Sample Code for Bot Interactions through Python and Flask

Can you give me code to create a simple question and answer bot

Sure! Here’s some example code for creating a simple question and answer bot using Python and the Flask micro-framework:

pythonCopy codefrom flask import Flask, request, jsonify

app = Flask(__name__)

# Define some sample questions and answers
qa_pairs = {
    "What is your name?": "My name is Bot.",
    "How old are you?": "I was created recently, so I am quite young.",
    "What can you do?": "I can answer questions and have simple conversations.",
    "How are you doing?": "I'm doing well, thank you for asking!"
}

@app.route('/bot', methods=['POST'])
def bot():
    message = request.form['message']
    if message in qa_pairs:
        response = qa_pairs[message]
    else:
        response = "I'm sorry, I don't understand your question."
    return jsonify({"response": response})

if __name__ == '__main__':
    app.run()

In this code, we define a dictionary called qa_pairs that maps questions to their corresponding answers. The bot() function listens for incoming POST requests to the /bot endpoint, and extracts the user’s message from the request. If the message matches a question in qa_pairs, the bot returns the corresponding answer. Otherwise, the bot returns a generic “I’m sorry” message.

To test the bot, you can send a POST request to the /bot endpoint with a message parameter containing your question. For example, you can use the following Python code to send a request using the requests library:

pythonCopy codeimport requests

response = requests.post('http://localhost:5000/bot', data={'message': 'What is your name?'})
print(response.json()['response'])

This should return the response “My name is Bot.”

zenia@zenia.com

How would I add utterances to that?

To add utterances to the question and answer bot, you can modify the qa_pairs dictionary to include a list of possible utterances for each question. You can then update the bot() function to loop through the possible utterances for each question and check if the user’s message matches any of them.

Here’s an example of how you can modify the code to include utterances:

pythonCopy codefrom flask import Flask, request, jsonify

app = Flask(__name__)

# Define some sample questions and answers with possible utterances
qa_pairs = {
    "What is your name?": {
        "utterances": ["what's your name?", "who are you?"],
        "answer": "My name is Bot."
    },
    "How old are you?": {
        "utterances": ["how old are you?", "what's your age?"],
        "answer": "I was created recently, so I am quite young."
    },
    "What can you do?": {
        "utterances": ["what can you do?", "what are your capabilities?"],
        "answer": "I can answer questions and have simple conversations."
    },
    "How are you doing?": {
        "utterances": ["how are you?", "how are you doing?"],
        "answer": "I'm doing well, thank you for asking!"
    }
}

def check_utterance(message, utterances):
    # Check if message matches any of the given utterances
    for utterance in utterances:
        if message.lower() == utterance.lower():
            return True
    return False

@app.route('/bot', methods=['POST'])
def bot():
    message = request.form['message']
    for question, qa_pair in qa_pairs.items():
        utterances = qa_pair['utterances']
        if check_utterance(message, utterances):
            response = qa_pair['answer']
            break
    else:
        response = "I'm sorry, I don't understand your question."
    return jsonify({"response": response})

if __name__ == '__main__':
    app.run()

In this modified code, each question in qa_pairs is now represented as a dictionary that includes a list of possible utterances and its corresponding answer. The check_utterance() function is a helper function that checks if a message matches any of the given utterances.

In the bot() function, we now loop through the qa_pairs dictionary and check each question’s possible utterances using the check_utterance() function. If the user’s message matches any of the utterances for a question, we return the corresponding answer. If no matches are found, we return a generic “I’m sorry” message.

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