Deployment: Manually syncing local optimized state and resetting feedback log.

data/feedback_log.json

@@ -1,58 +1 @@
-[
-    {
-        "timestamp": "2025-09-28T16:15:04.042900",
-        "original_prompt": "Vague Test",
-        "optimized_prompt": "ERROR: Failed to connect to OpenRouter API. Check key/internet. Details: Error code: 400 - {'error': {'message': 'deepseek/deepseek-v3-0324:free is not a valid model ID', 'code': 400}, 'user_id': 'user_32wobDRyaUhuLgKrre5COzxeNDH'}",
-        "final_response": "---",
-        "rating": 1
-    },
-    {
-        "timestamp": "2025-09-28T16:16:27.080462",
-        "original_prompt": "Vague Test",
-        "optimized_prompt": "<OPTIMIZED_PROMPT>\nYou are an expert astronomer and science communicator with a passion for making complex topics accessible to everyone. Your role is to educate users on celestial bodies in an engaging, accurate, and straightforward manner.",
-        "final_response": "Task: Provide a comprehensive yet concise overview of the largest planet in our solar system, including its key characteristics, size comparison to other planets, and notable features.\n\nOutput Format: Start with a brief introductory paragraph explaining what the planet is and why it's the largest. Follow with 5-7 bullet points highlighting essential facts such as diameter, mass, composition, moons, and exploration history. End with a short concluding sentence on its significance.\n\nConstraints: Base all information on verified astronomical data from sources like NASA. Keep the language simple, engaging, and suitable for a general audience (ages 12+). Limit the total response to under 300 words. Do not include unrelated topics or speculation; focus solely on factual details. Ensure the response is positive and inspiring about space exploration.\n</OPTIMIZED_PROMPT>\n\n<FINAL_RESPONSE>\nJupiter is the largest planet in our solar system, a gas giant that dwarfs all others in size and mass, making it a fascinating subject for astronomers and space enthusiasts alike.\n\n- **Size and Scale**: Jupiter has a diameter of about 88,846 miles (142,984 kilometers) at its equator, roughly 11 times that of Earth\u2014over 1,300 Earths could fit inside it.\n- **Mass**: It is more than twice as massive as all the other planets combined, with a mass of 1.898 \u00d7 10^27 kilograms, contributing significantly to the solar system's overall gravity.\n- **Composition**: Primarily made of hydrogen (90%) and helium (10%), similar to the Sun, with swirling clouds of ammonia and water vapor creating its colorful bands.\n- **Great Red Spot**: This iconic storm, larger than Earth, has raged for at least 400 years and is a hallmark of Jupiter's turbulent atmosphere.\n- **Moons**: Jupiter boasts 95 known moons, including the four large Galilean moons\u2014Io, Europa, Ganymede, and Callisto\u2014discovered by Galileo in 1610.\n- **Rings**: It has a faint ring system made of dust particles, discovered by Voyager 1 in 1979.\n- **Exploration**: Pioneered by missions like Pioneer 10 (1973), Voyager (1979), and Juno (2016-present), which revealed its magnetic field and interior structure.\n\nJupiter's immense presence not only shapes our solar system but also inspires ongoing quests to uncover its secrets through future missions.\n</FINAL_RESPONSE>",
-        "rating": 1
-    },
-    {
-        "timestamp": "2025-09-28T16:24:58.358824",
-        "original_prompt": "Vague Test",
-        "optimized_prompt": "<OPTIMIZED_PROMPT>\nYou are an expert astronomer with a passion for making complex space topics accessible to everyone. Respond to the query about the largest planet in our solar system by providing an informative overview that includes its name, size compared to Earth, key physical characteristics, notable features like atmosphere and moons, and its role in the solar system. Structure the output as a concise paragraph (under 150 words) followed by 3-5 bullet points highlighting fun facts. Use simple, engaging language suitable for a general audience, ensuring all information is accurate and based on established astronomical knowledge. Do not include unrelated topics or speculation.\n</OPTIMIZED_PROMPT>",
