owi-litellm-tool/ARCHITECTURE.md

LiteLLM Dashboard Tool — Architecture & Design

Created: 2026-06-04 Authors: Kagamine Rin (Chief Engineer) & Ryan Neef (General / Co-Processor)

Product Definition

A single Open WebUI Tool that provides LiteLLM proxy health status and cost breakdown. Designed for the Network but built for general use — any LiteLLM proxy instance.

OWI Integration Model

Type: Open WebUI Tool (not a Pipeline, not a Filter)

How it works:

1. Tool is added to the OWI Workspace
2. Tool is activated on a per-model or per-chat basis
3. Valves pass the LiteLLM proxy address and master key
4. No hardcoded connection details — the tool is portable

Why a Tool, not a Pipeline/Filter:

• Pipelines run on every request (wrong scope — this is on-demand, not per-request)
• Filters modify request/response flow (wrong scope — this is informational)
• Tools are invoked when needed, by the model, in context. This is the right pattern for "check cost" and "check health" — you ask, it answers.

Valve Configuration

The tool needs two valves:

Valve	Type	Purpose	Default
litellm_url	string	LiteLLM proxy base URL (e.g., http://localhost:4000)	http://localhost:4000
litellm_master_key	string	LiteLLM master API key for auth	(empty — must be configured)

Security consideration: The master key will be stored in the OWI valve configuration. This is the same security model as other API keys in OWI (LiteLLM proxy key, etc.). The key is not exposed in chat context — OWI valves are injected at tool execution time, not displayed to the user.

Docker networking note: If OWI runs inside Docker (typical), the litellm_url valve must use host.docker.internal:4000 instead of localhost:4000 to reach the LiteLLM proxy on the host.

Function 1: Health Check

LiteLLM Endpoint: GET {litellm_url}/health Auth: Authorization: Bearer {litellm_master_key}

Response Processing

The /health endpoint returns healthy_endpoints and unhealthy_endpoints arrays. Each endpoint object contains a massive litellm_metadata blob (~2KB per model) with full auth context. This is stripped for token efficiency.

Stripped Fields

These fields are removed from the /health response because they bloat output without providing useful information:

• litellm_metadata — ~2KB of auth/internal context per model
• safety_settings — internal safety filter config
• cache_control_injection_points — internal routing detail
• use_in_pass_through, use_litellm_proxy, merge_reasoning_content_in_choices — internal flags

Retained Fields

• model — the LiteLLM model identifier
• rpm — rate limit
• timeout — request timeout in seconds
• reasoning_effort — if present and not "none" (e.g., "low")
• service_tier — if present (e.g., "flex")

Output Format

LiteLLM Health Check — http://host.docker.internal:4000
==================================================
✅ Authenticated with master key

Healthy: 8  |  Unhealthy: 0

--- Healthy Models (8) ---
  ✅ gemini-2.5-pro  — rpm: 60, timeout: 300.0s  (reasoning: low, tier: flex)
  ✅ gemini-2.5-flash  — rpm: 60, timeout: 300.0s
  ...

Error Paths

Condition	Response
No master key configured	Warning shown, public health only
401 Unauthorized	Auth failed message
403 Forbidden	Permission denied message
Connection refused	Connection failed message
Timeout (>15s)	Timeout message
Other non-200	Status code + first 500 chars of response

Function 2: Cost Breakdown

LiteLLM Endpoint: GET {litellm_url}/user/daily/activity Auth: Authorization: Bearer {litellm_master_key} Params: start_date (YYYY-MM-DD), end_date (YYYY-MM-DD)

Response Processing

The /user/daily/activity endpoint returns a rich breakdown structure:

results[] → per date:
  metrics: { spend, prompt_tokens, completion_tokens, total_tokens, successful_requests, failed_requests, api_requests, cache_read_input_tokens, cache_creation_input_tokens }
  breakdown:
    models: { model_name → metrics }
    model_groups: { group_name → metrics }
    providers: { provider_name → metrics }
    endpoints: { endpoint_path → metrics }
    api_keys: { key_hash → metrics }
    entities: { entity_id → metrics }

The tool aggregates per-model totals across all dates and formats a readable report.

Output Format

LiteLLM Cost Report: 2026-06-03 to 2026-06-04
============================================================
Total Spend:     $1.65
Total Tokens:    2,011,201 (1,993,600 prompt + 17,601 completion)
Cache Hit Rate:  69.5% (1,395,954 / 2,007,561 input tokens)
Requests:        31 successful, 1 failed (32 total)

By Model:
  Model                      Spend |       Requests |    Tokens
  gemini-3.5-flash          $1.20 |  26 ok, 0 fail | 2,003,116 tokens
  gemini-3.1-flash-image    $0.45 |   5 ok, 0 fail |     8,085 tokens

By Date:
  2026-06-04: $1.28 | 27 ok, 0 fail | 2,004,642 tokens
  2026-06-03: $0.37 |  4 ok, 0 fail |     6,559 tokens

Key Metrics Surfaced

• Total spend (USD)
• Token counts (prompt, completion, total)
• Cache hit rate (cache_read_input_tokens / total_input_tokens)
• Request counts (successful + failed)
• Per-model breakdown (sorted by spend, descending)
• Per-date breakdown

Condensed/Stripped

• api_key_breakdown sub-levels — too granular for general display
• metadata: {} — empty in current responses
• cache_creation_input_tokens — shown only when non-zero

Error Paths

Condition	Response
No master key configured	Error — key required for cost data
401 Unauthorized	Auth failed message
403 Forbidden	Permission denied message
Connection refused	Connection failed message
Timeout (>30s)	Timeout message (large date ranges may be slow)
No results	"No cost data found for [range]"

Additional Endpoints (Future Consideration)

Endpoint	Purpose	Priority
GET /global/spend/keys	Per-key lifetime spend	Nice-to-have
GET /spend/logs?start_date=&end_date=	Individual transaction logs	Low (returned empty in testing)
GET /health/live	Simple {"status":"healthy"} liveness check	Low (less useful than /health)

These are documented but not in scope for v1. The two-function design is the right scope.

Design Principles

1. Two functions, that's it. No scope creep. Health check and cost breakdown.
2. Portable. No hardcoded URLs or keys. Valves pass everything.
3. Token-efficient. Strip litellm_metadata from health. Format cost data as readable text, not raw JSON dumps.
4. General-purpose. Designed for the Network but usable by anyone with a LiteLLM proxy.
5. Read-only. These endpoints are GET only. No mutations, no risk.