basic app

app.py

@@ -1,7 +1,97 @@
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+
+import nltk
+nltk.download('all')
+from nltk.corpus import wordnet as wn
+import numpy as np
+
 import gradio as gr
+import pyjokes
+
+iface = gr.Interface(fn=generator, inputs="text", outputs="text")
+iface.launch()
+
+
+def similarity(input, joke):
+    return cosine_similarity(input, joke)
+
+
+def get_best(input):
+    model = SentenceTransformer('bert-base-nli-mean-tokens')
+    max_similarity = -1
+    max_idx = 0
+    jokes = pyjokes.get_jokes(language='en', category='all')
+    jokes_embedding = model.encode(jokes)
+    input_embedding = model.encode(input)
+    for idx, joke_embedding in enumerate(jokes_embedding):
+        sim = similarity(joke_embedding.reshape(-1, 1), input_embedding.reshape(-1,1))
+        if(np.sum(sim) > np.sum(max_similarity)):
+            max_idx = idx
+            max_similarity = sim
+    if(np.sum(max_similarity) != -1):
+        return jokes[max_idx]
+    else:
+        return None
+
+def generate_list(input):
+    result = []
+    n = len(input)
+    for Len in range(2, n + 1):
+        for i in range(n - Len + 1):
+            j = i + Len - 1
+            tem = ""
+            for k in range(i, j + 1):
+                tem += input[k]
+            result.append(tem)
+    return result
+
+
+def pattern(input):
+    response = input
+    for substr in generate_list(input):
+        try :
+          syn = wn.synsets(substr)[1].hypernyms()[0].hyponyms()[0].hyponyms()[0].lemmas()[0].name()
+        except:
+          continue
+        if(syn != None):
+            response = response.replace(substr, syn.upper())
+
+    if(input == response):
+      return None
+    else :
+      return response
+
+
+def GPT(input):
+    return None
+
+
+def generator(input=None):
+    response = []
+    if input:
+
+        out1 = GPT(input)
+        if(out1):
+            for out in out1:
+                response.append(out)
+
+        out2 = pattern(input)
+        if(out2):
+            response.append(out2)
+
+        out3 = get_best(input)
+        if(out3):
+            response.append(out3)
+
+    else:
+        out1 = GPT("Hi, what's the matter")
+        if(out1):
+            for out in out1:
+                response.append(out)
 
-def greet(name):
-    return "Hello " + name + "!!"
+        out2 = pyjokes.get_joke(language='en', category='all')
+        if(out2):
+            response.append(out2)
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+    return response #[0] think of doing this

requirements.txt

@@ -0,0 +1,8 @@
+sentence_transformers==2.2.2
+sklearn==1.0.2
+nltk==3.7
+gradio==3.2
+pyjokes==0.6.0
+fastai==2.7.9
+pandas==1.3.5
+numpy==1.21.6