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Generative AI > OpenAI API > OpenAI Assistants API - Building Persistent AI Assistants

OpenAI Assistants API - Building Persistent AI Assistants

Author: Venkata Sudhakar

The OpenAI Assistants API provides a managed framework for building AI assistants with persistent conversation threads, file handling, and built-in tools like code interpreter and file search. Unlike the Chat Completions API where you manually manage conversation history, the Assistants API stores threads server-side so you never have to pass history in every request - making it ideal for customer service bots that need long-running sessions.

The key concepts are: Assistant (a configured AI persona with instructions and tools), Thread (a persistent conversation session), Message (a single turn in a thread), and Run (an execution of the assistant on a thread). Each Run processes all messages in the thread and produces a response. Threads can hold unlimited history without any token limit management on your side.

The below example creates a ShopMax India customer support assistant using the OpenAI Assistants API with a persistent thread that remembers previous conversation context.

from openai import OpenAI
import time

client = OpenAI(api_key="YOUR_OPENAI_API_KEY")

# Create the assistant (do this once, save the ID)
assistant = client.beta.assistants.create(
    name="ShopMax Support Agent",
    instructions="""You are a customer support specialist for ShopMax India.
Key policies:
- Returns accepted within 10 days in original packaging
- 1-year warranty on all electronics
- Free delivery on orders above Rs 500
- 0% EMI available on purchases above Rs 30000
Always be empathetic and provide specific actionable steps.""",
    model="gpt-4o-mini"
)
print(f"Assistant created: {assistant.id}")

# Create a persistent thread
thread = client.beta.threads.create()
print(f"Thread created: {thread.id}")

def ask(question):
    client.beta.threads.messages.create(
        thread_id=thread.id,
        role="user",
        content=question
    )
    run = client.beta.threads.runs.create_and_poll(
        thread_id=thread.id,
        assistant_id=assistant.id
    )
    messages = client.beta.threads.messages.list(thread_id=thread.id, order="desc", limit=1)
    return messages.data[0].content[0].text.value

print("Q1:", ask("What is the return policy at ShopMax?"))
print("Q2:", ask("Does that apply to the laptop I bought last week too?"))

It gives the following output,

Assistant created: asst_abc123xyz
Thread created: thread_def456uvw
Q1: ShopMax India accepts returns within 10 days of purchase.
Items must be in original packaging with all accessories.
Visit any ShopMax store or use the app to initiate a return.
Q2: Yes, absolutely! The 10-day return policy applies to all
electronics including your laptop. As long as it was purchased
within the last 10 days and is in original packaging, you can
return it without any issues.

The second question "Does that apply to the laptop I bought last week?" received a correct contextual answer because the thread remembered the previous exchange - without any manual history management. Save the thread ID in your database to resume any customer conversation from where it left off. For ShopMax, create one thread per customer session and reuse it across multiple interactions for seamless continuity.

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