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Merge Landrun + Browser-Use + Chromium with AI agent support (without binary files)
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"""
Convenient access to LLM models.
Usage:
from browser_use import llm
# Simple model access
model = llm.azure_gpt_4_1_mini
model = llm.openai_gpt_4o
model = llm.google_gemini_2_5_pro
model = llm.bu_latest
"""
import os
from typing import TYPE_CHECKING
from browser_use.llm.azure.chat import ChatAzureOpenAI
from browser_use.llm.browser_use.chat import ChatBrowserUse
from browser_use.llm.cerebras.chat import ChatCerebras
from browser_use.llm.google.chat import ChatGoogle
from browser_use.llm.openai.chat import ChatOpenAI
# Optional OCI import
try:
from browser_use.llm.oci_raw.chat import ChatOCIRaw
OCI_AVAILABLE = True
except ImportError:
ChatOCIRaw = None
OCI_AVAILABLE = False
if TYPE_CHECKING:
from browser_use.llm.base import BaseChatModel
# Type stubs for IDE autocomplete
openai_gpt_4o: 'BaseChatModel'
openai_gpt_4o_mini: 'BaseChatModel'
openai_gpt_4_1_mini: 'BaseChatModel'
openai_o1: 'BaseChatModel'
openai_o1_mini: 'BaseChatModel'
openai_o1_pro: 'BaseChatModel'
openai_o3: 'BaseChatModel'
openai_o3_mini: 'BaseChatModel'
openai_o3_pro: 'BaseChatModel'
openai_o4_mini: 'BaseChatModel'
openai_gpt_5: 'BaseChatModel'
openai_gpt_5_mini: 'BaseChatModel'
openai_gpt_5_nano: 'BaseChatModel'
azure_gpt_4o: 'BaseChatModel'
azure_gpt_4o_mini: 'BaseChatModel'
azure_gpt_4_1_mini: 'BaseChatModel'
azure_o1: 'BaseChatModel'
azure_o1_mini: 'BaseChatModel'
azure_o1_pro: 'BaseChatModel'
azure_o3: 'BaseChatModel'
azure_o3_mini: 'BaseChatModel'
azure_o3_pro: 'BaseChatModel'
azure_gpt_5: 'BaseChatModel'
azure_gpt_5_mini: 'BaseChatModel'
google_gemini_2_0_flash: 'BaseChatModel'
google_gemini_2_0_pro: 'BaseChatModel'
google_gemini_2_5_pro: 'BaseChatModel'
google_gemini_2_5_flash: 'BaseChatModel'
google_gemini_2_5_flash_lite: 'BaseChatModel'
cerebras_llama3_1_8b: 'BaseChatModel'
cerebras_llama3_3_70b: 'BaseChatModel'
cerebras_gpt_oss_120b: 'BaseChatModel'
cerebras_llama_4_scout_17b_16e_instruct: 'BaseChatModel'
cerebras_llama_4_maverick_17b_128e_instruct: 'BaseChatModel'
cerebras_qwen_3_32b: 'BaseChatModel'
cerebras_qwen_3_235b_a22b_instruct_2507: 'BaseChatModel'
cerebras_qwen_3_235b_a22b_thinking_2507: 'BaseChatModel'
cerebras_qwen_3_coder_480b: 'BaseChatModel'
bu_latest: 'BaseChatModel'
bu_1_0: 'BaseChatModel'
def get_llm_by_name(model_name: str):
"""
Factory function to create LLM instances from string names with API keys from environment.
Args:
model_name: String name like 'azure_gpt_4_1_mini', 'openai_gpt_4o', etc.
Returns:
LLM instance with API keys from environment variables
Raises:
ValueError: If model_name is not recognized
"""
if not model_name:
raise ValueError('Model name cannot be empty')
# Parse model name
parts = model_name.split('_', 1)
if len(parts) < 2:
raise ValueError(f"Invalid model name format: '{model_name}'. Expected format: 'provider_model_name'")
provider = parts[0]
model_part = parts[1]
# Convert underscores back to dots/dashes for actual model names
if 'gpt_4_1_mini' in model_part:
model = model_part.replace('gpt_4_1_mini', 'gpt-4.1-mini')
elif 'gpt_4o_mini' in model_part:
model = model_part.replace('gpt_4o_mini', 'gpt-4o-mini')
elif 'gpt_4o' in model_part:
model = model_part.replace('gpt_4o', 'gpt-4o')
elif 'gemini_2_0' in model_part:
model = model_part.replace('gemini_2_0', 'gemini-2.0').replace('_', '-')
elif 'gemini_2_5' in model_part:
model = model_part.replace('gemini_2_5', 'gemini-2.5').replace('_', '-')
elif 'llama3_1' in model_part:
model = model_part.replace('llama3_1', 'llama3.1').replace('_', '-')
elif 'llama3_3' in model_part:
model = model_part.replace('llama3_3', 'llama-3.3').replace('_', '-')
elif 'llama_4_scout' in model_part:
model = model_part.replace('llama_4_scout', 'llama-4-scout').replace('_', '-')
elif 'llama_4_maverick' in model_part:
model = model_part.replace('llama_4_maverick', 'llama-4-maverick').replace('_', '-')
elif 'gpt_oss_120b' in model_part:
model = model_part.replace('gpt_oss_120b', 'gpt-oss-120b')
elif 'qwen_3_32b' in model_part:
model = model_part.replace('qwen_3_32b', 'qwen-3-32b')
elif 'qwen_3_235b_a22b_instruct' in model_part:
if model_part.endswith('_2507'):
model = model_part.replace('qwen_3_235b_a22b_instruct_2507', 'qwen-3-235b-a22b-instruct-2507')
