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Showing 98 open source projects for "error"
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1
Gemini-API
Reverse-engineered Python API for Google Gemini web app
...The project is licensed under AGPL-3.0, emphasizing the “open” nature but also requiring derivative works to remain open. It has a strong community following and active discussions/issue tracking around model support, error handling, and new features. -
2
SkillKit
Supercharge AI coding agents with portable skills
...It supports integration with common agent runtimes and toolkits, allowing skills to be plugged into existing architectures without requiring deep infrastructure rewrites. The kit also includes example skills, documentation on best practices, and mechanisms for handling edge cases such as error states, fallbacks, and contextual switches. -
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RA.Aid
Develop software autonomously
RA.Aid is an AI-powered assistant designed to enhance the efficiency of software development workflows. It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality. -
4
ComfyUI-Copilot
AI assistant for ComfyUI workflow generation, debugging, and tuning
...ComfyUI-Copilot leverages large language model capabilities to analyze user intent, recommend nodes, and suggest models that match specific requirements. It also provides automated error detection and repair suggestions, improving reliability during development. -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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5
Anthropic SDK Python
Provides convenient access to the Anthropic REST API from any Python 3
...The library includes definitions for all request and response parameters using Python typed objects, automatically handles serialization and deserialization, and wraps HTTP logic (timeouts, retries, error mapping) so that developers can call the API in a clean, high-level way. The SDK supports both synchronous and asynchronous usage (via async/await) depending on context. Importantly, it also supports streaming responses via Server-Sent Events (SSE) so that large outputs can be consumed incrementally rather than waiting for the full response. ... -
6
Generative AI Swift
This SDK is now deprecated, use the unified Firebase SDK
...Although marked “deprecated”, the repo demonstrates how to integrate Gemini inference into iOS and macOS apps via Swift APIs, providing boilerplate for prompt dispatching, streaming responses, UI integration, and error handling. It includes a sample app that showcases a chat interface, where users send messages and receive responses streamed in real time, with UI updates as tokens arrive. The code also handles request queuing, cancellation, and retry logic, giving developers a realistic foundation rather than a minimalist “hello world.” Despite its deprecated label, the repo remains valuable for developers who want to see how a native Swift integration might be structured before migrating to newer SDKs. ... -
7
Thinc
A refreshing functional take on deep learning
...Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers. -
8
MCPJam
Postman for MCPs - A tool for testing and debugging MCPs
Inspector by MCPJam is a visual developer tool—akin to Postman—for testing and debugging MCP servers, with capabilities to simulate and trace tool execution via various transports and LLM integrations. -
9
llmfit
157 models, 30 providers, one command to find what runs on hardware
...It provides both an interactive terminal user interface and a traditional CLI mode, enabling flexible workflows for different user preferences. llmfit also supports advanced configurations including multi-GPU setups, mixture-of-experts architectures, and dynamic quantization recommendations. By presenting clear performance estimates and compatibility guidance, the project reduces the trial-and-error typically involved in local LLM experimentation. Overall, llmfit serves as a practical decision assistant for developers who want to run language models efficiently on their own machines. -
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10
ZAPI
ZAPI by Adopt AI is an open-source Python library
...It emphasizes a declarative router and schema model that uses types to define request and response formats, providing clear contracts for frontend and backend teams while automatically generating documentation. Zapi abstracts many repetitive tasks such as validation, authentication flows, and error handling so developers can focus on business logic instead of infrastructure plumbing. It integrates smoothly into modern development stacks, supports hot reloading for rapid iteration, and includes a command-line toolchain for scaffolding new endpoints or services with sensible defaults. The framework also supports plugin extensions that add things like rate limiting, caching layers, and telemetry without cluttering core code. -
11
Happy Coder
Mobile and Web client for Codex and Claude Code, with realtime voice
Happy is an open-source, cross-platform mobile and web client designed to bring powerful AI coding agents such as Claude Code and Codex to your fingertips no matter where you are. At its core, Happy wraps existing AI coding tools with a unified interface, providing real-time voice interactions, encrypted communication, and seamless device switching between desktop and mobile. You can start a coding session locally through the Happy CLI or connect from a phone or browser, allowing developers... -
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FastMCP
The fast, Pythonic way to build Model Context Protocol servers
FastMCP is a fast, Pythonic framework for building servers and clients using the Model Context Protocol (MCP). It abstracts away protocol complexity like serialization, validation, and error handling, letting developers focus entirely on their business logic. With simple decorators, you can expose Python functions as tools, resources, or prompts that AI agents can safely and efficiently use. FastMCP introduces clear abstractions—components, providers, and transforms—that make it easy to control what agents see and how they interact with your system. ... -
