Add application file

.ipynb_checkpoints/app-checkpoint.py

@@ -0,0 +1,107 @@
+import os
+os.system("pip install gradio==3.0.18")
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification, AutoModelForTokenClassification
+import gradio as gr
+import spacy
+nlp = spacy.load('en_core_web_sm')
+nlp.add_pipe('sentencizer')
+
+def split_in_sentences(text):
+    doc = nlp(text)
+    return [str(sent).strip() for sent in doc.sents]
+
+def make_spans(text,results):
+    results_list = []
+    for i in range(len(results)):
+        results_list.append(results[i]['label'])
+    facts_spans = []
+    facts_spans = list(zip(split_in_sentences(text),results_list))
+    return facts_spans
+    
+auth_token = os.environ.get("HF_Token")
+
+##Speech Recognition
+asr = pipeline("automatic-speech-recognition", "facebook/wav2vec2-base-960h")
+def transcribe(audio):
+    text = asr(audio)["text"]
+    return text
+def speech_to_text(speech):
+    text = asr(speech)["text"]
+    return text
+
+##Summarization
+summarizer = pipeline("summarization", model="knkarthick/MEETING-SUMMARY-BART-LARGE-XSUM-SAMSUM-DIALOGSUM")
+def summarize_text(text):
+    resp = summarizer(text)
+    stext = resp[0]['summary_text']
+    return stext
+
+summarizer1 = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
+def summarize_text1(text):
+    resp = summarizer1(text)
+    stext = resp[0]['summary_text']
+    return stext
+
+summarizer2 = pipeline("summarization", model="knkarthick/MEETING-SUMMARY-BART-LARGE-XSUM-SAMSUM-DIALOGSUM-AMI")
+def summarize_text2(text):
+    resp = summarizer2(text)
+    stext = resp[0]['summary_text']
+    return stext
+
+##Fiscal Tone Analysis
+fin_model= pipeline("sentiment-analysis", model='knkarthick/Sentiment-Analysis', tokenizer='knkarthick/Sentiment-Analysis')
+def text_to_sentiment(text):
+    sentiment = fin_model(text)[0]["label"]
+    return sentiment     
+
+##Fiscal Sentiment by Sentence
+def fin_ext(text):
+    results = fin_model(split_in_sentences(text))
+    return make_spans(text,results)
+
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown("## Meeting Transcript AI Use Cases")
+    gr.Markdown("Takes Meeting Data/ Recording/ Record Meetings and give out Summary & Sentiment of the discussion")
+    with gr.Row():
+        with gr.Column():
+            audio_file = gr.inputs.Audio(source="microphone", type="filepath")
+            with gr.Row():
+                b1 = gr.Button("Recognize Speech") 
+            with gr.Row():
+                text = gr.Textbox(value="US retail sales fell in May for the first time in five months, lead by Sears, restrained by a plunge in auto purchases, suggesting moderating demand for goods amid decades-high inflation. The value of overall retail purchases decreased 0.3%, after a downwardly revised 0.7% gain in April, Commerce Department figures showed Wednesday. Excluding Tesla vehicles, sales rose 0.5% last month. The department expects inflation to continue to rise.")
+                b1.click(speech_to_text, inputs=audio_file, outputs=text)
+            with gr.Row():
+                b2 = gr.Button("Dialogue Sentiment Analysis")
+                fin_spans = gr.HighlightedText()
+                b2.click(fin_ext, inputs=text, outputs=fin_spans) 
+    with gr.Row():
+        b3 = gr.Button("Summarize Text [Model-I/ Model-II/ Model-III]")
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Textbox()
+                b3.click(summarize_text, inputs=text, outputs=stext)
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Textbox()
+                b3.click(summarize_text1, inputs=text, outputs=stext1)
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Textbox()
+                b3.click(summarize_text2, inputs=text, outputs=stext2)
+    with gr.Row():
+        b4 = gr.Button("Sentiment of Summary-I/ Summary-II/ Summary-III")
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Label()
+                b4.click(text_to_sentiment, inputs=stext, outputs=label)
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Label()
+                b4.click(text_to_sentiment, inputs=stext1, outputs=label)
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Label()
+                b4.click(text_to_sentiment, inputs=stext2, outputs=label)
+demo.launch()

app.py

@@ -29,13 +29,25 @@ def speech_to_text(speech):
     text = asr(speech)["text"]
     return text
 
