Search Results for "multi search"
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44 projects for "multi search" with 2 filters applied:
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Telegram Search
AI-powered Telegram chat backup and semantic search tool system
Telegram Search is a self-hosted tool designed to export, back up, and intelligently search Telegram chat histories using modern AI techniques. It addresses the limitations of Telegram’s native search by enabling accurate retrieval of messages across languages through advanced tokenization and semantic understanding. Telegram Search processes chat data into searchable formats, including vector embeddings, which allow users to perform fuzzy and meaning-based searches instead of relying solely... -
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Deep Search Agent
Implement a concise and clear Deep Search Agent from 0
Deep Search Agent is an experimental demonstration project that showcases an autonomous AI agent designed to perform multi-step research and information gathering tasks. The repository illustrates how large language models can be orchestrated with tools and planning logic to execute complex search workflows rather than single-prompt responses. -
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SearChat
Search + Chat = SearChat(AI Chat with Search)
SearChat is an open-source conversational search platform that combines traditional web search engines with large language model reasoning to create an interactive research environment. The project is designed to transform the process of web searching into a multi-turn conversational experience where users can refine queries and explore results through dialogue. Built using a modern monorepo architecture, the system includes a Node.js and Koa backend alongside a Vue 3 and TypeScript frontend that delivers a responsive chat interface. ... -
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Vedana
Open source multi-agent RAG over a knowledge graph
Vedana is an open-source multi-agent RAG system built around a typed knowledge graph. It is designed for questions that require structure, completeness, and traceability instead of simple text similarity. The system lets agents navigate data step by step through Cypher queries, vector search, document lookup, and source verification. Its architecture combines a knowledge graph, pgvector-based embeddings, incremental ETL, and a backoffice interface for chat, metrics, prompt tuning, and data loading. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Zvec
A lightweight, lightning-fast, in-process vector database
Zvec is an open-source, lightweight, in-process vector database designed to embed directly into applications and serve fast similarity search workloads without the overhead of a separate server process. Developed by Alibaba’s Tongyi Lab, it positions itself as the “SQLite of vector databases” by being easy to integrate, minimal in dependencies, and capable of handling high throughput with low latency on edge devices or small systems. Zvec excels at approximate nearest neighbor search and... -
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MemFree
Hybrid AI Search Engine & AI Page Generator
memfree is an open source hybrid AI search engine and page generation platform designed to help users retrieve information from both personal knowledge bases and the public web through a unified interface. The project combines retrieval-augmented search with AI summarization to deliver concise answers instead of forcing users to manually sift through multiple sources. It supports multiple AI models and search providers, enabling flexible configuration depending on cost, performance, or... -
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macai
All-in-one native macOS AI chat application
...The app supports a wide range of providers, including OpenAI, Anthropic, Google Gemini, xAI, Perplexity, and Ollama, allowing users to switch between local and cloud-based models without changing tools. It includes advanced features such as multimodal capabilities, image generation, search integration, and reasoning workflows, making it more than just a simple chat client. The application also emphasizes privacy by avoiding telemetry and offering optional iCloud synchronization for cross-device continuity. With its combination of native performance, multi-provider flexibility, and user-friendly design, macai serves as a comprehensive AI hub for macOS users. -
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Semantra
Multi-tool for semantic search
Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. The system runs... -
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Deep Research Web UI
AI-powered research assistant that performs iterative, deep research
Deep Research Web UI is an AI-powered research assistant interface designed to automate complex, multi-step information gathering workflows through a combination of search engines, web scraping, and large language models. It operates as a front-end system for deep research agents that iteratively refine queries, retrieve information from multiple sources, and synthesize structured outputs into coherent reports. The platform emphasizes long-horizon reasoning, allowing users to explore topics in depth rather than receiving shallow, single-response answers. ... -
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Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. ... -
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Feynman
The open source AI research agent
Feynman is a command-line AI research agent designed to automate complex research workflows by orchestrating multiple specialized agents that collaborate to gather, analyze, and synthesize information into structured outputs. It operates as a “Claude Code for research,” allowing users to input natural language queries and receive fully developed, source-grounded research briefs, literature reviews, or experimental analyses. The system is built around a multi-agent architecture that includes... -
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security-audit
A coding-agent skill for multi-phase security audits
security-audit is a coding-agent skill for running structured security audits on software repositories. It organizes the audit into multiple phases so the agent does not simply search randomly for vulnerabilities. The workflow begins with reconnaissance, then moves into parallel hunting across attack classes such as injection, access control, business logic, cryptography, feature abuse, and chained attacks. Findings are then challenged through separate validation agents to reduce false... -
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ReCall
Learning to Reason with Search for LLMs via Reinforcement Learning
...The framework uses reinforcement learning to train models to perform these tool calls effectively while solving multi-step reasoning tasks. -
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SimpleMem
SimpleMem: Efficient Lifelong Memory for LLM Agents
