--- title: "langchain4j vs llm-python" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain4j-langchain4j-vs-onlyphantom-llm-python" tools: ["langchain4j-langchain4j", "onlyphantom-llm-python"] --- # langchain4j vs llm-python *GraphCanon updated Aug 21, 2026* ## Verdict Pick langchain4j if langChain4j is a Java library for building applications utilizing Large Language Models (LLMs) on the JVM. It provides a unified API over various LLM providers and vector stores to simplify tool calling, agent creation,R; pick llm-python if jupyter Notebook tutorials and scripts for working with LangChain, OpenAI API, llamaindex, GPT models, ChromaDB, and Pinecone. [langchain4j](https://docs.langchain4j.dev) reports 13k GitHub stars, 2.4k forks, and 892 open issues, last pushed Aug 6, 2026. [llm-python](https://www.youtube.com/playlist?list=PLXsFtK46HZxUQERRbOmuGoqbMD-KWLkOS) has 927 stars, 316 forks, and 0 open issues, last pushed Feb 20, 2026. Figures are from public GitHub metadata via [langchain4j's repository](https://github.com/langchain4j/langchain4j) and [llm-python's repository](https://github.com/onlyphantom/llm-python). | | [langchain4j](/tools/langchain4j-langchain4j.md) | [llm-python](/tools/onlyphantom-llm-python.md) | | --- | --- | --- | | Tagline | Java library for building LLM-powered applications on the JVM | LLM tutorials and scripts covering langchain, openai, llamaindex, GPT, ChromaDB, Pinecone | | Stars | 12,813 | 927 | | Forks | 2,435 | 316 | | Open issues | 892 | 0 | | Language | Java | Jupyter Notebook | | Adopt for | LangChain4j is a Java library for building applications utilizing Large Language Models (LLMs) on the JVM. It provides a unified API over various LLM providers and vector stores to simplify tool calling, agent creation,R | Jupyter Notebook tutorials and scripts for working with LangChain, OpenAI API, llamaindex, GPT models, ChromaDB, and Pinecone. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, Vector Databases | LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain4j](/tools/langchain4j-langchain4j.md) | [llm-python](/tools/onlyphantom-llm-python.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 1d | 181d | | Open issues (now) | 892 | 0 | | Stars delta | +265 (30d) | +1 (30d) | | Open issues delta | +108 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/langchain4j-langchain4j/trust.md) | [trust report](/tools/onlyphantom-llm-python/trust.md) | ## Decision facts: langchain4j - **Adopt for:** LangChain4j is a Java library for building applications utilizing Large Language Models (LLMs) on the JVM. It provides a unified API over various LLM providers and vector stores to simplify tool calling, agent creation,R ## Decision facts: llm-python - **Adopt for:** Jupyter Notebook tutorials and scripts for working with LangChain, OpenAI API, llamaindex, GPT models, ChromaDB, and Pinecone. ## Choose when ### Choose langchain4j if… - langchain4j is primarily Java; llm-python is Jupyter Notebook. - License: langchain4j is Apache-2.0, llm-python is MIT. - Tags unique to langchain4j: anthropic, chatgpt, chroma, embeddings. - If you are working in a Java environment and aim to integrate Large Language Models into your applications ### Choose llm-python if… - llm-python is primarily Jupyter Notebook; langchain4j is Java. - License: llm-python is MIT, langchain4j is Apache-2.0. - Tags unique to llm-python: chromadb, gpt-3, langchain, llama-index. - When you want comprehensive Jupyter-based tutorials on integrating multiple LLM tools including OpenAI and LangChain. ## When NOT to use langchain4j - Avoid if your project exclusively uses languages other than Java, as LangChain4j is specifically designed for Java-based projects on the JVM - If you require a framework that heavily supports non-JVM based large language models and doesn't integrate well with modern enterprise Java frameworks like Quarkus or Spring Boot ## When NOT to use llm-python - Avoid if you require a purely code-library without tutorial-like content in Jupyter Notebooks. - Not suitable if your project strictly demands proprietary or closed-access LLM tools not covered in the repo, like those beyond OpenAI and LangChain. ## Common questions ### What is the difference between langchain4j and llm-python? langchain4j: Java library for building LLM-powered applications on the JVM. llm-python: LLM tutorials and scripts covering langchain, openai, llamaindex, GPT, ChromaDB, Pinecone. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain4j over llm-python? Choose langchain4j over llm-python when langchain4j is primarily Java; llm-python is Jupyter Notebook; License: langchain4j is Apache-2.0, llm-python is MIT; Tags unique to langchain4j: anthropic, chatgpt, chroma, embeddings; If you are working in a Java environment and aim to integrate Large Language Models into your applications. ### When should I choose llm-python over langchain4j? Choose llm-python over langchain4j when llm-python is primarily Jupyter Notebook; langchain4j is Java; License: llm-python is MIT, langchain4j is Apache-2.0; Tags unique to llm-python: chromadb, gpt-3, langchain, llama-index; When you want comprehensive Jupyter-based tutorials on integrating multiple LLM tools including OpenAI and LangChain. ### When should I avoid langchain4j? Avoid if your project exclusively uses languages other than Java, as LangChain4j is specifically designed for Java-based projects on the JVM If you require a framework that heavily supports non-JVM based large language models and doesn't integrate well with modern enterprise Java frameworks like Quarkus or Spring Boot ### When should I avoid llm-python? Avoid if you require a purely code-library without tutorial-like content in Jupyter Notebooks. Not suitable if your project strictly demands proprietary or closed-access LLM tools not covered in the repo, like those beyond OpenAI and LangChain. ### Is langchain4j or llm-python more popular on GitHub? langchain4j has more GitHub stars (12,813 vs 927). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain4j and llm-python open source? Yes - both are open-source projects on GitHub (langchain4j: Apache-2.0, llm-python: MIT). ### Where can I find alternatives to langchain4j or llm-python? GraphCanon lists graph-backed alternatives at [langchain4j alternatives](/tools/langchain4j-langchain4j/alternatives) and [llm-python alternatives](/tools/onlyphantom-llm-python/alternatives) ([langchain4j markdown twin](/tools/langchain4j-langchain4j/alternatives.md), [llm-python markdown twin](/tools/onlyphantom-llm-python/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/langchain4j-langchain4j-vs-onlyphantom-llm-python.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain4j or llm-python? langchain4j: Very active. llm-python: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for langchain4j and llm-python? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain4j trust report](/tools/langchain4j-langchain4j/trust); [llm-python trust report](/tools/onlyphantom-llm-python/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langchain4j-langchain4j`](/api/graphcanon/graph?tool=langchain4j-langchain4j) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_