> ## Documentation Index
> Fetch the complete documentation index at: https://docs.voight.xyz/llms.txt
> Use this file to discover all available pages before exploring further.

# Bitfrost (Python)

> Drop-in OpenTelemetry observability for Python LLM apps — standalone, or shipping to Voight.

`bitfrost` is a Python package that turns the OpenTelemetry spans your LLM
libraries already emit into a clean, queryable event stream — in your
terminal, in a local web dashboard, in SQLite, or shipped to Voight. One
line to start, no account required.

It's the Python counterpart to the JavaScript [`@voightxyz/vercel-ai`](/ai-apps/vercel-ai)
exporter: same backend, same dashboard, different runtime. Events from
both land side-by-side under the same agent.

## Install

```bash theme={null}
pip install bitfrost                 # core
pip install 'bitfrost[cli,serve]'    # + CLI, TUI, and local web dashboard
pip install 'bitfrost[all]'          # everything
```

Python 3.10–3.13, MIT licensed.

## Quick start

```python theme={null}
import bitfrost

bitfrost.quickstart(agent="my-app")   # auto-detects openai / anthropic / litellm / smolagents
```

Every LLM call now streams to your terminal — color-coded, with tokens,
latency, and an estimated cost. No network calls, no account.

## Ship to Voight

The hosted dashboard is one opt-in backend:

```python theme={null}
import bitfrost
from bitfrost.backends.voight import VoightBackend

bitfrost.instrument_auto(backend=VoightBackend(api_key="vk_..."), agent="my-app")
```

Set `VOIGHT_KEY` in the environment and you can drop the `api_key` argument.
Events appear under **AI Apps** alongside your other SDKs.

## Backends

| Backend   | Import                                     | Use it for                                      |
| --------- | ------------------------------------------ | ----------------------------------------------- |
| Console   | `bitfrost.backends.console.ConsoleBackend` | live, color-coded terminal output               |
| SQLite    | `bitfrost.backends.sqlite.SQLiteBackend`   | persistent local log; powers `bitfrost serve`   |
| JSONL     | `bitfrost.backends.jsonl.JSONLBackend`     | one JSON object per line; replay-able           |
| OTLP/HTTP | `bitfrost.backends.otlp.OTLPBackend`       | POST events as JSON to any collector or webhook |
| Voight    | `bitfrost.backends.voight.VoightBackend`   | hosted dashboards (opt-in)                      |
| Tee       | `bitfrost.backends.tee.TeeBackend`         | fan out to several at once                      |

## Auto-instrument helpers

```python theme={null}
import bitfrost

bitfrost.instrument_openai()
bitfrost.instrument_anthropic()
bitfrost.instrument_litellm()
bitfrost.instrument_smolagents()
bitfrost.instrument_auto()    # every supported lib that's installed
```

Each accepts `backend`, `agent`, `session_id`, and `privacy`.

## CLI

```bash theme={null}
bitfrost watch  capture.db        # live tail
bitfrost replay capture.jsonl     # re-render a captured run
bitfrost query  capture.db "SELECT model, COUNT(*) FROM events GROUP BY model"
bitfrost tui    capture.db        # full-screen terminal dashboard
bitfrost serve  capture.db        # local web dashboard
```

## Privacy

Three levels, applied in-process before any event is sent:

* `minimal` — metadata only, no prompt/response content
* `standard` *(default)* — content kept, PII scrubbed (12 patterns + Luhn)
* `full` — everything verbatim (local debugging only)

```python theme={null}
bitfrost.instrument_openai(privacy="minimal")
```

## Standalone by design

Bitfrost's core has no dependency on any hosted service. The terminal
output, SQLite log, JSONL files, CLI, TUI, and web dashboard all work with
zero network access. Voight is one backend among several — recommended
for managed dashboards and per-user cost attribution, never required.

See the [README](https://github.com/Voightxyz/bitfrost) and the
[cookbook](https://github.com/Voightxyz/bitfrost/blob/main/docs/cookbook.md)
for more.