Psychotherapy Orientation Agent

Psychotherapy Orientation Agent is an experimental AI-powered decision-support prototype that explores how conversational AI and vector-based modeling can help users navigate different psychotherapy approaches. The system conducts a multi-turn conversational interaction using Google Gemini, combining free-text responses with structured inputs to build a multidimensional behavioral profile based on communication patterns, preferences, symptom descriptions, and self-reported context. A computational matching pipeline then transforms this profile into a numerical representation and compares it against predefined therapy archetypes using vector similarity scoring (cosine similarity). Rather than making diagnoses or clinical recommendations, the system explores how explainable mathematical matching models might support psychotherapy orientation and comparative decision support. The architecture combines LLM-based conversational analysis with deterministic Python scoring logic, enabling transparent reasoning between user inputs and suggested therapeutic frameworks. The prototype is designed to explore multiple usage scenarios, including self-guided orientation, practitioner-facing decision-support experimentation, and future expert-informed calibration workflows. Privacy is preserved by storing only anonymized numerical representations rather than identifiable conversational content. Built with Google Gemini, LangChain, LangGraph, Streamlit, Python/NumPy, Vultr Object Storage, Vultr Cloude Compute (Vultr VM backend deployment: 192.248.178.19), SMTP Email, Speechmatics.