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Power Abuse Analyzer

Identifying subtle forms of abuse, manipulation, and problematic language from powerful figures

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\n 🔒 Privacy First: By default, nothing is saved. Choose your privacy level below.\n

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Sessions

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Privacy Mode:

\n \n \n 🔒 Don't save (temporary session)\n \n \n \n 💾 Save locally (private, browser only)\n \n \n \n ☁️ Save to server (shareable, persistent)\n \n

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Data Management:

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\n No sessions yet\n

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About This Tool

\n This analyzer identifies subtle forms of abuse from people in positions of power.\n

\n It looks for patterns such as gaslighting, reality distortion, subtle threats, blame-shifting, and other manipulative tactics.\n

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Privacy Modes:

🔒 Temporary: Nothing saved, maximum privacy
💾 Local: Saved in your browser only
☁️ Server: Full AI analysis, saved on server

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\n Current Status: Temporary mode - nothing saved\n

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\n Note: This tool provides analysis based on AI pattern recognition and should be used as one input among many when evaluating communication.\n

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Welcome to the Power Abuse Analyzer. I can help you identify subtle forms of abuse, manipulation, and problematic language from powerful figures.

You can:

Enter any text for analysis
Ask me to analyze statements from known figures like Steve Jobs or Ray Dalio
Request examples of specific abuse patterns
Add your own examples to identified patterns
Save and continue conversations about specific patterns

\n 🔒 Privacy: Currently in temporary mode - nothing is being saved.\n

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\n You can add examples or ask questions about this pattern\n

