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Add RALPH-loop recipe to Copilot SDK cookbook
Add iterative RALPH-loop (Read, Act, Log, Persist, Halt) pattern implementations for all four supported languages: - C#/.NET: ralph-loop.cs with documentation - Node.js/TypeScript: ralph-loop.ts with documentation - Python: ralph_loop.py with documentation (async API) - Go: ralph-loop.go with documentation Each recipe demonstrates: - Self-referential iteration where AI reviews its own output - Completion promise detection to halt the loop - Max iteration safety limits - File persistence between iterations Verified against real Copilot SDK APIs: - Python: fully verified end-to-end with github-copilot-sdk - Node.js: fully verified end-to-end with @github/copilot-sdk - C#: compiles and runs successfully with GitHub.Copilot.SDK - Go: compiles against github.com/github/copilot-sdk/go v0.1.23
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cookbook/copilot-sdk/nodejs/ralph-loop.md
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cookbook/copilot-sdk/nodejs/ralph-loop.md
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# RALPH-loop: Iterative Self-Referential AI Loops
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Implement self-referential feedback loops where an AI agent iteratively improves work by reading its own previous output.
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> **Runnable example:** [recipe/ralph-loop.ts](recipe/ralph-loop.ts)
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>
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> ```bash
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> cd nodejs/recipe
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> npm install
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> npx tsx ralph-loop.ts
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> ```
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## What is RALPH-loop?
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RALPH-loop is a development methodology for iterative AI-powered task completion. Named after the Ralph Wiggum technique, it embodies the philosophy of persistent iteration:
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- **One prompt, multiple iterations**: The same prompt is processed repeatedly
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- **Self-referential feedback**: The AI reads its own previous work (file changes, git history)
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- **Completion detection**: Loop exits when a completion promise is detected in output
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- **Safety limits**: Always include a maximum iteration count to prevent infinite loops
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## Example Scenario
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You need to iteratively improve code until all tests pass. Instead of asking Claude to "write perfect code," you use RALPH-loop to:
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1. Send the initial prompt with clear success criteria
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2. Claude writes code and tests
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3. Claude runs tests and sees failures
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4. Loop automatically re-sends the prompt
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5. Claude reads test output and previous code, fixes issues
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6. Repeat until all tests pass and completion promise is output
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## Basic Implementation
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```typescript
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import { CopilotClient } from "@github/copilot-sdk";
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class RalphLoop {
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private client: CopilotClient;
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private iteration: number = 0;
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private maxIterations: number;
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private completionPromise: string;
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private lastResponse: string | null = null;
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constructor(maxIterations: number = 10, completionPromise: string = "COMPLETE") {
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this.client = new CopilotClient();
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this.maxIterations = maxIterations;
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this.completionPromise = completionPromise;
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}
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async run(initialPrompt: string): Promise<string> {
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await this.client.start();
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const session = await this.client.createSession({ model: "gpt-5" });
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try {
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while (this.iteration < this.maxIterations) {
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this.iteration++;
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console.log(`\n--- Iteration ${this.iteration}/${this.maxIterations} ---`);
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// Build prompt including previous response as context
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const prompt = this.iteration === 1
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? initialPrompt
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: `${initialPrompt}\n\nPrevious attempt:\n${this.lastResponse}\n\nContinue improving...`;
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const response = await session.sendAndWait({ prompt });
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this.lastResponse = response?.data.content || "";
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console.log(`Response (${this.lastResponse.length} chars)`);
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// Check for completion promise
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if (this.lastResponse.includes(this.completionPromise)) {
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console.log(`✓ Completion promise detected: ${this.completionPromise}`);
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return this.lastResponse;
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}
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console.log(`Continuing to iteration ${this.iteration + 1}...`);
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}
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throw new Error(
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`Max iterations (${this.maxIterations}) reached without completion promise`
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);
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} finally {
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await session.destroy();
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await this.client.stop();
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}
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}
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}
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// Usage
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const loop = new RalphLoop(5, "COMPLETE");
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const result = await loop.run("Your task here");
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console.log(result);
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```
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## With File Persistence
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For tasks involving code generation, persist state to files so the AI can see changes:
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```typescript
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import fs from "fs/promises";
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import path from "path";
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import { CopilotClient } from "@github/copilot-sdk";
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class PersistentRalphLoop {
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private client: CopilotClient;
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private workDir: string;
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private iteration: number = 0;
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private maxIterations: number;
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constructor(workDir: string, maxIterations: number = 10) {
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this.client = new CopilotClient();
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this.workDir = workDir;
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this.maxIterations = maxIterations;
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}
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async run(initialPrompt: string): Promise<string> {
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await fs.mkdir(this.workDir, { recursive: true });
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await this.client.start();
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const session = await this.client.createSession({ model: "gpt-5" });
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try {
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// Store initial prompt
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await fs.writeFile(path.join(this.workDir, "prompt.md"), initialPrompt);
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while (this.iteration < this.maxIterations) {
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this.iteration++;
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console.log(`\n--- Iteration ${this.iteration} ---`);
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// Build context from previous outputs
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let context = initialPrompt;
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const prevOutputFile = path.join(this.workDir, `output-${this.iteration - 1}.txt`);
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try {
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const prevOutput = await fs.readFile(prevOutputFile, "utf-8");
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context += `\n\nPrevious iteration:\n${prevOutput}`;
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} catch {
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// No previous output yet
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}
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const response = await session.sendAndWait({ prompt: context });
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const output = response?.data.content || "";
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// Persist output
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await fs.writeFile(
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path.join(this.workDir, `output-${this.iteration}.txt`),
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output
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);
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if (output.includes("COMPLETE")) {
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return output;
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}
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}
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throw new Error("Max iterations reached");
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} finally {
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await session.destroy();
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await this.client.stop();
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}
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}
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}
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```
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## Best Practices
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1. **Write clear completion criteria**: Include exactly what "done" looks like
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2. **Use output markers**: Include `<promise>COMPLETE</promise>` or similar in completion condition
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3. **Always set max iterations**: Prevents infinite loops on impossible tasks
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4. **Persist state**: Save files so AI can see what changed between iterations
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5. **Include context**: Feed previous iteration output back as context
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6. **Monitor progress**: Log each iteration to track what's happening
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## Example: Iterative Code Generation
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```typescript
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const prompt = `Write a function that:
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1. Parses CSV data
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2. Validates required fields
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3. Returns parsed records or error
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4. Has unit tests
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5. Output <promise>COMPLETE</promise> when done`;
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const loop = new RalphLoop(10, "COMPLETE");
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const result = await loop.run(prompt);
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```
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## Handling Failures
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```typescript
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try {
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const result = await loop.run(prompt);
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console.log("Task completed successfully!");
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} catch (error) {
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console.error("Task failed:", error.message);
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// Analyze what was attempted and suggest alternatives
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}
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```
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## When to Use RALPH-loop
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**Good for:**
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- Code generation with automatic verification (tests, linters)
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- Tasks with clear success criteria
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- Iterative refinement where each attempt learns from previous failures
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- Unattended long-running improvements
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**Not good for:**
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- Tasks requiring human judgment or design input
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- One-shot operations
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- Tasks with vague success criteria
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- Real-time interactive debugging
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