What do you want to automate

with PostgreSQL and OpenAI (ChatGPT)?

Execute a custom PostgreSQL query. See our docs to learn more about working with SQL in Pipedream.

The Chat API, using the gpt-3.5-turbo or gpt-4 model. See the documentation

Deletes a row or rows from a table. See the documentation

Chat using the web search tool. See the documentation

Finds a row in a table via a lookup column. See the documentation

Chat with your models and allow them to invoke functions. Optionally, you can build and invoke workflows as functions. See the documentation

Finds a row in a table via a custom query. See the documentation

Chat with your files knowledge base (vector stores). See the documentation

Adds a new row. See the documentation

Summarizes text using the Chat API. See the documentation

Classify items into specific categories using the Chat API. See the documentation

Translate text from one language to another using the Chat API. See the documentation

Transcribes audio into the input language. See the documentation

Creates an image given a prompt returning a URL to the image. See the documentation

Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. See the documentation

Execute a SQL Query. See our docs to learn more about working with SQL in Pipedream.

OpenAI recommends using the Chat action for the latest gpt-3.5-turbo API, since it's faster and 10x cheaper. This action creates a completion for the provided prompt and parameters using the older /completions API. See the documentation

Updates an existing row. See the documentation

Send a message or question about an image and receive a response. See the documentation

Adds a new row or updates an existing row. See the documentation

Cancels a run that is in progress. See the documentation

Sends a message and generates a response, storing the message history for a continuous conversation. See the documentation

Send a chat via the Responses API, mixing built-in tools and MCP server tools. See the documentation

Generates audio from the input text. See the documentation

Creates an assistant with a model and instructions. See the documentation

Creates and executes a batch from an uploaded file of requests. See the documentation

Creates a job that fine-tunes a specified model from a given dataset. See the documentation

Classifies if text is potentially harmful. See the documentation

Creates a thread with optional messages and metadata, and optionally runs the thread using the specified assistant. See the documentation

Create a vector store. See the documentation

Create a vector store file. See the documentation

Deletes a specified file from OpenAI. See the documentation

Delete a vector store. See the documentation

Deletes a vector store file. See the documentation

Returns a list of files that belong to the user's organization. See the documentation

Lists the messages for a given thread. See the documentation

Returns a list of run steps belonging to a run. See the documentation

Returns a list of runs belonging to a thread. See the documentation

Returns a list of vector store file. See the documentation

Returns a list of vector stores. See the documentation

Modifies an existing OpenAI assistant. See the documentation

Retrieves a specific file from OpenAI. See the documentation

Retrieves the contents of the specified file. See the documentation

Retrieves a specific run within a thread. See the documentation

Retrieve a specific run step in a thread. See the documentation

Retrieve a vector store. See the documentation

Retrieve a vector store file. See the documentation

Submits tool outputs to a run that requires action. See the documentation

Upload a file that can be used across various endpoints/features. The size of individual files can be a maximum of 512mb. See the documentation