> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pylva.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Supported Integrations

> See which Pylva integrations are automatic, callback-based, or manual.

Pylva supports TypeScript and Python agent runtimes.

TypeScript auto-instruments OpenAI, Anthropic, and Vercel AI. Python auto-instruments OpenAI and Anthropic. LangGraph and LangChain use the callback path. Custom tools, non-LLM usage, and unsupported provider paths use `reportUsage` or `report_usage`.

## Integration matrix

| Stack                     | Package or entrypoint                                | Capture path             |
| ------------------------- | ---------------------------------------------------- | ------------------------ |
| TypeScript OpenAI         | `@pylva/sdk`                                         | Auto-instrumentation     |
| TypeScript Anthropic      | `@pylva/sdk`                                         | Auto-instrumentation     |
| TypeScript Vercel AI      | `@pylva/sdk`                                         | Auto-instrumentation     |
| Python OpenAI             | `pylva-sdk`, import `pylva`                          | Auto-instrumentation     |
| Python Anthropic          | `pylva-sdk`, import `pylva`                          | Auto-instrumentation     |
| LangGraph or LangChain    | `PylvaCallbackHandler`                               | Callback instrumentation |
| Non-LLM tools             | `reportUsage` or `report_usage`                      | Manual usage reporting   |
| Unsupported provider path | `reportUsage`, `report_usage`, or custom integration | Manual usage reporting   |

## What Pylva captures

Pylva captures cost-shaped metadata:

* Provider and model.
* Token counts when the provider or framework exposes them.
* Latency and status.
* `customer_id` and `step_name`.
* Metric and metric value for non-LLM usage.

Pylva does not need prompts, completions, raw messages, tool inputs, tool outputs, emails, API keys, or raw tool arguments.

## Which path should I use?

Use auto-instrumentation when your runtime calls a supported provider client directly.

Use the callback path when LangGraph or LangChain owns the model call.

Use `reportUsage` or `report_usage` when the cost comes from a custom tool, non-LLM service, or unsupported provider path.

## Avoid double counting

Use one capture path for the same model call.

* Do not use provider auto-instrumentation and a framework callback for the same call.
* Do not manually report a provider call that the SDK already captures.
* Manually report only usage that is not already captured.

If you are not sure whether a source is covered, see [Cost Source Discovery](cost-source-discovery).