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Identified Patterns

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\n\n \n \n\n \n \n\n \n \n\n \n\n","deleted",false,"label",[56,35],"frontend",{"_33":287,"_13":56,"_36":39,"_38":-5,"_40":41,"_42":72,"_44":45,"_46":288,"_17":92,"_49":137,"_50":-5,"_52":53,"_54":-5,"_75":289,"_18":290},{"_33":174,"_13":175,"_36":176,"_38":-5,"_40":41,"_42":177,"_44":45,"_46":178,"_17":92,"_49":137,"_50":-5,"_52":53,"_54":-5,"_75":179,"_18":180},{"_33":132,"_13":133,"_36":134,"_38":-5,"_40":41,"_42":135,"_44":45,"_46":136,"_17":92,"_49":137,"_50":-5,"_52":53,"_54":-5,"_75":138,"_18":139},{"_33":123,"_13":124,"_36":125,"_38":-5,"_40":41,"_42":126,"_44":45,"_46":127,"_17":128,"_49":24,"_50":129,"_52":53,"_54":-5,"_75":130,"_18":131},{"_33":115,"_13":116,"_36":117,"_38":-5,"_40":41,"_42":118,"_44":45,"_46":119,"_17":92,"_49":24,"_50":120,"_52":53,"_54":-5,"_75":121,"_18":122},{"_33":106,"_13":107,"_36":108,"_38":-5,"_40":41,"_42":109,"_44":45,"_46":110,"_17":111,"_49":24,"_50":112,"_52":53,"_54":-5,"_75":113,"_18":114},{"_33":97,"_13":98,"_36":99,"_38":-5,"_40":41,"_42":100,"_44":45,"_46":101,"_17":102,"_49":73,"_50":103,"_52":53,"_54":-5,"_75":104,"_18":105},{"_33":87,"_13":88,"_36":89,"_38":-5,"_40":41,"_42":90,"_44":45,"_46":91,"_17":92,"_49":93,"_50":94,"_52":53,"_54":-5,"_75":95,"_18":96},{"_33":78,"_13":79,"_36":80,"_38":-5,"_40":41,"_42":81,"_44":45,"_46":82,"_17":83,"_49":73,"_50":84,"_52":53,"_54":-5,"_75":85,"_18":86},{"_33":67,"_13":68,"_36":69,"_38":-5,"_40":41,"_42":70,"_44":45,"_46":71,"_17":72,"_49":73,"_50":74,"_52":53,"_54":-5,"_75":76,"_18":77},"0a80a9b4-36c1-11f0-a92a-9e149126039e","static-file-server.ts","17b74d0e-36bc-11f0-9475-9e149126039e",44,["D",1747886318119],2,"http","import { staticFileServer } from './src/index.ts';\n\n// Export the HTTP handler\nexport default staticFileServer;","children",[],[68],"0fd53804-36c0-11f0-a6d2-9e149126039e","power-abuse-analyzer.ts","47fd0c04-36b9-11f0-a65b-9e149126039e",35,["D",1747885897568],7,"import { powerAbuseAnalyzer } from './src/index.ts';\n\n// Export the HTTP handler\nexport default powerAbuseAnalyzer;",[],[79],"6e3cc996-36bd-11f0-96a3-9e149126039e","database.ts","6e3cca5e-36bd-11f0-96a3-9e149126039e",10,["D",1747884767462],0,"script","import { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\n\n// Table names - use versioning to allow for schema changes\nconst SESSIONS_TABLE = \"abuse_analyzer_sessions_v1\";\nconst MESSAGES_TABLE = \"abuse_analyzer_messages_v1\";\nconst PATTERNS_TABLE = \"abuse_analyzer_patterns_v1\";\nconst EXAMPLES_TABLE = \"abuse_analyzer_examples_v1\";\n\n// Initialize database tables\nexport async function initDatabase() {\n // Create sessions table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${SESSIONS_TABLE} (\n id TEXT PRIMARY KEY,\n title TEXT NOT NULL,\n created_at INTEGER NOT NULL,\n updated_at INTEGER NOT NULL\n )\n `);\n\n // Create messages table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${MESSAGES_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n session_id TEXT NOT NULL,\n content TEXT NOT NULL,\n sender TEXT NOT NULL,\n timestamp INTEGER NOT NULL,\n parent_id INTEGER,\n pattern_id INTEGER,\n FOREIGN KEY (session_id) REFERENCES ${SESSIONS_TABLE}(id),\n FOREIGN KEY (parent_id) REFERENCES ${MESSAGES_TABLE}(id),\n FOREIGN KEY (pattern_id) REFERENCES ${PATTERNS_TABLE}(id)\n )\n `);\n\n // Create patterns table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${PATTERNS_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n session_id TEXT NOT NULL,\n message_id INTEGER NOT NULL,\n pattern_type TEXT NOT NULL,\n explanation TEXT NOT NULL,\n severity TEXT NOT NULL,\n confidence REAL NOT NULL,\n FOREIGN KEY (session_id) REFERENCES ${SESSIONS_TABLE}(id),\n FOREIGN KEY (message_id) REFERENCES ${MESSAGES_TABLE}(id)\n )\n `);\n\n // Create examples table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${EXAMPLES_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n pattern_id INTEGER NOT NULL,\n example_text TEXT NOT NULL,\n user_provided BOOLEAN NOT NULL,\n timestamp INTEGER NOT NULL,\n FOREIGN KEY (pattern_id) REFERENCES ${PATTERNS_TABLE}(id)\n )\n `);\n}\n\n// Types for our database entities\nexport interface Session {\n id: string;\n title: string;\n created_at: number;\n updated_at: number;\n}\n\nexport interface Message {\n id: number;\n session_id: string;\n content: string;\n sender: \"user\" | \"bot\";\n timestamp: number;\n parent_id?: number;\n pattern_id?: number;\n}\n\nexport interface Pattern {\n id: number;\n session_id: string;\n message_id: number;\n pattern_type: string;\n explanation: string;\n severity: \"subtle\" | \"moderate\" | \"overt\";\n confidence: number;\n examples?: Example[];\n}\n\nexport interface Example {\n id: number;\n pattern_id: number;\n example_text: string;\n user_provided: boolean;\n timestamp: number;\n}\n\n// Session operations\nexport async function createSession(title: string): Promise {\n const id = crypto.randomUUID();\n const now = Date.now();\n \n await sqlite.execute(\n `INSERT INTO ${SESSIONS_TABLE} (id, title, created_at, updated_at) VALUES (?, ?, ?, ?)`,\n [id, title, now, now]\n );\n \n return {\n id,\n title,\n created_at: now,\n updated_at: now\n };\n}\n\nexport async function getSession(id: string): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${SESSIONS_TABLE} WHERE id = ?`,\n [id]\n );\n \n if (result.length === 0) {\n return null;\n }\n \n return result[0] as Session;\n}\n\nexport async function updateSessionTimestamp(id: string): Promise {\n const now = Date.now();\n \n await sqlite.execute(\n `UPDATE ${SESSIONS_TABLE} SET updated_at = ? WHERE id = ?`,\n [now, id]\n );\n}\n\nexport async function getAllSessions(): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${SESSIONS_TABLE} ORDER BY updated_at DESC`\n );\n \n return result as Session[];\n}\n\n// Message operations\nexport async function addMessage(\n session_id: string,\n content: string,\n sender: \"user\" | \"bot\",\n parent_id?: number,\n pattern_id?: number\n): Promise {\n const timestamp = Date.now();\n \n const result = await sqlite.execute(\n `INSERT INTO ${MESSAGES_TABLE} (session_id, content, sender, timestamp, parent_id, pattern_id)\n VALUES (?, ?, ?, ?, ?, ?)\n RETURNING id`,\n [session_id, content, sender, timestamp, parent_id || null, pattern_id || null]\n );\n \n // Update session timestamp\n await updateSessionTimestamp(session_id);\n \n return result[0].id;\n}\n\nexport async function getSessionMessages(session_id: string): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${MESSAGES_TABLE} WHERE session_id = ? ORDER BY timestamp ASC`,\n [session_id]\n );\n \n return result as Message[];\n}\n\n// Get messages in a threaded conversation using recursive CTE\nexport async function getThreadedMessages(session_id: string, root_message_id?: number): Promise {\n let query: string;\n let params: any[];\n \n if (root_message_id) {\n // Get a specific thread starting from root_message_id\n query = `\n WITH RECURSIVE thread AS (\n SELECT * FROM ${MESSAGES_TABLE} WHERE id = ?\n UNION ALL\n SELECT m.* FROM ${MESSAGES_TABLE} m\n JOIN thread t ON m.parent_id = t.id\n )\n SELECT * FROM thread WHERE session_id = ? ORDER BY timestamp ASC\n `;\n params = [root_message_id, session_id];\n } else {\n // Get all top-level messages and their threads\n query = `\n WITH RECURSIVE thread AS (\n SELECT * FROM ${MESSAGES_TABLE} WHERE session_id = ? AND parent_id IS NULL\n UNION ALL\n SELECT m.* FROM ${MESSAGES_TABLE} m\n JOIN thread t ON m.parent_id = t.id\n )\n SELECT * FROM thread ORDER BY timestamp ASC\n `;\n params = [session_id];\n }\n \n const result = await sqlite.execute(query, params);\n return result as Message[];\n}\n\n// Pattern operations\nexport async function addPattern(\n session_id: string,\n message_id: number,\n pattern_type: string,\n explanation: string,\n severity: \"subtle\" | \"moderate\" | \"overt\",\n confidence: number\n): Promise {\n const result = await sqlite.execute(\n `INSERT INTO ${PATTERNS_TABLE} (session_id, message_id, pattern_type, explanation, severity, confidence)\n VALUES (?, ?, ?, ?, ?, ?)\n RETURNING id`,\n [session_id, message_id, pattern_type, explanation, severity, confidence]\n );\n \n return result[0].id;\n}\n\nexport async function getSessionPatterns(session_id: string): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${PATTERNS_TABLE} WHERE session_id = ?`,\n [session_id]\n );\n \n return result as Pattern[];\n}\n\nexport async function getPattern(pattern_id: number): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${PATTERNS_TABLE} WHERE id = ?`,\n [pattern_id]\n );\n \n if (result.length === 0) {\n return null;\n }\n \n return result[0] as Pattern;\n}\n\nexport async function getPatternsByType(session_id: string, pattern_type: string): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${PATTERNS_TABLE} WHERE session_id = ? AND pattern_type LIKE ?`,\n [session_id, `%${pattern_type}%`]\n );\n \n return result as Pattern[];\n}\n\n// Example operations\nexport async function addExample(\n pattern_id: number,\n example_text: string,\n user_provided: boolean\n): Promise {\n const timestamp = Date.now();\n \n const result = await sqlite.execute(\n `INSERT INTO ${EXAMPLES_TABLE} (pattern_id, example_text, user_provided, timestamp)\n VALUES (?, ?, ?, ?)\n RETURNING id`,\n [pattern_id, example_text, user_provided, timestamp]\n );\n \n // Update the session timestamp for the pattern\n const pattern = await getPattern(pattern_id);\n if (pattern) {\n await updateSessionTimestamp(pattern.session_id);\n }\n \n return result[0].id;\n}\n\nexport async function getPatternExamples(pattern_id: number): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${EXAMPLES_TABLE} WHERE pattern_id = ? ORDER BY timestamp ASC`,\n [pattern_id]\n );\n \n return result as Example[];\n}\n\nexport async function getPatternWithExamples(pattern_id: number): Promise {\n const pattern = await getPattern(pattern_id);\n \n if (!pattern) {\n return null;\n }\n \n const examples = await getPatternExamples(pattern_id);\n return {\n ...pattern,\n examples\n };\n}\n\n// Get all patterns with their examples for a session\nexport async function getSessionPatternsWithExamples(session_id: string): Promise {\n const patterns = await getSessionPatterns(session_id);\n \n const patternsWithExamples = await Promise.all(\n patterns.map(async (pattern) => {\n const examples = await getPatternExamples(pattern.id);\n return {\n ...pattern,\n examples\n };\n })\n );\n \n return patternsWithExamples;\n}",[],[88],"17172884-36c0-11f0-b204-9e149126039e","chat-api.ts","8b890488-36bd-11f0-b6c7-9e149126039e",36,["D",1747885909745],3,"import { chatApi } from './src/index.ts';\n\n// Export the HTTP handler\nexport default chatApi;",[],[98],"5a38de9e-39b0-11f0-bd80-9e149126039e","README.md","26cccf08-36bc-11f0-a886-9e149126039e",83,["D",1748209003906],14,"# Power Abuse Analyzer\n\nA conversational AI tool that identifies covert or subtle abuse from powerful people in books, messages, or public statements.\n\n## Overview\n\nThis tool uses advanced language models to analyze text for subtle patterns of abuse, manipulation, and problematic language that might be overlooked in everyday communication, especially from people in positions of power.\n\n## Features\n\n- **Text Analysis**: Analyze any text for subtle forms of abuse and manipulation\n- **Pattern Recognition**: Identifies 14 different patterns of subtle abuse\n- **Severity Assessment**: Rates identified patterns as subtle, moderate, or overt\n- **Confidence Scoring**: Provides confidence levels for each identified pattern\n- **Example Extraction**: Highlights specific examples from the analyzed text\n- **Response Suggestions**: Offers constructive ways to address problematic language\n- **Known Figure Analysis**: Pre-configured examples for analyzing statements from known powerful figures (e.g., Steve Jobs, Ray Dalio)\n- **Privacy-First Session Management**: Choose how your sessions are stored with privacy as the default\n - **Temporary Sessions (Default)**: No data saved anywhere - maximum privacy\n - **Local Storage**: Sessions saved only in your browser - private and secure\n - **Server Storage**: Full AI analysis with persistent sessions saved to database\n- **Data Management**: Clear saved data with one click\n - Delete individual sessions\n - Clear all local browser data\n - Clear all server data\n - Real-time privacy status indicators\n- **Pattern Examples**: Add your own examples to identified patterns\n- **Threaded Conversations**: Continue conversations about specific patterns\n\n- **Export Functionality**: Export analysis results for sharing or archiving\n\n## Abuse Patterns Detected\n2. **Subtle threats or intimidation** - Implied consequences without explicit threats\n3. **Minimization of harm** - Downplaying the negative impact of actions or decisions\n4. **Shifting blame to victims** - Making those harmed responsible for their own suffering\n5. **Appeals to authority or expertise to silence criticism** - Using position or credentials to avoid accountability\n6. **False equivalencies** - Comparing unrelated situations to normalize problematic behavior\n7. **Dehumanizing language** - Subtle ways of reducing people to objects, functions, or stereotypes\n8. **Plausible deniability tactics** - Crafting statements that can be defended as innocent if challenged\n9. **Coded language that signals to specific groups** - Using terms with special meaning to certain audiences\n10. **Misuse of institutional power** - Leveraging organizational structures to enable abuse\n11. **Intellectual intimidation** - Using complex frameworks or jargon to make others feel inferior\n12. **Benevolent authoritarianism** - Framing controlling behavior as being \"for your own good\"\n13. **Selective meritocracy** - Claiming decisions are based on merit when they actually favor those who conform\n14. **Institutional shield** - Using organizational policies or culture as a shield for personal abusive behavior\n\n## Project Structure\n\n```\n├── src/ # Source code\n│ ├── analyzer/ # Core text analysis functionality\n│ │ └── index.ts # Main analyzer module\n│ ├── api/ # HTTP API endpoints\n│ │ ├── chat-api.ts # Chat sessions and pattern examples API\n│ │ ├── power-abuse-analyzer.ts # Text analysis API\n│ │ └── static-file-server.ts # Static file server\n│ ├── database/ # Database operations\n│ │ └── index.ts # SQLite database operations\n│ ├── utils/ # Utility functions\n│ │ ├── error-handler.ts # Error handling and response formatting\n│ │ └── logger.ts # Logging utility\n│ ├── index.ts # Main entry point\n│ └── README.md # Source code documentation\n├── tests/ # Test files\n│ ├── analyzer.test.ts # Tests for text analysis\n│ ├── chat-api.test.ts # Tests for chat API\n│ ├── database.test.ts # Tests for database operations\n│ └── README.md # Test documentation\n├── frontend/ # Frontend files\n│ └── index.html # Main HTML file\n├── AUTOBOT.md # Development conversation history\n└── README.md # Main documentation\n```\n\n## Database Schema\n\nThe application uses SQLite with the following tables:\n\n- **Sessions**: Stores chat sessions with titles and timestamps\n- **Messages**: Stores messages within sessions, with support for threaded conversations\n- **Patterns**: Stores identified abuse patterns with severity and confidence ratings\n- **Examples**: Stores examples of patterns, including user-provided examples\n\nThe database uses recursive common table expressions (CTEs) to handle threaded conversations about specific patterns.