Add application file

app.py

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+import gradio as gr
+from Bio import Entrez
+from transformers import pipeline
+import spacy
+
+# ---------------------------- 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
+# ---------------------------- Global Variables ----------------------------
+
+summarizer = None  # Initialized in the setup function
+nlp = None # Initialized in the setup function
+
+# ---------------------------- 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
+        record = Entrez.read(handle)
+        handle.close()
+        return record["IdList"]
+    except Exception as 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:
+        handle = Entrez.efetch(db="pubmed", id=article_id, rettype="abstract", retmode="text")
+        abstract = handle.read()
+        handle.close()
+        return abstract
+    except Exception as 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
+    if summarizer is None:
+        return "Summarizer not initialized. Please reload the interface."
+
+    try:
+        summary = summarizer(abstract, max_length=130, min_length=30, do_sample=False)[0]['summary_text']
+        return summary
+    except Exception as e:
+        return f"Error during summarization: {e}"
+
+def extract_entities(text: str) -> list:
+    """Extracts entities (simplified) using SpaCy."""
+    global nlp
+    try:
+        doc = nlp(text)
+        entities = [(ent.text, ent.label_) for ent in doc.ents]
+        return entities
+    except Exception as e:
+        return [f"Error during entity extraction: {e}"]
+
+
+# ---------------------------- Agent Function (Simplified) ----------------------------
+
+def medai_agent(query: str) -> str:
+    """Orchestrates the medical literature review and summarization."""
+    article_ids = search_pubmed(query)
+
+    if isinstance(article_ids, list) and article_ids:
+        results = []
+        for article_id in article_ids:
+            abstract = fetch_abstract(article_id)
+            if "Error" not in abstract:
+                summary = summarize_abstract(abstract)
+                entities = extract_entities(abstract) #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")
+        return "\n".join(results)
+    else:
+        return f"No articles found or error occurred: {article_ids}"
+
+# ---------------------------- Gradio Interface ----------------------------
+
+def setup():
+    """Initializes the summarization model and Spacy model."""
+    global summarizer, nlp
+    try:
+        summarizer = pipeline("summarization", model=SUMMARIZATION_MODEL, token=HUGGINGFACE_API_TOKEN)
+        nlp = spacy.load(SPACY_MODEL)
+        return "MedAI Agent initialized successfully!"
+    except Exception as e:
+        return f"Initialization error: {e}"
+
+def launch_gradio():
+    """Launches the Gradio interface."""
+    with gr.Blocks() as iface:
+        gr.Markdown("# MedAI: Medical Literature Review and Summarization")
+        status = gr.Textbox(value="Initializing...", interactive=False)
+        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)
+
+        # Initialization setup
+        status.value = setup()
+
+    iface.launch()
+
+# ---------------------------- Main Execution ----------------------------
+
+if __name__ == "__main__":
+    launch_gradio()