Update app.py

app.py

@@ -446,222 +446,223 @@ elif Usage == 'Random Questions':
     6. Current Affairs and News.
     7. Create or compose tweets or Linkedin posts or email.''')
     
-    Input_type = st.radio(
-        "**Input type:**",
-        ('TEXT', 'SPEECH')
-        )
-    
-    if Input_type == 'TEXT':
-        #page_bg_img2 = """
-        #<style>
-        #[data-testid="stAppViewContainer"] {
-        #background-color: #e5e5f7;
-        #opacity: 0.8;
-        #background-size: 20px 20px;
-        #background-image:  repeating-linear-gradient(0deg, #32d947, #32d947 1px, #e5e5f7 1px, #e5e5f7);
-        #}
-        #</style>
-        #"""
-        #st.markdown(page_bg_img, unsafe_allow_html=True)
-        st.write('**You are now in Text input mode**')
-        mytext = st.text_input('**Go on! Ask me anything:**')
-        if st.button("SUBMIT"):
-            question=mytext
-            response = openai.Completion.create(
-              model="text-davinci-003",
-              prompt=f'''Your name is alexa and  knowledge cutoff date is 2021-09, and it is not aware of any events after that time. if the  
-                        Answer to following questions is not  from your knowledge base or in case of queries like weather 
-                          updates / stock updates / current news Etc which requires you to have internet connection  then print i don't have access to internet to answer your question, 
-                          if  question is related to  image or  painting or drawing generation then print ipython type output   function gen_draw("detailed prompt of image to be generated")
-                          if the question is related to playing a song or video or music of a singer then print ipython type output  function vid_tube("relevent search query")
-                          if the question is related to operating home appliances then print ipython type output function home_app(" action(ON/Off),appliance(TV,Geaser,Fridge,Lights,fans,AC)") . 
-                          if question is realted to sending mail or sms then print ipython type output function messenger_app(" message of us ,messenger(email,sms)")
-                          \nQuestion-{question}
-                          \nAnswer -''',
-              temperature=0.49,
-              max_tokens=256,
-              top_p=1,
-              frequency_penalty=0,
-              presence_penalty=0
-            )
-            string_temp=response.choices[0].text
+    # Input_type = st.radio(
+    #     "**Input type:**",
+    #     ('TEXT', 'SPEECH')
+    #     )
     
