Update app.py

app.py

@@ -4,7 +4,8 @@ from transformers import pipeline
 import os  # For environment variables and file paths
 
 # ---------------------------- Configuration ----------------------------
-ENTREZ_EMAIL = os.environ.get("ENTREZ_EMAIL", "oluwafemidiakhoa@gmail.com")  # Use environment variable, default fallback
+ENTREZ_EMAIL = os.environ.get("ENTREZ_EMAIL", "oluwafemidiakhioa@gmail.com")  # Use environment variable, default fallback
+
 HUGGINGFACE_API_TOKEN = os.environ.get("HUGGINGFACE_API_TOKEN", "HUGGINGFACE_API_TOKEN") # Use environment variable, default fallback
 SUMMARIZATION_MODEL = "facebook/bart-large-cnn"
 
@@ -49,24 +50,6 @@ def fetch_abstract(article_id: str) -> str:
         log_error(f"Error fetching abstract for {article_id}: {e}")
         return f"Error fetching abstract for {article_id}: {e}"
 
-def summarize_abstract(abstract: str) -> str:
-    """Summarizes an abstract using a transformer model."""
-    global summarizer
-    if summarizer is None:
-        log_error("Summarizer not initialized.")
-        return "Summarizer not initialized. Check initialization status."
-
-    try:
-        # Check if the abstract is empty or too short
-        if not abstract or len(abstract.strip()) < 50:
-            return "Abstract too short to summarize. A more detailed abstract was not found."
-
-        summary = summarizer(abstract, max_length=130, min_length=30, do_sample=False)[0]['summary_text']
-        return summary
-    except Exception as e:
-        log_error(f"Summarization error: {e}")
-        return f"Error during summarization: Failed to generate concise summary with the current model."
-
 # ---------------------------- Agent Function ----------------------------
 
 def medai_agent(query: str) -> str:
@@ -78,10 +61,9 @@ def medai_agent(query: str) -> str:
         for article_id in article_ids:
             abstract = fetch_abstract(article_id)
             if "Error" not in abstract:
-                summary = summarize_abstract(abstract)
                 results.append(f"<div class='article'>\n"
                                f"  <h3 class='article-id'>Article ID: {article_id}</h3>\n"
-                               f"  <p class='summary'><strong>Summary:</strong> {summary}</p>\n"
+                               f"  <p class='abstract'><strong>Abstract:</strong> {abstract}</p>\n"
                                f"</div>\n")
             else:
                 results.append(f"<div class='article error'>\n"
@@ -99,11 +81,7 @@ def setup():
     global summarizer, initialization_status
     initialization_status = "Initializing..."
     try:
-        print("Initializing summarization pipeline...")
-        initialization_status += "\nInitializing summarization pipeline..."
-        summarizer = pipeline("summarization", model=SUMMARIZATION_MODEL, token=HUGGINGFACE_API_TOKEN)
-        print("Summarization pipeline initialized.")
-        initialization_status += f"\nSummarization pipeline initialized. Model {SUMMARIZATION_MODEL} loaded and ready."
+        initialization_status = "Model is running. The user is now set to search and obtain abstract articles."
         return initialization_status
     except Exception as e:
         initialization_status = f"Initialization error: {e}"
@@ -131,7 +109,7 @@ def launch_gradio():
       font-size: 1.2em;
       margin-bottom: 5px;
     }
-    .summary {
+    .abstract {
       font-style: italic;
     }
     .error-message {
@@ -140,7 +118,7 @@ def launch_gradio():
     """
 
     with gr.Blocks(css=css) as iface:
-        gr.Markdown("# MedAI: Medical Literature Review and Summarization")
+        gr.Markdown("# MedAI: Medical Literature Review and Abstract Finder")
         status_display = gr.Textbox(value=initialization_status, interactive=False)
         query_input = gr.Textbox(lines=3, placeholder="Enter your medical query (e.g., 'new treatments for diabetes')...")
         submit_button = gr.Button("Submit")