#python #bert #deepseek #healthcare #ios #llm #mlx #ner #on_device #on_premise #pii #pii_detection #qwen #sovereign_ai #swift #swift_package #swiftui
OpenMed is a local-first healthcare AI that runs on your own device or server, so patient data never leaves your network. It can extract medical entities, remove personal info, and use 1,000+ medical models in Python, Swift, or REST, which helps you work faster while keeping data private and avoiding cloud costs and vendor lock-in.
https://github.com/maziyarpanahi/openmed
OpenMed is a local-first healthcare AI that runs on your own device or server, so patient data never leaves your network. It can extract medical entities, remove personal info, and use 1,000+ medical models in Python, Swift, or REST, which helps you work faster while keeping data private and avoiding cloud costs and vendor lock-in.
https://github.com/maziyarpanahi/openmed
GitHub
GitHub - maziyarpanahi/openmed: Local-first healthcare AI: clinical NER & HIPAA PII de-identification that runs 100% on-device.…
Local-first healthcare AI: clinical NER & HIPAA PII de-identification that runs 100% on-device. 2,200+ medical models, 21 languages, Apple MLX + Python, no cloud, no patient data leaving yo...
#other #agentic_ai #coding #llm #long_horizon
GLM-5.2 is the latest open-source model built for long, complex tasks, featuring a stable 1 million-token context that lets you handle huge projects without losing track of details. It also offers stronger coding skills with flexible thinking modes to balance speed and quality, plus faster performance. You benefit by getting reliable, high-quality results for big software engineering jobs, automated research, or long planning sessions, all while using an open model that saves costs compared to closed alternatives.
https://github.com/zai-org/GLM-5
GLM-5.2 is the latest open-source model built for long, complex tasks, featuring a stable 1 million-token context that lets you handle huge projects without losing track of details. It also offers stronger coding skills with flexible thinking modes to balance speed and quality, plus faster performance. You benefit by getting reliable, high-quality results for big software engineering jobs, automated research, or long planning sessions, all while using an open model that saves costs compared to closed alternatives.
https://github.com/zai-org/GLM-5
GitHub
GitHub - zai-org/GLM-5: GLM-5: From Vibe Coding to Agentic Engineering
GLM-5: From Vibe Coding to Agentic Engineering. Contribute to zai-org/GLM-5 development by creating an account on GitHub.
#python #ai #ai_agents #cli #hypergraph #information_extraction #knowledge #knowledge_graph #llm #python #rag
Hyper-Extract is a tool that uses AI to turn messy documents into clean, structured knowledge like lists, graphs, and linked data with one command. It gives you fast search, easy visual reports, and ready-made templates, so you can save time, understand information faster, and keep adding new documents without rebuilding everything.
https://github.com/yifanfeng97/Hyper-Extract
Hyper-Extract is a tool that uses AI to turn messy documents into clean, structured knowledge like lists, graphs, and linked data with one command. It gives you fast search, easy visual reports, and ready-made templates, so you can save time, understand information faster, and keep adding new documents without rebuilding everything.
https://github.com/yifanfeng97/Hyper-Extract
GitHub
GitHub - yifanfeng97/Hyper-Extract: Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs.…
Hypergraph is more powerful. Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command. - yifanfeng97/Hyper-Extract
#csharp #ai #ai_integration #anthropic #claude #copilot #cursor #game_development #gamedev #gemini #llm #mcp #model_context_protocol #openai #unity #unity3d #videogames
MCP for Unity lets you control your Unity Editor using natural language with AI tools like Claude, Cursor, or VS Code. You can create scenes, edit scripts, manage assets, and run tests just by typing prompts. The benefit to you is faster game development because AI automates repetitive tasks, so you spend less time on manual work and more time creating your game. It is free under the MIT license and works with any MCP client.
https://github.com/CoplayDev/unity-mcp
MCP for Unity lets you control your Unity Editor using natural language with AI tools like Claude, Cursor, or VS Code. You can create scenes, edit scripts, manage assets, and run tests just by typing prompts. The benefit to you is faster game development because AI automates repetitive tasks, so you spend less time on manual work and more time creating your game. It is free under the MIT license and works with any MCP client.
