Create app.py

app.py

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+from statistics import mode
+import urllib.request
+import gradio as gr
+import unidecode
+import string
+import json
+
+urllib.request.urlretrieve(
+    'https://drive.google.com/uc?export=download&id=1TXD41vfqNWA6UNDQ73WhtJdZivCJatn-',
+    'bot_questions_tags.json'
+)
+
+answers = ['Hello! My name is Ai.ra, and I am an artificial intelligence (AI). More specifically, I am an NLP (Natural Language Processing) model trained in conversation (a chatbot!).',
+ 'You can ask me things about "Artificial Intelligence," "Machine Learning," "AI Safety," or "AI Ethics."',
+ "I don't have that kind of property hahaha I am software!",
+ "AIRES (AI Robotics Ethics Society) is a society focused on educating the leaders and developers of tomorrow's Artificial Intelligence (AI) to ensure that AI is created ethically and responsibly.",
+ 'Aron Hui is the president/founder of AIRES.',
+ 'What "intelligence" is, remains an open question. However, not to leave you in the lurch, I will define "intelligence" as follows: "Intelligence is the ability of an agent to achieve goals in a wide range of environments."',
+ 'There is no consensus in the literature on what "AI" is (a corollary of not having a robust definition of what "intelligence\'\' is). However, we can say that AI is the intelligence demonstrated by machines, as opposed to the natural intelligence possessed by animals and humans.',
+ 'General Intelligence, or Universal Intelligence, can be defined as the ability to efficiently achieve goals in a wide range of domains.',
+ 'GOFAI ("good-old-fashioned-ai"), or symbolic artificial intelligence, is the term used to refer to methods of developing AI systems based on high-level symbolic (interpretable) representations, logic, and search.',
+ 'A multi-agent system (MAS "Multi-Agent Systems") is a computer system composed of multiple interacting intelligent agents.',
+ 'Machine Learning (ML) is a field of research dedicated to understanding and building methods that "learn", i.e., methods that use information/data to improve performance on some tasks.']
+
+
+with open('bot_questions_tags.json') as json_file:
+    dictionary = json.load(json_file)
+
+
+def generate_ngrams(text, WordsToCombine):
+    """
+    Generates n-grams of length WordsToCombine from the input text.
+
+    Args:
+        text: A string representing the input text
+        WordsToCombine: An integer representing the
+            size of the n-grams to be generated
+
+    Returns:
+        A list of n-grams generated from the input text, where each
+        n-gram is a list of WordsToCombine words
+    """
+    words = text.split()
+    output = []
+    for i in range(len(words) - WordsToCombine+1):
+        output.append(words[i:i+WordsToCombine])
+    return output
+
+
+def make_keys(text, WordsToCombine):
+    """
+    Given a text and a number of words to combine, returns
+    a list of keys that correspond to all possible combinations
+    of n-grams (sequences of n consecutive words) in the text.
+
+    Args:
+        - text (str): The input text.
+        - WordsToCombine (int): The number of words to combine.
+
+    Returns:
+        - sentences (list of str): A list of all the keys, which are
+        the n-grams in the text.
+    """
+    gram = generate_ngrams(text, WordsToCombine)
+    sentences = []
+    for i in range(0, len(gram)):
+        sentence = ' '.join(gram[i])
+        sentences.append(sentence)
+    return sentences
+
+
+def chat(message, history):
+    """
+    A function that generates a response to a user input message
+    based on a pre-built dictionary of responses.
+
+    Args:
+        message (str): A string representing the user's input message.
+        history (list): A list of tuples containing previous
+        messages and responses.
+
+    Returns:
+        tuple: A tuple containing two lists of tuples. The first list is
+        the original history with the user's input message and the bot's
+        response appended as a tuple. The second list is an updated history
+        with the same tuples.
+    """
+    history = history or []
+    text = message.lower()
+    sentences = []
+    values = []
+    new_text = text.translate(str.maketrans('', '', string.punctuation))
+    new_text = unidecode.unidecode(new_text)
+
+    if len(new_text.split()) == 1:
+        if new_text in dictionary.keys():
+            l = [dictionary[new_text]] * 100
+            values.append(l)
+        new_text = new_text + ' ' + new_text
+
+    else:
+        if new_text in dictionary.keys():
+            l = [dictionary[new_text]] * 100
+            values.append(l)
+
+    for i in range(1, len(new_text.split()) + 1):
+        sentence = make_keys(new_text, i)
+        sentences.append(sentence)
+
+    for i in range(len(sentences)):
+        attention = sentences[i]
+        for i in range(len(attention)):
+            if attention[i] in dictionary.keys():
+                l = [dictionary[attention[i]]] * i
+                values.append(l)
+
+    if len([item for sublist in values for item in sublist]) == 0:
+        bot_input_ids = "I'm sorry, either I didn't understand the question, or it is not part of my domain of expertise... :( Try asking it in another way or using other words. Maybe then I can help you!"
+        history.append((message, bot_input_ids))
+        return history, history
+
+    else:
+        values = [item for sublist in values for item in sublist]
+        prediction = mode(values)
+        bot_input_ids = answers[int(prediction)-1]
+        history.append((message, bot_input_ids))
+        return history, history
+
+title = "Basic Chatbot - By Teeny-Tiny Castle 🏰"
+
+head = (
+  "<center>"
+  "<img src='https://d2vrvpw63099lz.cloudfront.net/do-i-need-a-chatbot/header-chat-box.png' width=400>"
+  "This is an example of a rules-based closed domain chatbot. It knows a couple of answers to questions related to AI."
+  "<br>"
+  "</center>"
+)
+
+ref = (
+"<center>"
+"To see its full version (ML style) of this bot, go to <a href='https://playground.airespucrs.org/aira)'>this link</a>."
+"</center>")
+
+# create a chat interface
+#chatbot = gr.Chatbot().style(color_map=("green", "pink")) # Não aceitou style deu erro: AttributeError: 'Chatbot' object has no attribute 'style'
+chatbot = gr.Chatbot()
+
+demo = gr.Interface(
+    chat,
+    ["text", "state"],
+    [chatbot, "state"],
+    allow_flagging="never",
+    title=title,
+    description=head,
+    article=ref
+)
+
+demo.launch()