OpenAI Assistants API: Building Stateful AI Applications

The Assistants API provides a stateful interface for building AI assistants with memory, tools, and file handling.

Creating an Assistant

from openai import OpenAI

client = OpenAI()

# Create assistant
assistant = client.beta.assistants.create(
    name="Code Helper",
    instructions="You are a helpful coding assistant. Help users with Python programming.",
    model="gpt-4-turbo-preview",
    tools=[{"type": "code_interpreter"}]
)

print(f"Assistant ID: {assistant.id}")

Managing Threads and Messages

# Create thread
thread = client.beta.threads.create()

# Add message
message = client.beta.threads.messages.create(
    thread_id=thread.id,
    role="user",
    content="How do I reverse a string in Python?"
)

# Run assistant
run = client.beta.threads.runs.create(
    thread_id=thread.id,
    assistant_id=assistant.id
)

# Wait for completion
import time
while run.status != "completed":
    run = client.beta.threads.runs.retrieve(
        thread_id=thread.id,
        run_id=run.id
    )
    time.sleep(1)

# Get response
messages = client.beta.threads.messages.list(thread_id=thread.id)
print(messages.data[0].content[0].text.value)

File Handling

# Upload file
file = client.files.create(
    file=open("data.csv", "rb"),
    purpose="assistants"
)

# Create assistant with file access
assistant = client.beta.assistants.create(
    name="Data Analyst",
    instructions="Analyze data files",
    model="gpt-4-turbo-preview",
    tools=[{"type": "code_interpreter"}],
    file_ids=[file.id]
)

# Ask questions about the file
message = client.beta.threads.messages.create(
    thread_id=thread.id,
    role="user",
    content="What's the average value in the data?"
)

Function Calling

# Define functions
tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get weather for a location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {"type": "string"}
                },
                "required": ["location"]
            }
        }
    }
]

assistant = client.beta.assistants.create(
    name="Weather Assistant",
    tools=tools,
    model="gpt-4-turbo-preview"
)

# Handle function calls in run
if run.status == "requires_action":
    tool_calls = run.required_action.submit_tool_outputs.tool_calls
    
    tool_outputs = []
    for call in tool_calls:
        if call.function.name == "get_weather":
            # Execute function
            result = get_weather(call.function.arguments)
            tool_outputs.append({
                "tool_call_id": call.id,
                "output": result
            })
    
    # Submit outputs
    run = client.beta.threads.runs.submit_tool_outputs(
        thread_id=thread.id,
        run_id=run.id,
        tool_outputs=tool_outputs
    )

The Assistants API simplifies building stateful, capable AI applications!