What it does

Chat is a Python 3.3–3.6 library for building chatbots around natural language understanding and machine learning. It bundles semantic analysis tools, sentence similarity, and knowledge graph construction via Neo4j. The pitch: go from zero to a working bot with multi-user concurrency and custom multi-turn dialogue scenarios.

The interesting bit

The knowledge graph angle is the hook. Rather than treating Q&A as pure retrieval, Chat structures domain knowledge in Neo4j and traverses it for answers. The repo ships with pre-built databases for banking and hospital scenarios, so you can see multi-turn dialogue in action without inventing your own ontology first.

Key highlights

• Ships with three test users and sample knowledge bases (banking, hospital, basic chitchat)
• Supports concurrent clients with isolated per-user dialogue state
• Modular architecture: semantic analysis, graph operations, and QA layers are separable
• Includes a server/client model plus a direct chat.qa.Robot API for simpler integrations
• Chinese-language documentation on ReadTheDocs

Caveats

• Python 3.3–3.6 only; effectively frozen in time
• Requires manual Neo4j setup: edit config files, set passwords, point to the right .db path
• The README’s “quick start” is three steps of terminal wrangling before you say hello
• Last meaningful activity appears to be 2017; contributor list is sparse

Verdict

Worth a look if you’re specifically studying KBQA in Chinese or need a Neo4j-based dialogue skeleton to hack on. Skip it if you want a modern, batteries-included framework—this is more of a research-era artifact with decent bones.