-            if ("gen_draw" in string_temp):
+    # if Input_type == 'TEXT':
+    #page_bg_img2 = """
+    #<style>
+    #[data-testid="stAppViewContainer"] {
+    #background-color: #e5e5f7;
+    #opacity: 0.8;
+    #background-size: 20px 20px;
+    #background-image:  repeating-linear-gradient(0deg, #32d947, #32d947 1px, #e5e5f7 1px, #e5e5f7);
+    #}
+    #</style>
+    #"""
+    #st.markdown(page_bg_img, unsafe_allow_html=True)
+    st.write('**You are now in Text input mode**')
+    mytext = st.text_input('**Go on! Ask me anything:**')
+    if st.button("SUBMIT"):
+        question=mytext
+        response = openai.Completion.create(
+          model="text-davinci-003",
+          prompt=f'''Your name is HyperBot and  knowledge cutoff date is 2021-09, and you are not aware of any events after that time. if the  
+                    Answer to following questions is not from your knowledge base or in case of queries like weather 
+                      updates / stock updates / current news or people which requires you to have internet connection  then print i don't have access to internet to answer your question, 
+                      if  question is related to  image or  painting or drawing generation then print ipython type output function gen_draw("detailed prompt of image to be generated")
+                      if the question is related to playing a song or video or music of a singer then print ipython type output  function vid_tube("relevent search query")
+                      if the question is related to operating home appliances then print ipython type output function home_app(" action(ON/Off),appliance(TV,Geaser,Fridge,Lights,fans,AC)") . 
+                      if question is realted to sending mail or sms then print ipython type output function messenger_app(" message of us ,messenger(email,sms)")
+                      \nQuestion-{question}
+                      \nAnswer -''',
+          temperature=0.49,
+          max_tokens=256,
+          top_p=1,
+          frequency_penalty=0,
+          presence_penalty=0
+        )
+        string_temp=response.choices[0].text
+
+        if ("gen_draw" in string_temp):
+            try:
                 try:
-                    try:
-                        wget.download(openai_response(prompt))
-                        img2 = Image.open(wget.download(openai_response(prompt)))
-                        img2.show()
-                        rx = 'Image returned'
-                        g_sheet_log(mytext, rx)
-                    except:
-                        urllib.request.urlretrieve(openai_response(prompt),"img_ret.png")
-                        img = Image.open("img_ret.png")
-                        img.show()
-                        rx = 'Image returned'
-                        g_sheet_log(mytext, rx)
+                    wget.download(openai_response(prompt))
+                    img2 = Image.open(wget.download(openai_response(prompt)))
+                    img2.show()
+                    rx = 'Image returned'
+                    g_sheet_log(mytext, rx)
                 except:
-                    # Set up our initial generation parameters.
-                    answers = stability_api.generate(
-                    prompt = mytext,
-                    seed=992446758, # If a seed is provided, the resulting generated image will be deterministic.
-                            # What this means is that as long as all generation parameters remain the same, you can always recall the same image simply by generating it again.
-                            # Note: This isn't quite the case for Clip Guided generations, which we'll tackle in a future example notebook.
-                    steps=30, # Amount of inference steps performed on image generation. Defaults to 30.
-                    cfg_scale=8.0, # Influences how strongly your generation is guided to match your prompt.
-                        # Setting this value higher increases the strength in which it tries to match your prompt.
-                        # Defaults to 7.0 if not specified.
-                    width=512, # Generation width, defaults to 512 if not included.
-                    height=512, # Generation height, defaults to 512 if not included.
-                    samples=1, # Number of images to generate, defaults to 1 if not included.
-                    sampler=generation.SAMPLER_K_DPMPP_2M # Choose which sampler we want to denoise our generation with.
-                                                        # Defaults to k_dpmpp_2m if not specified. Clip Guidance only supports ancestral samplers.
-                                                        # (Available Samplers: ddim, plms, k_euler, k_euler_ancestral, k_heun, k_dpm_2, k_dpm_2_ancestral, k_dpmpp_2s_ancestral, k_lms, k_dpmpp_2m)
-                    )
-    
-                    # Set up our warning to print to the console if the adult content classifier is tripped.
-                    # If adult content classifier is not tripped, save generated images.
-                    for resp in answers:
-                        for artifact in resp.artifacts:
-                            if artifact.finish_reason == generation.FILTER:
-                                warnings.warn(
-                                    "Your request activated the API's safety filters and could not be processed."
-                                    "Please modify the prompt and try again.")
-                            if artifact.type == generation.ARTIFACT_IMAGE:
-                                img = Image.open(io.BytesIO(artifact.binary))
-                                st.image(img)
-                                img.save(str(artifact.seed)+ ".png") # Save our generated images with their seed number as the filename.
-                                rx = 'Image returned'
-                                g_sheet_log(mytext, rx)
-                                
-                # except:        
-                #     st.write('image is being generated please wait...')
-                #     def extract_image_description(input_string):
-                #         return input_string.split('gen_draw("')[1].split('")')[0]
-                #     prompt=extract_image_description(string_temp)
-                #     # model_id = "CompVis/stable-diffusion-v1-4"
-                #     model_id='runwayml/stable-diffusion-v1-5'
-                #     device = "cuda"
-    
-    
-                #     pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
-                #     pipe = pipe.to(device)
-    
-                #     # prompt = "a photo of an astronaut riding a horse on mars"
-                #     image = pipe(prompt).images[0]  
-                    
-                #     image.save("astronaut_rides_horse.png")
-                #     st.image(image)
-                #     # image
-    
-            elif ("vid_tube" in string_temp):
-                s = Search(mytext)
-                search_res = s.results
-                first_vid = search_res[0]
-                print(first_vid)
-                string = str(first_vid)
-                video_id = string[string.index('=') + 1:-1]
