So I am making a chat bot. Things like Intent classification,entity extraction and dialog generation are almost done.The conversations are stateless and now i am stuck at implementing context in conversation(meaning chat bot can remember what the user said and respond accordingly ).
Is there any python library to do that?
If not can anyone guide me how can i do that?
I want the context management to be almost same as IBM Watson Conversation.
Thanks
At the present time, deep learning is the state of the art and Tensorflow is the great technology to take advantage of deep learning.
This is an amazing chatbot framework to build a conversational model for your custom chat bot. You should edit this JSON file to create your conversational intents. Moreover, you can edit the JSON file dynamically according to user's messages or information which are shared by user. You can create and develop an architecture for it so you can reach the stateless conversation system.
For example, you can analyze each messages of users by NLP and update the JSON file.
As a summary, you can develop an architecture by using this chatbot framework to create the stateless conversation system.
Related
I am working on a real-time problem to identify an emotion of the music. I would to do this with Azure bot framework and my challenge here is to make bot which I create to accept the music file upload mechanism in between the chat conversation and need to identify the emotion of the music and categorize it.
The thing I also want to make my bot to identify is the original album recognition of the music bit uploaded.
I hope this sounds crazy, but I would like to combine azure bot services, cognitive services and natural language processing to work in my bot.
Any solution for this!
In combine, there is no such solution till now as new voices are added recently into the speech algorithms. There is a possibility to do this individually.
Create a chatbot with azure bot framework and enable to upload the files
https://learn.microsoft.com/en-us/microsoftteams/platform/resources/bot-v3/bots-files
When the files are uploaded, it must be connected to a logic app where cognitive services are enabled.
Perform the task internally and present the result in the chat.
There are new language updates came out.
https://azure.microsoft.com/en-us/blog/announcing-new-voices-and-emotions-to-azure-neural-text-to-speech/
I have built an NLP Engine in Python for domain-specific language. It takes in raw text and extracts semantics and entities. Also through socket method I have built in the state-management of the conversation. However now this needs to be pushed into Teams and I have understood that this can't be done directly (outgoing webhook Teams) due to security compliance, so I have to use Azure Cloud. I have been going through MSFT BotBuilder Framework, but this is not what I want. I need either:
Teams to be like the client.py that I currently have in the socket-method and use the state-management I currently have.
somehow for Teams to send a POST message to Python (Flask) and then manage the state, which I have no clue how to approach. How should this be done, there seem so many steps involved from Azure to MSFT botbuilder framework. However I don't need the bots from msft, already have my own bot, which I want to invoke in python.
Has anyone experience with any of the above approaches?
Thanks
As the title suggests I have made a chatbot through IBM Watson Assistant and have implemented on my website. I have also made a separate CRM through Python and Django and I have created a separate Messages html where I want the chatbot messages to be recorded so that the sales representatives can follow up with potential customers.
Is there an easy way to do this? Can the messages be recorded in the CRM??
You can integrate your chatbat (your assistant) in several ways. You probably have taken a look at the sections on integrating with your website and custom integrations. A custom integration is probably what you need if you want to store the messages in your CRM. Basically, you would use the API to send messages to Watson Assistant and receive the responses. Your app would collect user input and display the responses. Both could be stored in your CRM.
I am creating a chat bot using python chatter bot library. I am able to train the chat bot in the English language. Next thing I want to accomplish is to build a chat bot to provide selection options to the user for filtering the data.
Example:
Request from user is Book a movie ticket.
I want to display the response as 3 buttons
In which time slot you want to book a movie ticket ?
a. Morning
b. Afternoon
c. Evening.
Is there any feature in Python ChatterBot to send back selection options as response to the user.
You can't get that type of response using GuntherCox's chatterbot Library considering the last stable version.
Read the following documentation to know more: Documentation Link
Else you can raise a issue and also here is their code base for your consideration to look deep down into it: Github Link
If you want intent and entity based chatbot you can look into Snips-nlu and Rasa.
https://github.com/snipsco/snips-nlu
https://github.com/RasaHQ/rasa
So far what I have seen is that chatterbot can only provide static responses. Snips has module for generating json dataset from yaml file where you can define intents, entities, multiple slots etc.
https://snips-nlu.readthedocs.io/en/latest/dataset.html
Rasa can provide what you are looking for. Provide response options based question. Provides easy training, HTTP API, python SDK etc.
https://rasa.com/docs/rasa/user-guide/rasa-tutorial/
Finally, this is a tool for generating training data for snips, rasa and others.
https://rasa.com/docs/rasa/user-guide/rasa-tutorial/
I am developing a chatbot using DialogFlow, as my natural language processing handler, and Python as my client.
My application aims to talk with a human in a python environment (I am currently using a Jupyter Notebook), send the request to DialogFlow, get the response, then calculate the data using some python libraries and show the results to the user.
All the process described above is already working.
Now I must to find a way that lets the people uses my chatbot on line.
Here is my problem, I don't know how to model this.
I think I should put my chatbot in a webpage and make it communicate with my python application stored in a server.
Did anybody make something similar?
Given your current architecture, you'll have to do the following:
Write a client for your chatbot in HTML and JavaScript
Write a server in Python that contains your application logic and makes the API calls to Dialogflow
This is a pretty normal architecture for a web application. Given that you're using Python, you might find Flask or Django helpful.
There should be plenty of samples out there that can help you figure out what to do; I just found this blog post that demonstrates how to build a simple chat client/server with Flask and websockets.
If you're willing to change your architecture so that the user interacts directly with Dialogflow, and all of your application logic lives in the Dialogflow fulfillment webhook, you can make use of Dialogflow's Web Demo integration that provides a pre-built chat widget you can embed into an HTML page.