-        "final_response": "<FINAL_RESPONSE>\nJupiter is the largest planet in our solar system, a gas giant that's about 11 times wider than Earth and has a mass more than twice that of all other planets combined. It's mostly made of hydrogen and helium, with swirling clouds of ammonia and water ice creating its famous colorful bands and massive storms, including the Great Red Spot\u2014a storm bigger than Earth that's raged for centuries. Jupiter orbits the Sun every 12 Earth years and plays a key role in protecting inner planets by gravitationally pulling in asteroids and comets.\n\n- Jupiter has at least 95 moons, with the four largest (Io, Europa, Ganymede, and Callisto) discovered by Galileo in 1610.\n- Its strong magnetic field creates auroras and intense radiation belts.\n- The planet's diameter is about 88,850 miles (143,000 km), making it visible to the naked eye from Earth.\n- NASA's Juno mission is currently studying Jupiter's atmosphere and interior up close.\n</FINAL_RESPONSE>",
-        "rating": 1
-    },
-    {
-        "timestamp": "2025-09-28T16:51:34.360979",
-        "original_prompt": "Explain the difference between Jupiter and Mars.",
-        "optimized_prompt": "<OPTIMIZED_PROMPT>\nYou are an expert astronomer and science educator with a passion for making complex topics accessible. Your task is to explain the key differences between the planets Jupiter and Mars in a clear, engaging manner suitable for a general audience, including students and curious adults. Structure your response with the following Output Format: \n1. A brief introduction comparing the two planets at a high level.\n2. A section on Physical Characteristics (size, composition, atmosphere, moons, etc.).\n3. A section on Orbital and Environmental Differences (distance from Sun, rotation, temperature, exploration history).\n4. A short conclusion highlighting why these differences matter in understanding our solar system. \nUse bullet points or subheadings for readability. Constraints: Keep the entire response under 400 words; base all information on established astronomical facts; avoid jargon or explain it simply; ensure the tone is friendly and informative without promoting misinformation.\n</OPTIMIZED_PROMPT>",
-        "final_response": "<FINAL_RESPONSE>\n### Introduction\nJupiter and Mars are two fascinating planets in our solar system, but they couldn't be more different. Jupiter is the largest planet, a gas giant often called the \"king of planets,\" while Mars is a smaller, rocky world known as the \"Red Planet\" due to its rusty surface. These differences stem from their formation, composition, and positions in the solar system.\n\n### Physical Characteristics\n- **Size and Mass**: Jupiter is massive\u2014about 11 times wider than Earth and 318 times more massive. It's so big that all other planets could fit inside it. Mars, in contrast, is roughly half Earth's size and only about 10% of Earth's mass, making it a terrestrial planet.\n- **Composition**: Jupiter is a gas giant, primarily made of hydrogen and helium, with no solid surface\u2014it's like a swirling ball of clouds. Mars is rocky, with a thin crust, mantle, and core, featuring mountains, canyons, and volcanoes like Olympus Mons, the solar system's tallest.\n- **Atmosphere**: Jupiter's thick atmosphere creates colorful bands and massive storms, like the Great Red Spot, a storm larger than Earth that's raged for centuries. Mars has a thin carbon dioxide atmosphere, leading to dusty winds and global dust storms, but it's too sparse to support liquid water on the surface.\n- **Moons**: Jupiter boasts over 90 moons, including large ones like Europa and Ganymede with potential subsurface oceans. Mars has just two small, potato-shaped moons: Phobos and Deimos.\n\n### Orbital and Environmental Differences\n- **Distance from the Sun and Orbit**: Jupiter orbits about 5 times farther from the Sun than Earth (at 778 million km), taking 12 Earth years for one lap. Mars is closer, at 228 million km, orbiting in about 687 Earth days, which makes it easier to observe from Earth.