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758929a e3fae6c 758929a e3fae6c 758929a e3fae6c 758929a 9d540bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | # Chatbot App Split and Service-Intent Model Ops
The chatbot project now keeps responsibilities separated without moving internal orchestration into Django.
## Apps
- `apps.chat`
- Chat API/UI.
- Knowledge-base retrieval.
- Runtime service detection.
- internal orchestration microservice execution client.
- `apps.service_intents`
- Dataset ownership commands.
- Rebuilds runtime and model-training service intent CSV files.
- `apps.model_ops`
- Optional Hugging Face model installation.
- Fine-tuning service-intent/slot extractor.
- Optional ONNX dynamic quantization.
## Datasets
- `apps/chat/training_models/data/service_intents.csv`
- Runtime detector only.
- Original six columns.
- `apps/chat/training_models/data/service_intents_model_training.csv`
- Model training dataset.
- Includes `is_service`, `parameters_json`, `missing_fields_json`, `role_context`, `service_action`, and `source`.
## Commands
Rebuild both datasets:
```powershell
python manage.py build_service_intent_datasets
```
Install optional ML dependencies:
```powershell
python -m pip install -r requirements-ml.txt
```
Install the base model, train, and quantize:
```powershell
python manage.py prepare_service_intent_model --rebuild-datasets
```
Dry-run without downloading/training:
```powershell
python manage.py prepare_service_intent_model --dry-run --skip-install
```
## internal orchestration
internal orchestration remains an external microservice. Django still talks to it through the existing service executor. |