GraphicAINovel

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awacke1 commited on Mar 7, 2024

Commit

c7521e9

verified ·

1 Parent(s): 05f994e

Update app.py

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Files changed (1) hide show

app.py +11 -105

app.py CHANGED Viewed

@@ -167,6 +167,7 @@ roleplaying_glossary = {
 # HTML5 based Speech Synthesis (Text to Speech in Browser)
 def SpeechSynthesis(result):
     documentHTML5='''
     <!DOCTYPE html>
@@ -316,6 +317,7 @@ FileSidebar()
 # ---- Art Card Sidebar with Random Selection of image:
 def get_image_as_base64(url):
     response = requests.get(url)
     if response.status_code == 200:
@@ -324,6 +326,7 @@ def get_image_as_base64(url):
     else:
         return None
 def create_download_link(filename, base64_str):
     href = f'<a href="data:file/png;base64,{base64_str}" download="{filename}">Download Image</a>'
     return href
@@ -502,6 +505,7 @@ topic_emojis = {
 }
 # Adjusted display_buttons_with_scores function
 def display_buttons_with_scores():
     for category, games in roleplaying_glossary.items():
         category_emoji = topic_emojis.get(category, "🔍")  # Default to search icon if no match
@@ -546,6 +550,7 @@ def create_search_url_ai(keyword):
     base_url = "https://huggingface.co/spaces/awacke1/GraphicAINovel?q="
     return base_url + keyword.replace(' ', '+')
 def display_videos_and_links():
     video_files = [f for f in os.listdir('.') if f.endswith('.mp4')]
     if not video_files:
@@ -595,7 +600,7 @@ def display_videos_and_links():
             #st.markdown(links_md)
             #col_index += 1
 def display_images_and_wikipedia_summaries():
     image_files = [f for f in os.listdir('.') if f.endswith('.png')]
     if not image_files:
@@ -656,6 +661,7 @@ def clear_query_params():
 # Function to display content or image based on a query
 def display_content_or_image(query):
     # Check if the query matches any glossary term
     for category, terms in transhuman_glossary.items():
@@ -677,63 +683,6 @@ def display_content_or_image(query):
     return False
-# ------------------------------------
-def add_Med_Licensing_Exam_Dataset():
-    import streamlit as st
-    from datasets import load_dataset
-    dataset = load_dataset("augtoma/usmle_step_1")['test']  # Using 'test' split
-    st.title("USMLE Step 1 Dataset Viewer")
-    if len(dataset) == 0:
-        st.write("😢 The dataset is empty.")
-    else:
-        st.write("""
-        🔍 Use the search box to filter questions or use the grid to scroll through the dataset.
-        """)
-        # 👩‍🔬 Search Box
-        search_term = st.text_input("Search for a specific question:", "")
-        # 🎛 Pagination
-        records_per_page = 100
-        num_records = len(dataset)
-        num_pages = max(int(num_records / records_per_page), 1)
-        # Skip generating the slider if num_pages is 1 (i.e., all records fit in one page)
-        if num_pages > 1:
-            page_number = st.select_slider("Select page:", options=list(range(1, num_pages + 1)))
-        else:
-            page_number = 1  # Only one page
-        # 📊 Display Data
-        start_idx = (page_number - 1) * records_per_page
-        end_idx = start_idx + records_per_page
-        # 🧪 Apply the Search Filter
-        filtered_data = []
-        for record in dataset[start_idx:end_idx]:
-            if isinstance(record, dict) and 'text' in record and 'id' in record:
-                if search_term:
-                    if search_term.lower() in record['text'].lower():
-                        st.markdown(record)
-                        filtered_data.append(record)
-                else:
-                    filtered_data.append(record)
-        # 🌐 Render the Grid
-        for record in filtered_data:
-            st.write(f"## Question ID: {record['id']}")
-            st.write(f"### Question:")
-            st.write(f"{record['text']}")
-            st.write(f"### Answer:")
-            st.write(f"{record['answer']}")
-            st.write("---")
-        st.write(f"😊 Total Records: {num_records} | 📄 Displaying {start_idx+1} to {min(end_idx, num_records)}")
 # 1. Constants and Top Level UI Variables
 # My Inference API Copy
@@ -752,52 +701,6 @@ key = os.getenv('OPENAI_API_KEY')
 prompt = f"Write instructions to teach discharge planning along with guidelines and patient education. List entities, features and relationships to CCDA and FHIR objects in boldface."
 should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.")
-# 2. Prompt label button demo for LLM
-def add_witty_humor_buttons():
-    with st.expander("Wit and Humor 🤣", expanded=True):
-        # Tip about the Dromedary family
-        st.markdown("🔬 **Fun Fact**: Dromedaries, part of the camel family, have a single hump and are adapted to arid environments. Their 'superpowers' include the ability to survive without water for up to 7 days, thanks to their specialized blood cells and water storage in their hump.")
-        # Define button descriptions
-        descriptions = {
-            "Generate Limericks 😂": "Write ten random adult limericks based on quotes that are tweet length and make you laugh 🎭",
-            "Wise Quotes 🧙": "Generate ten wise quotes that are tweet length 🦉",
-            "Funny Rhymes 🎤": "Create ten funny rhymes that are tweet length 🎶",
-            "Medical Jokes 💉": "Create ten medical jokes that are tweet length 🏥",
-            "Minnesota Humor ❄️": "Create ten jokes about Minnesota that are tweet length 🌨️",
-            "Top Funny Stories 📖": "Create ten funny stories that are tweet length 📚",
-            "More Funny Rhymes 🎙️": "Create ten more funny rhymes that are tweet length 🎵"
-        }
-        # Create columns
-        col1, col2, col3 = st.columns([1, 1, 1], gap="small")
-        # Add buttons to columns
-        if col1.button("Wise Limericks 😂"):
-            StreamLLMChatResponse(descriptions["Generate Limericks 😂"])
-        if col2.button("Wise Quotes 🧙"):
-            StreamLLMChatResponse(descriptions["Wise Quotes 🧙"])
-        #if col3.button("Funny Rhymes 🎤"):
-        #    StreamLLMChatResponse(descriptions["Funny Rhymes 🎤"])
-        col4, col5, col6 = st.columns([1, 1, 1], gap="small")
-        if col4.button("Top Ten Funniest Clean Jokes 💉"):
-            StreamLLMChatResponse(descriptions["Top Ten Funniest Clean Jokes  💉"])
-        if col5.button("Minnesota Humor ❄️"):
-            StreamLLMChatResponse(descriptions["Minnesota Humor ❄️"])
-        if col6.button("Origins of Medical Science True Stories"):
-            StreamLLMChatResponse(descriptions["Origins of Medical Science True Stories"])
-        col7 = st.columns(1, gap="small")
-        if col7[0].button("Top Ten Best Write a streamlit python program prompts to build AI programs. 🎙️"):
-            StreamLLMChatResponse(descriptions["Top Ten Best Write a streamlit python program prompts to build AI programs. 🎙️"])
 # 3. Stream Llama Response
@@ -844,10 +747,13 @@ def StreamLLMChatResponse(prompt):
         st.write('Llama model is asleep. Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
 # 4. Run query with payload
 def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
     st.markdown(response.json())
     return response.json()
 def get_output(prompt):
     return query({"inputs": prompt})
@@ -857,7 +763,6 @@ def generate_filename(prompt, file_type):
     safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
     replaced_prompt = prompt.replace(" ", "_").replace("\n", "_")
     safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:255]  # 255 is linux max, 260 is windows max
-    #safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:45]
     return f"{safe_date_time}_{safe_prompt}.{file_type}"
 # 6. Speech transcription via OpenAI service
@@ -897,6 +802,7 @@ def save_and_play_audio(audio_recorder):
     return None
 # 8. File creator that interprets type and creates output file for text, markdown and code
 def create_file(filename, prompt, response, should_save=True):
     if not should_save:
         return

