passing everything to vectara

app.py

@@ -257,10 +257,18 @@ def process_summary_with_openai(summary):
         return str(e)
         
 
-def process_and_query(text=None):
+def process_and_query(input_language=None,audio_input=None,image_input=None,text_input=None):
     try:
-        # augment the prompt before feeding it to vectara
-        text = "the user asks the following to his health adviser " + text
+        if text is not None :
+            # augment the prompt before feeding it to vectara
+            text = "the user asks the following to his health adviser " + text
+        # process audio
+        if audio_input is not None :
+            text += "\n"+process_speech(input_language,audio_input)
+        # process image
+        if image_input is not None :
+            text += "\n"+process_image(image_input)
+        
         
         # Use the text to query Vectara
         vectara_response_json = query_vectara(text)
@@ -411,20 +419,20 @@ with gr.Blocks(theme='ParityError/Anime') as iface :
         input_language = gr.Dropdown(languages, label="select the language",value="English",interactive=True)
         audio_input = gr.Audio(label="speak",type="filepath",sources="microphone")
         audio_output = gr.Markdown(label="output text")
-        audio_button = gr.Button("process audio")
-        audio_button.click(process_speech, inputs=[input_language,audio_input], outputs=audio_output)
+        # audio_button = gr.Button("process audio")
+        # audio_button.click(process_speech, inputs=[input_language,audio_input], outputs=audio_output)
         gr.Examples([["English","sample_input.mp3"]],inputs=[input_language,audio_input])
     with gr.Accordion("image identification",open=True):
         image_input = gr.Image(label="upload image")
         image_output = gr.Markdown(label="output text")
-        image_button = gr.Button("process image")
-        image_button.click(process_image, inputs=image_input, outputs=image_output)
+        # image_button = gr.Button("process image")
+        # image_button.click(process_image, inputs=image_input, outputs=image_output)
         gr.Examples(["sick person.jpeg"],inputs=[image_input])
     with gr.Accordion("text summarization",open=True):
         text_input = gr.Textbox(label="input text",lines=5)
         text_output = gr.Markdown(label="output text")
         text_button = gr.Button("process text")
-        text_button.click(process_and_query, inputs=text_input, outputs=text_output)
+        text_button.click(process_and_query, inputs=[input_language,audio_input,image_input,text_input], outputs=text_output)
         gr.Examples([
             ["What is the proper treatment for buccal herpes?"],
             ["Male, 40 presenting with swollen glands and a rash"],