Search Results for "openai-python"
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Showing 2166 open source projects for "openai-python"
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OpenAI Python
The official Python library for the OpenAI API
The OpenAI Python library provides convenient access to the OpenAI REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx. -
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OpenAI Agents (Python)
A lightweight, powerful framework for multi-agent workflows
openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling. -
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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
Harmony is a response format developed by OpenAI for use with the gpt-oss model series. It defines a structured way for language models to produce outputs, including regular text, reasoning traces, tool calls, and structured data. By mimicking the OpenAI Responses API, Harmony provides developers with a familiar interface while enabling more advanced capabilities such as multiple output channels, instruction hierarchies, and tool namespaces. -
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OpenAI Swarm
Educational framework exploring multi-agent orchestration
Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions; Agents and handoffs. An Agent encompasses instructions and tools, and can at any point choose to hand off a conversation to another Agent. These primitives are powerful enough to express rich dynamics between tools and networks of agents, allowing you to build scalable, real-world solutions while avoiding a steep learning... -
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OpenAI Agent Skills
Skills Catalog for Codex
OpenAI Agent Skills is an open-source repository that serves as a broad catalog of agent skills designed to extend the capabilities of OpenAI Codex and other AI coding agents. It organizes reusable, task-specific workflows, instructions, scripts, and resources into modular skill folders so that an AI agent can reliably perform complex tasks without repeated custom prompting, making agent behavior more predictable and composable. -
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LiteLLM
lightweight package to simplify LLM API calls
Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, Azure OpenAI etc.] liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response. Streaming is supported for OpenAI, Azure, Anthropic, and Huggingface models. -
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OpenAI-Compatible Edge-TTS API
Free, high-quality text-to-speech API endpoint to replace OpenAI
OpenAI-Compatible Edge-TTS API is a local, OpenAI-compatible text-to-speech API that uses edge-tts—Microsoft Edge’s online TTS service—as the backend. The project emulates the /v1/audio/speech endpoint used by OpenAI, so any client that can talk to the OpenAI TTS API can be redirected to this service with minimal changes. It exposes parameters for input text, voice selection, audio format, and playback speed, mirroring the OpenAI interface while mapping popular OpenAI voice names to equivalent Edge voices. ... -
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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. -
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MCP Bridge
A middleware to provide an openAI compatible endpoint
MCP-Bridge serves as a middleware that connects the OpenAI API with MCP tools, allowing developers to utilize MCP functionalities through the OpenAI API interface. It provides endpoints compatible with OpenAI, facilitating seamless integration and enabling the use of MCP tools without requiring explicit MCP support in clients. -
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Instructor Python
Structured outputs for llms
Instructor is a Python library that bridges OpenAI responses with structured data validation using Pydantic models. It lets developers specify expected output schemas and ensures that the responses from OpenAI APIs are automatically parsed and validated against those models. This makes integrating LLMs into structured workflows safer and more predictable, especially in production applications. -
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EPUB to Audiobook Converter
EPUB to audiobook converter, optimized for Audiobookshelf
...It can be run directly with Python or via Docker. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training set). Note: unlike in a typical supervised setting, the performance of a zero-shot classifier greatly depends on how the label itself is structured. ... -
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Nexa SDK
Nexa SDK is a comprehensive toolkit for supporting ONNX and GGML
...It supports text generation, image generation, vision-language models (VLM), and speech-to-text (ASR), and text-to-speech (TTS) capabilities. Additionally, it offers an OpenAI-compatible API server with JSON schema mode for function calling and streaming support, and a user-friendly Streamlit UI. Users can run Nexa SDK in any device with Python environment, and GPU acceleration is supported, including CUDA, Metal, and ROCm. An executable version is also available. -
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Improved Diffusion
Release for Improved Denoising Diffusion Probabilistic Models
...The implementation is intended for researchers and practitioners who want to explore the theoretical and practical aspects of diffusion models in deep learning. By making this code available, OpenAI provides a foundation for further experimentation and development in generative modeling research. -
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ElevenLabs Python
The official Python SDK for the ElevenLabs API
elevenlabs-python is the official Python SDK for the ElevenLabs API, giving developers a convenient way to access ElevenLabs’ high-quality, lifelike voices. The library wraps the HTTP API into a typed Python client, so you can perform text-to-speech, streaming, voice cloning, voice management, and agents-related operations with simple method calls. -
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Portia SDK Python
Portia Labs Python SDK for building agentic workflows
portia‑sdk‑python is an open-source Python SDK by Portia Labs for creating reliable, stateful, authenticated multi-agent AI workflows. It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. -
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ShellGPT
A command-line productivity tool powered by AI large language models
...By default, ShellGPT uses OpenAI's API and GPT-4 model. You'll need an API key, you can generate one here. You will be prompted for your key which will then be stored in ~/.config/shell_gpt/.sgptrc. OpenAI API is not free of charge, please refer to the OpenAI pricing for more information. -
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highway-env
A minimalist environment for decision-making in autonomous driving
HighwayEnv is an OpenAI Gym-compatible environment focused on autonomous driving scenarios. It provides flexible simulations for testing decision-making algorithms in highway, intersection, and merging traffic situations. -
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optillm
Optimizing inference proxy for LLMs
OptiLLM is an optimizing inference proxy for Large Language Models (LLMs) that implements state-of-the-art techniques to enhance performance and efficiency. It serves as an OpenAI API-compatible proxy, allowing for seamless integration into existing workflows while optimizing inference processes. OptiLLM aims to reduce latency and resource consumption during LLM inference. -
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python-telegram
Python client for the Telegram's tdlib
Python API for the tdlib library. It helps you build your own Telegram clients. -
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LazyLLM
Easiest and laziest way for building multi-agent LLMs applications
LazyLLM is an optimized, lightweight LLM server designed for easy and fast deployment of large language models. It is fully compatible with the OpenAI API specification, enabling developers to integrate their own models into applications that normally rely on OpenAI’s endpoints. LazyLLM emphasizes low resource usage and fast inference while supporting multiple models. -
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Groq Python
The official Python Library for the Groq API
Groq Python is the official Python SDK for the Groq REST API, giving Python developers straightforward access to Groq’s LLM, chat, audio, and other AI services. Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. -
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MNE-Python
Magnetoencephalography (MEG) and Electroencephalography EEG in Python
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more. -
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tika-python
Python binding to the Apache Tika™ REST services
A Python port of the Apache Tika library that makes Tika available using the Tika REST Server. This makes Apache Tika available as a Python library, installable via Setuptools, Pip and easy to install. To use this library, you need to have Java 7+ installed on your system as tika-python starts up the Tika REST server in the background. To get this working in a disconnected environment, download a tika server file (both tika-server.jar and tika-server.jar.md5, which can be found here) and set the TIKA_SERVER_JAR environment variable to TIKA_SERVER_JAR="file:////tika-server.jar" which successfully tells python-tika to "download" this file and move it to /tmp/tika-server.jar and run as a background process. ... -
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ChatGLM3
ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat
...It keeps the series’ smooth dialog and low deployment cost while adding native tool use (function calling), a built-in code interpreter, and agent-style workflows. The family includes base and long-context variants (8K/32K/128K). The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit), CPU/MPS support, and accelerator backends (TensorRT-LLM, OpenVINO, chatglm.cpp) enable lightweight local or edge deployment.
