Comparison
deep-research vs LLocalSearch
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 LLocalSearch if lLocalSearch is a locally-running search engine that leverages language model agents to find answers without needing external API keys.
Markdown twin · deep-research alternatives · LLocalSearch alternatives
GraphCanon updated 6d
vs
Trust & integrity
| Signal | deep-research | LLocalSearch |
|---|---|---|
| Maintenance | Slowing (129d since push) As of 6d · github_public_v1 | Archived (136d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 6d · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- deep-research
- An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.
- LLocalSearch
- Locally running search aggregator using LLM Agents
Stars
- deep-research
- 20k
- LLocalSearch
- 6.0k
Forks
- deep-research
- 2.0k
- LLocalSearch
- 364
Open issues
- deep-research
- 93
- LLocalSearch
- 58
Language
- deep-research
- TypeScript
- LLocalSearch
- Go
Adopt for
- deep-research
- 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.
- LLocalSearch
- LLocalSearch is a locally-running search engine that leverages language model agents to find answers without needing external API keys.
Persona
- deep-research
- -
- LLocalSearch
- -
Runtime
- deep-research
- -
- LLocalSearch
- -
License
- deep-research
- MIT
- LLocalSearch
- The tool is released under the Apache-2.0 license, allowing for extensive use including modification and redistribution with proper attribution.
Last pushed
- deep-research
- Apr 11, 2026
- LLocalSearch
- Mar 24, 2026
Categories
- deep-research
- AI Agents, Data & Retrieval
- LLocalSearch
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- deep-research
- Slowing (36%)
- LLocalSearch
- Archived (8%)
Days since push
- deep-research
- 129d
- LLocalSearch
- 136d
Archived on GitHub
- deep-research
- No
- LLocalSearch
- Yes
Open issues (now)
- deep-research
- 93
- LLocalSearch
- 58
Stars delta
- deep-research
- +195 (30d)
- LLocalSearch
- Unknown
Open issues delta
- deep-research
- +3 (30d)
- LLocalSearch
- Unknown
Full report
- deep-research
- Trust report
- LLocalSearch
- Trust report
Choose deep-research if…
- deep-research is primarily TypeScript; LLocalSearch is Go.
- License: deep-research is MIT, LLocalSearch is Apache-2.0.
- Requirements: Requires Docker.
- Tags unique to deep-research: agent, ai, gpt, o3-mini.
- When you need a tool that can refine its topic focus over time through repeated iterations.
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.
Choose LLocalSearch if…
- LLocalSearch is primarily Go; deep-research is TypeScript.
- License: LLocalSearch is Apache-2.0, deep-research is MIT.
- Pricing: Free to use, but customization or complex setups may require additional expertise.
- Requirements: Min 4 GB RAM; Requires Docker.
- Tags unique to LLocalSearch: agent-based-search, docker-supported, language-models, llm.
- When you prefer local processing for privacy reasons
When NOT to use LLocalSearch
- In environments where cloud-based solutions are mandatory due to company policies
- If real-time responses are required as LLocalSearch might have latency issues depending on local resources
- For users who prefer simple installations without setting up a local Docker environment
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (dzhng/deep-research) · observed Aug 19, 2026
- GitHub forks (dzhng/deep-research) · observed Aug 19, 2026
- Last push (dzhng/deep-research) · observed Apr 11, 2026
- License file (MIT) · observed Aug 19, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (nilsherzig/LLocalSearch) · observed Aug 7, 2026
- GitHub forks (nilsherzig/LLocalSearch) · observed Aug 7, 2026
- Last push (nilsherzig/LLocalSearch) · observed Mar 24, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deep-research 20k · LLocalSearch 6.0k (synced Aug 19, 2026).
Common questions
- What is the difference between deep-research and LLocalSearch?
- deep-research: An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.. LLocalSearch: Locally running search aggregator using LLM Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose deep-research over LLocalSearch?
- Choose deep-research over LLocalSearch when deep-research is primarily TypeScript; LLocalSearch is Go; License: deep-research is MIT, LLocalSearch is Apache-2.0; Requirements: Requires Docker; Tags unique to deep-research: agent, ai, gpt, o3-mini; When you need a tool that can refine its topic focus over time through repeated iterations.
- When should I choose LLocalSearch over deep-research?
- Choose LLocalSearch over deep-research when LLocalSearch is primarily Go; deep-research is TypeScript; License: LLocalSearch is Apache-2.0, deep-research is MIT; Pricing: Free to use, but customization or complex setups may require additional expertise; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to LLocalSearch: agent-based-search, docker-supported, language-models, llm; When you prefer local processing for privacy reasons.
- 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 LLocalSearch?
- In environments where cloud-based solutions are mandatory due to company policies If real-time responses are required as LLocalSearch might have latency issues depending on local resources For users who prefer simple installations without setting up a local Docker environment
- Is deep-research or LLocalSearch more popular on GitHub?
- deep-research has more GitHub stars (19,571 vs 5,955). Stars measure visibility, not whether either tool fits your constraints.
- Are deep-research and LLocalSearch open source?
- Yes - both are open-source projects on GitHub (deep-research: MIT, LLocalSearch: Apache-2.0).
- Where can I find alternatives to deep-research or LLocalSearch?
- GraphCanon lists graph-backed alternatives at deep-research alternatives and LLocalSearch alternatives (deep-research markdown twin, LLocalSearch markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, deep-research or LLocalSearch?
- deep-research: Slowing. LLocalSearch: Archived. 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 LLocalSearch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deep-research trust report; LLocalSearch trust report.