else:
model = model_part.replace('qwen_3_235b_a22b_instruct', 'qwen-3-235b-a22b-instruct-2507')
elif 'qwen_3_235b_a22b_thinking' in model_part:
if model_part.endswith('_2507'):
model = model_part.replace('qwen_3_235b_a22b_thinking_2507', 'qwen-3-235b-a22b-thinking-2507')
else:
model = model_part.replace('qwen_3_235b_a22b_thinking', 'qwen-3-235b-a22b-thinking-2507')
elif 'qwen_3_coder_480b' in model_part:
model = model_part.replace('qwen_3_coder_480b', 'qwen-3-coder-480b')
else:
model = model_part.replace('_', '-')
# OpenAI Models
if provider == 'openai':
api_key = os.getenv('OPENAI_API_KEY')
return ChatOpenAI(model=model, api_key=api_key)
# Azure OpenAI Models
elif provider == 'azure':
api_key = os.getenv('AZURE_OPENAI_KEY') or os.getenv('AZURE_OPENAI_API_KEY')
azure_endpoint = os.getenv('AZURE_OPENAI_ENDPOINT')
return ChatAzureOpenAI(model=model, api_key=api_key, azure_endpoint=azure_endpoint)
# Google Models
elif provider == 'google':
api_key = os.getenv('GOOGLE_API_KEY')
return ChatGoogle(model=model, api_key=api_key)
# OCI Models
elif provider == 'oci':
# OCI requires more complex configuration that can't be easily inferred from env vars
# Users should use ChatOCIRaw directly with proper configuration
raise ValueError('OCI models require manual configuration. Use ChatOCIRaw directly with your OCI credentials.')
# Cerebras Models
elif provider == 'cerebras':
api_key = os.getenv('CEREBRAS_API_KEY')
return ChatCerebras(model=model, api_key=api_key)
# Browser Use Models
elif provider == 'bu':
# Handle bu_latest -> bu-latest conversion (need to prepend 'bu-' back)
model = f'bu-{model_part.replace("_", "-")}'
api_key = os.getenv('BROWSER_USE_API_KEY')
return ChatBrowserUse(model=model, api_key=api_key)
else:
available_providers = ['openai', 'azure', 'google', 'oci', 'cerebras', 'bu']
raise ValueError(f"Unknown provider: '{provider}'. Available providers: {', '.join(available_providers)}")
# Pre-configured model instances (lazy loaded via __getattr__)
def __getattr__(name: str) -> 'BaseChatModel':
"""Create model instances on demand with API keys from environment."""
# Handle chat classes first
if name == 'ChatOpenAI':
return ChatOpenAI # type: ignore
elif name == 'ChatAzureOpenAI':
return ChatAzureOpenAI # type: ignore
elif name == 'ChatGoogle':
return ChatGoogle # type: ignore
elif name == 'ChatOCIRaw':
if not OCI_AVAILABLE:
raise ImportError('OCI integration not available. Install with: pip install "browser-use[oci]"')
return ChatOCIRaw # type: ignore
elif name == 'ChatCerebras':
return ChatCerebras # type: ignore
elif name == 'ChatBrowserUse':
return ChatBrowserUse # type: ignore
# Handle model instances - these are the main use case
try:
return get_llm_by_name(name)
except ValueError:
raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
# Export all classes and preconfigured instances, conditionally including ChatOCIRaw
__all__ = [
'ChatOpenAI',
'ChatAzureOpenAI',
'ChatGoogle',
'ChatCerebras',
'ChatBrowserUse',
]
if OCI_AVAILABLE:
__all__.append('ChatOCIRaw')
__all__ += [
'get_llm_by_name',
# OpenAI instances - created on demand
'openai_gpt_4o',
'openai_gpt_4o_mini',
'openai_gpt_4_1_mini',
'openai_o1',
'openai_o1_mini',
'openai_o1_pro',
'openai_o3',
'openai_o3_mini',
'openai_o3_pro',
'openai_o4_mini',
'openai_gpt_5',
'openai_gpt_5_mini',
'openai_gpt_5_nano',
# Azure instances - created on demand
'azure_gpt_4o',
'azure_gpt_4o_mini',
'azure_gpt_4_1_mini',
'azure_o1',
'azure_o1_mini',
'azure_o1_pro',
'azure_o3',
'azure_o3_mini',
'azure_o3_pro',
'azure_gpt_5',
'azure_gpt_5_mini',
# Google instances - created on demand
'google_gemini_2_0_flash',
'google_gemini_2_0_pro',
'google_gemini_2_5_pro',
'google_gemini_2_5_flash',
'google_gemini_2_5_flash_lite',
# Cerebras instances - created on demand
'cerebras_llama3_1_8b',
'cerebras_llama3_3_70b',
'cerebras_gpt_oss_120b',
'cerebras_llama_4_scout_17b_16e_instruct',
'cerebras_llama_4_maverick_17b_128e_instruct',
'cerebras_qwen_3_32b',
'cerebras_qwen_3_235b_a22b_instruct_2507',
'cerebras_qwen_3_235b_a22b_thinking_2507',
'cerebras_qwen_3_coder_480b',
# Browser Use instances - created on demand
'bu_latest',
'bu_1_0',
]
# NOTE: OCI backend is optional. The try/except ImportError and conditional __all__ are required
# so this module can be imported without browser-use[oci] installed.