glassbrain
AI-native error tracking and observability for Python applications. Captures errors, LLM calls, and application traces with AI-powered fix suggestions.
Installation
pip install glassbrain
Quick Start
from glassbrain import GlassBrain
gb = GlassBrain(api_key="gb_your_key")
# Capture errors
try:
risky_operation()
except Exception as e:
gb.capture_error(e, metadata={"user_id": "123"})
# Capture warnings and info
gb.capture_warning("Disk usage above 90%")
gb.capture_info("Deployment completed", metadata={"version": "1.2.0"})
# Get AI fix suggestions for a trace
suggestions = gb.get_suggestions(trace_id="...")
Auto-trace OpenAI calls
from openai import OpenAI
from glassbrain import GlassBrain, wrap_openai
gb = GlassBrain(api_key="gb_your_key")
client = wrap_openai(OpenAI(), gb)
# All completions are now traced automatically
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello"}]
)
Auto-trace Anthropic calls
from anthropic import Anthropic
from glassbrain import GlassBrain, wrap_anthropic
gb = GlassBrain(api_key="gb_your_key")
client = wrap_anthropic(Anthropic(), gb)
response = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}]
)
Decorators
from glassbrain import GlassBrain, trace_function, trace_endpoint
gb = GlassBrain(api_key="gb_your_key")
@trace_function(gb)
def process_data(items):
# Automatically traces errors and performance
...
@trace_endpoint(gb)
def handle_request():
# Traces API endpoint calls
...
Framework Middleware
FastAPI
from fastapi import FastAPI
from glassbrain import GlassBrain
from glassbrain.middleware import FastAPIMiddleware
app = FastAPI()
gb = GlassBrain(api_key="gb_your_key")
app.add_middleware(FastAPIMiddleware, glassbrain=gb)
Flask
from flask import Flask
from glassbrain import GlassBrain
from glassbrain.middleware import FlaskMiddleware
app = Flask(__name__)
gb = GlassBrain(api_key="gb_your_key")
FlaskMiddleware(app, glassbrain=gb)
Django
Add to settings.py:
GLASSBRAIN_API_KEY = "gb_your_key"
MIDDLEWARE = [
"glassbrain.middleware.DjangoMiddleware",
...
]
Publishing to PyPI
cd packages/glassbrain-python
pip install build twine
python -m build
twine upload dist/*
License
MIT
Metadata
Release files for glassbrain 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| glassbrain-0.2.1.tar.gz | 7.0 kB | Without provenance | Details for glassbrain-0.2.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| glassbrain-0.2.1-py3-none-any.whl | Python 3 | none | any | Details for glassbrain-0.2.1-py3-none-any.whl |
Total release size: 16.5 kB
Release files / glassbrain-0.2.1.tar.gz
| Download URL | glassbrain-0.2.1.tar.gz |
|---|---|
| Size | 7.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a542ca7b3dca8da804459e9809af4ce66a8dd0d936d3d2d0739c10fe7c1ec5f1
|
|
BLAKE2b-256 checksum How to use checksums |
a238118450e2e9b24710c42ad80afb29213bd46fa1f5619629683f321426205f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.9
|
Release files / glassbrain-0.2.1-py3-none-any.whl
| Download URL | glassbrain-0.2.1-py3-none-any.whl |
|---|---|
| Size | 9.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6310a40e3f978c3fe5458e5221ce60e713a04c2d689c6d8f7a103b81d9731f6f
|
|
BLAKE2b-256 checksum How to use checksums |
66de1bf9e90235230ff2fac4d2c629b6163ea0101008c1280485bd74ddf511d8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.9
|
Security for glassbrain 0.2.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.