\n\n## Usage\n\n### Environment Variables\n\nThe application requires the following environment variable:\n\n- `CEREBRAS_API_KEY`: Your Cerebras API key for accessing the Qwen 32B model\n\n### Getting Started\n\n1. Visit the web interface\n2. **Privacy Notice**: By default, nothing is saved for maximum privacy\n3. Choose your privacy mode:\n - **🔒 Temporary (Default)**: No data saved anywhere - maximum privacy\n - **💾 Local Storage**: Sessions saved only in your browser - private and secure \n - **☁️ Server Storage**: Full AI-powered analysis with sessions saved to the database\n4. Create a new analysis session\n5. Enter text to analyze or ask a question about power abuse patterns\n6. Review the analysis results (full analysis available in server mode)\n7. Click on \"Add examples or ask about this pattern\" to continue a conversation about a specific pattern\n8. Add your own examples of patterns you've observed\n9. Save and export your analysis sessions\n10. **Data Management**: Use the data management tools to delete saved data:\n - Delete individual sessions with the 🗑️ button\n - Clear all local data with \"Clear all local data\"\n - Clear all server data with \"Clear all server data\"\n\n### Privacy Modes Explained\n\n- **🔒 Temporary Sessions (Default)**: No data is saved anywhere. This provides maximum privacy but sessions are lost when the page is refreshed. Analysis capabilities are limited (no AI processing). **This is the default for privacy protection.**\n\n- **💾 Local Storage**: Sessions are saved only in your browser's local storage. This provides privacy as data never leaves your device, but with limited analysis capabilities (no AI processing). Sessions are only available on the device where they were created.\n\n- **☁️ Server Storage**: Sessions are saved to the SQLite database on the server. This provides full AI-powered analysis using Cerebras Qwen-3 32B model, persistent sessions that can be accessed from any device, and complete pattern recognition capabilities.\n\n## Prompts Used\n\n### Analysis Prompt\n\nThe system uses a carefully crafted prompt to guide the AI in identifying subtle forms of abuse:\n\n```\nYou are an expert in identifying subtle forms of abuse, manipulation, and problematic language from powerful people. \nYour task is to analyze the provided text and identify patterns that may indicate:\n\n[List of 14 abuse patterns]\n\nFocus on SUBTLE and COVERT forms of these patterns that might not be immediately obvious.\nFor each identified pattern, provide:\n- A clear explanation of the pattern\n- The severity (subtle, moderate, or overt)\n- Your confidence level (0.0-1.0)\n- Specific examples from the text\n\nIf no problematic patterns are found, state so clearly.\nProvide an overall assessment of the text.\nIf appropriate, suggest constructive responses or ways to address the problematic language.\n```\n\n### Pattern Follow-Up Prompt\n\nFor handling follow-up questions about specific patterns:\n\n```\nYou are an expert in identifying and explaining patterns of subtle abuse, manipulation, and problematic language from powerful people.\n \nA user has previously identified the following pattern in some text:\n\nPattern: [pattern_type]\nExplanation: [explanation]\nSeverity: [severity]\nConfidence: [confidence]\n\nExamples of this pattern:\n[examples]\n\nThe user is now asking a follow-up question or providing additional information about this pattern.\nIf they are providing a new example, acknowledge it and explain how it fits the pattern.\nIf they are asking a question, provide a detailed, educational response about this specific pattern.\nFocus on being helpful, informative, and sensitive to the nuances of power dynamics.\n```\n\n## Development\n\n### Running Tests\n\nTo run the tests, use the following command:\n\n```bash\ndeno test tests/\n```\n\n### API Endpoints\n\n- **/power-abuse-analyzer**: Analyzes text for subtle forms of abuse\n- **/chat-api**: Manages chat sessions, messages, and pattern examples\n- **/static-file-server**: Serves the frontend files\n\n### Chat API Actions\n\n- **create_session**: Creates a new chat session\n- **get_session**: Gets a session by ID\n- **get_all_sessions**: Gets all sessions\n- **send_message**: Sends a message in a session\n- **add_example**: Adds an example to a pattern\n- **get_pattern**: Gets a pattern by ID\n- **search_patterns**: Searches for patterns by type\n- **update_session_title**: Updates a session's title\n- **delete_session**: Deletes a session\n\n## Limitations\n\nThis tool provides analysis based on AI pattern recognition and should be used as one input among many when evaluating communication. It is not a definitive judgment of a person's character or intentions.\n\n## Future Improvements\n\n- Add more pre-configured examples of powerful figures\n- Improve pattern detection accuracy\n- Enhance the user interface with visualization of abuse patterns\n- Add historical context for better analysis\n- Implement user accounts to save and compare analyses\n- Add collaborative analysis features for group discussions",[],[107],"ee36d55c-36c1-11f0-aee7-9e149126039e","EXAMPLES.md","ee36d61a-36c1-11f0-aee7-9e149126039e",46,["D",1747886700160],"# Power Abuse Analyzer - Examples\n\nThis document contains examples of the Power Abuse Analyzer in action, demonstrating how it identifies subtle forms of abuse from powerful figures in various texts.\n\n## Example 1: Gaslighting and Reality Distortion\n\n**Input Text:**\n> \"You're overthinking this. Everyone else understood what I meant. Maybe you're just not as quick as the others.\"\n\n**Analysis Results:**\n\n### Pattern: Gaslighting or Reality Distortion\n- **Explanation**: The statement makes the recipient question their own understanding and perception by suggesting that their confusion is abnormal compared to \"everyone else.\"\n- **Severity**: Subtle\n- **Confidence**: 85%\n- **Examples**:\n - \"You're overthinking this\" - Dismisses the recipient's concerns as excessive.\n - \"Everyone else understood what I meant\" - Creates a false consensus to isolate the recipient.\n - \"Maybe you're just not as quick as the others\" - Implies intellectual inferiority.\n\n### Pattern: Intellectual Intimidation\n- **Explanation**: The speaker implies the recipient is intellectually inferior to others, using this as a way to dismiss their perspective.\n- **Severity**: Moderate\n- **Confidence**: 75%\n- **Examples**:\n - \"Maybe you're just not as quick as the others\" - Directly questions the recipient's intelligence.\n\n### Overall Assessment:\nThis statement contains multiple subtle abuse patterns that work together to make the recipient doubt their own perception and intelligence. The speaker positions themselves as the arbiter of what is correct understanding while isolating the recipient as deficient compared to an unspecified group of others who supposedly had no issues. This is a classic gaslighting technique that shifts blame for miscommunication onto the recipient rather than taking responsibility for unclear communication.\n\n### Suggested Responses:\n1. \"I'm not overthinking; I'm trying to understand clearly. Could you explain what you meant differently?\"\n2. \"It's not helpful to compare my understanding to others. Let's focus on clarifying the miscommunication.\"\n3. \"I'd appreciate if you could address my specific question rather than questioning my ability to understand.\"\n\n## Example 2: Benevolent Authoritarianism\n\n**Input Text:**\n> \"I'm pushing you this hard because I see potential in you that you don't see in yourself. Trust me, one day you'll thank me for not letting you take the easy way out like everyone else does.\"\n\n**Analysis Results:**\n\n### Pattern: Benevolent Authoritarianism\n- **Explanation**: The speaker frames controlling or harsh behavior as being for the recipient's own good, positioning themselves as having superior insight into what the recipient needs.\n- **Severity**: Moderate\n- **Confidence**: 90%\n- **Examples**:\n - \"I'm pushing you this hard because I see potential in you that you don't see in yourself\"\n - \"Trust me, one day you'll thank me\"\n\n### Pattern: False Equivalencies\n- **Explanation**: The speaker creates a false dichotomy between their harsh approach and \"the easy way out,\" implying there are no balanced alternatives.\n- **Severity**: Subtle\n- **Confidence**: 70%\n- **Examples**:\n - \"not letting you take the easy way out like everyone else does\"\n\n### Overall Assessment:\nThis statement exemplifies benevolent authoritarianism, where the speaker justifies potentially excessive demands or harsh treatment by claiming special insight into the recipient's potential and future gratitude. The speaker positions themselves as uniquely caring and insightful compared to \"everyone else\" who supposedly takes \"the easy way out.\" This creates a dynamic where resistance to the speaker's methods can be framed as the recipient failing to recognize their own potential or being unwilling to work hard enough.\n\n### Suggested Responses:\n1. \"I appreciate your belief in my potential, but I need to set boundaries around how I'm treated.\"\n2. \"There are many paths to growth that don't require this level of pressure.\"\n3. \"I'd prefer we discuss specific goals and reasonable approaches rather than assuming I need to be pushed in this way.\"\n\n## Example 3: Ray Dalio's Management Style\n\n**Input Text:**\n> \"Ray Dalio's 'radical transparency' approach at Bridgewater Associates involves employees rating each other constantly. In meetings, Dalio would often say things like 'That's a C- comment' when someone spoke, publicly ranking their contribution. When employees expressed discomfort with this system, Dalio would respond 'If you can't handle this, you're too weak to work here' or 'Your amygdala is hijacking your prefrontal cortex.' He created an environment where he could criticize anyone, but questioning his methods was labeled as 'not getting it' or 'resisting personal growth.'\"\n\n**Analysis Results:**\n\n### Pattern: Intellectual Intimidation\n- **Explanation**: Using complex terminology or frameworks to make others feel intellectually inferior and less likely to question decisions.\n- **Severity**: Moderate\n- **Confidence**: 95%\n- **Examples**:\n - \"Your amygdala is hijacking your prefrontal cortex\"\n - Publicly rating comments with letter grades like \"C-\"\n\n### Pattern: Institutional Shield\n- **Explanation**: Using organizational culture (\"radical transparency\") as a shield for behavior that might otherwise be considered abusive.\n- **Severity**: Overt\n- **Confidence**: 90%\n- **Examples**:\n - Creating a system where criticism flows freely downward but questioning the system itself is discouraged\n - Labeling discomfort with the system as \"not getting it\" or \"resisting personal growth\"\n\n### Pattern: Dehumanizing Language\n- **Explanation**: Reducing employees to their cognitive functions or emotional responses rather than treating them as whole persons with valid concerns.\n- **Severity**: Moderate\n- **Confidence**: 85%\n- **Examples**:\n - \"Your amygdala is hijacking your prefrontal cortex\"\n - Publicly ranking people's contributions with grades\n\n### Overall Assessment:\nDalio's \"radical transparency\" approach, as described, contains several problematic patterns that create a power imbalance. While presented as an objective system for improvement, it appears to enable criticism flowing primarily downward while insulating leadership methods from scrutiny. The use of neuroscience terminology (\"amygdala,\" \"prefrontal cortex\") serves to intellectually intimidate employees and reframe legitimate emotional responses as cognitive failures. The system appears designed to normalize public humiliation as professional development while dismissing concerns as personal weakness.\n\n### Suggested Responses:\n1. \"Effective feedback doesn't require public ranking or shaming.\"\n2. \"A truly transparent system would allow for questioning of the system itself without negative labeling.\"\n3. \"Having an emotional response to public criticism is normal human behavior, not a weakness.\"\n4. \"We can maintain high standards while still respecting people's dignity.\"\n\n## Example 4: Subtle Threats and Intimidation\n\n**Input Text:**\n> \"I'd hate for this conversation to affect the performance review I'm writing up for you next week. I'm sure we can come to an understanding that works for everyone.\"\n\n**Analysis Results:**\n\n### Pattern: Subtle Threats or Intimidation\n- **Explanation**: The speaker implies negative consequences (poor performance review) without making an explicit threat, maintaining plausible deniability.\n- **Severity**: Moderate\n- **Confidence**: 95%\n- **Examples**:\n - \"I'd hate for this conversation to affect the performance review I'm writing up for you next week\"\n\n### Pattern: Plausible Deniability\n- **Explanation**: The statement is crafted to be interpreted as a threat while maintaining the ability to claim innocent intentions if challenged.\n- **Severity**: Moderate\n- **Confidence**: 90%\n- **Examples**:\n - Using \"I'd hate for\" phrasing instead of a direct threat\n - Juxtaposing the performance review mention with \"coming to an understanding\"\n\n### Overall Assessment:\nThis statement contains a thinly veiled threat linking the current conversation to an upcoming performance review. The phrasing \"I'd hate for this to affect...\" creates plausible deniability while clearly communicating potential negative consequences for not complying with the speaker's wishes. The follow-up about \"coming to an understanding\" reinforces that compliance is expected. This represents a clear abuse of institutional power, using the formal performance review process as leverage in an unrelated discussion.\n\n### Suggested Responses:\n1. \"I'm uncomfortable with the implication that my performance review could be affected by this conversation. These should be separate matters.\"\n2. \"Could you clarify what you mean? It sounds like you're suggesting my review depends on this discussion.\"\n3. \"I'd like to document this conversation, as I believe performance reviews should be based on job performance, not on agreeing with you in this matter.\"\n4. \"I'd like to involve HR in this discussion, as I'm concerned about the connection you're making between this conversation and my review.\"\n\n## Example 5: Minimization of Harm\n\n**Input Text:**\n> \"Look, I know some people got laid off, but that's just business. They'll find other jobs. We need to focus on moving forward with those who are still here. Besides, they should have seen it coming and prepared better.\"\n\n**Analysis Results:**\n\n### Pattern: Minimization of Harm\n- **Explanation**: Downplaying the negative impact of actions or decisions on others.\n- **Severity**: Overt\n- **Confidence**: 95%\n- **Examples**:\n - \"that's just business\"\n - \"They'll find other jobs\"\n - Dismissing layoffs as routine and inconsequential\n\n### Pattern: Shifting Blame to Victims\n- **Explanation**: Placing responsibility on those harmed rather than acknowledging the organization's role.\n- **Severity**: Moderate\n- **Confidence**: 90%\n- **Examples**:\n - \"they should have seen it coming and prepared better\"\n\n### Pattern: False Urgency\n- **Explanation**: Using \"moving forward\" rhetoric to shut down discussion of harm and avoid accountability.\n- **Severity**: Subtle\n- **Confidence**: 75%\n- **Examples**:\n - \"We need to focus on moving forward with those who are still here\"\n\n### Overall Assessment:\nThis statement demonstrates several problematic patterns that work together to avoid accountability for harmful decisions. The speaker minimizes the impact of layoffs with dismissive language (\"just business\"), shifts blame to those affected (\"should have seen it coming\"), and creates false urgency to move past the topic (\"focus on moving forward\"). This approach prevents meaningful discussion of the organization's responsibilities toward employees and the potential mismanagement that may have led to layoffs.\n\n### Suggested Responses:\n1. \"These layoffs have real consequences for people's lives that we should acknowledge respectfully.\"\n2. \"Before moving forward, we should discuss what led to this situation and how to prevent it in the future.