Pyvis attempt

app.py

@@ -1,9 +1,21 @@
 import gradio as gr
 import json
+from pyvis.network import Network
+
 from transformers import pipeline
 # Load the pipeline
 tourModel = pipeline(model="manhan/GPT-Tour")
 
+def vizTour(activityList):
+    net = Network(directed=True)
+    net.add_node(activityList[0])
+    for activity in activityList[1:]:
+        if activity not in net.get_nodes():
+            net.add_node(activity)
+        net.add_edge(activityList[0], activity)
+    net.show('tour.html')
+    return True
+
 def getTour(income,size,years,sex,edu,wrk): 
     # person = a dict with person-level and hh-level attributes:
     person = {}
@@ -68,7 +80,8 @@ def getTour(income,size,years,sex,edu,wrk):
                 print(e)
         else:
             print("Nothing extracted!")
-    return activity_list
+    success = vizTour(activity_list)
+    return activity_list, success
 
 with gr.Interface(fn=getTour, inputs=[
     gr.inputs.Textbox(label="Annual Household Income (in dollars)"),
@@ -76,6 +89,7 @@ with gr.Interface(fn=getTour, inputs=[
     gr.inputs.Textbox(label="Traveler Age (years)"),
     gr.inputs.Dropdown(["unknown", "male", "female"], label="Gender/sex"),
     gr.inputs.Dropdown(["unknown", "grade school","highschool", "associates", "bachelors", "graduate"], label="Educational attainment level"),
-    gr.inputs.Dropdown(["unknown", "yes","no"], label="Worker status")
-], outputs="json", title="GPT-Tour", description="Generate a tour for a person", allow_flagging=False, allow_screenshot=False, allow_embedding=False) as iface:
+    gr.inputs.Dropdown(["unknown", "yes","no"], label="Worker status")], 
+    outputs=["json",
+            gr.HTML(value=open('tour.html'))], title="GPT-Tour", description="Generate a tour for a person", allow_flagging=False, allow_screenshot=False, allow_embedding=False) as iface:
     iface.launch()

requirements.txt

@@ -1,2 +1,3 @@
 torch
-transformers
+transformers
+pyviz