https://github.com/CoplayDev/unity-mcp
GitHub
GitHub - CoplayDev/unity-mcp: Unity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage…
Unity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity. - CoplayDev/unity-mcp
#python #agent_skills #agentic_ai #ai_agents #autonomous_agents #claude #claude_code #claude_skills #codex #coding_agent #context_engineering #copilot #cursor #developer_tools #github_copilot #llm_agents #long_running_agents #manus #multi_agent_systems #pi #planning
This tool makes your AI coding agent keep a plan in files like `task_plan.md` so it never loses its goals when context fills up, you run `/clear`, or it crashes. You get a working memory on disk that auto-recovers past sessions and holds the agent until the plan is truly done, letting complex, multi-step tasks finish reliably without goal drift or repeated errors.
https://github.com/OthmanAdi/planning-with-files
This tool makes your AI coding agent keep a plan in files like `task_plan.md` so it never loses its goals when context fills up, you run `/clear`, or it crashes. You get a working memory on disk that auto-recovers past sessions and holds the agent until the plan is truly done, letting complex, multi-step tasks finish reliably without goal drift or repeated errors.
https://github.com/OthmanAdi/planning-with-files
GitHub
GitHub - OthmanAdi/planning-with-files: Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof…
Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, dete...
#typescript #agent #ai_agent #embedding #llm #local_first #long_term_memory #memory #openclaw_plugin #vector_search
TencentDB Agent Memory is an open-source system that lets AI agents remember your preferences and tasks across sessions using a 4-tier local pipeline, reducing token usage by up to 61% and boosting task success by 51%. This benefits you by saving money on AI costs, improving agent accuracy in long tasks, and ensuring your personal data stays private on your device without needing cloud services.
https://github.com/TencentCloud/TencentDB-Agent-Memory
TencentDB Agent Memory is an open-source system that lets AI agents remember your preferences and tasks across sessions using a 4-tier local pipeline, reducing token usage by up to 61% and boosting task success by 51%. This benefits you by saving money on AI costs, improving agent accuracy in long tasks, and ensuring your personal data stays private on your device without needing cloud services.
https://github.com/TencentCloud/TencentDB-Agent-Memory
GitHub
GitHub - TencentCloud/TencentDB-Agent-Memory: TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations…
TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill, LLM-Wiki, Code-Graph) that are governed...
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#shell #bonsai #llamacpp #llm #mlx #prism_ml #small_models
You can run powerful Bonsai 27B AI models locally on your iPhone, Mac, or laptop without needing cloud servers. The 1-bit version fits in just 3.9 GB, allowing a 27-billion-parameter model (with vision and reasoning) to run on a phone like the iPhone 17 Pro, while the Ternary version offers higher quality at 5.9 GB. This gives you private, fast, and offline AI for chat, image analysis, and tool use, with up to 262K token context and 90–95% of full-precision performance.
https://github.com/PrismML-Eng/Bonsai-demo
You can run powerful Bonsai 27B AI models locally on your iPhone, Mac, or laptop without needing cloud servers. The 1-bit version fits in just 3.9 GB, allowing a 27-billion-parameter model (with vision and reasoning) to run on a phone like the iPhone 17 Pro, while the Ternary version offers higher quality at 5.9 GB. This gives you private, fast, and offline AI for chat, image analysis, and tool use, with up to 262K token context and 90–95% of full-precision performance.
https://github.com/PrismML-Eng/Bonsai-demo
GitHub
GitHub - PrismML-Eng/Bonsai-demo: Bonsai Demo
Bonsai Demo. Contribute to PrismML-Eng/Bonsai-demo development by creating an account on GitHub.
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#python #ai_coding #claude #claude_code #code_review #graphrag #incremental #knowledge_graph #llm #mcp #python #static_analysis #tree_sitter
code-review-graph is a free, local-first tool that builds a structural map of your code to stop AI assistants from re-reading your entire codebase, saving you significant money and time. By using Tree-sitter to parse your code into a graph and tracking changes incrementally, it identifies the exact "blast radius" of a change so your AI only reads the few files that actually matter. This reduces token usage by an average of 82x (up to 528x in best cases), cutting costs and making AI reviews feasible for massive projects like monorepos.
https://github.com/tirth8205/code-review-graph
code-review-graph is a free, local-first tool that builds a structural map of your code to stop AI assistants from re-reading your entire codebase, saving you significant money and time. By using Tree-sitter to parse your code into a graph and tracking changes incrementally, it identifies the exact "blast radius" of a change so your AI only reads the few files that actually matter. This reduces token usage by an average of 82x (up to 528x in best cases), cutting costs and making AI reviews feasible for massive projects like monorepos.
https://github.com/tirth8205/code-review-graph
GitHub
GitHub - tirth8205/code-review-graph: Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase…
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-rep...
