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[🌐 English](README.md) | [🇨🇳 中文](README.zh.md) | [🇯🇵 日本語](README.ja.md) | [🇰🇷 한국어](README.ko.md) | [🇩🇪 Deutsch](README.de.md) | [🇫🇷 Français](README.fr.md)
**All-in-One Agent Platform for Global × China Enterprises.**
*Wire every system you already run — global SaaS to the China stack — through one agent core.*
🌐 [Website](https://one.fim.ai/) · 📖 [Docs](https://docs.fim.ai) · 📋 [Changelog](https://docs.fim.ai/changelog) · 🐛 [Report Bug](https://github.com/fim-ai/fim-one/issues) · 💬 [Discord](https://discord.gg/z64czxdC7z) · 🐦 [Twitter](https://x.com/FIM_One) · 🏆 [Product Hunt](https://www.producthunt.com/products/fim-one)
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> [!TIP]
> **☁️ Skip the setup — try FIM One on Cloud.**
> A managed version is live at [cloud.fim.ai](https://cloud.fim.ai/) — no Docker, no API keys, no config. Sign in and start connecting your systems in seconds. _Early access, feedback welcome._
---
## Overview
Global enterprises run a sprawl of systems that don't talk to each other — ERP, CRM, OA, HR, finance, databases, IM platforms across regions. FIM One is the **all-in-one agent platform** that wires every system you already run into one agent core — global SaaS on one side, the full China stack (Feishu, WeCom, DingTalk, DM, Kingbase, etc.) on the other. One brain. Every system. Global SaaS × China Stack.
| Mode | What it is | Access |
| -------------- | ------------------------------------------------------- | ----------------------- |
| **Standalone** | General-purpose AI assistant — search, code, KB | Portal |
| **Copilot** | AI embedded in a host system's UI | iframe / widget / embed |
| **Hub** | Central AI orchestration across all connected systems | Portal / API |
```mermaid
graph LR
ERP <--> Hub["🧠 FIM One Agent Core"]
Database <--> Hub
Lark <--> Hub
Hub <--> CRM
Hub <--> OA
Hub <--> API[Custom API]
```
### Screenshots
**Dashboard** — stats, activity trends, token usage, and quick access to agents and conversations.
**Agent Chat** — ReAct reasoning with multi-step tool calling against a connected database.
**DAG Planner** — LLM-generated execution plan with parallel steps and live status tracking.
### Demo
**Using Agents**
**Using Planner Mode**
## Quick Start
### Docker (recommended)
```bash
git clone https://github.com/fim-ai/fim-one.git
cd fim-one
cp example.env .env
# Edit .env: set LLM_API_KEY (and optionally LLM_BASE_URL, LLM_MODEL)
docker compose up --build -d
```
Open http://localhost:3000 — on first launch you'll create an admin account. That's it.
```bash
docker compose up -d # start
docker compose down # stop
docker compose logs -f # view logs
```
### Local Development
Prerequisites: Python 3.11+, [uv](https://docs.astral.sh/uv/), Node.js 18+, pnpm.
```bash
git clone https://github.com/fim-ai/fim-one.git && cd fim-one
cp example.env .env # Edit: set LLM_API_KEY
uv sync --all-extras
cd frontend && pnpm install && cd ..
./start.sh dev # hot reload: Python --reload + Next.js HMR
```
| Command | What starts | URL |
| ---------------- | --------------------------------- | ------------------------------ |
| `./start.sh` | Next.js + FastAPI | localhost:3000 (UI) + :8000 |
| `./start.sh dev` | Same, with hot reload | Same |
| `./start.sh dev:api` | API only, dev mode (hot reload) | localhost:8000 |
| `./start.sh dev:ui` | Frontend only, dev mode (HMR) | localhost:3000 |
| `./start.sh api` | FastAPI only (headless) | localhost:8000/api |
> For production deployment (Docker, reverse proxy, zero-downtime updates), see the [Deployment Guide](https://docs.fim.ai/quickstart#production-deployment).
## Key Features
#### Cross-Border Connectivity
- **Three delivery modes** — Standalone assistant, embedded Copilot, or central Hub; same agent core.
