Config Model and Provider#

Midscene uses the OpenAI SDK to call AI services. Using this SDK limits the input and output schema of AI services, but it doesn't mean you can only use OpenAI's services. You can use any model service that supports the same interface (most platforms or tools support this).

In this article, we will show you how to config AI service provider and how to choose a different model. You may read Choose a model first to learn more about how to choose a model.

Configs#

These are the most common configs, in which OPENAI_API_KEY is required.

Config to use Qwen 2.5 VL model:

Config to use UI-TARS model:

For more information about the models, see Choose a model.

Some advanced configs are also supported. Usually you don't need to use them.

Two ways to config environment variables#

Pick one of the following ways to config environment variables.

1. Set environment variables in your system#

# replace by your own
export OPENAI_API_KEY="sk-abcdefghijklmnopqrstuvwxyz"

2. Set environment variables using dotenv#

This is what we used in our demo project.

Dotenv is a zero-dependency module that loads environment variables from a .env file into process.env.

# install dotenv
npm install dotenv --save

Create a .env file in your project root directory, and add the following content. There is no need to add export before each line.

Import the dotenv module in your script. It will automatically read the environment variables from the .env file.

import 'dotenv/config';

Using Azure OpenAI Service#

There are some extra configs when using Azure OpenAI Service.

Use ADT token provider#

This mode cannot be used in Chrome extension.

# this is always true when using Azure OpenAI Service
export MIDSCENE_USE_AZURE_OPENAI=1

export MIDSCENE_AZURE_OPENAI_SCOPE="https://cognitiveservices.azure.com/.default"
export AZURE_OPENAI_ENDPOINT="..."
export AZURE_OPENAI_API_VERSION="2024-05-01-preview"
export AZURE_OPENAI_DEPLOYMENT="gpt-4o"

Use keyless authentication#

export MIDSCENE_USE_AZURE_OPENAI=1
export AZURE_OPENAI_ENDPOINT="..."
export AZURE_OPENAI_KEY="..."
export AZURE_OPENAI_API_VERSION="2024-05-01-preview"
export AZURE_OPENAI_DEPLOYMENT="gpt-4o"

Example: Using gpt-4o from OpenAI#

Configure the environment variables:

export OPENAI_API_KEY="sk-..."
export OPENAI_BASE_URL="https://endpoint.some_other_provider.com/v1" # config this if you want to use a different endpoint
export MIDSCENE_MODEL_NAME="gpt-4o-2024-11-20" # optional, the default is "gpt-4o"

Example: Using qwen-vl-max-latest from Aliyun#

Configure the environment variables:

export OPENAI_API_KEY="sk-..."
export OPENAI_BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1"
export MIDSCENE_MODEL_NAME="qwen-vl-max-latest"
export MIDSCENE_USE_QWEN_VL=1

Example: Using ui-tars-72b-sft hosted by yourself#

Configure the environment variables:

export OPENAI_API_KEY="sk-..."
export OPENAI_BASE_URL="http://localhost:1234/v1"
export MIDSCENE_MODEL_NAME="ui-tars-72b-sft"
export MIDSCENE_USE_VLM_UI_TARS=1

Example: Config claude-3-opus-20240229 from Anthropic#

When configuring MIDSCENE_USE_ANTHROPIC_SDK=1, Midscene will use Anthropic SDK (@anthropic-ai/sdk) to call the model.

Configure the environment variables:

export MIDSCENE_USE_ANTHROPIC_SDK=1
export ANTHROPIC_API_KEY="....."
export MIDSCENE_MODEL_NAME="claude-3-opus-20240229"

Example: Using doubao-vision-pro-32k from Volcengine#

Create a inference point first: https://console.volcengine.com/ark/region:ark+cn-beijing/endpoint

In the inference point interface, find an ID like ep-202... as the model name.

Configure the environment variables:

export OPENAI_BASE_URL="https://ark.cn-beijing.volces.com/api/v3"
export OPENAI_API_KEY="..."
export MIDSCENE_MODEL_NAME="ep-202....."

Example: config request headers (like for openrouter)#

export OPENAI_BASE_URL="https://openrouter.ai/api/v1"
export OPENAI_API_KEY="..."
export MIDSCENE_MODEL_NAME="..."
export MIDSCENE_OPENAI_INIT_CONFIG_JSON='{"defaultHeaders":{"HTTP-Referer":"...","X-Title":"..."}}'

Example: Using gemini-1.5-pro from Google#

Configure the environment variables:

export OPENAI_BASE_URL="https://generativelanguage.googleapis.com/v1beta/openai"
export OPENAI_API_KEY="....."
export MIDSCENE_MODEL_NAME="gemini-1.5-pro"

Troubleshooting LLM Service Connectivity Issues#

If you want to troubleshoot connectivity issues, you can use the 'connectivity-test' folder in our example project: https://github.com/web-infra-dev/midscene-example/tree/main/connectivity-test

Put your .env file in the connectivity-test folder, and run the test with npm i && npm run test.