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feat: model registry and capabilities for multi-provider support (#2158)
* feat: Implement model registry and capabilities for multi-provider support - Added ModelRegistry to manage available models and their capabilities. - Introduced ModelProvider enum for different LLM providers. - Created ModelCapabilities dataclass to define model features. - Implemented methods to load models based on API keys and settings. - Added utility functions for model management in model_utils.py. - Updated settings.py to include provider-specific API keys. - Refactored LLM classes (Anthropic, OpenAI, Google, etc.) to utilize new model registry. - Enhanced utility functions to handle token limits and model validation. - Improved code structure and logging for better maintainability. * feat: Add model selection feature with API integration and UI component * feat: Add model selection and default model functionality in agent management * test: Update assertions and formatting in stream processing tests * refactor(llm): Standardize model identifier to model_id * fix tests --------- Co-authored-by: Alex <a@tushynski.me>
This commit is contained in:
Siddhant Rai
236
application/core/model_settings.py
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236
application/core/model_settings.py
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import logging
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from dataclasses import dataclass, field
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from enum import Enum
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from typing import Dict, List, Optional
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logger = logging.getLogger(__name__)
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class ModelProvider(str, Enum):
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OPENAI = "openai"
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AZURE_OPENAI = "azure_openai"
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ANTHROPIC = "anthropic"
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GROQ = "groq"
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GOOGLE = "google"
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HUGGINGFACE = "huggingface"
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LLAMA_CPP = "llama.cpp"
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DOCSGPT = "docsgpt"
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PREMAI = "premai"
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SAGEMAKER = "sagemaker"
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NOVITA = "novita"
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@dataclass
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class ModelCapabilities:
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supports_tools: bool = False
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supports_structured_output: bool = False
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supports_streaming: bool = True
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supported_attachment_types: List[str] = field(default_factory=list)
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context_window: int = 128000
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input_cost_per_token: Optional[float] = None
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output_cost_per_token: Optional[float] = None
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@dataclass
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class AvailableModel:
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id: str
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provider: ModelProvider
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display_name: str
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description: str = ""
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capabilities: ModelCapabilities = field(default_factory=ModelCapabilities)
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enabled: bool = True
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base_url: Optional[str] = None
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def to_dict(self) -> Dict:
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result = {
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"id": self.id,
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"provider": self.provider.value,
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"display_name": self.display_name,
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"description": self.description,
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"supported_attachment_types": self.capabilities.supported_attachment_types,
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"supports_tools": self.capabilities.supports_tools,
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"supports_structured_output": self.capabilities.supports_structured_output,
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"supports_streaming": self.capabilities.supports_streaming,
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"context_window": self.capabilities.context_window,
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"enabled": self.enabled,
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}
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if self.base_url:
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result["base_url"] = self.base_url
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return result
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class ModelRegistry:
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_instance = None
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_initialized = False
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def __new__(cls):
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if cls._instance is None:
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cls._instance = super().__new__(cls)
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return cls._instance
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def __init__(self):
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if not ModelRegistry._initialized:
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self.models: Dict[str, AvailableModel] = {}
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self.default_model_id: Optional[str] = None
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self._load_models()
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ModelRegistry._initialized = True
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@classmethod
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def get_instance(cls) -> "ModelRegistry":
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return cls()
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def _load_models(self):
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from application.core.settings import settings
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self.models.clear()
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self._add_docsgpt_models(settings)
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if settings.OPENAI_API_KEY or (
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settings.LLM_PROVIDER == "openai" and settings.API_KEY
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):
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self._add_openai_models(settings)
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if settings.OPENAI_API_BASE or (
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settings.LLM_PROVIDER == "azure_openai" and settings.API_KEY
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):
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self._add_azure_openai_models(settings)
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if settings.ANTHROPIC_API_KEY or (
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settings.LLM_PROVIDER == "anthropic" and settings.API_KEY
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):
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self._add_anthropic_models(settings)
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if settings.GOOGLE_API_KEY or (
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settings.LLM_PROVIDER == "google" and settings.API_KEY
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):
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self._add_google_models(settings)
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if settings.GROQ_API_KEY or (
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settings.LLM_PROVIDER == "groq" and settings.API_KEY
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):
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self._add_groq_models(settings)
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if settings.HUGGINGFACE_API_KEY or (
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settings.LLM_PROVIDER == "huggingface" and settings.API_KEY
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):
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self._add_huggingface_models(settings)