- **Any system, one pattern** — Connect APIs, databases, MCP servers. Actions auto-register as agent tools with auth injection. Progressive disclosure meta-tools reduce token usage by 80%+ across all tool types.
- **Database connectors** — PostgreSQL, MySQL, Oracle, SQL Server, and enterprise databases common in China (DM, KingbaseES, GBase, Highgo) that most global platforms can't reach. Schema introspection and AI-powered annotation.
- **Three ways to build** — Import OpenAPI spec, AI chat builder, or connect MCP servers directly.
#### Planning & Execution
- **Dynamic DAG planning** — LLM decomposes goals into dependency graphs at runtime. No hard-coded workflows.
- **Concurrent execution** — Independent steps run in parallel via asyncio; auto re-plan up to 3 rounds.
- **ReAct agent** — Structured reasoning-and-acting loop with automatic error recovery.
- **Agent harness** — Production-grade execution environment: ContextGuard for 5-layer token-budget management, progressive-disclosure meta-tools to keep the tool surface tractable, and self-reflection loops to counter goal drift.
- **Hook System** — Deterministic enforcement that runs outside the LLM loop. First shipped: `FeishuGateHook` gates sensitive tool calls behind a human approval card posted to a Feishu group. Extensible to audit logging, read-only-mode guards, and rate limits (v0.9).
- **Content guardrails** — Three-layer safety: tool-permission hooks (actions), credential / SSRF / MCP-auth checks (protocols), and content guardrails (input/output text). Default jailbreak-phrase detector aborts the turn before the LLM is invoked, saving tokens and surfacing a clear blocked notice in chat. Output guardrails optional via `FIM_GUARDRAILS_OUTPUT`.
- **Auto-routing** — Classifies queries and routes to optimal mode (ReAct or DAG). Configurable via `AUTO_ROUTING`.
- **Extended thinking** — Chain-of-thought for OpenAI o-series, Gemini 2.5+, Claude.
- **Prompt-cache observability** — Anthropic prompt-cache `read/create` token counts captured per turn, surfaced in the chat `done` payload and logged so operators can verify cache hits and detect relay stations that don't honor the discount.
#### Workflow & Tools
- **Visual workflow editor** — 12 node types, drag-and-drop canvas (React Flow v12), import/export as JSON.
- **Smart file handling** — Uploaded files auto-inlined into context (small) or readable on-demand via `read_uploaded_file` tool. Intelligent document processing: PDFs, DOCX, and PPTX files get vision-aware processing with embedded image extraction when the model supports vision. Smart PDF mode extracts text from text-rich pages and renders scanned pages as images.
- **Universal document conversion** — Built-in `convert_to_markdown` tool turns PDF / Word / Excel / PowerPoint / HTML / images / audio / Outlook `.msg` / EPUB / YouTube transcripts into clean Markdown via Microsoft MarkItDown. Vision-capable LLMs OCR embedded images and scanned pages — works with Claude, Gemini, Bedrock, and any LiteLLM-supported provider, no per-provider adapter code.
- **Pluggable tools** — Python, Node.js, shell exec with optional Docker sandbox (`CODE_EXEC_BACKEND=docker`).
- **V4A patch editing** — Beyond `find_replace`, agents can apply line-hunk patches with fuzzy whitespace matching via `file_ops.apply_patch` — robust to multi-line edits where exact-substring match would be brittle.
- **Full RAG pipeline** — Jina embedding + LanceDB + hybrid retrieval + reranker + inline `[N]` citations. Vision-aware ingestion routes scanned PDFs and Office embedded images through the workspace's default vision LLM for OCR.
- **Tool artifacts** — Rich outputs (HTML previews, files) rendered in-chat.
#### Messaging Channels (v0.8)
- **Org-scoped IM bridge** — `BaseChannel` abstraction for outbound messaging across Slack, Microsoft Teams, Discord, Feishu (Lark), WeCom, and DingTalk. First shipping implementation is Feishu; Slack / Teams / WeCom / Email are next on the v0.9 roadmap.
- **Fernet-encrypted credentials** — App secrets and encrypt keys encrypted at rest; every inbound callback signature-verified.
