docs: add automatic model routing to README

README.md

@@ -7,9 +7,9 @@ A unified, high-performance LLM proxy gateway built in Go. It provides OpenAI-co
 - **Unified API:** OpenAI-compatible `/v1/chat/completions`, `/v1/images/generations`, `/v1/responses`, and `/v1/models` endpoints.
   - The `/v1/responses` endpoint (OpenAI Responses API) is currently supported for OpenAI models only. Non-OpenAI providers (Gemini, DeepSeek, Moonshot, Grok, Ollama) return a "not supported" response.
 - **Multi-Provider Support:**
-  - **OpenAI:** GPT-4o, GPT-4o Mini, o1, o3 reasoning models, DALL-E 2/3 image generation.
-  - **Google Gemini:** Gemini 2.0 Flash, Pro, and vision models (with native CoT support), Imagen 3 image generation.
-  - **DeepSeek:** DeepSeek Chat and Reasoner (R1) models.
+  - **OpenAI:** GPT-4o, GPT-4o Mini, o1, o3 reasoning models, DALL-E 2/3 image generation. Group: `openai-auto`.
+  - **Google Gemini:** Gemini 2.0 Flash, Pro, and vision models (with native CoT support), Imagen 3 image generation. Group: `gemini-auto`.
+  - **DeepSeek:** DeepSeek Chat and Reasoner (R1) models. Group: `deepseek-auto`.
   - **Moonshot:** Kimi K2.5 and other Kimi models.
   - **xAI Grok:** Grok-4 models.
   - **Ollama:** Local LLMs running on your network.
@@ -20,6 +20,10 @@ A unified, high-performance LLM proxy gateway built in Go. It provides OpenAI-co
   - **Streaming Support:** Full SSE (Server-Sent Events) support for all providers.
 - **Multimodal (Vision):** Image processing (Base64 and remote URLs) across compatible providers.
 - **Image Generation:** DALL-E 2/3 (OpenAI) and Imagen 3 (Gemini) via OpenAI-compatible `/v1/images/generations` endpoint.
+- **Automatic Model Routing:** Define model groups (e.g. `deepseek-auto`) that route to the best concrete model based on the task.
+  - **Heuristic strategy:** Free, zero-latency keyword matching (e.g. "debug" or "step by step" routes to the reasoning model).
+  - **Classifier strategy:** Uses a cheap LLM to rate task complexity, then selects the appropriate model.
+  - Pre-seeded with `openai-auto`, `deepseek-auto`, and `gemini-auto` groups. Managed via the dashboard or API.
 - **Multi-User Access Control:**
   - **Admin Role:** Full access to all dashboard features, user management, and system configuration.
   - **Viewer Role:** Read-only access to usage analytics, costs, and monitoring.
@@ -106,6 +110,8 @@ Access the dashboard at `http://localhost:8080`.
 - **Usage:** Summary stats, time-series analytics, and provider breakdown.
 - **Clients:** API key management and per-client usage tracking.
 - **Providers:** Provider configuration and status monitoring.
+- **Model Groups:** Define auto-routing groups with heuristic or classifier strategies.
+- **Models:** Model enable/disable and cost configuration.
 - **Users:** Admin-only user management for dashboard access.
 - **Monitoring:** Live request stream via WebSocket.
 
@@ -172,6 +178,33 @@ print(response.output_text)
 
 **Note:** The `/v1/responses` endpoint is currently supported for OpenAI models only. Requests routed to Gemini, DeepSeek, Moonshot, Grok, or Ollama models return a "not supported" error.
 
+### Automatic Model Routing
+
+Use a model group name to let gophergate pick the best model automatically:
+
+```python
+from openai import OpenAI
+
+client = OpenAI(
+    base_url="http://localhost:8080/v1",
+    api_key="YOUR_CLIENT_API_KEY"
+)
+
+# Simple query - routes to the cheap/fast model in the group
+response = client.chat.completions.create(
+    model="deepseek-auto",
+    messages=[{"role": "user", "content": "What is 2+2?"}]
+)
+
+# Complex query - routes to the reasoning model automatically
+response = client.chat.completions.create(
+    model="openai-auto",
+    messages=[{"role": "user", "content": "Debug this Python code and explain step by step..."}]
+)
+```
+
+Pre-seeded groups: `openai-auto` (gpt-4o-mini / gpt-4o), `deepseek-auto` (deepseek-chat / deepseek-reasoner), `gemini-auto` (gemini-2.0-flash / gemini-2.5-pro). By default these use heuristic keyword matching. Switch any group to classifier mode in the dashboard to use LLM-based complexity rating instead.
+
 ### Image Generation (DALL-E / Imagen)
 
 ```python