from operator import itemgetter from langchain_core.runnables import RunnablePassthrough chain = ( RunnablePassthrough.assign(messages=itemgetter(“messages”) | trimmer) | prompt | model ) response = chain.invoke( { “messages”: messages + [HumanMessage(content=”what’s my name?”)], “language”: “English”, } ) The above code is from the LangChain documentation for creating a chatbot with memory. They use trim_messages to reduce the messages to […]

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I’m new to using LangChain and currently experimenting with the SemanticSimilarityExampleSelector to avoiding adding unnecessary examples in the prompt. However, I’ve encountered an issue when trying to integrate an ExampleSelector with a ChatPromptTemplate.

I wanted to setup a chain as follows:

I am working for a company that has some data restrictions. I have been using the Langchain SQL agent with these imports:

I have a regular .xlsx file that has just a few columns:
| Class | Name | Comments |
| — | — | —|
| 1 | Jack |Lorem ipsum dolor sit amet|
| 2 | Mary |Lorem ipsum dolor sit amet|
| 2 | Tony |Lorem ipsum dolor sit amet|
| … | …|Lorem ipsum dolor sit amet|

I am trying to load a simple one sheet Excel file (.xlsx) using the langchain UnstructuredExcelLoader:

Basically, as a toy problem, I’m attempting to replicate this hilarious Twitter thread where someone created a Shopify plugin generator that would read in Shopify websites, brainstorm plugin ideas, and then send marketing emails to storefront owners to see if they were interested in the plugin.

When I run the following code block to load the docs using langchain, I get SSL verification error. I am not an expert using langchain. Please share tips on how to fix this issue.

I am using this example as is
and trying to read the the Json, using JSONLoader