mirror of
https://github.com/browser-use/browser-use
synced 2026-05-06 17:52:15 +02:00
272 lines
8.6 KiB
Python
272 lines
8.6 KiB
Python
"""
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Convenient access to LLM models.
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Usage:
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from browser_use import llm
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# Simple model access
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model = llm.azure_gpt_4_1_mini
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model = llm.openai_gpt_4o
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model = llm.google_gemini_2_5_pro
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model = llm.bu_latest
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"""
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import os
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from typing import TYPE_CHECKING
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from browser_use.llm.azure.chat import ChatAzureOpenAI
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from browser_use.llm.browser_use.chat import ChatBrowserUse
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from browser_use.llm.cerebras.chat import ChatCerebras
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from browser_use.llm.google.chat import ChatGoogle
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from browser_use.llm.openai.chat import ChatOpenAI
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# Optional OCI import
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try:
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from browser_use.llm.oci_raw.chat import ChatOCIRaw
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OCI_AVAILABLE = True
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except ImportError:
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ChatOCIRaw = None
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OCI_AVAILABLE = False
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if TYPE_CHECKING:
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from browser_use.llm.base import BaseChatModel
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# Type stubs for IDE autocomplete
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openai_gpt_4o: 'BaseChatModel'
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openai_gpt_4o_mini: 'BaseChatModel'
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openai_gpt_4_1_mini: 'BaseChatModel'
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openai_o1: 'BaseChatModel'
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openai_o1_mini: 'BaseChatModel'
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openai_o1_pro: 'BaseChatModel'
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openai_o3: 'BaseChatModel'
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openai_o3_mini: 'BaseChatModel'
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openai_o3_pro: 'BaseChatModel'
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openai_o4_mini: 'BaseChatModel'
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openai_gpt_5: 'BaseChatModel'
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openai_gpt_5_mini: 'BaseChatModel'
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openai_gpt_5_nano: 'BaseChatModel'
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azure_gpt_4o: 'BaseChatModel'
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azure_gpt_4o_mini: 'BaseChatModel'
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azure_gpt_4_1_mini: 'BaseChatModel'
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azure_o1: 'BaseChatModel'
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azure_o1_mini: 'BaseChatModel'
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azure_o1_pro: 'BaseChatModel'
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azure_o3: 'BaseChatModel'
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azure_o3_mini: 'BaseChatModel'
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azure_o3_pro: 'BaseChatModel'
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azure_gpt_5: 'BaseChatModel'
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azure_gpt_5_mini: 'BaseChatModel'
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google_gemini_2_0_flash: 'BaseChatModel'
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google_gemini_2_0_pro: 'BaseChatModel'
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google_gemini_2_5_pro: 'BaseChatModel'
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google_gemini_2_5_flash: 'BaseChatModel'
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google_gemini_2_5_flash_lite: 'BaseChatModel'
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cerebras_llama3_1_8b: 'BaseChatModel'
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cerebras_llama3_3_70b: 'BaseChatModel'
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cerebras_gpt_oss_120b: 'BaseChatModel'
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cerebras_llama_4_scout_17b_16e_instruct: 'BaseChatModel'
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cerebras_llama_4_maverick_17b_128e_instruct: 'BaseChatModel'
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cerebras_qwen_3_32b: 'BaseChatModel'
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cerebras_qwen_3_235b_a22b_instruct_2507: 'BaseChatModel'
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cerebras_qwen_3_235b_a22b_thinking_2507: 'BaseChatModel'
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cerebras_qwen_3_coder_480b: 'BaseChatModel'
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bu_latest: 'BaseChatModel'
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bu_1_0: 'BaseChatModel'
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def get_llm_by_name(model_name: str):
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"""
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Factory function to create LLM instances from string names with API keys from environment.
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Args:
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model_name: String name like 'azure_gpt_4_1_mini', 'openai_gpt_4o', etc.
