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library for working with LLMs in Grafana plugins","maintainers":[{"email":"bot@grafana.com","name":"grafanabot"}],"readme":"# Frontend functions for LLM interaction\n\nThis is a collection of convenience functions and components to make interacting with LLM functionality in Grafana easier.\n\nFirst, add the latest version of `@grafana/llm` to your dependencies in package.json:\n\n```json\n{\n  \"dependencies\": {\n    \"@grafana/llm\": \"0.22.0\"\n  }\n}\n```\n\n**Note:** If you're writing tests that import from `@grafana/llm`, you may need to configure Jest to handle ES modules. See the Jest Configuration section below for details.\n\n## Jest Configuration\n\n### ESM errors with Jest\n\nWhen writing tests that import from `@grafana/llm`, you may encounter Jest errors like `SyntaxError: Cannot use import statement outside a module`. This happens because `@grafana/llm` uses ES module dependencies that Jest needs to transform.\n\nIf you're using Grafana's plugin scaffolding, extend your Jest configuration to include the additional ES modules. For convenience, `@grafana/llm` exports the required module list:\n\n```javascript\n// jest.config.js\nconst { grafanaESModules, nodeModulesToTransform } = require('./.config/jest/utils');\nconst { grafanaLLMESModules } = require('@grafana/llm/jest');\n\nmodule.exports = {\n  // Jest configuration provided by Grafana scaffolding\n  ...require('./.config/jest.config'),\n  transformIgnorePatterns: [nodeModulesToTransform([...grafanaESModules, ...grafanaLLMESModules])],\n};\n```\n\n### MCP Functionality\n\nIf you're testing code that uses MCP (Model Context Protocol) features, add the `TransformStream` polyfill to your `jest-setup.js`:\n\n```javascript\n// jest-setup.js\n// Jest setup provided by Grafana scaffolding\nimport './.config/jest-setup';\n\n// Add this import and global for MCP functionality\nimport { TransformStream } from 'node:stream/web';\nimport { TextEncoder } from 'util';\n\n// TextEncoder may already be present in your setup\nglobal.TextEncoder = TextEncoder;\n// Add this line for MCP TransformStream support\nglobal.TransformStream = TransformStream;\n```\n\n## Usage\n\nThen in your components you can use the `llm` object from `@grafana/llm` like so:\n\n```typescript\nimport React, { useState } from 'react';\nimport { useAsync } from 'react-use';\nimport { scan } from 'rxjs/operators';\n\nimport { openai } from '@grafana/llm';\nimport { PluginPage } from '@grafana/runtime';\n\nimport { Button, Input, Spinner } from '@grafana/ui';\n\nconst MyComponent = (): JSX.Element => {\n  const [input, setInput] = React.useState('');\n  const [message, setMessage] = React.useState('');\n  const [reply, setReply] = useState('');\n\n  const { loading, error } = useAsync(async () => {\n    const enabled = await openai.enabled();\n    if (!enabled) {\n      return false;\n    }\n    if (message === '') {\n      return;\n    }\n    // Stream the completions. Each element is the next stream chunk.\n    const stream = openai\n      .streamChatCompletions({\n        // model: openai.Model.LARGE, // defaults to BASE, use larger model for longer context and complex tasks\n        messages: [\n          { role: 'system', content: 'You are a helpful assistant with deep knowledge of the Grafana, Prometheus and general observability ecosystem.' },\n          { role: 'user', content: message },\n        ],\n      })\n      .pipe(\n        // Accumulate the stream chunks into a single string.\n        scan((acc, delta) => acc + delta, '')\n      );\n    // Subscribe to the stream and update the state for each returned value.\n    return stream.subscribe(setReply);\n  }, [message]);\n\n  if (error) {\n    // TODO: handle errors.\n    return null;\n  }\n\n  return (\n    <div>\n      <Input value={input} onChange={(e) => setInput(e.currentTarget.value)} placeholder=\"Enter a message\" />\n      <br />\n      <Button type=\"submit\" onClick={() => setMessage(input)}>\n        Submit\n      </Button>\n      <br />\n      <div>{loading ? <Spinner /> : reply}</div>\n    </div>\n  );\n};\n```\n","readmeFilename":"README.md"}