feat: add vLLM/local LLM support

- Add vllm provider configuration in config schema
- Auto-detect vLLM endpoints and use hosted_vllm/ prefix for LiteLLM
- Pass api_base directly to acompletion for custom endpoints
- Add vLLM status display in CLI status command
- Add vLLM setup documentation in README

nanobot/providers/litellm_provider.py

@@ -32,11 +32,17 @@ class LiteLLMProvider(LLMProvider):
             (api_base and "openrouter" in api_base)
         )
         
+        # Track if using custom endpoint (vLLM, etc.)
+        self.is_vllm = bool(api_base) and not self.is_openrouter
+        
         # Configure LiteLLM based on provider
         if api_key:
             if self.is_openrouter:
                 # OpenRouter mode - set key
                 os.environ["OPENROUTER_API_KEY"] = api_key
+            elif self.is_vllm:
+                # vLLM/custom endpoint - uses OpenAI-compatible API
+                os.environ["OPENAI_API_KEY"] = api_key
             elif "anthropic" in default_model:
                 os.environ.setdefault("ANTHROPIC_API_KEY", api_key)
             elif "openai" in default_model or "gpt" in default_model:
@@ -75,6 +81,11 @@ class LiteLLMProvider(LLMProvider):
         if self.is_openrouter and not model.startswith("openrouter/"):
             model = f"openrouter/{model}"
         
+        # For vLLM, use hosted_vllm/ prefix per LiteLLM docs
+        # Convert openai/ prefix to hosted_vllm/ if user specified it
+        if self.is_vllm:
+            model = f"hosted_vllm/{model}"
+        
         kwargs: dict[str, Any] = {
             "model": model,
             "messages": messages,
@@ -82,6 +93,10 @@ class LiteLLMProvider(LLMProvider):
             "temperature": temperature,
         }
         
+        # Pass api_base directly for custom endpoints (vLLM, etc.)
+        if self.api_base:
+            kwargs["api_base"] = self.api_base
+        
         if tools:
             kwargs["tools"] = tools
             kwargs["tool_choice"] = "auto"