Projects sharing features with Gemini Search

Colanode is a local-first collaboration platform designed for shared documents, chat, and databases. It provides a self-hosted suite for team collaboration and knowledge management, allowing users to maintain full control over their data and privacy on their own infrastructure. The platform is distinguished by a synchronization engine that uses WebSockets for real-time data broadcasting and a local-first approach to ensure work continues offline. It incorporates AI-powered retrieval through vector-based semantic search, enabling users to find information based on meaning across documents and

Azure Docs is the official technical documentation repository for Microsoft Azure, the cloud computing platform. It provides comprehensive guidance on the full spectrum of Azure services, covering everything from core infrastructure components like virtual machines, Kubernetes clusters, and serverless computing to platform services for AI, machine learning, data analytics, and storage. The documentation details how to provision, manage, and govern cloud resources at scale, including policy enforcement, identity management, and cost optimization. The documentation distinguishes Azure through i

PandaWiki is an AI-powered wiki and knowledge base platform that integrates large language models to automate content creation and information retrieval. It functions as a retrieval-augmented generation system for building technical wikis, FAQs, and documentation sites that provide automated answers grounded in a private knowledge base. The system acts as an enterprise knowledge bot, allowing the deployment of AI chatbots via web widgets and messaging applications like Discord. It further extends its operational capabilities by integrating with Model Context Protocol servers to connect the AI

Scira is an AI-powered search and synthesis engine that uses agentic research workflows to find and organize information from the web and academic sources. The system breaks complex queries into multi-step plans and generates grounded answers with inline citations for verification. The platform distinguishes itself by executing Python code within isolated sandboxes to perform data analysis and create visual charts from retrieved data. It also implements retrieval-augmented generation to perform semantic searches across uploaded documents, including PDFs and CSV files, and integrates with clou

Search with Lepton is a conversational search engine that combines a large language model with web search APIs to answer user queries in natural language conversation. It is designed as a demonstration application that shows how an LLM can generate conversational responses from real-time web search results, and it caches completed search results so they can be shared and revisited without repeating the original query. The application can be deployed to a cloud platform with a single command, making it easy to launch as a remote service. It maintains dialogue context across multiple turns by s

Bella is an AI companion system featuring a conversational interface for interacting with local and cloud artificial intelligence models. It integrates a local model manager to automate the download and organization of machine learning weights and a speech-to-text transcription engine to enable hands-free interaction. The project includes an emotion visualization system that uses cross-fading video playback to represent the agent's internal state. This is driven by a state-driven emotion mapping system and an interaction-based affinity system that tracks user engagement frequency to trigger s

This project is a browser extension and toolset designed to integrate real-time web search results and extracted page content into large language model prompts. It functions as a web search integrator and content parser that feeds current internet data into conversational AI interfaces to ensure responses are grounded in evidence. The system includes a prompt template manager for storing and executing pre-defined structures that trigger automated web crawls. It enables deep research workflows by performing comprehensive searches to generate detailed responses supported by citations and links

Geekai is a multi-model AI platform and SaaS framework designed to deploy and manage AI agents and multimodal models through a unified interface. It serves as a multimodal AI gateway, providing centralized access to large language models and generative tools for text, image, audio, and video production. The project functions as an AI agent orchestrator, allowing for the definition of specialized personas and the import of external workflows and knowledge bases. It distinguishes itself by providing a complete commercial service layer, including credit-based billing, subscription management, an

Morphic is an AI model aggregator and search engine designed to synthesize grounded answers with citations by coordinating large language models and external web search providers. It functions as a self-hosted AI gateway that connects to multiple model providers and local endpoints, utilizing a dynamic selector to route requests between different backends based on API key availability. The project features a generative UI framework that renders rich, interactive components by streaming JSON specifications instead of standard markdown. It also incorporates retrieval augmented generation capabi

freegpt-webui is a self-hosted web interface for interacting with large language models. It provides a chat-based frontend designed for communicating with GPT 3.5 and GPT 4 models. The application enables API keyless chat, allowing users to access conversational AI for text generation and information retrieval without providing or managing personal authentication keys. The system handles model integration through a reverse-proxy gateway and supports asynchronous stream processing for real-time text generation. User preferences and conversation history are persisted via client-side session st

Shell GPT is an AI-powered command-line interface that generates shell commands and source code from natural language prompts. It serves as a terminal-based tool for automating technical tasks, producing executable commands, and generating code snippets directly within the shell. The tool distinguishes itself through a read-eval-print loop for interactive chatting and the ability to maintain stateful conversational history via named sessions. It supports flexible backend routing, allowing users to connect to cloud-based APIs or local language model hosts for offline operation and data privacy

This project is a conversational interface framework and UI component library designed for building applications integrated with large language models. It provides a standardized provider integration layer to connect front-end components to various AI backends, alongside a dedicated response rendering engine for displaying generated content. The framework specializes in hybrid generative-UI composition, blending traditional interactive elements with dynamic model outputs. It features a protocol-driven system for converting structured data streams into interactive cards and includes tools for

This project is a reference implementation and application template for Retrieval-Augmented Generation (RAG). It integrates Azure OpenAI with Azure AI Search to enable conversational chat interfaces that provide grounded responses based on private enterprise data. The system is distinguished by its multimodal AI interface, allowing it to process and reason over combined text, image, and PDF content. It employs a hybrid search architecture that combines vector and keyword retrieval with semantic reranking to prioritize the most relevant documents for prompt augmentation. The project covers a

