Update backupapp.py

backupapp.py

@@ -1,4 +1,4 @@
-# Modify the program below to add a few picture buttons which will use emojis and a witty title to describe a prompt.  the first prompt I want is "Write ten random adult limerick based on quotes that are tweet length and make you laugh.  Show as numbered bold faced and large font markdown outline with emojis for each."  Modify this code to add the prompt emoji labeled buttons above the text box.  when you click them pass the varible they contain to a function which runs the chat through the Llama web service call in the code below.  refactor it so it is function based.  Put variables that set description for button and label for button right before the st.button() function calls and use st.expander() function to create a expanded description container with a witty label so user could collapse st.expander to hide buttons of a particular type.  This first type will be Wit and Humor.  Make sure each label contains appropriate emojis.  Code:  # Imports
+# Imports
 import base64
 import glob
 import json
@@ -44,41 +44,94 @@ prompt = f"Write instructions to teach anyone to write a discharge plan. List th
 st.set_page_config(page_title="GPT Streamlit Document Reasoner", layout="wide")
 
 # UI Controls
-should_save = st.sidebar.checkbox("💾 Save", value=True)
+should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.")
 
-# Functions
+# Function to add witty and humor buttons
+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("Generate 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("Medical Jokes 💉"):
+            StreamLLMChatResponse(descriptions["Medical Jokes 💉"])
+        
+        if col5.button("Minnesota Humor ❄️"):
+            StreamLLMChatResponse(descriptions["Minnesota Humor ❄️"])
+        
+        if col6.button("Top Funny Stories 📖"):
+            StreamLLMChatResponse(descriptions["Top Funny Stories 📖"])
+        
+        col7 = st.columns(1, gap="small")
+        
+        if col7[0].button("More Funny Rhymes 🎙️"):
+            StreamLLMChatResponse(descriptions["More Funny Rhymes 🎙️"])
+
+
+# Function to Stream Inference Client for Inference Endpoint Responses
 def StreamLLMChatResponse(prompt):
-    endpoint_url = API_URL
-    hf_token = API_KEY
-    client = InferenceClient(endpoint_url, token=hf_token)
-    gen_kwargs = dict(
-        max_new_tokens=512,
-        top_k=30,
-        top_p=0.9,
-        temperature=0.2,
-        repetition_penalty=1.02,
-        stop_sequences=["\nUser:", "<|endoftext|>", "</s>"],
-    )
-    stream = client.text_generation(prompt, stream=True, details=True, **gen_kwargs)
-    report=[]
-    res_box = st.empty()
-    collected_chunks=[]
-    collected_messages=[]
-    for r in stream:
-        if r.token.special:
-            continue
-        if r.token.text in gen_kwargs["stop_sequences"]:
-            break
-        collected_chunks.append(r.token.text)
-        chunk_message = r.token.text
-        collected_messages.append(chunk_message)
-        try:
-            report.append(r.token.text)
-            if len(r.token.text) > 0:
-                result="".join(report).strip()
-                res_box.markdown(f'*{result}*')
-        except:
-            st.write(' ')
+
+    try:
+        endpoint_url = API_URL
+        hf_token = API_KEY
+        client = InferenceClient(endpoint_url, token=hf_token)
+        gen_kwargs = dict(
+            max_new_tokens=512,
+            top_k=30,
+            top_p=0.9,
+            temperature=0.2,
+            repetition_penalty=1.02,
+            stop_sequences=["\nUser:", "<|endoftext|>", "</s>"],
+        )
+        stream = client.text_generation(prompt, stream=True, details=True, **gen_kwargs)
+        report=[]
+        res_box = st.empty()
+        collected_chunks=[]
+        collected_messages=[]
+        for r in stream:
+            if r.token.special:
+                continue
+            if r.token.text in gen_kwargs["stop_sequences"]:
+                break
+            collected_chunks.append(r.token.text)
+            chunk_message = r.token.text
+            collected_messages.append(chunk_message)
+            try:
+                report.append(r.token.text)
+                if len(r.token.text) > 0:
+                    result="".join(report).strip()
+                    res_box.markdown(f'*{result}*')
+            except:
+                st.write(' ')
+    except:
+        st.write('DromeLlama is asleep. Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
+
+
 
 def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
@@ -335,14 +388,21 @@ def get_zip_download_link(zip_file):
     return href
 
 def main():
-    st.title(" DrLlama7B")
+
+    st.title("DromeLlama7B")
     prompt = f"Write ten funny jokes that are tweet length stories that make you laugh.  Show as markdown outline with emojis for each."
-    example_input = st.text_input("Enter your example text:", value=prompt)
-    if st.button("Run Prompt With Dr Llama"):
+
+    # Add Wit and Humor buttons
+    add_witty_humor_buttons()
+
+    example_input = st.text_input("Enter your example text:", value=prompt, help="Enter text to get a response from DromeLlama.")
+    if st.button("Run Prompt With DromeLlama", help="Click to run the prompt."):
         try:
             StreamLLMChatResponse(example_input)
         except:
-            st.write('Dr. Llama is asleep.  Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
+            st.write('DromeLlama is asleep. Starting up now on A10 - please give 5 minutes then retry as KEDA scales up from zero to activate running container(s).')
+
+    
     openai.api_key = os.getenv('OPENAI_KEY')
     menu = ["txt", "htm", "xlsx", "csv", "md", "py"]
     choice = st.sidebar.selectbox("Output File Type:", menu)