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Responses API previous_response_id explained

Q: Responses API previous_response_id explained

The previous_response_id parameter in the OpenAI Responses API lets you reference a prior completion's ID to create a linked chain of responses, enabling context continuity or incremental generation. Use it to build conversational threads or track response lineage in your application.

Quick answer

The previous_response_id parameter in the OpenAI Responses API lets you reference a prior completion's ID to create a linked chain of responses, enabling context continuity or incremental generation. Use it to build conversational threads or track response lineage in your application.

PREREQUISITES

Python 3.8+
OpenAI API key (free tier works)
pip install openai>=1.0

Setup

Install the official OpenAI Python SDK and set your API key as an environment variable to authenticate requests.

bash

pip install openai>=1.0

Step by step

This example demonstrates how to create a chat completion and then use its id as the previous_response_id in a subsequent request to maintain response linkage.

python

import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

# First completion
response1 = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello, who won the 2024 Olympics?"}]
)
print("First response:", response1.choices[0].message.content)

# Use the previous response ID to chain
previous_id = response1.id

response2 = client.chat.completions.create(
    model="gpt-4o",
    previous_response_id=previous_id,
    messages=[{"role": "user", "content": "Can you give more details about the gold medalists?"}]
)
print("Second response:", response2.choices[0].message.content)

output

First response: The 2024 Olympics were held in Paris, and the United States topped the medal count.
Second response: The U.S. won gold medals in swimming, athletics, and gymnastics, with standout athletes like Katie Ledecky and Caeleb Dressel making history.

Common variations

Use previous_response_id to build multi-turn conversations or incremental content generation.
Combine with different models like gpt-4o-mini for cost-effective chaining.
Use async calls with asyncio for concurrent chained requests.

python

import asyncio
from openai import OpenAI

async def main():
    client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

    response1 = await client.chat.completions.acreate(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": "Summarize the latest AI trends."}]
    )
    print("Async first response:", response1.choices[0].message.content)

    response2 = await client.chat.completions.acreate(
        model="gpt-4o-mini",
        previous_response_id=response1.id,
        messages=[{"role": "user", "content": "Expand on AI in healthcare."}]
    )
    print("Async second response:", response2.choices[0].message.content)

asyncio.run(main())

output

Async first response: AI trends include generative models, multimodal AI, and increased adoption in industries.
Async second response: In healthcare, AI is improving diagnostics, personalized medicine, and drug discovery.

Troubleshooting

If you get an error about previous_response_id not found, verify the ID is correct and from the same model and API version.
Ensure your API key has permissions for the Responses API features.
Check that the previous_response_id is used only in supported endpoints; it is not valid for all request types.

✅

Key Takeaways

Use previous_response_id to link completions and maintain context across calls.
Always retrieve and store the id from the initial response to pass in subsequent requests.
The parameter enables building conversational threads or incremental content generation efficiently.

Verified 2026-04 · gpt-4o, gpt-4o-mini

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