# Conversation Analysis Integration ## Overview This integration provides enhanced conversation analysis capabilities for your Botpress bot. It serves as a replacement for the AGI/Connor integration, offering more flexibility and control over table configuration, including customizable row factors and LLM model selection. ## Features - **Flexible Table Management**: Create or duplicate conversation analysis tables with custom configurations - **Customizable Row Factor**: Choose your preferred row factor for table optimization - **LLM Model Selection**: Select from different LLM models for conversation analysis - **AI-Powered Analysis**: Automatically analyze conversations for topics, sentiment, resolution status, and escalations - **Comprehensive Schema**: Built-in schema for tracking conversation transcripts, summaries, and metadata ## Actions ### 1. Duplicate Table (`duplicate`) Use this action when you want to preserve existing conversation data from an AGI/Connor integration table. **When to use:** - You're migrating from AGI/Connor integration - You want to keep existing conversation analysis data - You need to create a copy of an existing table with different settings **Parameters:** - `sourceTableId` (required): ID of the existing table to duplicate - `newTableName` (required): Name for the new duplicated table - `factor` (optional, default: 3): Row factor for table optimization - `tags` (optional): Custom tags to apply to the new table - `frozen` (optional, default: false): Whether the table should be frozen ### 2. Create From Scratch (`createFromScratch`) Use this action when you want to start fresh with a new conversation analysis table. **When to use:** - Setting up a new bot - You don't need to preserve old conversation data - Starting a fresh conversation analysis implementation **Parameters:** - `tableName` (required): Name for the new table - `factor` (optional, default: 5): Row factor for table optimization - `tags` (optional): Custom tags to apply to the table - `frozen` (optional, default: false): Whether the table should be frozen ## Table Schema The integration creates tables with the following conversation analysis fields: - **Topics**: AI-identified topics from user conversations - **Summary**: AI-generated conversation summaries - **Resolved**: Boolean indicating if the issue was resolved - **Sentiment**: Overall conversation sentiment (very positive, positive, neutral, negative, very negative) - **Transcript**: Complete conversation transcript with sender information - **Escalations**: Moments when conversations were escalated - **Conversation ID**: Unique identifier for each chat session - **Date**: Timestamp field for tracking when conversations occurred (preserves original dates during duplication) ## Migration from AGI/Connor Integration If you're currently using the AGI/Connor integration and want to migrate: 1. **Identify your source table**: by default it's 'Int_Connor_Conversations_Table' (named 'conversations' in the Tables tab) -> get the exact tableId 2. **Use the duplicate action**: Run the `duplicate` action 3. **Configure settings**: Set your preferred row factor and tags 4. **Update your bot**: Replace the AGI/Connor integration with this one in your bot configuration ## Benefits Over AGI/Connor Integration - **Customizable Row Factor**: Unlike the fixed settings in AGI/Connor, you can optimize table performance - **Flexible LLM Selection**: Choose the best LLM model for your use case - **Enhanced Control**: More granular control over table settings and configurations - **Better Migration Path**: Seamless migration from existing setups with preserved timestamps - **Improved Schema**: More comprehensive conversation analysis fields with date tracking - **Timestamp Preservation**: Original conversation dates are preserved during table duplication ## Getting Started 1. Install the integration in your Botpress workspace 2. Choose between `duplicate` (for migration) or `createFromScratch` (for new setups) 3. Configure your preferred settings (row factor, tags, etc.) 4. Start analyzing conversations with enhanced flexibility and control ## Create the hook You have to create a hook to populate the table at the end of each conversation (triggered after timeout). If needed, change `conversationAnalysisTable` for the real name of your table. Hook `after conversation end` : ```javascript const results = await conversationAnalysisTable.createRecord({ conversationId: event.conversationId, transcript: event.state.session.history.length ? event.state.session.history.map((h) => ({ sender: h.sender, preview: h.preview })) : [{ sender: 'user', preview: event.preview }], // Automatically set the current date when creating new records date: new Date().toISOString(), // Added required fields with appropriate defaults for computed columns topics: null, // array summary: null, // string resolved: null, // boolean escalations: null // array }) ``` ### Important Notes: - **Date Field**: The `date` field is automatically populated with the current timestamp when new conversations are recorded - **Duplication**: When duplicating tables, original conversation dates from the source table are preserved in the `date` field - **Migration**: This ensures you maintain historical accuracy when migrating from AGI/Connor integration
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