FreeAskInternet is a self-hosted AI search aggregator and answer generation platform. It uses a language model to synthesize results from multiple web search engines into a single, comprehensive response, integrating with SearXNG to gather raw web data. The system is designed for local deployment through Docker containerization, allowing the search aggregator and user interface to run in isolated environments. It supports local language model integration and provides a provider-agnostic interface to switch between different local or remote model backends. The platform handles search and synt

Qwen is a comprehensive framework for large language model development, serving, and deployment. It provides a complete ecosystem for transformer-based sequence modeling, offering base models alongside specialized tools for instruction-tuned alignment, fine-tuning, and long-context inference. The project is designed to support both research and production environments, enabling users to train, optimize, and host generative models locally or across distributed hardware. The framework distinguishes itself through its focus on high-performance serving and extensibility. It features a high-perfor

GLM-4 is a large language model and fine-tuning framework designed for human-like text production, complex reasoning, and multilingual conversation. It functions as a multimodal system capable of processing high-resolution visual content and as a long-context model designed to analyze documents with a context window of up to one million tokens. The project differentiates itself through a function calling interface that enables AI agent development by connecting the model to external APIs and real-time web browsing. It includes specialized capabilities for generating functional programming cod

This project is a manual reconstruction of the Llama 3 transformer architecture implemented as a PyTorch neural network. It serves as a reference for the internal mathematical structure and tensor flow of a transformer-based language model designed for next token prediction. The implementation focuses on building the model from scratch using basic matrix operations and tensor manipulations. It demonstrates the manual construction of core components, including rotary positional embeddings, multi-head self-attention, and root mean square normalization. The codebase covers the full inference pi

Mistral Inference is a library for running Mistral large language models on a GPU, generating text from prompts with token streaming. It loads pretrained model weights from local disk or a remote registry into GPU memory, then produces output tokens one by one for real-time display in interactive applications. The library supports multimodal prompts that accept image URLs alongside text, enabling visual description and reasoning. It includes content safety guardrails that scan generated text against predefined policies to block or flag policy violations. For structured interactions, it provid

Baichuan-7B is an open-source 7 billion parameter bilingual Transformer model designed for text generation and few-shot learning across Chinese and English. It is built on a large Transformer architecture trained on a bilingual corpus, enabling it to produce coherent text in both languages from a single model. The model incorporates several optimization techniques that distinguish it from standard large language models. It uses rotary position embeddings that can extrapolate to longer sequences than seen during training, allowing context extension beyond the original 4096-token training lengt

Fern is a toolset for managing API specifications, generating type-safe client libraries, and producing hosted developer documentation. It provides a utility for validating, transforming, and exporting API definitions into standardized OpenAPI formats, serving as a system to maintain a consistent source of truth for API designs. The project differentiates itself through an automated SDK distribution pipeline that publishes generated libraries to package managers such as npm, PyPI, Maven, and NuGet. It also includes an AI-powered search assistant trained on API and SDK specifications to answer

This is an open-source framework for building stateful, durable AI agents that run on Cloudflare Workers. It provides a runtime for long-lived agents that maintain a persistent identity, local SQL storage, and real-time connections, utilizing a lifecycle where agents hibernate when idle and wake on demand. The project distinguishes itself through its multi-channel orchestration, allowing a single agent to be deployed across voice, email, and chat interfaces with unified state. It implements the Model Context Protocol for standardized tool and data exchange and includes a dedicated framework f

InternLM is a large language model and a comprehensive suite of weights designed for text generation and complex reasoning. It functions as an inference engine for serving responses, a fine-tuning framework for adjusting model weights, and a platform for building autonomous AI agents. The system is capable of processing long-context input sequences up to one million tokens for document analysis. It employs chain-of-thought reasoning to solve knowledge-intensive tasks by generating intermediate logic steps before producing a final answer. The project covers model weight optimization through s

Llama 3 is a collection of pretrained, autoregressive transformer-based models designed for natural language generation, reasoning, and complex instruction following. It functions as a generative AI framework that provides the infrastructure for managing model weights, executing neural network inference, and handling computational workloads across diverse knowledge domains. The project distinguishes itself through an integrated AI safety toolkit that employs secondary classification filtering to inspect inputs and outputs, ensuring adherence to usage compliance and safety standards. It suppor

This project is an LLM-powered web crawler and data extractor that uses large language models to navigate websites and parse content into structured JSON or Markdown formats. It functions as an automated browser orchestrator and domain discovery engine, interpreting plain English instructions to identify relevant pages and extract specific information. The system distinguishes itself through agentic browser automation, allowing it to perform human-like interactions such as clicking buttons and scrolling based on natural language commands. It employs goal-oriented crawling to analyze website s

DataHub is a metadata management platform designed to unify technical, operational, and business context across diverse data ecosystems. By utilizing a graph-based metadata model and an event-driven ingestion architecture, it creates a centralized source of truth that maps complex data relationships, lineage, and ownership. This foundational framework enables organizations to maintain a synchronized view of their data landscape, supporting both human-led discovery and automated data operations. The platform distinguishes itself through its focus on grounding artificial intelligence and autono

Planning with files is an enterprise knowledge graph platform designed to transform unstructured organizational data into a searchable, interconnected network. By utilizing a graph-based retrieval-augmented generation engine, the system grounds language model outputs in verified internal data, ensuring that responses are explainable, traceable, and free from hallucinations. The platform distinguishes itself through a focus on data sovereignty and secure, private infrastructure deployment. It enables organizations to maintain full control over sensitive information by processing data locally o