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docs(billing.md): improve proxy billing tutorial

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Krrish Dholakia 2024-05-16 15:27:23 -07:00
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docs/my-website/docs/proxy/billing.md
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@ -2,19 +2,40 @@ import Image from '@theme/IdealImage';
import Tabs from '@theme/Tabs'; import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem'; import TabItem from '@theme/TabItem';
# 💰 Billing # 💵 Billing
Bill users for their usage. Bill users for their usage.
Requirements: **🚨 Requirements**
- Setup a billing plan on Lago, for usage-based billing. We recommend following their Stripe tutorial - https://docs.getlago.com/templates/per-transaction/stripe#step-1-create-billable-metrics-for-transaction - [Setup Lago](https://docs.getlago.com/guide/self-hosted/docker#run-the-app), for usage-based billing. We recommend following [their Stripe tutorial](https://docs.getlago.com/templates/per-transaction/stripe#step-1-create-billable-metrics-for-transaction)
Steps: Steps:
- Connect the proxy to Lago - Connect the proxy to Lago
- Set the id you want to bill for (customers, internal users, teams) - Set the id you want to bill for (customers, internal users, teams)
- Start! - Start!
## 1. Connect proxy to Lago ## Quick Start
Bill internal users for their usage
### 1. Connect proxy to Lago
Set 'lago' as a callback on your proxy config.yaml
```yaml
model_name:
- model_name: fake-openai-endpoint
litellm_params:
model: openai/fake
api_key: fake-key
api_base: https://exampleopenaiendpoint-production.up.railway.app/
litellm_settings:
callbacks: ["lago"] # 👈 KEY CHANGE
general_settings:
master_key: sk-1234
```
Add your Lago keys to the environment Add your Lago keys to the environment
@ -22,34 +43,157 @@ Add your Lago keys to the environment
export LAGO_API_BASE="http://localhost:3000" # self-host - https://docs.getlago.com/guide/self-hosted/docker#run-the-app export LAGO_API_BASE="http://localhost:3000" # self-host - https://docs.getlago.com/guide/self-hosted/docker#run-the-app
export LAGO_API_KEY="3e29d607-de54-49aa-a019-ecf585729070" # Get key - https://docs.getlago.com/guide/self-hosted/docker#find-your-api-key export LAGO_API_KEY="3e29d607-de54-49aa-a019-ecf585729070" # Get key - https://docs.getlago.com/guide/self-hosted/docker#find-your-api-key
export LAGO_API_EVENT_CODE="openai_tokens" # name of lago billing code export LAGO_API_EVENT_CODE="openai_tokens" # name of lago billing code
export LAGO_API_CHARGE_BY="user_id" # 👈 Charges 'user_id' attached to proxy key
``` ```
Set 'lago' as a callback on your proxy config.yaml Start proxy
```yaml ```bash
... litellm --config /path/to/config.yaml
litellm_settings:
callbacks: ["lago"]
``` ```
## 2. Set the id you want to bill for ### 2. Create Key for Internal User
```bash
curl 'http://0.0.0.0:4000/key/generate' \
--header 'Authorization: Bearer sk-1234' \
--header 'Content-Type: application/json' \
--data-raw '{"user_id": "my-unique-id"}' # 👈 Internal User's ID
```
Response Object:
```bash
{
"key": "sk-tXL0wt5-lOOVK9sfY2UacA",
}
```
### 3. Start billing!
<Tabs>
<TabItem value="curl" label="Curl">
```bash
curl --location 'http://0.0.0.0:4000/chat/completions' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer sk-tXL0wt5-lOOVK9sfY2UacA' \ # 👈 User's Key
--data ' {
"model": "fake-openai-endpoint",
"messages": [
{
"role": "user",
"content": "what llm are you"
}
],
}
'
```
</TabItem>
<TabItem value="openai_python" label="OpenAI Python SDK">
```python
import openai
client = openai.OpenAI(
api_key="sk-tXL0wt5-lOOVK9sfY2UacA", # 👈 User's Key
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-3.5-turbo", messages = [
{
"role": "user",
"content": "this is a test request, write a short poem"
}
])
print(response)
```
</TabItem>
<TabItem value="langchain" label="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"] = "sk-tXL0wt5-lOOVK9sfY2UacA" # 👈 User's Key
chat = ChatOpenAI(
openai_api_base="http://0.0.0.0:4000",
model = "gpt-3.5-turbo",
temperature=0.1,
)
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)
```
</TabItem>
</Tabs>
**See Results on Lago**
<Image img={require('../../img/lago_2.png')} style={{ width: '500px', height: 'auto' }} />
## Advanced - Lago Logging object
This is what LiteLLM will log to Lagos
```
{
"event": {
"transaction_id": "<generated_unique_id>",
"external_customer_id": <selected_id>, # either 'end_user_id', 'user_id', or 'team_id'. Default 'end_user_id'.
