LlamaIndex
For optional help from your coding agent, use Set it up for me. It preserves your model connection and verifies a real trace after setup
Send LlamaIndex traces to LiteLLM Lens using the runnable examples in this repository.
Prerequisites
You need Lens installed alongside LiteLLM, a key with model access, and a configured model alias. The swarm example needs a model that supports tool calls. In Lens > Traces > Set up tracing, click Generate tracing key and copy the Traces endpoint under Connection details. Ask your administrator for these if you cannot create a tracing key.
Install uv. It uses the checked-in Python version and resolves each example’s dependencies from its uv workspace.
Configuration
For a fresh checkout:
git clone https://github.com/BerriAI/litellm-lens-example.git
cd litellm-lens-example/llamaindex
cp .env.example .env
If you already cloned the repository, run the remaining commands from llamaindex/. Copy .env.example to .env if it does not exist, then set:
| Variable | Value |
|---|---|
LITELLM_GATEWAY_URL | Your gateway’s base URL without a trailing slash or /v1, for example http://localhost:4002 |
LITELLM_API_KEY | Your LiteLLM model key |
LENS_URL | Copy Traces endpoint from Lens tracing setup and remove the final /v1/traces. Keep /lens-ingest if present. For example, http://localhost:4318 or https://gateway.example/lens-ingest |
LENS_TRACING_KEY | The dedicated tracing key from Lens tracing setup |
LITELLM_MODEL | A model alias configured on your gateway |
The checked-in values target a local development gateway. Replace them for your deployment. Keep the exporter settings from .env.example; the examples configure their trace exporters in code. They send traces to LENS_URL/v1/traces with the tracing key as a bearer token.
Leave MOCK_LITELLM_GATEWAY_URL unset unless you intend to send an additional trace copy to the local recorder.
Run an example
Simple agent
A FunctionAgent answers one question.
uv run --env-file .env --package lens-llamaindex-simple simple/main.py
See simple/main.py for the implementation.
Agent swarm
An AgentWorkflow hands off from research_agent to search_agent, then writer_agent.
uv run --env-file .env --package lens-llamaindex-swarm swarm/main.py
See swarm/main.py for the implementation.
Verify the trace
After the example prints its answer, open Lens > Traces on your gateway and select the new run. Look for the run associated with research_agent. Inspect the input, output, and model spans. For the swarm, inspect the specialist activity described above; its exact span layout depends on the framework.
How tracing works
The LlamaIndex instrumentor is enabled before importing the framework. The examples label the process as research_agent and disable framework streaming; specialist names appear in workflow and handoff data.
Troubleshooting
If model calls fail, check the gateway URL, key, and model alias. If an answer appears but the trace is missing, check the terminal for exporter errors and confirm the Lens ingestion service is reachable with your tracing key. A model call succeeding does not confirm that its trace export succeeded.
Multiple model-related spans can represent one model call. Specialist names and model-call spend depend on the attributes exported by the framework and how the gateway normalizes them.