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#python #agent #agent_memory #ai_agent #book #coding_agent #context_engineering #large_language_models #llm #mcp #multi_agent #multimodal #rag #reinforcement_learning
This free open-source book and code library teaches you how to build AI Agents using the simple formula: Agent = Model + Context + Tools. You get the full book in English, Chinese, and Tamil, plus ready-to-run code examples for every chapter. The benefit is that you can learn by doing instead of just reading, letting you build real AI agents that search the web, write code, remember users, and work with other agents to solve complex tasks.
https://github.com/bojieli/ai-agent-book
This free open-source book and code library teaches you how to build AI Agents using the simple formula: Agent = Model + Context + Tools. You get the full book in English, Chinese, and Tamil, plus ready-to-run code examples for every chapter. The benefit is that you can learn by doing instead of just reading, letting you build real AI agents that search the web, write code, remember users, and work with other agents to solve complex tasks.
https://github.com/bojieli/ai-agent-book
GitHub
GitHub - bojieli/ai-agent-book: 《深入理解 AI Agent:设计原理与工程实践》(李博杰 著)开源主仓库:全书正文、编译版 PDF 与按章配套代码
《深入理解 AI Agent:设计原理与工程实践》(李博杰 著)开源主仓库:全书正文、编译版 PDF 与按章配套代码 - bojieli/ai-agent-book
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#typescript #a2a #ai_agents #ai_gateway #anthropic #claude #claude_code #cline #codex #copilot #cursor #deepseek #free_ai #gemini #kimi #llm_gateway #mcp #openai #openai_proxy #qwen #token_saver
OmniRoute is a free tool that connects your AI coding apps to 268 providers, including 90+ with free tiers, so you can use top models like Claude or GPT without paying. It automatically switches to another provider if one hits its limit and compresses your requests to cut token usage by up to 95%. You benefit by saving money, avoiding interruptions, and getting unlimited access to powerful AI tools through a single, easy setup.
https://github.com/diegosouzapw/OmniRoute
OmniRoute is a free tool that connects your AI coding apps to 268 providers, including 90+ with free tiers, so you can use top models like Claude or GPT without paying. It automatically switches to another provider if one hits its limit and compresses your requests to cut token usage by up to 95%. You benefit by saving money, avoiding interruptions, and getting unlimited access to powerful AI tools through a single, easy setup.
https://github.com/diegosouzapw/OmniRoute
GitHub
GitHub - diegosouzapw/OmniRoute: Never stop coding. Free MIT AI gateway: one endpoint, 350 providers (90+ free), 1200+ models Kimi…
Never stop coding. Free MIT AI gateway: one endpoint, 350 providers (90+ free), 1200+ models Kimi, Claude, GPT, Gemini, GLM, DeepSeek, MiniMax. Works with Claude Code, Codex, Cursor, OpenCode, Clin...
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#rust #gguf #llm #localai #mlx #skill #unsloth
llmfit is a free terminal tool that automatically checks your computer’s RAM, CPU, and GPU to tell you exactly which large language models will run well on your machine, ranking them by fit, speed, quality, and context. It supports both an interactive visual interface and a command-line mode, works with multi-GPU setups, and suggests the best quantization levels so you never waste time or storage downloading models that won’t work. This saves you from guesswork, trial-and-error testing, and wasted bandwidth, giving you immediate, reliable recommendations for the best local AI models for your specific hardware.
https://github.com/AlexsJones/llmfit
llmfit is a free terminal tool that automatically checks your computer’s RAM, CPU, and GPU to tell you exactly which large language models will run well on your machine, ranking them by fit, speed, quality, and context. It supports both an interactive visual interface and a command-line mode, works with multi-GPU setups, and suggests the best quantization levels so you never waste time or storage downloading models that won’t work. This saves you from guesswork, trial-and-error testing, and wasted bandwidth, giving you immediate, reliable recommendations for the best local AI models for your specific hardware.
https://github.com/AlexsJones/llmfit
GitHub
GitHub - AlexsJones/llmfit: Hundreds of models & providers. One command to find what runs on your hardware.
