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How to bulk upload intents from a CSV file in Dialogflow

If you are creating a large FAQ chatbot in Dialogflow, typing out all the intents one by one can be a slooooooooow and painful process.

Thankfully, Dialogflow has an agent ZIP file import feature, and it is possible to programmatically create this ZIP file.

Note: this article talks about the use case where you have already identified the Dialogflow intents. If you haven’t yet defined the intents and the training phrases inside them, check out my tool which can help you automatically extract Dialogflow intents from your chat logs.

Alternatively, you can use the knowledge base feature. But there are some important differences.

I have created a table summarizing the differences between knowledge based FAQ bots and intent based FAQ bots.

Intent Based FAQ BotKnowledge Based FAQ Bot
How we build itUsing intents and training phrasesUsing the knowledge base feature
Support for multiple responses for the same queryNoYes
Multiple training phrases per intentYesNo
Supports entities in training phrasesYesNo
Support for contexts (and follow up)YesNo
Easy to construct rich responses (e.g. for Dialogflow Messenger)YesNo
Use term reinforcement for adding weights to specific words and phrasesYesBlackbox
Allows us to minimize intra-intent variance and maximize inter-intent variance (as recommended by Google)YesBlackbox
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As you can see, unless you are sure you need multiple responses from your chatbot, you are much better off going with the Intent Based FAQ Bot.

How to create a Knowledge Connector bot based on your WordPress website

In this lesson, I explain how you can use the Export All URLs WordPress plugin to quickly create a CSV file which you can use within the Dialogflow Knowledge Connector

Why I avoid the Knowledge Connector feature

Another way to quickly create a Dialogflow ES chatbot from a CSV file would be to create an Intent based FAQ bot using my BotFlo app. An intent based FAQ bot has quite a few advantages over the Knowledge Connector.

Intent based FAQ Bots vs Knowledge Connector FAQ Bots Summary

The Table below summarizes the difference between intent-based and knowledge-based FAQ chatbots in Dialogflow.

In this article, I describe how you can type out your intent information into a spreadsheet and then use a CSV export of your spreadsheet to generate a Dialogflow agent ZIP file. I also discuss the different aspects you need to consider as you try to use this approach for more complex FAQ bots.

By following this template, you should be able to build a tool which can create a Dialogflow FAQ chatbot with the push of a button.

Dissecting the Dialogflow agent ZIP file

I recently built an app which lets you do full text search across all your Dialogflow intents, as well as filter on input and output contexts. In the process, I needed to get a good understanding of what the Dialogflow agent ZIP files contain. Here is a summary of things I learnt. This could be useful if you wish to use the agent ZIP file to build out your own Dialogflow tooling.

How to build your own FAQ Bot Generator

First understand the agent ZIP file format. Then write some code in your favorite programming language to construct the agent ZIP file.

Simple question and answer FAQ chatbot

If you just want to create a simple FAQ bot with one question corresponding to one answer, it requires a simple CSV format. There is a column with a user says message (Query), and then another column with the text response (Response).

Adding input and output contexts

If you would like to add input and output contexts into the CSV format, you need to consider the following: You can have multiple input and output contexts per intent. Every output context should have an associated context lifespan

Adding entities

Specifying entities inside this CSV format is more complex. Why is this? It’s because when you add a training phrase containing an entity, Dialogflow automatically parses the entity value (annotates it, that is). For example, you can see below that the word tomorrow is automatically annotated as a date entity.

Adding followup intents

Since the number of hierarchical levels is (theoretically) unlimited, you can imagine that it is not possible to capture this very complex structure in the CSV format at all. So an app which can convert a CSV file into a Dialogflow agent ZIP file will NOT be able to capture followup intents. However,

Adding slot filling

First of all, I don’t recommend slot filling in Dialogflow ES. And if your bot does need slot filling AND also has a lot of intents,

Adding multiple training phrases per intent

Now, the simple 2 Column CSV format is not sufficient. For example, how can you handle multiple user says (training) phrases per intent What if you want to add multiple text responses? What should be used as the intent’s name?