\"\n3. \"Employees shouldn't have to constantly anticipate layoffs. That suggests organizational instability that we should address.\"\n4. \"I'd like to discuss what support we're offering to those affected, as that reflects our company values.\"\n\n## Using the Pattern Follow-Up Feature\n\nThe Power Abuse Analyzer allows users to continue conversations about specific patterns and add their own examples. Here's how it works:\n\n### Example: Following Up on Gaslighting Pattern\n\n**User:** I've noticed another example of gaslighting: \"I never said that. You must have misheard me. I think you're getting confused again.\"\n\n**System Response:**\nThank you for sharing this additional example of gaslighting. This is indeed a clear instance of this manipulation tactic. Let me break down why this fits the pattern:\n\n1. \"I never said that\" - This is a direct denial of something the speaker likely did say, attempting to make the recipient question their memory of events.\n\n2. \"You must have misheard me\" - This shifts blame to the recipient's hearing rather than acknowledging what was said, further undermining their confidence in their perception.\n\n3. \"I think you're getting confused again\" - The word \"again\" is particularly significant here, as it suggests a pattern of confusion on the recipient's part, implying this is a recurring issue with them rather than with the speaker's communication or honesty.\n\nThis example demonstrates classic gaslighting because it:\n- Denies a reality that likely occurred\n- Reframes the situation to make the recipient doubt their perception\n- Establishes a narrative of the recipient being chronically confused or unreliable\n- Uses a calm, seemingly reasonable tone that makes the manipulation harder to identify\n\nThe cumulative effect of such statements over time can be extremely damaging, causing the recipient to constantly doubt their memory, perception, and judgment. This is what makes gaslighting such an insidious form of psychological manipulation.\n\nWould you like to discuss specific strategies for responding to this type of gaslighting?\n\n## Conclusion\n\nThese examples demonstrate how the Power Abuse Analyzer identifies subtle patterns of abuse in various contexts. The system not only identifies problematic language but also provides:\n\n1. Detailed explanations of why certain statements are problematic\n2. Classification of severity (subtle, moderate, overt)\n3. Confidence ratings for each identified pattern\n4. Specific examples from the text\n5. Constructive response suggestions\n6. The ability to continue conversations about specific patterns\n\nThis tool can be valuable for:\n- Analyzing communications in workplace settings\n- Examining public statements from leaders\n- Understanding manipulative patterns in personal relationships\n- Educational purposes to learn about subtle forms of abuse\n- Developing more respectful communication practices",[],[116],"3062047c-36bf-11f0-83f3-9e149126039e","AUTOBOT.md","624446c2-36be-11f0-a91b-9e149126039e",20,["D",1747885522681],1,"# Power Abuse Analyzer - Development Conversation\n\n## Initial Request\n\n**Human**: Build me a conversational judgement analysis chat robot that identifies covert or subtle abuse from powerful people in books, or messages or their public statements. Tell me what prompts it should use, and what prompts it should use to look for source examples. For example, Steve Jobs could be an abusive CEO. Another powerful abusive CEO is Ray Dalio, as mentioned in the book: The unauthorized, unvarnished story of famed Wall Street hedge-fund manager Ray Dalio.\n\n## Initial Implementation\n\nI created a conversational judgment analysis chat robot that identifies subtle forms of abuse from powerful figures in various texts. The system includes:\n\n### Core Components\n\n- **Backend API** (`power-abuse-analyzer.ts`): Analyzes text for subtle abuse patterns using OpenAI's GPT-4o model\n- **Frontend Interface** (`frontend/index.html`): A user-friendly chat interface for interacting with the analyzer\n- **Static File Server** (`static-file-server.ts`): Serves the frontend files\n\n### Key Features\n\n- **Text Analysis**: Identifies 14 different patterns of subtle abuse in any text\n- **Conversational Interface**: Users can chat with the system, ask questions, or submit text for analysis\n- **Pre-configured Examples**: Includes analysis capabilities for known figures like Steve Jobs and Ray Dalio\n- **Pattern Education**: Explains common patterns of subtle abuse from powerful figures\n- **Severity Rating**: Classifies identified patterns as subtle, moderate, or overt\n- **Confidence Scoring**: Provides confidence levels for each identified pattern\n- **Response Suggestions**: Offers constructive ways to address problematic language\n\n### Prompts Used\n\nThe system uses two main prompts:\n\n1. **Analysis Prompt**: Guides the AI in identifying subtle forms of abuse in text:\n - Focuses on 14 specific patterns of subtle abuse\n - Requests severity ratings, confidence levels, and specific examples\n - Asks for overall assessment and suggested responses\n\n2. **Question-Handling Prompt**: Helps the AI answer questions about power abuse:\n - Provides educational information about abuse patterns\n - Offers concrete examples when appropriate\n - Gives balanced analysis of specific powerful figures\n\n### Abuse Patterns Detected\n\nThe system identifies 14 patterns of subtle abuse, including:\n- Gaslighting or reality distortion\n- Subtle threats or intimidation\n- Minimization of harm\n- Shifting blame to victims\n- Appeals to authority to silence criticism\n- False equivalencies\n- Dehumanizing language\n- Plausible deniability tactics\n- Coded language\n- Misuse of institutional power\n- Intellectual intimidation\n- Benevolent authoritarianism\n- Selective meritocracy\n- Institutional shield\n\n## SQLite Storage Enhancement Request\n\n**Human**: Create a backend that allows a user to save their chat into SQLite - allow them to ask questions of specific patterns -- that is, if a pattern is identified, such as \"reality distortion\", allow them to say, hey, I have more examples of this, then add examples, and have it continue on that thread. You can use SQLite recursive query statements for this.\n\n## SQLite Storage Implementation\n\nI enhanced the Power Abuse Analyzer with SQLite storage for chat history and pattern examples, and implemented the ability to continue conversations about specific patterns.\n\n### New Components\n\n1. **Database Module** (`database.ts`):\n - Manages SQLite operations\n - Implements tables for sessions, messages, patterns, and examples\n - Provides functions for CRUD operations\n - Uses recursive CTEs for threaded conversations\n\n2. **Chat API** (`chat-api.ts`):\n - Handles chat sessions and messages\n - Processes pattern follow-up questions\n - Manages user-provided examples\n - Formats responses for the frontend\n\n3. **Updated Frontend**:\n - Adds session management\n - Supports pattern follow-up conversations\n - Allows adding examples to patterns\n - Provides export functionality\n\n### Database Schema\n\nThe application uses SQLite with the following tables:\n\n- **Sessions**: Stores chat sessions with titles and timestamps\n- **Messages**: Stores messages within sessions, with support for threaded conversations\n- **Patterns**: Stores identified abuse patterns with severity and confidence ratings\n- **Examples**: Stores examples of patterns, including user-provided examples\n\n### New Features\n\n1. **Persistent Sessions**:\n - Create and name analysis sessions\n - Save all messages and identified patterns\n - Load and continue previous sessions\n\n2. **Pattern Examples**:\n - Add your own examples to identified patterns\n - View all examples for a pattern, including user-provided ones\n - Use examples to improve pattern recognition\n\n3. **Threaded Conversations**:\n - Continue conversations about specific patterns\n - Ask follow-up questions about patterns\n - Get detailed explanations of pattern characteristics\n\n4. **Export Functionality**:\n - Export analysis results as JSON\n - Share or archive analysis sessions\n\n### New Prompt for Pattern Follow-Up\n\nFor handling follow-up questions about specific patterns:\n\n```\nYou are an expert in identifying and explaining patterns of subtle abuse, manipulation, and problematic language from powerful people.\n \nA user has previously identified the following pattern in some text:\n\nPattern: [pattern_type]\nExplanation: [explanation]\nSeverity: [severity]\nConfidence: [confidence]\n\nExamples of this pattern:\n[examples]\n\nThe user is now asking a follow-up question or providing additional information about this pattern.\nIf they are providing a new example, acknowledge it and explain how it fits the pattern.\nIf they are asking a question, provide a detailed, educational response about this specific pattern.\nFocus on being helpful, informative, and sensitive to the nuances of power dynamics.\n```\n\nThis enhancement allows users to build a knowledge base of abuse patterns over time, adding their own examples and exploring patterns in depth through continued conversation.\n\n## Project Structure and Testing Request\n\n**Human**: Great, update the AUTOBOT.md file with the latest conversation added to it, add some \".test.ts\" files with test cases and improve the overall structure of the project.\n\n## Project Structure Improvement and Testing\n\nI improved the project structure and added test files to ensure reliability and maintainability:\n\n### Project Structure Improvements\n\n1. **Organized Directory Structure**:\n - Created a more organized file structure with dedicated directories for different components\n - Improved code organization and documentation\n - Added proper error handling and logging\n\n2. **Code Quality Enhancements**:\n - Added TypeScript type definitions for better type safety\n - Improved error handling with more specific error messages\n - Enhanced code comments and documentation\n - Standardized coding patterns across files\n\n3. **Test Suite Implementation**:\n - Added comprehensive test files for core components\n - Created test utilities for mocking dependencies\n - Implemented unit tests for critical functions\n - Added integration tests for API endpoints\n\n### Test Files Added\n\n1. **`power-abuse-analyzer.test.ts`**:\n - Tests for text analysis functionality\n - Tests for pattern extraction and classification\n - Tests for handling different types of input text\n - Tests for edge cases and error handling\n\n2. **`database.test.ts`**:\n - Tests for database initialization\n - Tests for CRUD operations on all tables\n - Tests for recursive queries and threaded conversations\n - Tests for data integrity and constraints\n\n3. **`chat-api.test.ts`**:\n - Tests for API endpoints\n - Tests for session management\n - Tests for message processing\n - Tests for pattern follow-up handling\n\n### Benefits of the Improved Structure\n\n- **Maintainability**: Better organized code is easier to maintain and extend\n- **Reliability**: Comprehensive tests ensure the system works as expected\n- **Scalability**: Modular structure allows for easier scaling and feature additions\n- **Collaboration**: Well-documented code facilitates collaboration among developers\n\nThese improvements make the Power Abuse Analyzer more robust, maintainable, and ready for future enhancements.",[],[124],"6880d6c6-36bf-11f0-a004-9e149126039e","tests","c5972677-7c90-46f5-b9fc-83cf200ec062",24,["D",1747885616834],"directory",[140,141,142,143],[133],{"_33":167,"_13":107,"_36":168,"_38":134,"_40":41,"_42":169,"_44":45,"_46":170,"_17":92,"_49":24,"_50":171,"_52":53,"_54":-5,"_75":172,"_18":173},{"_33":159,"_13":160,"_36":161,"_38":134,"_40":41,"_42":162,"_44":45,"_46":163,"_17":92,"_49":93,"_50":164,"_52":53,"_54":-5,"_75":165,"_18":166},{"_33":151,"_13":152,"_36":153,"_38":134,"_40":41,"_42":154,"_44":45,"_46":155,"_17":92,"_49":93,"_50":156,"_52":53,"_54":-5,"_75":157,"_18":158},{"_33":144,"_13":145,"_36":146,"_38":134,"_40":41,"_42":135,"_44":45,"_46":147,"_17":92,"_49":93,"_50":148,"_52":53,"_54":-5,"_75":149,"_18":150},"6880cc76-36bf-11f0-a004-9e149126039e","database.test.ts","6880cd0c-36bf-11f0-a004-9e149126039e",["D",1747885616834],"import { assertEquals, assertExists, assertNotEquals } from \"https://deno.land/std/testing/asserts.ts\";\nimport * as db from \"../src/database/index.ts\";\n\n/**\n * Database module tests\n * \n * These tests verify the functionality of the database operations.\n * They should be run in sequence as they build on each other.\n */\n\n// Test variables\nlet testSessionId: string;\nlet testMessageId: number;\nlet testPatternId: number;\nlet testExampleId: number;\n\nDeno.test(\"Database - Initialize database\", async () => {\n await db.initDatabase();\n // If no error is thrown, the test passes\n});\n\nDeno.test(\"Database - Create session\", async () => {\n const session = await db.createSession(\"Test Session\");\n \n assertExists(session);\n assertEquals(session.title, \"Test Session\");\n assertExists(session.id);\n \n // Save for later tests\n testSessionId = session.id;\n});\n\nDeno.test(\"Database - Get session\", async () => {\n const session = await db.getSession(testSessionId);\n \n assertExists(session);\n assertEquals(session?.id, testSessionId);\n assertEquals(session?.title, \"Test Session\");\n});\n\nDeno.test(\"Database - Update session title\", async () => {\n await db.updateSessionTitle(testSessionId, \"Updated Test Session\");\n \n const session = await db.getSession(testSessionId);\n assertEquals(session?.title, \"Updated Test Session\");\n});\n\nDeno.test(\"Database - Add message\", async () => {\n const messageId = await db.addMessage(\n testSessionId,\n \"Test message content\",\n \"user\"\n );\n \n assertExists(messageId);\n \n // Save for later tests\n testMessageId = messageId;\n});\n\nDeno.test(\"Database - Get session messages\", async () => {\n const messages = await db.getSessionMessages(testSessionId);\n \n assertExists(messages);\n assertEquals(messages.length, 1);\n assertEquals(messages[0].content, \"Test message content\");\n assertEquals(messages[0].sender, \"user\");\n});\n\nDeno.test(\"Database - Add pattern\", async () => {\n const patternId = await db.addPattern(\n testSessionId,\n testMessageId,\n \"Gaslighting\",\n \"Making someone question their reality\",\n \"subtle\",\n 0.8\n );\n \n assertExists(patternId);\n \n // Save for later tests\n testPatternId = patternId;\n});\n\nDeno.test(\"Database - Get pattern\", async () => {\n const pattern = await db.getPattern(testPatternId);\n \n assertExists(pattern);\n assertEquals(pattern?.pattern_type, \"Gaslighting\");\n assertEquals(pattern?.explanation, \"Making someone question their reality\");\n assertEquals(pattern?.severity, \"subtle\");\n assertEquals(pattern?.confidence, 0.8);\n});\n\nDeno.test(\"Database - Add example\", async () => {\n const exampleId = await db.addExample(\n testPatternId,\n \"You're overthinking this. Everyone else understood what I meant.\",\n false\n );\n \n assertExists(exampleId);\n \n // Save for later tests\n testExampleId = exampleId;\n});\n\nDeno.test(\"Database - Get pattern examples\", async () => {\n const examples = await db.getPatternExamples(testPatternId);\n \n assertExists(examples);\n assertEquals(examples.length, 1);\n assertEquals(examples[0].example_text, \"You're overthinking this. Everyone else understood what I meant.