# LiteLLM — User Demand Report

**Week:** 2026-W15
**Generated:** 2026-04-06
**Issues analyzed:** 22 (22 included)
**Need clusters:** 1

## Top 10 User Needs

| Rank | Need | Issues | Score | Category | Examples |
| --- | --- | --- | --- | --- | --- |
| 1 | LLM Provider Integration Fixes and Performance Observability | 22 | 5.9 | Integration | [#25191](https://github.com/BerriAI/litellm/issues/25191), [#25157](https://github.com/BerriAI/litellm/issues/25157), [#25116](https://github.com/BerriAI/litellm/issues/25116) |

## Rising Needs

| Need | Rising Score | This Week | Category |
| --- | --- | --- | --- |
| LLM Provider Integration Fixes and Performance Observability | 23.0x | 22 | Integration |

## Category Breakdown

- **Integration**: 1 clusters

## All Need Clusters

### 1. LLM Provider Integration Fixes and Performance Observability

Users are reporting multiple bugs affecting various LLM provider integrations (Bedrock, Vertex AI, Azure, Modal, Predibase, Together AI) including streaming inconsistencies, crashes, and incorrect parameter handling. Additionally, users want improved observability through built-in latency profiling and want to address security vulnerabilities in dependencies. These issues collectively affect the reliability and accuracy of the proxy when serving requests across different cloud providers and model types.

- **Volume:** 22 issues (22 open, 0 closed)
- **Demand Score:** 5.9
- **Avg Reactions:** 0.1 | **Avg Comments:** 0.5
- **Example issues:** [#25191](https://github.com/BerriAI/litellm/issues/25191), [#25157](https://github.com/BerriAI/litellm/issues/25157), [#25116](https://github.com/BerriAI/litellm/issues/25116), [#25214](https://github.com/BerriAI/litellm/issues/25214), [#25172](https://github.com/BerriAI/litellm/issues/25172)

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*This report analyzes public GitHub issues only. It represents a signal from public issue discussions, not the full user base.*

*Generated by [ReadYourUsers](https://github.com/study8677/ReadYourUsers)*