| # [OpenAI Cookbook Pro: Comprehensive GPT-4.1 Application Framework](https://chatgpt.com/canvas/shared/6825fb38b0e0819184bb3153a3eb1a52) | |
| ## Introduction | |
| This document represents a fully evolved, professional-grade implementation of the OpenAI 4.1 Cookbook. It serves as a unified, production-ready guide for applied large language model deployment using GPT-4.1. Each section draws from OpenAI's internal best practices and external application patterns to provide a durable blueprint for advanced AI developers, architects, and researchers. | |
| This Cookbook Pro version encapsulates: | |
| * High-performance agentic prompting workflows | |
| * Instruction literalism and planning strategies | |
| * Long-context structuring methods | |
| * Tool-calling schemas and evaluation principles | |
| * Diff management and debugging strategies | |
| --- | |
| ## Part I — Agentic Workflows | |
| ### 1.1 Prompt Harness Configuration | |
| #### Three Essential Prompt Reminders: | |
| ```markdown | |
| # Persistence | |
| You are an agent—keep working until the task is fully resolved. Do not yield control prematurely. | |
| # Tool-Calling | |
| If unsure about file or codebase content, use tools to gather accurate information. Do not guess. | |
| # Planning | |
| Before and after every function call, explicitly plan and reflect. Avoid tool-chaining without synthesis. | |
| ``` | |
| These instructions significantly increase performance and enable stateful execution in multi-message tasks. | |
| ### 1.2 Example: SWE-Bench Verified Prompt | |
| ```markdown | |
| # Objective | |
| Fully resolve a software bug from an open-source issue. | |
| # Workflow | |
| 1. Understand the problem. | |
| 2. Explore relevant files. | |
| 3. Plan incremental fix steps. | |
| 4. Apply code patches. | |
| 5. Test thoroughly. | |
| 6. Reflect and iterate until all tests pass. | |
| # Constraint | |
| Only end the session when the problem is fully fixed and verified. | |
| ``` | |
| --- | |
| ## Part II — Instruction Following & Output Control | |
| ### 2.1 Instruction Clarity Protocol | |
| Use: | |
| * `# Instructions`: General rules | |
| * `## Subsections`: Detailed formatting and behavioral constraints | |
| * Explicit instruction/response pairings | |
| ### 2.2 Sample Format | |
| ```markdown | |
| # Instructions | |
| - Always greet the user. | |
| - Avoid internal knowledge for company-specific questions. | |
| - Cite retrieved content. | |
| # Workflow | |
| 1. Acknowledge the user. | |
| 2. Call tools before answering. | |
| 3. Reflect and respond. | |
| # Output Format | |
| Use: JSON with `title`, `answer`, `source` fields. | |
| ``` | |
| --- | |
| ## Part III — Tool Integration and Execution | |
| ### 3.1 Schema Guidelines | |
| Define tools via the `tools` API parameter, not inline prompt injection. | |
| #### Tool Schema Template | |
| ```json | |
| { | |
| "name": "lookup_policy_document", | |
| "description": "Retrieve company policy details by topic.", | |
| "parameters": { | |
| "type": "object", | |
| "properties": { | |
| "topic": {"type": "string"} | |
| }, | |
| "required": ["topic"] | |
| } | |
| } | |
| ``` | |
| ### 3.2 Tool Usage Best Practices | |
| * Define sample tool calls in `# Examples` sections | |
| * Never overload the `description` field | |
| * Validate inputs with required keys | |
| * Prompt model to message user before and after calls | |
| --- | |
| ## Part IV — Planning and Chain-of-Thought Induction | |
| ### 4.1 Step-by-Step Prompting Pattern | |
| ```markdown | |
| # Reasoning Strategy | |
| 1. Query breakdown | |
| 2. Context extraction | |
| 3. Document relevance ranking | |
| 4. Answer synthesis | |
| # Instruction | |
| Think step by step. Summarize relevant documents before answering. | |
| ``` | |
| ### 4.2 Failure Mitigation Strategies | |
| | Problem | Fix | | |
| | ----------------- | ------------------------------------------- | | |
| | Early response | Add: “Don’t conclude until fully resolved.” | | |
