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music_recommendations.py

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+import streamlit as st
+from transformers import pipeline
+import scipy.io.wavfile
+from openai import OpenAI
+import time
+import numpy as np
+
+# Initialize the OpenAI client
+client = OpenAI(
+    api_key="a99ae8e15f1e439a935b5e1cf2005c8b",
+    base_url="https://api.aimlapi.com",
+)
+
+# Streamlit app layout
+st.title("Mood-based Music Generator")
+
+# Ask the user for their feeling and preferred music style via Streamlit inputs
+user_feeling = st.text_input("How are you feeling right now?", value="feeling down")
+music_style = st.text_input("What music style do you prefer?", value="pop")
+
+# Button to trigger music generation
+if st.button("Generate Music"):
+    with st.spinner("Generating music, please wait..."):
+        # Send the feeling and music style to the OpenAI model
+        response = client.chat.completions.create(
+            model="meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a musical assistant that, based on a user's feeling, can describe it as a musical instrument. Provide a short one-sentence response."
+                },
+                {
+                    "role": "user",
+                    "content": f"I am feeling {user_feeling}. Can you make me happy with a {music_style} style of music?"
+                },
+            ],
+        )
+
+        message = response.choices[0].message.content
+        st.write(f"Assistant: {message}")
+
+        # Load the synthesizer model for music generation
+        synthesiser = pipeline("text-to-audio", "facebook/musicgen-small")
+
+        # Simulate a short wait to represent loading time for music generation
+        time.sleep(2)
+
+        # Generate the music using the synthesizer model based on the message
+        music = synthesiser(message, forward_params={"do_sample": True, "guidance_scale": 1})
+
+        # Save the generated audio to a file
+        audio_filename = "musicgen_out.wav"
+        scipy.io.wavfile.write(audio_filename, rate=music["sampling_rate"], data=np.array(music["audio"]))
+
+        st.success("Music has been generated!")
+
+        # Play the generated audio in Streamlit
+        st.audio(audio_filename)
+

physical_activity.py

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+import streamlit as st
+from openai import OpenAI
+
+# Initialize the OpenAI client
+client = OpenAI(
+    api_key="9a70a7b82dd84c8cb2e8c43a156be3c7",  # Replace with your actual API key
+    base_url="https://api.aimlapi.com",  # Replace with the correct base URL if needed
+)
+
+# Streamlit page title
+st.title("Mood-based Exercise Recommendations")
+
+# User input: Ask the user how they feel
+user_feeling = st.text_input("How are you feeling right now?", placeholder="e.g., tired, stressed, happy...")
+
+# When the user submits their feeling, generate an exercise recommendation using the model
+if user_feeling:
+    with st.spinner("Generating exercise recommendation..."):
+        # Send the user's feeling to the OpenAI model
+        response = client.chat.completions.create(
+            model="meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a fitness coach and a doctor . Based on the user's current mood, suggest a suitable exercise in one sentence. and write them in bullet"
+                },
+                {
+                    "role": "user",
+                    "content": f"I am feeling {user_feeling}. What exercise should I do?"
+                },
+            ],
+        )
+        
+        # Get the model's response
+        message = response.choices[0].message.content
+        
+        # Display the exercise recommendation
+        st.write(f"Based on how you're feeling, here's an exercise suggestion for you: {message}")

positive_quotes.py

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+# Import necessary libraries
+from openai import OpenAI
+import streamlit as st
+
+# Initialize OpenAI Client
+client = OpenAI(api_key='2051e9263e2e4f0e9afb23afe4a654fa', base_url='https://api.aimlapi.com/')
+
+# Define the system prompt
+system_prompt = (
+    'You are a helpful assistant that provides positive, optimistic, uplifting, '
+    'and motivational quotes filled with wisdom, encouragement, and hope to uplift and inspire people.'
+)
+
+def generate_positive_quote(feeling):
+    # Create a personalized user prompt based on the user's input
+    user_prompt = f'Give me a positive quote that can help someone who feels {feeling}.'
+    
+    # Create messages for the API request
+    messages = [
+        {'role': 'system', 'content': system_prompt},
+        {'role': 'user', 'content': user_prompt}
+    ]
+
+    # Call the OpenAI API
+    response = client.chat.completions.create(
+        model="meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
+        messages=messages,
+        temperature=0.5,
+        max_tokens=100
+    )
+
+    # Extract and return the quote from the response
+    return response.choices[0].message.content
+
+
+ 
+   # Set up the Streamlit page
+st.title('✨ Positive Quote Generator ✨')
+    
+st.markdown("Welcome to the Positive Quote Generator! Click the button below to receive an uplifting message.")
+    # Input field for the user to describe how they feel
+feeling = st.text_input('How do you feel today?', '')
+
+    # Generate and display a quote when the button is clicked
+if st.button('Get Positive Quote'):
+        if feeling:
+            quote = generate_positive_quote(feeling)
+            st.success(quote)
+        else:
+            st.error('Please enter how you feel.')
+

talk_to_friend.py

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+import streamlit as st
+from openai import OpenAI
+
+# OpenAI Client
+client = OpenAI(api_key='up_CpZjdAyzHNZSbSTAQWVqYuJGgQNJW', base_url='https://api.upstage.ai/v1/solar')
+
+# Streamlit page configuration
+st.set_page_config(page_title='Chat with me 😊', layout='wide')
+st.title("Chat with me 😊")
+
+# Initialize session state
+if 'messages' not in st.session_state:
+    st.session_state.messages = [
+        {'role': 'system', 'content': 'You are a helpful friend that someone can depend on and want to chat with, you provides positive, optimistic, uplifting, and motivational suggestions and advices filled with wisdom, encouragement and hope to uplift and inspire people.'}
+    ]
+
+def generate_response(prompt: str) -> str:
+    response = client.chat.completions.create(
+        model="solar-pro",
+        messages=st.session_state.messages + [{'role': 'user', 'content': prompt}],
+        temperature=0.7,
+        max_tokens=200
+    )
+    
+    return response.choices[0].message.content
+
+# Display chat messages
+for message in st.session_state.messages[1:]:  # Skip the system message
+    with st.chat_message(message['role']):
+        st.write(message['content'])
+
+# Chat input
+user_input = st.chat_input("I am waiting to hear from you 😊")
+
+if user_input:
+    if user_input.lower() in ['quit', 'exit', 'escape', 'out', 'ex']:
+        st.session_state.messages = [st.session_state.messages[0]]  # Keep only the system message
+        st.success("Thanks for chatting with me!")
+    else:
+        # Add user message to chat history
+        st.session_state.messages.append({'role': 'user', 'content': user_input})
+        
+        # Display user message
+        with st.chat_message("user"):
+            st.write(user_input)
+        
+        # Generate bot response
+        response = generate_response(user_input)
+        
+        # Add bot response to chat history
+        st.session_state.messages.append({'role': 'assistant', 'content': response})
+        
+        # Display bot response
+        with st.chat_message("assistant"):
+            st.write(response)
+
+# No rerun needed