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| 1 | +// Pseudocode for integrating Self-Adapting into an Agent Framework |
| 2 | + |
| 3 | +class SelfAdaptingAgent { |
| 4 | + private selfEditBuffer: Array<SelfEdit> = []; |
| 5 | + private sftThreshold: number = 10; // Train after 10 edits |
| 6 | + private model: LLM; |
| 7 | + |
| 8 | + async handleInteraction(input: string, context: any): Promise<string> { |
| 9 | + const response = await this.model.generateResponse(input, context); |
| 10 | + |
| 11 | + // ... (User interacts, provides feedback, or agent encounters a novel situation) |
| 12 | + |
| 13 | + // Generate Self-Edit |
| 14 | + const selfEdit = this.generateSelfEdit(input, response, context); |
| 15 | + this.selfEditBuffer.push(selfEdit); |
| 16 | + |
| 17 | + // Check if ready for SFT |
| 18 | + if (this.selfEditBuffer.length >= this.sftThreshold) { |
| 19 | + await this.performSFT(); |
| 20 | + this.selfEditBuffer = []; // Clear buffer |
| 21 | + } |
| 22 | + |
| 23 | + return response; |
| 24 | + } |
| 25 | + |
| 26 | + private generateSelfEdit(input: string, output: string, context: any): SelfEdit { |
| 27 | + // Use LLM to analyze the interaction and suggest improvements |
| 28 | + // This is the core "self-generation" step |
| 29 | + const prompt = ` |
| 30 | + You are an AI agent reflecting on a recent interaction. |
| 31 | + Input: ${input} |
| 32 | + Your Output: ${output} |
| 33 | + Context: ${JSON.stringify(context)} |
| 34 | + What is one way you could improve your response? Generate a corrected version or specify a hyperparameter change. |
| 35 | + `; |
| 36 | + const edit = await this.model.generate(prompt); // This generates the "self-edit" |
| 37 | + return { input, original_output: output, improved_output: edit }; |
| 38 | + } |
| 39 | + |
| 40 | + private async performSFT() { |
| 41 | + // Use the selfEditBuffer to create a fine-tuning dataset |
| 42 | + const dataset = this.selfEditBuffer.map(edit => ({ |
| 43 | + prompt: edit.input, |
| 44 | + completion: edit.improved_output |
| 45 | + })); |
| 46 | + |
| 47 | + // Perform lightweight SFT on the model |
| 48 | + await this.model.fineTune(dataset); |
| 49 | + |
| 50 | + // Optional: Log performance before/after for reward signal |
| 51 | + // await this.evaluatePerformance(); |
| 52 | + } |
| 53 | +} |
| 54 | + |
| 55 | +interface SelfEdit { |
| 56 | + input: string; |
| 57 | + original_output: string; |
| 58 | + improved_output: string; |
| 59 | +} |
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