utterances | lightweight comments widget built on GitHub issues | Blog library

 by   utterance TypeScript Version: Current License: MIT

kandi X-RAY | utterances Summary

kandi X-RAY | utterances Summary

utterances is a TypeScript library typically used in Web Site, Blog applications. utterances has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

A lightweight comments widget built on GitHub issues. Use GitHub issues for blog comments, wiki pages and more!.

            kandi-support Support

              utterances has a medium active ecosystem.
              It has 7902 star(s) with 542 fork(s). There are 43 watchers for this library.
              It had no major release in the last 6 months.
              There are 128 open issues and 194 have been closed. On average issues are closed in 77 days. There are 23 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of utterances is current.

            kandi-Quality Quality

              utterances has no bugs reported.

            kandi-Security Security

              utterances has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              utterances is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              utterances releases are not available. You will need to build from source code and install.

            Top functions reviewed by kandi - BETA

            kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
            Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of utterances
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            utterances Key Features

            No Key Features are available at this moment for utterances.

            utterances Examples and Code Snippets

            No Code Snippets are available at this moment for utterances.

            Community Discussions


            Google Actions Re-certification requirements
            Asked 2021-Jun-09 at 17:02

            Do we need to re-certify a deployed skill if we edit Entities (eg: add synonyms) to Dialogflow or edit Types in case of using Actions Builder?

            Essentially is there an "Update Live Skill" option similar to Alexa Skills Kit, where any published skill can be updated immediately when changes are limited to sample utterances within an intent or slot/entity values.



            Answered 2021-Jun-09 at 17:02

            Yes updates to the conversational model will require a redeploy, which will require a review if you go to the beta or production channels. Alpha releases do not require a review.

            The releases documentation may provide more information.

            Source https://stackoverflow.com/questions/67898367


            Elongating a Data Frame in Pandas
            Asked 2021-Jun-04 at 21:40

            all. I am working on a personal NLP/NLU project using the nps_chat corpus. I am working on identifying all the questions asked and then doing some further analysis.

            It is a rather large data set and is formatted as such:



            Answered 2021-Jun-04 at 21:30

            Perhaps this is what you are looking for?

            Source https://stackoverflow.com/questions/67844110


            Identifying words from a list and code as 0 or 1 and words NOT on the list code as 1
            Asked 2021-May-25 at 21:35

            NOTE: An update/new question on this begins at =====================

            Original post: I am working with utterances, statements spoken by children. From each utterance, if one or more words in the statement match a predefined list of multiple 'core' words (probably 300 words), then I want to input '1' into 'Core' (and if none, then input '0' into 'Core').

            If there are one or more words in the statement that are NOT core words, then I want to input '1' into 'Fringe' (and if there are only core words and nothing extra, then input '0' into 'Fringe').

            Basically, right now I have only the utterances and from those, I need to identify if any words match one of the core and if there are any extra words, identify those as fringe. Here is a snippet of my data.



            Answered 2021-May-15 at 18:01

            A little trick to do this is to replace (gsub()) all core words in the utterances with an empty string "". Then check if the length of the string (nchar()) is still bigger than zero. If is bigger than zero it means that there are non-core words in the utterance. By applying trimws() to the strings after replacing the core words we make sure that no unwanted whitespaces remain that would be counted as characters.

            This is the code by itself.

            Source https://stackoverflow.com/questions/67548272


            Why are my sentences returning my intent even tough they are not in the utterance list of my intent?
            Asked 2021-May-25 at 14:45

            We are developing a skill and my invocation name is "call onstar"

            I got an intent "CallOnStarIntent"

            I got the next utterances

            "switch to onstar",

            "access onstar emergency",

            "access onstar advisor",

            "access onstar",

            "connect to onstar emergency",

            "connect to onstar advisor",

            "connect to onstar",

            "i want to use onstar",

            "open onstar",

            "call onstar emergency",

            "call onstar advisor",

            "call onstar",

            "use onstar",

            "start onstar",

            "onstar information",

            "onstar services",

            "onstar please",

            "onstar emergency",

            "onstar advisor"

            These are the listed utterances and they are working fine when i try a utterance "call square" i get Amazon.FallBackIntent as expected. But when i tried with utterances like "ping onstar" , "play onstar", or any utterances that has the word onstar it returns CallOnStarIntent.

            Does any one know why is this happening?

            Thanks in advance.