 # HTML5 based Speech Synthesis (Text to Speech in Browser)
+@st.cache_resource
 def SpeechSynthesis(result):
     documentHTML5='''
     <!DOCTYPE html>
 # ---- Art Card Sidebar with Random Selection of image:
+@st.cache_resource
 def get_image_as_base64(url):
     response = requests.get(url)
     if response.status_code == 200:
     else:
         return None
+@st.cache_resource
 def create_download_link(filename, base64_str):
     href = f'<a href="data:file/png;base64,{base64_str}" download="{filename}">Download Image</a>'
     return href
 }
 # Adjusted display_buttons_with_scores function
+@st.cache_resource
 def display_buttons_with_scores():
     for category, games in roleplaying_glossary.items():
         category_emoji = topic_emojis.get(category, "🔍")  # Default to search icon if no match
     base_url = "https://huggingface.co/spaces/awacke1/GraphicAINovel?q="
     return base_url + keyword.replace(' ', '+')
+@st.cache_resource
 def display_videos_and_links():
     video_files = [f for f in os.listdir('.') if f.endswith('.mp4')]
     if not video_files:
             #st.markdown(links_md)
             #col_index += 1
+@st.cache_resource
 def display_images_and_wikipedia_summaries():
     image_files = [f for f in os.listdir('.') if f.endswith('.png')]
     if not image_files:
 # Function to display content or image based on a query
+@st.cache_resource
 def display_content_or_image(query):
     # Check if the query matches any glossary term
     for category, terms in transhuman_glossary.items():
     return False
 # 1. Constants and Top Level UI Variables
 # My Inference API Copy
 prompt = f"Write instructions to teach discharge planning along with guidelines and patient education. List entities, features and relationships to CCDA and FHIR objects in boldface."
 should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.")
 # 3. Stream Llama Response
         st.write('Llama model is asleep. Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
 # 4. Run query with payload
+@st.cache_resource
 def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
     st.markdown(response.json())
     return response.json()
 def get_output(prompt):
     return query({"inputs": prompt})
     safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
     replaced_prompt = prompt.replace(" ", "_").replace("\n", "_")
     safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:255]  # 255 is linux max, 260 is windows max
     return f"{safe_date_time}_{safe_prompt}.{file_type}"
 # 6. Speech transcription via OpenAI service
     return None
 # 8. File creator that interprets type and creates output file for text, markdown and code
+@st.cache_resource
 def create_file(filename, prompt, response, should_save=True):
     if not should_save:
         return