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Update app.py
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app.py
CHANGED
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@@ -315,52 +315,6 @@ key = os.getenv('OPENAI_API_KEY')
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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."
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should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.")
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# 2. Prompt label button demo for LLM
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def add_witty_humor_buttons():
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with st.expander("Wit and Humor 🤣", expanded=True):
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# Tip about the Dromedary family
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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.")
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# Define button descriptions
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descriptions = {
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"Generate Limericks 😂": "Write ten random adult limericks based on quotes that are tweet length and make you laugh 🎭",
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"Wise Quotes 🧙": "Generate ten wise quotes that are tweet length 🦉",
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"Funny Rhymes 🎤": "Create ten funny rhymes that are tweet length 🎶",
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"Medical Jokes 💉": "Create ten medical jokes that are tweet length 🏥",
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"Minnesota Humor ❄️": "Create ten jokes about Minnesota that are tweet length 🌨️",
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"Top Funny Stories 📖": "Create ten funny stories that are tweet length 📚",
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"More Funny Rhymes 🎙️": "Create ten more funny rhymes that are tweet length 🎵"
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}
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# Create columns
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col1, col2, col3 = st.columns([1, 1, 1], gap="small")
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# Add buttons to columns
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if col1.button("Wise Limericks 😂"):
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StreamLLMChatResponse(descriptions["Generate Limericks 😂"])
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if col2.button("Wise Quotes 🧙"):
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StreamLLMChatResponse(descriptions["Wise Quotes 🧙"])
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#if col3.button("Funny Rhymes 🎤"):
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# StreamLLMChatResponse(descriptions["Funny Rhymes 🎤"])
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col4, col5, col6 = st.columns([1, 1, 1], gap="small")
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if col4.button("Top Ten Funniest Clean Jokes 💉"):
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StreamLLMChatResponse(descriptions["Top Ten Funniest Clean Jokes 💉"])
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if col5.button("Minnesota Humor ❄️"):
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StreamLLMChatResponse(descriptions["Minnesota Humor ❄️"])
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if col6.button("Origins of Medical Science True Stories"):
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StreamLLMChatResponse(descriptions["Origins of Medical Science True Stories"])
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col7 = st.columns(1, gap="small")
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if col7[0].button("Top Ten Best Write a streamlit python program prompts to build AI programs. 🎙️"):
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StreamLLMChatResponse(descriptions["Top Ten Best Write a streamlit python program prompts to build AI programs. 🎙️"])
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def SpeechSynthesis(result):
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documentHTML5='''
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<!DOCTYPE html>
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@@ -391,8 +345,6 @@ def SpeechSynthesis(result):
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components.html(documentHTML5, width=1280, height=300)
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#return result
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# 3. Stream Llama Response
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# @st.cache_resource
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def StreamLLMChatResponse(prompt):
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try:
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@@ -433,7 +385,7 @@ def StreamLLMChatResponse(prompt):
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SpeechSynthesis(result)
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return result
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except:
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st.write('
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# 4. Run query with payload
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def query(payload):
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@@ -448,8 +400,7 @@ def generate_filename(prompt, file_type):
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central = pytz.timezone('US/Central')
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safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
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replaced_prompt = prompt.replace(" ", "_").replace("\n", "_")
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safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:255] # 255 is linux max, 260 is windows max
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#safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:45]
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return f"{safe_date_time}_{safe_prompt}.{file_type}"
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# 6. Speech transcription via OpenAI service
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@@ -501,7 +452,9 @@ def create_file(filename, prompt, response, should_save=True):
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except:
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st.write('.')
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#has_python_code = bool(re.search(r"```python([\s\S]*?)```", prompt.strip() + '\r\n' + response))
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#if has_python_code:
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# python_code = re.findall(r"```python([\s\S]*?)```", response)[0].strip()
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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."
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should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.")
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def SpeechSynthesis(result):
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documentHTML5='''
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<!DOCTYPE html>
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components.html(documentHTML5, width=1280, height=300)
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#return result
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# @st.cache_resource
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def StreamLLMChatResponse(prompt):
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try:
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SpeechSynthesis(result)
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return result
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except:
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st.write('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).')
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# 4. Run query with payload
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def query(payload):
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central = pytz.timezone('US/Central')
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safe_date_time = datetime.now(central).strftime("%m%d_%H%M")
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replaced_prompt = prompt.replace(" ", "_").replace("\n", "_")
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safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:255] # 255 is linux max, 260 is windows max filename size.
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return f"{safe_date_time}_{safe_prompt}.{file_type}"
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# 6. Speech transcription via OpenAI service
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except:
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st.write('.')
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has_python_code = re.search(r"```python([\s\S]*?)```", prompt.strip() + '\r\n' + response)
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if has_python_code:
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st.markdown('# 🐍 Python Code - Lets make an app.py.')
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#has_python_code = bool(re.search(r"```python([\s\S]*?)```", prompt.strip() + '\r\n' + response))
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#if has_python_code:
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# python_code = re.findall(r"```python([\s\S]*?)```", response)[0].strip()
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