Building RepoRank — The Open Source Impact & Funding Readiness Engine

说明与用途

RepoRank 通过 Coral SQL 聚合 GitHub、PyPI、npm、HackerNews 和 Open Collective 的指标，然后使用 LLM 生成影响评分、叙述、推介语和资助建议，简化了筹资提案的准备流程。

问题

Maintainers struggle to compile impact metrics from multiple APIs to craft grant proposals and sponsorship applications.

结果

RepoRank reduces data aggregation from days to seconds, produces a 0‑100 impact score, a concise pitch, and targeted grant suggestions, streamlining funding workflows for open‑source maintainers.

工作流

• Define custom YAML source specs for PyPI, npm, HackerNews, Open Collective
• Integrate sources into Coral SQL engine
• Write a single cross-source JOIN query to fetch metrics
• Execute query via Coral to obtain unified JSON
• Pass JSON to Hugging Face Qwen 2.5 (72B) for analysis
• Generate impact score, narrative, pitch, and grant recommendations
• Display results in a dark‑mode dashboard with radar charts and grant cards

证据

Integrating 4+ external APIs usually takes days of reading docs and writing API wrapper code.

来源

Coral changes this completely by letting you query APIs using standard SQL.

来源

Using structured JSON schema outputs, Qwen acts as an expert open-source analyst, returning Impact Score, Narrative, Pitch, and Targeted Grants.

来源