Search Results for "telegram source code" - Page 4
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Showing 747 open source projects for "telegram source code"
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Unrivaled Embedded Payments Solutions | NMINMI Payments is an embedded payments solution that lets SaaS platforms, Software companies and ISVs integrate, brand, and manage payment acceptance directly within their software—without becoming a PayFac or building complex infrastructure. As a full-stack processor, acquirer, and technology partner, NMI handles onboarding, compliance, and risk so you can stay focused on growth. The modular, white-label platform supports omnichannel payments, from online, mobile and in-app to in-store and unattended. Choose from full-code, low-code, or no-code integration paths and launch in weeks, not months. Built-in risk tools, flexible monetization, and customizable branding help you scale faster while keeping full control of your experience. With NMI’s developer-first tools, sandbox testing, and modern APIs, you can embed payments quickly and confidently.
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MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design.MicroStation is the only computer-aided design software for infrastructure design, helping architects and engineers like you bring their vision to life, present their designs to their clients, and deliver their projects to the community.
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Nexent
Zero-code platform for building AI agents from natural language input
Nexent is an open source platform designed to enable users to create intelligent agents using natural language instead of traditional programming or visual orchestration tools. It focuses on a zero-code approach, allowing users to define workflows and agent behavior purely through language prompts, significantly lowering the barrier to entry for AI development. -
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UltraRAG
Less Code, Lower Barrier, Faster Deployment
UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It... -
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OpenSandbox
OpenSandbox is a general-purpose sandbox platform for AI applications
OpenSandbox is a general purpose sandbox platform designed to securely run and isolate AI applications and untrusted workloads in controlled environments. The project focuses on providing a unified sandbox API that simplifies the process of executing code safely across different runtime backends. It supports multiple programming languages through SDKs, allowing developers to integrate sandbox capabilities into their systems without building custom isolation layers. The platform is built to... -
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HumanEval
Code for the paper "Evaluating Large Language Models Trained on Code"
human-eval is a benchmark dataset and evaluation framework created by OpenAI for measuring the ability of language models to generate correct code. It consists of hand-written programming problems with unit tests, designed to assess functional correctness rather than superficial metrics like text similarity. Each task includes a natural language prompt and a function signature, requiring the model to generate an implementation that passes all provided tests. The benchmark has become a... -
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TorchRL
A modular, primitive-first, python-first PyTorch library
TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. TorchRL provides PyTorch and python-first, low and high-level abstractions for RL that are intended to be efficient, modular, documented, and properly tested. The code is aimed at supporting research in RL. Most of it is written in Python in a highly modular way, such that researchers can easily swap components, transform them, or write new ones with little effort. -
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LLM Action
Technical principles related to large models
LLM-Action is a knowledge/tutorial/repository that shares principles, techniques, and real-world experience related to large language models (LLMs), focusing on LLM engineering, deployment, optimization, inference, compression, and tooling. It organizes content in domains like training, inference, compression, alignment, evaluation, pipelines, and applications. Sections covering infrastructure, engineering, and deployment. Repository templates, sample code, and resource links. Articles/code... -
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C3
The goal of CLAIMED is to enable low-code/no-code rapid prototyping
C3 is an open-source framework designed to simplify the development and deployment of data science and machine learning workflows through reusable components and low-code development techniques. The framework focuses on enabling rapid prototyping while maintaining a path to production through automated CI/CD integration. CLAIMED provides a component-based architecture where data processing steps, models, and workflows can be packaged into reusable operators. -
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Gitingest
Create prompt-friendly codebase digests from any Git repository URL
Gitingest is a developer utility that converts an entire Git repository into a structured, prompt-friendly text digest suitable for use with large language models. It analyzes a repository and produces a consolidated textual representation that includes the file structure and code content in an organized format. This makes it easier to provide meaningful code context when working with AI systems that require compact, readable inputs. Developers can generate these digests from either a local... -
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HolyClaude
AI coding workstation: Claude Code + web UI + 5 AI CLIs + headless
HolyClaude is a developer-focused toolkit designed to enhance and extend the capabilities of Claude Code environments by providing structured prompts, utilities, and workflow enhancements for AI-assisted coding. The project centers around improving how developers interact with AI agents, enabling more efficient code generation, debugging, and task execution through optimized prompt engineering. It includes predefined templates and interaction patterns that guide the AI toward producing more... -
Zendesk: The Complete Customer Service SolutionEquip your agents with powerful AI tools and workflows that boost efficiency and elevate customer experiences across every channel.
