final fixes to add top_n. fix presentation of about section. add relative even frequency.

app.py

@@ -22,13 +22,23 @@ def format_pair_frequency_results(data: dict, drug_name: str, event_name: str) -
     if "error" in data:
         return f"An error occurred: {data['error']}"
     
-    total_reports = data.get("meta", {}).get("results", {}).get("total", 0)
+    results = data.get("meta", {}).get("results", {})
+    total_reports = results.get("total", 0)
+    total_for_drug = results.get("total_for_drug", 0)
+
+    percentage_string = ""
+    if total_for_drug > 0:
+        percentage = (total_reports / total_for_drug) * 100
+        percentage_string = (
+            f"\n\nThis combination accounts for **{percentage:.2f}%** of the **{total_for_drug:,}** "
+            f"total adverse event reports for '{drug_name.title()}' in the database."
+        )
 
     result = (
-        f"Found {total_reports:,} reports for the combination of "
-        f"'{drug_name.title()}' and '{event_name.title()}'.\n\n"
-        "Source: FDA FAERS via OpenFDA\n"
-        "Disclaimer: Spontaneous reports do not prove causation. Consult a healthcare professional."
+        f"Found **{total_reports:,}** reports for the combination of "
+        f"'{drug_name.title()}' and '{event_name.title()}'.{percentage_string}\n\n"
+        "**Source**: FDA FAERS via OpenFDA\n"
+        "**Disclaimer**: Spontaneous reports do not prove causation. Consult a healthcare professional."
     )
     return result
 
@@ -48,6 +58,8 @@ def top_adverse_events_tool(drug_name: str, top_n: int = 10, patient_sex: str =
     Returns:
         tuple: A Plotly figure, a Pandas DataFrame, and a summary string.
     """
+    if top_n is None:
+        top_n = 10
     if patient_sex is None:
         patient_sex = "all"
     if min_age is None:
@@ -105,6 +117,8 @@ def serious_outcomes_tool(drug_name: str, top_n: int = 6):
     Returns:
         tuple: A Plotly figure, a Pandas DataFrame, and a summary string.
     """
+    if top_n is None:
+        top_n = 6
     data = get_serious_outcomes(drug_name, limit=top_n)
 
     if "error" in data:
@@ -181,6 +195,8 @@ def report_source_tool(drug_name: str, top_n: int = 5):
     Returns:
         tuple: A Plotly figure, a Pandas DataFrame, and a summary string.
     """
+    if top_n is None:
+        top_n = 5
     data = get_report_source_data(drug_name, limit=top_n)
 
     if "error" in data:
@@ -213,127 +229,121 @@ def report_source_tool(drug_name: str, top_n: int = 5):
 with open("gradio_readme.md", "r") as f:
     readme_content = f.read()
 
