Khoj
Open-source personal AI assistant that searches and chats with your documents, notes, and the web.
Overzicht
Belangrijkste functies
- Semantic search across local documents
- Conversational chat with memory
- Integrations with Obsidian, Emacs, and Notion
- Web search and image generation
- Local or cloud deployment options
- Support for PDFs, Markdown, and plain text
Use cases
Chat with personal notes and PDFs
Query your local Markdown notes, PDFs, and text files in natural language to quickly retrieve information without manually searching through folders.
Augment Obsidian or Emacs workflows
Integrate Khoj into Obsidian, Emacs, or Notion to add semantic search and AI chat directly on top of your existing knowledge base.
Private self-hosted research assistant
Run Khoj locally with your preferred open-source LLM to summarize documents and explore ideas while keeping sensitive data on your own machine.
Long-term conversational companion
Use Khoj as a memory-enabled assistant that recalls prior chats and combines web search with personal context for ongoing projects.
Pluspunten & minpunten
Pluspunten
- Open-source and self-hostable
- Works with personal files and notes
- Supports multiple LLM providers
- Combines chat, search, and web browsing
Minpunten
- Self-hosting requires technical setup
- Quality depends on chosen LLM
- Smaller ecosystem than mainstream assistants
Reviews
Gemiddelde van 5 beoordelingen.
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Diego Fernández
Skeptical, then convinced
I went in skeptical — most tools in this space overpromise. It actually delivers on support for PDFs, Markdown, and plain text, and works with personal files and notes caught me off guard. Quality depends on chosen LLM is why this isn't a perfect score, still, I'd recommend giving it a real trial.
Esther Adeyemi
Compared a few options
Evaluated this against two competitors. Where it wins: conversational chat with memory and works with personal files and notes. On balance the feature set — especially local or cloud deployment options — justifies the 5 stars for our use case.
Aaliyah Johnson
Solid for our team
We rolled this out across the team last quarter and supports multiple LLM providers. Conversational chat with memory fits neatly into how we already work, and semantic search across local documents removed a step we used to do by hand. Quality depends on chosen LLM, which is the main caveat, but it has held up under daily use.
Sanjay Gupta
Compared a few options
Evaluated this against two competitors. Where it wins: local or cloud deployment options and combines chat, search, and web browsing. Where it lags: quality depends on chosen LLM. On balance the feature set — especially conversational chat with memory — justifies the 4 stars for our use case.
Grace Okafor
Does the job
Pretty happy overall. Integrations with Obsidian, Emacs, and Notion just works and combines chat, search, and web browsing. Quality depends on chosen LLM can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.
Q&A
Nog geen vragen — wees de eerste om er een te stellen.
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