The video introduces OpenAI’s new Conversations API, which streamlines managing conversation contexts by automatically handling conversation IDs and tool call outputs, allowing developers to easily maintain and reuse conversation history. It demonstrates practical usage through a script that preserves conversation state across sessions and highlights features like automatic inclusion of code execution results, enhancing the development of complex conversational applications.
The video introduces the new Conversations API from OpenAI, which simplifies managing conversation contexts by automatically handling conversation IDs and tool call outputs. Unlike previous methods where developers had to manually manage code outputs and context, this API integrates everything seamlessly, making it easier to maintain conversation history and tool interactions. Users can create new conversations or reuse existing ones by passing conversation IDs, streamlining the process of building conversational applications.
A key feature highlighted is the automatic inclusion of tool call outputs, such as code interpreter results, image URLs, file search results, and more, through a new parameter called “include.” This allows developers to specify what additional outputs they want to be part of the conversation context, enhancing the model’s understanding and response capabilities. The API leverages the existing responses API but adds this layer of conversation management, making it more convenient for developers to build complex interactions without manually tracking every detail.
The presenter demonstrates a simple script that interacts with the Conversations API, showing how it creates and stores conversation IDs in a file for persistence. This approach allows the conversation to continue across multiple runs of the script without losing context. If a new conversation is desired, deleting the stored ID file resets the context. The script accepts user input and sends it as a user message, with the API handling the rest, including maintaining the conversation state and tool outputs.
An example use case is shown where the model is asked to write Python code to find the 54th prime number using brute force. The code is generated, executed, and the result is returned, all while the conversation history, including the generated code, is preserved and viewable in the OpenAI conversation logs. This demonstrates the practical benefits of the Conversations API in managing complex interactions that involve code generation and execution within a persistent conversational context.
Finally, the video mentions additional resources provided by the presenter, including the full Conversations API documentation in a convenient text file and a script available on Patreon. The presenter encourages viewers to explore these resources and consider joining the Patreon community for more tutorials, applications, and consulting services related to large language models. The video concludes with an invitation to engage further and thanks viewers for watching.