-interface_about = gr.Interface(
-    fn=lambda: readme_content,
-    inputs=[],
-    outputs=gr.Markdown(),
-    title="About the Medication Adverse-Event Explorer",
-)
-
-interface1 = gr.Interface(
-    fn=top_adverse_events_tool,
-    inputs=[
-        gr.Textbox(
-            label="Drug Name", 
-            info="Enter a brand or generic drug name (e.g., 'Aspirin', 'Lisinopril')."
-        ),
-        gr.Slider(
-            5, 50, 
-            value=10, 
-            label="Number of Events to Show", 
-            step=1
-        ),
-        gr.Radio(
-            ["All", "Male", "Female"], 
-            label="Patient Sex", 
-            value="All"
-        ),
-        gr.Slider(
-            0, 120, 
-            value=0, 
-            label="Minimum Age", 
-            step=1
-        ),
-        gr.Slider(
-            0, 120, 
-            value=120, 
-            label="Maximum Age", 
-            step=1
-        ),
-    ],
-    outputs=[
-        gr.Plot(label="Top Adverse Events Chart"),
-        gr.DataFrame(label="Top Adverse Events", interactive=False),
-        gr.Markdown()
-    ],
-    title="Top Adverse Events by Drug",
-    description="Find the most frequently reported adverse events for a specific medication.",
-    examples=[["Lisinopril"], ["Ozempic"], ["Metformin"]],
-    #cache_examples=True,
-    allow_flagging="never",
-)
-
-interface3 = gr.Interface(
-    fn=serious_outcomes_tool,
-    inputs=[
-        gr.Textbox(
-            label="Drug Name", 
-            info="Enter a brand or generic drug name (e.g., 'Aspirin', 'Lisinopril')."
-        ),
-        gr.Slider(1, 6, value=6, label="Number of Outcomes to Show", step=1),
-    ],
-    outputs=[
-        gr.Plot(label="Top Serious Outcomes Chart"),
-        gr.DataFrame(label="Top Serious Outcomes", interactive=False),
-        gr.Markdown()
-    ],
-    title="Serious Outcome Analysis",
-    description="Find the most frequently reported serious outcomes (e.g., hospitalization, death) for a specific medication.",
-    examples=[["Lisinopril"], ["Ozempic"], ["Metformin"]],
-    allow_flagging="never",
-    #cache_examples=True,
-)
-
-interface2 = gr.Interface(
-    fn=drug_event_stats_tool,
-    inputs=[
-        gr.Textbox(label="Drug Name", info="e.g., 'Ibuprofen'"),
-        gr.Textbox(label="Adverse Event", info="e.g., 'Headache'")
-    ],
-    outputs=[gr.Textbox(label="Report Count", lines=5)],
-    title="Drug/Event Pair Frequency",
-    description="Get the total number of reports for a specific drug and adverse event combination.",
-    examples=[["Lisinopril", "Cough"], ["Ozempic", "Nausea"]],
-    #cache_examples=True,
-)
-
-interface4 = gr.Interface(
-    fn=time_series_tool,
-    inputs=[
-        gr.Textbox(label="Drug Name", info="e.g., 'Ibuprofen'"),
-        gr.Textbox(label="Adverse Event", info="e.g., 'Headache'"),
-        gr.Radio(["Yearly", "Quarterly"], label="Aggregation", value="Yearly")
-    ],
-    outputs=[gr.Plot(label="Report Trends")],
-    title="Time-Series Trend Plotting",
-    description="Plot the number of adverse event reports over time for a specific drug-event pair.",
-    examples=[["Lisinopril", "Cough", "Yearly"], ["Ozempic", "Nausea", "Quarterly"]],
-    #cache_examples=True,
-)
-
-interface5 = gr.Interface(
-    fn=report_source_tool,
-    inputs=[
-        gr.Textbox(label="Drug Name", info="e.g., 'Aspirin', 'Lisinopril'"),
-        gr.Slider(1, 5, value=5, label="Number of Sources to Show", step=1),
-    ],
-    outputs=[
-        gr.Plot(label="Report Source Breakdown"),
-        gr.DataFrame(label="Report Source Data", interactive=False),
-        gr.Markdown()
-    ],
-    title="Report Source Breakdown",
-    description="Show a pie chart breaking down the source of the reports (e.g., Consumer, Physician).",
-    examples=[["Lisinopril"], ["Ibuprofen"]],
-    allow_flagging="never",
-    #cache_examples=True,
-)
-
-demo = gr.TabbedInterface(
-    [interface_about, interface1, interface3, interface2, interface4, interface5], 
-    ["About", "Top Events", "Serious Outcomes", "Event Frequency", "Time-Series Trends", "Report Sources"],
-    title="Medication Adverse-Event Explorer"
-)
+with gr.Blocks(title="Medication Adverse-Event Explorer") as demo:
+    gr.Markdown("# Medication Adverse-Event Explorer")
+
+    with gr.Tabs():
+        with gr.TabItem("About"):
+            gr.Markdown(readme_content)
+
+        with gr.TabItem("Top Events"):
+            gr.Interface(
+                fn=top_adverse_events_tool,
+                inputs=[
+                    gr.Textbox(
+                        label="Drug Name", 
+                        info="Enter a brand or generic drug name (e.g., 'Aspirin', 'Lisinopril')."
