Step by step instructions for setting up basic LangChain agents to query our internal database since I am a beginner with Python.
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Fan-out diagram
The searches the AI actually ran for this prompt.
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Step by step instructions for setting up basic LangChain agents to query our internal database since I am a beginner with Python.
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
LangChain Python SQL database agent tutorial SQLDatabaseToolkit create_agent official docs Google ↗
LangChain agents create_agent documentation Python tools official docs Google ↗
- Python.org · python.org
- Visual Studio Code · code.visualstudio.com
- OpenAI API Keys · platform.openai.com
- SQLDatabaseToolkit | langchain_community · reference.langchain.com
- create_agent | langchain · reference.langchain.com
- SQLDatabase Toolkit · langchain.docs-hub.com
- base | langchain_community · reference.langchain.com
- create_sql_agent | langchain_community · reference.langchain.com
- LangChain Python Quickstart · docs.langchain.com
- LangChain SQL Agent Tutorial · docs.langchain.com
- LangChain Documentation · python.langchain.com
Queries
2 queries · click a column to sort