plano/demos/use_cases/llm_routing
Salman Paracha 8d0b468345
draft commit to add support for xAI, TogehterAI, AzureOpenAI (#570)
* draft commit to add support for xAI, LambdaAI, TogehterAI, AzureOpenAI

* fixing failing tests and updating rederend config file

* Update arch_config_with_aliases.yaml

* adding the AZURE_API_KEY to the GH workflow for e2e

* fixing GH secerts

* adding valdiating for azure_openai

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Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-167.local>
2025-09-18 18:36:30 -07:00
..
arch_config.yaml draft commit to add support for xAI, TogehterAI, AzureOpenAI (#570) 2025-09-18 18:36:30 -07:00
docker-compose.yaml add support for openwebui (#487) 2025-05-28 19:08:00 -07:00
jaeger_tracing_llm_routing.png refactor demos (#398) 2025-02-07 18:45:42 -08:00
llm_routing_demo.png refactor demos (#398) 2025-02-07 18:45:42 -08:00
README.md better model names (#517) 2025-07-11 16:42:16 -07:00
run_demo.sh refactor demos (#398) 2025-02-07 18:45:42 -08:00

LLM Routing

This demo shows how you can arch gateway to manage keys and route to upstream LLM.

Starting the demo

  1. Please make sure the pre-requisites are installed correctly
  2. Start Arch
    sh run_demo.sh
    
  3. Navigate to http://localhost:18080/

Following screen shows an example of interaction with arch gateway showing dynamic routing. You can select between different LLMs using "override model" option in the chat UI.

LLM Routing Demo

You can also pass in a header to override model when sending prompt. Following example shows how you can use x-arch-llm-provider-hint header to override model selection,


$ curl --header 'Content-Type: application/json' \
  --header 'x-arch-llm-provider-hint: mistral/ministral-3b' \
  --data '{"messages": [{"role": "user","content": "hello"}], "model": "none"}' \
  http://localhost:12000/v1/chat/completions 2> /dev/null | jq .
{
  "id": "xxx",
  "object": "chat.completion",
  "created": 1737760394,
  "model": "ministral-3b-latest",
  "choices": [
    {
      "index": 0,
      "messages": {
        "role": "assistant",
        "tool_calls": null,
        "content": "Hello! How can I assist you today? Let's chat about anything you'd like. 😊"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 4,
    "total_tokens": 25,
    "completion_tokens": 21
  }
}

Observability

Arch gateway publishes stats endpoint at http://localhost:19901/stats. In this demo we are using prometheus to pull stats from arch and we are using grafana to visualize the stats in dashboard. To see grafana dashboard follow instructions below,

  1. Navigate to http://localhost:3000/ to open grafana UI (use admin/grafana as credentials)
  2. From grafana left nav click on dashboards and select "Intelligent Gateway Overview" to view arch gateway stats
  3. For tracing you can head over to http://localhost:16686/ to view recent traces.

Following is a screenshot of tracing UI showing call received by arch gateway and making upstream call to LLM,

Jaeger Tracing