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Returns:
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LLM instance with API keys from environment variables
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Raises:
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ValueError: If model_name is not recognized
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"""
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if not model_name:
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raise ValueError('Model name cannot be empty')
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# Parse model name
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parts = model_name.split('_', 1)
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if len(parts) < 2:
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raise ValueError(f"Invalid model name format: '{model_name}'. Expected format: 'provider_model_name'")
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provider = parts[0]
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model_part = parts[1]
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# Convert underscores back to dots/dashes for actual model names
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if 'gpt_4_1_mini' in model_part:
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model = model_part.replace('gpt_4_1_mini', 'gpt-4.1-mini')
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elif 'gpt_4o_mini' in model_part:
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model = model_part.replace('gpt_4o_mini', 'gpt-4o-mini')
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elif 'gpt_4o' in model_part:
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model = model_part.replace('gpt_4o', 'gpt-4o')
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elif 'gemini_2_0' in model_part:
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model = model_part.replace('gemini_2_0', 'gemini-2.0').replace('_', '-')
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elif 'gemini_2_5' in model_part:
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model = model_part.replace('gemini_2_5', 'gemini-2.5').replace('_', '-')
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elif 'llama3_1' in model_part:
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model = model_part.replace('llama3_1', 'llama3.1').replace('_', '-')
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elif 'llama3_3' in model_part:
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model = model_part.replace('llama3_3', 'llama-3.3').replace('_', '-')
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elif 'llama_4_scout' in model_part:
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model = model_part.replace('llama_4_scout', 'llama-4-scout').replace('_', '-')
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elif 'llama_4_maverick' in model_part:
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model = model_part.replace('llama_4_maverick', 'llama-4-maverick').replace('_', '-')
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elif 'gpt_oss_120b' in model_part:
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model = model_part.replace('gpt_oss_120b', 'gpt-oss-120b')
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elif 'qwen_3_32b' in model_part:
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model = model_part.replace('qwen_3_32b', 'qwen-3-32b')
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elif 'qwen_3_235b_a22b_instruct' in model_part:
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if model_part.endswith('_2507'):
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model = model_part.replace('qwen_3_235b_a22b_instruct_2507', 'qwen-3-235b-a22b-instruct-2507')
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else:
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model = model_part.replace('qwen_3_235b_a22b_instruct', 'qwen-3-235b-a22b-instruct-2507')
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elif 'qwen_3_235b_a22b_thinking' in model_part:
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if model_part.endswith('_2507'):
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model = model_part.replace('qwen_3_235b_a22b_thinking_2507', 'qwen-3-235b-a22b-thinking-2507')
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else:
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model = model_part.replace('qwen_3_235b_a22b_thinking', 'qwen-3-235b-a22b-thinking-2507')
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elif 'qwen_3_coder_480b' in model_part:
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model = model_part.replace('qwen_3_coder_480b', 'qwen-3-coder-480b')
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else:
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model = model_part.replace('_', '-')
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# OpenAI Models
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if provider == 'openai':
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api_key = os.getenv('OPENAI_API_KEY')
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return ChatOpenAI(model=model, api_key=api_key)
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# Azure OpenAI Models
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elif provider == 'azure':
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api_key = os.getenv('AZURE_OPENAI_KEY') or os.getenv('AZURE_OPENAI_API_KEY')
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azure_endpoint = os.getenv('AZURE_OPENAI_ENDPOINT')
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return ChatAzureOpenAI(model=model, api_key=api_key, azure_endpoint=azure_endpoint)
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# Google Models
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elif provider == 'google':
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api_key = os.getenv('GOOGLE_API_KEY')
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return ChatGoogle(model=model, api_key=api_key)
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# OCI Models
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elif provider == 'oci':
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# OCI requires more complex configuration that can't be easily inferred from env vars
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# Users should use ChatOCIRaw directly with proper configuration
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raise ValueError('OCI models require manual configuration. Use ChatOCIRaw directly with your OCI credentials.')