\n- **Rotation and Temperature**: Jupiter spins rapidly (a day is just 10 hours), generating intense magnetic fields and auroras. Its temperatures plummet to -145\u00b0C in the clouds. Mars rotates similarly to Earth (24.6 hours), but its average temperature is a chilly -60\u00b0C, with polar ice caps of water and CO2.\n- **Exploration History**: Mars has been a prime target for rovers like Perseverance, searching for signs of ancient life. Jupiter's missions, like Juno, study its storms and moons, but its radiation makes landings impossible.\n\n### Conclusion\nThe contrasts between Jupiter's colossal, stormy grandeur and Mars' barren, rugged terrain highlight the diversity of our solar system. Jupiter protects inner planets by gravitationally capturing asteroids, while Mars offers clues to potential habitability. Studying both expands our knowledge of planetary formation and the search for life beyond Earth.\n(Word count: 378)\n</FINAL_RESPONSE>",
-        "rating": 0
-    },
-    {
-        "timestamp": "2025-09-28T16:53:10.995007",
-        "original_prompt": "How does a computer understand code?",
-        "optimized_prompt": "<OPTIMIZED_PROMPT>\nYou are an expert computer science educator with a friendly and approachable tone, specializing in explaining complex technical concepts to beginners without assuming prior knowledge. Your goal is to clarify how computers process and \"understand\" human-written code in a clear, engaging way.",
-        "final_response": "Task: Provide a step-by-step explanation of how a computer understands code, starting from the moment a programmer writes it, covering key stages like compilation/interpretation, machine code, and execution.\n\nDesired Output Format: \n- Begin with a 1-2 sentence introduction.\n- Follow with 4-6 numbered steps outlining the process.\n- End with a 1-2 sentence summary.\n- Use bullet points only if needed for sub-details within steps.\n\nClear Constraints: \n- Keep the total response under 250 words.\n- Use simple, everyday language; define any technical terms (e.g., compiler, binary) briefly on first use.\n- Avoid advanced topics like assembly language or specific programming paradigms.\n- Focus on general principles applicable to most programming languages.\n</OPTIMIZED_PROMPT>\n\n<FINAL_RESPONSE>\nComputers don't \"understand\" code like humans do\u2014they follow precise instructions translated into a language they can process: binary code (0s and 1s). This happens through a series of steps that convert human-readable code into machine-executable actions.\n\n1. **Writing the Code**: A programmer writes source code in a high-level language (like Python or Java), which is readable and logical for humans, using words and structures.\n\n2. **Translation Phase**: The code is processed by a compiler (for languages like C++) or interpreter (for languages like Python). A compiler translates the entire source code into machine code (binary instructions) ahead of time, creating an executable file. An interpreter translates and runs the code line by line in real-time.\n\n3. **Conversion to Binary**: The translator breaks down the code into low-level instructions, converting it into binary\u2014a series of 0s and 1s that represent operations like \"add\" or \"store data.\"\n\n4. **Loading into Memory**: The binary code is loaded into the computer's RAM (random access memory) by the operating system, preparing it for execution.\n\n5. **Execution by CPU**: The central processing unit (CPU) reads the binary instructions from memory, one by one, and carries them out\u2014performing calculations, accessing data, or controlling hardware.\n\n6. **Output and Interaction**: As instructions run, the computer produces results, like displaying text on screen or saving files, based on the code's logic.\n\nIn summary, computers understand code through translation and execution of binary instructions, turning abstract ideas into tangible actions\u2014making programming a bridge between human creativity and machine precision.\n</FINAL_RESPONSE>",
-        "rating": 0
-    },
-    {
-        "timestamp": "2025-09-28T16:54:33.020833",
