Open-source alternatives to Codeinterpreter Api

Koog is an LLM agent framework used to build autonomous entities that execute tool-based workflows. It utilizes a graph-based workflow engine to define agent behaviors and decision paths as a directed graph of nodes and edges. The framework distinguishes itself through a model provider orchestrator that enables dynamic switching, load balancing, and automatic fallbacks between different AI backends. It implements the Model Context Protocol to connect agents to remote tool servers and features a RAG memory system using vector embeddings to maintain long-term conversation context. The project

This project is an LLM agent framework and orchestration engine designed for building autonomous agents that reason, utilize tools, and execute multi-step plans. It provides a system for implementing the ReAct pattern, which interleaves reasoning and action cycles to solve complex problems through iterative observation and self-correction. The framework includes a tool integration layer that connects language models to external functions and APIs using structured schemas and embedding-based routing. It also features a memory management system to persist conversation history and user preferenc

GLaDOS is a multimodal AI agent framework designed to create autonomous systems that process text, speech, and visual data to interact with users and their environment. It centers on an AI personality framework that emulates complex character personas using a multi-agent architecture and configurable behavioral profiles. The project distinguishes itself through an integrated tool layer that connects language models to external hardware, smart home devices, and system APIs via a standardized protocol. It features a character text-to-speech engine with low-latency playback and interruption hand

GLM-4.5 is a multimodal large language model and advanced reasoning system. It functions as an AI coding assistant, an autonomous AI agent, and a multimodal content generator capable of processing and generating text, images, audio, and video within a single unified system. The project is distinguished by its deep reasoning capabilities, utilizing chain-of-thought processing to solve complex mathematical, logical, and technical problems. It features an agentic architecture that allows for autonomous task execution, long-horizon goal planning, and the ability to interact with external tools an

ruby_llm is an LLM integration framework and AI agent orchestrator designed to connect applications to multiple large language model providers through a unified interface. It serves as a toolkit for building autonomous assistants with custom personas, managing structured output via JSON schemas, and implementing vector embedding engines for semantic search. The project distinguishes itself as an observability suite and multimodal toolkit. It provides specialized capabilities for tracking token usage, calculating model costs, and tracing workflows via OpenTelemetry, while supporting the proces

OptiLLM is an inference proxy and gateway router that directs prompts to specific language models based on cost, performance, and provider health. It functions as a middleware layer designed to optimize requests through intelligent routing, load balancing, and context management. The project provides specialized capabilities for data protection by anonymizing personally identifiable information before requests reach a model. It also acts as a reasoning orchestrator and tool integration layer, using inference-time loops and self-reflection to improve accuracy while connecting models to externa

mistral.rs is an inference engine for large language models that runs locally and exposes models behind OpenAI and Anthropic-compatible APIs. It serves as a multi-model serving platform, capable of loading several models in a single server process with per-request routing and on-demand loading and unloading. The engine supports multimodal inference, processing text alongside images, video, audio, and speech inputs, and includes a quantized model deployment runtime that reduces memory use and speeds up inference on consumer hardware. The project distinguishes itself through an agentic tool exe

This repository is a collection of guides, notebooks, and recipes for implementing advanced prompting techniques and workflow patterns with large language models. It serves as a prompt engineering guide, an evaluation suite for scoring prompt quality, and a framework for orchestrating agents and integrating external tools. The project provides implementation patterns for building applications with Claude, specifically focusing on coordinating multiple models to split complex tasks between high-reasoning and high-efficiency agents. It includes technical demonstrations for multimodal data proce

iflow-cli is a command-line interface and suite of AI tools designed for software engineering, workflow orchestration, and multimodal data analysis. It functions as an LLM command line interface that enables users to execute AI workflows, analyze codebase structures, and interact with large language models directly from the terminal. The project features a plugin-based agent architecture that allows for the integration of specialized domain experts and custom instruction sets from an external marketplace. It distinguishes itself through a multimodal AI terminal capable of processing visual da

