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Showing 3 resources for "model-routing"
Saved
Active

1 trusted · 2 review in this set — compare to see which signals differ.

Trust snapshot

3 results in this view

Claimed
0%(0/3)

3 trust signals differ in this sample: Package trust, Source provenance, Submitter

Signals differ on Package trust, Source provenance, Submitter — add entries to compare before you install.

Rollout signal scan

2 rollout risk signals in current results

Biggest gaps: metadata review, package integrity. 0 entries have 2+ required gaps.

3 scanned

Install payload

Install payload is mixed and needs spot-checking.

watch

67% (2/3)

Adoption queue

Browse adoption queue · balanced

1/3 visible results are in hold tier and need mitigation before adoption.

ready 0caution 2hold 1

AnythingLLM

1 blockers: Metadata review

caution

50/100

Request metadata review from maintainers or internal owners.

Collect package checksum or signed artifact information.

tools/anythingllm · trust review · confidence 67%

LiteLLM

2 blockers: Metadata review, Install payload

hold

36/100

Request metadata review from maintainers or internal owners.

Add install/config payload for reproducible team rollout.

Collect package checksum or signed artifact information.

tools/litellm · trust review · confidence 50%

Decision confidence

Decision confidence scan · balanced

1/3 results are low-confidence and need review before adoption.

high 1medium 1low 1

AnythingLLM

Address Metadata review, Package integrity before broader rollout.

medium

54/100

Missing: Metadata reviewMissing: Package integrity

tools/anythingllm · trust review

LiteLLM

Hold adoption until Metadata review, Package integrity are resolved.

low

36/100

Missing: Metadata reviewMissing: Package integrityMissing: Install payload

tools/litellm · trust review

Freshness distribution

Mostly fresh with a few aging entries

Median age 55 days; 2 fresh, 1 aging or stale of 3 scanned.

median 55d

Aging

91–180 days

33%

1 entry

Stale

> 180 days

0%

0 entries

Theme distribution

Results center on model-routing

100% of this view shares the top theme. Leading themes: model-routing, ai-agents, ai-gateway.

Focused

16 distinct themes across 3 scanned

Design and validate model routing strategies that reduce cost and latency while preserving output quality.

Level:advancedType:generalVerified:draft
Safety ✓ Privacy ✓
Docker logo

Local-first AI application for private chat, document RAG, workspace agents, MCP-compatible tools, model routing, memories, scheduled tasks, multimodal workflows, multi-user Docker deployments, and self-hosted agent automation.

LiteLLM logo
LiteLLMby BerriAI · submitted by oktofeesh1

Open-source AI gateway and Python SDK for routing LLM calls through a unified OpenAI-compatible interface.