simple_test

app.py

@@ -2,7 +2,7 @@
 #import os
 #from llama_index.node_parser import SimpleNodeParser
 #from llama_index import StorageContext, load_index_from_storage
-import gradio as gr
+# import gradio as gr
 #import openai
 
 # os.environ['OPENAI_API_KEY'] = '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'
@@ -26,24 +26,30 @@ import gradio as gr
 #     return final_response
 
 
-def get_model_reply_no_prev_context(question):
-    final_response = question
-    return final_response
+# def get_model_reply_no_prev_context(question):
+#     final_response = question
+#     return final_response
+
+# title = "Knowledge Center at Penta Building Group"
+# description = """
+# The program is trained to answer questions based on the documentation of 'Lessons Learned' from previous projects!
+
+# """
 
-title = "Knowledge Center at Penta Building Group"
-description = """
-The program is trained to answer questions based on the documentation of 'Lessons Learned' from previous projects!
+# article = "Your feedback matters!If you like it, contact me at mgupta70@asu.edu"
 
-"""
+# gr.Interface(
+#     fn=get_model_reply_no_prev_context,
+#     inputs="textbox",
+#     outputs="text",
+#     title=title,
+#     description=description,
+#     article=article,
+#     examples=[["Which code is to be used while planning a pedestrian walkway?"], ["What is AHJ?"]], live=True
+# ).launch()
 
-article = "Your feedback matters!If you like it, contact me at mgupta70@asu.edu"
+import gradio as gr
+def sketch_recognition(img):
+    pass# Implement your sketch recognition model here...
 
-gr.Interface(
-    fn=get_model_reply_no_prev_context,
-    inputs="textbox",
-    outputs="text",
-    title=title,
-    description=description,
-    article=article,
-    examples=[["Which code is to be used while planning a pedestrian walkway?"], ["What is AHJ?"]], live=True
-).launch(share = True)
+gr.Interface(fn=sketch_recognition, inputs="sketchpad", outputs="label").launch()