"code": os.getenv("LAGO_API_EVENT_CODE"),
"properties": {
"input_tokens": <number>,
"output_tokens": <number>,
"model": <string>,
"response_cost": <number>, # 👈 LITELLM CALCULATED RESPONSE COST - https://github.com/BerriAI/litellm/blob/d43f75150a65f91f60dc2c0c9462ce3ffc713c1f/litellm/utils.py#L1473
}
}
}
```
## Advanced - Bill Customers, Internal Teams
For: For:
- Customers (id passed via 'user' param in /chat/completion call) = 'end_user_id' - Customers (id passed via 'user' param in /chat/completion call) = 'end_user_id'
- Internal Users (id set when [creating keys](https://docs.litellm.ai/docs/proxy/virtual_keys#advanced---spend-tracking)) = 'user_id' - Internal Users (id set when [creating keys](https://docs.litellm.ai/docs/proxy/virtual_keys#advanced---spend-tracking)) = 'user_id'
- Teams (id set when [creating keys](https://docs.litellm.ai/docs/proxy/virtual_keys#advanced---spend-tracking)) = 'team_id' - Teams (id set when [creating keys](https://docs.litellm.ai/docs/proxy/virtual_keys#advanced---spend-tracking)) = 'team_id'
```yaml
export LAGO_API_CHARGE_BY="end_user_id" # 👈 Charge 'Customers'. Default is 'end_user_id'.
```
## 3. Start billing!
<Tabs> <Tabs>
<TabItem value="customers" label="Customer Billing"> <TabItem value="customers" label="Customer Billing">
### **Curl** 1. Set 'LAGO_API_CHARGE_BY' to 'end_user_id'
```bash
export LAGO_API_CHARGE_BY="end_user_id"
```
2. Test it!
<Tabs>
<TabItem value="curl" label="Curl">
```shell ```shell
curl --location 'http://0.0.0.0:4000/chat/completions' \ curl --location 'http://0.0.0.0:4000/chat/completions' \
--header 'Content-Type: application/json' \ --header 'Content-Type: application/json' \
@ -65,8 +209,8 @@ curl --location 'http://0.0.0.0:4000/chat/completions' \
} }
' '
``` ```
</TabItem>
### **OpenAI Python SDK** <TabItem value="openai_sdk" label="OpenAI Python SDK">
```python ```python
import openai import openai
@ -86,7 +230,8 @@ response = client.chat.completions.create(model="gpt-3.5-turbo", messages = [
print(response) print(response)
``` ```
### **Langchain** </TabItem>
<TabItem value="langchain" label="Langchain">
```python ```python
from langchain.chat_models import ChatOpenAI from langchain.chat_models import ChatOpenAI
@ -121,50 +266,20 @@ response = chat(messages)
print(response) print(response)
``` ```
</TabItem> </TabItem>
<TabItem value="internal_user" label="Internal User (Key Owner) Billing"> </Tabs>
1. Create a key for that user
```bash
curl 'http://0.0.0.0:4000/key/generate' \
--header 'Authorization: Bearer <your-master-key>' \
--header 'Content-Type: application/json' \
--data-raw '{"user_id": "my-unique-id"}'
```
Response Object:
```bash
{
"key": "sk-tXL0wt5-lOOVK9sfY2UacA",
}
```
2. Make API Calls with that Key
```python
import openai
client = openai.OpenAI(
api_key="sk-tXL0wt5-lOOVK9sfY2UacA", # 👈 Generated key
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-3.5-turbo", messages = [
{
"role": "user",
"content": "this is a test request, write a short poem"
}
])
print(response)
```
</TabItem> </TabItem>
<TabItem value="teams" label="Team Billing"> <TabItem value="teams" label="Team Billing">
1. Create a key for that team 1. Set 'LAGO_API_CHARGE_BY' to 'team_id'
```bash
export LAGO_API_CHARGE_BY="team_id"
```
2. Create a key for that team
```bash ```bash
curl 'http://0.0.0.0:4000/key/generate' \ curl 'http://0.0.0.0:4000/key/generate' \
@ -181,7 +296,7 @@ Response Object:
} }
``` ```
2. Make API Calls with that Key 3. Make API Calls with that Key
```python ```python
import openai import openai
@ -202,28 +317,3 @@ print(response)
``` ```
</TabItem> </TabItem>
</Tabs> </Tabs>
**See Results on Lago**
<Image img={require('../../img/lago_2.png')} style={{ width: '500px', height: 'auto' }} />
## Advanced - Lago Logging object
This is what LiteLLM will log to Lagos
```
{
"event": {
"transaction_id": "<generated_unique_id>",
"external_customer_id": <selected_id>, # either 'end_user_id', 'user_id', or 'team_id'. Default 'end_user_id'.
"code": os.getenv("LAGO_API_EVENT_CODE"),
"properties": {
"input_tokens": <number>,
"output_tokens": <number>,
"model": <string>,
"response_cost": <number>, # 👈 LITELLM CALCULATED RESPONSE COST - https://github.com/BerriAI/litellm/blob/d43f75150a65f91f60dc2c0c9462ce3ffc713c1f/litellm/utils.py#L1473
}
}
}
```