+                    ),
+                    gr.Slider(
+                        5, 50, 
+                        value=10, 
+                        label="Number of Events to Show", 
+                        step=1
+                    ),
+                    gr.Radio(
+                        ["All", "Male", "Female"], 
+                        label="Patient Sex", 
+                        value="All"
+                    ),
+                    gr.Slider(
+                        0, 120, 
+                        value=0, 
+                        label="Minimum Age", 
+                        step=1
+                    ),
+                    gr.Slider(
+                        0, 120, 
+                        value=120, 
+                        label="Maximum Age", 
+                        step=1
+                    ),
+                ],
+                outputs=[
+                    gr.Plot(label="Top Adverse Events Chart"),
+                    gr.DataFrame(label="Top Adverse Events", interactive=False),
+                    gr.Markdown()
+                ],
+                title="Top Adverse Events by Drug",
+                description="Find the most frequently reported adverse events for a specific medication.",
+                examples=[["Lisinopril"], ["Ozempic"], ["Metformin"]],
+                allow_flagging="never",
+            )
+
+        with gr.TabItem("Serious Outcomes"):
+            gr.Interface(
+                fn=serious_outcomes_tool,
+                inputs=[
+                    gr.Textbox(
+                        label="Drug Name", 
+                        info="Enter a brand or generic drug name (e.g., 'Aspirin', 'Lisinopril')."
+                    ),
+                    gr.Slider(1, 6, value=6, label="Number of Outcomes to Show", step=1),
+                ],
+                outputs=[
+                    gr.Plot(label="Top Serious Outcomes Chart"),
+                    gr.DataFrame(label="Top Serious Outcomes", interactive=False),
+                    gr.Markdown()
+                ],
+                title="Serious Outcome Analysis",
+                description="Find the most frequently reported serious outcomes (e.g., hospitalization, death) for a specific medication.",
+                examples=[["Lisinopril"], ["Ozempic"], ["Metformin"]],
+                allow_flagging="never",
+            )
+
+        with gr.TabItem("Event Frequency"):
+            gr.Interface(
+                fn=drug_event_stats_tool,
+                inputs=[
+                    gr.Textbox(label="Drug Name", info="e.g., 'Ibuprofen'"),
+                    gr.Textbox(label="Adverse Event", info="e.g., 'Headache'")
+                ],
+                outputs=[gr.Textbox(label="Report Count", lines=5)],
+                title="Drug/Event Pair Frequency",
+                description="Get the total number of reports for a specific drug and adverse event combination.",
+                examples=[["Lisinopril", "Cough"], ["Ozempic", "Nausea"]],
+            )
+
+        with gr.TabItem("Time-Series Trends"):
+            gr.Interface(
+                fn=time_series_tool,
+                inputs=[
+                    gr.Textbox(label="Drug Name", info="e.g., 'Ibuprofen'"),
+                    gr.Textbox(label="Adverse Event", info="e.g., 'Headache'"),
+                    gr.Radio(["Yearly", "Quarterly"], label="Aggregation", value="Yearly")
+                ],
+                outputs=[gr.Plot(label="Report Trends")],
+                title="Time-Series Trend Plotting",
+                description="Plot the number of adverse event reports over time for a specific drug-event pair.",
+                examples=[["Lisinopril", "Cough", "Yearly"], ["Ozempic", "Nausea", "Quarterly"]],
+            )
+
+        with gr.TabItem("Report Sources"):
+            gr.Interface(
+                fn=report_source_tool,
+                inputs=[
+                    gr.Textbox(label="Drug Name", info="e.g., 'Aspirin', 'Lisinopril'"),
+                    gr.Slider(1, 5, value=5, label="Number of Sources to Show", step=1),
+                ],
+                outputs=[
+                    gr.Plot(label="Report Source Breakdown"),
+                    gr.DataFrame(label="Report Source Data", interactive=False),
+                    gr.Markdown()
+                ],
+                title="Report Source Breakdown",
+                description="Show a pie chart breaking down the source of the reports (e.g., Consumer, Physician).",
+                examples=[["Lisinopril"], ["Ibuprofen"]],
+                allow_flagging="never",
+            )
 
