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app.py

@@ -1,64 +1,73 @@
+from io import BytesIO
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+import pandas as pd
+import requests
+from matplotlib.image import imread
+
+
+ALFRED_URL = "http://192.168.1.202:8090"
+
+selected_columns = ["ecg_id", "patient_id", "age", "sex", "scp_codes", "report"]
+ptbxl_df = pd.read_csv("./res/ptbxl_database.csv")
+ptbxl_df = ptbxl_df[selected_columns]
+
+
+def get_ecg_id_from_dataframe(df: pd.DataFrame, evt: gr.SelectData):
+    return evt.row_value[0]
+
+
+def get_ecg_image_from_dataframe(ecg_id):
+    response = requests.post(
+        f"{ALFRED_URL}/hf_demo/ptbxl_to_image",
+        params={"ecg_id": ecg_id},
+    )
+    response.raise_for_status()
+    return imread(BytesIO(response.content))
+
+
+def get_alfred_from_dataframe(ecg_id):
+    response = requests.post(
+        f"{ALFRED_URL}/hf_demo/alfred",
+        params={"ecg_id": ecg_id},
+    )
+    response.raise_for_status()
+    return response.json()
+
+
+with gr.Blocks() as demo:
+    with gr.Tab("Example"):
+        with gr.Row():
+            gr_df = gr.Image(
+                value="./res/example.png",
+                interactive=False,
+                type="filepath",
+                label="This is an example screen. The service is not fully operational yet due to DNS issues. Please wait a moment.",
+            )
+
+    with gr.Tab("Coming Soon"):
+        with gr.Row():
+            gr_df = gr.Dataframe(
+                value=ptbxl_df,
+                interactive=False,
+                max_height=200,
+                label="All PTB-XL v1.3.0 data (https://physionet.org/content/ptb-xl/1.0.3/ptbxl_database.csv). You can refer to the following URL(https://physionet.org/content/ptb-xl/1.0.3/scp_statements.csv) to understand what 'scp_codes' represent.",
+            )
+
+        with gr.Row():
+            ecg_id_output = gr.Textbox(label="The selected ecg_id is")
+
+        with gr.Row():
+            ecg_viewer = gr.Image(interactive=False, label="The selected ecg is")
+
+        with gr.Row():
+            alfred_result = gr.JSON(value={}, label="Alfred said that")
+
+        gr_df.select(fn=get_ecg_id_from_dataframe, inputs=gr_df, outputs=ecg_id_output)
+        ecg_id_output.change(
+            fn=get_ecg_image_from_dataframe, inputs=ecg_id_output, outputs=ecg_viewer
+        )
+        ecg_id_output.change(
+            fn=get_alfred_from_dataframe, inputs=ecg_id_output, outputs=alfred_result
+        )
+
+demo.launch()

requirements.txt

@@ -1 +1,3 @@
-huggingface_hub==0.25.2
+huggingface_hub==0.25.2
+gradio==5.8.0
+matplotlib==3.9.3