https://github.com/plnech/chatbot-with-algolia-answers
Chatbot with Algolia Answers and Dialogflow
https://github.com/plnech/chatbot-with-algolia-answers
Last synced: 7 months ago
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Chatbot with Algolia Answers and Dialogflow
- Host: GitHub
- URL: https://github.com/plnech/chatbot-with-algolia-answers
- Owner: PLNech
- License: mit
- Created: 2021-06-30T07:36:00.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-06-30T07:36:33.000Z (about 5 years ago)
- Last Synced: 2025-01-29T06:51:17.256Z (over 1 year ago)
- Homepage: https://ni17w.sse.codesandbox.io/
- Size: 21.5 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Chatbot with Algolia Answers and Google Dialogflow Messenger
This sample app implements a chatbot that answers your questions about Covid-19 vaccines. With chatbots, you can ask questions using your natural language instead of using artificial search queries. Algolia Answers extracts the users' _intent_ from their questions (semantic understanding) and offers best-matching answers without the need for extra training of the model.
## Features
The sample app uses the following features:
- 🤖 Chatbot building made easy with [Google Cloud Dialogflow](https://cloud.google.com/dialogflow/)
The sample app uses [Dialogflow Messenger](https://cloud.google.com/dialogflow/es/docs/integrations/dialogflow-messenger), a visual chatbot interface (**1**). A [webhook service](https://cloud.google.com/dialogflow/es/docs/fulfillment-webhook) sends the question to Algolia Answers, which handles all user intents (questions).
- 🧠Semantic understanding using [Algolia Answers](https://www.algolia.com/products/answers-for-support/)
The heavy lifting is performed by Algolia Answers (**3**), Algolia's semantic search API. Answers [combines information from the search index](https://www.algolia.com/doc/guides/algolia-ai/answers/), such as relevance, synonyms, or rules, and applies semantic understanding of small snippets to rank which snippet best answers the question (**4**). You don't have to train anything!
Conventionally, you have to train Dialogflow by providing [training phrases and their variations](https://cloud.google.com/dialogflow/es/docs/tutorials/build-an-agent/create-customize-agent) together with matching responses.
You can also integrate Algolia Answers into existing chatbots by directing only a part of user intents to Algolia Answers while other intents are handled elsewhere. Instead of Dialog Messenger, you can also choose other chatbot interfaces, or implement your own.
- 📈 Data from the [World Health Organization's FAQ on Covid-19 vaccines]()
## Demo (Try it yourself!)
[Access the demo](https://ni17w.sse.codesandbox.io/)
## How to run the sample app locally
The sample app implements two servers in these programming languages:
- [Python](server/python)
- [Node.js/JavaScript](server/node)
The [client](client) is a single HTML page with the [Dialogflow Messenger](https://cloud.google.com/dialogflow/es/docs/integrations/dialogflow-messenger).
### 1. Clone this repository
```
git clone https://github.com/algolia-samples/chatbot-with-algolia-answers
```
Copy the file `.env.example` to the directory of the server you want to use and rename it to `.env`. For example, to use the Python implementation:
```bash
cp .env.example server/python/.env
```
### 2. Set up Algolia
To use this sample app, you need an Algolia account. If you don't have one already, [create an account for free](https://www.algolia.com/users/sign-up). Note your [Application ID](https://deploy-preview-5789--algolia-docs.netlify.app/doc/guides/sending-and-managing-data/send-and-update-your-data/how-to/importing-with-the-api/#application-id).
In the `.env` file, set the environment variables `ALGOLIA_APP_ID`:
```bash
ALGOLIA_APP_ID=
```
### 3. Create your Algolia index and upload data
After you set up your Algolia account and Algolia application, [create and populate an index](https://www.algolia.com/doc/guides/sending-and-managing-data/prepare-your-data/). Or, you can use the same data as the demo, [The World Health Organization COVID-19 FAQs](sample/who-covid-faq.json).
To upload your data, you can use the [Algolia dashboard](https://www.algolia.com/doc/guides/sending-and-managing-data/send-and-update-your-data/how-to/importing-from-the-dashboard/) or use on of Algolia's [API clients](https://www.algolia.com/developers/#integrations).
After creating the index and uploading the data, set the environment variable `ALGOLIA_INDEX_NAME` in the `.env` file:
```bash
ALGOLIA_INDEX_NAME=
```
### 4. Set up Algolia Answers
[Follow the instructions](https://www.algolia.com/doc/guides/algolia-ai/answers/#authentication) in Algolia's documentation to set up Algolia Answers for your index. After you added Algolia Answers to your account, set the environment variable `ALGOLIA_API_KEY` in the file `.env`.
```bash
ALGOLIA_API_KEY=
```
### 5. Create and configure a Dialogflow agent
This sample app uses Google Cloud's [Dialogflow](https://cloud.google.com/dialogflow) to bootstrap the chatbot
and the [fulfillment](https://cloud.google.com/dialogflow/es/docs/fulfillment-overview) webhook feature to connect it to Algolia Answers.
1. [Follow the Dialogflow guide](https://cloud.google.com/dialogflow/es/docs/agents-manage) to create an empty agent.
2. Replace the [default fallback intent](https://cloud.google.com/dialogflow/es/docs/intents-default#fallback) with [the file from the sample](sample/dialogflow-default-fallback-intent.json). The default fallback intent is the answer shown, when the agent couldn't find a matching response.
3. Populate the `agent-id` variable in the [index file](client/index.html)
### 6. Follow the instructions in the server directory
Each server directory has a file with instructions:
- [Node.js](server/node/README)
- [Python](server/python/README)
For example, to run the Python implementation of the server, follow these steps:
```bash
cd server/python # there's a README in this folder with instructions
python3 venv env
source env/bin/activate
pip3 install -r requirements.txt
export FLASK_APP=server.py
python3 -m flask run --port=4242
```
1. Expose your development server to the internet. For example, you can use [ngrok](https://ngrok.com/).
2. [Add the public URL](https://cloud.google.com/dialogflow/es/docs/fulfillment-webhook) of the development server to the Dialogflow webhook so it can use it to answer the queries.
3. Enter questions in the chatbot!
## Authors
- [@cdenoix](https://twitter.com/cdenoix)