Agents are one of the most powerful and fascinating approaches to using Large Language Models (LLMs). The explosion of interest in LLMs has led to agents becoming incredibly prevalent in AI-powered use cases.
Using agents allows us to give LLMs access to tools. These tools present an essentially infinite number of possibilities. With tools, LLMs can search the web, do math, run code, and much more.
The LangChain library provides a substantial selection of prebuilt tools. However, in many real-world projects, we'll often find that there are no tools that quite fit our requirements. Meaning we must modify existing tools or build entirely new ones.
In this video, we will explore how to build custom tools for agents in LangChain.
📌 Code Notebook:
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🌲 Pinecone article:
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👋🏼 NLP + LLM Consulting:
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00:00 LangChain agents and tools
01:46 What are LLM tools
03:12 Code notebook setup and prerequisites
05:58 Building a simple LangChain calculator tool
05:50 Initialize the conversational agent
10:08 Updating agent prompts
12:14 Building tools with multiple parameters
15:40 Helping ChatGPT understand images
23:05 What else can LangChain agents do
#artificialintelligence #langchain #openai #nlp
Create Custom Tools for Chatbots in LangChain — LangChain #8
Теги
pythonmachine learningartificial intelligencenatural language processingnlpjames briggschatgpt langchainchatgptlangchain chatbotchatbot langchainlangchain tutorialchatbot tutoriallangchain agentlangchain agent examplelangchain toolsllm agentscustom llm agentai chatgpt-3.5-turbogpt 4langchain agent toolsconversational aiai toolsai agentsai agents exampleslarge language modellarge language models tutorialgpt 3.5langchain
