Rasa NLU版本(0.11.3):
使用后端/管道(spacy_sklearn):
操作系统(osx):
问题:我尝试按照教程:https://rasahq.github.io/rasa_nlu/tutorial.html?highlight=project#,
下载示例文件并训练 我测试问候语和告别意图,他们是工作 但是当我用命令测试时:
curl -X POST localhost:5000 / parse -d' {" q":"我正在寻找墨西哥食物"}' | python -m json.tool
它返回:
{
"intent": {
"name": "None",
"confidence": 1.0
},
"entities": [],
"text": "yes"
}
配置文件的内容(如果使用和相关):
{
"project": null,
"fixed_model_name": null,
"config": "config.json",
"data": null,
"emulate": null,
"language": "en",
"log_file": null,
"log_level": "INFO",
"mitie_file": "data/total_word_feature_extractor.dat",
"spacy_model_name": null,
"num_threads": 1,
"max_training_processes": 1,
"path": "/rasa_nlu/projects",
"port": 5000,
"token": null,
"cors_origins": [],
"max_number_of_ngrams": 7,
"pipeline": [],
"response_log": "/rasa_nlu/logs",
"storage": null,
"aws_endpoint_url": null,
"duckling_dimensions": null,
"duckling_http_url": null,
"ner_crf": {
"BILOU_flag": true,
"features": [
[
"low",
"title",
"upper",
"pos",
"pos2"
],
[
"bias",
"low",
"word3",
"word2",
"upper",
"title",
"digit",
"pos",
"pos2",
"pattern"
],
[
"low",
"title",
"upper",
"pos",
"pos2"
]
],
"max_iterations": 50,
"L1_c": 1,
"L2_c": 0.001
},
"intent_classifier_sklearn": {
"C": [
1,
2,
5,
10,
20,
100
],
"kernel": "linear"
}
}
状态:
{
"available_projects": {
"default": {
"status": "ready",
"available_models": [
"fallback"
]
}
}
}
答案 0 :(得分:2)