Gemini #100
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,61 @@ | ||
| import { | ||
| CompletionHandler, | ||
| IInlineCompletionContext | ||
| } from '@jupyterlab/completer'; | ||
| import { ChatGoogleGenerativeAI } from '@langchain/google-genai'; | ||
| import { AIMessage, SystemMessage } from '@langchain/core/messages'; | ||
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| import { BaseCompleter } from '../../base-completer'; | ||
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| export class GeminiCompleter extends BaseCompleter { | ||
| constructor(options: BaseCompleter.IOptions) { | ||
| super(options); | ||
| this._completer = new ChatGoogleGenerativeAI({ | ||
| model: 'gemini-pro', | ||
| ...options.settings | ||
| }); | ||
| } | ||
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| async fetch( | ||
| request: CompletionHandler.IRequest, | ||
| context: IInlineCompletionContext | ||
| ) { | ||
| const { text, offset: cursorOffset } = request; | ||
| const prompt = text.slice(0, cursorOffset); | ||
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| const trimmedPrompt = prompt.trim(); | ||
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| const messages = [ | ||
| new SystemMessage(this.systemPrompt), | ||
| new AIMessage(trimmedPrompt) | ||
| ]; | ||
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| try { | ||
| const response = await this._completer.invoke(messages); | ||
| const items = []; | ||
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| // Gemini can return string or complex content, a list of string/images/other. | ||
| if (typeof response.content === 'string') { | ||
| items.push({ | ||
| insertText: response.content | ||
| }); | ||
| } else { | ||
| response.content.forEach(content => { | ||
| if (content.type !== 'text') { | ||
| return; | ||
| } | ||
| items.push({ | ||
| insertText: content.text, | ||
| filterText: prompt.substring(trimmedPrompt.length) | ||
| }); | ||
| }); | ||
| } | ||
| return { items }; | ||
| } catch (error) { | ||
| console.error('Error fetching completions', error); | ||
| return { items: [] }; | ||
| } | ||
| } | ||
|
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| protected _completer: ChatGoogleGenerativeAI; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,9 @@ | ||
| export default ` | ||
| <i class="fas fa-exclamation-triangle"></i> This extension is still very much experimental. It is not an official Google extension. | ||
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| 1. Go to <https://aistudio.google.com> and create an API key. | ||
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| 2. Open the JupyterLab settings and go to the **Ai providers** section to select the \`Gemini\` | ||
| provider and add your API key (required). | ||
| 3. Open the chat, or use the inline completer. | ||
| `; |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,64 @@ | ||
| { | ||
| "$schema": "http://json-schema.org/draft-07/schema#", | ||
| "type": "object", | ||
| "properties": { | ||
| "temperature": { | ||
| "type": "number", | ||
| "description": "Amount of randomness injected into the response. Ranges from 0 to 1. Use temp closer to 0 for analytical / multiple choice, and temp closer to 1 for creative and generative tasks." | ||
| }, | ||
| "topK": { | ||
| "type": "number", | ||
| "description": "Only sample from the top K options for each subsequent token. Used to remove \"long tail\" low probability responses." | ||
| }, | ||
| "topP": { | ||
| "type": "number", | ||
| "description": "Nucleus sampling parameter. Only the smallest set of most probable tokens with probabilities that add up to top_p or higher are kept for generation." | ||
| }, | ||
| "maxOutputTokens": { | ||
| "type": "number", | ||
| "description": "The maximum number of tokens to generate in the response." | ||
| }, | ||
| "stopSequences": { | ||
| "type": "array", | ||
| "items": { | ||
| "type": "string" | ||
| }, | ||
| "description": "A list of strings upon which to stop generating. You probably want something like [\"\\n\\nHuman:\"] for chat conversations." | ||
| }, | ||
| "streaming": { | ||
| "type": "boolean", | ||
| "description": "Whether to stream the results or not" | ||
| }, | ||
| "apiKey": { | ||
| "type": "string", | ||
| "description": "Google AI Studio API key" | ||
| }, | ||
| "model": { | ||
| "type": "string", | ||
| "description": "Model name to use (e.g., gemini-pro, gemini-2.0-flash, etc.)", | ||
| "default": "gemini-pro" | ||
| }, | ||
| "baseURL": { | ||
| "type": "string", | ||
| "description": "Base URL for the Google AI API" | ||
| }, | ||
| "safetySettings": { | ||
| "type": "array", | ||
| "description": "Safety settings for content filtering", | ||
| "items": { | ||
| "type": "object", | ||
| "properties": { | ||
| "category": { | ||
| "type": "string" | ||
| }, | ||
| "threshold": { | ||
| "type": "string" | ||
| } | ||
| } | ||
| } | ||
| } | ||
| }, | ||
| "additionalProperties": false, | ||
| "description": "Input to Google Generative AI Chat class.", | ||
| "definitions": {} | ||
| } |
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The latest version of
@langchain/google-genaiseems to depend on newer releases of@langchain/core, so bumping the other langchain dependencies here.