For Windows people getting used to a Mac, running the Window Mode full screen lets them go home to what they’re used to for a while. The three modes work well and give users some options how they want apps to behave. For the rare time when I want to use Windows, I switch to Window Mode and run it full-screen on Mountain Lion. I prefer to use Coherence Mode since I’m usually only running one or maybe two Windows apps at a time. Modality Mode – runs in scalable windows allowing the user to monitor whats going on in a window while working in the Mac environment.Window Mode – runs the operating system in a single window and works best for those who stay in the OS for long periods of time before switching back to Mac.Coherence Mode – runs each Windows app in a single Window as if they’re Mac apps and only works with Windows.Coherence Mode puts a Windows Start Menu button on the Mac Men Bar COHERE_API_URL = " # Place before client initilization cohere. ![]() You can configure a different base url with: CO_API_URL = " python3 foo.py You can run tests locally using: python -m pytest In addition, to ensure your code is formatted correctly, install pre-commit hooks using: pre-commit install Poetry install # install and update dependencies in your environment, the first time To set up a development environment, first ensure you have poetry 1.7+ installed and run: poetry shell # any time you want to run code or tests Please see the documentation's page on errors for more information about what the errors mean. Unsuccessful API calls from the SDK will raise an exception. Printing the Cohere response object itself will display an organized view of the instance variables. ![]() The names of these instance variables and a detailed breakdown of the response body can be found in the SDK Docs and Cohere Docs. The responses can be found as instance variables of the object (e.g. Learn more about the available models here( ) ResponsesĪll of the endpoint functions will return a Cohere object corresponding to the endpoint (e.g. The default model is great to get you started, but in production environments we recommend that you specify the model size yourself via the model parameter. When you call Cohere's APIs we decide on a good default model for your use-case behind the scenes. Endpointsįor a full breakdown of endpoints and arguments, please consult the SDK Docs and Cohere Docs. Look at the Changelog to see which SDK version to download. To use the SDK with an older API version, you need to download a version of the SDK tied to the API version you want. VersioningĮach SDK release is only compatible with the latest version of the Cohere API at the time of release. There is also an asyncio compatible client called cohere.AsyncClient with an equivalent interface. chat ( message = 'Howdy! □', model = 'command' ) # print the predicted text print ( f 'Chatbot: ' ) Client ( 'YOUR_API_KEY' ) # generate a prediction for a prompt prediction = co. ![]() import cohere # initialize the Cohere Client with an API Key co = cohere. This is a basic example of the creating the client and using the generate endpoint. API keys can be created through the platform. To use this library, you must have an API key and specify it as a string when creating the cohere.Client object. The package can be installed with pip: pip install -upgrade cohere
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |