91.9kGo+89/daypushed 0d ago
Use it for: Build RAG and agent-based systems that turn complex documents into a context layer for LLMs, with cloud or local deployment.
Quick start
- Try the hosted cloud service at cloud.ragflow.io
- Or follow the Local Deployment section of the README
- Ingest your documents into a dataset
- Use pre-built agent templates to build your AI workflow
90.9kPython+39/daypushed 24d ago
Use it for: Turn PDFs and images into structured text data that LLMs can use, with OCR support for over 100 languages.
Quick start
- Check that you have a supported Python version (3.8 to 3.12)
- Install the paddleocr package following the README install section
- Run OCR or document parsing on a sample image or PDF
- Use the structured output in your LLM or RAG pipeline
85.1kPython+96/daypushed 4d ago
Use it for: Crawl websites and turn them into clean Markdown that is ready for LLMs, RAG pipelines, and AI agents.
Quick start
- Install the package with: pip install -U crawl4ai
- Run the one-time browser setup: crawl4ai-setup
- Use AsyncWebCrawler in a Python script and call crawler.arun(url=...)
- Print result.markdown to see the clean output
59.5kPython+317/daypushed 1d ago
Use it for: Give AI assistants a local, searchable memory of your past conversations, stored verbatim and retrieved with semantic search.
Quick start
- Install the mempalace package from PyPI
- Follow the docs at mempalaceofficial.com for setup
- Mine your conversation history into the memory index
- Wire up auto-save hooks if you use Claude Code
58.8kJupyter Notebook+50/daypushed 96d ago
Use it for: Deploy ready-made RAG and enterprise search apps that stay in sync with live data sources like Google Drive, SharePoint, S3, Kafka and PostgreSQL.
Quick start
- Clone the repo and pick an application template that fits your needs
- Connect the template to your data sources such as file system, Google Drive or S3
- Run the template on your own machine, optionally using Docker
- Deploy to a cloud provider (GCP, AWS, Azure, Render) or on-premises
34.3kPython+212/daypushed 4d ago
Use it for: Convert a technical book PDF or document folder into an agent skill your coding assistant can query chapter by chapter.
Quick start
- Install the skill into your agent (Claude Code, Copilot CLI, etc.) following the README install section
- Point it at a book: /book-to-skill ./my-book.pdf
- Let it distill the book into frameworks, rules and per-chapter files
- Ask your agent about a topic, for example /my-book replication
32.8kGo+74/daypushed 1d ago
Use it for: Turn a team's documents into a searchable knowledge base with RAG Q&A, a multi-step reasoning agent, and an auto-maintained wiki.
Quick start
- Open the Quick Start section of the README
- Deploy the platform by following the README instructions
- Upload documents or connect a data source to create a knowledge base
- Ask questions with RAG, run the agent, or organize content in the wiki
