- Home
- Automation
- Logfire
Rating
Votes
0
score
Downloads
0
total
Price
Free
Access token required
Works With
About
Pydantic Logfire — Know more. Build faster.
From the team behind Pydantic Validation, Pydantic Logfire is an observability platform built on the same belief as our open source library — that the most powerful tools can be easy to use.
What sets Logfire apart:
- Simple and Powerful: Logfire's dashboard is simple relative to the power it provides, ensuring your entire engineering team will actually use it.
- Python-centric Insights: From rich display of Python objects, to event-loop telemetry, to profiling Python code and database queries, Logfire gives you unparalleled visibility into your Python application's behavior.
- SQL: Query your data using standard SQL — all the control and (for many) nothing new to learn. Using SQL also means you can query your data with existing BI tools and database querying libraries.
- OpenTelemetry: Logfire is an opinionated wrapper around OpenTelemetry, allowing you to leverage existing tooling, infrastructure, and instrumentation for many common Python packages, and enabling support for virtually any language. We offer full support for all OpenTelemetry signals (traces, metrics and logs).
- Pydantic Integration: Understand the data flowing through your Pydantic Validation models and get built-in analytics on validations.
See the documentation for more information.
Feel free to report issues and ask any questions about Logfire in this repository!
This repo contains the Python SDK for logfire and documentation; the server application for recording and displaying data is closed source.
Using Logfire
This is a very brief overview of how to use Logfire, the documentation has much more detail.
Install
pip install logfireAuthenticate
logfire authManual tracing
Here's a simple manual tracing (aka logging) example:
from datetime import date
import logfire
logfire.configure()
logfire.info('Hello, {name}!', name='world')
with logfire.span('Asking the user their {question}', question='age'):
user_input = input('How old are you [YYYY-mm-dd]? ')
dob = date.fromisoformat(user_input)
logfire.debug('{dob=} {age=!r}', dob=dob, age=date.today() - dob)Integration
Or you can also avoid manual instrumentation and instead integrate with lots of popular packages, here's an example of integrating with FastAPI:
from fastapi import FastAPI
from pydantic import BaseModel
import logfire
app = FastAPI()Don't lose this
Three weeks from now, you'll want Logfire again. Will you remember where to find it?
Save it to your library and the next time you need Logfire, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
AI observability platform for production LLM and agent systems. Best for anyone looking to make their AI assistant more capable in automation. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
What's New
Imported from GitHub
Ratings & Reviews
0.0
out of 5
0 ratings
No reviews yet. Be the first to share your experience.