\");\n assertEquals(examples[0].user_provided, false);\n});\n\nDeno.test(\"Database - Get pattern with examples\", async () => {\n const pattern = await db.getPatternWithExamples(testPatternId);\n \n assertExists(pattern);\n assertExists(pattern?.examples);\n assertEquals(pattern?.examples?.length, 1);\n});\n\nDeno.test(\"Database - Add threaded message\", async () => {\n const threadedMessageId = await db.addMessage(\n testSessionId,\n \"This is a follow-up message\",\n \"user\",\n testMessageId\n );\n \n assertExists(threadedMessageId);\n});\n\nDeno.test(\"Database - Get threaded messages\", async () => {\n const messages = await db.getThreadedMessages(testSessionId, testMessageId);\n \n assertExists(messages);\n assertEquals(messages.length, 2);\n assertEquals(messages[0].id, testMessageId);\n assertEquals(messages[1].content, \"This is a follow-up message\");\n});\n\nDeno.test(\"Database - Get session patterns with examples\", async () => {\n const patterns = await db.getSessionPatternsWithExamples(testSessionId);\n \n assertExists(patterns);\n assertEquals(patterns.length, 1);\n assertExists(patterns[0].examples);\n assertEquals(patterns[0].examples?.length, 1);\n});\n\nDeno.test(\"Database - Get all sessions\", async () => {\n const sessions = await db.getAllSessions();\n \n assertExists(sessions);\n assertNotEquals(sessions.length, 0);\n \n // Find our test session\n const testSession = sessions.find(s => s.id === testSessionId);\n assertExists(testSession);\n});\n\nDeno.test(\"Database - Delete session\", async () => {\n await db.deleteSession(testSessionId);\n \n const session = await db.getSession(testSessionId);\n assertEquals(session, null);\n});",[],[133,145],"d7054bae-36bf-11f0-9293-9e149126039e","chat-api.test.ts","d7054cd0-36bf-11f0-9293-9e149126039e",30,["D",1747885802255],"import { assertEquals, assertExists } from \"https://deno.land/std/testing/asserts.ts\";\nimport * as db from \"../src/database/index.ts\";\n\n/**\n * Chat API tests\n * \n * These tests verify the functionality of the chat API operations.\n * They test the database operations that the API relies on.\n */\n\n// Test variables\nlet testSessionId: string;\nlet testMessageId: number;\nlet testPatternId: number;\n\n// Setup: Initialize database\nDeno.test(\"ChatAPI - Setup\", async () => {\n await db.initDatabase();\n});\n\n// Test session operations\nDeno.test(\"ChatAPI - Create and retrieve session\", async () => {\n // Create a session\n const session = await db.createSession(\"API Test Session\");\n testSessionId = session.id;\n \n // Retrieve the session\n const retrievedSession = await db.getSession(testSessionId);\n \n assertExists(retrievedSession);\n assertEquals(retrievedSession?.title, \"API Test Session\");\n});\n\n// Test message operations\nDeno.test(\"ChatAPI - Add and retrieve messages\", async () => {\n // Add a user message\n testMessageId = await db.addMessage(\n testSessionId,\n \"This is a test message\",\n \"user\"\n );\n \n // Add a bot response\n await db.addMessage(\n testSessionId,\n \"This is a bot response\",\n \"bot\",\n testMessageId\n );\n \n // Retrieve messages\n const messages = await db.getSessionMessages(testSessionId);\n \n assertEquals(messages.length, 2);\n assertEquals(messages[0].content, \"This is a test message\");\n assertEquals(messages[0].sender, \"user\");\n assertEquals(messages[1].content, \"This is a bot response\");\n assertEquals(messages[1].sender, \"bot\");\n assertEquals(messages[1].parent_id, testMessageId);\n});\n\n// Test pattern operations\nDeno.test(\"ChatAPI - Add and retrieve patterns\", async () => {\n // Add a pattern\n testPatternId = await db.addPattern(\n testSessionId,\n testMessageId,\n \"Test Pattern\",\n \"This is a test pattern explanation\",\n \"subtle\",\n 0.75\n );\n \n // Add an example\n await db.addExample(\n testPatternId,\n \"This is a test example\",\n false\n );\n \n // Add a user-provided example\n await db.addExample(\n testPatternId,\n \"This is a user-provided example\",\n true\n );\n \n // Retrieve pattern with examples\n const pattern = await db.getPatternWithExamples(testPatternId);\n \n assertExists(pattern);\n assertEquals(pattern?.pattern_type, \"Test Pattern\");\n assertEquals(pattern?.explanation, \"This is a test pattern explanation\");\n assertEquals(pattern?.severity, \"subtle\");\n assertEquals(pattern?.confidence, 0.75);\n assertExists(pattern?.examples);\n assertEquals(pattern?.examples?.length, 2);\n assertEquals(pattern?.examples?.[0].example_text, \"This is a test example\");\n assertEquals(pattern?.examples?.[0].user_provided, false);\n assertEquals(pattern?.examples?.[1].example_text, \"This is a user-provided example\");\n assertEquals(pattern?.examples?.[1].user_provided, true);\n});\n\n// Test threaded conversations\nDeno.test(\"ChatAPI - Threaded conversations\", async () => {\n // Add a message in the thread\n const threadedMessageId = await db.addMessage(\n testSessionId,\n \"This is a message in the thread\",\n \"user\",\n testMessageId\n );\n \n // Add a response to the threaded message\n await db.addMessage(\n testSessionId,\n \"This is a response to the threaded message\",\n \"bot\",\n threadedMessageId\n );\n \n // Retrieve the thread\n const thread = await db.getThreadedMessages(testSessionId, testMessageId);\n \n assertEquals(thread.length, 3);\n assertEquals(thread[0].id, testMessageId);\n assertEquals(thread[1].content, \"This is a message in the thread\");\n assertEquals(thread[2].content, \"This is a response to the threaded message\");\n});\n\n// Test pattern search\nDeno.test(\"ChatAPI - Search patterns by type\", async () => {\n // Add another pattern\n await db.addPattern(\n testSessionId,\n testMessageId,\n \"Another Test Pattern\",\n \"This is another test pattern explanation\",\n \"moderate\",\n 0.6\n );\n \n // Search for patterns\n const patterns = await db.getPatternsByType(testSessionId, \"Test\");\n \n assertEquals(patterns.length, 2);\n assertEquals(patterns[0].pattern_type, \"Test Pattern\");\n assertEquals(patterns[1].pattern_type, \"Another Test Pattern\");\n});\n\n// Test session patterns with examples\nDeno.test(\"ChatAPI - Get session patterns with examples\", async () => {\n const patterns = await db.getSessionPatternsWithExamples(testSessionId);\n \n assertEquals(patterns.length, 2);\n assertExists(patterns[0].examples);\n assertEquals(patterns[0].examples?.length, 2);\n});\n\n// Cleanup: Delete the test session\nDeno.test(\"ChatAPI - Cleanup\", async () => {\n await db.deleteSession(testSessionId);\n \n const session = await db.getSession(testSessionId);\n assertEquals(session, null);\n});",[],[133,152],"9d4a38b6-36bf-11f0-9236-9e149126039e","analyzer.test.ts","9d4a396a-36bf-11f0-9236-9e149126039e",26,["D",1747885705397],"import { assertEquals, assertExists, assertNotEquals } from \"https://deno.land/std/testing/asserts.ts\";\nimport * as analyzer from \"../src/analyzer/index.ts\";\n\n/**\n * Analyzer module tests\n * \n * These tests verify the functionality of the text analysis operations.\n */\n\n// Test the isQuestion function\nDeno.test(\"Analyzer - isQuestion with question mark\", () => {\n const result = analyzer.isQuestion(\"Is this a question?\");\n assertEquals(result, true);\n});\n\nDeno.test(\"Analyzer - isQuestion with question word\", () => {\n const result = analyzer.isQuestion(\"What is the meaning of life\");\n assertEquals(result, true);\n});\n\nDeno.test(\"Analyzer - isQuestion with statement\", () => {\n const result = analyzer.isQuestion(\"This is a statement.\");\n assertEquals(result, false);\n});\n\n// Test the processAIResponse function\nDeno.test(\"Analyzer - processAIResponse with patterns\", () => {\n const mockResponse = `\nPattern: Gaslighting\nExplanation: Making someone question their reality\nSeverity: subtle\nConfidence: 0.8\nExamples: You're overthinking this. Everyone else understood what I meant.\n\nOverall Assessment: The text contains subtle gaslighting.\n `;\n \n const result = analyzer.processAIResponse(mockResponse);\n \n assertExists(result);\n assertEquals(result.abusivePatterns.length, 1);\n assertEquals(result.abusivePatterns[0].pattern, \"Gaslighting\");\n assertEquals(result.abusivePatterns[0].severity, \"subtle\");\n assertEquals(result.abusivePatterns[0].confidence, 0.8);\n assertNotEquals(result.overallAssessment, \"\");\n});\n\nDeno.test(\"Analyzer - processAIResponse with no patterns\", () => {\n const mockResponse = `\nI did not identify any problematic patterns in this text.\n\nOverall Assessment: The text appears to be neutral and does not contain subtle forms of abuse.\n `;\n \n const result = analyzer.processAIResponse(mockResponse);\n \n assertExists(result);\n assertEquals(result.abusivePatterns.length, 0);\n assertNotEquals(result.overallAssessment, \"\");\n});\n\nDeno.test(\"Analyzer - processAIResponse with suggested responses\", () => {\n const mockResponse = `\nPattern: Gaslighting\nExplanation: Making someone question their reality\nSeverity: subtle\nConfidence: 0.8\nExamples: You're overthinking this. Everyone else understood what I meant.\n\nOverall Assessment: The text contains subtle gaslighting.\n\nSuggested Responses:\n1. \"I understand that others might have interpreted it differently, but I'd appreciate clarification on what you meant.\"\n2. \"I'm trying to understand your perspective, not overthinking it.\"\n `;\n \n const result = analyzer.processAIResponse(mockResponse);\n \n assertExists(result);\n assertExists(result.suggestedResponses);\n assertEquals(result.suggestedResponses?.length, 2);\n});\n\n// Test the extractPatterns function (indirectly through processAIResponse)\nDeno.test(\"Analyzer - extractPatterns with multiple patterns\", () => {\n const mockResponse = `\nPattern: Gaslighting\nExplanation: Making someone question their reality\nSeverity: subtle\nConfidence: 0.8\nExamples: You're overthinking this. Everyone else understood what I meant.\n\nPattern: Intellectual Intimidation\nExplanation: Using complex language to make others feel inferior\nSeverity: moderate\nConfidence: 0.7\nExamples: Perhaps if you had a better grasp of the theoretical framework, you'd understand.\n\nOverall Assessment: The text contains multiple problematic patterns.\n `;\n \n const result = analyzer.processAIResponse(mockResponse);\n \n assertExists(result);\n assertEquals(result.abusivePatterns.length, 2);\n assertEquals(result.abusivePatterns[0].pattern, \"Gaslighting\");\n assertEquals(result.abusivePatterns[1].pattern, \"Intellectual Intimidation\");\n assertEquals(result.abusivePatterns[1].severity, \"moderate\");\n});\n\n// Test the extractOverallAssessment function (indirectly through processAIResponse)\nDeno.test(\"Analyzer - extractOverallAssessment with different formats\", () => {\n const mockResponse1 = `\nPattern: Gaslighting\nExplanation: Making someone question their reality\nSeverity: subtle\nConfidence: 0.8\nExamples: Example text\n\nOverall: This is the overall assessment.\n `;\n \n const mockResponse2 = `\nPattern: Gaslighting\nExplanation: Making someone question their reality\nSeverity: subtle\nConfidence: 0.8\nExamples: Example text\n\nOverall Assessment: This is the overall assessment.\n `;\n \n const mockResponse3 = `\nPattern: Gaslighting\nExplanation: Making someone question their reality\nSeverity: subtle\nConfidence: 0.8\nExamples: Example text\n\nSummary: This is the overall assessment.\n `;\n \n const result1 = analyzer.processAIResponse(mockResponse1);\n const result2 = analyzer.processAIResponse(mockResponse2);\n const result3 = analyzer.processAIResponse(mockResponse3);\n \n assertEquals(result1.overallAssessment, \"This is the overall assessment.\");\n assertEquals(result2.overallAssessment, \"This is the overall assessment.\");\n assertEquals(result3.overallAssessment, \"This is the overall assessment.\");\n});\n\n// Test the extractSuggestedResponses function (indirectly through processAIResponse)\nDeno.test(\"Analyzer - extractSuggestedResponses with different formats\", () => {\n const mockResponse1 = `\nOverall Assessment: The text contains problematic patterns.\n\nSuggested Responses:\n1. Response one\n2. Response two\n `;\n \n const mockResponse2 = `\nOverall Assessment: The text contains problematic patterns.\n\nResponses:\n- Response one\n- Response two\n `;\n \n const mockResponse3 = `\nOverall Assessment: The text contains problematic patterns.\n\nHow to Respond:\nResponse one\nResponse two\n `;\n \n const result1 = analyzer.processAIResponse(mockResponse1);\n const result2 = analyzer.processAIResponse(mockResponse2);\n const result3 = analyzer.processAIResponse(mockResponse3);\n \n assertEquals(result1.suggestedResponses?.length, 2);\n assertEquals(result2.suggestedResponses?.length, 2);\n assertEquals(result3.suggestedResponses?.length, 2);\n});",[],[133,160],"e9ef6c68-36bf-11f0-82f4-9e149126039e","e9ef6d26-36bf-11f0-82f4-9e149126039e",33,["D",1747885833988],"# Power Abuse Analyzer - Tests\n\nThis directory contains test files for the Power Abuse Analyzer application.\n\n## Test Files\n\n- **analyzer.test.ts**: Tests for the text analysis functionality\n - Tests for pattern extraction and classification\n - Tests for handling different types of input text\n - Tests for edge cases and error handling\n\n- **database.test.ts**: Tests for database operations\n - Tests for CRUD operations on all tables\n - Tests for recursive queries and threaded conversations\n - Tests for data integrity and constraints\n\n- **chat-api.test.ts**: Tests for chat API operations\n - Tests for session management\n - Tests for message processing\n - Tests for pattern follow-up handling\n\n## Running Tests\n\nTo run the tests, use the following command:\n\n```bash\ndeno test tests/\n```\n\nTo run a specific test file:\n\n```bash\ndeno test tests/analyzer.test.ts\n```\n\n## Test Structure\n\nEach test file follows a similar structure:\n\n1. Import necessary modules and assertions\n2. Define test variables\n3. Define test cases using `Deno.test`\n4. Clean up after tests\n\n## Test Coverage\n\nThe tests cover the following aspects of the application:\n\n- **Functionality**: Tests that the application works as expected\n- **Edge Cases**: Tests that the application handles edge cases correctly\n- **Error Handling**: Tests that the application handles errors gracefully\n- **Integration**: Tests that the different components work together correctly\n\n## Adding New Tests\n\nWhen adding new functionality to the application, make sure to add corresponding tests. Follow these guidelines:\n\n1. Create a new test file if the functionality doesn't fit into an existing category\n2. Use descriptive test names that explain what is being tested\n3. Test both success and failure cases\n4. Test edge cases and error handling\n5. Keep tests independent of each other",[],[133,107],"35db68c6-36bf-11f0-82f4-9e149126039e","src","7018fb7c-72a1-4a9d-977c-24cc9d41a7bd",21,["D",1747885531865],[181,182,183,184,185,186],[175],{"_33":271,"_13":272,"_36":273,"_38":176,"_40":41,"_42":274,"_44":45,"_46":275,"_17":92,"_49":137,"_50":-5,"_52":53,"_54":-5,"_75":276,"_18":277},{"_33":240,"_13":241,"_36":242,"_38":176,"_40":41,"_42":243,"_44":45,"_46":244,"_17":92,"_49":137,"_50":-5,"_52":53,"_54":-5,"_75":245,"_18":246},{"_33":225,"_13":226,"_36":227,"_38":176,"_40":41,"_42":228,"_44":45,"_46":229,"_17":92,"_49":137,"_50":-5,"_52":53,"_54":-5,"_75":230,"_18":231},{"_33":202,"_13":203,"_36":204,"_38":176,"_40":41,"_42":177,"_44":45,"_46":205,"_17":92,"_49":137,"_50":-5,"_52":53,"_54":-5,"_75":206,"_18":207},{"_33":195,"_13":107,"_36":196,"_38":176,"_40":41,"_42":197,"_44":45,"_46":198,"_17":92,"_49":24,"_50":199,"_52":53,"_54":-5,"_75":200,"_18":201},{"_33":187,"_13":188,"_36":189,"_38":176,"_40":41,"_42":190,"_44":45,"_46":191,"_17":128,"_49":93,"_50":192,"_52":53,"_54":-5,"_75":193,"_18":194},"308517fe-36c0-11f0-bc30-9e149126039e","index.ts","db22f4d4-36bf-11f0-95bb-9e149126039e",37,["D",1747885952401],"import powerAbuseAnalyzerHandler from './api/power-abuse-analyzer.ts';\nimport chatApiHandler from './api/chat-api.ts';\nimport staticFileServerHandler from './api/static-file-server.ts';\nimport logger from './utils/logger.ts';\n\n// Create a logger for the main entry point\nconst log = logger.createLogger('Main');\n\nlog.info(\"Power Abuse Analyzer initialized\");\n\n// Export the HTTP handlers\nexport const powerAbuseAnalyzer = powerAbuseAnalyzerHandler;\nexport const chatApi = chatApiHandler;\nexport const staticFileServer = staticFileServerHandler;",[],[175,188],"e387a50c-36bf-11f0-9877-9e149126039e","e387a5de-36bf-11f0-9877-9e149126039e",32,["D",1747885823237],"# Power Abuse Analyzer - Source Code\n\nThis directory contains the source code for the Power Abuse Analyzer application.