Search Results for "answer"
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Showing 17 open source projects for "answer"
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1
Buzz
A hive mind communication platform
...The platform includes channels, threads, direct messages, canvases, media sharing, full-text search, and a tamper-evident audit trail. Agents receive their own identities and memberships, allowing them to answer questions, review patches, manage workspaces, and run tools without impersonating users. YAML workflows can respond to messages, reactions, schedules, and webhooks while preserving execution traces. Buzz provides a Tauri desktop client, browser access, a JSON-oriented CLI, MCP support, and ACP integrations for popular coding agents. ... -
2
Dexter
An autonomous agent for deep financial research
...It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch data), and self-validation mechanisms: after getting results, Dexter checks its own outputs and refines them until it is confident about its answer. This means it's more than a simple script — it’s a research assistant that loops through analysis steps until convergence. -
3
agent-browser
Browser automation CLI for AI agents
agent-browser is a toolkit that embeds AI agent capabilities directly into the web browser, enabling agents to interact with web content, scripts, and user actions while maintaining security boundaries that respect user privacy and browser constraints. It effectively provides a sandbox where AI agents can read, scroll, click, and interpret pages in context, allowing them to automate workflows, answer questions about page content, or generate structured summaries directly from the user’s current tab. The project emphasizes standards and safety, defining interfaces that let agents access DOM data, interpret events, and generate actionable insights without exposing sensitive credential-level access or violating policy boundaries. ... -
4
LobsterAI
Your 24/7 all-scenario AI agent that gets work done for you
...It also supports remote control through messaging platforms, making it possible to trigger tasks from a phone. LobsterAI is designed for users who want an agent that can actually perform work, not just answer questions. -
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5
Personal AI Infrastructure
Agentic AI Infrastructure for magnifying HUMAN capabilities
...Unlike once-stateless chatbots, this platform captures context, memory, goals, preferences, and feedback to enable an AI that understands you and improves over time, using a full agentic stack rather than simple question-answer loops. PAI blends tools like browsing, code editing, execution, and more into a continuous Observe → Think → Plan → Execute → Verify → Learn cycle, letting the system refine its behavior with each use. Its architecture supports long-term memory, verification of actions, and ongoing self-improvement, blurring the line between “assistant” and persistent, evolving collaborator. -
6
zhengxi-views
Zheng Xi (Efonda Fund Manager) Investment Research Agent Skill
...The project organizes a corpus of Zheng Xi’s views from 2012 to 2026, then connects those materials to an extracted investment framework. It also includes real fund data snapshots for managed funds and broader fund comparison workflows. The skill can answer source-grounded questions, explain methodology, compare funds, and score funds against Zheng Xi’s stated framework. It is positioned as a research and learning assistant, not as financial advice. -
7
i-have-adhd
A skill for your coding agent to stop it from burying the answer
i-have-adhd is a compact instruction skill that makes coding assistants produce more direct and ADHD-friendly responses. It asks the agent to lead with the next action instead of opening with background, praise, or conversational filler. Multi-step tasks are numbered, tangents are suppressed, and lists are intentionally kept short. The style also restates the current state, makes completed progress visible, and describes errors without unnecessary drama. Every response should end with one... -
8
Clawra
Openclaw as your girlfriend
...Rather than being a static chatbot tied to a corporate ecosystem, Clawra runs locally or on a private server, giving users full control over the software and data that back her behavior. She is designed not just to answer questions but to maintain a persistent character with memory, backstory, and the ability to present visual outputs like generated selfies through integrated image tools, blending conversational AI with a playful persona. Clawra has captured attention as an experimental project showcasing how far open-source agents can be pushed in creating engaging and personalized interactions, with community interest spiking around her capabilities. -
9
Claude Code Video Vision
Give Claude the ability to watch and understand videos
...Instead of attempting to directly interpret raw video streams, the system extracts key frames using tools like ffmpeg and processes audio through transcription engines, converting both visual and auditory signals into structured inputs for the model. The result is a perception layer that feeds images and timestamped transcripts into Claude, allowing it to analyze events, answer questions, and summarize content with contextual awareness. The system dynamically adapts how much data it extracts based on the user’s query, adjusting frame rate, resolution, and time windows to optimize both performance and token efficiency. It supports multiple backends for audio processing, including local and cloud-based options, enabling flexible deployment depending on privacy or performance requirements. -
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10
Gemini Fullstack LangGraph Quickstart
Get started w/ building Fullstack Agents using Gemini 2.5 & LangGraph
...The backend agent dynamically generates search queries based on user input, retrieves information via the Google Search API, and performs reflective reasoning to identify knowledge gaps. It then iteratively refines its search until it produces a comprehensive, well-cited answer synthesized by the Gemini model. The repository provides both a browser-based chat interface and a command-line script (cli_research.py) for executing research queries directly. For production deployment, the backend integrates with Redis and PostgreSQL to manage persistent memory, streaming outputs, & background task coordination. -
11
TypeAgent Python
Structured RAG: ingest, index, query
TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language interactions into structured representations that can be processed by deterministic software components. This design allows the system to combine the flexibility of language models with the reliability of traditional programming logic. ... -
12
Pal
A personal context-agent that learns how you work
...The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information. Instead of acting as a simple chatbot, Pal continuously builds a structured database of a user’s knowledge and context so it can answer questions, recall information, and assist with future tasks more effectively. The agent can perform web research, summarize information, and store insights so that useful discoveries are not lost across conversations or sessions. Over time, the agent learns from interactions, remembers patterns that worked well, and applies those learnings to similar tasks in the future, allowing it to improve without requiring additional model training. -
13
Microsoft Learn MCP Server
Official Microsoft Learn MCP Server, powering LLMs and AI agents
...Rather than relying on training data that may be outdated or incomplete, MCP servers let agents like GitHub Copilot, Claude, or other LLM-based tools search and pull context directly from up-to-date Microsoft Learn content, including Azure, .NET, and other tech docs. By connecting to the MCP endpoint, coding agents can answer questions, retrieve code examples, and offer best practices grounded in authoritative sources without requiring API keys or manual browser searches. This capability helps eliminate hallucinations, improve accuracy, and streamline developer workflows by keeping relevant tech guidance close at hand. -
14
askimo
AI desktop app with local RAG, privacy-first, multi-model support
...It supports popular AI providers such as OpenAI, Anthropic (Claude), Gemini, Ollama, LocalAI, Docker AI, LM Studio, and X AI, allowing users to switch models easily without vendor lock-in. A core feature of Askimo is Retrieval-Augmented Generation (RAG). Users can connect the app to local files, documents, and project folders so the AI can answer questions using their own knowledge base. All indexing, search, and history storage happen locally, ensuring sensitive data stays on the user’s machine. Askimo is built around project-based sessions, customizable conversation styles (directives), and searchable local history, making it well suited for document analysis, research, planning, and daily business workflows. ... -
15
SolidGPT
Developer AI Persona Search Agent
SolidGPT is a AI searching assistant for developers that helps code and workspace semantic search. -
16
LangChain Apps on Production with Jina
Langchain Apps on Production with Jina & FastAPI
Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own... -
17
This article talks about how to create a chatterbot that can serve as an interactive help agent. The bot has been "taught" to answer FAQs about a system. It can help solve petty issues for users quickly or point them to a human agent.
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