-                # print(video_id)
-                YoutubeURL = "https://www.youtube.com/watch?v="
-                OurURL = YoutubeURL + video_id
-                st.write(OurURL)
-                st_player(OurURL)
-                ry = 'Youtube link and video returned'
-                g_sheet_log(mytext, ry)
-    
-            elif ("don't" in string_temp or "internet" in string_temp):
-                st.write('searching internet ')
-                search_internet(question)
-                rz = 'Internet result returned'
-                g_sheet_log(mytext, rz)
-    
-            else:
-                st.write(string_temp)
-                g_sheet_log(mytext, string_temp)
-        
-    elif Input_type == 'SPEECH':
-        stt_button = Button(label="Speak", width=100)
-        stt_button.js_on_event("button_click", CustomJS(code="""
-            var recognition = new webkitSpeechRecognition();
-            recognition.continuous = true;
-            recognition.interimResults = true;
-            recognition.onresult = function (e) {
-                var value = "";
-                for (var i = e.resultIndex; i < e.results.length; ++i) {
-                    if (e.results[i].isFinal) {
-                        value += e.results[i][0].transcript;
-                    }
-                }
-                if ( value != "") {
-                    document.dispatchEvent(new CustomEvent("GET_TEXT", {detail: value}));
-                }
-            }
-            recognition.start();
-            """))
+                    urllib.request.urlretrieve(openai_response(prompt),"img_ret.png")
+                    img = Image.open("img_ret.png")
+                    img.show()
+                    rx = 'Image returned'
+                    g_sheet_log(mytext, rx)
+            except:
+                # Set up our initial generation parameters.
+                answers = stability_api.generate(
+                prompt = mytext,
+                seed=992446758, # If a seed is provided, the resulting generated image will be deterministic.
+                        # What this means is that as long as all generation parameters remain the same, you can always recall the same image simply by generating it again.
+                        # Note: This isn't quite the case for Clip Guided generations, which we'll tackle in a future example notebook.
+                steps=30, # Amount of inference steps performed on image generation. Defaults to 30.
+                cfg_scale=8.0, # Influences how strongly your generation is guided to match your prompt.
+                    # Setting this value higher increases the strength in which it tries to match your prompt.
+                    # Defaults to 7.0 if not specified.
+                width=512, # Generation width, defaults to 512 if not included.
+                height=512, # Generation height, defaults to 512 if not included.
+                samples=1, # Number of images to generate, defaults to 1 if not included.
+                sampler=generation.SAMPLER_K_DPMPP_2M # Choose which sampler we want to denoise our generation with.
+                                                    # Defaults to k_dpmpp_2m if not specified. Clip Guidance only supports ancestral samplers.
+                                                    # (Available Samplers: ddim, plms, k_euler, k_euler_ancestral, k_heun, k_dpm_2, k_dpm_2_ancestral, k_dpmpp_2s_ancestral, k_lms, k_dpmpp_2m)
+                )
+
+                # Set up our warning to print to the console if the adult content classifier is tripped.
+                # If adult content classifier is not tripped, save generated images.
+                for resp in answers:
+                    for artifact in resp.artifacts:
+                        if artifact.finish_reason == generation.FILTER:
+                            warnings.warn(
+                                "Your request activated the API's safety filters and could not be processed."
+                                "Please modify the prompt and try again.")
+                        if artifact.type == generation.ARTIFACT_IMAGE:
+                            img = Image.open(io.BytesIO(artifact.binary))
+                            st.image(img)
+                            img.save(str(artifact.seed)+ ".png") # Save our generated images with their seed number as the filename.
+                            rx = 'Image returned'
+                            g_sheet_log(mytext, rx)
+                            
+            # except:        
+            #     st.write('image is being generated please wait...')
+            #     def extract_image_description(input_string):
+            #         return input_string.split('gen_draw("')[1].split('")')[0]
+            #     prompt=extract_image_description(string_temp)
+            #     # model_id = "CompVis/stable-diffusion-v1-4"
+            #     model_id='runwayml/stable-diffusion-v1-5'
+            #     device = "cuda"
+
+
+            #     pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+            #     pipe = pipe.to(device)
+
+            #     # prompt = "a photo of an astronaut riding a horse on mars"
+            #     image = pipe(prompt).images[0]  
+                
+            #     image.save("astronaut_rides_horse.png")
+            #     st.image(image)
+            #     # image
+
+        elif ("vid_tube" in string_temp):
+            s = Search(mytext)
+            search_res = s.results
+            first_vid = search_res[0]
+            print(first_vid)
+            string = str(first_vid)
+            video_id = string[string.index('=') + 1:-1]
+            # print(video_id)
+            YoutubeURL = "https://www.youtube.com/watch?v="
+            OurURL = YoutubeURL + video_id
+            st.write(OurURL)
+            st_player(OurURL)
+            ry = 'Youtube link and video returned'
+            g_sheet_log(mytext, ry)
+
+        elif ("don't" in string_temp or "internet" in string_temp):
+            st.write('searching internet ')
+            search_internet(question)
+            rz = 'Internet result returned'
+            g_sheet_log(mytext, string_temp)
+
+        else:
+            st.write(string_temp)
+            g_sheet_log(mytext, string_temp)
+else:
+    pass
+    # elif Input_type == 'SPEECH':
+    #     stt_button = Button(label="Speak", width=100)
+    #     stt_button.js_on_event("button_click", CustomJS(code="""
+    #         var recognition = new webkitSpeechRecognition();
+    #         recognition.continuous = true;
+    #         recognition.interimResults = true;
+    #         recognition.onresult = function (e) {
+    #             var value = "";
+    #             for (var i = e.resultIndex; i < e.results.length; ++i) {
+    #                 if (e.results[i].isFinal) {
+    #                     value += e.results[i][0].transcript;
+    #                 }
+    #             }
+    #             if ( value != "") {
+    #                 document.dispatchEvent(new CustomEvent("GET_TEXT", {detail: value}));
+    #             }
+    #         }
+    #         recognition.start();
+    #         """))
         
