Hi guys! Nice work at this thread!
RASA api has endpoint to set current model with put request
http://localhost:5005/model
{
"model_file": "/absolute-path-to-models-directory/models/20190512.tar.gz"
}
Replace the currently loaded model
Sometimes, i upload model file using SFTP (filezilla) and use this API endpoint to replace the current loaded without restart the server
Thanks @itsjhonny Interesting. I tried what you had and was able to get just the single line “model_file” to work. I had been trying the whole object
{
"model_file": "/rasa/mlflow-rasa/models/20220615-144600-cruel-guide.tar.gz",
"model_server": {
"url": "http://localhost:5005/model",
"params": {},
"headers": {},
"basic_auth": {},
"token": "",
"token_name": "",
"wait_time_between_pulls": 0
}
}
FYI I got that format from Rasa Open Source Documentation
Hi @itsjhonny , & jonathanpwheat Im trying to put model like this,
import json
import requests
obj = {
"model_file": "C:/Users/Akash/Desktop/MyChatbot/models/core-20220616-185933-soft-cycle.tar.gz"
}
print(obj)
r = requests.delete('http://localhost:5005/model')
print(r)
# print content of request
print(r.content)
r = requests.put('http://localhost:5005/model', data = json.dumps(obj))
# check status code for response received
# success code - 200
print(r)
# print content of request
print(r.content)
and running this python script, I’m sure I’m going wrong but dont know whats the answer It would be great if you can tell me what i can do with this I’m trying this on localhost Thanks
@ShirudeAkash I didn’t have to delete the old model, it just swapped out the new one.
The only difference I see is that I have headers in my call, everything else looks prett much the same
My code actually trains a new model then swaps it out in the same script. So I get the model info from the training_results.model which is actually models/whatever-the-mode-is-named.tar.gz
then I build the model_file complete absolute path and use that value in my data json object
model_path = training_results.model
model_file = '/rasa/mlflow-rasa/{}'.format(model_path)
rasa_server_url = 'http://localhost:5005/model'
headers = {'Content-Type': 'application/json'}
data = {
"model_file":'{}'.format(model_file)
}
request = requests.put(rasa_server_url, headers=headers, data=json.dumps(data), verify=False)
You mention in your comments you’re getting a 200 code, are you certain it didn’t swap out the model?
I ran rasa run -m models --enable-api --log-file out.log --cors "*" --endpoints endpoints-local.yml --credentials credentials.yml --debug so I could see it working when the new model was injected
@ShirudeAkash I was incorrect and updated my post. I ran rasa (in server mode) with
rasa run -m models --enable-api --log-file out.log --cors "*" --endpoints endpoints.yml --credentials credentials.yml
And used a separate chat client to interact with it.
You can see the change here in the console of the server
2022-06-16 13:13:00 INFO rasa.core.processor - Loading model models/20220615-164453-pallid-island.tar.gz...
2022-06-16 13:13:01 INFO rasa.nlu.utils.spacy_utils - Trying to load SpaCy model with name 'en_core_web_md'.
2022-06-16 13:13:02 INFO rasa.nlu.utils.spacy_utils - Trying to load SpaCy model with name 'en_core_web_md'.
2022-06-16 13:13:27 INFO root - Rasa server is up and running.
2022-06-16 13:15:52 INFO rasa.core.processor - Loading model /home/jwheat/Code/NearlyHuman/rasa/mlflow-rasa/models/20220616-131544-piercing-platform.tar.gz...
2022-06-16 13:15:52 INFO rasa.nlu.utils.spacy_utils - Trying to load SpaCy model with name 'en_core_web_md'.
2022-06-16 13:15:53 INFO rasa.nlu.utils.spacy_utils - Trying to load SpaCy model with name 'en_core_web_md'.
hi @ShirudeAkash `` import requests,json
#model_path=models
model_file=‘rasa_actions/models/20220622-082403-chilly-surfer.tar.gz’
rasa_server_url=‘http://localhost:5005/model’
headers = {‘Content-Type’: ‘application/json’}
data = {
"model_file":model_file
}
request = requests.put(rasa_server_url, headers=headers, data=json.dumps(data), verify=False)
print(request.status_code)
I am getiing response 400(rasa_actions/models/20220622-082403-chilly-surfer.tar.gz' could not be loaded.).What i need to change after running the command `rasa run -m models --enable-api --log-file out.log --cors "*" --endpoints endpoints.yml --credentials credentials.yml
`it worked now
import requests,json
#model_path=models
model_file='models\\20220622-084642-blaring-bumper.tar.gz'
rasa_server_url='http://localhost:5005/model'
headers = {'Content-Type': 'application/json'}
data = {
"model_file":'{}'.format(model_file)
}
request = requests.put(rasa_server_url, headers=headers, data=json.dumps(data), verify=False)
print(request.status_code)
After 3 days the put request worked nothing help from rasa-http documentation
thanks everyone @jonathanpwheat
Sorry was just seeing this and spotted the incorrect model_file path right away.
Glad you got it sorted out!
In postman you have to pass in the body parameters like{ "model_file":"models\\nlu-20220627-133551-edee-g.tar.gz", "rasa_server_url":{ "url":"http://localhost:5005/model" } }
For linux server yu have to change like this forward slash{ "model_file":"models//nlu-20220627-133551-d-e.tar.gz", "rasa_server_url":{ "url":"http://localhost:5005/model" } }
@jonathanpwheat How to train model very fast I am using GPU but it’s very slow.My server name is (https://www.amd.com/en/products/professional-graphics/instinct-mi25). As epochs takes long time to load model should I use NPU or FPGA