- **Interactive approval cards** — Channel-native `GateHook` (Feishu today, Slack/Teams next) posts an Approve / Reject card to your group when a sensitive tool call fires; the tool blocks until a group member taps a verdict. Human-in-the-loop approval without a custom workflow engine.
- **Configurable approval routing per agent** — Three modes (Auto / Inline only / Channel only) with an approver-scope selector (initiator / agent owner / any org member). One audit path stamps `approver_user_id` and `decided_at` whether the verdict came from chat or from the channel. Auto mode falls back to inline if no channel is linked, so agents always get a real approval UX.
- **Task-completion notifications** — Long-running ReAct or DAG agents can push a summary card to the org's channel when work finishes. Configurable per-agent in Settings → Agent → Notifications.
- **Browse-and-pick UI** — No copying raw channel IDs from the vendor console; the portal calls the IM platform's API and shows a group picker.
#### Platform
- **Multi-tenant** — JWT auth, org isolation, admin panel with usage analytics and connector metrics. Multi-worker support via `WORKERS=N` with a Redis interrupt broker for cross-worker relay.
- **Marketplace** — Publish and subscribe to agents, connectors, KBs, skills, workflows.
- **Global skills (SOPs)** — Reusable operating procedures loaded for every user; progressive mode cuts tokens ~80%.
- **Stripe billing & per-user quotas** — Optional Pro-plan upgrade via Stripe Checkout + Customer Portal. Quota chain (per-user override → plan tier → system default) with `0` for unlimited. Admin feature flag gates the entire pipeline; private deployments without Stripe stay clean.
- **Evaluation Center** — Test-dataset management, parallel eval runs with LLM-graded judgments, per-case pass/fail/latency/token results viewer with auto-polling.
- **Conversation recovery** — Synthetic `tool_result` rows persist after interrupted turns; clients auto-reconnect dropped SSE streams via `/chat/resume` with exponential backoff and a "Reconnecting…" indicator.
- **6 languages** — EN, ZH, JA, KO, DE, FR. Translations are [fully automated](https://docs.fim.ai/quickstart#internationalization) — single glossary drives every LLM translation call (JSON, MDX, README), pre-commit hook refuses manual edits to generated locale files.
- **First-run setup wizard**, dark/light theme, command palette, streaming SSE, DAG visualization.
> Deep dive: [Architecture](https://docs.fim.ai/architecture/system-overview) · [Hook System](https://docs.fim.ai/architecture/hook-system) · [Channels](https://docs.fim.ai/configuration/channels/overview) · [Execution Modes](https://docs.fim.ai/concepts/execution-modes) · [Why FIM One](https://docs.fim.ai/why) · [Competitive Landscape](https://docs.fim.ai/strategy/competitive-landscape)
## Architecture
```mermaid
graph TB
subgraph app["Application Layer"]
a["Portal · API · iframe · Feishu · Slack · WeCom · DingTalk · Teams · Email · Contract Systems · Custom Webhooks"]
end
subgraph mid["FIM One"]
direction LR
m1["Connectors<br/>+ MCP Hub"] ~~~ m2["Orch Engine<br/>ReAct / DAG"] ~~~ m3["RAG /<br/>Knowledge"] ~~~ m5["Hook System<br/>+ Channels"] ~~~ m4["Auth /<br/>Admin"]
end
subgraph biz["Business Systems"]
b["ERP · CRM · OA · Finance · Databases · Contract Mgmt · Custom APIs"]
end
app --> mid --> biz
```
Each connector and channel is a standardized bridge — the agent doesn't know or care whether it's talking to SAP, a custom contract system, or a Feishu group. The Hook System runs platform code outside the LLM loop for approvals, audit, and rate limits; Channels carry outbound notifications and approval cards to external IM platforms. See [Connector Architecture](https://docs.fim.ai/architecture/connector-architecture), [Hook System](https://docs.fim.ai/architecture/hook-system), and [Channels](https://docs.fim.ai/configuration/channels/overview) for details.
