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-/https://github.com/berriai/litellm/issues/29295
GitHub · issue

#29295 Your project is tracked on HVTracker — any data we should correct?

  • State: open
  • Author: @YugantM

Hi — [HVTracker](https://hvtracker.net) is an independent trust registry tracking 171 open-source AI agents. **LiteLLM** is ranked **#23** with a score of **73.5/100** (Grade B).

We're currently missing build provenance for your project — if there's a package name, provenance attestation, or signal we're not picking up correctly, we'd like to fix it. Your profile: [hvtracker.net/agents/litellm/](https://hvtracker.net/agents/litellm/)

All data comes from public APIs (GitHub, npm/PyPI, OSSF Scorecard via deps.dev). Methodology: [hvtracker.net/methodology](https://hvtracker.net/methodology)

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vote history (6 events)
#0 of 0 · 31d19h4m31s ago — entered · #import:https:::github.com:berriai:litellm post #1784
The right issue is harder because it spans coupled API update paths, persistence semantics, backward compatibility, and regression coverage; the left issue is primarily an external project-metadata clarification with little implementation scope.
The left requires coordinated changes across schema handling, router registration, cost computation, persistence, and regression coverage, with compatibility risks in pricing behavior. The right requires little or no product engineering work.
A new provider integration spans authentication, API wiring, response normalization, multiple execution paths, compatibility handling, and comprehensive tests; the other item is non-code administrative work with negligible implementation risk.
25402 requires code changes across fallback handling and Responses API metadata propagation, with regression testing across routes and providers; 29295 is an informational outreach item requiring no implementation.
Issue 26179 requires debugging and modifying streaming response parsing across multiple API paths, plus compatibility validation and regression tests; issue 29295 is primarily an informational project-metadata request with minimal engineering scope.
#0 of 0 · 31d18h12m22s ago — current · #import:https:::github.com:berriai:litellm post #2639
The left requires diagnosing and correcting behavior across provider-specific error classification, streaming control flow, retry policy, and fallback integration, with regression coverage and operational risk. The right is informational and requires no product implementation.
discussed in #import:https:::github.com:berriai:litellm

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