Text Responses¶

The simplest use case: send a prompt and receive a plain-text answer. This guide covers both async and sync usage, system prompts, and notes on content that is not supported.

Async Example¶

async_example.py

import asyncio
from pydantic_ai import Agent
import pydantic_ai_web_models

async def main():
    agent = Agent(model="google-web:gemini-3-flash")
    result = await agent.run("Explain quantum computing in one paragraph.")
    print(result.data)

asyncio.run(main())

Sync Example¶

sync_example.py

from pydantic_ai import Agent
import pydantic_ai_web_models

agent = Agent(model="openai-web:gpt-5-3")
result = agent.run_sync("Write a haiku about Python programming.")
print(result.data)

System Prompts¶

Single System Prompt¶

Pass a static system prompt as a string directly to Agent:

system_prompt_string.py

from pydantic_ai import Agent
import pydantic_ai_web_models

agent = Agent(
    model="google-web:gemini-3-flash",
    system_prompt="You are a helpful cooking assistant. Keep answers concise.",
)
result = agent.run_sync("How do I make scrambled eggs?")
print(result.data)

Multiple System Prompts with Decorators¶

For more complex setups you can compose several system prompt functions using the @agent.system_prompt decorator. Each decorated function returns a string; all strings are concatenated (in registration order) before the user prompt.

system_prompt_decorators.py

from pydantic_ai import Agent
import pydantic_ai_web_models

agent = Agent(model="openai-web:gpt-5-3")


@agent.system_prompt
def base_prompt() -> str:
    return "You are a travel guide specializing in European destinations."


@agent.system_prompt
def style_prompt() -> str:
    return "Always include a practical tip at the end of your response."


result = agent.run_sync("What should I see in Prague?")
print(result.data)

Binary content is silently skipped

If any message in the conversation contains binary content — such as an image or file attachment — that part of the message is silently ignored. Only the text portions are forwarded to the Temporal workflow. This means agents that rely on vision or document understanding will not work correctly with this provider; use a native API-based provider for those cases.