Rename model_*, pydantic reserves that namespace

libs/core/kiln_ai/adapters/ml_model_list.py

@@ -42,17 +42,17 @@ class KilnModelProvider(BaseModel):
 
 
 class KilnModel(BaseModel):
-    model_family: str
-    model_name: str
+    family: str
+    name: str
     providers: List[KilnModelProvider]
     supports_structured_output: bool = True
 
 
 built_in_models: List[KilnModel] = [
     # GPT 4o Mini
     KilnModel(
-        model_family=ModelFamily.gpt,
-        model_name=ModelName.gpt_4o_mini,
+        family=ModelFamily.gpt,
+        name=ModelName.gpt_4o_mini,
         providers=[
             KilnModelProvider(
                 name=ModelProviderName.openai,
@@ -62,8 +62,8 @@ class KilnModel(BaseModel):
     ),
     # GPT 4o
     KilnModel(
-        model_family=ModelFamily.gpt,
-        model_name=ModelName.gpt_4o,
+        family=ModelFamily.gpt,
+        name=ModelName.gpt_4o,
         providers=[
             KilnModelProvider(
                 name=ModelProviderName.openai,
@@ -73,8 +73,8 @@ class KilnModel(BaseModel):
     ),
     # Llama 3.1-8b
     KilnModel(
-        model_family=ModelFamily.llama,
-        model_name=ModelName.llama_3_1_8b,
+        family=ModelFamily.llama,
+        name=ModelName.llama_3_1_8b,
         providers=[
             KilnModelProvider(
                 name=ModelProviderName.groq,
@@ -97,8 +97,8 @@ class KilnModel(BaseModel):
     ),
     # Llama 3.1 70b
     KilnModel(
-        model_family=ModelFamily.llama,
-        model_name=ModelName.llama_3_1_70b,
+        family=ModelFamily.llama,
+        name=ModelName.llama_3_1_70b,
         providers=[
             KilnModelProvider(
                 name=ModelProviderName.groq,
@@ -122,8 +122,8 @@ class KilnModel(BaseModel):
     ),
     # Mistral Large
     KilnModel(
-        model_family=ModelFamily.mistral,
-        model_name=ModelName.mistral_large,
+        family=ModelFamily.mistral,
+        name=ModelName.mistral_large,
         providers=[
             KilnModelProvider(
                 name=ModelProviderName.amazon_bedrock,
@@ -141,8 +141,8 @@ class KilnModel(BaseModel):
     ),
     # Phi 3.5
     KilnModel(
-        model_family=ModelFamily.phi,
-        model_name=ModelName.phi_3_5,
+        family=ModelFamily.phi,
+        name=ModelName.phi_3_5,
         supports_structured_output=False,
         providers=[
             KilnModelProvider(
@@ -154,21 +154,19 @@ class KilnModel(BaseModel):
 ]
 
 
-def langchain_model_from(
-    model_name: str, provider_name: str | None = None
-) -> BaseChatModel:
-    if model_name not in ModelName.__members__:
-        raise ValueError(f"Invalid model_name: {model_name}")
+def langchain_model_from(name: str, provider_name: str | None = None) -> BaseChatModel:
+    if name not in ModelName.__members__:
+        raise ValueError(f"Invalid name: {name}")
 
-    # Select the model from built_in_models using the model_name
-    model = next(filter(lambda m: m.model_name == model_name, built_in_models))
+    # Select the model from built_in_models using the name
+    model = next(filter(lambda m: m.name == name, built_in_models))
     if model is None:
-        raise ValueError(f"Model {model_name} not found")
+        raise ValueError(f"Model {name} not found")
 
     # If a provider is provided, select the provider from the model's provider_config
     provider: KilnModelProvider | None = None
     if model.providers is None or len(model.providers) == 0:
-        raise ValueError(f"Model {model_name} has no providers")
+        raise ValueError(f"Model {name} has no providers")
     elif provider_name is None:
         # TODO: priority order
         provider = model.providers[0]
@@ -177,7 +175,7 @@ def langchain_model_from(
             filter(lambda p: p.name == provider_name, model.providers), None
         )
     if provider is None:
-        raise ValueError(f"Provider {provider_name} not found for model {model_name}")
+        raise ValueError(f"Provider {provider_name} not found for model {name}")
 
     if provider.name == ModelProviderName.openai:
         return ChatOpenAI(**provider.provider_options)
@@ -188,7 +186,7 @@ def langchain_model_from(
     elif provider.name == ModelProviderName.ollama:
         return ChatOllama(**provider.provider_options, base_url=ollama_base_url())
     else:
-        raise ValueError(f"Invalid model or provider: {model_name} - {provider_name}")
+        raise ValueError(f"Invalid model or provider: {name} - {provider_name}")
 
 
 def ollama_base_url():