Include logfire with pydantic-ai package (#2683)

Co-authored-by: Douwe Maan <[email protected]>

Author: Kludex

docs/install.md

@@ -8,20 +8,14 @@ pip/uv-add pydantic-ai
 
 (Requires Python 3.10+)
 
-This installs the `pydantic_ai` package, core dependencies, and libraries required to use all the models
-included in Pydantic AI. If you want to use a specific model, you can install the ["slim"](#slim-install) version of Pydantic AI.
+This installs the `pydantic_ai` package, core dependencies, and libraries required to use all the models included in Pydantic AI.
+If you want to install only those dependencies required to use a specific model, you can install the ["slim"](#slim-install) version of Pydantic AI.
 
 ## Use with Pydantic Logfire
 
 Pydantic AI has an excellent (but completely optional) integration with [Pydantic Logfire](https://pydantic.dev/logfire) to help you view and understand agent runs.
 
-To use Logfire with Pydantic AI, install `pydantic-ai` or `pydantic-ai-slim` with the `logfire` optional group:
-
-```bash
-pip/uv-add "pydantic-ai[logfire]"
-```
-
-From there, follow the [Logfire setup docs](logfire.md#using-logfire) to configure Logfire.
+Logfire comes included with `pydantic-ai` (but not the ["slim" version](#slim-install)), so you can typically start using it immediately by following the [Logfire setup docs](logfire.md#using-logfire).
 
 ## Running Examples
 

docs/logfire.md

@@ -31,10 +31,16 @@ A trace is generated for the agent run, and spans are emitted for each model req
 
 ## Using Logfire
 
-To use Logfire, you'll need a Logfire [account](https://logfire.pydantic.dev), and the Logfire Python SDK installed:
+To use Logfire, you'll need a Logfire [account](https://logfire.pydantic.dev). The Logfire Python SDK is included with `pydantic-ai`:
 
 ```bash
-pip/uv-add "pydantic-ai[logfire]"
+pip/uv-add pydantic-ai
+```
+
+Or if you're using the slim package, you can install it with the `logfire` optional group:
+
+```bash
+pip/uv-add "pydantic-ai-slim[logfire]"
 ```
 
 Then authenticate your local environment with Logfire:

pydantic_ai_slim/pydantic_ai/usage.py

@@ -122,11 +122,13 @@ class RunUsage(UsageBase):
 
     cache_write_tokens: int = 0
     """Total number of tokens written to the cache."""
+
     cache_read_tokens: int = 0
     """Total number of tokens read from the cache."""
 
     input_audio_tokens: int = 0
     """Total number of audio input tokens."""
+
     cache_audio_read_tokens: int = 0
     """Total number of audio tokens read from the cache."""
 

pydantic_ai_slim/pyproject.toml

@@ -66,7 +66,7 @@ dependencies = [
 
 [tool.hatch.metadata.hooks.uv-dynamic-versioning.optional-dependencies]
 # WARNING if you add optional groups, please update docs/install.md
-logfire = ["logfire>=3.14.1"]
+logfire = ["logfire[httpx]>=3.14.1"]
 # Models
 openai = ["openai>=1.99.9"]
 cohere = ["cohere>=5.16.0; platform_system != 'Emscripten'"]

pyproject.toml

@@ -46,12 +46,11 @@ requires-python = ">=3.10"
 
 [tool.hatch.metadata.hooks.uv-dynamic-versioning]
 dependencies = [
-    "pydantic-ai-slim[openai,vertexai,google,groq,anthropic,mistral,cohere,bedrock,huggingface,cli,mcp,evals,ag-ui,retries,temporal]=={{ version }}",
+    "pydantic-ai-slim[openai,vertexai,google,groq,anthropic,mistral,cohere,bedrock,huggingface,cli,mcp,evals,ag-ui,retries,temporal,logfire]=={{ version }}",
 ]
 
 [tool.hatch.metadata.hooks.uv-dynamic-versioning.optional-dependencies]
 examples = ["pydantic-ai-examples=={{ version }}"]
-logfire = ["logfire>=3.14.1"]
 a2a = ["fasta2a>=0.4.1"]
 
 [project.urls]

tests/test_examples.py

@@ -43,25 +43,15 @@
 
 from .conftest import ClientWithHandler, TestEnv, try_import
 
-try:
-    from pydantic_ai.providers.google import GoogleProvider
-except ImportError:  # pragma: lax no cover
-    GoogleProvider = None
-
-
-try:
-    import logfire
-except ImportError:  # pragma: lax no cover
-    logfire = None
-
-
 with try_import() as imports_successful:
+    # We check whether pydantic_ai_examples is importable as a proxy for whether all extras are installed, as some docs examples require them
+    import pydantic_ai_examples  # pyright: ignore[reportUnusedImport] # noqa: F401
+
     from pydantic_evals.reporting import EvaluationReport
 
 
 pytestmark = [
     pytest.mark.skipif(not imports_successful(), reason='extras not installed'),
-    pytest.mark.skipif(logfire is None or GoogleProvider is None, reason='logfire or google-provider not installed'),
 ]
 code_examples: dict[str, CodeExample] = {}
 

tests/test_temporal.py

@@ -81,7 +81,10 @@
 with workflow.unsafe.imports_passed_through():
     # Workaround for a race condition when running `logfire.info` inside an activity with attributes to serialize and pandas importable:
     # AttributeError: partially initialized module 'pandas' has no attribute '_pandas_parser_CAPI' (most likely due to a circular import)
-    import pandas  # pyright: ignore[reportUnusedImport] # noqa: F401
+    try:
+        import pandas  # pyright: ignore[reportUnusedImport] # noqa: F401
+    except ImportError:  # pragma: lax no cover
+        pass
 
     # https://github.com/temporalio/sdk-python/blob/3244f8bffebee05e0e7efefb1240a75039903dda/tests/test_client.py#L112C1-L113C1
     from inline_snapshot import snapshot