Building Your Own Langchain Agents and Tools with LLMs: A Step-by-Step Tutorial
World of Large Language models are taking a path that other technologies have taken till date. Take a peek at how LLMs are used to call Python functions and based on the Prompts generated by the Agent Classes inside the LangChain library. You read it correct, LLMs call the Python function anyone can write, and use the value returned by the function to make further search and automation. The code used in this post is at https://github.com/insightbuilder/python_de_learners_data/blob/main/code_script_notebooks/projects/langChain_exploration/agentsandtools.ipynb
Building Your Own Langchain Agents and Tools with LLMs: A Step-by-Step Tutorial World of Large Language models are taking a path that other technologies have taken till date. Take a peek at how LLMs are used to call Python functions and based on the Prompts generated by the Agent Classes inside the LangChain library. You read it correct, LLMs call the Python function anyone can write, and use the value returned by the function to make further search and automation. The code used in this post is at https://github.com/insightbuilder/python_de_learners_data/blob/main/code_script_notebooks/projects/langChain_exploration/agentsandtools.ipynb data-analysis
Building Langchain Agents Tools LLMs StepbyStep Tutorial World Large Language model taking path technology taken till date Take peek LLMs used call Python function based Prompts generated Agent Classes inside LangChain library read correct LLMs call Python function anyone write use value returned function make search automation code used post httpsgithubcominsightbuilderpythondelearnersdatablobmaincodescriptnotebooksprojectslangChainexplorationagentsandtoolsipynb dataanalysis