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# Cerebras Models
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elif provider == 'cerebras':
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api_key = os.getenv('CEREBRAS_API_KEY')
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return ChatCerebras(model=model, api_key=api_key)
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# Browser Use Models
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elif provider == 'bu':
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# Handle bu_latest -> bu-latest conversion (need to prepend 'bu-' back)
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model = f'bu-{model_part.replace("_", "-")}'
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api_key = os.getenv('BROWSER_USE_API_KEY')
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return ChatBrowserUse(model=model, api_key=api_key)
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else:
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available_providers = ['openai', 'azure', 'google', 'oci', 'cerebras', 'bu']
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raise ValueError(f"Unknown provider: '{provider}'. Available providers: {', '.join(available_providers)}")
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# Pre-configured model instances (lazy loaded via __getattr__)
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def __getattr__(name: str) -> 'BaseChatModel':
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"""Create model instances on demand with API keys from environment."""
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# Handle chat classes first
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if name == 'ChatOpenAI':
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return ChatOpenAI # type: ignore
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elif name == 'ChatAzureOpenAI':
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return ChatAzureOpenAI # type: ignore
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elif name == 'ChatGoogle':
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return ChatGoogle # type: ignore
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elif name == 'ChatOCIRaw':
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if not OCI_AVAILABLE:
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raise ImportError('OCI integration not available. Install with: pip install "browser-use[oci]"')
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return ChatOCIRaw # type: ignore
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elif name == 'ChatCerebras':
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return ChatCerebras # type: ignore
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elif name == 'ChatBrowserUse':
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return ChatBrowserUse # type: ignore
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# Handle model instances - these are the main use case
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try:
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return get_llm_by_name(name)
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except ValueError:
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raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
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# Export all classes and preconfigured instances, conditionally including ChatOCIRaw
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__all__ = [
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'ChatOpenAI',
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'ChatAzureOpenAI',
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'ChatGoogle',
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'ChatCerebras',
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'ChatBrowserUse',
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]
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if OCI_AVAILABLE:
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__all__.append('ChatOCIRaw')
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__all__ += [
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'get_llm_by_name',
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# OpenAI instances - created on demand
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'openai_gpt_4o',
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'openai_gpt_4o_mini',
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'openai_gpt_4_1_mini',
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'openai_o1',
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'openai_o1_mini',
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'openai_o1_pro',
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'openai_o3',
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'openai_o3_mini',
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'openai_o3_pro',
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'openai_o4_mini',
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'openai_gpt_5',
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'openai_gpt_5_mini',
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'openai_gpt_5_nano',
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# Azure instances - created on demand
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'azure_gpt_4o',
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'azure_gpt_4o_mini',
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'azure_gpt_4_1_mini',
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'azure_o1',
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'azure_o1_mini',
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'azure_o1_pro',
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'azure_o3',
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'azure_o3_mini',
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'azure_o3_pro',
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'azure_gpt_5',
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'azure_gpt_5_mini',
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# Google instances - created on demand
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'google_gemini_2_0_flash',
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'google_gemini_2_0_pro',
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'google_gemini_2_5_pro',
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'google_gemini_2_5_flash',
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'google_gemini_2_5_flash_lite',
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# Cerebras instances - created on demand
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'cerebras_llama3_1_8b',
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'cerebras_llama3_3_70b',
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'cerebras_gpt_oss_120b',
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'cerebras_llama_4_scout_17b_16e_instruct',
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'cerebras_llama_4_maverick_17b_128e_instruct',
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'cerebras_qwen_3_32b',
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'cerebras_qwen_3_235b_a22b_instruct_2507',
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'cerebras_qwen_3_235b_a22b_thinking_2507',
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'cerebras_qwen_3_coder_480b',
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# Browser Use instances - created on demand
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'bu_latest',
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'bu_1_0',
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]
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# NOTE: OCI backend is optional. The try/except ImportError and conditional __all__ are required
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# so this module can be imported without browser-use[oci] installed.
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