Add Depends like behaviour
#32
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pydantic_ai/_system_prompt.py
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| # Annotated with Depends(...) | ||
| new_params.append(param) | ||
| continue | ||
| type_hint = annotated_args[0] |
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not sure we need this, I worry it opens up some potentially annoying precedent to allow Annotated[CallContext(..), ...].
pydantic_ai/depends.py
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| Callable[P, T], | ||
| _InjectWrapper[P, T], | ||
| ]: | ||
| """Basically the same as `fast_depends.Depends`, just adds a marker indicating that it was called.""" |
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| """Basically the same as `fast_depends.Depends`, just adds a marker indicating that it was called.""" | |
| """Basically the same as `fast_depends.inject`, just adds a marker indicating that it was called.""" |
pydantic_ai/depends.py
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| return result | ||
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| def is_injected(func: Callable[..., Any]) -> bool: |
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probably want to mark this as private, it shouldn't be in the public API.
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presumably we have to relax the signature of |
pydantic_ai/depends.py
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| P = ParamSpec('P') | ||
| T = TypeVar('T') | ||
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| DependsType = model.Depends |
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we should have an __all__. and Depends at least should be re-exported from __init__.py.
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dmontagu
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Overall this looks like a good start, my main concern that there's a lot more work to do.
I also wonder if we should add a way to customise Deps similar to dependency_provider.scope but specifically for accessing them from CallContext. Something like
with pydantic_ai.override_deps(MyAgent, custom_deps):
...I think next steps (in order of priority):
- make sure
Dependsis working in system prompts, retrievers and result validation - add tests
- get the API right so stuff we don't want to expose is private
- add thorough docstrings
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I would suggest we move /_depends to /depends to make it public, then only export Depends form the root __init__.py
Making this file public should also make the API documentation easier.
| @@ -0,0 +1,118 @@ | |||
| import inspect | |||
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one line docstring would be nice.
| use_cache: bool = True, | ||
| is_sync: bool | None = None, | ||
| ) -> CallModel[P, T]: | ||
| name = getattr(call, '__name__', type(call).__name__) |
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I think we assume elsewhere that call.__name__ is always available for callables.
| for arg in annotated_args[1:]: | ||
| if isinstance(arg, DependsType): | ||
| if dep: | ||
| raise ValueError(f'Cannot specify multiple `Depends` arguments for `{param_name}`!') |
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We should probably use our UserError exception, or remove it and use plain ValueError everywhere.
| *, | ||
| use_cache: bool = True, | ||
| is_sync: bool | None = None, | ||
| ) -> CallModel[P, T]: |
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quick docstring even if this is private.
| # Define the response type | ||
| @dataclass | ||
| class ReviewAnalysisResponse: | ||
| score: int # Between -5 (most negative) and +5 (most positive) |
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constraint, also use Field to add a description to help the LLM.
| @dataclass | ||
| class ReviewAnalysisResponse: | ||
| score: int # Between -5 (most negative) and +5 (most positive) | ||
| tags: list[ReviewTag] # Extracted tags from the review |
| tags: list[ReviewTag] # Extracted tags from the review | ||
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| Response = ReviewAnalysisResponse |
| agent = Agent[None, Response]( | ||
| result_type=Response, | ||
| retries=2, | ||
| model=GeminiModel('gemini-1.5-flash', api_key='<OMITTED>'), |
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| agent = Agent[None, Response]( | |
| result_type=Response, | |
| retries=2, | |
| model=GeminiModel('gemini-1.5-flash', api_key='<OMITTED>'), | |
| agent = Agent( | |
| 'gemini-1.5-flash' | |
| result_type=Response, | |
| retries=2, |
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The principle looks good, I think we need do a better job of separating the production code from the evals code.
samuelcolvin
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Depends like behaviour
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Closing in favor of alternative approaches, just too much to add here |
Can't believe it but it looks like this passes all tests and type-checking.
We'd need to do the same for the the other kinds of things that can be done with decorators but this seems pretty nice. Note that this requires
CallContextto work (can't use bareDeps), so I think it's probably best to keep that around.