            Answered 2021-May-18 at 08:47

            The list of utterances for an intent are not to be seen as a closed set of values like an enumeration in programming languages. They are only samples used to train your Alexa skill. It's described in the documentation page about best practices for sample utterances:

            "Alexa also attempts to generalize based on the samples you provide to interpret spoken phrases that differ in minor ways from the samples specified."

            Source https://stackoverflow.com/questions/67509930


            How to deal with large json files (flattening it to tsv)
            Asked 2021-May-21 at 01:51

            I am working with a large JSON file specifically the persona dataset (download here)

            Each entry in Persona-Chat is a dict with two keys personality and utterances, and the dataset is a list of entries.



            Answered 2021-May-20 at 19:22

            To fully flatten that file, you'd need something like

            Source https://stackoverflow.com/questions/67625201


            Dialog Flow: Today & Tomorrow needs to return with date and time - only returns date with noon
            Asked 2021-May-18 at 18:00

            We have a solution hosted on a server which uses Dialog Flow to convert our utterances to intent. Example utterances: What are the activities for today, What are the activities for tomorrow, What is for lunch today. What is for lunch tomorrow.

            We use entity: @sys.date-time for today/tomorrow. In response to these Dialog Flow sends us a date and time in this format (date, noon and time zone): "2021-05-18T12:00:00+06:00" (+6 seems to be India IST TZ).

            A person can request these queries from anywhere in the world, hence today and tomorrow is relative to where the person is residing. We do know the TZ of the person requesting the service.

            We use the Dialog flow's date, time and TZ and the TZ of the user and calculate the users date. The date comes our incorrect. Reason being that Dialog is always returning Time T12:00:00. If DF gave current time + TZ, our calculations would be correct.

            How do we have Dialog Flow return actual time and not noon for Today/Tomorrow, so we can calculate the correct date for the user (using user's TZ - Time Zone).



            Answered 2021-May-18 at 18:00

            You can pass an IANA time zone identifier such as America/New_York or Asia/Kolkata in the timeZone value in the query parameter, or set a default in the agent settings.

            From the DialogFlow ES documentation:

            timeZone string

            The time zone of this conversational query from the time zone database, e.g., America/New_York, Europe/Paris. If not provided, the time zone specified in agent settings is used.

            Also, India's time zone uses a +05:30 offset. If you're seeing +06:00, that could be any of 10 different time zones, but it's not India.

            Source https://stackoverflow.com/questions/67587284


            identify words within a phrase and code as 0 or 1
            Asked 2021-May-17 at 12:15

            I am working with utterances, statements spoken by children. From each utterance, if one or more words in the statement match a predefined list of multiple 'core' words (probably 300 words), then I want to input '1' into 'Core' (and if none, then input '0' into 'Core').

            Likewise, if there are one or more words in the statement that match a different predefined listed of 'fringe' words (probably 300 fringe words; again which are different than the core words), then I want to input '1' into 'Fringe' (and if none, then input '0' into 'Fringe').

            Basically, right now I have only the utterances and from those, I need to identify if any words match one of the core and match any fringe word. Here is a snippet of my data.



            Answered 2021-Apr-29 at 19:05

            Here is a quick way to maybe solve your question (though I'm sure there are more elegant solutions)...

            Source https://stackoverflow.com/questions/67323478


            Compute frequency list of final words in utterances of variable length
            Asked 2021-May-06 at 14:23

            I have a large dataframe with utterances of variable sizes:



            Answered 2021-May-06 at 11:37

            You can subset df by using the row (seq_len(nrow(df)) and the value in df$size, make a table and calculate the proportions.

            Source https://stackoverflow.com/questions/67417178


            Compute grouped averages across varying numbers of columns
            Asked 2021-May-06 at 06:49

            I have a (very large) dataframe with words in utterances of different sizes and corpus frequencies of the words:



            Answered 2021-May-06 at 06:49

            I had to guess a lot but I think you are looking for this:

            Source https://stackoverflow.com/questions/67412787


            How do I get text I compiled from a txt file into its corresponding row in a dataframe?
            Asked 2021-May-06 at 00:14

            Here is part of the txt file I'm working with:



            Answered 2021-May-04 at 06:16

            You were very close but this is how you would do it using regex:

            Source https://stackoverflow.com/questions/67377446

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install utterances

            You can download it from GitHub.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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