Connect any REST API using a standard API key
The Generic API Key connector provides a powerful method for integrating with any service that exposes a REST API and uses an API key for authentication. This common authentication pattern involves passing a key-value pair in the request headers, such as 'X-API-Key: YOUR_KEY' or 'Authorization: ApiKey YOUR_KEY'.
By configuring the API base URL, endpoint paths, and authentication details within Flows360, you can create robust, custom integrations. This allows you to send and receive data from internal systems, specialized industry software, or any SaaS application not yet featured in our connector directory. It offers the flexibility to define your own data models and trigger workflows based on HTTP responses, putting you in full control of your integration logic without waiting for a pre-built connector.
Common use cases
- Connect to internal APIs or private microservices
- Integrate with niche SaaS platforms not in the main directory
- Prototype integrations before a dedicated connector is built
- Pull data from proprietary databases exposed via a REST API
Sync scenarios
- Custom Object Sync
- Data Retrieval from Custom Endpoints
- Data Ingestion to Custom Endpoints
- Real-time Event Triggering
Objects supported
- Model (GPT-4, etc.)
- Assistant
- Thread
- Message
- File
- Fine-Tuning Job
- Vector Store
Actions
- create_chat_completion
- generate_image_dall_e
- create_text_embedding
- transcription_whisper
- analyze_image_vision
- moderation_check
- message_assistant
- text_translation
Frequently asked questions
What kind of API key authentication is supported?
The connector supports passing the API key in the request headers. You can customize the header name (e.g., 'X-API-Key', 'Authorization') and the value format (e.g., 'ApiKey {key}').
Can I use this for APIs that require more than just a key?
This connector is designed for simple key-based authentication. for more complex schemes like OAuth 2.0, Basic Auth, or Bearer Tokens, use our specific generic connectors for those standards.
How do I handle different data formats like XML?
The connector is agnostic to the payload format. You can construct and parse any text-based format, including JSON and XML, within your workflow logic. You must set the 'Content-Type' header appropriately for your requests.
- Auth method: API Key
- Required scopes: 1
- Supported objects: 7
- Supported actions: 8
Overview
The OpenAI connector allows you to integrate directly with OpenAI's REST API using an API key for authentication. This provides access to a wide range of artificial intelligence models and tools, including GPT for advanced chat completions, DALL-E for image generation, and Whisper for audio transcription.
By configuring the connector, you can make direct calls to OpenAI API endpoints. This enables you to build powerful workflows that can analyze text, generate content, moderate user input, create text embeddings for semantic search, and interact with the Assistants API to build complex, stateful conversational agents. The connector supports handling various objects like Models, Assistants, Threads, Messages, and Files, giving you granular control over your AI-powered integrations.
Setup steps
1. Log in to OpenAI Platform: Access your OpenAI account at [platform.openai.com](https://platform.openai.com/).
2. Navigate to API Keys: In the left-hand navigation menu, select the "API Keys" section.
3. Create a New Secret Key: Click the "Create new secret key" button. Give your key a descriptive name (e.g., "Flows360 Production") for easy identification.
4. Copy the API Key: Your new API key will be displayed once. Copy it immediately and store it securely, as you will not be able to view it again.
5. Enter Key in Flows360: In the Flows360 OpenAI connector configuration, paste the copied key into the "API Key" field.
6. Configure Authorization Header: Ensure the request header is set to `Authorization: Bearer YOUR_API_KEY`, where `YOUR_API_KEY` is the token from the previous step.
Required scopes
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Supported objects
- Model
- Assistant
- Thread
- Message
- File
- Fine-Tuning Job
- Vector Store
Supported actions
- create_chat_completion — Generates a model response for a given chat conversation or prompt (GPT models).
- generate_image_dall_e — Creates an image from a text prompt using a DALL-E model.
- create_text_embedding — Returns a vector representation of a given input text string.
- transcription_whisper — Transcribes audio into text using the Whisper model.
- analyze_image_vision — Analyzes an image and responds to questions about its content (GPT-4 with Vision).
- moderation_check — Checks if a text string violates OpenAI's content policy.
- message_assistant — Adds a message to an Assistant Thread and triggers a run to get a response.
- text_translation — Translates text from one language to another using a GPT model.
Use cases
- Marketing Automation
- Product Analytics
- Support Ticket Sync
- Data Warehousing
Limitations
The connector operates within the rate limits and quota restrictions of your OpenAI API account tier. Check your OpenAI account for specific limits on tokens per minute (TPM), requests per minute (RPM), and monthly usage quotas. Exceeding these limits will result in API errors (HTTP 429). The connector does not manage model fine-tuning processes directly; it can only initiate and monitor jobs. File and Vector Store management may require multi-step workflows for uploads, processing, and attachment to objects like Assistants or Threads.
