Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 3
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159 projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" with 2 filters applied:
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EasySend is a no-code platform that transforms customer journeysEvolve forms into smart, AI-powered digital workflows that streamline your data intake and elevate customer experiences.
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Simplify Time-consuming and Overly Complicated Financial Processes.Zahara's cloud based platform automates budget management, suppliers, purchase requisitions, multi-level purchase approvals, deliveries and invoice reconciliation and approvals. Zahara integrates with most leading accounting software such as QuickBooks Online and Xero to give expanding SME's real time visibility and centralized control of their purchasing. Zahara can be used to control spend in an organization. We take the initial request to buy something and automate the approval process and sending of the PO to the Vendor. Deliveries can be receipted, vendors invoices matched and processed and then exported to finance. Zahara adds control yet speeds up processing.
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LangServe
Helps developers deploy LangChain runnables and chains as a REST API
...Instead of manually writing API endpoints, developers can use LangServe to automatically generate a server that exposes LangChain workflows through HTTP interfaces. The framework is built on top of FastAPI and uses Pydantic for request validation and structured data handling. It also includes client libraries that allow developers to interact with deployed chains from Python or JavaScript applications. LangServe is commonly used to deploy AI applications such as chatbots, document analysis pipelines, and agent-based systems that require scalable access through APIs. -
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chatd
Chat with your documents using local AI
chatd is an open-source desktop application that allows users to interact with their documents through a locally running large language model. The software focuses on privacy and security by ensuring that all document processing and inference occur entirely on the user’s computer without sending data to external cloud services. It includes a built-in integration with the Ollama runtime, which provides a cross-platform environment for running large language models locally. The application typically runs models such as Mistral-7B and allows users to load and analyze documents while asking questions in natural language. Unlike many document-chat tools that require manual installation of model servers, chatd packages the model runner with the application so that users can start interacting with documents immediately after launching the program. -
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LangChain for Java
LangChain4j is an open-source Java library
...The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. Its architecture includes abstractions for prompts, chat interactions, document processing, embeddings, and vector storage, enabling developers to build complex AI workflows with minimal boilerplate code. LangChain4j also implements common design patterns used in generative AI systems, such as retrieval-augmented generation pipelines, tool calling, and intelligent agent frameworks. These abstractions allow developers to orchestrate interactions between language models, external tools, and knowledge bases in a structured and scalable way. -
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JSON_REPAIR
A python module to repair invalid JSON from LLMs
...The repair process can also be combined with optional JSON Schema validation to enforce structural constraints and ensure the output conforms to expected data types and formats. Developers can integrate the library into applications as a drop-in replacement for standard JSON parsing functions, allowing systems to tolerate imperfect structured data without crashing. -
Securden Password VaultStore, manage, and share passwords, files, SSH keys, and DevOps secrets among IT teams. Enforce password security best practices. Ensure compliance with industry standards using comprehensive audit trails.
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LLM Council
LLM Council works together to answer your hardest questions
LLM Council is a creative open-source web application by Andrej Karpathy that lets you consult multiple large language models together to answer questions more reliably than querying a single model. Instead of relying on one provider, this application sends your query simultaneously to several LLMs supported via OpenRouter, collects each model’s independent response, and then orchestrates a multi-stage evaluation where the models critique and rank each other’s outputs anonymously. After this... -
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trench
Open-Source Analytics Infrastructure
...By combining streaming ingestion with fast analytical queries, the system supports use cases such as product analytics dashboards, observability pipelines, and machine learning data preparation. -
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
MarkPDFdown is an open-source document processing tool designed to convert PDF files into structured Markdown output that can be easily used for documentation, content pipelines, and AI processing workflows. The project focuses on extracting text, formatting, and structural information from complex PDF documents and transforming that information into clean Markdown that preserves the original hierarchy of headings, paragraphs, tables, and lists. -
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LLaMA-Mesh
Unifying 3D Mesh Generation with Language Models
...The project includes a supervised fine-tuning dataset composed of interleaved text and mesh data, allowing the model to learn relationships between textual descriptions and 3D structures. As a result, the model can generate mesh models directly from text prompts, explain mesh structures in natural language, or output mixed text-and-mesh sequences. This unified representation enables a single model to operate across both textual and spatial domains. -
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TaxHacker
Self-hosted AI accounting app. LLM analyzer for receipts
...It integrates large language models to analyze these documents, extract relevant financial information, and categorize expenses or income based on configurable rules. Users can deploy the application on their own infrastructure, ensuring that financial data remains private and under their control rather than being processed by external services. The software provides tools for tracking income streams, monitoring expenses, and organizing financial records in a structured format. Because the system supports customizable prompts and categories, users can adapt the AI analysis to match their accounting workflows or tax requirements. -
OpenMetal is an automated bare metal and on-demand private cloud provider.OpenMetal is an automated bare metal and on-demand private cloud provider. Our mission is to empower your team with cost effective private infrastructure that outperforms traditional public cloud.