## Configuration
FIM One works with **any OpenAI-compatible provider**:
| Provider | `LLM_API_KEY` | `LLM_BASE_URL` | `LLM_MODEL` |
| ------------------ | ------------- | ------------------------------ | -------------------- |
| **OpenAI** | `sk-...` | *(default)* | `gpt-4o` |
| **DeepSeek** | `sk-...` | `https://api.deepseek.com/v1` | `deepseek-chat` |
| **Anthropic** | `sk-ant-...` | `https://api.anthropic.com/v1` | `claude-sonnet-4-6` |
| **Ollama** (local) | `ollama` | `http://localhost:11434/v1` | `qwen2.5:14b` |
Minimal `.env`:
```bash
LLM_API_KEY=sk-your-key
# LLM_BASE_URL=https://api.openai.com/v1 # default
# LLM_MODEL=gpt-4o # default
JINA_API_KEY=jina_... # unlocks web tools + RAG
```
> Full reference: [Environment Variables](https://docs.fim.ai/configuration/environment-variables)
## Tech Stack
| Layer | Technology |
| ----------- | ------------------------------------------------------------------- |
| Backend | Python 3.11+, FastAPI, SQLAlchemy, Alembic, asyncio |
| Frontend | Next.js 14, React 18, Tailwind CSS, shadcn/ui, React Flow v12 |
| AI / RAG | OpenAI-compatible LLMs, Jina AI (embed + search), LanceDB |
| Database | SQLite (dev) / PostgreSQL (prod) |
| Messaging | `BaseChannel` abstraction (Slack, Teams, Discord, Feishu/Lark, WeCom, DingTalk), Fernet-encrypted credentials, HMAC signature verification |
| Infra | Docker, uv, pnpm, SSE streaming |
## Development
```bash
uv sync --all-extras # install dependencies
pytest # run tests
pytest --cov=fim_one # with coverage
ruff check src/ tests/ # lint
mypy src/ # type check
bash scripts/setup-hooks.sh # install git hooks (enables auto i18n)
```
## Roadmap
See the full [Roadmap](https://docs.fim.ai/roadmap) for version history and planned features.
## FAQ
Common questions about deployment, LLM providers, system requirements, and more — see the [FAQ](https://docs.fim.ai/faq).
## Contributing
We welcome contributions of all kinds — code, docs, translations, bug reports, and ideas.
> **Pioneer Program**: The first 100 contributors who get a PR merged are recognized as **Founding Contributors** with permanent credits, a badge, and priority issue support. [Learn more →](CONTRIBUTING.md#-pioneer-program)
**Quick links:**
- [**Contributing Guide**](CONTRIBUTING.md) — setup, conventions, PR process
- [**Development Conventions**](https://docs.fim.ai/contributing) — type safety, testing, and code quality standards
- [**Good First Issues**](https://github.com/fim-ai/fim-one/labels/good%20first%20issue) — curated for newcomers
- [**Open Issues**](https://github.com/fim-ai/fim-one/issues) — bugs & feature requests
**Security:** To report a vulnerability, please open a [GitHub issue](https://github.com/fim-ai/fim-one/issues) with the `[SECURITY]` tag. For sensitive disclosures, contact us via Discord DM.
