How dawidnolove/app-chat-cli works
This is a Python chat application: a user submits text to a Flask endpoint, which delegates to the chat orchestrator. The orchestrator corrects the text, classifies its intent, and generates a response; weather requests additionally query an external weather service and translate its condition. The README describes classification as TF-IDF plus a linear SVM, while the sampled classifier loads a serialized model. The graph reflects that documented model description; other unsampled model internals are not inferred.
Main entry points: main.py Chat orchestrator · server.py Flask chat API · weather.py Weather lookup · error_correction.py Text correction
Components 11
Chat interface
- Flask chat API
server.py - Chat orchestrator
main.py
Text processing
- Text correction
error_correction.py - Correction vocabulary
error_correction_dict.py - TF-IDF SVM classifier
text_classification.py - Serialized model
model.pkl
Response generation
- Intent responses
response_generator.py
Weather integration
- Weather lookup
weather.py - Condition translations
weather_dict.py
Other components
- Chat user
- WeatherAPI
Connections 11
- Chat user → Flask chat API: submits text
- Flask chat API → Chat orchestrator: calls
- Chat orchestrator → Text correction: corrects text
- Text correction → Correction vocabulary: matches against
- Chat orchestrator → TF-IDF SVM classifier: classifies text
- TF-IDF SVM classifier → Serialized model: loads
- Chat orchestrator → Intent responses: generates answer
- Intent responses → Weather lookup: requests weather
- Weather lookup → WeatherAPI: queries
- Weather lookup → Condition translations: translates condition
- Flask chat API → Chat user: returns result