SimpleMem is a lightweight memory-augmented model framework that helps developers build AI applications that retain long-term context and recall relevant information without overloading model context windows. It provides easy-to-use APIs for storing structured memory entries, querying those memories using semantic search, and retrieving context to augment prompt inputs for downstream processing. Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory... -
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EverMemOS
Long-term memory OS for AI with structured recall and context awarenes
EverMemOS is an open-source memory operating system built to give AI agents long-term, structured memory. It captures conversations, transforms them into organized memory units, and enables agents to recall past interactions with context and meaning. Instead of treating each prompt independently, it builds evolving user profiles, tracks preferences, and connects related events into coherent narratives. Its architecture combines memory storage, indexing, and retrieval with agent-level... -
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PokeeResearch-7B
Pokee Deep Research Model Open Source Repo
...It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response. The repository includes evaluation results on multi-step QA and research benchmarks, illustrating how web-time context boosts accuracy. Because the system is modular, you can swap the search component, reader, or policy to fit private deployments or different data domains. It’s aimed at developers who want a transparent, hackable research agent they can run locally or wire into existing workflows. -
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AingDesk
AI assistant that supports knowledge bases, model APIs
...The software enables users to run local AI models or connect to external model APIs through a unified interface. One of its primary goals is to simplify the process of building knowledge-based assistants by allowing users to create local knowledge bases that the AI can search and analyze. The system supports additional features such as web search, intelligent agent workflows, and multi-model conversations within a single session. AingDesk can be deployed locally on personal machines or installed as a server using containerized environments. Its design emphasizes accessibility, making it suitable for both beginners and experienced developers who want to experiment with AI tools. -
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GitMCP
Turn any GitHub repository into an MCP documentation server for AI
GitMCP is an open source remote Model Context Protocol (MCP) server designed to transform GitHub repositories into structured documentation hubs that AI assistants can query directly. It enables developer-focused AI tools to access up-to-date project documentation and source code so that responses are grounded in real repository content rather than outdated training data. By exposing repository documentation and code through standardized MCP tools, GitMCP helps reduce incorrect or fabricated... -
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Anything to NotebookLM
Multi-source content processor for NotebookLM
Qiaomu Anything to NotebookLM is a Claude Code skill that turns many types of source material into structured NotebookLM-ready outputs. It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It... -
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kg-gen
Knowledge Graph Generation from Any Text
kg-gen is an open-source framework developed by the STAIR Lab that automatically generates knowledge graphs from unstructured text using large language models. The system is designed to transform plain text sources such as documents, articles, or conversation transcripts into structured graphs composed of entities and relationships. Instead of relying on traditional rule-based extraction techniques, KG-Gen uses language models to identify entities and their relationships, producing... -
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Cube Studio
Cube Studio open source cloud native one-stop machine learning
Cube Studio is an open-source, cloud-native end-to-end machine learning and AI platform designed to support the full lifecycle of AI development — from data preparation and interactive notebook coding to distributed training, model tuning, and deployment in production-ready environments. It provides a unified interface where teams can manage data sources, track datasets, and build pipelines using drag-and-drop workflow orchestration, making it accessible for both engineers and data... -
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Oh My OpenCode Slim
Slimmed, cleaned and fine-tuned oh-my-opencode fork
Oh My OpenCode Slim is a lightweight, optimized fork of the broader oh-my-opencode ecosystem, designed to deliver high-performance multi-agent coding workflows while significantly reducing token consumption and system overhead. It retains the core concept of orchestrating multiple specialized AI agents but streamlines their configuration, execution, and communication to make the system more efficient and practical for everyday use. The framework introduces a structured “pantheon” of agents,... -
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Datapizza AI
Build reliable Gen AI solutions without overhead
Datapizza AI is a lightweight framework for building modular, multi-agent AI systems that collaborate to solve complex tasks through orchestration and tool usage. The project focuses on simplicity and transparency, enabling developers to construct agent-based workflows without the heavy abstractions and dependencies often found in larger AI frameworks. It provides a flexible architecture where individual agents can be assigned specialized roles, such as web search, reasoning, or domain-specific expertise, and can communicate with each other to complete tasks collaboratively. ... -
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MiroThinker
MiroThinker is an open source deep research agent
MiroThinker is an open-source deep research AI agent designed to perform complex reasoning, information gathering, and predictive analysis tasks. The system focuses on enabling long-horizon research workflows by allowing the agent to interact repeatedly with external tools, search systems, and data sources while refining its reasoning through iterative steps. Rather than simply generating responses from a single prompt, the agent performs structured multi-step reasoning processes that involve searching for information, analyzing evidence, and synthesizing conclusions. The platform is optimized for research tasks such as financial forecasting, knowledge discovery, and large-scale information synthesis. ... -
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Conversational Health Agents (CHA)
A Personalized LLM-powered Agent Frameworks
CHA, or Conversational Health Agents, is an open-source framework designed to build intelligent healthcare assistants powered by large language models and external data sources. The system enables developers to create personalized AI agents that can interact with users through natural language while performing multi-step reasoning and task execution. It integrates orchestration capabilities that allow the agent to gather information from APIs, knowledge bases, and external services in order...
