/pydantic-ai-common-pitfalls

name: pydantic-ai-common-pitfalls
description: Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.

PydanticAI Common Pitfalls and Debugging

Tool Decorator Errors

Wrong: RunContext in tool_plain

# ERROR: RunContext not allowed in tool_plain
@agent.tool_plain
async def bad_tool(ctx: RunContext[MyDeps]) -> str:
    return "oops"
# UserError: RunContext annotations can only be used with tools that take context

**Fix**: Use `@agent.tool` if you need context:

@agent.tool
async def good_tool(ctx: RunContext[MyDeps]) -> str:
    return "works"

Wrong: Missing RunContext in tool

# ERROR: First param must be RunContext
@agent.tool
def bad_tool(user_id: int) -> str:
    return "oops"
# UserError: First parameter of tools that take context must be annotated with RunContext[...]

**Fix**: Add RunContext as first parameter:

@agent.tool
def good_tool(ctx: RunContext[MyDeps], user_id: int) -> str:
    return "works"

Wrong: RunContext not first

# ERROR: RunContext must be first parameter
@agent.tool
def bad_tool(user_id: int, ctx: RunContext[MyDeps]) -> str:
    return "oops"

**Fix**: RunContext must always be the first parameter.

Valid Patterns (Not Errors)

Raw Function Tool Registration

The following pattern IS valid and supported by pydantic-ai:

from pydantic_ai import Agent, RunContext

async def search_db(ctx: RunContext[MyDeps], query: str) -> list[dict]:
    """Search the database."""
    return await ctx.deps.db.search(query)

async def get_user(ctx: RunContext[MyDeps], user_id: int) -> dict:
    """Get user by ID."""
    return await ctx.deps.db.get_user(user_id)

# Valid: Pass raw functions to Agent(tools=[...])
agent = Agent(
    'openai:gpt-4o',
    deps_type=MyDeps,
    tools=[search_db, get_user]  # RunContext detected from signature
)

**Why this works:** PydanticAI inspects function signatures. If the first parameter is `RunContext[T]`, it's treated as a context-aware tool. No decorator required.

**Reference:** https://ai.pydantic.dev/agents/#registering-tools-via-the-tools-argument

**Do NOT flag** code that passes functions with `RunContext` signatures to `Agent(tools=[...])`. This is equivalent to using `@agent.tool` and is explicitly documented.

Dependency Type Mismatches

Wrong: Missing deps at runtime

agent = Agent('openai:gpt-4o', deps_type=MyDeps)

# ERROR: deps required but not provided
result = agent.run_sync('Hello')  # Missing deps!

**Fix**: Always provide deps when deps_type is set:

result = agent.run_sync('Hello', deps=MyDeps(...))

Wrong: Wrong deps type

@dataclass
class AppDeps:
    db: Database

@dataclass
class WrongDeps:
    api: ApiClient

agent = Agent('openai:gpt-4o', deps_type=AppDeps)

# Type error: WrongDeps != AppDeps
result = agent.run_sync('Hello', deps=WrongDeps(...))

Output Type Issues

Pydantic validation fails

class Response(BaseModel):
    count: int
    items: list[str]

agent = Agent('openai:gpt-4o', output_type=Response)
result = agent.run_sync('List items')
# May fail if LLM returns wrong structure

**Fix**: Increase retries or improve prompt:

agent = Agent(
    'openai:gpt-4o',
    output_type=Response,
    retries=3,  # More attempts
    instructions='Return JSON with count (int) and items (list of strings).'
)

Complex nested types

# May cause schema issues with some models
class Complex(BaseModel):
    nested: dict[str, list[tuple[int, str]]]

**Fix**: Simplify or use intermediate models:

class Item(BaseModel):
    id: int
    name: str

class Simple(BaseModel):
    items: list[Item]

Async vs Sync Mistakes

Wrong: Calling async in sync context

# ERROR: Can't await in sync function
def handler():
    result = await agent.run('Hello')  # SyntaxError!

**Fix**: Use run_sync or make handler async:

def handler():
    result = agent.run_sync('Hello')

# Or
async def handler():
    result = await agent.run('Hello')

Wrong: Blocking in async tools

@agent.tool
async def slow_tool(ctx: RunContext[Deps]) -> str:
    time.sleep(5)  # WRONG: Blocks event loop!
    return "done"

**Fix**: Use async I/O:

@agent.tool
async def slow_tool(ctx: RunContext[Deps]) -> str:
    await asyncio.sleep(5)  # Correct
    return "done"

Model Configuration Errors

Missing API key

# ERROR: OPENAI_API_KEY not set
agent = Agent('openai:gpt-4o')
result = agent.run_sync('Hello')
# ModelAPIError: Authentication failed

**Fix**: Set environment variable or use defer_model_check:

# For testing
agent = Agent('openai:gpt-4o', defer_model_check=True)
with agent.override(model=TestModel()):
    result = agent.run_sync('Hello')

Invalid model string

# ERROR: Unknown provider
agent = Agent('unknown:model')
# ValueError: Unknown model provider

**Fix**: Use valid provider:model format.

Streaming Issues

Wrong: Using result before stream completes

async with agent.run_stream('Hello') as response:
    # DON'T access .output before streaming completes
    print(response.output)  # May be incomplete!

# Correct: access after context manager
print(response.output)  # Complete result

Wrong: Not iterating stream

async with agent.run_stream('Hello') as response:
    pass  # Never consumed!

# Stream was never read - output may be incomplete

**Fix**: Always consume the stream:

async with agent.run_stream('Hello') as response:
    async for chunk in response.stream_output():
        print(chunk, end='')

Tool Return Issues

Wrong: Returning non-serializable

@agent.tool_plain
def bad_return() -> object:
    return CustomObject()  # Can't serialize!

*