Search Results for "telegram-bot-api" - Page 15
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Showing 2317 open source projects for "telegram-bot-api"
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GenAI Processors
GenAI Processors is a lightweight Python library
...Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. The library offers built-in processors for classic turn-based Gemini calls as well as Live API streaming, so you can mix “batch” and real-time interactions in the same graph. It leans on Python’s asyncio to coordinate concurrency, handle network I/O, and juggle background compute threads without blocking. -
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Mirascope
LLM abstractions that aren't obstructions
Mirascope is a powerful, flexible, and user-friendly library that simplifies the process of working with LLMs through a unified interface that works across various supported providers, including OpenAI, Anthropic, Mistral, Gemini, Groq, Cohere, LiteLLM, Azure AI, Vertex AI, and Bedrock. Whether you're generating text, extracting structured information, or developing complex AI-driven agent systems, Mirascope provides the tools you need to streamline your development process and create... -
3
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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Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major CL benchmarks (similar to what has been done for torchvision). Provides all the necessary utilities concerning model training. This includes simple and efficient ways of implementing new continual learning strategies as well as a set of pre-implemented CL baselines and state-of-the-art algorithms you will be able to use for comparison! ... -
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5
SAM 3D Objects
Models for object and human mesh reconstruction
SAM 3D Objects is a foundation model that reconstructs full 3D geometry, texture, and spatial layout of objects and scenes from a single image. Given one RGB image and object masks (for example, from the Segment Anything family), it can generate a textured 3D mesh for each object, including pose and approximate scene layout. The model is specifically designed to be robust in real-world images with clutter, occlusions, small objects, and unusual viewpoints, where many earlier 3D-from-image... -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
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TorchMetrics AI
Machine learning metrics for distributed, scalable PyTorch application
TorchMetrics is a collection of 100+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. -
8
GPTCache
Semantic cache for LLMs. Fully integrated with LangChain
ChatGPT and various large language models (LLMs) boast incredible versatility, enabling the development of a wide range of applications. However, as your application grows in popularity and encounters higher traffic levels, the expenses related to LLM API calls can become substantial. Additionally, LLM services might exhibit slow response times, especially when dealing with a significant number of requests. To tackle this challenge, we have created GPTCache, a project dedicated to building a semantic cache for storing LLM responses. This project is undergoing swift development, and as such, the API may be subject to change at any time. -
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Basketball Reference
NBA Stats API via Basketball Reference
...This library was created for another Python project where I was trying to estimate an NBA player's productivity. A lot of sports-related APIs are expensive - luckily, Basketball Reference provides a free service which can be scraped and translated into a usable API. -
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10
StatsForecast
Fast forecasting with statistical and econometric models
StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery... -
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Public APIs
A collective list of free APIs
...Curated by community contributors and the team at APILayer, it serves as a centralized resource for discovering APIs across a wide range of domains, including data, machine learning, weather, entertainment, and finance. The project aims to make API exploration and integration more accessible by offering a single, organized index of open and free-to-use APIs. Developers can leverage this list to enhance their products, prototypes, or research projects without the need to build data sources from scratch. The repository’s open nature encourages contributions, allowing anyone to submit new APIs or updates through pull requests. ... -
12
DocTR
Library for OCR-related tasks powered by Deep Learning
...User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document datasets, comparable with GoogleVision/AWS Textract. Easy integration (available templates for browser demo & API deployment). End-to-End OCR is achieved in docTR using a two-stage approach: text detection (localizing words), then text recognition (identify all characters in the word). As such, you can select the architecture used for text detection, and the one for text recognition from the list of available implementations. -
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MCP Text Editor
Provides line-oriented text file editing capabilities
The MCP Text Editor Server provides line-oriented text file editing capabilities through a standardized API, optimized for integration with Large Language Models (LLMs). It enables efficient partial file access, minimizing token usage while ensuring safe concurrent editing. -
14
mobsfscan
Static analysis tool that can find insecure code patterns in code
mobsfscan is a fast and powerful static analysis tool for identifying security vulnerabilities in mobile app source code. It supports Android, iOS, and Flutter codebases and helps developers secure apps before deployment. -
15
DataProfiler
Extract schema, statistics and entities from datasets
DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. Profiling the Data, the library identifies the schema, statistics, entities (PII / NPI), and... -