13
LiteParse
A fast, helpful, and open-source document parser
...LiteParse supports integration with multiple language models, allowing developers to choose the best balance between accuracy and efficiency. It also includes mechanisms for validation and error handling, ensuring that outputs conform to expected schemas and reducing the need for manual postprocessing. The library is particularly useful for tasks such as data extraction, document processing, and building pipelines that require structured outputs from natural language input. -
14
TreeQuest
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
...It allows developers to define custom state-generation and scoring functions (e.g., via LLMs), and then efficiently explores possible answer trees during runtime. With support for multi-LLM collaboration, checkpointing, and mixed policies, TreeQuest enables smarter, trial‑and‑error question answering by leveraging both breadth (multiple attempts) and depth (iterative refinement) strategies to find better outputs dynamically -
15
n8n-MCP
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor
...It ships with organized resources and tool definitions that map cleanly to n8n’s ecosystem, improving reliability compared with ad-hoc prompt patterns. The project targets practical agent ops: safer mutations, better error reporting, and predictable behavior when automating or refactoring automations. Community posts highlight the goal of giving agents accurate knowledge of hundreds of n8n nodes and keeping that knowledge fresh as n8n evolves. -
16
Zypher Agent
A minimal yet powerful framework for creating AI agents
...Zypher prioritizes native support for multiple model providers such as OpenAI and Anthropic Claude, while also offering a rich set of tools for file system operations, search, and terminal execution. It includes mechanisms like checkpointing to version agent decision states, concurrency protections, error handling, and operational interceptors to customize behavior after each reasoning step. Its API is built with TypeScript and is suitable for production contexts where agents must handle real tasks with configurability, logging, and observability. -
17
E2B Code Interpreter
Python & JS/TS SDK for running AI-generated code/code
An interactive coding tool enabling real-time code interpretation for multiple languages. -
18
LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application,... -
19
Fish Speech
SOTA Open Source TTS
...The repository hosts the code and tooling for training, fine-tuning, and serving high-quality TTS, while the current flagship models (OpenAudio-S1 and S1-mini) are distributed via Fish Audio’s playground and Hugging Face. The models are evaluated with Seed TTS metrics and achieve exceptionally low word and character error rates, indicating strong intelligibility and alignment between text and audio. Fish Speech emphasizes expressive and controllable voices: it supports a long list of emotion tags, tone markers, and special audio effect markers that can be embedded in the text to drive prosody and vocal style, from basic emotions to nuanced states like sarcastic, conciliative, or hysterical. ... -
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Model Context Protocol Python SDK
The official Python SDK for Model Context Protocol servers and clients
The Python SDK for Model Context Protocol provides utilities to interact with the protocol, enabling seamless communication with AI models. -
21
SAM 2
The repository provides code for running inference with SAM 2
...The project also includes scripts and notebooks to compare SAM2 against SAM on edge cases, benchmarks showing improvements, and evaluation suites to measure mask quality metrics like IoU and boundary error. -
22
Firecrawl MCP Server
Adds powerful web scraping and search to Cursor and Claude
...Built-in behaviors include JavaScript rendering, automatic retries, and streamable HTTP so long pages and large crawls can flow incrementally into agents. Because it’s an MCP server, clients get typed inputs/outputs and standardized error handling rather than ad-hoc prompt instructions. The repository is active, widely starred, and includes quick starts that make it easy to add web research to an agent stack. -
23
PearAI
The Open Source AI-Powered Code Editor. A fork of VSCode and Continue
...This also works with choosing specific folders, online docs, terminal content, files, and more. PearAI can directly code in your files, and allow you to see diffs. Try CMD+I (CTRL+I on Windows). Here, we ask PearAI to help us add error handling and comments. Without writing a single line of code, we were able to make a new feature in an unfamiliar codebase: adding a documentation page to the PearAI landing page. Speed up your development process by seamlessly integrating AI into your workflow. PearAI's goal is to reduce the time it takes for an individual to go from idea to creation. ... -
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Axon
Nx-powered Neural Networks
Nx-powered Neural Networks for Elixir. Axon consists of the following components. Functional API – A low-level API of numerical definitions (defn) of which all other APIs build on. Model Creation API – A high-level model creation API which manages model initialization and application. Optimization API – An API for creating and using first-order optimization techniques based on the Optax library. Training API – An API for quickly training models, inspired by PyTorch Ignite. Axon provides... -
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Agent Behavior Monitoring
The open source post-building layer for agents
Agent Behavior Monitoring is an open-source framework designed to monitor, evaluate, and improve the behavior of AI agents operating in real or simulated environments. The system focuses on agent behavior monitoring by collecting interaction data and analyzing how agents perform across different scenarios and tasks. Developers can use the framework to observe agent actions in both online production environments and offline evaluation settings, making it useful for debugging and performance...