## Activity
## Contributors
Thanks to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):
<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
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<td align="center" valign="top" width="12.5%"><a href="https://github.com/tao-hpu"><img src="https://avatars.githubusercontent.com/u/1250043?v=4?s=80" width="80px;" alt="Tao An"/><br /><sub><b>Tao An</b></sub></a><br /><a href="https://github.com/fim-ai/fim-one/commits?author=tao-hpu" title="Code">💻</a> <a href="#maintenance-tao-hpu" title="Maintenance">🚧</a> <a href="#design-tao-hpu" title="Design">🎨</a> <a href="https://github.com/fim-ai/fim-one/commits?author=tao-hpu" title="Documentation">📖</a> <a href="#projectManagement-tao-hpu" title="Project Management">📆</a> <a href="#ideas-tao-hpu" title="Ideas, Planning, & Feedback">🤔</a> <a href="#infra-tao-hpu" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a> <a href="https://github.com/fim-ai/fim-one/issues?q=author%3Atao-hpu" title="Bug reports">🐛</a> <a href="https://github.com/fim-ai/fim-one/commits?author=tao-hpu" title="Tests">⚠️</a></td>
<td align="center" valign="top" width="12.5%"><a href="https://github.com/tgonzalezc5"><img src="https://avatars.githubusercontent.com/u/102870299?v=4?s=80" width="80px;" alt="Teo Gonzalez Collazo"/><br /><sub><b>Teo Gonzalez Collazo</b></sub></a><br /><a href="https://github.com/fim-ai/fim-one/commits?author=tgonzalezc5" title="Code">💻</a> <a href="https://github.com/fim-ai/fim-one/commits?author=tgonzalezc5" title="Tests">⚠️</a></td>
<td align="center" valign="top" width="12.5%"><a href="https://github.com/Houjiawei330"><img src="https://avatars.githubusercontent.com/u/49180524?v=4?s=80" width="80px;" alt="Houx."/><br /><sub><b>Houx.</b></sub></a><br /><a href="https://github.com/fim-ai/fim-one/commits?author=Houjiawei330" title="Code">💻</a> <a href="https://github.com/fim-ai/fim-one/issues?q=author%3AHoujiawei330" title="Bug reports">🐛</a></td>
<td align="center" valign="top" width="12.5%"><a href="https://github.com/wcboy"><img src="https://avatars.githubusercontent.com/u/85050716?v=4?s=80" width="80px;" alt="Chenying Wang"/><br /><sub><b>Chenying Wang</b></sub></a><br /><a href="https://github.com/fim-ai/fim-one/commits?author=wcboy" title="Code">💻</a></td>
<td align="center" valign="top" width="12.5%"><a href="https://github.com/Joshua-Medvinsky"><img src="https://avatars.githubusercontent.com/u/76570188?v=4?s=80" width="80px;" alt="Joshua Medvinsky"/><br /><sub><b>Joshua Medvinsky</b></sub></a><br /><a href="#security-Joshua-Medvinsky" title="Security">🛡️</a></td>
<td align="center" valign="top" width="12.5%"><a href="https://github.com/Aryan-theccool"><img src="https://avatars.githubusercontent.com/u/146411259?v=4?s=80" width="80px;" alt="Aryan singh Bhadoria"/><br /><sub><b>Aryan singh Bhadoria</b></sub></a><br /><a href="https://github.com/fim-ai/fim-one/issues?q=author%3AAryan-theccool" title="Bug reports">🐛</a> <a href="https://github.com/fim-ai/fim-one/commits?author=Aryan-theccool" title="Documentation">📖</a> <a href="https://github.com/fim-ai/fim-one/commits?author=Aryan-theccool" title="Tests">⚠️</a> <a href="https://github.com/fim-ai/fim-one/commits?author=Aryan-theccool" title="Code">💻</a></td>
</tr>
</tbody>
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This project follows the [all-contributors](https://allcontributors.org/) specification. Contributions of any kind welcome!
## About FIM
FIM One is developed by [FIM](https://fim.ai). FIM is a brand shared by two independent companies: FIM Labs Pte. Ltd. (Singapore) and Beijing FIM Network Technology Co., Ltd. (Beijing, founded 2013).
## License
FIM One Source Available License. This is **not** an OSI-approved open source license.
**Permitted**: internal use, modification, distribution with license intact, embedding in non-competing applications.
**Restricted**: multi-tenant SaaS, competing agent platforms, white-labeling, removing branding.
For commercial licensing inquiries, please open an issue on [GitHub](https://github.com/fim-ai/fim-one).
See [LICENSE](LICENSE) for full terms.
---
<div align="center">
🌐 [Website](https://one.fim.ai/) · 📖 [Docs](https://docs.fim.ai) · 📋 [Changelog](https://docs.fim.ai/changelog) · 🐛 [Report Bug](https://github.com/fim-ai/fim-one/issues) · 💬 [Discord](https://discord.gg/z64czxdC7z) · 🐦 [Twitter](https://x.com/FIM_One) · 🏆 [Product Hunt](https://www.producthunt.com/products/fim-one)
</div>