SWE-agent is an autonomous software engineering platform designed to automate repository maintenance and issue resolution. By orchestrating language models to navigate codebases, diagnose software bugs, and apply fixes, the framework functions as an autonomous agent capable of executing shell commands, editing source code, and managing pull requests within isolated, containerized environments. The platform distinguishes itself through its focus on end-to-end task autonomy and observability. It features a robust trajectory logging system that records every thought, action, and environment obse

AIOS is an LLM agent operating system and orchestration kernel designed to manage memory, resource scheduling, and tool execution for multiple autonomous AI agents. It serves as a comprehensive framework for developing and deploying agents, featuring a dedicated resource manager that coordinates model backends, GPU memory, and isolated kernel instances. The system distinguishes itself through a semantic memory engine that uses vector search and autonomous clustering for long-term knowledge management, and a semantic file system that allows users to control computer files and system operations

Filestash is a unified storage management platform that provides a web-based interface for browsing, managing, and accessing files across diverse local and cloud storage backends. It functions as a centralized gateway, aggregating services such as S3, SFTP, WebDAV, and FTP into a single, consistent environment for remote filesystem administration and secure document handling. The platform distinguishes itself through a modular, plugin-based architecture that supports custom storage drivers, authentication providers, and authorization logic. It includes built-in capabilities for server-side me

This project is an application framework and execution environment that integrates large language models with local system execution and external hardware control. It functions as a multi-modal orchestrator, coordinating vision, speech, and domain-expert models within a single processing loop to reason across diverse data types. The framework enables autonomous code generation and execution, allowing language models to write and run Python scripts via a code interpreter to automate operating system tasks and host software. It further extends these capabilities to physical environments through

This project is a self-hosted Telegram Bot API server that implements a REST gateway to manage bots independently of official cloud infrastructure. It functions as messaging platform middleware, utilizing a translation layer to convert high-level REST API calls into low-level functions via a TDLib-based core. The server allows for local hosting, which enables the removal of cloud file size limits for uploads and downloads and the use of arbitrary local IP addresses and ports for webhook delivery. It provides a local file system storage mechanism for handling large files and supports session-b

Quivr is a retrieval-augmented generation platform designed to transform raw documents into searchable knowledge bases. It functions as a centralized environment where users can ingest files, index them into vector databases, and interact with language models to receive contextually relevant, data-backed responses. The platform distinguishes itself through an agentic workflow orchestrator that sequences retrieval tasks, tool execution, and model interactions to resolve complex, multi-step queries. This engine is entirely configuration-driven, allowing users to define document ingestion, chunk

Monty is a sandboxed execution environment designed primarily for running Python code generated by AI models. It provides a secure, isolated runtime that blocks host access, enforces resource limits, and supports pre-execution type checking against built-in type hints to catch signature mismatches before code runs. The sandbox can persist its interpreter state at external function calls, allowing execution sessions to be serialized, stored, and later resumed from a file or database. What distinguishes Monty is its combination of stateful, resumable execution with multi-language native embeddi

This project is a comprehensive suite of AI tools and frameworks, featuring an LLM multi-agent orchestrator, an autonomous agent runtime, and a stateful application framework. It provides the infrastructure to build and manage specialized AI agents capable of coordinating complex tasks through graph-based workflows and shared state. The system is distinguished by its implementation of the Model Context Protocol, allowing for standardized resource discovery and communication between AI clients and servers. It further includes an AI-powered documentation generator designed to analyze source cod

mcp-context-forge is a Model Context Protocol federation gateway that unifies diverse AI tool servers and APIs into a single consistent interface for discovery and execution. It acts as a centralized proxy that aggregates multiple servers and APIs, allowing AI agents to access and invoke a unified set of tools, prompts, and resources. The project distinguishes itself through a multi-protocol translation bridge that converts communication between standard I/O, SSE, gRPC, and REST to enable interoperability between disparate tool servers. It includes a comprehensive LLM evaluation framework for

