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"""Model configuration helpers and preset models."""
from typing import Any
# Preset provider models for quick selection
PROVIDER_PRESETS = {
"GPT-5.2 Pro": {
"model": "gpt-5.2-pro-2025-12-11",
"tokenizer": "openai/gpt-5.2-pro-2025-12-11",
"max_context": 272000,
"api_key_env": "OPENAI_API_KEY",
},
"GPT-5.2": {
"model": "gpt-5.2-2025-12-11",
"tokenizer": "openai/gpt-5.2-2025-12-11",
"max_context": 272000,
"api_key_env": "OPENAI_API_KEY",
},
"GPT-5.1": {
"model": "gpt-5.1-2025-11-13",
"tokenizer": "openai/gpt-5.1-2025-11-13",
"max_context": 272000,
"api_key_env": "OPENAI_API_KEY",
},
"GPT-5": {
"model": "gpt-5-2025-08-07",
"tokenizer": "openai/gpt-5-2025-08-07",
"max_context": 272000,
"api_key_env": "OPENAI_API_KEY",
},
"GPT-5 Mini": {
"model": "gpt-5-mini-2025-08-07",
"tokenizer": "openai/gpt-5-mini-2025-08-07",
"max_context": 272000,
"api_key_env": "OPENAI_API_KEY",
},
"GPT-5 Nano": {
"model": "gpt-5-nano-2025-08-07",
"tokenizer": "openai/gpt-5-nano-2025-08-07",
"max_context": 272000,
"api_key_env": "OPENAI_API_KEY",
},
"Claude Opus 4.5": {
"model": "claude-opus-4-5-202511019",
"tokenizer": "anthropic/claude-opus-4-5-20251101",
"max_context": 200000,
"api_key_env": "ANTHROPIC_API_KEY",
},
"Claude Sonnet 4.5": {
"model": "claude-sonnet-4-5-20250929",
"tokenizer": "anthropic/claude-sonnet-4-5-20250929",
"max_context": 200000,
"api_key_env": "ANTHROPIC_API_KEY",
},
"Claude Haiku 4.5": {
"model": "claude-haiku-4-5-20251001",
"tokenizer": "anthropic/claude-haiku-4-5-20251001",
"max_context": 200000,
"api_key_env": "ANTHROPIC_API_KEY",
},
"Gemini 3.0 Pro": {
"model": "gemini/gemini-3-pro-preview",
"tokenizer": "gemini/gemini-3-pro-preview",
"max_context": 2000000,
"api_key_env": "GEMINI_API_KEY",
},
"Gemini 3.0 Flash": {
"model": "gemini/gemini-3-flash-preview",
"tokenizer": "gemini/gemini-3-flash-preview",
"max_context": 1000000,
"api_key_env": "GEMINI_API_KEY",
},
"Gemini 2.5 Pro": {
"model": "gemini/gemini-2.5-pro",
"tokenizer": "gemini/gemini-2.5-pro",
"max_context": 2000000,
"api_key_env": "GEMINI_API_KEY",
},
"Gemini 2.5 Flash": {
"model": "gemini/gemini-2.5-flash",
"tokenizer": "gemini/gemini-2.5-flash",
"max_context": 1000000,
"api_key_env": "GEMINI_API_KEY",
},
}
def create_local_model_config(
model: str,
api_base: str | None = None,
max_context: int = 131072,
tokenizer: str | None = None,
) -> dict[str, Any]:
"""
Create a local model configuration.
Args:
model: Model name (e.g., "ollama/llama2" or "gpt-3.5-turbo" for vLLM)
api_base: API base URL (defaults based on model type)
max_context: Maximum context window size
tokenizer: Tokenizer name for token counting
Returns:
Model configuration dictionary
"""
# Set default API base based on model type
if api_base is None:
if model.startswith("ollama/"):
api_base = "http://localhost:11434"
elif model.startswith("vllm/") or not model.startswith(("ollama/", "openrouter/")):
# Assume OpenAI-compatible (vLLM)
api_base = "http://localhost:8000/v1"
# Infer tokenizer if not provided
if tokenizer is None:
if model.startswith("ollama/"):
# Try to infer from model name
model_name = model.replace("ollama/", "")
tokenizer = f"hf/{model_name}"
else:
# For vLLM/OpenAI-compatible, try to infer
tokenizer = model.replace("vllm/", "")
return {
"type": "local",
"model": model,
"api_base": api_base,
"max_context": max_context,
"tokenizer": tokenizer,
}
def create_provider_model_config(
model: str,
api_key: str,
max_context: int = 128000,
tokenizer: str | None = None,
) -> dict[str, Any]:
"""
Create a provider model configuration.
Args:
model: Model name in litellm format
api_key: API key for the provider
max_context: Maximum context window size
tokenizer: Tokenizer name for token counting
Returns:
Model configuration dictionary
"""
# Infer tokenizer if not provided
if tokenizer is None:
# Try to infer from model name
if model.startswith("openai/") or not "/" in model:
# OpenAI models
model_name = model.replace("openai/", "")
tokenizer = f"openai/{model_name}"
elif model.startswith("anthropic/") or model.startswith("claude-"):
# Anthropic models
model_name = model.replace("anthropic/", "")
tokenizer = f"anthropic/{model_name}"
elif model.startswith("gemini/"):
# Gemini models
model_name = model.replace("gemini/", "")
tokenizer = f"gemini/{model_name}"
else:
# Generic fallback
tokenizer = "gpt2"
return {
"type": "provider",
"model": model,
"api_key": api_key,
"max_context": max_context,
"tokenizer": tokenizer,
}
def get_provider_from_model(model: str) -> str:
"""
Infer provider name from model identifier.
Args:
model: Model name in litellm format
Returns:
Provider name hint (e.g., "openai", "anthropic", "gemini")
"""
model_lower = model.lower()
if model_lower.startswith("openai/") or not "/" in model:
return "openai"
elif model_lower.startswith("anthropic/") or model_lower.startswith("claude-"):
return "anthropic"
elif model_lower.startswith("gemini/"):
return "gemini"
elif model_lower.startswith("openrouter/"):
return "openrouter"
elif model_lower.startswith("cohere/"):
return "cohere"
elif model_lower.startswith("mistral/"):
return "mistral"
else:
return "other"
def get_api_key_env_name(provider: str) -> str:
"""
Get the environment variable name for API key based on provider.
Args:
provider: Provider name
Returns:
Environment variable name for API key
"""
provider_to_key = {
"openai": "OPENAI_API_KEY",
"anthropic": "ANTHROPIC_API_KEY",
"gemini": "GEMINI_API_KEY",
"openrouter": "OPENROUTER_API_KEY",
"cohere": "COHERE_API_KEY",
"mistral": "MISTRAL_API_KEY",
"other": "API_KEY",
}
return provider_to_key.get(provider.lower(), "API_KEY")
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