wehub-resource-sync
42 lines
3.2 KiB
Markdown
42 lines
3.2 KiB
Markdown
# LEANN — Long-Term Vision
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## The Best Personal Data Management Platform
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LEANN's ultimate goal is to be the **unified personal knowledge layer** that lives on your machine. Not a cloud service. Not a SaaS product. A local-first system that understands everything you've ever worked on — code, documents, emails, chats, browser history, images — and makes it all instantly searchable and usable.
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### 1. Continuous Learning from Your Context
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LEANN should get smarter over time by continuously ingesting and indexing your data as you produce it:
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- **Always-on indexing**: Watch your filesystem, email, browser, and chat sources. Incrementally update indexes as new data arrives — no manual rebuilds.
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- **Cross-source connections**: Surface relationships across data sources. A Slack conversation about a bug should link to the relevant code change, the related email thread, and the document that describes the feature.
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- **Temporal awareness**: Understand when things happened. "What was I working on last Tuesday?" should be a searchable query.
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- **Personalized ranking**: Learn from your search patterns and usage to rank results by relevance to *you*, not just semantic similarity.
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### 2. The Best MCP for Code Retrieval
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AI coding assistants are only as good as the context they receive. LEANN aims to be the best context provider:
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- **AST-aware chunking**: Understand code structure — functions, classes, modules — not just raw text blocks. Retrieve semantically meaningful units.
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- **Dynamic index updates**: The index stays current as you edit. No stale results. No manual rebuilds. Save a file, and the index reflects the change within seconds.
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- **Cross-file understanding**: Resolve symbols across files. When you search for a function, also surface its callers, its tests, and the types it depends on.
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- **Dead-simple interface**: One command to build (`leann build`), automatic incremental updates, MCP server that any AI assistant can plug into with zero configuration.
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- **Repository-scale search**: Handle monorepos and large codebases without breaking a sweat. The storage efficiency (97% reduction vs. traditional vector DBs) makes this feasible on a laptop.
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### 3. Multimodal Knowledge Base
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Text is just the beginning:
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- **Image search**: CLIP-based retrieval for screenshots, diagrams, photos. "Find the architecture diagram from last month."
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- **Video retrieval**: Index video content — lectures, meetings, screen recordings — and search by what was said or shown.
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- **OCR pipeline**: Extract and index text from scanned documents, handwritten notes, whiteboard photos.
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- **Unified search**: One query searches across all modalities. The answer might be in a PDF, a screenshot, a code comment, or a Slack message.
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### 4. Platform for Personal AI
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Looking further ahead, LEANN becomes the memory and retrieval layer for personal AI agents:
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- **Agent memory**: AI agents that remember your preferences, past decisions, and project context across sessions.
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- **Deep research**: Agents that can search your entire personal knowledge base to answer complex questions, synthesize information, and generate insights.
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- **Proactive suggestions**: Surface relevant context before you ask for it — "You discussed this exact problem with a colleague 3 months ago, here's what you decided."
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