KI-Agenten
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Open-source LLM observability: trace, evaluate and monitor apps and agents
★ 22,5 Tsd. SterneApache-2.0
Anleitung ansehen →future-agi ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von future-agi (future-agi/future-agi auf GitHub). Es hat 2.127 Sterne auf GitHub und 671 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 8. Oktober 2026 auf GitHub aktualisiert.
One open platform to simulate, evaluate, guardrail, trace, and optimise LLM and agent apps, self-hostable.
Decide whether to self-host (standalone on a laptop or VM, distributed, or Kubernetes) or start with the hosted cloud trial.
Clone the repository and run the installer, which checks your machine, writes local secrets, and downloads the platform images.
Sign in locally, create an account, and copy your API key and secret key from the Keys page.
Instrument your agent with the OpenTelemetry package, send your first trace, then add evaluations, simulations, and guardrails.
OpenTelemetry-native tracing across many agent frameworks, with span graphs, latency, and token-cost dashboards.
Dozens of metrics under one evaluate call, covering areas such as groundedness, hallucination, tool-use correctness, and tone, using LLM-as-judge, heuristic, and ML methods.
Multi-turn conversation simulation against personas, adversarial inputs, and edge cases, for both text and voice agents.
Built-in scanners for issues such as PII and prompt injection, plus adapters for external guardrail vendors, usable inline in the gateway or as an SDK.
An OpenAI-compatible gateway with routing across many providers, semantic caching, and virtual keys.
Several prompt-optimisation algorithms that learn from production traces, closing the loop from monitoring to improvement.
Requires Docker with Compose; the installer prepares secrets and images.
git clone https://github.com/future-agi/future-agi.git
cd future-agi
./bin/installOpen the local app, create your account, and copy the API and secret keys from the Keys page in the sidebar.
# open the installed web app locally and copy FI_API_KEY / FI_SECRET_KEY from KeysInstall the instrumentation package, export your keys, and emit a span from Python.
pip install fi-instrumentation-otel
export FI_API_KEY=<your key>It is maintained by future-agi on GitHub, alongside a commercial cloud offering.
The platform core is Apache-2.0 licensed and free to self-host; the company also offers a managed cloud and enterprise editions.
Not for the platform itself, but evaluations and optimisation call LLMs, so you configure your own provider keys for those features.
Tools such as Langfuse or Phoenix focus mainly on tracing and evals; Future AGI bundles simulation, guardrails, a gateway, and prompt optimisation into the same platform, per its own comparison.
Clone the repo, run ./bin/install, sign in locally, copy your keys, and pip install fi-instrumentation-otel to send a first trace.
Open-source LLM observability: trace, evaluate and monitor apps and agents
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