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+# Lance + LangChain on Pandas 2.0
+
+## simple Pandas 2.0 documentation Q&A answering bot using LangChain
+
+To demonstrate using Lance, we’re going to build a simple Q&A answering bot using LangChain — an open-source framework that allows you to build composable LLM-based applications easily. We’ll use chat-langchain, a simple Q&A answering bot app as an example. Note: in this fork of chat-langchain, we’re also using a forked version of LangChain integration where we’ve built a Lance integration.
+
+The first step is to generate embeddings. You could build a bot using your own data, like a wiki page or internal documentation. For this example, we’re going to use the Pandas API documentation. LangChain offers document loaders to read and pre-process many document types. Since the Pandas API is in HTML, reading the docs is straightforward:
+
+```python
+for p in Path("./pandas.documentation").rglob("*.html"):
+   if p.is_dir():
+     continue
+   loader = UnstructuredHTMLLoader(p)
+   raw_document = loader.load()
+   docs = docs + raw_document
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