MVPandey/DTS
🌳 MCTS-inspired parallel beam search for conversation optimization. Explore multiple dialogue strategies simultaneously, stress-test against diverse user personas, score with multi-judge consensus, and discover winning conversation paths that single-shot LLMs miss.
This helps product managers, customer support leads, or marketers design and test multi-turn conversations for chatbots or virtual assistants. It takes an initial user message and explores many different dialogue strategies and user reactions to find the most effective conversation paths. The outcome is robust, goal-oriented conversation designs that anticipate varied user behaviors and achieve desired outcomes.
Use this if you need to optimize an AI chatbot's ability to handle complex, multi-turn interactions and want to ensure it guides users effectively towards a specific goal.
Not ideal if you are looking for a simple, single-response chatbot or if your primary concern is generating basic factual answers rather than strategic conversation flow.
Stars
35
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 18, 2026
Commits (30d)
0
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