LangChain Tutorial (Python) #6: Self-Reasoning Agents with Tools
#openai #langchain
Agents are one of the most important features of Langchain and extremely fun to use.
We can give our agent an instruction, and it will use the power of LLM's and Tools to figure out the actions to take, the sequence of events and then use tools the achieve it's goals.
☕ Buy me a coffee:
https://www.buymeacoffee.com/leonvanzyl
📑 Useful Links:
Langchain Python docs: https://python.langchain.com/docs/get...
Source Code: https://github.com/leonvanzyl/langcha...
Langsmith: https://www.langchain.com/langsmith
Tavily Search API: https://app.tavily.com/home
🕒 TIMESTAMPS:
00:00 - Intro
00:22 - Project setup
01:40 - Prompt Agent Scratchpad
02:59 - Agent Types
03:21 - Creating our agent
03:50 - Create agent executor
04:41 - Add Tavily Search Tool
05:08 - Tavily API Key
05:52 - Langsmith
06:53 - Adding chat history
09:28 - Add Retriever as Tool
11:38 - Create retriever tool