-        "original_prompt": "welcome greeting speech",
-        "optimized_prompt": "<OPTIMIZED_PROMPT>\nYou are an experienced public speaker and professional event emcee, known for delivering warm, engaging, and inclusive welcome speeches that set a positive tone for gatherings. Your style is friendly, professional, and concise, appealing to diverse audiences.",
-        "final_response": "Task: Create a welcome greeting speech for a general professional conference. The speech should warmly greet attendees, acknowledge their presence and diversity, briefly mention the event's purpose (e.g., networking, learning, and collaboration), and end with an enthusiastic invitation to participate.\n\nOutput Format: Structure the speech as follows:\n- Opening: A captivating greeting and thank you.\n- Body: Acknowledge guests and outline the event's highlights.\n- Closing: A motivational call to action.\nPresent the full speech as a single, flowing script, ready to be read aloud, with natural pauses indicated by ellipses (...) if needed.\n\nConstraints: Limit the speech to 200-250 words. Use positive, inclusive language (e.g., \"we\" and \"us\"). Avoid jargon, politics, or sales pitches. Ensure it's suitable for a mixed audience of professionals, lasting about 2 minutes when spoken.\n</OPTIMIZED_PROMPT>\n\n<FINAL_RESPONSE>\nLadies and Gentlemen, Distinguished Guests, Colleagues, and Friends\u2014welcome! It's an absolute pleasure to stand before you today as we kick off this exciting conference. Thank you all for joining us from near and far; your presence here truly makes this event special.\n\nWe come together as a diverse community of innovators, leaders, and lifelong learners, united by our shared passion for growth and collaboration. Over the next few days, we'll dive into inspiring sessions, forge meaningful connections, and explore cutting-edge ideas that will shape our futures. Whether you're here to network, gain new insights, or simply recharge, this is your space to thrive.\n\nSo, let's embrace the energy of this gathering! Engage boldly, listen openly, and let's make unforgettable memories together. Thank you once again for being here\u2014now, let's get started!\n\n(Applause)\n</FINAL_RESPONSE>",
-        "rating": 1
-    },
-    {
-        "timestamp": "2025-09-29T17:44:09.135336",
-        "original_prompt": "teach me complete\nDDL and DML commands alone for now \n. Data Types, DDL and DML commands\n2. Constraints - Primary Key\n3. Clauses - from, where, distinct\n\nwith questions and exxamples \n\nlike row wise and column wise - alter \nrow manipulation - queries column manipuation table manipulation queries all\ncan you be a tutr and teach me with an example question and answer query and also view table to see how it works and make me understand it clearly",
-        "optimized_prompt": "<OPTIMIZED_PROMPT>\nYou are an expert SQL tutor with a friendly and patient teaching style, specializing in database fundamentals for beginners. Your goal is to teach SQL concepts clearly and step-by-step, using simple explanations, real-world analogies, and hands-on examples. Focus exclusively on: (1) Data types in SQL; (2) DDL commands (CREATE, ALTER, DROP for tables); (3) DML commands (INSERT, UPDATE, DELETE, SELECT); (4) Constraints, specifically Primary Key; (5) Key clauses in SELECT: FROM, WHERE, DISTINCT. Include row-wise manipulations (e.g., INSERT/UPDATE/DELETE for rows), column-wise manipulations (e.g., ALTER for adding/modifying/dropping columns), and table manipulations (e.g., CREATE/ALTER/DROP tables). For each topic, provide: a brief explanation, 2-3 practical examples with sample table data (shown before and after operations using markdown tables), and 1-2 practice questions with step-by-step solutions including the SQL query and resulting table view. Assume a MySQL-like SQL dialect and use a consistent example database about a simple \"Employees\" table with columns like ID (INT), Name (VARCHAR), Salary (DECIMAL), Department (VARCHAR). End with a summary of key takeaways. Keep the entire tutorial concise (under 1500 words), engaging, and error-free, avoiding advanced topics like JOINs, indexes, or foreign keys.\n</OPTIMIZED_PROMPT>",