16
crawler
Collection of JS reverse engineering examples for web scraping study
...Each directory in the project focuses on a specific target service or scenario, showing how browser network requests and JavaScript code can be studied to reproduce API calls programmatically. Many examples illustrate techniques such as debugging scripts, intercepting requests, analyzing encrypted parameters, and understanding authentication flows. crawler also explores common anti-scraping defenses and demonstrates how developers can examine them through debugging tools and reverse engineering techniques. -
17
Responder
A familiar HTTP Service Framework for Python
...This gets you a ASGI app, with a production static files server (WhiteNoise) pre-installed, jinja2 templating (without additional imports), and a production web server based on uvloop, serving up requests with gzip compression automatically. A pleasant API, with a single import statement. Class-based views without inheritance. ASGI framework, the future of Python web services. WebSocket support! The ability to mount any ASGI / WSGI app at a subroute. f-string syntax route declaration. Mutable response object passed into each view. No need to return anything. Background tasks spawned off in a ThreadPoolExecutor. ... -
18
redshift_connector
Amazon Redshift connector for Python
...Easy integration with pandas and numpy, as well as support for numerous Amazon Redshift-specific features help you get the most out of your data. redshift_connector integrates with various open-source projects to provide an interface to Amazon Redshift. Please open an issue with our project to request new integrations or get support for a redshift_connector issue seen in an existing integration. Following the DB-API specification, autocommit is off by default. It can be turned on by using the autocommit property of the connection. The paramstyle for a cursor can be modified via cursor.paramstyle. The default paramstyle used is format. Valid values for paramstyle include qmark, numeric, named, format, pyformat. redshift_connector uses logging for providing detailed error messages regarding IdP authentication. ... -
19
cloud-morph
Decentralize, Self-host Cloud Gaming/Application
...It is designed to run as a backend service that processes media streams or files and applies transformations such as transcoding, filtering, and format conversion. The system supports API-driven workflows, allowing integration into web applications or automation pipelines. It leverages containerization and distributed architecture to handle workloads efficiently across multiple nodes. cloud-morph focuses on flexibility, enabling users to define custom processing pipelines for different media scenarios. It can be used for applications such as streaming, video processing, and content delivery optimization. ... -
20
SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion
SimpleTuner is an open-source toolkit designed to simplify the fine-tuning of modern diffusion models for generating images, video, and audio. The project focuses on providing a clear and understandable training environment for researchers, developers, and artists who want to customize generative AI models without navigating complex machine learning pipelines. It supports fine-tuning workflows for models such as Stable Diffusion variants and other diffusion architectures, enabling users to... -
21
Datumaro
Dataset Management Framework, a Python library and a CLI tool to build
Datumaro is a flexible Python-based dataset management framework and command-line tool for building, analyzing, transforming, and converting computer vision datasets in many popular formats. It supports importing and exporting annotations and images across a wide variety of standards like COCO, PASCAL VOC, YOLO, ImageNet, Cityscapes, and many more, enabling easy integration with different training pipelines and tools. Datumaro makes it easy to merge datasets, split them into... -
22
VectorVein
No-code AI workflow
...Vector vein is affected LangChain as well as langflow The uncode AI workflow software developed by the inspiration aims to combine the powerful capabilities of large language models and allow users to realize the intelligibility and automation of various daily workflows through simple drag. After the software is opened normally, click on the set button. Please fill in API Key of OpenAI to use the AI function and select the output folder for storing the files during workflow output. If you need to use the function of mail delivery, please fill in the mailbox information on the set page. A workflow represents a work task process that includes input, output, and workflow triggering methods. You can arbitrarily define what the input is, what the output is, and how the input is processed and reaches the output result. -
23
Saleor Commerce
A modular, high performance, headless e-commerce platform
...Saleor is a rapidly-growing open source e-commerce platform that has served high-volume companies from branches like publishing and apparel since 2012. Based on Python and Django, the latest major update introduces a modular front end powered by a GraphQL API and written with React and TypeScript. A comprehensive system for orders, dispatch, and refunds. Advanced payment and tax options, with full control over discounts and promotions. Packed with features that get stores to a wider audience. -
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BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference... -
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Gradio
Create UIs for your machine learning model in Python in 3 minutes
...Once you've created an interface, you can permanently host it on Hugging Face. Hugging Face Spaces will host the interface on its servers and provide you with a link you can share. One of the best ways to share your machine learning model, API, or data science workflow with others is to create an interactive demo that allows your users or colleagues to try out the demo in their browsers.