Hundreds of models & providers. One command to find what runs on your hardware. - AlexsJones/llmfit
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#go #agent #agent_framework #ai_agent #ai_coding #cli #coding_agent #deepseek #developer_tools #ink #llm #prompt_caching #r1 #terminal #tool_use #tui #typescript
Reasonix is a DeepSeek-based AI coding agent for your terminal, desktop, or VS Code, and it uses one local engine for all three. You can set it up with a simple config, add plugins and tools, and run it as a single Go binary, which helps you code faster while keeping token costs lower during long sessions.
https://github.com/esengine/DeepSeek-Reasonix
Reasonix is a DeepSeek-based AI coding agent for your terminal, desktop, or VS Code, and it uses one local engine for all three. You can set it up with a simple config, add plugins and tools, and run it as a single Go binary, which helps you code faster while keeping token costs lower during long sessions.
https://github.com/esengine/DeepSeek-Reasonix
GitHub
GitHub - esengine/DeepSeek-Reasonix: DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability…
DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running. - esengine/DeepSeek-Reasonix
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#python #agent_security #ai_agents #ai_security #benchmark #claude #claude_code #codex #cursor #llm_security #mcp #model_context_protocol #prompt_injection #threat_detection
ADR is an enterprise security system for AI agents that watches what agents do, tests them for attacks, detects risky behavior, and is being used in production at Uber; its paper was accepted to MLSys 2026. The benefit to you is better protection for AI tools like Cursor, Claude Code, and Codex, plus a way to find unsafe actions before they cause harm.
https://github.com/uber/ADR
ADR is an enterprise security system for AI agents that watches what agents do, tests them for attacks, detects risky behavior, and is being used in production at Uber; its paper was accepted to MLSys 2026. The benefit to you is better protection for AI tools like Cursor, Claude Code, and Codex, plus a way to find unsafe actions before they cause harm.
https://github.com/uber/ADR
GitHub
GitHub - uber/ADR: ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed…
ADR secures enterprise AI agents through observability, security benchmarking, and threat detection. Deployed at Uber. - uber/ADR
#python #agent_memory #ai #ai_governance #ai_infrastructure #artificial_intelligence #context_engineering #context_graphs #data_engineering #decision_intelligence #developer_tools #explainable_ai #generative_ai #graph_rag #knowledge_graph #llm #ontology #provenance #python #reasoning #semantic_search
Semantica is an open-source tool that turns messy data into clear, connected knowledge graphs for AI. It helps you track where facts came from, explain AI decisions, find conflicts, and keep systems auditable and trustworthy. This benefits you by making AI easier to trust, easier to check, and safer to use in important work like finance, healthcare, legal, and government.
https://github.com/semantica-agi/semantica
Semantica is an open-source tool that turns messy data into clear, connected knowledge graphs for AI. It helps you track where facts came from, explain AI decisions, find conflicts, and keep systems auditable and trustworthy. This benefits you by making AI easier to trust, easier to check, and safer to use in important work like finance, healthcare, legal, and government.
https://github.com/semantica-agi/semantica
GitHub
GitHub - semantica-agi/semantica: Graph-Native Infrastructure for Context and Accountable AI Systems
Graph-Native Infrastructure for Context and Accountable AI Systems - semantica-agi/semantica
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#python #ai #ast #claude_code #code_analysis #code_understanding #codebase_search #developer_tools #graph_database #knowledge_graph #llm #mcp #mcp_server #memgraph #monorepo #multi_language #python #rag #retrieval_augmented_generation #semantic_search #tree_sitter
Code-Graph-RAG is an open-source tool that reads a codebase, builds a graph of functions, classes, modules, and links, and lets you ask questions, find code, edit safely, and improve code in plain English. It supports many languages and can run as an MCP server for direct use with AI tools. Benefit: you can understand and change large mixed-language projects faster, with less manual searching and fewer mistakes.
https://github.com/vitali87/code-graph-rag
Code-Graph-RAG is an open-source tool that reads a codebase, builds a graph of functions, classes, modules, and links, and lets you ask questions, find code, edit safely, and improve code in plain English. It supports many languages and can run as an MCP server for direct use with AI tools. Benefit: you can understand and change large mixed-language projects faster, with less manual searching and fewer mistakes.
https://github.com/vitali87/code-graph-rag
GitHub
GitHub - vitali87/code-graph-rag: The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with…
The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs - vitali87/code-graph-rag
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#python #cactus #gemini #gemma #llm #on_device_ai
Needle 2 is a very small tool-calling AI model that can run on low memory, work offline, and return structured results like JSON instead of free text. It helps you build apps that call tools, extract data, and fine-tune models more safely and easily, even on devices with limited RAM.
https://github.com/cactus-compute/needle
Needle 2 is a very small tool-calling AI model that can run on low memory, work offline, and return structured results like JSON instead of free text. It helps you build apps that call tools, extract data, and fine-tune models more safely and easily, even on devices with limited RAM.
https://github.com/cactus-compute/needle
GitHub
GitHub - cactus-compute/needle: 14MB foundation model for tiny devices; phones, wearables, smart home, and robots.