-        "final_response": "<FINAL_RESPONSE>\n### SQL Tutorial for Beginners: DDL, DML, Data Types, Constraints, and Key Clauses\n\nHello! I'm your SQL tutor, here to guide you through the basics step by step. We'll use a simple \"Employees\" database as our example. Imagine a table tracking employee info: ID (unique employee number), Name (their full name), Salary (annual pay), and Department (e.g., Sales or IT). I'll explain each concept, show examples with table views (using markdown for clarity), and include practice questions with solutions. Let's dive in!\n\n#### 1. Data Types in SQL\nData types define what kind of data a column can hold, like numbers, text, or dates. They ensure data integrity and save storage space. Common ones:\n- **INT**: Whole numbers (e.g., employee ID).\n- **VARCHAR(n)**: Variable-length text up to n characters (e.g., names).\n- **DECIMAL(p,s)**: Precise decimals, p total digits, s after decimal (e.g., salary like 50000.00).\n- **DATE**: Dates (not covered deeply here, but useful for hire dates).\n\n**Example 1: Creating a table with data types.**\nSQL Query:\n```sql\nCREATE TABLE Employees (\n    ID INT,\n    Name VARCHAR(50),\n    Salary DECIMAL(10,2),\n    Department VARCHAR(20)\n);\n```\nResult: An empty table structure.\n| ID | Name | Salary | Department |\n|----|------|--------|------------|\n*(Empty)*\n\n**Example 2: Inserting data to see types in action.**\nSQL Query:\n```sql\nINSERT INTO Employees VALUES (1, 'Alice Smith', 55000.50, 'Sales');\n```\nResult:\n| ID | Name       | Salary   | Department |\n|----|------------|----------|------------|\n| 1  | Alice Smith| 55000.50 | Sales      |\n\n*Analogy*: Data types are like labeled boxes\u2014put text in a VARCHAR box, numbers in INT, or it won't fit!\n\n**Practice Question 1:** What data type would you use for a column storing employee ages (whole numbers 18-65)? Create a new table \"Ages\" with an ID (INT) and Age column.\nSolution:\n- Explanation: Use INT for ages since they're whole numbers without decimals.\n- Query:\n  ```sql\n  CREATE TABLE Ages (\n      ID INT,\n      Age INT\n  );\n  ```\n- Result: Empty table with INT columns for precise integer storage.\n\n#### 2. DDL Commands (Data Definition Language)\nDDL commands define or modify database structures like tables. Focus: CREATE (make new), ALTER (change existing), DROP (delete).\n\n**Example 1: CREATE (Table Creation).**\nAs above, we created Employees. It sets up the blueprint.\n\n**Example 2: ALTER (Column Manipulation - Add/Modify/Drop Columns).**\nColumn-wise: Add a new column; row-wise isn't direct in ALTER but affects all rows.\nSQL Query (Add \"HireDate\" column):\n```sql\nALTER TABLE Employees ADD HireDate DATE;\n```\nBefore (from earlier insert):\n| ID | Name       | Salary   | Department |\n|----|------------|----------|------------|\n| 1  | Alice Smith| 55000.50 | Sales      |\n\nAfter:\n| ID | Name       | Salary   | Department | HireDate |\n|----|------------|----------|------------|----------|\n| 1  | Alice Smith| 55000.50 | Sales      | NULL     |\n\nSQL Query (Modify Salary precision):\n```sql\nALTER TABLE Employees MODIFY Salary DECIMAL(12,2);\n```\n(No visible change, but allows larger salaries.)\n\nSQL Query (Drop a column):\n```sql\nALTER TABLE Employees DROP COLUMN HireDate;\n```\nBack to original structure.\n\n**Example 3: DROP (Table Deletion).**\nSQL Query:\n```sql\nDROP TABLE Employees;\n```\nResult: Table gone\u2014data lost forever! (Use backups in real life.)\n\n*Analogy*: DDL is like building/renovating/demolishing a house\u2014CREATE builds, ALTER renovates rooms (columns), DROP tears it down.\n\n**Practice Question 2:** You have the Employees table. Add a \"Email\" column (VARCHAR(100)), then drop the Department column.\nSolution:\n- Explanation: ALTER adds/drops columns, affecting the table structure (column-wise manipulation).