langflow/docs/docs/examples/conversation-chain.mdx
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🔧 chore(chains.mdx): fix formatting and indentation for better code readability
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🔧 chore(chains.mdx): fix formatting and indentation for better code readability
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🔧 chore(chains.mdx): fix formatting and indentation for better code readability
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📝 chore(docs): update import statements for Admonition component in examples

📝 chore(docs): update link in Prompts component to use Admonition component

📝 chore(docs): update import statements for Admonition component in examples

📝 chore(docs): update link in Conversation Chain component to use Admonition component

📝 chore(docs): update import statements for Admonition component in examples

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import Admonition from "@theme/Admonition";
# Conversation Chain
This example shows how to instantiate a simple `ConversationChain` component using a Language Model (LLM). Once the Node Status turns green 🟢, the chat will be ready to take in user messages. Here, we used `ChatOpenAI` to act as the required LLM input, but you can use any LLM for this purpose.
<Admonition type="info">
Make sure to always get the API key from the provider.
</Admonition>
## ⛓️ Langflow Example
import ThemedImage from "@theme/ThemedImage";
import useBaseUrl from "@docusaurus/useBaseUrl";
import ZoomableImage from "/src/theme/ZoomableImage.js";
<ZoomableImage
alt="Docusaurus themed image"
sources={{
light: "img/basic-chat.png",
}}
/>
#### <a target="\_blank" href="json_files/Basic_Chat.json" download>Download Flow</a>
<Admonition type="note" title="LangChain Components 🦜🔗">
- [`ConversationChain`](https://python.langchain.com/docs/modules/chains/)
- [`ChatOpenAI`](https://python.langchain.com/docs/modules/model_io/models/chat/integrations/openai)
</Admonition>