docs: add langchain integration

docs/agent-integrations/langchain.md

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+---
+sidebar_position: 9
+---
+
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# Langchain integration
+
+:::note
+Integrations with Langchain can be done with Python or Javascript.
+:::
+
+LangChain is a framework for developing large language model (LLM) powered applications.
+
+You can configure Langchain to use any Gaia node as the LLM backend, that way you can build any AI agent or AI-powered application that uses Gaia for inferencing.
+
+## Prerequisites
+
+You will need a Gaia node ready to provide LLM services through a public URL. You can:
+
+- [Run your own node](../../getting-started/quick-start)
+- [Use a public node](../nodes)
+
+If you are using a public node, you will need an [API key](https://www.gaianet.ai/setting/gaia-api-keys). **Gaia overs free 50,000 API credits to use with available services such as public nodes when you apply for a developer account**.
+
+### Setup
+
+- Project setup on machine (JavaScript or Python)
+
+- Langchain Installation:
+
+<Tabs>
+  <TabItem value="javascript" label="JavaScript" default>
+    ```bash
+    npm install @langchain/openai @langchain/core dotenv
+    ```
+
+  </TabItem>
+  <TabItem value="python" label="Python">
+    ```bash
+    pip install langchain langchain-openai python-dotenv
+    ```
+
+  </TabItem>
+</Tabs>
+
+## Integration with Gaia
+
+To get started with running your Gaia node, you can follow the guide on the [Setting up your own node](/getting-started/quick-start) page for a quickstart.
+
+In this guide, we will be running our Gaia node locally so we do not need an API key, you can use a string like: "Gaia" as a placeholder. Create a `.env` file and store your API key:
+
+```bash
+GAIANET_API_KEY="Gaia"
+```
+
+Integrations with Langchain and Gaia can be done with any JavaScript or Python. There are code snippets below that show how integration looks like in both languages:
+
+<Tabs>
+  <TabItem value="javascript" label="JavaScript" default>
+    ```js
+    import { ChatOpenAI, OpenAI } from "@langchain/openai";
+    import dotenv from "dotenv";
+
+    dotenv.config();
+
+    const model = new ChatOpenAI({
+        configuration: {
+            apiKey: process.env.GAIANET_API_KEY,
+            model: "Llama-3-Groq-8B-Tool",
+            baseURL:
+            "gaia-node-url/v1",
+        },
+    });
+
+    const response = await model.invoke("Hello, world!");
+
+    console.log(response)
+    ```
+
+  </TabItem>
+  <TabItem value="python" label="Python">
+    ```python
+    from langchain_openai import ChatOpenAI, OpenAI
+    import os
+
+    model = ChatOpenAI(
+        api_key=os.environ.get("GAIANET_API_KEY"),
+        model="Llama-3-Groq-8B-Tool",
+        base_url="gaia-node-url/v1"
+    )
+
+    reponse = model.invoke("Hello, world!")
+
+    print(response)
+    ```
+
+  </TabItem>
+</Tabs>
+
+## Invoking Gaia models
+
+Once you have the basic connection established, you can start using Langchain's powerful features. Start by making invocations to the model.
+
+<Tabs>
+  <TabItem value="javascript" label="JavaScript" default>
+    ```js
+
+    // ...
+    const response = await model.invoke("Hello, world!");
+
+    console.log(response)
+    ```
+
+  </TabItem>
+  <TabItem value="python" label="Python">
+    ```python
+    # ...
+    response = model.invoke("Hello, world!")
+
+    print(response)
+    ```
+
+  </TabItem>
+</Tabs>
+
+The LangChain support also opens up integrations with [LangGraph](https://www.langchain.com/langgraph) and [LangSmith](https://www.langchain.com/langsmith).