shroominic/codeinterpreter-api
Codeinterpreter Api
This project provides a programmatic interface and framework for integrating large language models with secure, stateful, and multimodal code execution environments. It functions as a code interpreter API that enables the execution of arbitrary Python scripts within isolated sandboxed runtimes.
The system supports multimodal data analysis by processing combined text and file inputs to generate visualizations and computational results. It manages stateful workflows by maintaining conversation memory and session history, allowing language models to complete multi-step technical tasks.
The framework includes capabilities for dynamic dependency management and package installation at runtime, along with file management within the execution environment. It also provides a self-correcting execution loop and the ability to scale workloads through remote execution infrastructure.
Features
- Python Execution Sandboxes - Provides isolated environments specifically optimized for the safe execution of generated Python scripts.
- AI Code Interpreters - Provides an environment where AI models can generate and execute code to perform data analysis tasks.
- LLM Tooling Integrations - Connects large language models to an external runtime to automate technical tasks via code generation.
- Conversation Memory Managers - Maintains a persistent history of inputs and outputs to provide context for multi-step computational workflows.
- Session State Persistence - Maintains persistent session state and query history to provide context for multi-step technical workflows.
- Dynamic Dependency Managers - Provides runtime management for fetching and installing the required code modules and libraries.
- Container-Based Sandboxes - Implements secure isolation of Python code execution within ephemeral container environments to protect the host system.
- Stateful Workflow Orchestrators - Manages conversation history and multi-step technical tasks between a language model and a code runtime.
- Dynamic Dependency Installation - Automatically identifies and installs required software packages at runtime when missing imports are detected.
- AI Agent State Coordination - Coordinates the execution state and tool interactions for AI agents performing multi-step technical workflows.
- Multi-Modal Input Processors - Ingests and normalizes a mixture of text and files as inputs for processing by the language model.
- Script Correction Loops - Implements an iterative loop that captures runtime errors and feeds them back to the LLM for script correction.
- Multimodal Analysis Tools - Analyzes visual and textual media to generate computational results and data visualizations.
- Multimodal Data Processing - Processes and analyzes multiple data types, such as text and files, to support complex computational tasks.
- Automated Exploratory Analysis - Automates the generation of statistical summaries and visual reports by dynamically executing analysis scripts.
- File Storage Management - Manages the lifecycle of files, including processing inputs and returning outputs from the code runtime environment.
- Chatbots and Assistants - Open source implementation of code interpreter.
