [x] [Together.ai](https://www.together.ai/)
- [x] [Fireworks.ai](https://www.together.ai/)
- [x] [Novita](https://www.novita.ai/)
- [x] [Zhipu](https://bigmodel.cn)
- [x] [SiliconFlow](https://cloud.siliconflow.cn/i/rKXmRobW)
- [x] [Stepfun](https://platform.stepfun.com/)
- [x] [Baichuan](https://platform.baichuan-ai.com)
- [x] [Minimax](https://api.minimax.chat/)
- [x] [Moonshot AI](https://platform.moonshot.cn/)
- [x] [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro)
- [x] [Player2](https://player2.game/)
- [x] [Tencent Cloud](https://cloud.tencent.com/document/product/1729)
- [ ] [Sparks](https://www.xfyun.cn/doc/spark/Web.html) (PR welcome)
- [ ] [Volcano Engine](https://www.volcengine.com/experience/ark?utm_term=202502dsinvite&ac=DSASUQY5&rc=2QXCA1VI) (PR welcome)

## Sub-projects Born from This Project

- [Awesome AI VTuber](https://github.com/proj-airi/awesome-ai-vtuber): A curated list of AI VTubers and related projects
- [`unspeech`](https://github.com/moeru-ai/unspeech): Universal endpoint proxy server for `/audio/transcriptions` and `/audio/speech`, like LiteLLM but for any ASR and TTS
- [`hfup`](https://github.com/moeru-ai/hfup): tools to help on deploying, bundling to HuggingFace Spaces
- [`xsai-transformers`](https://github.com/moeru-ai/xsai-transformers): Experimental [🤗 Transformers.js](https://github.com/huggingface/transformers.js) provider for [xsAI](https://github.com/moeru-ai/xsai).
- [WebAI: Realtime Voice Chat](https://github.com/proj-airi/webai-realtime-voice-chat): Full example of implementing ChatGPT's realtime voice from scratch with VAD + STT + LLM + TTS.
- [`@proj-airi/drizzle-duckdb-wasm`](https://github.com/moeru-ai/airi/tree/main/packages/drizzle-duckdb-wasm/README.md): Drizzle ORM driver for DuckDB WASM
- [`@proj-airi/duckdb-wasm`](https://github.com/moeru-ai/airi/tree/main/packages/duckdb-wasm/README.md): Easy to use wrapper for `@duckdb/duckdb-wasm`
- [`tauri-plugin-mcp`](https://github.com/moeru-ai/airi/blob/main/crates/tauri-plugin-mcp/README.md): A Tauri plugin for interacting with MCP servers.
- [AIRI Factorio](https://github.com/moeru-ai/airi-factorio): Allow AIRI to play Factorio
- [Factorio RCON API](https://github.com/nekomeowww/factorio-rcon-api): RESTful API wrapper for Factorio headless server console
- [`autorio`](https://github.com/moeru-ai/airi-factorio/tree/main/packages/autorio): Factorio automation library
- [`tstl-plugin-reload-factorio-mod`](https://github.com/moeru-ai/airi-factorio/tree/main/packages/tstl-plugin-reload-factorio-mod): Reload Factorio mod when developing
- [Velin](https://github.com/luoling8192/velin): Use Vue SFC and Markdown to write easy to manage stateful prompts for LLM
- [`demodel`](https://github.com/moeru-ai/demodel): Easily boost the speed of pulling your models and datasets from various of inference runtimes.
- [`inventory`](https://github.com/moeru-ai/inventory): Centralized model catalog and default provider configurations backend service
- [MCP Launcher](https://github.com/moeru-ai/mcp-launcher): Easy to use MCP builder & launcher for all possible MCP servers, just like Ollama for models!
- [🥺 SAD](https://github.com/moeru-ai/sad): Documentation and notes for self-host and browser running LLMs.

```mermaid
%%{ init: { 'flowchart': { 'curve': 'catmullRom' } } }%%

flowchart TD
  Core("Core")
  Unspeech("unspeech")
  DBDriver("@proj-airi/drizzle-duckdb-wasm")