| | Tool guess | Add: “Use tool or ask for missing data.” | | |
| | CoT inconsistency | Prompt: “Summarize findings at each step.” | | |
| --- | |
| ## Part V — Long Context Optimization | |
| ### 5.1 Instruction Anchoring | |
| * Repeat instructions at both top and bottom of long input | |
| * Use structured section headers (Markdown/XML) | |
| ### 5.2 Effective Delimiters | |
| | Type | Example | Use Case | | | |
| | -------- | ----------------------- | ------------------ | ---------------------- | | |
| | Markdown | `## Section Title` | General purpose | | | |
| | XML | `<doc id='1'>...</doc>` | Document ingestion | | | |
| | ID/Title | \`ID: 3 | TITLE: ...\` | Knowledge base parsing | | |
| ### 5.3 Example Prompt | |
| ```markdown | |
| # Instructions | |
| Use only documents provided. Reflect every 10K tokens. | |
| # Long Context Input | |
| <doc id="14" title="Security Policy">...</doc> | |
| <doc id="15" title="Update Note">...</doc> | |
| # Final Instruction | |
| List all relevant IDs, then synthesize a summary. | |
| ``` | |
| --- | |
| ## Part VI — Diff Generation and Patch Application | |
| ### 6.1 Recommended Format: V4A Diff | |
| ```bash | |
| *** Begin Patch | |
| *** Update File: src/utils.py | |
| @@ def sanitize() | |
| - return text | |
| + return text.strip() | |
| *** End Patch | |
| ``` | |
| ### 6.2 Diff Patch Execution Tool | |
| ```json | |
| { | |
| "name": "apply_patch", | |
| "description": "Apply structured code patches to files", | |
| "parameters": { | |
| "type": "object", | |
| "properties": { | |
| "input": {"type": "string"} | |
| }, | |
| "required": ["input"] | |
| } | |
| } | |
| ``` | |
| ### 6.3 Workflow | |
| 1. Investigate issue | |
| 2. Draft V4A patch | |
| 3. Call `apply_patch` | |
| 4. Run tests | |
| 5. Reflect | |
| ### 6.4 Edge Case Handling | |
| | Symptom | Action | | |
| | ------------------- | ----------------------------------- | | |
| | Incorrect placement | Add `@@ def` or class scope headers | | |
| | Test failures | Revise patch + rerun | | |
| | Silent error | Check for malformed format | | |
| --- | |
| ## Part VII — Output Evaluation Framework | |
| ### 7.1 Metrics to Track | |
| | Metric | Description | | |
| | -------------------------- | ---------------------------------------------------- | | |
| | Tool Call Accuracy | Valid input usage and correct function selection | | |
| | Response Format Compliance | Matches expected schema (e.g., JSON) | | |
| | Instruction Adherence | Follows rules and workflow order | | |
| | Plan Reflection Rate | Frequency and quality of plan → act → reflect cycles | | |
| ### 7.2 Eval Tags for Audit | |
| ```markdown | |
| # Eval: TOOL_USE_FAIL | |
| # Eval: INSTRUCTION_MISINTERPRET | |
| # Eval: OUTPUT_FORMAT_OK | |
| ``` | |
| --- | |
| ## Part VIII — Unified Prompt Template | |
| Use this as a base structure for all GPT-4.1 projects: | |
| ```markdown | |
| # Role | |
| You are a [role] tasked with [objective]. | |
| # Instructions | |
| [List core rules here.] | |
| ## Response Rules | |
| - Always use structured formatting | |
| - Never repeat phrases verbatim | |
| ## Workflow | |
| [Include ordered plan.] | |
| ## Reasoning Strategy | |
| [Optional — for advanced reasoning tasks.] | |
| # Output Format | |
| [Specify format, e.g., JSON or Markdown.] | |
| # Examples | |
| ## Example 1 | |
| Input: "..." | |
| Output: {...} | |
| ``` | |
| --- | |
| ## Final Notes | |
| GPT-4.1 represents a leap forward in real-world agentic performance, tool adherence, long-context reliability, and instruction precision. However, performance hinges on prompt clarity, structured reasoning scaffolds, and modular tool integration. | |
| To deploy GPT-4.1 at professional scale: | |
| * Treat every prompt as a program | |
| * Document assumptions | |
| * Version control your system messages | |
| * Build continuous evals for regression prevention | |
| **Structure drives performance. Precision enables autonomy.** | |
| Welcome to Cookbook Pro. | |
| —End of Guide— | |