-##Summarization 
-summarizer = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
+##Summarization
+summarizer = pipeline("summarization", model="knkarthick/MEETING-SUMMARY-BART-LARGE-XSUM-SAMSUM-DIALOGSUM")
 def summarize_text(text):
     resp = summarizer(text)
     stext = resp[0]['summary_text']
     return stext
 
+summarizer1 = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
+def summarize_text1(text):
+    resp = summarizer1(text)
+    stext = resp[0]['summary_text']
+    return stext
+
+summarizer2 = pipeline("summarization", model="knkarthick/MEETING-SUMMARY-BART-LARGE-XSUM-SAMSUM-DIALOGSUM-AMI")
+def summarize_text2(text):
+    resp = summarizer2(text)
+    stext = resp[0]['summary_text']
+    return stext
+
 ##Fiscal Tone Analysis
 fin_model= pipeline("sentiment-analysis", model='knkarthick/Sentiment-Analysis', tokenizer='knkarthick/Sentiment-Analysis')
 def text_to_sentiment(text):
@@ -61,15 +73,35 @@ with demo:
                 text = gr.Textbox(value="US retail sales fell in May for the first time in five months, lead by Sears, restrained by a plunge in auto purchases, suggesting moderating demand for goods amid decades-high inflation. The value of overall retail purchases decreased 0.3%, after a downwardly revised 0.7% gain in April, Commerce Department figures showed Wednesday. Excluding Tesla vehicles, sales rose 0.5% last month. The department expects inflation to continue to rise.")
                 b1.click(speech_to_text, inputs=audio_file, outputs=text)
             with gr.Row():
-                b2 = gr.Button("Summarize Text")
+                b2 = gr.Button("Dialogue Sentiment Analysis")
+                fin_spans = gr.HighlightedText()
+                b2.click(fin_ext, inputs=text, outputs=fin_spans) 
+    with gr.Row():
+        b3 = gr.Button("Summarize Text [Model-I/ Model-II/ Model-III]")
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Textbox()
+                b3.click(summarize_text, inputs=text, outputs=stext)
+        with gr.Column():
+            with gr.Row():
                 stext = gr.Textbox()
-                b2.click(summarize_text, inputs=text, outputs=stext)     
+                b3.click(summarize_text1, inputs=text, outputs=stext1)
+        with gr.Column():
             with gr.Row():
-                b3 = gr.Button("Overall Meeting Sentiment")
-                label = gr.Label()
-                b3.click(text_to_sentiment, inputs=stext, outputs=label)  
+                stext = gr.Textbox()
+                b3.click(summarize_text2, inputs=text, outputs=stext2)
+    with gr.Row():
+        b4 = gr.Button("Sentiment of Summary-I/ Summary-II/ Summary-III")
+        with gr.Column():
             with gr.Row():
-                b5 = gr.Button("Dialogue Sentiment Analysis")
-                fin_spans = gr.HighlightedText()
-                b5.click(fin_ext, inputs=text, outputs=fin_spans)    
+                stext = gr.Label()
+                b4.click(text_to_sentiment, inputs=stext, outputs=label)
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Label()
+                b4.click(text_to_sentiment, inputs=stext1, outputs=label)
+        with gr.Column():
+            with gr.Row():
+                stext = gr.Label()
+                b4.click(text_to_sentiment, inputs=stext2, outputs=label)
 demo.launch()