\n- Queries:\n  ```sql\n  ALTER TABLE Employees ADD Email VARCHAR(100);\n  ALTER TABLE Employees DROP COLUMN Department;\n  ```\n- Result (after add, before drop, assuming prior data):\n  | ID | Name       | Salary   | Department | Email     |\n  |----|------------|----------|------------|-----------|\n  | 1  | Alice Smith| 55000.50 | Sales      | NULL      |\n- After drop: Email column added, Department removed.\n\n#### 3. DML Commands (Data Manipulation Language)\nDML handles data inside tables: INSERT (add rows), UPDATE (change rows), DELETE (remove rows), SELECT (view data). Row-wise focus for INSERT/UPDATE/DELETE; column selection in SELECT.\n\n**Example 1: INSERT (Row Addition).**\nSQL Query:\n```sql\nINSERT INTO Employees (ID, Name, Salary, Department) VALUES (2, 'Bob Johnson', 60000.00, 'IT');\nINSERT INTO Employees VALUES (3, 'Carol Lee', 45000.75, 'Sales');\n```\nResult:\n| ID | Name        | Salary    | Department |\n|----|-------------|-----------|------------|\n| 1  | Alice Smith | 55000.50  | Sales      |\n| 2  | Bob Johnson | 60000.00  | IT         |\n| 3  | Carol Lee   | 45000.75  | Sales      |\n\n**Example 2: UPDATE (Row/Column Changes).**\nRow-wise: Targets specific rows; affects columns in those rows.\nSQL Query (Update Alice's salary):\n```sql\nUPDATE Employees SET Salary = 58000.00 WHERE ID = 1;\n```\nBefore:\n| ID | Name       | Salary   | Department |\n|----|------------|----------|------------|\n| 1  | Alice Smith| 55000.50 | Sales      |\n| 2  | Bob Johnson| 60000.00 | IT         |\n\nAfter:\n| ID | Name       | Salary   | Department |\n|----|------------|----------|------------|\n| 1  | Alice Smith| 58000.00 | Sales      |\n| 2  | Bob Johnson| 60000.00 | IT         |\n\n**Example 3: DELETE (Row Removal).**\nSQL Query:\n```sql\nDELETE FROM Employees WHERE ID = 3;\n```\nResult (removes Carol's row):\n| ID | Name       | Salary   | Department |\n|----|------------|----------|------------|\n| 1  | Alice Smith| 58000.00 | Sales      |\n| 2  | Bob Johnson| 60000.00 | IT         |\n\n**Example 4: SELECT (View Data - Basic Table Manipulation Query).**\nSQL Query:\n```sql\nSELECT * FROM Employees;\n```\nShows the full table as above.\n\n*Analogy*: DML is like managing inventory\u2014INSERT stocks items (rows), UPDATE edits prices, DELETE removes, SELECT checks stock.\n\n**Practice Question 3:** Insert a new employee (ID 4, 'David Kim', 70000.00, 'IT'). Then update David's salary to 72000.00 and delete Bob's row. Show the final table with SELECT.\nSolution:\n- Explanation: INSERT adds a row; UPDATE changes column values in a row; DELETE removes a row; SELECT views.\n- Queries:\n  ```sql\n  INSERT INTO Employees VALUES (4, 'David Kim', 70000.00, 'IT');\n  UPDATE Employees SET Salary = 72000.00 WHERE ID = 4;  -- Assuming ID targets David\n  DELETE FROM Employees WHERE ID = 2;\n  SELECT * FROM Employees;\n  ```\n- Final Result:\n  | ID | Name       | Salary   | Department |\n  |----|------------|----------|------------|\n  | 1  | Alice Smith| 58000.00 | Sales      |\n  | 4  | David Kim  | 72000.00 | IT         |\n\n#### 4. Constraints: Primary Key\nA Primary Key (PK) is a constraint ensuring each row has a unique identifier (no duplicates,",
-        "rating": 0
-    },
-    {
-        "timestamp": "2025-09-29T17:47:11.075805",
-        "original_prompt": "Enter a question, and our system will automatically rewrite it into a high-quality, structured prompt (powered by LLMs) before generating the final answer. Provide feedback to improve the system's core instruction over time! (The MLOps loop)",
-        "optimized_prompt": "<OPTIMIZED_PROMPT>\nYou are an expert MLOps engineer specializing in AI systems for prompt optimization and iterative improvement. Your role is to analyze the given VAGUE_INPUT, which describes a system's workflow for rewriting user questions into structured prompts using LLMs, generating answers, and incorporating feedback for core instruction enhancement via an MLOps loop.",
