{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"GenAgent provides utilities for building applications with large language models, including integrations with OpenAI and Anthropic, agent memory management, chat sessions, and structured output generation.","skillfed_tags":["llm-integration","agent-framework","multi-provider"],"use_cases":["Building chatbot or assistant applications that maintain conversation history and retrieve relevant memories.","Extracting structured data from unstructured text using modular instruction templates.","Running parallel LLM experiments using the parallelization utilities.","Prototyping multi-provider LLM applications without rewriting code for each API.","Implementing agent systems that need semantic memory search across stored facts."],"what_it_does":"GenAgent is a Python library that wraps interactions with multiple large language model providers\u2014OpenAI, Anthropic, and Cerebras\u2014behind a unified interface. It simplifies common LLM tasks like text generation, prompt engineering, and structured output extraction. The package also provides agent utilities: memory storage and retrieval, chat session management with system prompts, and modular instruction-based generation for extracting multiple fields from a single LLM call.\n\nThe library depends on eight runtime packages, including pydantic for validation, numpy for numerical work, tqdm for progress bars, and python-dotenv for environment configuration. It is designed for developers building agent-like applications that need to maintain context across multiple LLM calls and retrieve relevant memories based on queries. Configuration is handled via environment variables, allowing you to set a default provider and model once rather than passing them to every function call.","worth_installing":"Yes, with conditions. GenAgent is useful for rapid prototyping of LLM-based agents and offers a clean abstraction over multiple providers. However, maintenance is aging (240 days since last release), the license treatment is unclear in the metadata, and you will need active API keys for OpenAI or Anthropic. Install it if you are building a prototype or internal tool and can tolerate potential lag on dependency updates; avoid it for production systems requiring long-term support guarantees."},"id":"genagent","links":{"html":"https://skillfed.io/packages/genagent","md":"https://skillfed.io/packages/genagent.md","pypi":"https://pypi.org/project/genagent/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-12-17","license_spdx":null,"license_treatment":"unclear","name":"genagent","python_support":"supports_current","summary":"Python utilities for generative agent tasks, including LLM interactions and agent memory."},"popularity":{"monthly_downloads":243043,"position":8830,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.4.1"}