From 05f4d2c426022f44894a873e16cb704f6bf7f5c2 Mon Sep 17 00:00:00 2001 From: alwx Date: Thu, 5 Nov 2020 10:33:07 +0100 Subject: [PATCH] Docs wording --- docs/docs/migrate-from/google-dialogflow-to-rasa.mdx | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/docs/migrate-from/google-dialogflow-to-rasa.mdx b/docs/docs/migrate-from/google-dialogflow-to-rasa.mdx index 4fc9b32d6309..540f7f7b4e0b 100644 --- a/docs/docs/migrate-from/google-dialogflow-to-rasa.mdx +++ b/docs/docs/migrate-from/google-dialogflow-to-rasa.mdx @@ -14,7 +14,7 @@ Navigate to your agent's settings by clicking the gear icon. import dialogflowExport1 from './dialogflow_export.png'; -In DialogFlow, the gear icon that indicates settings sits next to the dropdown menu for choosing between projects. +In Dialogflow, the gear icon that indicates settings sits next to the dropdown menu for choosing between projects. Click on the 'Export and Import' tab and click on the 'Export as ZIP' button. @@ -44,7 +44,7 @@ mv testagent data/ ## Step 3: Train your NLU model -To train a model using your dialogflow data, run: +To train a model using your Dialogflow data, run: ```bash rasa train nlu @@ -80,7 +80,7 @@ To send a request to the server, run: ```bash curl 'localhost:5005/model/parse?emulation_mode=dialogflow' -d '{"text": "hello"}' The `emulation_mode` parameter tells Rasa that you want your JSON response to have the same format as you would -get from DialogFlow `sessions.detectIntent` method (the format is +get from the Dialogflow `sessions.detectIntent` endpoint (the format is described [here](https://cloud.google.com/dialogflow/es/docs/reference/rest/v2/DetectIntentResponse)). You can also leave it out to get the result in the usual Rasa format.