Bitfab
Bitfab client for provider-based API calls.
Monorepo Structure
This package is part of the Harvest monorepo. While the TypeScript/JavaScript packages use a pnpm workspace for shared dependencies, this Python package uses Poetry for its dependency management.
Note: The pnpm workspace includes:
bitfab-web- Next.js web applicationbitfab-typescript-sdk- TypeScript SDKbitfab-vscode- VS Code extensionfrontend- Legacy frontend
From the root directory, you can run TypeScript tests and validation across all packages with pnpm test or pnpm validate.
Installation
Python 3.10 or newer is required.
Basic Installation
pip install bitfab-py
With OpenAI Tracing Support
If you want to use the OpenAI Agents SDK tracing integration:
pip install bitfab-py[openai-tracing]
Local Development
For local development:
cd bitfab-python-sdk
poetry install --with dev
After installation, you can use developer tasks. For the best experience, add Poetry's venv to your PATH:
# Add to your ~/.zshrc or ~/.bashrc
export PATH="$(poetry env info --path)/bin:$PATH"
# Then you can use 'dev' directly (no ./run or poetry run needed!)
dev list
dev test
See Development Tasks below for all available commands.
Or install as an editable package from the parent directory:
poetry add --editable ../bitfab-python-sdk
Usage
Basic Usage
from bitfab import Bitfab
client = Bitfab(
api_key="bf_your_api_key_here",
service_url="https://bitfab.ai", # Optional, defaults to production
env_vars={"OPENAI_API_KEY": "sk-your-openai-key"}, # Optional, for local BAML execution
)
result = client.call("method_name", arg1="value1", arg2="value2")
OpenAI Agents SDK Tracing
If you have the openai-agents package installed (via pip install bitfab-py[openai-tracing]), you can use the tracing processor:
from bitfab import Bitfab
from agents import Agent, add_trace_processor
bitfab = Bitfab(api_key="bf_your_api_key_here")
# Register the processor once: it captures agent internals (LLM/tool/handoff spans).
add_trace_processor(bitfab.get_openai_tracing_processor())
agent = Agent(name="my-agent", instructions="...")
# The run wrapper records a replayable root carrying the run input.
handler = bitfab.get_openai_agent_handler("my-agent")
# Swap Runner.run(agent, input) -> handler.wrap_run(agent, input)
result = await handler.wrap_run(agent, "user input here")
The processor alone records a root with no input, so a processor-only trace is not replayable; wrap_run (a drop-in for Runner.run) records the keyed, replayable root.
Note: If you try to use get_openai_tracing_processor() without installing the openai-tracing extra, you'll get a helpful error message telling you to install it.
Configuration
api_key: Required - Your Bitfab API key (generate from your Bitfab dashboard)service_url: Optional - The Bitfab service URL (defaults tohttps://bitfab.ai)env_vars: Optional - Environment variables for LLM providers (e.g.,{"OPENAI_API_KEY": "..."})enabled: Optional - Enable/disable tracing (defaults toTrue). WhenFalse, decorated functions still execute but no spans are sent.
OpenTelemetry Transport
Bitfab keeps its public decorators and framework handlers, while one private
OpenTelemetry TracerProvider and BatchSpanProcessor per client
manage the bounded queue, batch worker, export scheduling, flush, and shutdown
lifecycle. Pipelines are created lazily on the first trace send and are not
installed globally, so an unused or disabled client starts no OTel worker and
the SDK does not replace an application's OTel setup. Framework integrations
submit the existing replay-safe Bitfab payload through the same transport
interface. Flush and shutdown honor one total caller-supplied deadline.
Long-running processes that create transient clients should call
client.close() or use with Bitfab(...) as client: to release that client's
workers; shared clients still shut down automatically at process exit.
The LangGraph/LangChain handler keeps langsmith:hidden scheduler callbacks
only for local parent resolution and submits visible Bitfab spans through OTel.
OTel schedules exports in internal batches of at most 512 carriers. The
exporter packs that candidate window into requests containing at most eight
carriers and no more than the configured encoded-byte target, then runs up to
32 complete requests concurrently. Set BITFAB_OTEL_EXPORT_CONCURRENCY to an
integer from 1 through 64 to tune that concurrency; invalid values fall back
to 32.
Requests are limited to approximately 3 MB. Set BITFAB_OTEL_MAX_REQUEST_BYTES
to a positive integer no greater than 3000000 to use a smaller target for a
proxy with a stricter limit. Invalid or larger values fall back to 3000000. A
carrier that exceeds the configured limit by itself cannot be split without
changing the captured payload; the SDK logs the failed export without
interrupting the host application.
Each carrier is encoded once and the request body is assembled from those encodings, so a batch is never re-encoded to measure its size.
Before finalizing a replay, the SDK flushes OTel and polls Bitfab's replay-status API until every expected trace completion and span count is persisted.
If Bitfab accepts only part of a batch, it returns the standard OTLP
partialSuccess response and the SDK logs the rejected-span count and reason.
See the OpenTelemetry Transport Architecture for the full component ownership, carrier format, replay barrier, batching, and lifecycle design.
Development Tasks
This project uses a Python-based developer tasks module (dev/) instead of Makefiles for better cross-platform support and more robust CLI capabilities.
Using Developer Tasks
After running poetry install --with dev, you can use developer tasks:
Quick Setup (One-time)
# Install dependencies (creates the 'dev' script in the venv)
poetry install --with dev
# Run this script to add to PATH for current session and get command to make it permanent
./setup-dev-path.sh
# Copy-paste the command it outputs, then reload your shell config:
source ~/.zshrc # or ~/.bashrc
The setup-dev-path.sh script will:
- Add the venv bin to PATH for your current session
- Detect your shell (zsh/bash) and output a command you can copy-paste to make it permanent
- Skip if already configured
Using Developer Commands
Once PATH is set up, use commands directly - just like make <target>:
dev list # List all available commands
dev test # Run tests
dev test --verbose # Run tests with verbose output
dev lint # Lint code
dev format # Format code
dev build # Build package
dev publish patch # Publish with version bump
How it works: When you define [tool.poetry.scripts] in pyproject.toml, Poetry creates executable scripts in the venv's bin/ directory. Adding that bin/ to PATH makes those scripts available as commands.
Key advantage: Just like Makefiles, it's super clear - dev <command> is as obvious as make <target>!
Module Structure
Each command is in its own file in the dev/ module:
dev/test.py- Test commandsdev/lint.py- Lintingdev/build.py- Buildingdev/publish.py- Publishing- etc.
This makes it easy to find and modify individual commands.
Publishing
This package uses bump-my-version for version management. To publish a new version:
# Use the dev command
dev publish patch # Bump patch (0.3.0 -> 0.3.1)
dev publish minor # Bump minor (0.3.0 -> 0.4.0)
dev publish major # Bump major (0.3.0 -> 1.0.0)
dev publish version=1.2.3 # Custom version
# Or just bump version without publishing
dev bump patch
dev bump minor
The publish process will:
- Run all tests
- Bump the version in
pyproject.toml - Commit and tag the changes
- Build the package
- Prompt for confirmation before publishing to PyPI
Note: Publishing requires:
- A clean git working directory (no uncommitted changes)
- Poetry installed and configured
- PyPI credentials configured (via
poetry config pypi-token.pypi <token>)
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