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AstronRPA
Agent-ready RPA suite with visual workflow automation tools engine
Astron RPA is an enterprise-grade robotic process automation platform designed to help organizations and developers build automated workflows for desktop and web applications. It provides a visual workflow designer that supports low-code and no-code development, allowing users to create automation processes through a drag-and-drop interface instead of writing extensive code. It enables automation of common desktop software and browser-based tasks, making it suitable for repetitive business... -
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Loki Mode
Multi-agent autonomous startup system for Claude Code
Loki Mode is a multi-agent autonomous execution system designed to take structured product requirements or specifications and autonomously drive the creation, testing, deployment, and scaling of complex software projects using a large team of specialized AI agents. It orchestrates dozens of agent types across swarms that handle designated roles — such as architecture, coding, QA, deployment, and business workflows — running in parallel to cover both engineering and operational tasks without... -
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and... -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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DocETL
A system for agentic LLM-powered data processing and ETL
DocETL is an open-source system designed to build and execute data processing pipelines powered by large language models, particularly for analyzing complex collections of documents and unstructured datasets. The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. -
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Open Interpreter
A natural language interface for computers
Open Interpreter is an open-source tool that provides a natural-language interface for interacting with your computer. It lets large language models (LLMs) run code locally (Python, JavaScript, shell, etc.), enabling you to ask your computer to do tasks like data analysis, file manipulation, browsing, etc. in human terms (“chat with your computer”), with safeguards. -
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Spec Kit
Toolkit to help you get started with Spec-Driven Development
Spec Kit is an open-source toolkit designed to enable specification-driven development workflows powered by AI coding assistants. It introduces a structured process in which developers define detailed specifications first, then allow AI tools to generate plans, tasks, and implementation code aligned with those requirements. The toolkit provides scaffolding, prompt templates, and automation scripts that help teams maintain a clear source of truth throughout the development lifecycle. ... -
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DeepAudit
AI multi-agent platform for automated code security auditing system
DeepAudit is an open source code security auditing platform that uses a multi-agent architecture to analyze and identify vulnerabilities in software projects. Instead of relying solely on traditional static analysis, it simulates the reasoning process of security experts through coordinated agents responsible for orchestration, reconnaissance, analysis, and verification. -
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Wan2.2
Wan2.2: Open and Advanced Large-Scale Video Generative Model
Wan2.2 is a major upgrade to the Wan series of open and advanced large-scale video generative models, incorporating cutting-edge innovations to boost video generation quality and efficiency. It introduces a Mixture-of-Experts (MoE) architecture that splits the denoising process across specialized expert models, increasing total model capacity without raising computational costs. Wan2.2 integrates meticulously curated cinematic aesthetic data, enabling precise control over lighting,... -
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CodeGen
Open-source model for program synthesis
CodeGen is a family of open-source large language models designed specifically for program synthesis and code generation tasks. Developed by Salesforce Research, the models are trained on large datasets containing both natural language and programming language content. This allows them to translate natural language descriptions into functional code across a variety of programming languages. -
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Quark Agent
Quark Agent - Your AI-powered Android APK Analyst
With Quark Agent, you can perform analyses using only natural language. It creates Quark Script code following your ideas and adjusts the code promptly as you provide feedback. -
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ZenML
Build portable, production-ready MLOps pipelines
...Keep yourself open to new tools - ZenML is easily extensible and forever open-source! -
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magentic
Seamlessly integrate LLMs as Python functions
Easily integrate Large Language Models into your Python code. Simply use the @prompt and @chatprompt decorators to create functions that return structured output from the LLM. Mix LLM queries and function calling with regular Python code to create complex logic. -
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Wan2.1
Wan2.1: Open and Advanced Large-Scale Video Generative Model
Wan2.1 is a foundational open-source large-scale video generative model developed by the Wan team, providing high-quality video generation from text and images. It employs advanced diffusion-based architectures to produce coherent, temporally consistent videos with realistic motion and visual fidelity. Wan2.1 focuses on efficient video synthesis while maintaining rich semantic and aesthetic detail, enabling applications in content creation, entertainment, and research. The model supports... -
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IQuest-Coder-V1 Model Family
New family of code large language models (LLMs)
IQuest-Coder-V1 is a cutting-edge family of open-source large language models specifically engineered for code generation, deep code understanding, and autonomous software engineering tasks. These models range from tens of billions to smaller footprints and are trained on a novel code-flow multi-stage paradigm that captures how real software evolves over time — not just static code snapshots — giving them a deeper semantic understanding of programming logic. ... -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs.
