pydantic-ai-dependency-injectionlisted
Install: claude install-skill existential-birds/beagle
# PydanticAI Dependency Injection
## Core Pattern
Dependencies flow through `RunContext`:
```python
from dataclasses import dataclass
from pydantic_ai import Agent, RunContext
@dataclass
class Deps:
db: DatabaseConn
api_client: HttpClient
user_id: int
agent = Agent(
'openai:gpt-4o',
deps_type=Deps, # Type for static analysis
)
@agent.tool
async def get_user_balance(ctx: RunContext[Deps]) -> float:
"""Get the current user's account balance."""
return await ctx.deps.db.get_balance(ctx.deps.user_id)
# At runtime, provide deps
result = await agent.run(
'What is my balance?',
deps=Deps(db=db_conn, api_client=client, user_id=123)
)
```
## Defining Dependencies
Use dataclasses or Pydantic models:
```python
from dataclasses import dataclass
from pydantic import BaseModel
# Dataclass (recommended for simplicity)
@dataclass
class Deps:
db: DatabaseConnection
cache: CacheClient
user_context: UserContext
# Pydantic model (if you need validation)
class Deps(BaseModel):
api_key: str
endpoint: str
timeout: int = 30
```
## Accessing Dependencies
In tools and instructions:
```python
@agent.tool
async def query_database(ctx: RunContext[Deps], query: str) -> list[dict]:
"""Run a database query."""
return await ctx.deps.db.execute(query)
@agent.instructions
async def add_user_context(ctx: RunContext[Deps]) -> str:
user = await ctx.deps.db.get_user(ctx.deps.user_id)
return f"User name: {user.name}, Role: