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import json
import re
import textwrap
import openai
import gradio as gr
def gpt3_completion(prompt, engine='text-davinci-002', temp=0.6, top_p=1.0, tokens=1000, freq_pen=0.25, pres_pen=0.0, stop=['<<END>>']):
print("here");
max_retry = 5
retry = 0
response = openai.Completion.create(
engine=engine,
prompt=prompt,
temperature=0.7,
max_tokens=963,
top_p=1,
frequency_penalty=0,
presence_penalty=0)
text = response['choices'][0]['text'].strip()
text = re.sub('\s+', ' ', text)
return text
def summarize_podcast(podcast):
# Open the transcript file
vtt = podcast
transcript = vtt.read().decode()
res = len(transcript.split())
transcript = transcript.replace("WEBVTT", "")
transcript = "\n".join(filter(None, transcript.splitlines()))
transcript = re.sub(r"\d\d:\d\d:\d\d\.\d\d\d \d\d:\d\d:\d\d\.\d\d\d", "", transcript)
text = transcript
lines = text.split('\n')
names = []
unique_list=[]
for line in lines:
if ':' in line:
name = line.split(':')[0]
names.append(name)
for x in range(0,len(names)):
if names[x] not in unique_list:
unique_list.append(names[x])
sp=""
al=["A","B","C","D","E","F","G","H","I","K","L","M","N","O","P","Q","R","S","T","V","X","Y","Z"]
for x in range(0,len(unique_list)):
transcript = transcript.replace(unique_list[x], al[x])
sp=sp+"Speaker "+str(x+1)+" "+unique_list[x]+"\n"
transcript=sp+""+transcript
openai.api_key = "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"
chunks = textwrap.wrap(transcript, 8000)
result = list()
count = 0
tempstr=""
for chunk in chunks:
count = count + 1
prompt = sp+"""\n
Summarize the portion of the podcast. The summary should be around 200 words. use the Name instead of A, B, C...
Podcast:
"""+str(chunk)+"""'\n\n"""
summary = gpt3_completion(prompt)
summary="chunk : "+str(count)+summary
result.append(summary)
tempstr=tempstr+"\n"+summary
return str(tempstr)
input_file = gr.inputs.File(label="Upload your podcast in VTT format.")
output_text = gr.outputs.Textbox(label="Podcast Summary")
sample_url = "https://www.example.com/sample.vtt"
iface = gr.Interface(fn=summarize_podcast, inputs=input_file, outputs=output_text, title="Podcast Summarizer",
description="This tool summarizes a podcast in VTT format, providing a summary of each chunk of text.")
iface.launch() |