Model request tags documentation (#20290)

* Add request tags documentation for spend tracking

- Add new concise doc explaining how to tag model requests
- Include Python SDK and cURL examples
- Show where tags appear in spend logs
- Add common use cases table (AWS accounts, teams, projects)
- Include how to set default tags on API keys
- Add to Spend Tracking section in sidebar

Co-authored-by: ishaan <ishaan@berri.ai>

* Simplify request tags doc for AI Gateway usage

- Focus on config.yaml setup with default_key_generate_params
- Show both request body and header methods for sending tags
- Remove SDK examples, keep concise cURL examples
- Streamline for quick reference

Co-authored-by: ishaan <ishaan@berri.ai>

* Update request tags doc to show model-level config

- Set tags directly on model deployments in litellm_params
- Requests just specify model, tags applied automatically
- Use clear naming: AWS_IAM_PROD, AWS_IAM_DEV

Co-authored-by: ishaan <ishaan@berri.ai>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: ishaan <ishaan@berri.ai>
This commit is contained in:
Ishaan Jaff
2026-02-02 11:32:00 -08:00
committed by GitHub
co-authored by Cursor Agent ishaan
parent 0a1b98895b
commit 73691fb373
2 changed files with 59 additions and 0 deletions
@@ -0,0 +1,58 @@
# Request Tags for Spend Tracking
Add tags to model deployments to track spend by environment, AWS account, or any custom label.
Tags appear in the `request_tags` field of LiteLLM spend logs.
## Config Setup
Set tags on model deployments in `config.yaml`:
```yaml title="config.yaml"
model_list:
- model_name: gpt-4
litellm_params:
model: azure/gpt-4-prod
api_key: os.environ/AZURE_PROD_API_KEY
api_base: https://prod.openai.azure.com/
tags: ["AWS_IAM_PROD"] # 👈 Tag for production
- model_name: gpt-4-dev
litellm_params:
model: azure/gpt-4-dev
api_key: os.environ/AZURE_DEV_API_KEY
api_base: https://dev.openai.azure.com/
tags: ["AWS_IAM_DEV"] # 👈 Tag for development
```
## Make Request
Requests just specify the model - tags are automatically applied:
```bash
curl -X POST 'http://0.0.0.0:4000/chat/completions' \
-H 'Authorization: Bearer sk-1234' \
-H 'Content-Type: application/json' \
-d '{
"model": "gpt-4",
"messages": [{"role": "user", "content": "Hello"}]
}'
```
## Spend Logs
The tag from the model config appears in `LiteLLM_SpendLogs`:
```json
{
"request_id": "chatcmpl-abc123",
"request_tags": ["AWS_IAM_PROD"],
"spend": 0.002,
"model": "gpt-4"
}
```
## Related
- [Spend Tracking Overview](cost_tracking.md)
- [Tag Budgets](tag_budgets.md) - Set budget limits per tag
+1
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@@ -442,6 +442,7 @@ const sidebars = {
label: "Spend Tracking",
items: [
"proxy/cost_tracking",
"proxy/request_tags",
"proxy/custom_pricing",
"proxy/pricing_calculator",
"proxy/provider_margins",