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#!/usr/bin/env python3
"""
Model management system for GAIA agent.
Handles model initialization, fallback chains, and lifecycle management.
"""
import os
import time
import random
from typing import Optional, List, Dict, Any, Union
from abc import ABC, abstractmethod
from enum import Enum
from ..config.settings import Config, ModelType, config
from ..utils.exceptions import (
ModelError, ModelNotAvailableError, ModelAuthenticationError,
ModelOverloadedError, create_error
)
class ModelStatus(Enum):
"""Model status states."""
AVAILABLE = "available"
UNAVAILABLE = "unavailable"
OVERLOADED = "overloaded"
AUTHENTICATING = "authenticating"
ERROR = "error"
class ModelProvider(ABC):
"""Abstract base class for model providers."""
def __init__(self, name: str, model_type: ModelType):
self.name = name
self.model_type = model_type
self.status = ModelStatus.UNAVAILABLE
self.last_error: Optional[str] = None
self.retry_count = 0
self.last_used = None
@abstractmethod
def initialize(self) -> bool:
"""Initialize the model provider. Returns True if successful."""
pass
@abstractmethod
def is_available(self) -> bool:
"""Check if the model is available for use."""
pass
@abstractmethod
def create_model(self, **kwargs):
"""Create model instance."""
pass
def reset_error_state(self) -> None:
"""Reset error state for retry attempts."""
self.retry_count = 0
self.last_error = None
self.status = ModelStatus.UNAVAILABLE
def record_usage(self) -> None:
"""Record model usage timestamp."""
self.last_used = time.time()
def handle_error(self, error: Exception) -> None:
"""Handle and categorize model errors."""
error_str = str(error).lower()
if "overloaded" in error_str or "503" in error_str:
self.status = ModelStatus.OVERLOADED
self.last_error = "Model overloaded"
elif "authentication" in error_str or "401" in error_str or "403" in error_str:
self.status = ModelStatus.ERROR
self.last_error = "Authentication failed"
else:
self.status = ModelStatus.ERROR
self.last_error = str(error)
self.retry_count += 1
class LiteLLMProvider(ModelProvider):
"""Provider for LiteLLM-based models (Gemini, Kluster.ai)."""
def __init__(self, model_name: str, api_key: str, api_base: Optional[str] = None):
self.model_name = model_name
self.api_key = api_key
self.api_base = api_base
self._model_instance = None
model_type = self._determine_model_type(model_name)
super().__init__(model_name, model_type)
def _determine_model_type(self, model_name: str) -> ModelType:
"""Determine model type from name."""
if "gemini" in model_name.lower():
return ModelType.GEMINI
elif hasattr(self, 'api_base') and self.api_base and "kluster" in str(self.api_base).lower():
return ModelType.KLUSTER
else:
return ModelType.QWEN
def initialize(self) -> bool:
"""Initialize LiteLLM model."""
try:
# Import the class from the same module
from .providers import LiteLLMModel
self.status = ModelStatus.AUTHENTICATING
# Configure environment
if self.model_type == ModelType.GEMINI:
os.environ["GEMINI_API_KEY"] = self.api_key
elif self.api_base:
os.environ["OPENAI_API_KEY"] = self.api_key
os.environ["OPENAI_API_BASE"] = self.api_base
# Create model instance
self._model_instance = LiteLLMModel(
model_name=self.model_name,
api_key=self.api_key,
api_base=self.api_base
)
self.status = ModelStatus.AVAILABLE
return True
except Exception as e:
self.handle_error(e)
return False
def is_available(self) -> bool:
"""Check if model is available."""
return self.status == ModelStatus.AVAILABLE and self._model_instance is not None
def create_model(self, **kwargs):
"""Create model instance."""
if not self.is_available():
raise ModelNotAvailableError(f"Model {self.name} is not available")
self.record_usage()
return self._model_instance
class HuggingFaceProvider(ModelProvider):
"""Provider for HuggingFace models."""
def __init__(self, model_name: str, api_key: str):
super().__init__(model_name, ModelType.QWEN)
self.model_name = model_name
self.api_key = api_key
self._model_instance = None
def initialize(self) -> bool:
"""Initialize HuggingFace model."""
try:
from smolagents import InferenceClientModel
self.status = ModelStatus.AUTHENTICATING
self._model_instance = InferenceClientModel(
model_id=self.model_name,
token=self.api_key
)
self.status = ModelStatus.AVAILABLE
return True
except Exception as e:
self.handle_error(e)
return False
def is_available(self) -> bool:
"""Check if model is available."""
return self.status == ModelStatus.AVAILABLE and self._model_instance is not None
def create_model(self, **kwargs):
"""Create model instance."""
if not self.is_available():
raise ModelNotAvailableError(f"Model {self.name} is not available")
self.record_usage()
return self._model_instance
class ModelManager:
"""Manages model providers and fallback chains."""
def __init__(self, config_instance: Optional[Config] = None):
self.config = config_instance or config
self.providers: Dict[str, ModelProvider] = {}
self.fallback_chain: List[str] = []
self.current_provider: Optional[str] = None
self._initialize_providers()
def _initialize_providers(self) -> None:
"""Initialize all available model providers."""
# Kluster.ai models
if self.config.has_api_key("kluster"):
kluster_key = self.config.get_api_key("kluster")
for model_key, model_name in self.config.model.KLUSTER_MODELS.items():
provider_name = f"kluster_{model_key}"
provider = LiteLLMProvider(
model_name=model_name,
api_key=kluster_key,
api_base=self.config.model.KLUSTER_API_BASE
)
self.providers[provider_name] = provider
# Gemini models
if self.config.has_api_key("gemini"):
gemini_key = self.config.get_api_key("gemini")
provider = LiteLLMProvider(
model_name=self.config.model.GEMINI_MODEL,
api_key=gemini_key
)
self.providers["gemini"] = provider
# HuggingFace models
if self.config.has_api_key("huggingface"):
hf_key = self.config.get_api_key("huggingface")
provider = HuggingFaceProvider(
model_name=self.config.model.QWEN_MODEL,
api_key=hf_key
)
self.providers["qwen"] = provider
# Set up fallback chain
self._setup_fallback_chain()
def _setup_fallback_chain(self) -> None:
"""Set up model fallback chain based on availability and preference."""
