RAG · Search

RAG · Search

big names on the move
01
tirth8205/code-review-graph
+888 ★/dayaccelerating

It builds a persistent structural map of your codebase so AI assistants read only the files in a change's blast radius instead of the whole repo.

26.4k Python Coding Assistants · explained
02
Graphify-Labs/graphify
+700 ★/daycooling

Graphify builds a queryable knowledge graph from your whole project so AI assistants can answer architecture questions without grepping raw files.

95.9k Python Coding Assistants · explained Feature
04
Panniantong/Agent-Reach
+438 ★/daycooling

Because making AI agents read Twitter, Reddit, or Bilibili usually means wrestling with a dozen scrapers, API keys, and cookie jars.

60.8k Python Agents · explained Feature
05
topoteretes/cognee
+160 ★/dayaccelerating

Cognee gives AI agents persistent memory by treating documents as a living knowledge graph rather than a vector dump.

29.3k Python Agents · explained Feature
07
langgenius/dify
+140 ★/dayaccelerating

Because stitching together LLM workflows, RAG, agents, and observability by hand is a full-time job.

150.2k TypeScript Agents · explained
08
ruvnet/ruflo
+130 ★/daycooling

Ruflo turns Claude Code from a solo assistant into a coordinated swarm with shared memory, plugins, and cross-machine federation.

66k TypeScript Agents · explained
09
open-webui/open-webui
+120 ★/dayaccelerating

To wrap every LLM backend, RAG pipeline, and enterprise auth scheme into a single self-hosted interface.

146.7k Python Chat Assistants · explained
10
thedotmack/claude-mem
+115 ★/daycooling

Persistent memory for coding agents that currently forget everything when the session ends.

88.6k JavaScript Agents · explained
11
anthropics/claude-cookbooks
+110 ★/daycooling

Official Jupyter notebooks demonstrating how to wire Claude into production tasks like RAG, SQL queries, and multimodal pipelines.

49.9k Jupyter Notebook Learning · explained
12
infiniflow/ragflow
+92 ★/dayaccelerating

RAGFlow fuses deep document parsing with agentic workflows so LLMs can answer from messy corporate documents without making things up.

86k Go RAG · Search · explained
13
mem0ai/mem0
+79 ★/dayaccelerating

Mem0 gives AI agents a persistent memory layer that accumulates user context across sessions instead of overwriting it every time.

61.7k TypeScript Agents · explained
14
garrytan/gbrain
+77 ★/daycooling

GBrain gives AI agents a persistent memory, synthesizing cited answers from your notes and wiring a knowledge graph autonomously while you sleep.

27.1k TypeScript Agents · explained
15
getzep/graphiti
+73 ★/dayaccelerating

Graphiti continuously ingests structured and unstructured data into temporal context graphs so agents can query what is true now—or was true at any specific moment—without rebuilding the graph from scratch.

29.2k Python RAG · Search · explained
17
HKUDS/LightRAG
+69 ★/dayaccelerating

It exists because pure vector search often misses the big picture, so LightRAG auto-maps entities and relationships into a knowledge graph for richer retrieval.

38.1k Python RAG · Search · explained
18
VectifyAI/PageIndex
+67 ★/dayaccelerating

PageIndex replaces vector similarity search with hierarchical tree reasoning to retrieve complex documents more accurately.

34.6k Python RAG · Search · explained
19

OpenDataLoader PDF exists to extract structured data from PDFs for AI pipelines while auto-tagging untagged documents for screen readers, all without proprietary dependencies.

27.9k Java Data Tooling · explained
20
langflow-ai/langflow
+54 ★/dayaccelerating

Langflow is a visual schematic editor for AI workflows that deploys your graphs as APIs or MCP servers, saving you from writing yet another Python script to chain LLM calls together.

152.4k Python Agents · explained
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