- Teams operating production LLM and agent applications
- Developers who want OpenTelemetry-native AI observability
- Builders comparing evaluation and guardrail platforms
Apache-2.0 ยท Tools
OpenLIT
OpenTelemetry-native open-source AI engineering platform for LLM observability, evaluations, guardrails, prompts, and GPU monitoring.
2.5K stars 0.3K forks Apache-2.0 license 2026-06-10 verified
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# OpenLIT$
pip install openlit$
npx openlit --help Open source
Overview
What is OpenLIT?
OpenLIT is an open-source AI engineering platform for observability, evaluations, guardrails, prompt management, vault workflows, playgrounds, and GPU monitoring. It integrates with many LLM providers, vector databases, and agent frameworks.
OpenTelemetry-native observability
OpenLIT focuses on AI observability through OpenTelemetry-native tracing and monitoring.
Teams can connect agent behavior to existing observability systems instead of creating isolated AI dashboards.Evaluation and guardrails
The platform includes evaluations and guardrail workflows.
Operational visibility is stronger when paired with repeatable quality and safety checks.Broad integration surface
OpenLIT describes integrations across LLM providers, vector databases, agent frameworks, and GPUs.
Agent stacks are heterogeneous, so observability tools need broad coverage. Use cases
What teams use it for
Ecosystem
Tags & capabilities
Comparison
How it stacks up
When to choose OpenLIT
Compare it with nearby tools by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need.
FAQ
Questions
Is OpenLIT open source?
Yes. The GitHub repository is listed under the Apache-2.0 license.
How does OpenLIT fit with MLflow or Langfuse?
OpenLIT is especially interesting for teams that want OpenTelemetry-native observability and operational monitoring around LLM and agent systems.
Decision brief
JSON
Should you use OpenLIT?
- Solo prototypes that only need a small prompt test file
- Teams looking for a low-level agent framework
- Verified 2026-06-10
- License: Apache-2.0
- Repo: openlit/openlit
- Open-source signal
Deployment
self hosted, cloud
Permission surface
Low explicit permission surface in metadata
Decision signals
No extra signals recorded
Agent packet
Structured decision data for OpenLIT
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
automation, workflow
Constraints
open source
Deployment
self hosted, cloud
Permission surface
Low explicit permission surface in metadata
Recommended workflows
Browser automation, Evaluation and observability, Reusable skill workflow
Overview
What OpenLIT does
What it is
It is a tool layer around LLM and agent applications, not an agent framework.
Why it matters
Teams need to see what agents are doing in production and catch regressions before users do.
How to evaluate it
Start by instrumenting one agent workflow, then add evaluation and guardrail checks around the highest-risk steps.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type tool
Category Tools
Maturity active
Difficulty Unknown
License Apache-2.0
Pricing open source
Verified 2026-06-10
Source confidence high
Risk level low
Fit matrix
Where OpenLIT fits in an agent stack
strong
Browser automation
OpenLIT has multiple signals for browser automation, including matching tags, capabilities, category, or positioning.
- Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong
Evaluation and observability
OpenLIT has multiple signals for evaluation and observability, including matching tags, capabilities, category, or positioning.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong
Reusable skill workflow
OpenLIT has multiple signals for reusable skill workflow, including matching tags, capabilities, category, or positioning.
- Run one skill end to end and check whether it produces evidence or structured output.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Coding agent workflow
OpenLIT has at least one signal for coding agent workflow, but should be checked against a real task before adoption.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Local or private AI stack
OpenLIT has at least one signal for local or private ai stack, but should be checked against a real task before adoption.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Connector or protocol layer
OpenLIT is not primarily positioned for connector or protocol layer in the current metadata.
- Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Repositories, files, issues, terminal output, and test results
- Official setup instructions and a small real workflow
Likely outputs
- Diffs, commits, explanations, test results, or review notes
- Scores, traces, regression results, dashboards, or failure cases
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
GitHub github
Repository source for code, license, issues, releases, and implementation details.
Homepage homepageOfficial or project-controlled source for this resource profile.
OpenLIT is listed as open source.
License metadata: Apache-2.0OpenLIT has a recorded GitHub repository: openlit/openlit.
Resource facts and GitHub source link.OpenLIT supports these recorded deployment modes: self hosted, cloud.
OpenAgent decision signal metadata.OpenLIT is tagged with automation, workflow capabilities.
OpenAgent capability taxonomy.- Dedicated docs link is missing.
- Repository freshness has not been recorded.
Next action
How to start evaluating OpenLIT
Inspect repository
Check license, recent activity, issues, examples, and security-sensitive code paths.
Open sourceOpen Homepage
Start from the official source before adopting third-party instructions.
Open source Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about OpenLIT
Is OpenLIT open source?
Yes. The GitHub repository is listed under the Apache-2.0 license.
How does OpenLIT fit with MLflow or Langfuse?
OpenLIT is especially interesting for teams that want OpenTelemetry-native observability and operational monitoring around LLM and agent systems.