mirror of
https://github.com/browser-use/browser-use
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157 lines
2.9 KiB
Plaintext
157 lines
2.9 KiB
Plaintext
---
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title: "Supported Models"
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description: "Guide to using different chat models with Browser Use"
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icon: "robot"
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---
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## Overview
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Here's how to configure the models.
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### Migration from Langchain
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We have recently switched from Langchain to our own implementation of the models. To migrate the previous code, just replace `from langchain_openai import ChatOpenAI` with `from browser_use.llm import ChatOpenAI` etc. The methods should be compatible(ish).
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## Model Recommendations
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We recommend using GPT-4.1 for the best performance (best accuracy ~$0.01 per step). The best price to performance can be achieved using `gemini-2.0-flash-exp` (currently also the most popular model, costs ~$0.001 per step).
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## Supported Models
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Our library natively supports the following models:
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- OpenAI
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- Anthropic
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- Azure OpenAI
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- Gemini
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- Groq
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We also support all other models that can be called via OpenAI compatible API (deepseek, novita, x, qwen). Please open a PR if you want to add a model.
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We have natively switched to structured output when possible,
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### OpenAI
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OpenAI's GPT-4.1 models are recommended for best performance.
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```python
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from browser_use.llm import ChatOpenAI
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from browser_use import Agent
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# Initialize the model
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llm = ChatOpenAI(
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model="gpt-4.1",
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)
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# Create agent with the model
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agent = Agent(
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task="Your task here",
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llm=llm
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)
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```
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Required environment variables:
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```bash .env
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OPENAI_API_KEY=
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```
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### Anthropic
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```python
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from browser_use.llm import ChatAnthropic
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from browser_use import Agent
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# Initialize the model
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llm = ChatAnthropic(
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model_name="claude-3-5-sonnet-20240620",
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)
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# Create agent with the model
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agent = Agent(
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task="Your task here",
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llm=llm
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)
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```
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And add the variable:
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```bash .env
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ANTHROPIC_API_KEY=
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```
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### Azure OpenAI
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```python
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from browser_use.llm import ChatAzureOpenAI
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from browser_use import Agent
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from pydantic import SecretStr
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import os
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# Initialize the model
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llm = ChatAzureOpenAI(
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model="gpt-4.1",
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)
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# Create agent with the model
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agent = Agent(
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task="Your task here",
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llm=llm
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)
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```
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Required environment variables:
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```bash .env
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AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com/
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AZURE_OPENAI_API_KEY=
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```
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### Gemini
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> [!IMPORTANT] `GEMINI_API_KEY` was the old environment var name, it should be called `GOOGLE_API_KEY` as of 2025-05.
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```python
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from browser_use.llm import ChatGoogle
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from browser_use import Agent
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from dotenv import load_dotenv
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# Read GOOGLE_API_KEY into env
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load_dotenv()
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# Initialize the model
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llm = ChatGoogle(model='gemini-2.0-flash-exp')
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# Create agent with the model
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agent = Agent(
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task="Your task here",
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llm=llm
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)
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```
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Required environment variables:
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```bash .env
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GOOGLE_API_KEY=
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```
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## Groq
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```python
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from browser_use.llm import ChatGroq
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from browser_use import Agent
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llm = ChatGroq(model="meta-llama/llama-4-maverick-17b-128e-instruct")
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agent = Agent(
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task="Your task here",
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llm=llm
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)
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```
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Required environment variables:
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```bash .env
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GROQ_API_KEY=
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```
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