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import google.generativeai as genai
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from vault import add_to_vault
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# 1. Define the Tool (Limbs)
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def reindex_file(file_path: str, chunk_size: int = 500):
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    """Re-chunks a file with specific granularity when information is vague."""
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    print(f"Action: Re-indexing {file_path}...")
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    # Logic to trigger process_file and add_to_vault goes here
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    return "Vault updated with higher density chunks."
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# 2. Forge the Model with Tools
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model = genai.GenerativeModel(
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    model_name='gemini-1.5-pro',
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    tools=[reindex_file]
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)
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# 3. Execute Autonomous Chat
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chat = model.start_chat(enable_automatic_function_calling=True)
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res = chat.send_message("The context for 'bridge.py' is too thin. Re-index it now.")
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print(res.text)

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import { GoogleGenerativeAI } from "@google/generative-ai";
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// 1. Tool Declaration
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const reindexTool = {
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functionDeclarations: [{
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    name: "reindex_file",
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    description: "Triggers a re-ingestion of a specific file with new parameters.",
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    parameters: {
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    type: "OBJECT",
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    properties: {
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        filePath: { type: "STRING" },
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        chunkSize: { type: "NUMBER" }
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    },
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    required: ["filePath"]
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    }
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}]
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};
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const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
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const model = genAI.getGenerativeModel({
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model: "gemini-1.5-pro",
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tools: [reindexTool],
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});
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// 2. JS requires manual handling of tool outputs or specific SDK wrapper
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async function runRecursiveEngine() {
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    const chat = model.startChat();
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    const result = await chat.sendMessage("Re-index 'vault.js' please.");
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    // SDK handles the function call request if configured
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    console.log(result.response.text());
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}

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import dev.langchain4j.agent.tool.Tool;
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import dev.langchain4j.service.AiServices;
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public class RecursiveEngine {
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    // 1. Define the Tool Limb
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    static class VaultTools {
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        @Tool("Re-chunks and re-indexes a file for better RAG retrieval")
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        public String reindexFile(String filePath, int chunkSize) {
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            System.out.println("Java Sentinel: Re-indexing " + filePath);
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            return "Success: High-density chunks stored.";
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        }
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    }
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    interface Assistant {
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        String chat(String message);
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    }
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    public static void main(String[] args) {
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        // 2. Bind Tools to Gemini
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        Assistant assistant = AiServices.builder(Assistant.class)
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            .chatLanguageModel(GoogleAiGeminiChatModel.builder()
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                .apiKey(System.getenv("GEMINI_API_KEY"))
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                .modelName("gemini-1.5-pro").build())
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            .tools(new VaultTools())
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            .build();
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        // 3. Command
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        System.out.println(assistant.chat("The memory for 'Orchestrator.java' is vague. Re-index it."));
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    }
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}