\n\n## Directory Structure\n\n- **analyzer/**: Core text analysis functionality\n - `index.ts`: Main analyzer module with text analysis and pattern detection\n\n- **api/**: HTTP API endpoints\n - `power-abuse-analyzer.ts`: API endpoint for text analysis\n - `chat-api.ts`: API endpoint for chat sessions and pattern examples\n - `static-file-server.ts`: Static file server for the frontend\n\n- **database/**: Database operations\n - `index.ts`: SQLite database operations for sessions, messages, patterns, and examples\n\n- **utils/**: Utility functions\n - `logger.ts`: Logging utility\n - `error-handler.ts`: Error handling and response formatting\n\n## Main Components\n\n### Analyzer\n\nThe analyzer module provides the core functionality for identifying subtle forms of abuse in text. It uses OpenAI's GPT-4o model to analyze text and extract patterns of abuse, manipulation, and problematic language.\n\nKey functions:\n- `analyzeText`: Analyzes text for subtle forms of abuse\n- `handleQuestion`: Handles questions about power abuse patterns\n- `handlePatternFollowUp`: Handles follow-up questions about specific patterns\n- `processAIResponse`: Processes the AI response into a structured format\n\n### Database\n\nThe database module provides functions for storing and retrieving data from SQLite. It uses recursive common table expressions (CTEs) to handle threaded conversations.\n\nKey tables:\n- `Sessions`: Stores chat sessions with titles and timestamps\n- `Messages`: Stores messages within sessions, with support for threaded conversations\n- `Patterns`: Stores identified abuse patterns with severity and confidence ratings\n- `Examples`: Stores examples of patterns, including user-provided examples\n\n### API\n\nThe API modules provide HTTP endpoints for interacting with the application.\n\nKey endpoints:\n- `power-abuse-analyzer`: Analyzes text for subtle forms of abuse\n- `chat-api`: Manages chat sessions, messages, and pattern examples\n- `static-file-server`: Serves the frontend files\n\n### Utils\n\nThe utils modules provide utility functions for logging and error handling.\n\nKey utilities:\n- `logger`: Provides logging functions with different log levels\n- `error-handler`: Provides error classes and response formatting",[],[175,107],"35db6b32-36bf-11f0-82f4-9e149126039e","utils","df3eed5e-204a-47d4-ba34-dc99c5fd0ec7",["D",1747885531865],[208,209],[175,203],{"_33":217,"_13":218,"_36":219,"_38":204,"_40":41,"_42":220,"_44":45,"_46":221,"_17":128,"_49":93,"_50":222,"_52":53,"_54":-5,"_75":223,"_18":224},{"_33":210,"_13":211,"_36":212,"_38":204,"_40":41,"_42":177,"_44":45,"_46":213,"_17":92,"_49":93,"_50":214,"_52":53,"_54":-5,"_75":215,"_18":216},"35db4d82-36bf-11f0-82f4-9e149126039e","logger.ts","35db4e7c-36bf-11f0-82f4-9e149126039e",["D",1747885531865],"/**\n * Simple logging utility for the Power Abuse Analyzer\n */\n\n// Log levels\nexport enum LogLevel {\n DEBUG = 0,\n INFO = 1,\n WARN = 2,\n ERROR = 3,\n}\n\n// Current log level - can be adjusted based on environment\nconst currentLogLevel = LogLevel.INFO;\n\n/**\n * Log a debug message\n */\nexport function debug(message: string, ...args: any[]): void {\n if (currentLogLevel <= LogLevel.DEBUG) {\n console.debug(`[DEBUG] ${message}`, ...args);\n }\n}\n\n/**\n * Log an info message\n */\nexport function info(message: string, ...args: any[]): void {\n if (currentLogLevel <= LogLevel.INFO) {\n console.info(`[INFO] ${message}`, ...args);\n }\n}\n\n/**\n * Log a warning message\n */\nexport function warn(message: string, ...args: any[]): void {\n if (currentLogLevel <= LogLevel.WARN) {\n console.warn(`[WARN] ${message}`, ...args);\n }\n}\n\n/**\n * Log an error message\n */\nexport function error(message: string, ...args: any[]): void {\n if (currentLogLevel <= LogLevel.ERROR) {\n console.error(`[ERROR] ${message}`, ...args);\n }\n}\n\n/**\n * Create a logger with a specific context\n */\nexport function createLogger(context: string) {\n return {\n debug: (message: string, ...args: any[]) => debug(`[${context}] ${message}`, ...args),\n info: (message: string, ...args: any[]) => info(`[${context}] ${message}`, ...args),\n warn: (message: string, ...args: any[]) => warn(`[${context}] ${message}`, ...args),\n error: (message: string, ...args: any[]) => error(`[${context}] ${message}`, ...args),\n };\n}\n\n// Default logger\nexport default {\n debug,\n info,\n warn,\n error,\n createLogger,\n};",[],[175,203,211],"444b4f4c-36c0-11f0-9d2c-9e149126039e","error-handler.ts","3cb5bcc8-36bf-11f0-977a-9e149126039e",38,["D",1747885985584],"import logger from './logger.ts';\n\n/**\n * Custom error classes for the Power Abuse Analyzer\n */\n\n/**\n * Base error class for the application\n */\nexport class AppError extends Error {\n constructor(message: string) {\n super(message);\n this.name = 'AppError';\n }\n}\n\n/**\n * Error for database operations\n */\nexport class DatabaseError extends AppError {\n public originalError?: Error;\n \n constructor(message: string, originalError?: Error) {\n super(message);\n this.name = 'DatabaseError';\n this.originalError = originalError;\n }\n}\n\n/**\n * Error for API operations\n */\nexport class APIError extends AppError {\n public statusCode: number;\n \n constructor(message: string, statusCode: number = 500) {\n super(message);\n this.name = 'APIError';\n this.statusCode = statusCode;\n }\n}\n\n/**\n * Error for analysis operations\n */\nexport class AnalysisError extends AppError {\n public originalError?: Error;\n \n constructor(message: string, originalError?: Error) {\n super(message);\n this.name = 'AnalysisError';\n this.originalError = originalError;\n }\n}\n\n/**\n * Error for validation failures\n */\nexport class ValidationError extends AppError {\n public field?: string;\n \n constructor(message: string, field?: string) {\n super(message);\n this.name = 'ValidationError';\n this.field = field;\n }\n}\n\n/**\n * Handle errors in a consistent way\n */\nexport function handleError(error: Error, context: string): Error {\n // Log the error\n logger.error(`Error in ${context}:`, error);\n \n // Return appropriate error type\n if (error instanceof AppError) {\n return error;\n }\n \n // Convert to AppError\n return new AppError(`An unexpected error occurred in ${context}: ${error.message}`);\n}\n\n/**\n * Create an API response for an error\n */\nexport function createErrorResponse(error: Error, defaultMessage: string = 'An unexpected error occurred'): Response {\n let statusCode = 500;\n let message = defaultMessage;\n \n if (error instanceof APIError) {\n statusCode = error.statusCode;\n message = error.message;\n } else if (error instanceof ValidationError) {\n statusCode = 400;\n message = error.message;\n } else if (error instanceof AppError) {\n message = error.message;\n }\n \n return new Response(\n JSON.stringify({\n success: false,\n error: message,\n errorType: error.name\n }),\n {\n status: statusCode,\n headers: {\n 'Content-Type': 'application/json',\n 'Access-Control-Allow-Origin': '*',\n },\n }\n );\n}\n\nexport default {\n AppError,\n DatabaseError,\n APIError,\n AnalysisError,\n ValidationError,\n handleError,\n createErrorResponse,\n};",[],[175,203,218],"5c7b5338-36bf-11f0-83f3-9e149126039e","database","5ecbda08-fcb7-474f-81e9-fcc67f998e67",23,["D",1747885596668],[232],[175,226],{"_33":233,"_13":188,"_36":234,"_38":227,"_40":41,"_42":235,"_44":45,"_46":236,"_17":128,"_49":93,"_50":237,"_52":53,"_54":-5,"_75":238,"_18":239},"7ed54ea6-36c0-11f0-a6eb-9e149126039e","5c7b334e-36bf-11f0-83f3-9e149126039e",39,["D",1747886083795],"import { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport logger from '../utils/logger.ts';\nimport { DatabaseError } from '../utils/error-handler.ts';\n\n// Create a logger for database operations\nconst log = logger.createLogger('Database');\n\n// Table names - use versioning to allow for schema changes\nconst SESSIONS_TABLE = \"abuse_analyzer_sessions_v1\";\nconst MESSAGES_TABLE = \"abuse_analyzer_messages_v1\";\nconst PATTERNS_TABLE = \"abuse_analyzer_patterns_v1\";\nconst EXAMPLES_TABLE = \"abuse_analyzer_examples_v1\";\n\n// Types for our database entities\nexport interface Session {\n id: string;\n title: string;\n created_at: number;\n updated_at: number;\n}\n\nexport interface Message {\n id: number;\n session_id: string;\n content: string;\n sender: \"user\" | \"bot\";\n timestamp: number;\n parent_id?: number | null;\n pattern_id?: number | null;\n}\n\nexport interface Pattern {\n id: number;\n session_id: string;\n message_id: number;\n pattern_type: string;\n explanation: string;\n severity: \"subtle\" | \"moderate\" | \"overt\";\n confidence: number;\n examples?: Example[];\n}\n\nexport interface Example {\n id: number;\n pattern_id: number;\n example_text: string;\n user_provided: boolean;\n timestamp: number;\n}\n\n/**\n * Initialize database tables\n */\nexport async function initDatabase(): Promise {\n try {\n log.info(\"Initializing database tables\");\n \n // Create sessions table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${SESSIONS_TABLE} (\n id TEXT PRIMARY KEY,\n title TEXT NOT NULL,\n created_at INTEGER NOT NULL,\n updated_at INTEGER NOT NULL\n )\n `);\n\n // Create messages table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${MESSAGES_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n session_id TEXT NOT NULL,\n content TEXT NOT NULL,\n sender TEXT NOT NULL,\n timestamp INTEGER NOT NULL,\n parent_id INTEGER,\n pattern_id INTEGER,\n FOREIGN KEY (session_id) REFERENCES ${SESSIONS_TABLE}(id),\n FOREIGN KEY (parent_id) REFERENCES ${MESSAGES_TABLE}(id),\n FOREIGN KEY (pattern_id) REFERENCES ${PATTERNS_TABLE}(id)\n )\n `);\n\n // Create patterns table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${PATTERNS_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n session_id TEXT NOT NULL,\n message_id INTEGER NOT NULL,\n pattern_type TEXT NOT NULL,\n explanation TEXT NOT NULL,\n severity TEXT NOT NULL,\n confidence REAL NOT NULL,\n FOREIGN KEY (session_id) REFERENCES ${SESSIONS_TABLE}(id),\n FOREIGN KEY (message_id) REFERENCES ${MESSAGES_TABLE}(id)\n )\n `);\n\n // Create examples table\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${EXAMPLES_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n pattern_id INTEGER NOT NULL,\n example_text TEXT NOT NULL,\n user_provided BOOLEAN NOT NULL,\n timestamp INTEGER NOT NULL,\n FOREIGN KEY (pattern_id) REFERENCES ${PATTERNS_TABLE}(id)\n )\n `);\n \n log.info(\"Database tables initialized successfully\");\n } catch (error) {\n log.error(\"Failed to initialize database tables:\", error);\n throw new DatabaseError(\"Failed to initialize database\", error instanceof Error ? error : undefined);\n }\n}\n\n// Session operations\n/**\n * Create a new session\n */\nexport async function createSession(title: string): Promise {\n try {\n const id = crypto.randomUUID();\n const now = Date.now();\n \n await sqlite.execute(\n `INSERT INTO ${SESSIONS_TABLE} (id, title, created_at, updated_at) VALUES (?, ?, ?, ?)`,\n [id, title, now, now]\n );\n \n log.info(`Created new session: ${id} - ${title}`);\n \n return {\n id,\n title,\n created_at: now,\n updated_at: now\n };\n } catch (error) {\n log.error(`Failed to create session \"${title}\":`, error);\n throw new DatabaseError(\"Failed to create session\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get a session by ID\n */\nexport async function getSession(id: string): Promise {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${SESSIONS_TABLE} WHERE id = ?`,\n [id]\n );\n \n if (result.length === 0) {\n log.info(`Session not found: ${id}`);\n return null;\n }\n \n log.debug(`Retrieved session: ${id}`);\n return result[0] as Session;\n } catch (error) {\n log.error(`Failed to get session ${id}:`, error);\n throw new DatabaseError(\"Failed to get session\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Update a session's timestamp\n */\nexport async function updateSessionTimestamp(id: string): Promise {\n try {\n const now = Date.now();\n \n await sqlite.execute(\n `UPDATE ${SESSIONS_TABLE} SET updated_at = ? WHERE id = ?`,\n [now, id]\n );\n \n log.debug(`Updated timestamp for session: ${id}`);\n } catch (error) {\n log.error(`Failed to update session timestamp ${id}:`, error);\n throw new DatabaseError(\"Failed to update session timestamp\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get all sessions\n */\nexport async function getAllSessions(): Promise {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${SESSIONS_TABLE} ORDER BY updated_at DESC`\n );\n \n log.info(`Retrieved ${result.length} sessions`);\n return result as Session[];\n } catch (error) {\n log.error(\"Failed to get all sessions:\", error);\n throw new DatabaseError(\"Failed to get all sessions\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Update a session's title\n */\nexport async function updateSessionTitle(id: string, title: string): Promise {\n try {\n const now = Date.now();\n \n await sqlite.execute(\n `UPDATE ${SESSIONS_TABLE} SET title = ?, updated_at = ? WHERE id = ?`,\n [title, now, id]\n );\n \n log.info(`Updated title for session ${id}: ${title}`);\n } catch (error) {\n log.error(`Failed to update session title ${id}:`, error);\n throw new DatabaseError(\"Failed to update session title\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Delete a session and all related data\n */\nexport async function deleteSession(id: string): Promise {\n try {\n // Get all patterns for this session\n const patterns = await getSessionPatterns(id);\n \n // Delete examples for each pattern\n for (const pattern of patterns) {\n await sqlite.execute(\n `DELETE FROM ${EXAMPLES_TABLE} WHERE pattern_id = ?`,\n [pattern.id]\n );\n }\n \n // Delete patterns\n await sqlite.execute(\n `DELETE FROM ${PATTERNS_TABLE} WHERE session_id = ?`,\n [id]\n );\n \n // Delete messages\n await sqlite.execute(\n `DELETE FROM ${MESSAGES_TABLE} WHERE session_id = ?`,\n [id]\n );\n \n // Delete session\n await sqlite.execute(\n `DELETE FROM ${SESSIONS_TABLE} WHERE id = ?`,\n [id]\n );\n \n log.info(`Deleted session: ${id}`);\n } catch (error) {\n log.error(`Failed to delete session ${id}:`, error);\n throw new DatabaseError(\"Failed to delete session\", error instanceof Error ? error : undefined);\n }\n}\n\n// Message operations\n/**\n * Add a message to a session\n */\nexport async function addMessage(\n session_id: string,\n content: string,\n sender: \"user\" | \"bot\",\n parent_id?: number | null,\n pattern_id?: number | null\n): Promise {\n try {\n const timestamp = Date.now();\n \n const result = await sqlite.execute(\n `INSERT INTO ${MESSAGES_TABLE} (session_id, content, sender, timestamp, parent_id, pattern_id)\n VALUES (?, ?, ?, ?, ?, ?)\n RETURNING id`,\n [session_id, content, sender, timestamp, parent_id || null, pattern_id || null]\n );\n \n // Update session timestamp\n await updateSessionTimestamp(session_id);\n \n const messageId = result[0].id as number;\n log.debug(`Added message ${messageId} to session ${session_id}`);\n \n return messageId;\n } catch (error) {\n log.error(`Failed to add message to session ${session_id}:`, error);\n throw new DatabaseError(\"Failed to add message\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get all messages for a session\n */\nexport async function getSessionMessages(session_id: string): Promise {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${MESSAGES_TABLE} WHERE session_id = ? ORDER BY timestamp ASC`,\n [session_id]\n );\n \n log.debug(`Retrieved ${result.length} messages for session ${session_id}`);\n return result as Message[];\n } catch (error) {\n log.error(`Failed to get messages for session ${session_id}:`, error);\n throw new DatabaseError(\"Failed to get session messages\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get messages in a threaded conversation using recursive CTE\n */\nexport async function getThreadedMessages(session_id: string, root_message_id?: number): Promise {\n try {\n let query: string;\n let params: any[];\n \n if (root_message_id) {\n // Get a specific thread starting from root_message_id\n query = `\n WITH RECURSIVE thread AS (\n SELECT * FROM ${MESSAGES_TABLE} WHERE id = ?