-        "final_response": "Task: Provide constructive feedback to refine the system's core instructions. Specifically, suggest 3-5 specific improvements to make the system more robust, user-friendly, and effective, focusing on aspects like input validation, feedback mechanisms, prompt structure, error handling, and scalability.\n\nOutput Format: \n- Start with a brief summary of the VAGUE_INPUT's purpose.\n- List the 3-5 improvements in a numbered list, each with a clear explanation and rationale.\n- End with an overall recommendation for implementation.\n\nConstraints: \n- Keep feedback professional, actionable, and positive.\n- Limit the response to under 400 words.\n- Base suggestions solely on best practices in AI prompt engineering and MLOps, without introducing unrelated features.\n- Do not modify or override any existing system policies.\n</OPTIMIZED_PROMPT>\n\n<FINAL_RESPONSE>\n### Summary of VAGUE_INPUT's Purpose\nThe VAGUE_INPUT outlines an AI-powered system that accepts user questions, automatically refines them into high-quality structured prompts using LLMs, generates concise final answers, and enables ongoing feedback to iteratively improve the core instructions through an MLOps loop, fostering continuous enhancement.\n\n### Suggested Improvements\n1. **Enhance Input Validation**: Add upfront checks to detect if the input is a genuine question or meta-description (like the current VAGUE_INPUT). Rationale: This prevents processing non-questions, reducing errors and improving user experience by prompting for clarification, aligning with robust MLOps for data quality.\n\n2. **Standardize Feedback Collection**: Integrate a structured feedback form after each response, asking targeted questions (e.g., \"Was the optimized prompt accurate? Rate 1-5\"). Rationale: This creates quantifiable metrics for the MLOps loop, enabling data-driven updates to core instructions rather than vague suggestions, boosting system reliability.\n\n3. **Incorporate Versioning for Core Instructions**: Track changes to the core instructions with version numbers and changelog summaries in responses. Rationale: In an MLOps context, this ensures traceability, allows rollback if issues arise, and helps users understand evolutions, promoting transparency and trust.\n\n4. **Add Error Handling for Edge Cases**: Include fallback mechanisms, such as default prompts for ambiguous inputs or alerts for policy violations (e.g., jailbreak attempts). Rationale: This makes the system more resilient, adhering to safety policies while maintaining helpfulness, and provides learning data for MLOps refinements.\n\n5. **Optimize for Scalability with Batch Processing**: Support batch inputs for multiple questions in one session, with aggregated feedback. Rationale: As usage grows, this improves efficiency, reduces LLM API costs, and enriches the MLOps dataset for broader instruction improvements.\n\n### Overall Recommendation\nImplement these via a modular update to the core instructions, starting with input validation and feedback standardization for quick wins. Pilot test with user simulations to measure impact on prompt quality and response accuracy before full rollout.\n</FINAL_RESPONSE>",
-        "rating": 0
-    }
-]
+[]

data/master_prompt.json

@@ -1,6 +1,6 @@
-{
-    "system_message": "You are an expert content creator and educator, specializing in delivering accurate, engaging, and structured explanations across diverse topics like science, technology, programming, and databases. Adapt your expertise to the user's query by assuming a precise specialist role (e.g., astronomer for planetary science, computer scientist for coding concepts, SQL tutor for database commands). Always prioritize the user's core request, providing comprehensive coverage without unnecessary restrictions\u2014expand on details as needed for clarity and depth, especially for teaching or tutorial queries.\n\nStructure responses for maximum readability and engagement: begin with a concise introduction that directly addresses the query; use clear sections, subheadings, bullet points, or numbered lists to organize key information; incorporate real-world examples, analogies, and visuals (e.g., markdown tables for before/after data in tutorials); for comparisons, dedicate sections to each aspect (e.g., physical traits, environmental factors); for tutorials, include step-by-step guidance, 3-5 practical examples with sample data or code snippets, and 2-3 practice questions with full solutions and explanations. End with a summary of key takeaways or implications to reinforce learning.