


How to implement context-related dialogue function in OpenAI's API?
Context dialogue in OpenAI API: Cleverly use Prompt to achieve continuous interaction
The simple Q&A features of the OpenAI API are easy to get started, but it takes some tricks to achieve more natural context-related conversations. The official documentation does not directly provide context
or conversation_id
parameters to maintain the context, so we need to manage the conversation history ourselves.
This article will guide you how to implement context-related dialogue functionality by cleverly building Prompt.
Key Strategy: Manage conversation history in the application and integrate it into Prompt
The specific steps are as follows:
Conversation History: Your app needs to maintain a list that records questions and replies to the model each time the user enters.
Build an effective Prompt: Every time a user asks, integrate conversation history into the new Prompt. This allows the model to understand the previous conversation and generates more coherent replies.
-
Control Prompt length: The OpenAI API has restrictions on Prompt length. If the conversation history is too long, the following strategies need to be considered:
- Truncate: Delete earlier conversation content.
- Abstract: Use summary technology to condense conversation history into shorter text.
Process and update history: After receiving a model reply, add it to the conversation history and display it to the user.
In this way, even without direct context parameters, the dialogue context can be effectively managed at the application level, achieving smooth and natural continuous dialogue. This is a flexible and efficient solution that allows your application to interact with the OpenAI API at a higher level.
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