backend/
├── agents/
│   ├── __init__.py
│   ├── base_agent.py          # Base agent class
│   └── [feature]_agent.py     # Feature-specific agents
├── tools/
│   ├── __init__.py
│   └── [tool_name].py         # Tool definitions
└── config/
    └── agent_config.py        # Agent configurations

pip install pydantic-ai httpx pydantic python-dotenv

from pydantic_ai import Agent
from pydantic import BaseModel
import os

class AgentResponse(BaseModel):
    result: str
    confidence: float

agent = Agent(
    model='openrouter:openai/gpt-4o',
    output_type=AgentResponse,
    tools=[tool1, tool2],
    system_prompt="You are a helpful AI assistant."
)

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import os
from pydantic_ai.models import OpenRouterModel

model = OpenRouterModel(
    name='openai/gpt-4o',
    api_key=os.getenv('OPENROUTER_API_KEY'),
    http_referer=os.getenv('FRONTEND_URL')
)

OPENROUTER_API_KEY=sk-or-v1-...
FRONTEND_URL=http://localhost:3000

from pydantic import BaseModel, Field
from pydantic_ai import Agent, Tool

class GenerateImageArgs(BaseModel):
    prompt: str = Field(description="Image description")
    num_images: int = Field(ge=1, le=10, default=1)

async def generate_image_tool(args: GenerateImageArgs) -> dict:
    # Your implementation
    return {"images": [...]}

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async def stream_response(agent, message):
    async for chunk in agent.stream(message):
        yield {
            "type": "text" if isinstance(chunk, str) else "tool_call",
            "content": chunk
        }

from pydantic_ai import Agent, RetryConfig

agent = Agent(
    model='openrouter:openai/gpt-4o',
    retry_config=RetryConfig(
        max_retries=3,
        retry_on=[ValidationError, TimeoutError]
    )
)

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from fastapi import FastAPI, HTTPException
from pydantic import BaseModel

app = FastAPI()

class ChatRequest(BaseModel):
    message: str
    history: list = []

@app.post("/chat")
async def chat_endpoint(request: ChatRequest):
    try:
        result = await agent.run(
            request.message,
            context={"history": request.history}
        )
        return {"response": result.result}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

import pytest
from pydantic_ai import Agent

@pytest.mark.asyncio
async def test_agent_response():
    agent = Agent(
        model='openrouter:openai/gpt-4o',
        system_prompt="You are a test assistant"
    )

    result = await agent.run("Say hello")
    assert "hello" in result.lower()

from pydantic_ai import Agent, Tool
from pydantic import BaseModel, Field
import os

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