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MER is a software that identifies and highlights manipulative communication in text from human conversations and AI-generated responses. MER can evaluate LLM responses for manipulative expressions, fostering development of transparency and safety in AI. It also supports manipulation victims by detecting manipulative patterns in human communication.
A Python SDK for checkpoint-based conversation branching in LLM applications. Solve context pollution by creating isolated exploration branches without losing your context in the main conversation.
This project leverages Langchain and Groq to analyze conversations between recovery agents and borrowers. The analysis includes summarization, key actions identification, sentiment analysis, named entity recognition (NER), and non-compliance checks.
A modular framework for building psychologically-informed AI assistants. Processes real-life conversations and generates therapeutic responses using vector databases for knowledge management and retrieval.
🔍 Extract and analyze your Claude Code conversation history to discover usage patterns, generate insights, and create custom slash commands from your prompting style.
Offline GUI-tool to convert common subtitle files (such as created by Whisper AI) to interview transcripts for qualitative data analysis. Supported import file formats are SRT, VTT, TXT, JSON and TSV. Exported interview transcripts based on GAT2/TiQ/Dresing & Pehl/Kuckartz transcript format convention.