--- title: "awesome-ai-web-search vs cherche" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/felladrin-awesome-ai-web-search-vs-raphaelsty-cherche" tools: ["felladrin-awesome-ai-web-search", "raphaelsty-cherche"] --- # awesome-ai-web-search vs cherche *GraphCanon updated Aug 25, 2026* ## Verdict Pick awesome-ai-web-search if a curated HTML list of AI-powered web search tools under CC0-1.0 license; pick cherche if cherche is a Python library for implementing neural search capabilities. [awesome-ai-web-search](https://hf.co/spaces/felladrin/awesome-ai-web-search) reports 1.4k GitHub stars, 125 forks, and 1 open issues, last pushed Aug 14, 2026. [cherche](https://github.com/raphaelsty/cherche) has 332 stars, 14 forks, and 4 open issues, last pushed Jun 1, 2024. Figures are from public GitHub metadata via [awesome-ai-web-search's repository](https://github.com/felladrin/awesome-ai-web-search) and [cherche's repository](https://github.com/raphaelsty/cherche). | | [awesome-ai-web-search](/tools/felladrin-awesome-ai-web-search.md) | [cherche](/tools/raphaelsty-cherche.md) | | --- | --- | --- | | Tagline | List of AI-assisted web search software | Neural Search | | Stars | 1,416 | 332 | | Forks | 125 | 14 | | Open issues | 1 | 4 | | Language | HTML | Python | | Adopt for | A curated HTML list of AI-powered web search tools under CC0-1.0 license. | Cherche is a Python library for implementing neural search capabilities. | | Persona | - | - | | Runtime | - | - | | License | CC0-1.0 | MIT | | Categories | Data & Retrieval, Evaluation & Observability | Data & Retrieval, Evaluation & Observability, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-ai-web-search](/tools/felladrin-awesome-ai-web-search.md) | [cherche](/tools/raphaelsty-cherche.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 10d | 812d | | Open issues (now) | 1 | 4 | | Stars delta | +25 (30d) | 0 (30d) | | Open issues delta | +1 (30d) | 0 (30d) | | Full report | [trust report](/tools/felladrin-awesome-ai-web-search/trust.md) | [trust report](/tools/raphaelsty-cherche/trust.md) | ## Decision facts: awesome-ai-web-search - **Adopt for:** A curated HTML list of AI-powered web search tools under CC0-1.0 license. ## Decision facts: cherche - **Adopt for:** Cherche is a Python library for implementing neural search capabilities. ## Choose when ### Choose awesome-ai-web-search if… - awesome-ai-web-search is primarily HTML; cherche is Python. - License: awesome-ai-web-search is CC0-1.0, cherche is MIT. - Tags unique to awesome-ai-web-search: ai-search-engine, metasearch, question-answering, rag. - Need a comprehensive overview of AI-assisted web search options without code integration ### Choose cherche if… - cherche is primarily Python; awesome-ai-web-search is HTML. - License: cherche is MIT, awesome-ai-web-search is CC0-1.0. - Tags unique to cherche: bm25, flashtext, machine-learning, natural-language-processing. - Also covers Vector Databases. - Cherche is a Python library for implementing neural search capabilities. ## When NOT to use awesome-ai-web-search - Requiring direct API access or integrations with specific AI search tools - Looking for a live, interactive AI web search service rather than a resource listing - Need tool evaluations or comparative analysis instead of just project listings ## When NOT to use cherche - Last GitHub push was 815 days ago (dormant maintenance, Jun 1, 2024). Validate activity before betting a new project on cherche. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between awesome-ai-web-search and cherche? awesome-ai-web-search: List of AI-assisted web search software. cherche: Neural Search. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-ai-web-search over cherche? Choose awesome-ai-web-search over cherche when awesome-ai-web-search is primarily HTML; cherche is Python; License: awesome-ai-web-search is CC0-1.0, cherche is MIT; Tags unique to awesome-ai-web-search: ai-search-engine, metasearch, question-answering, rag; Need a comprehensive overview of AI-assisted web search options without code integration. ### When should I choose cherche over awesome-ai-web-search? Choose cherche over awesome-ai-web-search when cherche is primarily Python; awesome-ai-web-search is HTML; License: cherche is MIT, awesome-ai-web-search is CC0-1.0; Tags unique to cherche: bm25, flashtext, machine-learning, natural-language-processing; Also covers Vector Databases; Cherche is a Python library for implementing neural search capabilities. ### When should I avoid awesome-ai-web-search? Requiring direct API access or integrations with specific AI search tools Looking for a live, interactive AI web search service rather than a resource listing Need tool evaluations or comparative analysis instead of just project listings ### When should I avoid cherche? Last GitHub push was 815 days ago (dormant maintenance, Jun 1, 2024). Validate activity before betting a new project on cherche. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is awesome-ai-web-search or cherche more popular on GitHub? awesome-ai-web-search has more GitHub stars (1,416 vs 332). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-ai-web-search and cherche open source? Yes - both are open-source projects on GitHub (awesome-ai-web-search: CC0-1.0, cherche: MIT). ### Where can I find alternatives to awesome-ai-web-search or cherche? GraphCanon lists graph-backed alternatives at [awesome-ai-web-search alternatives](/tools/felladrin-awesome-ai-web-search/alternatives) and [cherche alternatives](/tools/raphaelsty-cherche/alternatives) ([awesome-ai-web-search markdown twin](/tools/felladrin-awesome-ai-web-search/alternatives.md), [cherche markdown twin](/tools/raphaelsty-cherche/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/felladrin-awesome-ai-web-search-vs-raphaelsty-cherche.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-ai-web-search or cherche? awesome-ai-web-search: Active. cherche: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for awesome-ai-web-search and cherche? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-ai-web-search trust report](/tools/felladrin-awesome-ai-web-search/trust); [cherche trust report](/tools/raphaelsty-cherche/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=felladrin-awesome-ai-web-search`](/api/graphcanon/graph?tool=felladrin-awesome-ai-web-search) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_