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Contents

GitHub
AI Agent·2024
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ReMe

ReMe Team (Agentscope AI)·AgentScope

Stores agent memory as human- and agent-readable Markdown files with wikilinks instead of an opaque vector DB. Auto Memory/Resource/Dream jobs distill conversations into long-term notes, and hybrid wikilink + BM25 + embedding search retrieves them.

#ai-agent#embeddings#RAG#python#github+3
GitHub
AI Client·2024
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Fincept Terminal

Fincept Corporation

Desktop finance analytics terminal that combines CFA-level models, real-time trading and 100+ data connectors with embedded Python for analytics; includes 37 AI agents and local/multi-provider LLM support for automated research and decision workflows.

#finance#ai-agent#llm#python#terminal+2
GitHub
AI Deploy·2024
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LiteRT

Google AI Edge·Google

Runs and optimizes ML and generative-AI models on-device across mobile, desktop, web, and IoT. Successor to TensorFlow Lite, it adds automated GPU/NPU accelerator selection and zero-copy buffer interop to cut latency without cloud round-trips.

#google#ai-framework#ai-inference#ai-serving#LLM+3
GitHub
AI Image·2024
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MiniMind-V

Jingyao Gong (jingyaogong)

Trains a 65M-parameter vision-language model from scratch in ~2 hours on one RTX 3090, about 3 RMB (~$0.40) of GPU rental. Connects a frozen SigLIP2 encoder to a small MiniMind LLM via a two-layer MLP projector; full PyTorch code for pretraining and SFT.

#vision#pytorch#github#llm#ai-train+2
GitHub
AI Image·2024
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olmOCR

Allen Institute for AI (AI2), AllenNLP team·Allen Institute for AI (Ai2)

Turns PDFs and images into clean Markdown with a 7B vision-language model, keeping tables, equations, handwriting, and multi-column reading order while removing headers and footers. Runs on one 12GB+ GPU at about 1/32 the cost of GPT-4o APIs.

#ocr#vision#llm#foundation-model#huggingface+4
Hugging Face
AI Dataset·2024
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Wikimedia Structured Contents Dataset

Wikimedia Enterprise, Wikimedia Foundation

Provides pre-parsed Parquet snapshots of English and French Wikipedia articles with structured fields (sections, infoboxes, tables, references, images) and credibility signals — optimized for large-scale analysis, retrieval-augmented generation, and model development.

#huggingface#multilingual#nlp#RAG#pandas+3
AI Agent·2024
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Letta

Letta

Gives LLM agents self-editing memory that persists across sessions, so they keep learning about a user instead of resetting each chat. Model-agnostic: bring your own LLM while it handles the memory and agent state, run via API or open source.

#LLM#agent-skills#ai-api#ai-development#ai-agent+3
GitHub
MCP Server·2024
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MCP Python SDK

Model Context Protocol (organization), David Soria Parra +3·Anthropic, Model Context Protocol

Official Python implementation of the Model Context Protocol. Build servers that expose tools, resources, and prompts to any MCP host, or clients that connect to any server; type hints and docstrings become the schemas, so a server fits in ~15 lines.

#mcp#python#github#ai-api#mcp-server+1
GitHub
MCP Server·2024
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Model Context Protocol

David Soria Parra, Justin Spahr-Summers

An open protocol that standardizes how LLM applications connect to external data sources, tools, and services via JSON-RPC — TypeScript-first schema with JSON Schema exports, SDKs, and centralized documentation to enable interoperable integrations.

#mcp#mcp-server#mcp-client#typescript#json+3
GitHub
MCP Server·2024
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MCP TypeScript SDK

Model Context Protocol

Implements the Model Context Protocol in TypeScript, providing server and client libraries to expose tools, resources, and prompts to LLM hosts. Ships Streamable HTTP and stdio transports, optional middleware for Express/Fastify/Hono, and runnable examples for Node/Bun/Deno.

#typescript#mcp#mcp-server#mcp-client#nodejs+4
GitHub
AI Infra·2024
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Docling

Docling Team·IBM Research

Converts PDFs, Office files, HTML, images and audio into one structured DoclingDocument, with deep PDF layout, reading order, table-structure and formula recognition, OCR, and native LangChain/LlamaIndex/Haystack integrations for RAG pipelines.

#github#python#ocr#RAG#ai-tools+4
GitHub
Embodied AI·2024
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ProtoMotions3

Chen Tessler, Yifeng Jiang +7·NVIDIA Research (NVlabs)

GPU‑accelerated framework for training physically simulated humanoid characters and robots using reinforcement learning and motion imitation. Provides a modular multi‑backend simulator stack, large‑scale multi‑GPU training recipes, built‑in motion retargeting and an ONNX deployment pathway to real robots.

#robotics#RL#nvidia#ai-train#ai-deploy+3
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