--- title: "deep-research vs farfalle" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dzhng-deep-research-vs-rashadphz-farfalle" tools: ["dzhng-deep-research", "rashadphz-farfalle"] --- # deep-research vs farfalle *GraphCanon updated Sep 20, 2026* ## Verdict Pick deep-research if deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics; pick farfalle if farfalle is an AI search engine that supports both local and cloud-integrated LLMs, built in TypeScript with support for multiple frontend frameworks including Next.js and React under the Shadcn UI. [deep-research](https://github.com/dzhng/deep-research) reports 20k GitHub stars, 2.0k forks, and 93 open issues, last pushed Apr 11, 2026. [farfalle](https://www.farfalle.dev/) has 3.5k stars, 318 forks, and 52 open issues, last pushed Sep 27, 2024. Figures are from public GitHub metadata via [deep-research's repository](https://github.com/dzhng/deep-research) and [farfalle's repository](https://github.com/rashadphz/farfalle). | | [deep-research](/tools/dzhng-deep-research.md) | [farfalle](/tools/rashadphz-farfalle.md) | | --- | --- | --- | | Tagline | An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models. | AI search engine | | Stars | 19,571 | 3,541 | | Forks | 1,993 | 318 | | Open issues | 93 | 52 | | Language | TypeScript | TypeScript | | Adopt for | Deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics. | Farfalle is an AI search engine that supports both local and cloud-integrated LLMs, built in TypeScript with support for multiple frontend frameworks including Next.js and React under the Shadcn UI. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Data & Retrieval | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deep-research](/tools/dzhng-deep-research.md) | [farfalle](/tools/rashadphz-farfalle.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 129d | 722d | | Open issues (now) | 93 | 52 | | Stars delta | +195 (30d) | 0 (30d) | | Open issues delta | +3 (30d) | -1 (30d) | | Full report | [trust report](/tools/dzhng-deep-research/trust.md) | [trust report](/tools/rashadphz-farfalle/trust.md) | ## Decision facts: deep-research - **Requirements:** Requires Docker - **Adopt for:** Deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics. ## Decision facts: farfalle - **Requirements:** Setting up requires Docker for development purposes.; API keys may be required depending on the LLM chosen for integration. - **Adopt for:** Farfalle is an AI search engine that supports both local and cloud-integrated LLMs, built in TypeScript with support for multiple frontend frameworks including Next.js and React under the Shadcn UI. ## Choose when ### Choose deep-research if… - License: deep-research is MIT, farfalle is Apache-2.0. - Requirements: Requires Docker. - Tags unique to deep-research: agent, ai, gpt, o3-mini. - Also covers AI Agents. - deep-research ships Docker support for self-hosted deployment. - When you need a tool that can refine its topic focus over time through repeated iterations. ### Choose farfalle if… - License: farfalle is Apache-2.0, deep-research is MIT. - Requirements: Setting up requires Docker for development purposes.; API keys may be required depending on the LLM chosen for integration.. - Tags unique to farfalle: fastapi, generative-ui, gpt-4o, groq. - When you require self-hosting capabilities to maintain data privacy and security while utilizing an AI-powered search engine. ## When NOT to use deep-research - When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment. - If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys. ## When NOT to use farfalle - If your project strictly requires low-code or no-code solutions, as Farfalle demands a more technical setup including modifying environment files and API configurations. - In environments where a search engine needs to be up and running with minimal configuration time, since setting up Farfalle involves custom setup steps documented in separate instructions. ## Common questions ### What is the difference between deep-research and farfalle? deep-research: An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.. farfalle: AI search engine. See the comparison table for live GitHub stats and shared categories. ### When should I choose deep-research over farfalle? Choose deep-research over farfalle when License: deep-research is MIT, farfalle is Apache-2.0; Requirements: Requires Docker; Tags unique to deep-research: agent, ai, gpt, o3-mini; Also covers AI Agents; deep-research ships Docker support for self-hosted deployment; When you need a tool that can refine its topic focus over time through repeated iterations. ### When should I choose farfalle over deep-research? Choose farfalle over deep-research when License: farfalle is Apache-2.0, deep-research is MIT; Requirements: Setting up requires Docker for development purposes.; API keys may be required depending on the LLM chosen for integration.; Tags unique to farfalle: fastapi, generative-ui, gpt-4o, groq; When you require self-hosting capabilities to maintain data privacy and security while utilizing an AI-powered search engine. ### When should I avoid deep-research? When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment. If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys. ### When should I avoid farfalle? If your project strictly requires low-code or no-code solutions, as Farfalle demands a more technical setup including modifying environment files and API configurations. In environments where a search engine needs to be up and running with minimal configuration time, since setting up Farfalle involves custom setup steps documented in separate instructions. ### Is deep-research or farfalle more popular on GitHub? deep-research has more GitHub stars (19,571 vs 3,541). Stars measure visibility, not whether either tool fits your constraints. ### Are deep-research and farfalle open source? Yes - both are open-source projects on GitHub (deep-research: MIT, farfalle: Apache-2.0). ### Where can I find alternatives to deep-research or farfalle? GraphCanon lists graph-backed alternatives at [deep-research alternatives](/tools/dzhng-deep-research/alternatives) and [farfalle alternatives](/tools/rashadphz-farfalle/alternatives) ([deep-research markdown twin](/tools/dzhng-deep-research/alternatives.md), [farfalle markdown twin](/tools/rashadphz-farfalle/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/dzhng-deep-research-vs-rashadphz-farfalle.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deep-research or farfalle? deep-research: Slowing. farfalle: 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 deep-research and farfalle? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deep-research trust report](/tools/dzhng-deep-research/trust); [farfalle trust report](/tools/rashadphz-farfalle/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dzhng-deep-research`](/api/graphcanon/graph?tool=dzhng-deep-research) - 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/_