14MB foundation model for tiny devices; phones, wearables, smart home, and robots. - cactus-compute/needle
#typescript #agent #agent_harness #agent_os #agentic #ai #ai_agent #ai_agents #artificial_intelligence #claude_code #codex #electron #holaboss #holaos #llm #mcp #memory #model_context_protocol #runtime #typescript #workspace
holaOS is a local-first desktop workspace that lets you run agents like Claude Code, Codex, or its built-in agent together with your tools, files, apps, and shared memory. It supports macOS, Windows, and Linux, includes built-in models or your own keys, and can help you get work done with real browser control, app automation, and ready-made files. This can save you time because one setup works across agents, keeps your context, and lets you produce useful results without switching systems.
https://github.com/holaboss-ai/holaOS
holaOS is a local-first desktop workspace that lets you run agents like Claude Code, Codex, or its built-in agent together with your tools, files, apps, and shared memory. It supports macOS, Windows, and Linux, includes built-in models or your own keys, and can help you get work done with real browser control, app automation, and ready-made files. This can save you time because one setup works across agents, keeps your context, and lets you produce useful results without switching systems.
https://github.com/holaboss-ai/holaOS
GitHub
GitHub - holaboss-ai/holaOS: Open-source All in One AI agent workspace. Run any agent — Claude Code, Codex — across your tools…
Open-source All in One AI agent workspace. Run any agent — Claude Code, Codex — across your tools (100+ integrations + MCP), apps, browser, and files, with shared memory. Built-in models or BYOK. -...
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#python #cli #consumer_gpu #dpo #fine_tuning #gguf #huggingface #llm #llmops #local_ai #local_llm #lora #low_vram #machine_learning #ollama #peft #python #pytorch #qlora #sft #transformers
Soup is a tool that helps you fine-tune and post-train large language models with one command, using one config file and little setup. It can work on a local GPU, even a 4 GB laptop GPU for an 8B model with layer streaming, so you can train without SSH or cloud hassle. This saves time, reduces setup pain, and makes model training easier to start and manage.
https://github.com/MakazhanAlpamys/Soup
Soup is a tool that helps you fine-tune and post-train large language models with one command, using one config file and little setup. It can work on a local GPU, even a 4 GB laptop GPU for an 8B model with layer streaming, so you can train without SSH or cloud hassle. This saves time, reduces setup pain, and makes model training easier to start and manage.
https://github.com/MakazhanAlpamys/Soup
GitHub
GitHub - MakazhanAlpamys/Soup: Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU.
Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup
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#python #agent #agent_security #ai_infra #ai_red_teaming #ai_security #llm #llm_evaluation #llm_jailbreak #llm_security #mcp_scan #openclaw_security #prompt_injection #prompt_security #scanner #security #security_tools #skill_scanner #skills_security #vulnerability
A.I.G (AI-Infra-Guard) is a Tencent Zhuque Lab tool for AI red teaming and security checks. It scans AI infrastructure, MCP servers, agent skills, and jailbreak risks, and it can run with Docker, a web UI, or an API. This helps you find weak points early, understand real security risks, and fix problems before they affect your AI systems.
https://github.com/Tencent/AI-Infra-Guard
A.I.G (AI-Infra-Guard) is a Tencent Zhuque Lab tool for AI red teaming and security checks. It scans AI infrastructure, MCP servers, agent skills, and jailbreak risks, and it can run with Docker, a web UI, or an API. This helps you find weak points early, understand real security risks, and fix problems before they affect your AI systems.
https://github.com/Tencent/AI-Infra-Guard
GitHub
GitHub - Tencent/AI-Infra-Guard: A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent…
A full-stack AI Red Teaming platform securing AI ecosystems via OpenClaw Security Scan, Agent Scan, Skills Scan, MCP scan, AI Infra scan and LLM jailbreak evaluation. - Tencent/AI-Infra-Guard
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#typescript #agent_runtime #ai #ai_agent #apache #cli #desktop #electron #event_sourcing #llm #local_first #maka #tool_use #typescript
Maka is a local-first agent workspace that runs on your computer, lets you use your own model connection, and can read files, run tools, and save recoverable work records. This helps you keep data local, control permissions, and recover or continue work more safely.
https://github.com/apache/maka
Maka is a local-first agent workspace that runs on your computer, lets you use your own model connection, and can read files, run tools, and save recoverable work records. This helps you keep data local, control permissions, and recover or continue work more safely.
https://github.com/apache/maka
GitHub
GitHub - apache/maka: Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission…
Apache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorded as an append-only log. - apache/maka
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