OpenAI API Endpoint
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An OpenAI API Endpoint is an API endpoint within OpenAI API that enables developers to access specific AI models or services.
- Context:
- It can provide developers with access to OpenAI Models.
- It can require authentication via an OpenAI API Key.
- It can process requests and return responses in JSON Format.
- It can be monitored through the OpenAI API Status Page
https://status.openai.com/
. - It can include usage tracking and monitoring to manage costs, access levels, and API quotas, which are part of OpenAI's tiered pricing system.
- It can be accessed using OpenAI Python Library or other OpenAI API SDKs.
- It can provide error handling responses, such as rate-limit errors, authentication failures, or resource exhaustion, giving developers insight into how their applications interact with the OpenAI system.
- It can expose additional API capabilities, such as function calling, allowing models to execute structured commands based on user inputs, automating more complex tasks.
- ...
- Example(s):
- OpenAI.ChatCompletion: An endpoint designed to facilitate conversation-based tasks by processing input message history and generating responses based on context, commonly used in AI chatbots and customer service agents.
- OpenAI.Embeddings: An endpoint that transforms text into numerical vectors, enabling applications like semantic search, information retrieval, and document classification.
- OpenAI Fine-Tuning API: This endpoint allows developers to fine-tune existing models like GPT-3.5 and GPT-4 using custom datasets, creating more specialized models for domain-specific tasks.
- OpenAI.Audio.Transcriptions: This API endpoint is part of the Whisper Model family and is used for converting speech into text, enabling applications like automated transcription services and voice-controlled assistants.
- ...
- Counter-Example(s):
- Azure OpenAI Service REST API: A service offered by Microsoft, leveraging OpenAI models, but integrated into the Azure Cloud Platform, which differs from OpenAI's native API in terms of pricing, authentication, and platform integration.
- HuggingFace API: An alternative API that provides access to a wide variety of machine learning models, including many open-source models, offering a distinct ecosystem with different authentication methods and access rules.
- Self-hosted AI Models: In contrast to OpenAI's cloud-based API, these involve manually hosting and managing AI models, which offers greater control but lacks the scalability and ease of use provided by the OpenAI API.
- ...
- See: OpenAI Python Library, GPT-4, OpenAI Models, HuggingFace Transformers
References
2024
- https://platform.openai.com/docs/models
- NOTES:
- It can include models like:
- GPT-4o: OpenAI’s flagship model designed for complex, multi-step tasks. It supports text and image inputs with a context length of 128,000 tokens, generating text twice as fast as GPT-4 Turbo and at a lower cost per token.
- GPT-4o Mini: A smaller, more affordable variant of GPT-4o, designed for lightweight, fast tasks. It offers similar multimodal capabilities but is optimized for speed and lower cost, with a context window of 128,000 tokens.
- o1-Preview and o1-Mini: A new series of reasoning models using reinforcement learning to solve complex problems. The o1-Preview model handles harder reasoning tasks, while o1-Mini is optimized for faster, cheaper performance in math, coding, and science tasks.
- Continuous Model Upgrades: OpenAI continuously updates model versions, like GPT-4o-latest, allowing developers to use the latest versions in production. Developers can also contribute evaluations via OpenAI Evals to help improve models for different use cases.
- Model Context Windows: OpenAI API models, such as GPT-4o, support large context windows of up to 128,000 tokens, allowing for long and complex inputs and outputs in a single API request.
- Model Pricing Tiers: OpenAI provides a variety of models with different pricing points, from high-performance models like GPT-4o to more affordable options like GPT-4o Mini. Each model is designed to cater to different computational needs and budgets.
- DALL·E: OpenAI’s image generation model, capable of creating and editing images based on natural language prompts. The latest iteration, DALL·E 3, offers improved resolution and image fidelity compared to previous versions.
- Text-to-Speech (TTS) Models: OpenAI’s TTS models, including tts-1 and tts-1-hd, convert text into natural-sounding spoken audio. They can be used for real-time speech synthesis applications.
- Whisper Model: A general-purpose speech recognition model, Whisper is available through the OpenAI API and excels at multilingual speech recognition, translation, and language identification. It is optimized for faster inference when used via the API.