# Priority order: Kluster.ai (highest tier) -> Gemini -> Qwen
priority_providers = []
# Add Kluster.ai models (prefer qwen3-235b)
if "kluster_qwen3-235b" in self.providers:
priority_providers.append("kluster_qwen3-235b")
elif "kluster_gemma3-27b" in self.providers:
priority_providers.append("kluster_gemma3-27b")
# Add other available providers
if "gemini" in self.providers:
priority_providers.append("gemini")
if "qwen" in self.providers:
priority_providers.append("qwen")
self.fallback_chain = priority_providers
if not self.fallback_chain:
raise ModelNotAvailableError("No model providers available")
def initialize_all(self) -> Dict[str, bool]:
"""Initialize all model providers."""
results = {}
for name, provider in self.providers.items():
try:
success = provider.initialize()
results[name] = success
if success and self.current_provider is None:
self.current_provider = name
except Exception as e:
results[name] = False
provider.handle_error(e)
return results
def get_current_model(self, **kwargs):
"""Get current active model."""
if self.current_provider is None:
self._select_best_provider()
if self.current_provider is None:
raise ModelNotAvailableError("No models available")
provider = self.providers[self.current_provider]
try:
return provider.create_model(**kwargs)
except Exception as e:
provider.handle_error(e)
# Try to switch to fallback
if self._switch_to_fallback():
return self.get_current_model(**kwargs)
else:
raise ModelError(f"All models failed: {str(e)}")
def _select_best_provider(self) -> None:
"""Select the best available provider from fallback chain."""
for provider_name in self.fallback_chain:
provider = self.providers.get(provider_name)
if provider and provider.is_available():
self.current_provider = provider_name
return
elif provider and provider.status == ModelStatus.UNAVAILABLE:
# Try to initialize
if provider.initialize():
self.current_provider = provider_name
return
self.current_provider = None
def _switch_to_fallback(self) -> bool:
"""Switch to next available model in fallback chain."""
if self.current_provider is None:
return False
try:
current_index = self.fallback_chain.index(self.current_provider)
# Try next providers in chain
for i in range(current_index + 1, len(self.fallback_chain)):
provider_name = self.fallback_chain[i]
provider = self.providers[provider_name]
if provider.is_available() or provider.initialize():
self.current_provider = provider_name
return True
except ValueError:
pass
# No fallback available
self.current_provider = None
return False
def retry_current_model(self, max_retries: int = 3) -> bool:
"""Retry current model with exponential backoff."""
if self.current_provider is None:
return False
provider = self.providers[self.current_provider]
for attempt in range(max_retries):
if provider.status == ModelStatus.OVERLOADED:
wait_time = (2 ** attempt) + random.random()
time.sleep(wait_time)
# Reset error state and try to reinitialize
provider.reset_error_state()
if provider.initialize():
return True
return False
def get_model_status(self) -> Dict[str, Dict[str, Any]]:
"""Get status of all model providers."""
status = {}
for name, provider in self.providers.items():
status[name] = {
"status": provider.status.value,
"model_type": provider.model_type.value,
"last_error": provider.last_error,
"retry_count": provider.retry_count,
"last_used": provider.last_used,
"is_current": name == self.current_provider
}
return status
def switch_to_provider(self, provider_name: str) -> bool:
"""Manually switch to specific provider."""
if provider_name not in self.providers:
raise ModelNotAvailableError(f"Provider {provider_name} not found")
provider = self.providers[provider_name]
if provider.is_available() or provider.initialize():
self.current_provider = provider_name
return True
return False
def get_available_providers(self) -> List[str]:
"""Get list of available providers."""
available = []
for name, provider in self.providers.items():
if provider.is_available():
available.append(name)
return available
def reset_all_providers(self) -> None:
"""Reset all providers to allow retry."""
for provider in self.providers.values():
provider.reset_error_state()
self.current_provider = None
self._select_best_provider()
# Monkey patch for smolagents compatibility
def monkey_patch_smolagents():
"""Apply compatibility patches for smolagents."""
try:
import smolagents.monitoring
from smolagents.monitoring import TokenUsage
# Store original update_metrics function
original_update_metrics = smolagents.monitoring.Monitor.update_metrics
def patched_update_metrics(self, step_log):
"""Patched version that handles dict token_usage"""
try:
# If token_usage is a dict, convert it to TokenUsage object
if hasattr(step_log, 'token_usage') and isinstance(step_log.token_usage, dict):
token_dict = step_log.token_usage
# Create TokenUsage object from dict
step_log.token_usage = TokenUsage(
input_tokens=token_dict.get('prompt_tokens', 0),
output_tokens=token_dict.get('completion_tokens', 0)
)
# Call original function
return original_update_metrics(self, step_log)
except Exception as e:
# If patching fails, try to handle gracefully
print(f"Token usage patch warning: {e}")
return original_update_metrics(self, step_log)
# Apply the patch
smolagents.monitoring.Monitor.update_metrics = patched_update_metrics
print("✅ Applied smolagents token usage compatibility patch")
except ImportError:
print("⚠️ smolagents not available, skipping compatibility patch")
except Exception as e:
print(f"⚠️ Failed to apply smolagents patch: {e}")
# Apply monkey patch on import
monkey_patch_smolagents() |