  MemoryDriver("[WIP] Memory Alaya")
  DB1("@proj-airi/duckdb-wasm")
  SVRT("@proj-airi/server-runtime")
  Memory("Memory")
  STT("STT")
  Stage("Stage")
  StageUI("@proj-airi/stage-ui")
  UI("@proj-airi/ui")

  subgraph AIRI
    DB1 --> DBDriver --> MemoryDriver --> Memory --> Core
    UI --> StageUI --> Stage --> Core
    Core --> STT
    Core --> SVRT
  end

  subgraph UI_Components
    UI --> StageUI
    UITransitions("@proj-airi/ui-transitions") --> StageUI
    UILoadingScreens("@proj-airi/ui-loading-screens") --> StageUI
    FontCJK("@proj-airi/font-cjkfonts-allseto") --> StageUI
    FontXiaolai("@proj-airi/font-xiaolai") --> StageUI
  end

  subgraph Apps
    Stage --> StageWeb("@proj-airi/stage-web")
    Stage --> StageTamagotchi("@proj-airi/stage-tamagotchi")
    Core --> RealtimeAudio("@proj-airi/realtime-audio")
    Core --> PromptEngineering("@proj-airi/playground-prompt-engineering")
  end

  subgraph Server_Components
    Core --> ServerSDK("@proj-airi/server-sdk")
    ServerShared("@proj-airi/server-shared") --> SVRT
    ServerShared --> ServerSDK
  end

  STT -->|Speaking| Unspeech
  SVRT -->|Playing Factorio| F_AGENT
  SVRT -->|Playing Minecraft| MC_AGENT

  subgraph Factorio_Agent
    F_AGENT("Factorio Agent")
    F_API("Factorio RCON API")
    factorio-server("factorio-server")
    F_MOD1("autorio")

    F_AGENT --> F_API -.-> factorio-server
    F_MOD1 -.-> factorio-server
  end

  subgraph Minecraft_Agent
    MC_AGENT("Minecraft Agent")
    Mineflayer("Mineflayer")
    minecraft-server("minecraft-server")

    MC_AGENT --> Mineflayer -.-> minecraft-server
  end

  XSAI("xsAI") --> Core
  XSAI --> F_AGENT
  XSAI --> MC_AGENT

  Core --> TauriMCP("@proj-airi/tauri-plugin-mcp")
  Memory_PGVector("@proj-airi/memory-pgvector") --> Memory

  style Core fill:#f9d4d4,stroke:#333,stroke-width:1px
  style AIRI fill:#fcf7f7,stroke:#333,stroke-width:1px
  style UI fill:#d4f9d4,stroke:#333,stroke-width:1px
  style Stage fill:#d4f9d4,stroke:#333,stroke-width:1px
  style UI_Components fill:#d4f9d4,stroke:#333,stroke-width:1px
  style Server_Components fill:#d4e6f9,stroke:#333,stroke-width:1px
  style Apps fill:#d4d4f9,stroke:#333,stroke-width:1px
  style Factorio_Agent fill:#f9d4f2,stroke:#333,stroke-width:1px
  style Minecraft_Agent fill:#f9d4f2,stroke:#333,stroke-width:1px

  style DBDriver fill:#f9f9d4,stroke:#333,stroke-width:1px
  style MemoryDriver fill:#f9f9d4,stroke:#333,stroke-width:1px
  style DB1 fill:#f9f9d4,stroke:#333,stroke-width:1px
  style Memory fill:#f9f9d4,stroke:#333,stroke-width:1px
  style Memory_PGVector fill:#f9f9d4,stroke:#333,stroke-width:1px
```

## Similar Projects

### Open sourced ones

- [kimjammer/Neuro: A recreation of Neuro-Sama originally created in 7 days.](https://github.com/kimjammer/Neuro): very well completed implementation.
- [SugarcaneDefender/z-waif](https://github.com/SugarcaneDefender/z-waif): Great at gaming, autonomous, and prompt engineering
- [semperai/amica](https://github.com/semperai/amica/): Great at VRM, WebXR
- [elizaOS/eliza](https://github.com/elizaOS/eliza): Great examples and software engineering on how to integrate agent into various of systems and APIs
- [ardha27/AI-Waifu-Vtuber](https://github.com/ardha27/AI-Waifu-Vtuber): Great about Twitch API integratio

... [README content truncated due to size. Visit the repository for the complete README] ...

]]> TypeScript