Install payload
Install payload is sparse; verify before rollout decisions.
0% (0/4)
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Showing 4 resources for "model-serving"
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Select entries to compare install and trust signals side by side.
Trust snapshot
4 results in this view
Claimed
0%(0/4)
1 trust signal differs in this sample: Submitter
Signals differ on Submitter — add entries to compare before you install.
Rollout signal scan
3 rollout risk signals in current results
Biggest gaps: metadata review, package integrity. 0 entries have 2+ required gaps.
risk
Most at-risk entries in this view
Adoption queue
Browse adoption queue · balanced
4/4 visible results are in hold tier and need mitigation before adoption.
ready 0caution 0hold 4
BentoML
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/bentoml · trust review · confidence 50%
LitServe
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/litserve · trust review · confidence 50%
Ray
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/ray · trust review · confidence 50%
vLLM
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/vllm · trust review · confidence 50%
Decision confidence
Decision confidence scan · balanced
4/4 results are low-confidence and need review before adoption.
high 0medium 0low 4
BentoML
Hold adoption until Metadata review, Package integrity are resolved.
low
36/100
Missing: Metadata reviewMissing: Package integrityMissing: Install payload
tools/bentoml · trust review
LitServe
Hold adoption until Metadata review, Package integrity are resolved.
low
36/100
Missing: Metadata reviewMissing: Package integrityMissing: Install payload
tools/litserve · trust review
Ray
Hold adoption until Metadata review, Package integrity are resolved.
low
36/100
Missing: Metadata reviewMissing: Package integrityMissing: Install payload
tools/ray · trust review
vLLM
Hold adoption until Metadata review, Package integrity are resolved.
low
36/100
Missing: Metadata reviewMissing: Package integrityMissing: Install payload
tools/vllm · trust review
Freshness distribution
Current results are broadly fresh
Median age 54 days; all 4 scanned entries are within 90 days.
Theme distribution
Results center on model-serving
100% of this view shares the top theme. Leading themes: model-serving, inference, ai-infrastructure.
- model-serving100% (4)
- inference75% (3)
- ai-infrastructure25% (1)
- deployment25% (1)
- distributed-computing25% (1)
- machine-learning25% (1)
- openai-compatible25% (1)
7 distinct themes across 4 scanned
LitServeby Lightning AI · submitted by jaytbarimbao-collab
Lightweight open-source serving framework for building custom AI model inference APIs by defining a LitAPI with setup and predict methods, with batching, streaming, multi-GPU autoscaling, OpenAI-compatible endpoints, and support for compound, multimodal, RAG, and agent pipelines.
BentoMLby BentoML · submitted by oktofeesh1
Apache-2.0 Python framework for building, packaging, serving, containerizing, and deploying AI model inference APIs and multi-model serving systems.
Rayby Ray Project · submitted by oktofeesh1
Apache-2.0 distributed AI compute engine for scaling Python, ML data processing, training, tuning, reinforcement learning, and model serving workloads.
vLLMby vLLM Project · submitted by oktofeesh1
Open-source high-throughput LLM inference and serving engine with PagedAttention, continuous batching, OpenAI-compatible APIs, tool calling, and structured outputs.