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# Default model selection
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if settings.LLM_NAME and settings.LLM_NAME in self.models:
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self.default_model_id = settings.LLM_NAME
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elif settings.LLM_PROVIDER and settings.API_KEY:
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for model_id, model in self.models.items():
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if model.provider.value == settings.LLM_PROVIDER:
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self.default_model_id = model_id
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break
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else:
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self.default_model_id = next(iter(self.models.keys()))
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logger.info(
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f"ModelRegistry loaded {len(self.models)} models, default: {self.default_model_id}"
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)
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def _add_openai_models(self, settings):
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from application.core.model_configs import OPENAI_MODELS
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if settings.OPENAI_API_KEY:
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for model in OPENAI_MODELS:
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self.models[model.id] = model
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return
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if settings.LLM_PROVIDER == "openai" and settings.LLM_NAME:
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for model in OPENAI_MODELS:
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if model.id == settings.LLM_NAME:
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self.models[model.id] = model
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return
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for model in OPENAI_MODELS:
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self.models[model.id] = model
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def _add_azure_openai_models(self, settings):
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from application.core.model_configs import AZURE_OPENAI_MODELS
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if settings.LLM_PROVIDER == "azure_openai" and settings.LLM_NAME:
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for model in AZURE_OPENAI_MODELS:
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if model.id == settings.LLM_NAME:
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self.models[model.id] = model
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return
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for model in AZURE_OPENAI_MODELS:
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self.models[model.id] = model
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def _add_anthropic_models(self, settings):
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from application.core.model_configs import ANTHROPIC_MODELS
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if settings.ANTHROPIC_API_KEY:
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for model in ANTHROPIC_MODELS:
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self.models[model.id] = model
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return
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if settings.LLM_PROVIDER == "anthropic" and settings.LLM_NAME:
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for model in ANTHROPIC_MODELS:
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if model.id == settings.LLM_NAME:
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self.models[model.id] = model
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return
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for model in ANTHROPIC_MODELS:
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self.models[model.id] = model
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def _add_google_models(self, settings):
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from application.core.model_configs import GOOGLE_MODELS
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if settings.GOOGLE_API_KEY:
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for model in GOOGLE_MODELS:
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self.models[model.id] = model
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return
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if settings.LLM_PROVIDER == "google" and settings.LLM_NAME:
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for model in GOOGLE_MODELS:
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if model.id == settings.LLM_NAME:
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self.models[model.id] = model
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return
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for model in GOOGLE_MODELS:
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self.models[model.id] = model
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def _add_groq_models(self, settings):
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from application.core.model_configs import GROQ_MODELS
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if settings.GROQ_API_KEY:
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for model in GROQ_MODELS:
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self.models[model.id] = model
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return
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if settings.LLM_PROVIDER == "groq" and settings.LLM_NAME:
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for model in GROQ_MODELS:
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if model.id == settings.LLM_NAME:
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self.models[model.id] = model
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return
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for model in GROQ_MODELS:
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self.models[model.id] = model
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def _add_docsgpt_models(self, settings):
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model_id = "docsgpt-local"
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model = AvailableModel(
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id=model_id,
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provider=ModelProvider.DOCSGPT,
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display_name="DocsGPT Model",
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description="Local model",
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capabilities=ModelCapabilities(
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supports_tools=False,
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supported_attachment_types=[],
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),
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)
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self.models[model_id] = model
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def _add_huggingface_models(self, settings):
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model_id = "huggingface-local"
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model = AvailableModel(
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id=model_id,
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provider=ModelProvider.HUGGINGFACE,
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display_name="Hugging Face Model",
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description="Local Hugging Face model",
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capabilities=ModelCapabilities(
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supports_tools=False,
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supported_attachment_types=[],
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),
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)
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self.models[model_id] = model
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def get_model(self, model_id: str) -> Optional[AvailableModel]:
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return self.models.get(model_id)
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def get_all_models(self) -> List[AvailableModel]:
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return list(self.models.values())
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def get_enabled_models(self) -> List[AvailableModel]:
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return [m for m in self.models.values() if m.enabled]
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def model_exists(self, model_id: str) -> bool:
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return model_id in self.models
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