-        result = streamlit_bokeh_events(
-        stt_button,
-        events="GET_TEXT",
-        key="listen",
-        refresh_on_update=False,
-        override_height=75,
-        debounce_time=0)
+    #     result = streamlit_bokeh_events(
+    #     stt_button,
+    #     events="GET_TEXT",
+    #     key="listen",
+    #     refresh_on_update=False,
+    #     override_height=75,
+    #     debounce_time=0)
     
-        if result:
-            if "GET_TEXT" in result:
-                st.write(result.get("GET_TEXT"))
-                question = result.get("GET_TEXT")
-                response = openai.Completion.create(
-                model="text-davinci-003",
-                prompt=f'''Your knowledge cutoff is 2021-09, and it is not aware of any events after that time. if the  
-                          Answer to following questions is not  from your knowledge base or in case of queries like weather 
-                            updates / stock updates / current news Etc which requires you to have internet connection  then print i don't have access to internet to answer your question, 
-                            if  question is related to  image or  painting or drawing generation then print ipython type output   function gen_draw("detailed prompt of image to be generated")
-                            if the question is related to playing a song or video or music of a singer then print ipython type output  function vid_tube("relevent search query")
-                            \nQuestion-{question}
-                            \nAnswer -''',
-                temperature=0.49,
-                max_tokens=256,
-                top_p=1,
-                frequency_penalty=0,
-                presence_penalty=0
-                )
-                string_temp=response.choices[0].text
+    #     if result:
+    #         if "GET_TEXT" in result:
+    #             st.write(result.get("GET_TEXT"))
+    #             question = result.get("GET_TEXT")
+    #             response = openai.Completion.create(
+    #             model="text-davinci-003",
+    #             prompt=f'''Your knowledge cutoff is 2021-09, and it is not aware of any events after that time. if the  
+    #                       Answer to following questions is not  from your knowledge base or in case of queries like weather 
+    #                         updates / stock updates / current news Etc which requires you to have internet connection  then print i don't have access to internet to answer your question, 
+    #                         if  question is related to  image or  painting or drawing generation then print ipython type output   function gen_draw("detailed prompt of image to be generated")
+    #                         if the question is related to playing a song or video or music of a singer then print ipython type output  function vid_tube("relevent search query")
+    #                         \nQuestion-{question}
+    #                         \nAnswer -''',
+    #             temperature=0.49,
+    #             max_tokens=256,
+    #             top_p=1,
+    #             frequency_penalty=0,
+    #             presence_penalty=0
+    #             )
+    #             string_temp=response.choices[0].text
     
