Just released pact-langchain v0.1.0 - a LangChain memory system that tracks emotional context alongside conversation history.
Background: 25 years in behavioral science. Built this because AI conversations often miss emotional nuance. When users say "I'm frustrated," most systems just store the text without understanding the emotional state that shapes the conversation.
PACT adds emotional intelligence to LangChain's memory system:
- Tracks emotional state across conversations
- Session-based persistence
- Cloud-native architecture
- Drop-in replacement for existing LangChain memory
This is an MVP (v0.1.0). Basic emotional tracking works, but advanced analysis is coming in v0.2.0.
Technical stack: Python, FastAPI, SQLAlchemy, deployed on Render.
Would love feedback from the HN community - especially on:
1. Emotional analysis approaches (LLM-based vs traditional ML)
2. Privacy considerations for emotional data
3. Use cases that need this
Background: 25 years in behavioral science. Built this because AI conversations often miss emotional nuance. When users say "I'm frustrated," most systems just store the text without understanding the emotional state that shapes the conversation.
PACT adds emotional intelligence to LangChain's memory system: - Tracks emotional state across conversations - Session-based persistence - Cloud-native architecture - Drop-in replacement for existing LangChain memory
This is an MVP (v0.1.0). Basic emotional tracking works, but advanced analysis is coming in v0.2.0.
Technical stack: Python, FastAPI, SQLAlchemy, deployed on Render.
PyPI: https://pypi.org/project/pact-langchain/ GitHub: https://github.com/neurobloomai/pact-hx
Would love feedback from the HN community - especially on: 1. Emotional analysis approaches (LLM-based vs traditional ML) 2. Privacy considerations for emotional data 3. Use cases that need this
Open source, MIT licensed.