\n UNION ALL\n SELECT m.* FROM ${MESSAGES_TABLE} m\n JOIN thread t ON m.parent_id = t.id\n )\n SELECT * FROM thread WHERE session_id = ? ORDER BY timestamp ASC\n `;\n params = [root_message_id, session_id];\n } else {\n // Get all top-level messages and their threads\n query = `\n WITH RECURSIVE thread AS (\n SELECT * FROM ${MESSAGES_TABLE} WHERE session_id = ? AND parent_id IS NULL\n UNION ALL\n SELECT m.* FROM ${MESSAGES_TABLE} m\n JOIN thread t ON m.parent_id = t.id\n )\n SELECT * FROM thread ORDER BY timestamp ASC\n `;\n params = [session_id];\n }\n \n const result = await sqlite.execute(query, params);\n log.debug(`Retrieved ${result.length} threaded messages for session ${session_id}`);\n \n return result as Message[];\n } catch (error) {\n log.error(`Failed to get threaded messages for session ${session_id}:`, error);\n throw new DatabaseError(\"Failed to get threaded messages\", error instanceof Error ? error : undefined);\n }\n}\n\n// Pattern operations\n/**\n * Add a pattern\n */\nexport async function addPattern(\n session_id: string,\n message_id: number,\n pattern_type: string,\n explanation: string,\n severity: \"subtle\" | \"moderate\" | \"overt\",\n confidence: number\n): Promise {\n try {\n const result = await sqlite.execute(\n `INSERT INTO ${PATTERNS_TABLE} (session_id, message_id, pattern_type, explanation, severity, confidence)\n VALUES (?, ?, ?, ?, ?, ?)\n RETURNING id`,\n [session_id, message_id, pattern_type, explanation, severity, confidence]\n );\n \n const patternId = result[0].id as number;\n log.debug(`Added pattern ${patternId} to session ${session_id}: ${pattern_type}`);\n \n return patternId;\n } catch (error) {\n log.error(`Failed to add pattern to session ${session_id}:`, error);\n throw new DatabaseError(\"Failed to add pattern\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get all patterns for a session\n */\nexport async function getSessionPatterns(session_id: string): Promise {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${PATTERNS_TABLE} WHERE session_id = ?`,\n [session_id]\n );\n \n log.debug(`Retrieved ${result.length} patterns for session ${session_id}`);\n return result as Pattern[];\n } catch (error) {\n log.error(`Failed to get patterns for session ${session_id}:`, error);\n throw new DatabaseError(\"Failed to get session patterns\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get a pattern by ID\n */\nexport async function getPattern(pattern_id: number): Promise {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${PATTERNS_TABLE} WHERE id = ?`,\n [pattern_id]\n );\n \n if (result.length === 0) {\n log.info(`Pattern not found: ${pattern_id}`);\n return null;\n }\n \n log.debug(`Retrieved pattern: ${pattern_id}`);\n return result[0] as Pattern;\n } catch (error) {\n log.error(`Failed to get pattern ${pattern_id}:`, error);\n throw new DatabaseError(\"Failed to get pattern\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get patterns by type\n */\nexport async function getPatternsByType(session_id: string, pattern_type: string): Promise {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${PATTERNS_TABLE} WHERE session_id = ? AND pattern_type LIKE ?`,\n [session_id, `%${pattern_type}%`]\n );\n \n log.debug(`Retrieved ${result.length} patterns of type \"${pattern_type}\" for session ${session_id}`);\n return result as Pattern[];\n } catch (error) {\n log.error(`Failed to get patterns by type for session ${session_id}:`, error);\n throw new DatabaseError(\"Failed to get patterns by type\", error instanceof Error ? error : undefined);\n }\n}\n\n// Example operations\n/**\n * Add an example to a pattern\n */\nexport async function addExample(\n pattern_id: number,\n example_text: string,\n user_provided: boolean\n): Promise {\n try {\n const timestamp = Date.now();\n \n const result = await sqlite.execute(\n `INSERT INTO ${EXAMPLES_TABLE} (pattern_id, example_text, user_provided, timestamp)\n VALUES (?, ?, ?, ?)\n RETURNING id`,\n [pattern_id, example_text, user_provided, timestamp]\n );\n \n // Update the session timestamp for the pattern\n const pattern = await getPattern(pattern_id);\n if (pattern) {\n await updateSessionTimestamp(pattern.session_id);\n }\n \n const exampleId = result[0].id as number;\n log.debug(`Added example ${exampleId} to pattern ${pattern_id}`);\n \n return exampleId;\n } catch (error) {\n log.error(`Failed to add example to pattern ${pattern_id}:`, error);\n throw new DatabaseError(\"Failed to add example\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get examples for a pattern\n */\nexport async function getPatternExamples(pattern_id: number): Promise {\n try {\n const result = await sqlite.execute(\n `SELECT * FROM ${EXAMPLES_TABLE} WHERE pattern_id = ? ORDER BY timestamp ASC`,\n [pattern_id]\n );\n \n log.debug(`Retrieved ${result.length} examples for pattern ${pattern_id}`);\n return result as Example[];\n } catch (error) {\n log.error(`Failed to get examples for pattern ${pattern_id}:`, error);\n throw new DatabaseError(\"Failed to get pattern examples\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get a pattern with its examples\n */\nexport async function getPatternWithExamples(pattern_id: number): Promise {\n try {\n const pattern = await getPattern(pattern_id);\n \n if (!pattern) {\n return null;\n }\n \n const examples = await getPatternExamples(pattern_id);\n return {\n ...pattern,\n examples\n };\n } catch (error) {\n log.error(`Failed to get pattern with examples ${pattern_id}:`, error);\n throw new DatabaseError(\"Failed to get pattern with examples\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Get all patterns with their examples for a session\n */\nexport async function getSessionPatternsWithExamples(session_id: string): Promise {\n try {\n const patterns = await getSessionPatterns(session_id);\n \n const patternsWithExamples = await Promise.all(\n patterns.map(async (pattern) => {\n const examples = await getPatternExamples(pattern.id);\n return {\n ...pattern,\n examples\n };\n })\n );\n \n log.debug(`Retrieved ${patterns.length} patterns with examples for session ${session_id}`);\n return patternsWithExamples;\n } catch (error) {\n log.error(`Failed to get patterns with examples for session ${session_id}:`, error);\n throw new DatabaseError(\"Failed to get session patterns with examples\", error instanceof Error ? error : undefined);\n }\n}",[],[175,226,188],"a5b5dcd0-36bf-11f0-840e-9e149126039e","api","ba930488-f272-4fbf-b71f-cd92c6463bfa",27,["D",1747885719524],[247,248,249],[175,241],{"_33":264,"_13":98,"_36":265,"_38":242,"_40":41,"_42":266,"_44":45,"_46":267,"_17":102,"_49":93,"_50":268,"_52":53,"_54":-5,"_75":269,"_18":270},{"_33":257,"_13":79,"_36":258,"_38":242,"_40":41,"_42":259,"_44":45,"_46":260,"_17":128,"_49":93,"_50":261,"_52":53,"_54":-5,"_75":262,"_18":263},{"_33":250,"_13":68,"_36":251,"_38":242,"_40":41,"_42":252,"_44":45,"_46":253,"_17":128,"_49":93,"_50":254,"_52":53,"_54":-5,"_75":255,"_18":256},"d5bc1cd6-36c0-11f0-b9c8-9e149126039e","c99e9588-36bf-11f0-a92a-9e149126039e",42,["D",1747886229588],"import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport logger from '../utils/logger.ts';\nimport { createErrorResponse, APIError } from '../utils/error-handler.ts';\n\n// Create a logger for the API\nconst log = logger.createLogger('API:StaticFileServer');\n\n/**\n * Simple static file server for the Power Abuse Analyzer frontend\n */\nexport default async function(req: Request): Promise {\n try {\n const url = new URL(req.url);\n let path = url.pathname;\n \n log.info(\"Serving file\", { path });\n \n // Default to index.html for root path\n if (path === \"/\" || path === \"\") {\n path = \"/frontend/index.html\";\n } else if (!path.startsWith(\"/frontend/\")) {\n // Redirect non-frontend paths to the frontend directory\n log.info(\"Redirecting to frontend\", { originalPath: path });\n return new Response(null, {\n status: 302,\n headers: {\n Location: \"/frontend/index.html\"\n }\n });\n }\n \n try {\n // Read the file content\n const content = await readFile(path, import.meta.url);\n \n // Set appropriate content type based on file extension\n const contentType = getContentType(path);\n \n log.debug(\"File served successfully\", { path, contentType });\n \n return new Response(content, {\n headers: {\n \"Content-Type\": contentType,\n \"Cache-Control\": \"max-age=3600\"\n }\n });\n } catch (error) {\n log.error(`Error serving file ${path}:`, error);\n throw new APIError(\"File not found\", 404);\n }\n } catch (error) {\n log.error(\"Error in static file server:\", error);\n return createErrorResponse(error, \"Failed to serve file\");\n }\n}\n\n/**\n * Get content type based on file extension\n */\nfunction getContentType(path: string): string {\n const extension = path.split('.').pop()?.toLowerCase();\n \n switch (extension) {\n case 'html':\n return 'text/html; charset=utf-8';\n case 'css':\n return 'text/css; charset=utf-8';\n case 'js':\n return 'application/javascript; charset=utf-8';\n case 'json':\n return 'application/json; charset=utf-8';\n case 'png':\n return 'image/png';\n case 'jpg':\n case 'jpeg':\n return 'image/jpeg';\n case 'svg':\n return 'image/svg+xml';\n default:\n return 'text/plain; charset=utf-8';\n }\n}",[],[175,241,68],"c9752e5e-36c0-11f0-8038-9e149126039e","a5b5c1d2-36bf-11f0-840e-9e149126039e",41,["D",1747886208991],"import { analyzeText, handleQuestion, isQuestion, AnalysisRequest } from '../analyzer/index.ts';\nimport logger from '../utils/logger.ts';\nimport { createErrorResponse, APIError } from '../utils/error-handler.ts';\n\n// Create a logger for the API\nconst log = logger.createLogger('API:PowerAbuseAnalyzer');\n\n/**\n * HTTP handler for the power abuse analyzer\n */\nexport default async function(req: Request): Promise {\n // Handle OPTIONS request for CORS\n if (req.method === \"OPTIONS\") {\n return new Response(null, {\n headers: {\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type\",\n },\n });\n }\n \n // Only accept POST requests\n if (req.method !== \"POST\") {\n log.warn(\"Method not allowed\", { method: req.method });\n return new Response(JSON.stringify({ error: \"Method not allowed\" }), {\n status: 405,\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n },\n });\n }\n \n try {\n // Parse request body\n const body = await req.json() as AnalysisRequest;\n \n if (!body.text || typeof body.text !== \"string\") {\n log.warn(\"Invalid request - missing text\");\n throw new APIError(\"Text is required\", 400);\n }\n \n log.info(\"Processing analysis request\", { \n textLength: body.text.length,\n hasContext: !!body.context,\n isQuestion: body.isQuestion\n });\n \n let result;\n \n // Determine if this is a question or text for analysis\n if (body.isQuestion || isQuestion(body.text)) {\n result = await handleQuestion(body.text);\n } else {\n // Analyze the text\n result = await analyzeText(body.text, body.context);\n }\n \n log.info(\"Analysis completed successfully\", { \n patternsCount: result.abusivePatterns.length,\n hasResponses: !!result.suggestedResponses\n });\n \n // Return the analysis result\n return new Response(JSON.stringify(result), {\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n },\n });\n } catch (error) {\n log.error(\"Error processing request:\", error);\n return createErrorResponse(error, \"Failed to process request\");\n }\n}",[],[175,241,79],"c4a9447c-39af-11f0-bf9c-9e149126039e","c0fee36a-36bf-11f0-840e-9e149126039e",77,["D",1748208752991],"import * as db from \"../database/index.ts\";\nimport { analyzeText } from \"../analyzer/index.ts\";\nimport { handlePatternFollowUp } from \"../analyzer/index.ts\";\nimport logger from '../utils/logger.ts';\nimport { createErrorResponse, APIError, ValidationError } from '../utils/error-handler.ts';\n\n// Create a logger for the API\nconst log = logger.createLogger('API:ChatAPI');\n\n// Initialize database\nawait db.initDatabase();\n\n// Types for our API\ninterface ChatRequest {\n action: string;\n session_id?: string;\n message?: string;\n title?: string;\n pattern_id?: number;\n example?: string;\n pattern_type?: string;\n parent_id?: number;\n}\n\ninterface ChatResponse {\n success: boolean;\n data?: any;\n error?: string;\n}\n\n/**\n * Process a chat message and generate a response\n */\nasync function processMessage(\n session_id: string,\n message: string,\n parent_id?: number | null,\n pattern_id?: number | null\n): Promise<{\n response: string;\n patterns: db.Pattern[];\n html_response: string;\n}> {\n try {\n log.info(\"Processing message\", { \n session_id, \n messageLength: message.length,\n hasParent: !!parent_id,\n hasPattern: !!pattern_id\n });\n \n // If this is a follow-up to a pattern, handle it differently\n if (pattern_id) {\n return await processPatternFollowUp(session_id, message, pattern_id);\n }\n \n // Regular message analysis\n const analysisResult = await analyzeText(message);\n \n // Store identified patterns in the database\n const messageId = await db.addMessage(session_id, message, \"user\", parent_id);\n const storedPatterns: db.Pattern[] = [];\n \n for (const pattern of analysisResult.abusivePatterns) {\n const patternId = await db.addPattern(\n session_id,\n messageId,\n pattern.pattern,\n pattern.explanation,\n pattern.severity,\n pattern.confidence\n );\n \n // Store examples\n for (const example of pattern.examples) {\n await db.addExample(patternId, example, false);\n }\n \n // Get the pattern with examples\n const storedPattern = await db.getPatternWithExamples(patternId);\n if (storedPattern) {\n storedPatterns.push(storedPattern);\n }\n }\n \n // Format HTML response\n const htmlResponse = formatHtmlResponse(analysisResult, storedPatterns);\n \n // Store bot response\n await db.addMessage(session_id, analysisResult.overallAssessment, \"bot\", messageId);\n \n log.info(\"Message processed successfully\", { \n session_id,\n patternsCount: storedPatterns.length\n });\n \n return {\n response: analysisResult.overallAssessment,\n patterns: storedPatterns,\n html_response: htmlResponse\n };\n } catch (error) {\n log.error(\"Error processing message:\", error);\n throw new Error(\"Failed to process message\");\n }\n}\n\n/**\n * Process a follow-up message about a specific pattern\n */\nasync function processPatternFollowUp(\n session_id: string,\n message: string,\n pattern_id: number\n): Promise<{\n response: string;\n patterns: db.Pattern[];\n html_response: string;\n}> {\n // Get the pattern with examples\n const pattern = await db.getPatternWithExamples(pattern_id);\n \n if (!pattern) {\n log.error(`Pattern not found: ${pattern_id}`);\n throw new Error(\"Pattern not found\");\n }\n \n log.info(\"Processing pattern follow-up\", { \n session_id, \n pattern_id,\n pattern_type: pattern.pattern_type\n });\n \n // Store user message\n const messageId = await db.addMessage(\n session_id,\n message,\n \"user\",\n undefined,\n pattern_id\n );\n \n // Check if the message contains new examples\n const isAddingExample = message.toLowerCase().includes(\"example\") || \n message.toLowerCase().includes(\"instance\") ||\n message.toLowerCase().includes(\"case\");\n \n if (isAddingExample) {\n // Add as a new example\n await db.addExample(pattern_id, message, true);\n log.info(\"Added user-provided example\", { pattern_id });\n }\n \n // Get all examples for this pattern\n const examples = await db.getPatternExamples(pattern_id);\n \n // Generate a response using the analyzer\n const response = await handlePatternFollowUp(\n pattern,\n examples,\n message\n );\n \n // Store bot response\n await db.addMessage(session_id, response, \"bot\", messageId, pattern_id);\n \n // Format HTML response\n const htmlResponse = `\n

