Update app.py

app.py

@@ -2,65 +2,86 @@ import gradio as gr
 from Bio import Entrez
 from transformers import pipeline
 import spacy
+import os  # For environment variables and file paths
 
 # ---------------------------- Configuration ----------------------------
-ENTREZ_EMAIL = "oluwafemidiakhoa@gmail.com"  # Replace with your email!
-HUGGINGFACE_API_TOKEN = "HUGGINGFACE_API_TOKEN"  # Replace with your Hugging Face API token!
-SUMMARIZATION_MODEL = "facebook/bart-large-cnn"  # Or try "google/pegasus-large"
-SPACY_MODEL = "en_core_web_sm" # Small model for faster processing
+ENTREZ_EMAIL = os.environ.get("ENTREZ_EMAIL", "your_email@example.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"
+SPACY_MODEL = "en_core_web_sm"
+
 # ---------------------------- Global Variables ----------------------------
+summarizer = None
+nlp = None
+initialization_status = "Initializing..."  # Track initialization state
+
 
-summarizer = None  # Initialized in the setup function
-nlp = None # Initialized in the setup function
+# ---------------------------- Helper Functions ----------------------------
+
+def log_error(message: str):
+    """Logs an error message to the console and a file (if possible)."""
+    print(f"ERROR: {message}")
+    try:
+        with open("error_log.txt", "a") as f:
+            f.write(f"{message}\n")
+    except:
+        print("Couldn't write to error log file.")  #If logging fails, still print to console
 
 # ---------------------------- Tool Functions ----------------------------
 
 def search_pubmed(query: str) -> list:
     """Searches PubMed and returns a list of article IDs."""
-    Entrez.email = ENTREZ_EMAIL
     try:
-        handle = Entrez.esearch(db="pubmed", term=query, retmax="5")  # Limit to 5 for demonstration
+        Entrez.email = ENTREZ_EMAIL
+        handle = Entrez.esearch(db="pubmed", term=query, retmax="5")
         record = Entrez.read(handle)
         handle.close()
         return record["IdList"]
     except Exception as e:
+        log_error(f"PubMed search error: {e}")
         return [f"Error during PubMed search: {e}"]
 
 def fetch_abstract(article_id: str) -> str:
     """Fetches the abstract for a given PubMed article ID."""
-    Entrez.email = ENTREZ_EMAIL
     try:
+        Entrez.email = ENTREZ_EMAIL
         handle = Entrez.efetch(db="pubmed", id=article_id, rettype="abstract", retmode="text")
         abstract = handle.read()
         handle.close()
         return abstract
     except Exception as e:
+        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  # Access the global summarizer
+    global summarizer
     if summarizer is None:
-        return "Summarizer not initialized. Please reload the interface."
+        log_error("Summarizer not initialized.")
+        return "Summarizer not initialized. Check initialization status."
 
     try:
         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: {e}"
 
 def extract_entities(text: str) -> list:
     """Extracts entities (simplified) using SpaCy."""
     global nlp
+    if nlp is None:
+        log_error("SpaCy model not initialized.")
+        return "SpaCy model not initialized. Check initialization status."
     try:
         doc = nlp(text)
         entities = [(ent.text, ent.label_) for ent in doc.ents]
         return entities
     except Exception as e:
+        log_error(f"Entity extraction error: {e}")
         return [f"Error during entity extraction: {e}"]
 
-
-# ---------------------------- Agent Function (Simplified) ----------------------------
+# ---------------------------- Agent Function ----------------------------
 
 def medai_agent(query: str) -> str:
     """Orchestrates the medical literature review and summarization."""
@@ -72,7 +93,7 @@ def medai_agent(query: str) -> str:
             abstract = fetch_abstract(article_id)
             if "Error" not in abstract:
                 summary = summarize_abstract(abstract)
-                entities = extract_entities(abstract) #extract_entities(abstract)
+                entities = extract_entities(abstract)
                 results.append(f"**Article ID:** {article_id}\n\n**Summary:** {summary}\n\n**Entities:** {entities}\n\n---\n")
             else:
                 results.append(f"Error processing article {article_id}: {abstract}\n\n---\n")
@@ -80,31 +101,44 @@ def medai_agent(query: str) -> str:
     else:
         return f"No articles found or error occurred: {article_ids}"
 
-# ---------------------------- Gradio Interface ----------------------------
+# ---------------------------- Initialization and Setup ----------------------------
 
 def setup():
-    """Initializes the summarization model and Spacy model."""
-    global summarizer, nlp
+    """Initializes the summarization model and SpaCy model."""
+    global summarizer, nlp, initialization_status
+    initialization_status = "Initializing..."
     try:
+        print("Initializing summarization pipeline...")
         summarizer = pipeline("summarization", model=SUMMARIZATION_MODEL, token=HUGGINGFACE_API_TOKEN)
+        print("Summarization pipeline initialized.")
+        print("Loading SpaCy model...")
         nlp = spacy.load(SPACY_MODEL)
-        return "MedAI Agent initialized successfully!"
+        print("SpaCy model loaded.")
+        initialization_status = "MedAI Agent initialized successfully!"
+        return initialization_status  # Return the status message
     except Exception as e:
-        return f"Initialization error: {e}"
+        initialization_status = f"Initialization error: {e}"
+        log_error(initialization_status)
+        return initialization_status  # Return the error message
+
+# ---------------------------- Gradio Interface ----------------------------
 
 def launch_gradio():
     """Launches the Gradio interface."""
+    global initialization_status #Allows the function to modify global variable
     with gr.Blocks() as iface:
         gr.Markdown("# MedAI: Medical Literature Review and Summarization")
-        status = gr.Textbox(value="Initializing...", interactive=False)
+        status_display = gr.Textbox(value=initialization_status, interactive=False) # Displays initialization status
         query_input = gr.Textbox(lines=3, placeholder="Enter your medical query (e.g., 'new treatments for diabetes')...")
         submit_button = gr.Button("Submit")
         output_results = gr.Markdown()
 
         submit_button.click(medai_agent, inputs=query_input, outputs=output_results)
+        #The run of the agent will not change.
 
-        # Initialization setup
-        status.value = setup()
+        #The setup is running. The value of the text display will update based on this step.
+        setup_result = setup()
+        status_display.value = setup_result #update the status display.
 
     iface.launch()