---
title: "Lago"
url: "/docs/observability/lago"
canonical_url: "https://docs.litellm.ai/docs/observability/lago"
type: "docs"
last_updated: "2026-10-10"
summary: "Lago offers a self-hosted and cloud, metering and usage-based billing solution."
related:
  - "/docs/observability/greenscale_integration"
  - "/docs/observability/mavvrik"
---
# Lago

> Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt


[Lago](https://www.getlago.com/) offers a self-hosted and cloud, metering and usage-based billing solution.

## Quick Start
Use just 1 lines of code, to instantly log your responses **across all providers** with Lago

Get your Lago [API Key](https://docs.getlago.com/guide/self-hosted/docker#find-your-api-key)

```python
litellm.callbacks = ["lago"] # logs cost + usage of successful calls to lago
```

**SDK**

```python
# uv add lago 
import litellm
import os

os.environ["LAGO_API_BASE"] = "" # http://0.0.0.0:3000
os.environ["LAGO_API_KEY"] = ""
os.environ["LAGO_API_EVENT_CODE"] = "" # The billable metric's code - https://docs.getlago.com/guide/events/ingesting-usage#define-a-billable-metric
os.environ["LAGO_API_CHARGE_BY"] = "user_id" # the default, end_user_id, is only populated for proxy requests

# LLM API Keys
os.environ['OPENAI_API_KEY']=""

# set lago as a callback, litellm will send the data to lago
litellm.success_callback = ["lago"] 
 
# openai call
response = litellm.completion(
  model="gpt-5.6-luna",
  messages=[
    {"role": "user", "content": "Hi 👋 - i'm openai"}
  ],
  metadata={"user_api_key_user_id": "your_customer_id"} # 👈 SET YOUR CUSTOMER ID HERE
)
```

**PROXY**

1. Add to Config.yaml
```yaml
model_list:
- litellm_params:
    api_base: https://openai-function-calling-workers.tasslexyz.workers.dev/
    api_key: my-fake-key
    model: openai/my-fake-model
  model_name: fake-openai-endpoint

litellm_settings:
  callbacks: ["lago"] # 👈 KEY CHANGE
```

2. Start Proxy

```
litellm --config /path/to/config.yaml
```

3. Test it! 

**Curl**

```bash
curl --location 'http://0.0.0.0:4000/chat/completions' \
--header 'Content-Type: application/json' \
--data ' {
      "model": "fake-openai-endpoint",
      "messages": [
        {
          "role": "user",
          "content": "what llm are you"
        }
      ],
      "user": "your-customer-id" # 👈 SET YOUR CUSTOMER ID
    }
'
```
**OpenAI Python SDK**

```python
import openai
client = openai.OpenAI(
    api_key="anything",
    base_url="http://0.0.0.0:4000"
)

# request sent to model set on litellm proxy, `litellm --model`
response = client.chat.completions.create(model="gpt-5.6-luna", messages = [
    {
        "role": "user",
        "content": "this is a test request, write a short poem"
    }
], user="my_customer_id") # 👈 whatever your customer id is

print(response)
```
**Langchain**

```python
from langchain.chat_models import ChatOpenAI
from langchain.prompts.chat import (
    ChatPromptTemplate,
    HumanMessagePromptTemplate,
    SystemMessagePromptTemplate,
)
from langchain.schema import HumanMessage, SystemMessage
import os 

os.environ["OPENAI_API_KEY"] = "anything"

chat = ChatOpenAI(
    openai_api_base="http://0.0.0.0:4000",
    model = "gpt-5.6-luna",
    temperature=0.1,
    extra_body={
        "user": "my_customer_id"  # 👈 whatever your customer id is
    }
)

messages = [
    SystemMessage(
        content="You are a helpful assistant that im using to make a test request to."
    ),
    HumanMessage(
        content="test from litellm. tell me why it's amazing in 1 sentence"
    ),
]
response = chat(messages)

print(response)
```

## Advanced - Lagos Logging object 

This is what LiteLLM will log to Lagos

```
{
    "event": {
      "transaction_id": "<generated_unique_id>",
      "external_subscription_id": <customer_id>, # selected by LAGO_API_CHARGE_BY
      "code": os.getenv("LAGO_API_EVENT_CODE"), 
      "properties": {
          "model": <string>,
          "response_cost": <number>, # 👈 LITELLM CALCULATED RESPONSE COST - https://github.com/BerriAI/litellm/blob/d43f75150a65f91f60dc2c0c9462ce3ffc713c1f/litellm/utils.py#L1473
          "prompt_tokens": <number>,
          "completion_tokens": <number>,
          "total_tokens": <number>
      }
    }
}
```

`LAGO_API_CHARGE_BY` picks the value sent as `external_subscription_id`. `end_user_id` (default) uses the `user` param of a proxy request, `user_id` uses the virtual key's `user_id` and `team_id` uses the virtual key's `team_id`. If the selected value is missing, nothing is sent to Lago. In the SDK there is no proxy request, so set `LAGO_API_CHARGE_BY=user_id` and pass the customer id as `metadata={"user_api_key_user_id": ...}`

## Related pages

- [Greenscale](https://docs.litellm.ai/docs/observability/greenscale_integration.md)
- [Mavvrik](https://docs.litellm.ai/docs/observability/mavvrik.md)