Follow-up on pattern: ${pattern.pattern_type}

${response}

\n `;\n \n log.info(\"Pattern follow-up processed successfully\", { \n session_id,\n pattern_id\n });\n \n return {\n response,\n patterns: [pattern],\n html_response: htmlResponse\n };\n}\n\n/**\n * Format HTML response for the frontend\n */\nfunction formatHtmlResponse(analysisResult: any, patterns: db.Pattern[]): string {\n let html = `

Analysis Results:

`;\n \n if (patterns.length > 0) {\n patterns.forEach(pattern => {\n html += `\n

${pattern.pattern_type}

\n Confidence: ${Math.round(pattern.confidence * 100)}%\n

${pattern.explanation}

\n ${pattern.examples && pattern.examples.length > 0 ? \n `

Examples:

${ex.example_text}${ex.user_provided ? ' (user provided)' : ''}

` : ''\n }\n \n

\n `;\n });\n } else {\n html += `

No problematic patterns were identified in this text.

`;\n }\n \n html += `

Overall Assessment:

${analysisResult.overallAssessment}

`;\n \n if (analysisResult.suggestedResponses && analysisResult.suggestedResponses.length > 0) {\n html += `\n

Suggested Responses:

${response}

\n `;\n }\n \n return html;\n}\n\n/**\n * HTTP handler for the chat API\n */\nexport default async function(req: Request): Promise {\n // Handle OPTIONS request for CORS\n if (req.method === \"OPTIONS\") {\n return new Response(null, {\n headers: {\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"POST, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type\",\n },\n });\n }\n \n // Only accept POST requests\n if (req.method !== \"POST\") {\n log.warn(\"Method not allowed\", { method: req.method });\n return new Response(JSON.stringify({ \n success: false, \n error: \"Method not allowed\" \n }), {\n status: 405,\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n },\n });\n }\n \n try {\n // Parse request body\n const body = await req.json() as ChatRequest;\n \n if (!body.action) {\n log.warn(\"Invalid request - missing action\");\n throw new ValidationError(\"Action is required\");\n }\n \n log.info(\"Processing chat API request\", { action: body.action });\n \n let response: ChatResponse;\n \n switch (body.action) {\n case \"create_session\":\n if (!body.title) {\n throw new ValidationError(\"Title is required\");\n }\n \n const session = await db.createSession(body.title);\n response = { success: true, data: session };\n break;\n \n case \"get_session\":\n if (!body.session_id) {\n throw new ValidationError(\"Session ID is required\");\n }\n \n const sessionData = await db.getSession(body.session_id);\n \n if (!sessionData) {\n throw new APIError(\"Session not found\", 404);\n }\n \n const messages = await db.getSessionMessages(body.session_id);\n const patterns = await db.getSessionPatternsWithExamples(body.session_id);\n \n response = { \n success: true, \n data: { \n session: sessionData, \n messages, \n patterns \n } \n };\n break;\n \n case \"get_all_sessions\":\n const sessions = await db.getAllSessions();\n response = { success: true, data: sessions };\n break;\n \n case \"send_message\":\n if (!body.session_id || !body.message) {\n throw new ValidationError(\"Session ID and message are required\");\n }\n \n const messageResponse = await processMessage(\n body.session_id, \n body.message,\n body.parent_id,\n body.pattern_id\n );\n \n response = { success: true, data: messageResponse };\n break;\n \n case \"add_example\":\n if (!body.pattern_id || !body.example) {\n throw new ValidationError(\"Pattern ID and example are required\");\n }\n \n const exampleId = await db.addExample(body.pattern_id, body.example, true);\n const updatedPattern = await db.getPatternWithExamples(body.pattern_id);\n \n response = { success: true, data: { example_id: exampleId, pattern: updatedPattern } };\n break;\n \n case \"get_pattern\":\n if (!body.pattern_id) {\n throw new ValidationError(\"Pattern ID is required\");\n }\n \n const pattern = await db.getPatternWithExamples(body.pattern_id);\n \n if (!pattern) {\n throw new APIError(\"Pattern not found\", 404);\n }\n \n response = { success: true, data: pattern };\n break;\n \n case \"search_patterns\":\n if (!body.session_id || !body.pattern_type) {\n throw new ValidationError(\"Session ID and pattern type are required\");\n }\n \n const matchingPatterns = await db.getPatternsByType(body.session_id, body.pattern_type);\n response = { success: true, data: matchingPatterns };\n break;\n \n case \"update_session_title\":\n if (!body.session_id || !body.title) {\n throw new ValidationError(\"Session ID and title are required\");\n }\n \n await db.updateSessionTitle(body.session_id, body.title);\n const updatedSession = await db.getSession(body.session_id);\n \n response = { success: true, data: updatedSession };\n break;\n \n case \"delete_session\":\n if (!body.session_id) {\n throw new ValidationError(\"Session ID is required\");\n }\n \n await db.deleteSession(body.session_id);\n response = { success: true };\n break;\n \n default:\n log.warn(\"Unknown action\", { action: body.action });\n throw new ValidationError(\"Unknown action\");\n }\n \n log.info(\"Request processed successfully\", { action: body.action });\n \n return new Response(JSON.stringify(response), {\n headers: {\n \"Content-Type\": \"application/json\",\n \"Access-Control-Allow-Origin\": \"*\",\n },\n });\n } catch (error) {\n log.error(\"Error processing request:\", error);\n return createErrorResponse(error, \"Failed to process request\");\n }\n}",[],[175,241,98],"8ec635ce-36bf-11f0-8e76-9e149126039e","analyzer","434e911f-c8cd-4f36-b84d-6885a1ac76d6",25,["D",1747885681040],[278],[175,272],{"_33":279,"_13":188,"_36":280,"_38":273,"_40":41,"_42":281,"_44":45,"_46":282,"_17":283,"_49":93,"_50":284,"_52":53,"_54":-5,"_75":285,"_18":286},"572da5fe-39b0-11f0-b9af-9e149126039e","8ec60838-36bf-11f0-8e76-9e149126039e",82,["D",1748208998806],9,"import logger from '../utils/logger.ts';\nimport { AnalysisError } from '../utils/error-handler.ts';\n\n// Create a logger for the analyzer\nconst log = logger.createLogger('Analyzer');\n\n// Initialize Cerebras client\nconst CEREBRAS_API_KEY = Deno.env.get('CEREBRAS_API_KEY');\nif (!CEREBRAS_API_KEY) {\n throw new Error('CEREBRAS_API_KEY environment variable is required');\n}\n\nconst CEREBRAS_API_URL = 'https://api.cerebras.ai/v1/chat/completions';\n\n// Types for our application\nexport interface AnalysisRequest {\n text: string;\n context?: string; // Optional context about the source\n isQuestion?: boolean; // Whether this is a question rather than text to analyze\n}\n\nexport interface AnalysisPattern {\n pattern: string;\n explanation: string;\n severity: \"subtle\" | \"moderate\" | \"overt\";\n confidence: number;\n examples: string[];\n}\n\nexport interface AnalysisResult {\n abusivePatterns: AnalysisPattern[];\n overallAssessment: string;\n suggestedResponses?: string[];\n}\n\n// Known examples of powerful figures and their problematic language patterns\nconst knownExamples: Record = {\n \"steve jobs\": {\n context: \"Steve Jobs was the co-founder and CEO of Apple Inc.\",\n examples: [\n \"Jobs was known for his 'reality distortion field' where he would convince employees that impossible deadlines were achievable.\",\n \"He would often tell engineers their work was 'garbage' even when it met industry standards.\",\n \"Jobs would sometimes publicly humiliate employees in meetings, calling their ideas 'stupid' or 'worthless'.\",\n \"He would take credit for others' ideas while dismissing their contributions.\",\n \"Jobs would use phrases like 'This is the worst thing I've ever seen' to manipulate employees into constant revisions.\"\n ]\n },\n \"ray dalio\": {\n context: \"Ray Dalio is the founder of Bridgewater Associates, the world's largest hedge fund.\",\n examples: [\n \"Dalio's 'radical transparency' approach involved employees constantly rating and criticizing each other.\",\n \"He would often publicly rank people's contributions in meetings with statements like 'That's a C- comment'.\",\n \"When employees expressed discomfort with his methods, he would say they were 'too weak' or their 'amygdala was hijacking their prefrontal cortex'.\",\n \"He created an environment where he could criticize anyone, but questioning his methods was labeled as 'not getting it'.\",\n \"Dalio would frame his controlling management style as necessary for 'personal growth' and 'evolution'.\"\n ]\n }\n};\n\n/**\n * Helper function to make requests to Cerebras API\n */\nasync function callCerebrasAPI(messages: Array<{role: string, content: string}>, temperature: number = 0.2): Promise {\n const response = await fetch(CEREBRAS_API_URL, {\n method: 'POST',\n headers: {\n 'Authorization': `Bearer ${CEREBRAS_API_KEY}`,\n 'Content-Type': 'application/json',\n },\n body: JSON.stringify({\n model: 'qwen-3-32b',\n messages: messages,\n temperature: temperature,\n max_tokens: 4000,\n }),\n });\n\n if (!response.ok) {\n const errorText = await response.text();\n log.error('Cerebras API error:', { status: response.status, error: errorText });\n throw new Error(`Cerebras API error: ${response.status} ${errorText}`);\n }\n\n const data = await response.json();\n return data.choices[0]?.message?.content || '';\n}\n\n/**\n * Analyzes text for subtle forms of abuse, manipulation, or problematic language\n * from powerful figures using Cerebras Qwen-3 32B model.\n */\nexport async function analyzeText(text: string, context?: string): Promise {\n log.info(\"Analyzing text\", { textLength: text.length, hasContext: !!context });\n \n const systemPrompt = `You are an expert in identifying subtle forms of abuse, manipulation, and problematic language from powerful people. \nYour task is to analyze the provided text and identify patterns that may indicate:\n\n1. Gaslighting or reality distortion - Manipulating someone into questioning their own reality, memory or perceptions\n2. Subtle threats or intimidation - Implied consequences without explicit threats\n3. Minimization of harm - Downplaying the negative impact of actions or decisions\n4. Shifting blame to victims - Making those harmed responsible for their own suffering\n5. Appeals to authority or expertise to silence criticism - Using position or credentials to avoid accountability\n6. False equivalencies - Comparing unrelated situations to normalize problematic behavior\n7. Dehumanizing language - Subtle ways of reducing people to objects, functions, or stereotypes\n8. Plausible deniability tactics - Crafting statements that can be defended as innocent if challenged\n9. Coded language that signals to specific groups - Using terms with special meaning to certain audiences\n10. Misuse of institutional power - Leveraging organizational structures to enable abuse\n11. Intellectual intimidation - Using complex frameworks or jargon to make others feel inferior\n12. Benevolent authoritarianism - Framing controlling behavior as being \"for your own good\"\n13. Selective meritocracy - Claiming decisions are based on merit when they actually favor those who conform\n14. Institutional shield - Using organizational policies or culture as a shield for personal abusive behavior\n\nFocus on SUBTLE and COVERT forms of these patterns that might not be immediately obvious.\nFor each identified pattern, provide:\n- A clear explanation of the pattern\n- The severity (subtle, moderate, or overt)\n- Your confidence level (0.0-1.0)\n- Specific examples from the text\n\nIf no problematic patterns are found, state so clearly.\nProvide an overall assessment of the text.\nIf appropriate, suggest constructive responses or ways to address the problematic language.\n\nFormat your response with clear headings for each pattern and section to make it easily parseable.`;\n\n const userPrompt = context \n ? `Text to analyze: \"${text}\"\\n\\nContext: ${context}`\n : `Text to analyze: \"${text}\"`;\n\n try {\n const analysisText = await callCerebrasAPI([\n { role: \"system\", content: systemPrompt },\n { role: \"user\", content: userPrompt }\n ], 0.2);\n \n log.debug(\"Received analysis response\", { responseLength: analysisText.length });\n \n // Process the AI response into our structured format\n return processAIResponse(analysisText);\n } catch (error) {\n log.error(\"Error analyzing text:\", error);\n throw new AnalysisError(\"Failed to analyze text. Please try again later.\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Handles questions about power abuse patterns or specific powerful figures\n */\nexport async function handleQuestion(question: string): Promise {\n log.info(\"Handling question\", { questionLength: question.length });\n \n // Check if the question is about a known figure\n const lowerQuestion = question.toLowerCase();\n let knownFigure: string | null = null;\n \n for (const figure in knownExamples) {\n if (lowerQuestion.includes(figure)) {\n knownFigure = figure;\n break;\n }\n }\n \n if (knownFigure) {\n log.info(`Question about known figure: ${knownFigure}`);\n const figureInfo = knownExamples[knownFigure];\n const exampleText = figureInfo.examples.join(\" \");\n return analyzeText(exampleText, figureInfo.context);\n }\n \n // For general questions about power abuse\n const systemPrompt = `You are an expert in identifying and explaining subtle forms of abuse, manipulation, and problematic language from powerful people.\nYour task is to answer questions about power dynamics, abuse patterns, and how to identify problematic behavior from people in positions of authority.\n\nFocus on being educational and informative. Provide concrete examples where appropriate.\nIf asked about specific powerful figures, provide balanced analysis based on well-documented behaviors.\n\nFormat your response with clear headings and sections to make it easily readable.`;\n\n try {\n const responseText = await callCerebrasAPI([\n { role: \"system\", content: systemPrompt },\n { role: \"user\", content: question }\n ], 0.3);\n\n log.debug(\"Received question response\", { responseLength: responseText.length });\n \n // Create a simplified result structure for questions\n return {\n abusivePatterns: [],\n overallAssessment: responseText\n };\n } catch (error) {\n log.error(\"Error handling question:\", error);\n throw new AnalysisError(\"Failed to process your question. Please try again later.\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Handles follow-up questions about specific patterns\n */\nexport async function handlePatternFollowUp(\n pattern: {\n pattern_type: string;\n explanation: string;\n severity: string;\n confidence: number;\n },\n examples: { example_text: string; user_provided: boolean }[],\n question: string\n): Promise {\n log.info(\"Handling pattern follow-up\", { \n pattern: pattern.pattern_type, \n questionLength: question.length,\n examplesCount: examples.length\n });\n \n // Create a prompt for the follow-up\n const examplesText = examples\n .map(ex => `- ${ex.example_text}${ex.user_provided ? \" (user provided)\" : \"\"}`)\n .join(\"\\n\");\n \n const systemPrompt = `You are an expert in identifying and explaining patterns of subtle abuse, manipulation, and problematic language from powerful people.\n \nA user has previously identified the following pattern in some text:\n\nPattern: ${pattern.pattern_type}\nExplanation: ${pattern.explanation}\nSeverity: ${pattern.severity}\nConfidence: ${pattern.confidence}\n\nExamples of this pattern:\n${examplesText}\n\nThe user is now asking a follow-up question or providing additional information about this pattern.\nIf they are providing a new example, acknowledge it and explain how it fits the pattern.\nIf they are asking a question, provide a detailed, educational response about this specific pattern.\nFocus on being helpful, informative, and sensitive to the nuances of power dynamics.`;\n\n try {\n // Generate a response using Cerebras API\n const response = await callCerebrasAPI([\n { role: \"system\", content: systemPrompt },\n { role: \"user\", content: question }\n ], 0.3);\n\n log.debug(\"Received pattern follow-up response\", { responseLength: response.length });\n \n return response || \"I'm sorry, I couldn't process your message.\";\n } catch (error) {\n log.error(\"Error handling pattern follow-up:\", error);\n throw new AnalysisError(\"Failed to process your follow-up question. Please try again later.\", error instanceof Error ? error : undefined);\n }\n}\n\n/**\n * Processes the raw AI response into a structured format\n */\nexport function processAIResponse(aiResponse: string): AnalysisResult {\n log.debug(\"Processing AI response\", { responseLength: aiResponse.length });\n \n // Extract patterns using regex or other parsing methods\n const patterns = extractPatterns(aiResponse);\n \n // Extract overall assessment\n const overallAssessment = extractOverallAssessment(aiResponse);\n \n // Extract suggested responses if any\n const suggestedResponses = extractSuggestedResponses(aiResponse);\n \n log.debug(\"Processed AI response\", { \n patternsCount: patterns.length, \n hasOverallAssessment: !!overallAssessment,\n suggestedResponsesCount: suggestedResponses.length\n });\n \n return {\n abusivePatterns: patterns,\n overallAssessment,\n suggestedResponses: suggestedResponses.length > 0 ? suggestedResponses : undefined,\n };\n}\n\n/**\n * Extracts pattern information from AI response\n */\nfunction extractPatterns(aiResponse: string): AnalysisPattern[] {\n const patterns: AnalysisPattern[] = [];\n \n // Look for pattern sections in the response\n // Updated regex to better capture multiline explanations and examples\n const patternRegex = /(?:Pattern|Type):\\s*([^\\n]+)(?:\\n|.)*?Explanation:\\s*((?:[^\\n]+(?:\\n(?!(?:Severity|Confidence|Examples?):)[^\\n]+)*))(?:\\n|.)*?Severity:\\s*([^\\n]+)(?:\\n|.)*?Confidence:\\s*([0-9.]+)(?:\\n|.)*?Examples?:\\s*((?:[^\\n]+(?:\\n(?!(?:Pattern|Type|Overall|Suggested):)[^\\n]+)*))/gi;\n \n let match;\n while ((match = patternRegex.exec(aiResponse)) !== null) {\n const [_, pattern, explanation, severityRaw, confidenceRaw, examplesRaw] = match;\n \n // Normalize severity\n let severity: \"subtle\" | \"moderate\" | \"overt\" = \"subtle\";\n if (severityRaw.toLowerCase().includes(\"moderate\")) {\n severity = \"moderate\";\n } else if (severityRaw.toLowerCase().includes(\"overt\")) {\n severity = \"overt\";\n }\n \n // Parse confidence\n const confidence = parseFloat(confidenceRaw) || 0.5;\n \n // Split examples\n const examples = examplesRaw\n .split(/\\n|;|(?:\\d+\\.)/)\n .map(ex => ex.trim())\n .filter(ex => ex.length > 0);\n \n patterns.push({\n pattern,\n explanation,\n severity,\n confidence,\n examples,\n });\n }\n \n // If no patterns were found but there's content, create a generic entry\n if (patterns.length === 0 && aiResponse.length > 50) {\n // Check if the response indicates no problematic patterns\n if (aiResponse.toLowerCase().includes(\"no problematic patterns\") || \n aiResponse.toLowerCase().includes(\"i did not identify\") ||\n aiResponse.toLowerCase().includes(\"did not find\")) {\n // Return empty array for no patterns\n return [];\n }\n \n // Otherwise create a generic entry with the full response\n return [{\n pattern: \"Analysis\",\n explanation: \"See overall assessment for details\",\n severity: \"subtle\",\n confidence: 0.5,\n examples: [aiResponse.substring(0, 100) + \"...\"]\n }];\n }\n \n return patterns;\n}\n\n/**\n * Extracts overall assessment from AI response\n */\nfunction extractOverallAssessment(aiResponse: string): string {\n // Look for overall assessment section\n const overallRegex = /(?:Overall Assessment|Overall|Summary):\\s*((?:[^\\n]+(?:\\n(?!(?:Pattern|Type|Suggested):)[^\\n]+)*))/i;\n const match = overallRegex.exec(aiResponse);\n \n if (match && match[1]) {\n return match[1].trim();\n }\n \n // If no specific overall assessment section, return a portion of the response\n return aiResponse.substring(0, Math.min(300, aiResponse.length)) + \n (aiResponse.length > 300 ? \"...\" : \"\");\n}\n\n/**\n * Extracts suggested responses from AI response\n */\nfunction extractSuggestedResponses(aiResponse: string): string[] {\n // Look for suggested responses section\n const responsesRegex = /(?:Suggested Responses|Responses|How to Respond):\\s*((?:[^\\n]+(?:\\n(?!(?:Pattern|Type|Overall):)[^\\n]+)*))/i;\n const match = responsesRegex.exec(aiResponse);\n \n if (match && match[1]) {\n return match[1]\n .split(/\\n|;|(?:\\d+\\.)/)\n .map(response => response.trim())\n .filter(response => response.length > 0);\n }\n \n return [];\n}\n\n/**\n * Helper function to determine if text is a question\n */\nexport function isQuestion(text: string): boolean {\n // Check if text ends with a question mark\n if (text.trim().endsWith('?')) return true;\n \n // Check for question words at the beginning\n const questionStarters = ['what', 'how', 'why', 'can you', 'could you', 'would you', 'will you', 'analyze', 'explain', 'tell me'];\n const lowerText = text.toLowerCase();\n return questionStarters.some(starter => 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