Scira is an AI-powered search and synthesis engine that uses agentic research workflows to find and organize information from the web and academic sources. The system breaks complex queries into multi-step plans and generates grounded answers with inline citations for verification. The platform distinguishes itself by executing Python code within isolated sandboxes to perform data analysis and create visual charts from retrieved data. It also implements retrieval-augmented generation to perform semantic searches across uploaded documents, including PDFs and CSV files, and integrates with clou

OpenSandbox is a secure sandbox runtime and containerized code execution engine designed to run AI-generated code and scripts in isolated environments. It serves as a workload orchestrator that prevents host system contamination by utilizing kernel-level isolation to execute arbitrary commands and scripts. The project distinguishes itself by providing a model context server that bridges large language models to the sandbox for performing file operations and system commands. It also includes a remote GUI sandbox that supports browser automation and desktop interfaces via remote access protocol

Dangerzone is a security tool and content sanitizer that converts untrusted files into safe PDFs. It removes malicious content by rendering documents as raw pixels within a sandboxed environment and rebuilding them as new PDF files to strip executable scripts and hidden threats. The project utilizes container-based sandboxing to isolate file processing from the host operating system. It is designed for air-gapped execution, allowing the sanitization process to operate on hardware without network connectivity to prevent malware from communicating with external servers. To maintain document ut

Claude-engineer is an autonomous software engineering agent and command-line interface for interacting with the Claude 3.5 Sonnet model. It functions as an AI code editor that writes code, manages local files, and executes terminal commands to automate technical workflows. The system features a self-evolving tool framework that allows the agent to design and implement its own functional scripts to expand its capabilities during a session. It utilizes a sandboxed Python executor to run scripts for data analysis and complex computations in a secure remote environment. The project covers a broa

The inspector is a diagnostic and validation tool for the Model Context Protocol. It provides an interactive interface and a transport proxy to discover, inspect, and execute the tools, prompts, and resources provided by an MCP server. The project serves as a debugger and compliance tester to verify that server implementations adhere to the protocol specification and JSON-RPC standards. It allows for real-time monitoring of message exchanges and logs between clients and servers across various transport layers, such as standard input/output and Server-Sent Events. The tool covers a broad rang

container-use is a containerized AI execution environment and code sandbox designed to provide a secure space for AI coding agents to execute commands and build applications. It functions as a workspace orchestrator that provisions isolated containers mapped to git branches, allowing multiple agents to operate in parallel without state conflicts or affecting the host system. The project serves as a Model Context Protocol server, bridging AI agents to containerized environments for standardized tool access. It enables a workflow for reviewing and merging changes made by agents within these iso

OpenShell is a security framework and sandboxed execution runtime for autonomous AI agents. It provides isolated environments using containers and virtual machines to protect host infrastructure and sensitive data from unauthorized access during agent execution. The system distinguishes itself by combining hardware-accelerated passthrough for host GPU access with a security gateway that intercepts model API calls. This gateway manages credentials by stripping caller information and injecting backend secrets, ensuring sensitive API keys remain off the local filesystem. The platform covers bro

This project is a secure container runtime that provides strong isolation for application workloads by implementing a userspace kernel. By intercepting system calls and executing them within a memory-safe, restricted environment, it minimizes the attack surface exposed to the host kernel. It functions as a drop-in engine for standard container orchestration platforms, ensuring compatibility with industry-standard runtime specifications while maintaining a hardened execution boundary. The runtime distinguishes itself through its ability to virtualize core system resources, including an indepen

Open Interpreter is an autonomous agent runtime that translates natural language instructions into executable code to interact with local software and operating systems. It functions as an orchestration framework that connects language models to a secure execution environment, enabling the development of agents capable of managing system resources and performing complex tasks. To ensure safety, the system mandates explicit user verification before executing any generated code and provides robust isolation through containerized sandboxing. The project distinguishes itself through its deep inte