Update app.py

app.py

@@ -39,7 +39,7 @@ def gpt3_short(question,vqa_answer,caption):
     prompt="prompt: This is a picture of Caption: "+caption+". Question: "+question+" VQA model predicts:"+"A: "+vqa_answer[0]+"socre:"+str(vqa_score[0])+\
            " B: "+vqa_answer[1]+" score:"+str(vqa_score[1])+" C: "+vqa_answer[2]+" score:"+str(vqa_score[2])+\
             " D: "+vqa_answer[3]+'score:'+str(vqa_score[3])+\
-           ". Choose A if it is not in conflict with the description of the picture and A's score is bigger than 0.8; otherwise choose the B, C or D based on the description."
+           ". Choose A if it is not in conflict with the description of the picture and A's score is bigger than 0.8; otherwise choose the B, C or D based on the description. Answer with A or B or C or D."
     
     # prompt=caption+"\n"+question+"\n"+vqa_answer+"\n Tell me the right answer."
     response = openai.Completion.create(
@@ -184,11 +184,11 @@ with gr.Blocks(
                         [gpt3_output_v1],
                     )
         '''
-    examples=[['bird.jpeg',"How many birds are there in the tree?","There are two birds in the tree.","2","2"],
-              ['qa9.jpg',"What type of vehicle is being pulled by the horses ?",'The vehicle being pulled by the horses is likely a sleigh.','carriage','Sled'],
-                ['upload4.jpg',"What is this old man doing?","The old man is fishing.","fishing","Fishing"]]
+    examples=[['bird.jpeg',"How many birds are there in the tree?","2","2","2"],
+              ['qa9.jpg',"What type of vehicle is being pulled by the horses ?",'carriage','carriage','Sled'],
+                ['upload4.jpg',"What is this old man doing?","fishing.","fishing","Fishing"]]
     examples = gr.Examples(
-       examples=examples,inputs=[image_input, chat_input,caption_output_v1,caption_output,gpt3_output_v1],
+       examples=examples,inputs=[image_input, chat_input,caption_output,caption_output_v1,gpt3_output_v1],
     )
 
 iface.queue(concurrency_count=1, api_open=False, max_size=10)