    • This article is about using a spreadsheet software like a CMS for creating your Dialogflow FAQ chatbot. That is, you will be manually assigning the Intent ID which groups all information for a single intent. Its goal is to speed up input for large-ish Dialogflow FAQ bots.

      I don’t think that is what you are talking about. If you tell me your end goal, maybe I can give some suggestions.

  • Great tutorials!

    Do the intent IDs need to be in sequential order, or can they be any random number?

    Can I use your tool to upload new intents? Where I select the “Import from zip” option?

    I am looking to train the agent, by uploading new intents, or even new training phrases.

    In order to train the agents, I would need to reupload a new zipfile and restore agent?

    Or would I need to:

    1- export the agent,

    2-convert the Json file back to csv (in order to get the list of intents)

    3. then add in my new intents,

    4. then convert back to the zip file using your tool?

    • >> Do the intent IDs need to be in sequential order, or can they be any random number?

      They can be any random number, but you do need to use a unique number per intent obviously.

      I think it is fair to say the rest of your questions boil down to whether or not my app can help with two way updates. Before I answer that question, can you tell me a little bit more about your use case
      a) what kind of bot are you creating?
      b) what kind of training will you be doing? (i.e. using system entities, or developer entities)?

      • Cool thanks for your reply!!

        a) I will be creating an FAQ bot in a sense. That explains which products are needed based on the user input.

        So I would need to update the bot with new intents (new products).

        b) for the training, I will be using Developer entities. Each new product is an entity.

        I would need to train the bot in various ways, the user will ask for this product.

        • I wrote a reply to your question.

          Also, is there any reason you cannot use a single entity to represent all your products, and use a webhook to fetch the answer? That might make your life much simpler.

  • Hello Aravind,
    I have a question about your application. I would like to be able to update the intents that I have on a regular basis. Is it possible to update the intents and integrate new intents into existing hierarchies and contexts with your app?

    Manuel

    • 1 If you mean update the intents from the CSV file, then yes.

      2 You cannot, however, update the intents in Dialogflow and convert the ZIP file in Dialogflow into a CSV format, because of the inherently flat structure of the CSV file.

      3 As for hierarchies, the CSV format cannot naturally support hierarchical intents (i.e. followup intents) again because of its flat structure.

      4 While in theory it is possible to modify the app to support followup intents, it will also make the UX a lot more confusing.

      5 My app does support contexts though, and you can update the contexts (and their lifespans) in the CSV and recreate the ZIP file.

    • In theory, this could happen if the language of your agent isn’t actually English, and you use the _en suffix for the user says JSON files. If you use a non-English language you should look up the corresponding language code and use it in the usersays file names.

  • Excellent tool! I had to wait 2 days before the app was unlocked on your free course, but was worth the wait. You should note: DialogFlow will not accept ZIPs with any intent names greater than 100 characters.

    • A note for those reading this comment: the app is now a paid app (with a very tiny, token payment). This stops the spammers who are using disposable email addresses to sign up.

      • Another update. I don’t offer the limited app anymore as it confused people a lot. If you want to see a demo of the app, you can check out the link mentioned in this post.

  • Hi Aravind.
    Your tool is awesome, but it doesn’t work with more than one response. I think that it should be possible if you find a way to make a comma in between responses (this should still just be in one column). For example:
    IntentID=1; IntentName=Hello; Query=Hello; Response=Hi, Hello;

    • Hi Ame,
      I have tested that it works with multiple responses, but only if you split the multiple responses into multiple lines in the original CSV file. Also the purpose of putting it into two different lines is that otherwise you will need to deal with the exact same issue you are talking about here – you need a separator to indicate the multiple lines (for example a comma like you have used here), and a) it is hard for people to write such text compared to simply putting it into multiple lines and b) you can run into parsing issues.

  • Thanks for a great documentation Aravind!
    I have a question though. Do you know if it’s possible to return with a custom payload instead of the text?

    • Hi Filip,
      This means you need to specify the custom payload JSON inside the CSV file, which I think is very hard to do. Do you mind posting your sample CSV file online where I could take a look at the custom payload’s format?