更新 README.md

README.md

@@ -11,32 +11,71 @@ datasets:
 
 # HuggingClaw 🦀
 
-Deploy [OpenClaw](https://openclaw.ai) on HuggingFace Spaces for free — 2 vCPU, 16 GB RAM, 50 GB storage, always online.
+Deploy [OpenClaw](https://openclaw.ai) on HuggingFace Spaces for free —
+2 vCPU · 16 GB RAM · 50 GB storage · always online.
+
+AI provider calls are routed through **LiteLLM Proxy** so you can plug in
+any provider (OpenAI, Anthropic, Gemini, Azure, OpenRouter, Ollama, local
+endpoints …) with just two variables.
+
+---
 
 ## Required Secrets
 
-Set these in your Space → Settings → Repository secrets:
+Set these in **Space → Settings → Repository secrets**:
+
+| Secret | Example | Description |
+|--------|---------|-------------|
+| `HF_TOKEN` | `hf_xxx…` | HuggingFace token with **read + write** access |
+| `OPENCLAW_DATASET_REPO` | `your-name/HuggingClaw-data` | Private dataset repo used to persist OpenClaw config |
+| `LITELLM_API_KEY` | `sk-xxx…` | Your AI provider API key |
+| `LITELLM_MODEL` | `openai/gpt-4o` | Model in LiteLLM format (see table below) |
 
-| Secret | Description |
-|--------|-------------|
-| `HF_TOKEN` | Your HuggingFace token (needs read + write access) |
-| `OPENCLAW_DATASET_REPO` | Dataset repo to persist data, e.g. `your-name/HuggingClaw-data` |
+---
 
 ## Optional Secrets
 
 | Secret | Default | Description |
 |--------|---------|-------------|
-| `AUTO_CREATE_DATASET` | `false` | Set `true` to auto-create the dataset repo on first start |
-| `SYNC_INTERVAL` | `60` | Seconds between workspace sync pushes |
-| `OPENCLAW_DEFAULT_MODEL` | — | Default AI model, e.g. `gpt-4o` |
-| `ANTHROPIC_API_KEY` | — | Anthropic API key |
-| `OPENAI_API_KEY` | — | OpenAI API key |
-| `OPENROUTER_API_KEY` | — | OpenRouter API key |
+| `LITELLM_API_BASE` | *(provider default)* | Custom API endpoint — required for Azure, OpenRouter, local, etc. |
+| `AUTO_CREATE_DATASET` | `false` | Set `true` to auto-create the dataset repo on first boot |
+| `SYNC_INTERVAL` | `60` | Seconds between workspace sync pushes to HuggingFace |
+
+---
+
+## Model Examples
+
+| Provider | `LITELLM_MODEL` | `LITELLM_API_BASE` |
+|----------|----------------|-------------------|
+| OpenAI | `openai/gpt-4o` | *(leave empty)* |
+| Anthropic | `anthropic/claude-3-5-sonnet-20241022` | *(leave empty)* |
+| Google Gemini | `gemini/gemini-1.5-pro` | *(leave empty)* |
+| Azure OpenAI | `azure/<deployment-name>` | `https://<resource>.openai.azure.com` |
+| OpenRouter | `openrouter/openai/gpt-4o` | `https://openrouter.ai/api/v1` |
+| Ollama (local) | `ollama/llama3` | `http://localhost:11434` |
+| Any OpenAI-compat | `openai/<model-name>` | your custom base URL |
+
+---
 
 ## Setup
 
 1. **Duplicate this Space** on the HuggingFace Space page.
 2. Create a **private Dataset repo** at [huggingface.co/new-dataset](https://huggingface.co/new-dataset).
-3. Set `OPENCLAW_DATASET_REPO` and `HF_TOKEN` as Repository Secrets.
-4. Edit this README and update the `datasets:` field above to match your dataset repo.
-5. The Space will build and OpenClaw will be available on port 7860.
+3. Set all **Required Secrets** above.
+4. Edit this README: update the `datasets:` field to match your dataset repo.
+5. The Space will build; OpenClaw will be available on port **7860**.
+
+---
+
+## Architecture
+
+```
+HF Space (Docker)
+├── openclaw-hf-sync  ← Rust binary (pid 1 via tini)
+│   ├── on boot  : pull ~/.openclaw from HF dataset
+│   ├── every 60s: push ~/.openclaw changes to HF dataset
+│   └── on exit  : final push
+└── start.sh  ← child process
+    ├── LiteLLM Proxy  (127.0.0.1:4000)  ← routes to your AI provider
+    └── OpenClaw Gateway  (:7860)  ← points to LiteLLM Proxy
+```