-                if ("gen_draw" in string_temp):
-                    st.write('*image is being generated please wait..* ')
-                    def extract_image_description(input_string):
-                        return input_string.split('gen_draw("')[1].split('")')[0]
-                    prompt=extract_image_description(string_temp)
-                    # model_id = "CompVis/stable-diffusion-v1-4"
-                    model_id='runwayml/stable-diffusion-v1-5'
-                    device = "cuda"
+    #             if ("gen_draw" in string_temp):
+    #                 st.write('*image is being generated please wait..* ')
+    #                 def extract_image_description(input_string):
+    #                     return input_string.split('gen_draw("')[1].split('")')[0]
+    #                 prompt=extract_image_description(string_temp)
+    #                 # model_id = "CompVis/stable-diffusion-v1-4"
+    #                 model_id='runwayml/stable-diffusion-v1-5'
+    #                 device = "cuda"
     
-                    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
-                    pipe = pipe.to(device)
+    #                 pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+    #                 pipe = pipe.to(device)
     
-                    # prompt = "a photo of an astronaut riding a horse on mars"
-                    image = pipe(prompt).images[0]  
+    #                 # prompt = "a photo of an astronaut riding a horse on mars"
+    #                 image = pipe(prompt).images[0]  
                       
-                    image.save("astronaut_rides_horse.png")
-                    st.image(image)
-                    # image 
+    #                 image.save("astronaut_rides_horse.png")
+    #                 st.image(image)
+    #                 # image 
                 
-                elif ("vid_tube" in string_temp):
-                    s = Search(question)
-                    search_res = s.results
-                    first_vid = search_res[0]
-                    print(first_vid)
-                    string = str(first_vid)
-                    video_id = string[string.index('=') + 1:-1]
-                    # print(video_id)
-                    YoutubeURL = "https://www.youtube.com/watch?v="
-                    OurURL = YoutubeURL + video_id
-                    st.write(OurURL)
-                    st_player(OurURL)
+    #             elif ("vid_tube" in string_temp):
+    #                 s = Search(question)
+    #                 search_res = s.results
+    #                 first_vid = search_res[0]
+    #                 print(first_vid)
+    #                 string = str(first_vid)
+    #                 video_id = string[string.index('=') + 1:-1]
+    #                 # print(video_id)
+    #                 YoutubeURL = "https://www.youtube.com/watch?v="
+    #                 OurURL = YoutubeURL + video_id
+    #                 st.write(OurURL)
+    #                 st_player(OurURL)
     
-                elif ("don't" in string_temp or "internet" in string_temp  ):
-                    st.write('*searching internet*')
-                    search_internet(question)
-                else:
-                    st.write(string_temp)
+    #             elif ("don't" in string_temp or "internet" in string_temp  ):
+    #                 st.write('*searching internet*')
+    #                 search_internet(question)
+    #             else:
+    #                 st.write(string_temp)