add async and add default values

app.py

@@ -3,75 +3,118 @@ import os
 import gradio as gr
 import pandas as pd
 from pinecone import Pinecone
-from utils import get_zotero_ids, get_arxiv_papers, get_hf_embeddings, upload_to_pinecone, get_new_papers, recommend_papers
-
-HF_API_KEY = os.getenv('HF_API_KEY')
-PINECONE_API_KEY = os.getenv('PINECONE_API_KEY')
-INDEX_NAME = os.getenv('INDEX_NAME')
-NAMESPACE_NAME = os.getenv('NAMESPACE_NAME')
+from utils import (
+    get_zotero_ids,
+    get_arxiv_papers,
+    get_hf_embeddings,
+    upload_to_pinecone,
+    get_new_papers,
+    recommend_papers,
+)
+from dotenv import load_dotenv
+
+load_dotenv(".env")
+HF_API_KEY = os.getenv("HF_API_KEY")
+PINECONE_API_KEY = os.getenv("PINECONE_API_KEY")
+INDEX_NAME = os.getenv("INDEX_NAME")
+NAMESPACE_NAME = os.getenv("NAMESPACE_NAME")
 
 script_dir = os.path.dirname(os.path.abspath(__file__))
-os.chdir(script_dir) 
+os.chdir(script_dir)
+
 
 def category_radio(cat):
-    if cat == 'Computer Vision and Pattern Recognition':
-        return 'cs.CV'
-    elif cat == 'Computation and Language':
-        return 'cs.CL'
-    elif cat == 'Artificial Intelligence':
-        return 'cs.AI'
-    elif cat == 'Robotics':
-        return 'cs.RO'
+    if cat == "Computer Vision and Pattern Recognition":
+        return "cs.CV"
+    elif cat == "Computation and Language":
+        return "cs.CL"
+    elif cat == "Artificial Intelligence":
+        return "cs.AI"
+    elif cat == "Robotics":
+        return "cs.RO"
+
 
 def comment_radio(com):
-    if com == 'None':
+    if com == "None":
         return None
     else:
         return com
-    
+
+
 def reset_project():
-    file_path = 'arxiv-scrape.csv'
+    file_path = "arxiv-scrape.csv"
     if os.path.exists(file_path):
         os.remove(file_path)
-        logging.info(f"{file_path} has been deleted. Delete reset_project() if you want to persist recommended papers.")
+        logging.info(
+            f"{file_path} has been deleted. Delete reset_project() if you want to persist recommended papers."
+        )
 
-    api_key = os.getenv('PINECONE_API_KEY')
-    index = os.getenv('INDEX_NAME')
-    pc = Pinecone(api_key = api_key)
+    api_key = os.getenv("PINECONE_API_KEY")
+    index = os.getenv("INDEX_NAME")
+    pc = Pinecone(api_key=api_key)
     if index in pc.list_indexes().names():
         pc.delete_index(index)
-        logging.info(f"{index} index has been deleted from the vectordb. Delete reset_project() if you want to persist recommended papers.")
+        logging.info(
+            f"{index} index has been deleted from the vectordb. Delete reset_project() if you want to persist recommended papers."
+        )
     return f"{file_path} has been deleted.<br />{index} index has been deleted from the vectordb.<br />"
 
+
 def reset_csv():
-    file_path = 'arxiv-scrape.csv'
+    file_path = "arxiv-scrape.csv"
     if os.path.exists(file_path):
         os.remove(file_path)
-        logging.info(f"{file_path} has been deleted. Delete reset_project() if you want to persist recommended papers.")
+        logging.info(
+            f"{file_path} has been deleted. Delete reset_project() if you want to persist recommended papers."
+        )
+
 
 with gr.Blocks() as demo:
 
-    zotero_api_key = gr.Textbox(label="Zotero API Key")
+    zotero_api_key = gr.Textbox(
+        label="Zotero API Key", type="password", value=os.getenv("ZOTERO_API_KEY")
+    )
 
-    zotero_library_id = gr.Textbox(label="Zotero Library ID")
+    zotero_library_id = gr.Textbox(
+        label="Zotero Library ID", value=os.getenv("ZOTERO_LIBRARY_ID")
+    )
 
-    zotero_tag = gr.Textbox(label="Zotero Tag")
+    zotero_tag = gr.Textbox(label="Zotero Tag", value=os.getenv("ZOTERO_TAG"))
 
     arxiv_category_name = gr.State([])
-    radio_arxiv_category_name = gr.Radio(['Computer Vision and Pattern Recognition', 'Computation and Language', 'Artificial Intelligence', 'Robotics'], value= ['Computer Vision and Pattern Recognition'], label="ArXiv Category Query")
-    radio_arxiv_category_name.change(fn = category_radio, inputs= radio_arxiv_category_name, outputs= arxiv_category_name)
+    radio_arxiv_category_name = gr.Radio(
+        [
+            "Computer Vision and Pattern Recognition",
+            "Computation and Language",
+            "Artificial Intelligence",
+            "Robotics",
+        ],
+        value=["Computer Vision and Pattern Recognition"],
+        label="ArXiv Category Query",
+    )
+    radio_arxiv_category_name.change(
+        fn=category_radio, inputs=radio_arxiv_category_name, outputs=arxiv_category_name
+    )
 
