Update app.py

app.py

@@ -493,100 +493,177 @@ elif Usage == 'Random Questions':
         ('TEXT', 'SPEECH')
         )
     
-        if Input_type == 'TEXT':
-            st.write('**You are now in Text input mode**')
-            mytext = st.text_input('**Go on! Ask me anything:**')
-            if st.button("SUBMIT"):
-                question=mytext
+    if Input_type == 'TEXT':
+        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:
+                        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)
+                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)
+
+    elif Input_type == 'SPEECH':
+        try:
+            st.text("Record your audio, **max length - 5 seconds**")
+            if st.button("Record"):
+                st.write("Recording...")
+                audio_file = record_audio()
+                st.write("Recording complete.")
+                file = open(audio_file, "rb")
+            
+                # Play the recorded audio
+                st.audio(audio_file)
+            
+                transcription = openai.Audio.transcribe("whisper-1", file)
+                result = transcription["text"]
+                st.write(f"Fetched from audio - {result}")
+                question = result
                 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
+                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):
-                    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)
-                    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
-        
+                    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)
+                    s = Search(question)
                     search_res = s.results
                     first_vid = search_res[0]
                     print(first_vid)
@@ -597,35 +674,45 @@ elif Usage == 'Random Questions':
                     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 ')
+    
+                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)
-
-        elif Input_type == 'SPEECH':
-            try:
-                st.text("Record your audio, **max length - 5 seconds**")
-                if st.button("Record"):
-                    st.write("Recording...")
-                    audio_file = record_audio()
-                    st.write("Recording complete.")
-                    file = open(audio_file, "rb")
-                
-                    # Play the recorded audio
-                    st.audio(audio_file)
                 
-                    transcription = openai.Audio.transcribe("whisper-1", file)
-                    result = transcription["text"]
-                    st.write(f"Fetched from audio - {result}")
-                    question = result
+        except:
+            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)
+        
+            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  
@@ -680,92 +767,5 @@ elif Usage == 'Random Questions':
                         search_internet(question)
                     else:
                         st.write(string_temp)
-                    
-            except:
-                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)
-            
-                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"
-            
-                            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(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)
 else:
     pass