Search Results for "act"
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Showing 9 open source projects for "act"
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SillyTavern
LLM Frontend for Power Users
Mobile-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI, OpenRouter, Claude, Scale), VN-like Waifu Mode, Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters... -
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LLM Agents Papers
Must-read Papers on LLM Agents
LLM Agent Papers is an open-source repository that curates research papers related to large language model agents and autonomous AI systems. The project organizes academic literature that explores how language models can act as agents capable of reasoning, planning, and interacting with external tools or environments. Rather than providing software code, the repository functions as a structured knowledge base that helps researchers navigate the rapidly expanding field of agent-based AI research. Papers are categorized into thematic groups covering topics such as tool use, planning algorithms, reasoning strategies, and multi-agent collaboration. ... -
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Emscripten
Emscripten: An LLVM-to-WebAssembly Compiler
Emscripten is a complete open-source compiler toolchain that transforms C, C++, and other LLVM-based source code into WebAssembly (and JavaScript), enabling native‑like applications to run in web browsers, Node.js, and other Wasm environments. While Emscripten mostly focuses on compiling C and C++ using Clang, it can be integrated with other LLVM-using compilers (for example, Rust has Emscripten integration, with the wasm32-unknown-emscripten and asmjs-unknown-emscripten targets). Emscripten... -
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History LLMs
Information hub for our project training the largest possible LLMs
...This approach enables researchers in the humanities and social sciences to explore how people at different historical moments would have discussed world events, norms, and ideas without later developments influencing the model. It contains documentation about model families like Ranke-4B, which are trained from scratch with historical corpora and can act as “aggregate witnesses” to the textual culture of their era. -
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Sage Chat
Chat with any codebase in under two minutes | Fully local
...Developers can ask natural language questions about a project, and the system responds with explanations supported by references to the relevant code, documentation, or external technical resources. The project aims to act as a contextual knowledge layer for software teams by combining language models with repository indexing and documentation retrieval. Sage can operate locally or connect to external AI services, depending on the configuration, providing flexibility for privacy-sensitive environments. -
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Cake
Distributed LLM and StableDiffusion inference
...The tool is designed to work with multiple protocols and supports dynamic rule definitions so that incoming and outgoing connections can be routed, rewritten, or logged according to user-defined policies. Unlike many simple proxies, Cake can act as a full connection broker: it can bind to arbitrary interfaces, handle simultaneous upstream/downstream sessions, and apply traffic rules on the fly. This makes it suitable for troubleshooting tricky network behavior, simulating network conditions, or chaining services in a modular test environment. -
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Tongyi DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
DeepResearch (Tongyi DeepResearch) is an open-source “deep research agent” developed by Alibaba’s Tongyi Lab designed for long-horizon, information-seeking tasks. It’s built to act like a research agent: synthesizing, reasoning, retrieving information via the web and documents, and backing its outputs with evidence. The model is about 30.5 billion parameters in size, though at any given token only ~3.3B parameters are active. It uses a mix of synthetic data generation, fine-tuning and reinforcement learning; supports benchmarks like web search, document understanding, question answering, “agentic” tasks; provides inference tools, evaluation scripts, and “web agent” style interfaces. ... -
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code-act
Official Repo for ICML 2024 paper
code-act is a research framework for building intelligent language-model agents that interact with their environment through executable code actions. The system proposes a unified action representation where language models produce Python code that can be executed directly, allowing the model to interact with external tools and environments in a structured way. -
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Agents 2.0
An Open-source Framework for Data-centric Language Agents
...The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During training, the system performs a forward execution where the agent completes a task and records the trajectory of prompts, outputs, and tool usage. A prompt-based loss function is then applied to evaluate the quality of the outcome, generating language-based gradients that guide improvements to the agent pipeline. -
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