rasa: Training a new rasa model from http-api using example provided fails.
Rasa version:2.0.6
Rasa SDK version (if used & relevant):
Rasa X version (if used & relevant):
Python version:3.8.5
Operating system (windows, osx, …):osx
Issue: Using the http-api & example provided unable to train the model
Error (including full traceback):
2020-11-24 09:22:19 DEBUG rasa.server - Extracting JSON payload with Markdown training data from request body.
2020-11-24 09:22:19 DEBUG rasa.server - request payload is:{'domain': 'intents:\n - greet\n - goodbye\n - affirm\n - deny\n - mood_great\n - mood_unhappy\n\nresponses:\n utter_greet:\n - text: "Hey! How are you?"\n\n utter_cheer_up:\n - text: "Here is something to cheer you up:"\n image: "https://i.imgur.com/nGF1K8f.jpg"\n\n utter_did_that_help:\n - text: "Did that help you?"\n\n utter_happy:\n - text: "Great carry on!"\n\n utter_goodbye:\n - text: "Bye"', 'config': 'language: en\npipeline: supervised_embeddings\npolicies:\n - name: MemoizationPolicy\n - name: TEDPolicy', 'nlu': '- intent: greet\n examples: |\n - hey\n - hello\n - hi\n\n- intent: goodbye\n examples: |\n - bye\n - goodbye\n - have a nice day\n - see you\n\n- intent: affirm\n examples: |\n - yes\n - indeed\n\n- intent: deny\n examples: |\n - no\n - never\n\n- intent: mood_great\n examples: |\n - perfect\n - very good\n - great\n\n- intent: mood_unhappy\n examples: |\n - sad\n - not good\n - unhappy', 'responses': "chitchat/ask_name: - text: my name is Sara, Rasa's documentation bot! chitchat/ask_weather: - text: it's always sunny where I live", 'stories': '- story: happy path\n steps:\n - intent: greet\n - action: utter_greet\n - intent: mood_great\n - action: utter_happy\n\n- story: sad path 1\n steps:\n - intent: greet\n - action: utter_greet\n - intent: mood_unhappy\n - action: utter_cheer_up\n - action: utter_did_that_help\n - intent: affirm\n - action: utter_happy\n\n- story: sad path 2\n steps:\n - intent: greet\n - action: utter_greet\n - intent: mood_unhappy\n - action: utter_cheer_up\n - action: utter_did_that_help\n - intent: deny\n - action: utter_goodbye\n\n- story: say goodbye\n steps:\n - intent: goodbye\n - action: utter_goodbye', 'force': False, 'save_to_default_model_directory': True}
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/config.yml' is 'unk'.
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/domain.yml' is 'rasa_yml'.
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/nlu.md' is 'unk'.
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/responses.md' is 'unk'.
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/stories.md' is 'unk'.
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/nlu.md' is 'unk'.
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/responses.md' is 'unk'.
2020-11-24 09:22:19 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/stories.md' is 'unk'.
2020-11-24 09:22:20 INFO rasa.shared.utils.validation - The 'version' key is missing in the training data file /var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/domain.yml. Rasa Open Source will read the file as a version '2.0' file. See https://rasa.com/docs/rasa/training-data-format.
2020-11-24 09:22:20 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/domain.yml' is 'rasa_yml'.
2020-11-24 09:22:20 INFO rasa.shared.utils.validation - The 'version' key is missing in the training data file /var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/domain.yml. Rasa Open Source will read the file as a version '2.0' file. See https://rasa.com/docs/rasa/training-data-format.
2020-11-24 09:22:20 DEBUG rasa.shared.importers.importer - Added 0 training data examples from the story training data.
2020-11-24 09:22:20 DEBUG rasa.shared.nlu.training_data.loading - Training data format of '/var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/domain.yml' is 'rasa_yml'.
2020-11-24 09:22:20 INFO rasa.shared.utils.validation - The 'version' key is missing in the training data file /var/folders/cp/1v9r04wd7mz63xtx_klyr9g40000gn/T/tmpguneyh_s/domain.yml. Rasa Open Source will read the file as a version '2.0' file. See https://rasa.com/docs/rasa/training-data-format.
No training data given. Please provide stories and NLU data in order to train a Rasa model using the '--data' argument.
2020-11-24 09:22:20 ERROR rasa.server - Ran training, but it finished without a trained model.
Command or request that led to error:
Content of configuration file (config.yml) (if relevant):
Content of domain file (domain.yml) (if relevant):
About this issue
- Original URL
- State: closed
- Created 4 years ago
- Reactions: 1
- Comments: 15 (5 by maintainers)
i guess this is causing the training to fail
https://github.com/RasaHQ/rasa/blob/c3e91670c2ae68762108560ea0b388edfbef116d/rasa/server.py#L1171
https://github.com/RasaHQ/rasa/blob/c3e91670c2ae68762108560ea0b388edfbef116d/rasa/server.py#L1175
https://github.com/RasaHQ/rasa/blob/c3e91670c2ae68762108560ea0b388edfbef116d/rasa/server.py#L1179
the file when saved as yaml succeeds training i tried with my own training data and the model got trained
can i make a pr for it?
@tmbo I am prototyping a chatbot generator able to create/update a chatbot from a Python script. NLU data are scraped by the script from a web site. The Python script is preparing the training data and activating training through the HTTP API, in order to replace the active model of the deployed Rasa chatbot with the newly generated model. I understand this can be entirely accomplished using CI/CD techniques, however, in this prototyping phase, I find using the API a little bit more agile. Any comments/suggestions highly appreciated 😊
I am using Rasa version 2.1.1 and was able to temporarily solve the issue in my local environment thanks to @cr33dx’s suggestion (waiting for an official fix of course 😃 However, it seems the example provided in the http-api doc is not working anymore, so in order to perform a complete training (NLU + Core) I had to modify the payload to reflect the latest format of the training data files.