mirror of
https://github.com/browser-use/browser-use
synced 2026-05-06 17:52:15 +02:00
80 lines
2.6 KiB
Python
80 lines
2.6 KiB
Python
"""
|
|
Example of using Cerebras with browser-use.
|
|
|
|
To use this example:
|
|
1. Set your CEREBRAS_API_KEY environment variable
|
|
2. Run this script
|
|
|
|
Cerebras integration is working great for:
|
|
- Direct text generation
|
|
- Simple tasks without complex structured output
|
|
- Fast inference for web automation
|
|
|
|
Available Cerebras models (9 total):
|
|
Small/Fast models (8B-32B):
|
|
- cerebras_llama3_1_8b (8B parameters, fast)
|
|
- cerebras_llama_4_scout_17b_16e_instruct (17B, instruction-tuned)
|
|
- cerebras_llama_4_maverick_17b_128e_instruct (17B, extended context)
|
|
- cerebras_qwen_3_32b (32B parameters)
|
|
|
|
Large/Capable models (70B-480B):
|
|
- cerebras_llama3_3_70b (70B parameters, latest version)
|
|
- cerebras_gpt_oss_120b (120B parameters, OpenAI's model)
|
|
- cerebras_qwen_3_235b_a22b_instruct_2507 (235B, instruction-tuned)
|
|
- cerebras_qwen_3_235b_a22b_thinking_2507 (235B, complex reasoning)
|
|
- cerebras_qwen_3_coder_480b (480B, code generation)
|
|
|
|
Note: Cerebras has some limitations with complex structured output due to JSON schema compatibility.
|
|
"""
|
|
|
|
import asyncio
|
|
import os
|
|
|
|
from browser_use import Agent
|
|
|
|
|
|
async def main():
|
|
# Set your API key (recommended to use environment variable)
|
|
api_key = os.getenv('CEREBRAS_API_KEY')
|
|
if not api_key:
|
|
raise ValueError('Please set CEREBRAS_API_KEY environment variable')
|
|
|
|
# Option 1: Use the pre-configured model instance (recommended)
|
|
from browser_use import llm
|
|
|
|
# Choose your model:
|
|
# Small/Fast models:
|
|
# model = llm.cerebras_llama3_1_8b # 8B, fast
|
|
# model = llm.cerebras_llama_4_scout_17b_16e_instruct # 17B, instruction-tuned
|
|
# model = llm.cerebras_llama_4_maverick_17b_128e_instruct # 17B, extended context
|
|
# model = llm.cerebras_qwen_3_32b # 32B
|
|
|
|
# Large/Capable models:
|
|
# model = llm.cerebras_llama3_3_70b # 70B, latest
|
|
# model = llm.cerebras_gpt_oss_120b # 120B, OpenAI's model
|
|
# model = llm.cerebras_qwen_3_235b_a22b_instruct_2507 # 235B, instruction-tuned
|
|
model = llm.cerebras_qwen_3_235b_a22b_thinking_2507 # 235B, complex reasoning
|
|
# model = llm.cerebras_qwen_3_coder_480b # 480B, code generation
|
|
|
|
# Option 2: Create the model instance directly
|
|
# model = ChatCerebras(
|
|
# model="qwen-3-coder-480b", # or any other model ID
|
|
# api_key=os.getenv("CEREBRAS_API_KEY"),
|
|
# temperature=0.2,
|
|
# max_tokens=4096,
|
|
# )
|
|
|
|
# Create and run the agent with a simple task
|
|
task = 'Explain the concept of quantum entanglement in simple terms.'
|
|
agent = Agent(task=task, llm=model)
|
|
|
|
print(f'Running task with Cerebras {model.name} (ID: {model.model}): {task}')
|
|
history = await agent.run(max_steps=3)
|
|
result = history.final_result()
|
|
|
|
print(f'Result: {result}')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
asyncio.run(main())
|