 if __name__ == "__main__":
     demo.launch(mcp_server=True, server_name="0.0.0.0") 

openfda_client.py

@@ -210,14 +210,15 @@ def get_top_adverse_events(drug_name: str, limit: int = 10, patient_sex: Optiona
 def get_drug_event_pair_frequency(drug_name: str, event_name: str) -> dict:
     """
     Query OpenFDA to get the total number of reports for a specific
-    drug-adverse event pair.
+    drug-adverse event pair, and the total reports for the drug alone.
 
     Args:
         drug_name (str): The name of the drug.
         event_name (str): The name of the adverse event.
 
     Returns:
-        dict: The JSON response from the API, or an error dictionary.
+        dict: A dictionary containing the results or an error message.
+              Includes `total` (for the pair) and `total_for_drug`.
     """
     if not drug_name or not event_name:
         return {"error": "Drug name and event name cannot be empty."}
@@ -229,25 +230,51 @@ def get_drug_event_pair_frequency(drug_name: str, event_name: str) -> dict:
     cache_key = f"pair_freq_{drug_name_processed}_{event_name_processed}"
     if cache_key in cache:
         return cache[cache_key]
-
-    query = (
-        f'search=patient.drug.medicinalproduct:"{drug_name_processed}"'
-        f'+AND+patient.reaction.reactionmeddrapt:"{event_name_processed}"'
-    )
-
+    
     try:
+        # First, get total reports for the drug to see if it exists
+        drug_query = f'search=patient.drug.medicinalproduct:"{drug_name_processed}"'
         time.sleep(REQUEST_DELAY_SECONDS)
+        drug_response = requests.get(f"{API_BASE_URL}?{drug_query}")
         
-        response = requests.get(f"{API_BASE_URL}?{query}")
-        response.raise_for_status()
+        # This is a critical failure if the drug isn't found
+        drug_response.raise_for_status() 
+        
+        drug_data = drug_response.json()
+        total_for_drug = drug_data.get("meta", {}).get("results", {}).get("total", 0)
+
+        # Second, get reports for the specific drug-event pair
+        pair_query = (
+            f'search=patient.drug.medicinalproduct:"{drug_name_processed}"'
+            f'+AND+patient.reaction.reactionmeddrapt:"{event_name_processed}"'
+        )
+        time.sleep(REQUEST_DELAY_SECONDS)
+        pair_response = requests.get(f"{API_BASE_URL}?{pair_query}")
+        
+        total_for_pair = 0
+        if pair_response.status_code == 200:
+            pair_data = pair_response.json()
+            total_for_pair = pair_data.get("meta", {}).get("results", {}).get("total", 0)
+        # We don't raise for 404 on the pair, as it just means 0 results
+        elif pair_response.status_code != 404:
+            pair_response.raise_for_status()
+
+        # Construct a consistent response structure
+        data = {
+            "meta": {
+                "results": {
+                    "total": total_for_pair,
+                    "total_for_drug": total_for_drug
+                }
+            }
+        }
         
-        data = response.json()
         cache[cache_key] = data
         return data
 
     except requests.exceptions.HTTPError as http_err:
-        if response.status_code == 404:
-            return {"error": f"No data found for drug '{drug_name}' and event '{event_name}'. They may be misspelled or not in the database."}
+        if http_err.response.status_code == 404:
+            return {"error": f"No data found for drug '{drug_name}'. It may be misspelled or not in the database."}
         return {"error": f"HTTP error occurred: {http_err}"}
     except requests.exceptions.RequestException as req_err:
         return {"error": f"A network request error occurred: {req_err}"}