- Embeddings API: OpenAI’s Embeddings API converts text into numerical vectors for use in search, recommendation systems, anomaly detection, and clustering. The latest models, such as text-embedding-3-large, improve performance across both English and non-English tasks.
- Moderation Models: OpenAI’s Moderation API helps detect unsafe or sensitive content based on categories like hate speech, violence, and self-harm. The API processes up to 32,768 tokens in each moderation check and provides high accuracy in text classification.
- NOTES: Model endpoint compatibility
Endpoint | Model name | Description |
---|---|---|
/v1/chat/completions | gpt-4, gpt-4o, gpt-4o-mini, gpt-3.5-turbo | Supports both text and image inputs with the latest chat completion features. |
/v1/completions | text-davinci-003, text-davinci-002, text-curie-001, text-babbage-001, text-ada-001 | Legacy completions endpoint used for traditional text completions. |
/v1/edits | text-davinci-edit-001, code-davinci-edit-001 | Used for editing or inserting text based on instructions. |
/v1/audio/transcriptions | whisper-1 | Converts speech into text using the Whisper model. |
/v1/audio/translations | whisper-1 | Translates speech into different languages using the Whisper model. |
/v1/fine-tunes | gpt-4o, gpt-4o-mini, gpt-3.5-turbo, davinci, curie, babbage, ada | Enables fine-tuning models for specific tasks. |
/v1/embeddings | text-embedding-3-large, text-embedding-3-small, text-embedding-ada-002 | Converts text into numerical vectors for use in search, recommendation, and classification systems. |
/v1/moderations | text-moderation-stable, text-moderation-latest | Used to detect unsafe or sensitive content in text. |
/v1/images/generations | dall-e-2, dall-e-3 | Generates or edits images based on text prompts using the DALL·E models. |
/v1/audio/speech | tts-1, tts-1-hd | Converts text into natural-sounding spoken audio using the Text-to-Speech (TTS) models. |
2024
- GPT-4
- The OpenAI API provides developers with endpoints that offer access to powerful AI models for various tasks. These include model completions, chat completions, embeddings, and more. The API also supports function calling for complex tasks and is governed by rate limits and pricing tiers. More details on the OpenAI API can be found in the official documentation. <a href="https://platform.openai.com/docs/models">More details</a>.
- Model Endpoints: The OpenAI API provides model endpoints like Chat Completions, Text Completions, and Function Calling, which can be leveraged for Natural Language Processing (NLP), data analysis, and content creation. More details are available in the official OpenAI API documentation: <a href="https://platform.openai.com/docs/api-reference/chat/create">More details</a>.
- Function Calling Capability: This feature allows developers to transform natural language commands into structured API requests or SQL queries, enabling automation directly from user input. <a href="https://platform.openai.com/docs">More details</a>.
- Rate Limits and Usage Tiers: OpenAI provides several pricing models based on usage, ensuring scalability for both small developers and enterprise-level applications. <a href="https://platform.openai.com/docs">More details</a>.
- Accessibility and Ethics: OpenAI enforces responsible use of the API, limiting access and ensuring compliance with safety standards to prevent misuse. <a href="https://openai.com/api">More details</a>.
- The OpenAI API provides developers with endpoints that offer access to powerful AI models for various tasks. These include model completions, chat completions, embeddings, and more. The API also supports function calling for complex tasks and is governed by rate limits and pricing tiers. More details on the OpenAI API can be found in the official documentation. <a href="https://platform.openai.com/docs/models">More details</a>.
2023
- https://platform.openai.com/docs/models/gpt-3
- Model endpoint compatibility
Endpoint | Model name | |
---|---|---|
/v1/chat/completions | gpt-4, gpt-4-0314, gpt-4-32k, gpt-4-32k-0314, gpt-3.5-turbo, gpt-3.5-turbo-0301 | |
/v1/completions | text-davinci-003, text-davinci-002, text-curie-001, text-babbage-001, text-ada-001, davinci, curie, babbage, ada | |
/v1/edits | text-davinci-edit-001, code-davinci-edit-001 | |
/v1/audio/transcriptions | whisper-1 | |
/v1/audio/translations | whisper-1 | |
/v1/fine-tunes | davinci, curie, babbage, ada | |
/v1/embeddings | text-embedding-ada-002, text-search-ada-doc-001 | |
/v1/moderations | text-moderation-stable, text-moderation-latest |