Fix model resolution bug for non-Ollama models in easy API (v3.0.1)

purpose_agent/unified.py

@@ -178,30 +178,16 @@ class Agent:
     @staticmethod
     def _resolve_model(model: str, api_key: str | None = None) -> LLMBackend:
         """Resolve a model string to an LLMBackend."""
-        # Local Ollama models (contain ":" like "qwen3:1.7b")
-        if ":" in model and not model.startswith("http"):
-            from purpose_agent.slm_backends import OllamaBackend
-            return OllamaBackend(model=model)
-
-        # Known SLM registry keys
         from purpose_agent.slm_backends import SLM_REGISTRY
+        
+        # Known SLM registry keys
         if model in SLM_REGISTRY:
             from purpose_agent.slm_backends import create_slm_backend
             return create_slm_backend(model)
 
-        # OpenAI models
-        if model.startswith("gpt-") or model.startswith("o1") or model.startswith("o3"):
-            from purpose_agent.llm_backend import OpenAICompatibleBackend
-            return OpenAICompatibleBackend(model=model, api_key=api_key)
-
-        # HuggingFace models (contain "/")
-        if "/" in model:
-            from purpose_agent.llm_backend import HFInferenceBackend
-            return HFInferenceBackend(model_id=model, api_key=api_key)
-
-        # Fallback: try Ollama
-        from purpose_agent.slm_backends import OllamaBackend
-        return OllamaBackend(model=model)
+        # Delegate to the centralized resolver for all other models (e.g. groq:, openai:)
+        from purpose_agent.llm_backend import resolve_backend
+        return resolve_backend(model, api_key)
 
 
 class _ToolEnvironment(Environment):

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "purpose-agent"
-version = "3.0.0"
+version = "3.0.1"
 description = "A local-first self-improvement kernel for agents. Turns traces into tested memory so agents improve without fine-tuning."
 readme = "README.md"
 license = {text = "MIT"}