feat: add support for self hosted llm models

api/services/configuration/check_validity.py

@@ -40,6 +40,7 @@ class UserConfigurationValidator:
             ServiceProviders.SPEECHMATICS.value: self._check_speechmatics_api_key,
             ServiceProviders.CAMB.value: self._check_camb_api_key,
             ServiceProviders.AWS_BEDROCK.value: self._check_aws_bedrock_api_key,
+            ServiceProviders.SELF_HOSTED.value: self._check_self_hosted_api_key,
         }
 
     async def validate(self, configuration: UserConfiguration) -> APIKeyStatusResponse:
@@ -74,6 +75,20 @@ class UserConfigurationValidator:
 
         provider = service_config.provider
 
+        # Self-hosted doesn't require an API key
+        if provider == ServiceProviders.SELF_HOSTED.value:
+            try:
+                if not self._check_self_hosted_api_key(provider, service_config):
+                    return [
+                        {
+                            "model": service_name,
+                            "message": f"Invalid {provider} configuration",
+                        }
+                    ]
+            except ValueError as e:
+                return [{"model": service_name, "message": str(e)}]
+            return []
+
         # AWS Bedrock uses AWS credentials instead of api_key
         if provider == ServiceProviders.AWS_BEDROCK.value:
             try:
@@ -163,7 +178,12 @@ class UserConfigurationValidator:
 
     def _check_camb_api_key(self, model: str, api_key: str) -> bool:
         return True
-      
+
+    def _check_self_hosted_api_key(self, model: str, service_config) -> bool:
+        if not getattr(service_config, "base_url", None):
+            raise ValueError("base_url is required for self-hosted LLM")
+        return True
+
     def _check_aws_bedrock_api_key(self, model: str, service_config) -> bool:
         if not service_config.aws_access_key or not service_config.aws_secret_key:
             raise ValueError("AWS access key and secret key are required for Bedrock")

api/services/configuration/registry.py

@@ -27,6 +27,7 @@ class ServiceProviders(str, Enum):
     SPEECHMATICS = "speechmatics"
     CAMB = "camb"
     AWS_BEDROCK = "aws_bedrock"
+    SELF_HOSTED = "self_hosted"
 
 
 class BaseServiceConfiguration(BaseModel):
@@ -40,6 +41,7 @@ class BaseServiceConfiguration(BaseModel):
         ServiceProviders.AZURE,
         ServiceProviders.DOGRAH,
         ServiceProviders.AWS_BEDROCK,
+        ServiceProviders.SELF_HOSTED,
         # ServiceProviders.SARVAM,
     ]
     api_key: str | list[str]
@@ -249,6 +251,22 @@ class AWSBedrockLLMConfiguration(BaseLLMConfiguration):
     api_key: str | list[str] | None = Field(default=None)
 
 
+SELF_HOSTED_LLM_MODELS = ["llama3", "mistral", "phi3", "qwen2", "gemma2", "deepseek-r1"]
+
+
+@register_llm
+class SelfHostedLLMConfiguration(BaseLLMConfiguration):
+    provider: Literal[ServiceProviders.SELF_HOSTED] = ServiceProviders.SELF_HOSTED
+    model: str = Field(
+        default="llama3", json_schema_extra={"examples": SELF_HOSTED_LLM_MODELS}
+    )
+    base_url: str = Field(
+        default="http://localhost:11434/v1",
+        description="OpenAI-compatible endpoint (Ollama, vLLM, etc.)",
+    )
+    api_key: str | list[str] | None = Field(default=None)
+
+
 LLMConfig = Annotated[
     Union[
         OpenAILLMService,
@@ -258,6 +276,7 @@ LLMConfig = Annotated[
         AzureLLMService,
         DograhLLMService,
         AWSBedrockLLMConfiguration,
+        SelfHostedLLMConfiguration,
     ],
     Field(discriminator="provider"),
 ]
@@ -334,6 +353,12 @@ class CartesiaTTSConfiguration(BaseTTSConfiguration):
     )
     voice: str = Field(default="3faa81ae-d3d8-4ab1-9e44-e50e46d33c30")
     speed: float = Field(default=1.0, ge=0.6, le=1.5, description="Speed of the voice")
+    volume: float = Field(
+        default=1.0,
+        ge=0.5,
+        le=2.0,
+        description="Volume multiplier for generated speech",
+    )
 
 
 SARVAM_TTS_MODELS = ["bulbul:v2", "bulbul:v3"]