Add your API key to the newly created .env file Run the app $ npm run devYou should now be able to access the app at http://localhost:3000! For the full context behind this example app, check out the tutorial.About Node.js example app from the OpenAI API quickstart tutorial beta....
This repository hosts multiple quickstart apps for different OpenAI API endpoints (chat, assistants, etc). Check out the examples folder to try out different examples and get started using the OpenAI API.Basic requestTo send your first API request with the OpenAI Python SDK, make sure you have...
Learn how to use Azure OpenAI's powerful models including the GPT-4o, GPT-4o mini, GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, DALL-E 3 and Embeddings model series
For this tutorial we will be using a NIM model, no additional steps are needed, and you may leave the OpenAI API Key unchanged for this quick start guide. Currently we are supporting installation of turn servers (coturn/twilio) on same machine as the application instance, so we only need ...
In this quickstart, learn how to use grounding data from Azure AI Search with a chat model on Azure OpenAI.
it’ll call an Inference Server API endpoint, hosted by the Model Runner through Docker Desktop, and provide an OpenAI compatible API. The Inference Server will usellama.cppas the Inference Engine, running as a native host process, load the requested model on demand, and then perform the infe...
11 # API key for OpenAI. 12 OPENAI_API_KEY="<openai_api_key>"</openai_api_key> 13 14 # Name of the index to use for vector storage 15 MONGODB_VECTOR_INDEX='vector_index' 16 17 # Name of the collection in MongoDB where embedding data is stored 18 MONGODB_VECTOR_COLL_LANGCHAI...
CREATEML_ENGINE openai_engineFROMopenaiUSINGopenai_api_key='your-openai-api-key'; Use theCREATE MODELstatement to create, train, and deploy an AI model based on the AI engine created in step 2. Copy CREATEMODEL question_answering_modelPREDICT answerUSINGengine='openai_engine',prompt_template='...
Learn how to use Azure OpenAI's powerful models including o-series, GPT-4o, GPT-4o mini, GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, GPT-image-1, and Embeddings model series
$ cd openai-quickstart-python Create a new virtual environment: $ python -m venv venv $ . venv/bin/activate Install the requirements: $ pip install -r requirements.txt Make a copy of the example environment variables file: $ cp .env.example .env Add your API key to the newly created ....