Astra

Astra is a modular framework for evaluating, fine-tuning, and improving large language models (LLMs) for domain-specific knowledge and real-world business tasks.

Astra

An LLM Evaluation, Training & Adaptation Framework

Astra is an open-source project designed to support the evaluation, training, fine-tuning, and continuous improvement of large language models (LLMs).

The project focuses on identifying model weaknesses, improving domain-specific understanding, and developing more reliable AI systems capable of performing complex, specialized tasks.

Rather than relying exclusively on general-purpose model capabilities, Astra aims to provide a structured approach to understanding how language models perform, where they fail, and which techniques can improve their performance.

Core Objectives

Model Evaluation

Evaluate model performance across domain-specific tasks, including factual accuracy, reasoning, semantic understanding, instruction following, and response consistency.

Error Detection & Analysis

Identify recurring mistakes, knowledge gaps, ambiguous interpretations, unsupported claims, and weaknesses in task execution.

Domain-Specific Adaptation

Develop datasets, evaluation criteria, and adaptation workflows for specialized industries and business functions.

Model Training & Fine-Tuning

Support supervised fine-tuning and other training techniques using curated datasets and measurable performance objectives.

Continuous Improvement

Compare model versions, measure improvements against established benchmarks, and identify regressions after training or configuration changes.

Planned Capabilities

• Configurable evaluation pipelines and benchmark suites
• Structured error classification and reporting
• Domain-specific dataset creation and validation
• Semantic and contextual reasoning assessments
• Integration with open-source and API-based language models
• Training and fine-tuning workflows for supported models
• Model comparison and performance tracking
• Experiment management and reproducible results

Applications

Astra is intended to support AI applications across business operations, education, professional services, knowledge management, customer communication, and other specialized domains.

Project Status

Early development architecture and research phase.

The initial focus is on building the evaluation infrastructure, developing a systematic error taxonomy, and establishing measurable criteria for model improvement. Training and adaptation capabilities will be developed as subsequent components.

Vision

To make language model development more systematic, transparent, measurable, and adaptable to the knowledge and requirements of different domains.