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from chatgpt_service import ChatGPTService
from everything2text4prompt.everything2text4prompt import Everything2Text4Prompt
from everything2text4prompt.util import BaseData, YoutubeData, PodcastData
from gradio_method_service import YoutubeChain, GradioInputs
from digester.util import get_config, Prompt
import json
class VideoExample:
def __init__(self, title, description, transcript):
self.title = title
self.description = description
self.transcript = transcript
@classmethod
def get_youtube_data(cls, api_key: str, video_id: str):
converter = Everything2Text4Prompt(openai_api_key=api_key)
text_data, is_success, error_msg = converter.convert_text("youtube", video_id)
text_data: YoutubeData
title = text_data.title
description = text_data.description
transcript = text_data.full_content
ts_transcript_list = text_data.ts_transcript_list
return YoutubeData(transcript, title, description, ts_transcript_list)
@staticmethod
def get_nthings_10_autogpt():
video_id = "lSTEhG021Jc"
return VideoExample.get_youtube_data("", video_id)
@staticmethod
def get_nthings_7_lifelesson():
video_id = "CUPe_TZECQQ"
return VideoExample.get_youtube_data("", video_id)
@staticmethod
def get_nthings_8_habits():
video_id = "IScN1SOcj7A"
return VideoExample.get_youtube_data("", video_id)
@staticmethod
def get_tutorial_skincare():
video_id = "OrElyY7MFVs"
return VideoExample.get_youtube_data("", video_id)
class YoutubeTestChain:
def __init__(self, api_key: str, gpt_model):
self.api_key = api_key
self.gpt_model = gpt_model
def run_testing_chain(self):
input_1 = """Give me 2 ideas for the summer"""
# input_1 = """Explain more on the first idea"""
response_1 = ChatGPTService.single_rest_call_chatgpt(self.api_key, input_1, self.gpt_model)
input_2 = """
For the first idea, suggest some step by step planning for me
"""
response_2 = ChatGPTService.single_rest_call_chatgpt(self.api_key, input_2, self.gpt_model, history=[input_1, response_1])
def test_youtube_classifier(self, gradio_inputs: GradioInputs, youtube_data: YoutubeData):
iter = YoutubeChain.execute_classifer_chain(gradio_inputs, youtube_data)
while True:
next(iter)
def test_youtube_timestamped_summary(self, gradio_inputs: GradioInputs, youtube_data: YoutubeData):
iter = YoutubeChain.execute_timestamped_summary_chain(gradio_inputs, youtube_data)
while True:
next(iter)
def test_youtube_final_summary(self, gradio_inputs: GradioInputs, youtube_data: YoutubeData, video_type):
iter = YoutubeChain.execute_final_summary_chain(gradio_inputs, youtube_data, video_type)
while True:
next(iter)
if __name__ == '__main__':
config = get_config()
api_key = config.get("openai").get("api_key")
assert api_key
gradio_inputs = GradioInputs(apikey_textbox=api_key, source_textbox="", source_target_textbox="", qa_textbox="", chatbot=[], history=[])
youtube_data: YoutubeData = VideoExample.get_nthings_8_habits()
youtube_test_chain = YoutubeTestChain(api_key)
# youtube_test_chain.test_youtube_classifier(gradio_inputs, youtube_data)
youtube_test_chain.test_youtube_timestamped_summary(gradio_inputs, youtube_data)
# video_type = "N things"
# video_type = "Tutorials"
# video_type = "Others"
# youtube_test_chain.test_youtube_final_summary(gradio_inputs, youtube_data, video_type)
# converter = Everything2Text4Prompt(openai_api_key="")
# source_textbox = "youtube"
# target_source_textbox = "CUPe_TZECQQ"
# text_data, is_success, error_msg = converter.convert_text(source_textbox, target_source_textbox)
# print(text_data.title)
# print(text_data.description)
# print(text_data.full_content)
# print(text_data.ts_transcript_list)
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