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TTRL
Test-Time Reinforcement Learning
TTRL is an open-source framework for test-time reinforcement learning in large language models, with a particular focus on reasoning tasks where ground-truth labels are not available during inference. The project addresses the problem of how to generate useful reward signals from unlabeled test-time data, and its central insight is that common test-time scaling practices such as majority voting can be repurposed into reward estimates for online reinforcement learning. This makes the framework especially interesting for scenarios where models must keep adapting during evaluation or deployment instead of relying only on fixed pretraining and static fine-tuning. ... -
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RecAI
Bridging LLM and Recommender System
RecAI is an open-source research platform developed by Microsoft to explore how large language models can be integrated into modern recommender systems. Traditional recommender systems rely on structured behavioral data such as user interactions and item embeddings, while large language models excel at understanding language and reasoning about user preferences. RecAI aims to bridge these two domains by creating architectures and training methods that allow LLMs to function as intelligent recommendation engines. The project explores several approaches, including fine-tuning language models using user behavior data, building recommender agents, and using LLMs to explain recommendation results. ... -
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POML
Prompt Orchestration Markup Language
POML, or Prompt Orchestration Markup Language, is a structured markup language created to improve the organization and maintainability of prompts used in large language model applications. Traditional prompt engineering often relies on unstructured text, which can become difficult to manage as prompts grow more complex and incorporate dynamic data sources. POML addresses this issue by introducing an HTML-like syntax that allows developers to organize prompts into structured components such as roles, tasks, and examples. This structure enables prompts to be reused, modified, and versioned more easily within complex AI applications. The language also supports integration of multiple data types including documents, tables, and other external inputs that must be incorporated into prompts dynamically. ... -
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LandPPT
An LLM-based presentation generation platform
LandPPT is an open-source AI platform that automatically generates professional presentation slides using large language models. The system allows users to create complete PowerPoint presentations simply by entering a topic or uploading source documents such as PDFs, Word files, or Markdown notes. Using natural language processing and structured content generation, the platform produces presentation outlines and converts them into fully formatted slide decks. The application integrates multiple AI models from providers such as OpenAI, Anthropic, Google, and locally hosted models to generate text, images, and structured presentation layouts. ... -
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BAML
The AI framework that adds the engineering to prompt engineering
BAML is an open-source framework and domain-specific language designed to bring structured engineering practices to prompt development for large language model applications. Instead of treating prompts as unstructured text, BAML introduces a schema-driven approach where prompts are defined as typed functions with explicit inputs and outputs. This design allows developers to treat language model interactions as predictable software components rather than ad-hoc prompt strings. The framework... -
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JamAI Base
The collaborative spreadsheet for AI
JamAI Base is an open-source backend platform designed to simplify the development of retrieval-augmented generation systems and AI-driven applications. The platform integrates both a relational database and a vector database into a single embedded architecture, allowing developers to store structured data alongside semantic embeddings. It includes built-in orchestration for large language models, vector search, and reranking pipelines so that AI applications can retrieve relevant information before generating responses. JamAI Base exposes its functionality through a simple REST API and a spreadsheet-style interface that allows users to manage AI workflows visually. ... -
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NBA Sports Betting Machine Learning
NBA sports betting using machine learning
NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present. Using this dataset, the project constructs matchup features that represent team performance trends and contextual information about each game. Machine learning models are then trained to estimate the probability that a team will win a game as well as whether the total score will fall above or below the sportsbook’s predicted total. ... -
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Integuru v0
The first AI agent that builds permissionless integrations
