Skip to main content

Experiential

gateway latency

Experiential is an open source gateway and router for agent workflows:

  1. Use hosted, BYOK, and local models through one OpenAI-compatible API.
  2. Control which users and agents can use which models, for which use cases, and how much they can spend.
  3. Turn production traffic into a custom router or model optimized for quality, speed, and cost.

Experiential workspace usage dashboard showing model traffic, identities, and spend

🌐 Platform | 📚 Docs | Discord

Getting Started

Start a local OpenAI-compatible gateway. On first run, the setup wizard uses the shared provider, model, and reasoning-effort selectors, persists every selected provider connection, then shows defaults for the public alias, identity, and $50.00 command budget before printing a one-time key:

pip install experiential
exp

Choose a public alias such as opus-5, capture the issued key, and send a request:

export EXP_GATEWAY_KEY=...
curl http://127.0.0.1:8000/v1/chat/completions \
  -H "Authorization: Bearer $EXP_GATEWAY_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"model":"opus-5","messages":[{"role":"user","content":"Help me"}]}'

Setup / get started with the hosted gateway

Prefer a managed gateway to running one locally? The hosted platform at platform.experientiallabs.ai serves the same OpenAI-compatible (and Anthropic Messages) API at https://api.experientiallabs.ai/v1. See SETUP.md for copy-paste prompts you hand to your coding agent (Claude Code, Cursor, Codex, and similar); the agent runs the setup for you. It collects four prompts:

  • Upload your LLM traces as telemetry: create an account instantly from your email, then pull or upload your existing LLM traces onto the platform as telemetry.
  • Connect your inference provider keys (BYOK): create an account, then connect your own OpenAI, Anthropic, Gemini, Azure, Bedrock, Fireworks, or OpenRouter keys for free pass-through.
  • Start calling models on the gateway: make your first /v1 call with the OpenAI and Anthropic SDKs using an xpl_ key, and optionally repoint your existing coding agents.
  • Full onboarding: create an account instantly from your email, connect your keys, import your spend, then repoint every coding agent (Claude Code, Cursor, Codex, Aider, and similar) or Conductor at the gateway.

Using the API

Start the local gateway with exp (or exp run); the compiled native data plane serves every route on loopback. From Python, load a fitted project router as an official OpenAI client backed by its own private gateway:

import exp

with exp.load_router("my-project") as client:
    response = client.chat.completions.create(
        model="my-project",
        messages=[{"role": "user", "content": "hello"}],
    )

Capture Traffic

Capture is designed to collect supported traces from the Codex and Claude Code desktop apps using your existing ChatGPT or Claude subscription, while requests go directly to OpenAI or Anthropic. It requires macOS, Python 3.13 or newer, and approval for its extension and certificate:

exp capture

Capture is experimental; macOS network reliability is still under investigation.

Use Experiential's gateway as middleware to control costs, enforce guardrails, and optimize quality, costs, and speed. Leave the terminal open while you work. Press Ctrl+C to stop capture. View your capture telemetry.

Optimize from Traffic

First, collect OpenTelemetry traces from your current agent. If you just want to try it out, grab the public terminal-tasks OTLP dataset:

curl -L -o traces.otel.jsonl \
  https://huggingface.co/datasets/experiential-labs/wmo-terminal-tasks-traces/resolve/540883e451dc13d34fb50fdd36b143cb0f1fb0db/traces.otel.jsonl

Then build a project. The build command walks you through providers, models, and budget, and asks for your trace file:

# Build simulation from your agent traces and optimize a router against it
exp build support-agent

After collecting traces from your router, fine-tune an open source model you own using Tinker.

exp optimize model support-agent

Telemetry

Anonymous aggregate PostHog product telemetry is enabled by default. It never includes prompts, traces, actions, observations, paths, model names, credentials, or raw customer content.

exp config telemetry status
exp config telemetry disable
exp config telemetry enable

The preference is stored locally in .exp/settings.toml.

Development

uv sync --extra dev
uv run ruff format --check .
uv run ruff check .
uv run ty check
uv run pytest -q

Repository and documentation conventions live in AGENTS.md.

Metadata

Release files for experiential 0.7.194

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for experiential 0.7.194
File Size Uploaded Provenance
experiential-0.7.194.tar.gz 6.5 MB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for experiential 0.7.194
File Interpreter ABI Platform
experiential-0.7.194-py3-none-any.whl Python 3 none any Details

Total release size: 11.3 MB

Release files / experiential-0.7.194.tar.gz

Download URL experiential-0.7.194.tar.gz
Size 6.5 MB
Tags Source
SHA-256 checksum
How to use checksums
4b6cec3e99b476541e08f553410a54321817047797a26fa4f1ade0ee1d993a80
BLAKE2b-256 checksum
How to use checksums
e14eef95ac5574f1ecb38a50592f578822e61653ed0302949245fe157847171f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.12.18 {"installer":{"name":"uv","version":"0.12.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"13","id":"trixie","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release files / experiential-0.7.194-py3-none-any.whl

Download URL experiential-0.7.194-py3-none-any.whl
Size 4.8 MB
Tags Python 3
SHA-256 checksum
How to use checksums
f97a71b3e40f56d6000705feabd40a9a915f0a272395b7fc6d0262d2eb473608
BLAKE2b-256 checksum
How to use checksums
5165b583751a8795180c26ddec7332999ebf4f1693bf8fdb3b73ef2d081ccc79
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.12.18 {"installer":{"name":"uv","version":"0.12.18","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Debian GNU/Linux","version":"13","id":"trixie","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Security for experiential 0.7.194

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.

Release history Release notifications | RSS feed

This release

0.7.194 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page