     arxiv_comment_query = gr.State([])
-    radio_arxiv_comment_query = gr.Radio(['CVPR', 'ACL', 'TACL', 'JAIR', 'IJRR', 'None'], value=['CVPR'], label="ArXiv Comment Query")
-    radio_arxiv_comment_query.change(fn = comment_radio, inputs= radio_arxiv_comment_query, outputs= arxiv_comment_query)
-
-    threshold = gr.Slider(minimum= 0.70, maximum= 0.99, value = 0.80, label="Similarity Score Threshold")
+    radio_arxiv_comment_query = gr.Radio(
+        ["CVPR", "ACL", "TACL", "JAIR", "IJRR", "None"],
+        value=["CVPR"],
+        label="ArXiv Comment Query",
+    )
+    radio_arxiv_comment_query.change(
+        fn=comment_radio, inputs=radio_arxiv_comment_query, outputs=arxiv_comment_query
+    )
+
+    threshold = gr.Slider(
+        minimum=0.70, maximum=0.99, value=0.80, label="Similarity Score Threshold"
+    )
 
     init_output = gr.Textbox(label="Project Initialization Result")
 
-    rec_output = gr.Markdown(label = "Recommended Papers")
+    rec_output = gr.Markdown(label="Recommended Papers")
 
-    reset_output = gr.Markdown(label = "Reset Declaration")
+    reset_output = gr.Markdown(label="Reset Declaration")
 
     init_btn = gr.Button("Initialize")
 
@@ -79,46 +122,73 @@ with gr.Blocks() as demo:
 
     reset_btn = gr.Button("Reset")
 
-    timer = gr.Timer(value=600)
-    timer.tick(reset_project)
-
-    reset_btn.click(fn = reset_project, inputs= [], outputs= [reset_output])
-
-    @init_btn.click(inputs= [zotero_api_key, zotero_library_id, zotero_tag], outputs= [init_output])
-    def init(zotero_api_key, zotero_library_id, zotero_tag, hf_api_key = HF_API_KEY,  pinecone_api_key = PINECONE_API_KEY, index_name = INDEX_NAME,  namespace_name = NAMESPACE_NAME):
-
-        logging.basicConfig(filename= 'logfile.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+    reset_btn.click(fn=reset_project, inputs=[], outputs=[reset_output])
+
+    @init_btn.click(
+        inputs=[zotero_api_key, zotero_library_id, zotero_tag], outputs=[init_output]
+    )
+    def init(
+        zotero_api_key,
+        zotero_library_id,
+        zotero_tag,
+        hf_api_key=HF_API_KEY,
+        pinecone_api_key=PINECONE_API_KEY,
+        index_name=INDEX_NAME,
+        namespace_name=NAMESPACE_NAME,
+    ):
+
+        logging.basicConfig(
+            filename="logfile.log",
+            level=logging.INFO,
+            format="%(asctime)s - %(levelname)s - %(message)s",
+        )
         logging.info("Project Initialization Script Started (Serverless)")
-        
+
         ids = get_zotero_ids(zotero_api_key, zotero_library_id, zotero_tag)
 
         df = get_arxiv_papers(ids)
 
         embeddings, dim = get_hf_embeddings(hf_api_key, df)
 
-        feedback = upload_to_pinecone(pinecone_api_key, index_name, namespace_name, embeddings, dim, df)
+        feedback = upload_to_pinecone(
+            pinecone_api_key, index_name, namespace_name, embeddings, dim, df
+        )
 
         logging.info(feedback)
         if isinstance(feedback, dict):
             return f"Retrieved {len(ids)} papers from Zotero. Successfully upserted {feedback['upserted_count']} embeddings in {namespace_name} namespace."
-        else :
+        else:
             return feedback
-    
-    @rec_btn.click(inputs= [arxiv_category_name, arxiv_comment_query, threshold], outputs= [rec_output])
-    def recs(arxiv_category_name, arxiv_comment_query, threshold, hf_api_key = HF_API_KEY,  pinecone_api_key = PINECONE_API_KEY, index_name = INDEX_NAME,  namespace_name = NAMESPACE_NAME):
+
+    @rec_btn.click(
+        inputs=[arxiv_category_name, arxiv_comment_query, threshold],
+        outputs=[rec_output],
+    )
+    def recs(
+        arxiv_category_name,
+        arxiv_comment_query,
+        threshold,
+        hf_api_key=HF_API_KEY,
+        pinecone_api_key=PINECONE_API_KEY,
+        index_name=INDEX_NAME,
+        namespace_name=NAMESPACE_NAME,
+    ):
         logging.info("Weekly Script Started (Serverless)")
 
-        df = get_arxiv_papers(category= arxiv_category_name, comment= arxiv_comment_query)
+        df = get_arxiv_papers(category=arxiv_category_name, comment=arxiv_comment_query)
 
         df = get_new_papers(df)
 
         if not isinstance(df, pd.DataFrame):
             return df
-        
+
         embeddings, _ = get_hf_embeddings(hf_api_key, df)
 
-        results = recommend_papers(pinecone_api_key, index_name, namespace_name, embeddings, df, threshold * 3)
+        results = recommend_papers(
+            pinecone_api_key, index_name, namespace_name, embeddings, df, threshold * 3
+        )
 
         return results
 
-demo.launch(share = True)
+
+demo.launch(share=True)