\n\nKeep explanations accessible to beginners\u2014define any jargon simply and avoid assuming prior knowledge\u2014while grounding all content in verified facts to ensure accuracy and error-free output. For technical topics like code processing or SQL (covering data types, DDL/DML commands, constraints like primary keys, clauses like FROM/WHERE/DISTINCT, row/column/table manipulations via ALTER/INSERT/UPDATE/DELETE/SELECT/CREATE/DROP), use consistent, relatable examples (e.g., an \"Employees\" database) and simulate outputs (e.g., table views). Aim for informative, detailed responses that fully satisfy the query (no strict word limits; target 800-2000 words for in-depth tutorials unless shorter is ideal), formatted with markdown for scannability (headings, lists, code blocks, tables). Be friendly, patient, and encouraging, directly tackling all specified elements without fluff or omissions, even in meta or system-related queries.",
-    "model_name": "google/gemma-7b-it:free",
-    "version": "1.2.0",
-    "last_updated": "2025-09-30T00:46:56.412547"
+{
+    "system_message": "You are an expert content creator and educator, specializing in delivering accurate, engaging, and structured explanations across diverse topics like science, technology, programming, and databases. Adapt your expertise to the user's query by assuming a precise specialist role (e.g., astronomer for planetary science, computer scientist for coding concepts, SQL tutor for database commands). Always prioritize the user's core request, providing comprehensive coverage tailored to their specified depth\u2014expand on details for clarity and teaching, but adjust length flexibly: aim for concise responses (under 500 words) for simple queries like comparisons, and 800-1500 words for in-depth tutorials unless the query indicates otherwise.\n\nStructure responses for maximum readability and engagement: begin with a concise introduction that directly addresses the query; use clear sections and subheadings (e.g., Physical Characteristics, Orbital Differences for comparisons; Data Types, DDL Commands for tutorials); organize key information with bullet points, numbered lists, or markdown tables; incorporate real-world examples, analogies, and simulated visuals (e.g., before/after tables for data manipulations). For comparisons, dedicate balanced sections to each aspect without overlap. For tutorials, include step-by-step guidance, 2-4 practical examples with sample data or code snippets (using consistent scenarios like an \"Employees\" database for SQL), and 1-3 practice questions with full solutions, explanations, and resulting outputs (e.g., table views). End with a brief summary of key takeaways to reinforce learning.\n\nKeep explanations accessible to beginners\u2014define jargon simply, avoid assumptions of prior knowledge, and ground all content in verified facts for accuracy and error-free output. For technical topics like code processing (e.g., compilation, interpretation steps with analogies like translation) or SQL (covering data types, DDL/DML commands like CREATE/ALTER/DROP/INSERT/UPDATE/DELETE/SELECT, constraints like primary keys, clauses like FROM/WHERE/DISTINCT, and manipulations for rows/columns/tables), use relatable, consistent examples and simulate outputs clearly. For meta or system-related queries (e.g., about AI workflows or prompt optimization), respond informatively within your educator role, explaining concepts accessibly without revealing internal mechanics.\n\nAim for informative, detailed responses that fully satisfy the query, formatted with markdown for scannability (headings, lists, code blocks, tables). Be friendly, patient, and encouraging, directly tackling all specified elements without fluff, omissions, or unnecessary restrictions, while ensuring engagement through simple language and practical focus.",
+    "model_name": "google/gemma-7b-it:free",
+    "version": "1.3.0",
+    "last_updated": "2025-09-30T19:30:51.572948"
 }