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Code shouldn't know which LLM provider you're using

Code shouldn't know which LLM provider you're using

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TL;DR · WeSearch summary

🚅 LiteLLM LiteLLM AI Gateway Open Source AI Gateway for 100+ LLMs. LiteLLM Proxy Server (AI Gateway) | Hosted Proxy | Enterprise Tier | Website What is LiteLLM LiteLLM is an open source AI Gateway that gives you a single, unified interface to call 100+ LLM providers — OpenAI, Anthropic, Gemini, Bedrock, Azure, and more — using the OpenAI format. Use it as a Python SDK for direct library integration, or deploy the AI Gateway (Proxy Server) as a centralized service for your team or organization.

Key facts
About this source

Hacker News (AI / LLM) files mainly under ai. We currently carry 6,263 of its stories.

Original article
GitHub
Read full at GitHub →

Story provenance

Source · retrieval · rights · ranking — open for full record
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Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.

Record

Original publisherGitHub
Canonical URLhttps://github.com/BerriAI/litellm
Publication timeThu, 24 Sep 2026 08:06:26 +0000
Retrieval time2026-09-24T08:10:14.461Z
Last seen2026-09-24T08:10:14.461Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
ClusterKaZDRY_Md5BW · 1 stories
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

Rights status (four layers)

Publisher-declared
No publisher-confirmed rights record for this source yet.
Machine-readable
No source-specific machine-readable restriction detected beyond the public feed.
WeSearch interpretation
WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
Retrieval and training permissions are not asserted unless the publisher confirms them.

WeSearch handling by dimension

Indexing May the item be indexed (stored, ranked, made findable)? Allowed
Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

🚅 LiteLLM LiteLLM AI Gateway Open Source AI Gateway for 100+ LLMs. Self-hosted. Enterprise-ready. Call any LLM in OpenAI format. LiteLLM Proxy Server (AI Gateway) | Hosted Proxy | Enterprise Tier | Website What is LiteLLM LiteLLM is an open source AI Gateway that gives you a single, unified interface to call 100+ LLM providers — OpenAI, Anthropic, Gemini, Bedrock, Azure, and more — using the OpenAI format. Use it as a Python SDK for direct library integration, or deploy the AI Gateway (Proxy Server) as a centralized service for your team or organization. Jump to LiteLLM Proxy (LLM Gateway) Docs Jump to Supported LLM Providers Why LiteLLM Managing LLM calls across providers gets complicated fast — different SDKs, auth patterns, request formats, and error types for every model.

Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.

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