...Instead of relying on official developer documentation or publicly available APIs, the system analyzes network traffic generated by user interactions within a web application. Developers capture browser requests and authentication data, which the agent then uses to infer the structure of the platform’s internal API endpoints. Based on this information, the system generates executable code that can replicate the original action programmatically. This approach allows developers to automate workflows and build integrations with services that do not provide official APIs or developer tools. ... -
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Index
The SOTA Open-Source Browser Agent
...The project is built to integrate easily with applications through a simple programming interface, allowing developers to embed browser automation capabilities directly into their software systems. Index can perform tasks such as navigating pages, filling forms, collecting data, and analyzing web content without requiring manual scripting for each website. -
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slime LLM
slime is an LLM post-training framework for RL Scaling
slime is an open-source large language model (LLM) post-training framework developed to support reinforcement learning (RL)-based scaling and high-performance training workflows for advanced LLMs, blending training and rollout modules into an extensible system. It offers a flexible architecture that connects high-throughput training (e.g., via Megatron-LM) with a customizable data generation pipeline, enabling researchers and engineers to iterate on new RL training paradigms effectively. The framework is designed to support a wide range of training modes, allowing both synchronous and asynchronous RL workflows and programmable rollout interfaces that simplify experimentation with custom environments and reward signals. ... -
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mllm
Fast Multimodal LLM on Mobile Devices
mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies... -
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HolmesGPT
CNCF Sandbox Project
...The system aggregates signals from observability tools such as logs, metrics, alerts, and distributed traces, then analyzes them using large language models to identify potential root causes. Rather than requiring engineers to manually correlate large volumes of monitoring data, HolmesGPT automatically synthesizes evidence and presents explanations in natural language. The project is developed by Robusta and has been accepted as a Cloud Native Computing Foundation Sandbox project, highlighting its relevance to the cloud-native ecosystem. It is designed to operate as an automated troubleshooting assistant that can analyze incidents continuously and support on-call engineers during outages. -
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NVIDIA Generative AI Examples
Generative AI reference workflows
...The repository includes examples covering topics such as retrieval-augmented generation pipelines, agent-based workflows, and multimodal AI applications that combine text, vision, and data processing. Many of the examples show how to deploy AI services using containerized environments, GPU acceleration, and microservices that can scale across modern infrastructure. Developers can explore sample chatbot applications, document question-answering systems, and knowledge-base pipelines that illustrate how generative AI can interact with external data sources. -
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Paper2Slides
From Paper to Presentation in One Click
Paper2Slides is an automation tool that converts research papers, reports, and other documents into polished slide decks and posters with minimal manual effort. It is designed to replace the repetitive work of turning dense technical documents into presentation-friendly structure by extracting key points, figures, and data into a coherent visual narrative. The system supports multiple input formats, so you can process PDFs and common office documents rather than being locked to a single file type. It uses an extraction approach intended to capture critical insights comprehensively, including important visuals and data points that often get missed in naive summarization. ... -
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LLM Datasets
Curated list of datasets and tools for post-training
...Licensing and provenance are surfaced to encourage compliant usage and to guide dataset selection in commercial settings. For practitioners, the repo is a practical “starting pantry” that accelerates experimentation and helps keep data wrangling from dominating the project timeline. -
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Fast MCP
A Ruby Implementation of the Model Context Protocol
Fast MCP is a lightweight framework designed to simplify the development and deployment of servers that implement the Model Context Protocol. The Model Context Protocol enables AI assistants and applications to connect with external tools, services, and data sources through a standardized interface. Fast-mcp provides developers with a streamlined toolkit for building MCP servers that expose application functionality to AI agents. The framework focuses on ease of use, allowing developers to quickly define tools, endpoints, and integrations that can be accessed through MCP-compatible clients. ...
