Azure OpenAI Service provides REST API access to OpenAI's powerful language models including the GPT-3, Codex and Embeddings model series. These models can be easily adapted to your specific task including but not limited to content generation, summarization, semantic search, and natural language to code translation. Users can access the service through REST APIs, Python SDK, or our web-based interface in the Azure OpenAI Studio.
Access is currently limited as we navigate high demand, upcoming product improvements, and Microsoft’s commitment to responsible AI. For now, we're working with customers with an existing partnership with Microsoft, lower risk use cases, and those committed to incorporating mitigations. In addition to applying for initial access, all solutions using Azure OpenAI are required to go through a use case review before they can be released for production use.
More specific information is included in the application form. We appreciate your patience as we work to responsibly enable broader access to Azure OpenAI.
Apply here for initial access or for a production review: Apply now
All solutions using Azure OpenAI are also required to go through a use case review before they can be released for production use, and are evaluated on a case-by-case basis. In general, the more sensitive the scenario the more important risk mitigation measures will be for approval.
Refer to the following documents for a better understanding of Azure OpenAI concepts and the related terminology:
At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes requiring applicants to show well-defined use cases, incorporating Microsoft’s principles for responsible AI use, building content filters to support customers, and providing responsible AI implementation guidance to onboarded customers.
More details on the RAI guidelines for the Azure OpenAI service can be found here.
This repository contains samples demonstrating how to use GPT and ChatGPT via Python SDK or REST API.
Install all Python modules and packages listed in the requirements.txt file using the below command.
pip install -r requirements.txtIn order to use the Open AI library or REST API with Microsoft Azure endpoints, you need to set COMPLETIONS_MODEL, EMBEDDINGS_MODEL, OPENAI_API_BASE & OPENAI_API_VERSION in config.json file.
{
"COMPLETIONS_MODEL":"<Completions Model Name>",
"EMBEDDINGS_MODEL":"<Embeddings Model Name>",
"OPENAI_API_BASE":"https://<Your Azure Resource Name>.openai.azure.com",
"OPENAI_API_VERSION":"<OpenAI API Version>"
}- Add "OPENAI_API_KEY" as variable name and <Your API Key Value> as variable value in the environment variables.
One can get the OPENAI_API_KEY value from the Azure Portal. Go to https://portal.azure.com, find your resource and then under "Resource Management" -> "Keys and Endpoints" look for one of the "Keys" values.
**STEPS** -
WINDOWS Users:
setx OPENAI_API_KEY "REPLACE_WITH_YOUR_KEY_VALUE_HERE"
MACOS/LINUX Users:
export OPENAI_API_KEY="REPLACE_WITH_YOUR_KEY_VALUE_HERE"
- For Completions scenario, one can start with using your model name ("COMPLETIONS_MODEL" in config.json file) as "text_davinci_003".
And for Embeddings scenario, one can use "text-embedding-ada-002" as model name ("EMBEDDINGS_MODEL"in config.json file). - To find your "OPENAI_API_BASE" go to https://portal.azure.com, find your resource and then under "Resource Management" -> "Keys and Endpoints" look for the "Endpoint" value.
- Current OpenAI api version is "2022-12-01".
Learn more about Azure OpenAI Service REST API here.
Python 3.8+
Jupyter Notebook 6.5.2
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