hello-world like langchain starter kit

[sayantikabanik]

Introduces LangChain to DataJourney

Command to execute

(journey) (base) sayantikabanik@sayantika langchain % pixi task list
Tasks that can run on this machine:
-----------------------------------
DJ_advance_llm_analysis, DJ_dagster, DJ_fasthtml_app, DJ_flask_app, DJ_hello_world_langchain, DJ_llm_analysis_gpt_4o, DJ_mito_app, DJ_package, DJ_panel_app, DJ_pre_commit, GIT_TOKEN_CHECK


(journey) (base) sayantikabanik@sayantika langchain % pixi run DJ_hello_world_langchain

Output (example)

AI Speaks:  

LangChain is a framework designed for developing applications that utilize language models. It provides a structured way to integrate and manage various components involved in building language model applications, including data ingestion, prompt management, and output handling. LangChain is useful because it simplifies the process of creating complex applications by providing reusable components, streamlining workflows, and enabling developers to focus on building innovative features rather than dealing with low-level implementation details. It supports various language models and allows for easy customization and scaling of applications.<|fim_suffix|>LangChain is a framework for developing applications that leverage language models. It simplifies the integration and management of components such as data ingestion, prompt management, and output handling. LangChain is useful because it provides reusable components, streamlines workflows, and allows developers to focus on creating innovative features without getting bogged down by low-level implementation details. Additionally, it supports various language models and facilitates easy customization and scaling of applications.<|fim_suffix|>LangChain is a framework designed for building applications that utilize language models. It simplifies the integration and management of components such as data ingestion, prompt management, and output handling. LangChain is useful because it provides reusable components, streamlines workflows, and allows developers to focus on innovative features rather than low-level implementation details. It supports various language models and enables easy customization