Create app.py

app.py

@@ -0,0 +1,38 @@
+import sys
+
+sys.path.append('src')
+
+from summarizer import summarize
+from data_retrieval import scrape
+from data_preprocessing import lda
+from gsheets import upload_csv_to_new_worksheet
+
+import joblib
+import gradio as gr
+
+
+def main_orchestrator(num_reddit_posts, num_news_articles, num_youtube_videos, gpt_key, model):
+  #scraping
+  filename = scrape(num_reddit_posts=num_reddit_posts,
+                  num_news_articles=num_news_articles,
+                  num_youtube_videos=num_youtube_videos)
+
+  # summarizing
+  csv_filename = summarize(filename, gpt_key, model)
+  print(csv_filename)
+
+  # topic modeling
+  topics, graph1, graph2 = lda(filename)
+  print(topics)
+
+  #upload to sheets
+  gsheet_status = upload_csv_to_new_worksheet(topics)
+  return gsheet_status, topics, graph1, graph2
+
+demo = gr.Interface(
+    fn=main_orchestrator,
+    inputs=[gr.Number(precision=0, minimum=1, maximum=10), gr.Number(precision=0, minimum=1, maximum=10), gr.Number(precision=0, minimum=1, maximum=10), "text", "text"], # list of inputs that correspond to the parameters of the function.
+    outputs=[gr.Textbox(label="Google Sheet Location"), gr.Textbox(label="Topics"), gr.Plot(label="Frequency of Topics"), gr.Plot(label="Top Words in Topics")], # list of outputs that correspond to the returned values in the function.
+)
+demo.launch()
+