Create app.py

app.py

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+import os
+import streamlit as st
+from langchain_huggingface import HuggingFaceEndpoint
+
+# Set the environment variable "HUGGINGFACEHUB_API_TOKEN" to the value of sec_key
+sec_key = ""
+os.environ["HUGGINGFACEHUB_API_TOKEN"] = sec_key
+
+# Specify the repository IDs of the Hugging Face models you want to use
+repo_id_mistral = "mistralai/Mistral-7B-Instruct-v0.3"
+repo_id_llama3 = "meta-llama/Meta-Llama-3-8B"  # Replace with the actual repo ID for Llama3
+
+# Streamlit app layout
+st.title("🤖 AI Query Wizard 🧙")
+
+# Custom background and styling
+st.markdown(
+    """
+    <style>
+   
+    .stTextInput, .stButton {
+        background-color: rgba(255, 255, 255, 0.8);
+        border-radius: 10px;
+        padding: 10px;
+    }
+    .response {
+        color: #FFD700; /* Gold color for responses */
+        font-weight: bold;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True
+)
+
+# Input text area for user query with enhanced instructions
+user_query = st.text_area(
+    "✨ Enter your magical query:",
+    height=100,
+    help="""
+    **Enhanced Prompting Instructions:**
+    - Be clear and specific about what you want to know.
+    - Use natural language to describe your query.
+    - If asking a question, ensure it is well-formed and unambiguous.
+    - For best results, provide context or background information if relevant.
+    """
+)
+
+# Slider for adjusting the temperature
+temperature = st.slider(
+    "Temperature",
+    min_value=0.1,
+    max_value=1.0,
+    value=0.7,
+    step=0.1,
+    help="""
+    **Temperature:**
+    - Lower values (e.g., 0.1) make the output more deterministic and focused.
+    - Higher values (e.g., 1.0) make the output more diverse and creative.
+    """
+)
+
+# Slider for adjusting the max length
+max_length = st.slider(
+    "Max Length",
+    min_value=32,
+    max_value=256,
+    value=128,
+    step=32,
+    help="""
+    **Max Length:**
+    - Controls the maximum number of tokens in the generated response.
+    - Adjust based on the desired length of the response.
+    """
+)
+
+# Button to trigger the query
+if st.button("🪄 Cast Spell"):
+    if user_query:
+        # Initialize the HuggingFaceEndpoint for Mistral
+        llm_mistral = HuggingFaceEndpoint(
+            repo_id=repo_id_mistral,
+            max_length=max_length,
+            temperature=temperature,
+            token=sec_key
+        )
+
+        # Initialize the HuggingFaceEndpoint for Llama3
+        llm_llama3 = HuggingFaceEndpoint(
+            repo_id=repo_id_llama3,
+            max_length=max_length,
+            temperature=temperature,
+            token=sec_key
+        )
+
+        # Invoke both models with the user's query
+        response_mistral = llm_mistral.invoke(user_query)
+        response_llama3 = llm_llama3.invoke(user_query)
+
+        # Display the responses side by side
+        col1, col2 = st.columns(2)
+
+        with col1:
+            st.markdown("🔮 <span class='response'>Response from Mistral-7B-Instruct-v0.3:</span>", unsafe_allow_html=True)
+            st.markdown(f"<span class='response'>{response_mistral}</span>", unsafe_allow_html=True)
+
+        with col2:
+            st.markdown("🔮 <span class='response'>Response from Llama3:</span>", unsafe_allow_html=True)
+            st.markdown(f"<span class='response'>{response_llama3}</span>", unsafe_allow_html=True)
+
+        # Save query and responses to session state
+        if 'history' not in st.session_state:
+            st.session_state.history = []
+        st.session_state.history.append((user_query, response_mistral, response_llama3))
+    else:
+        st.write("🚨 Please enter a query to cast your spell.")
+
+# Button to clear history
+if st.button("🗑️ Clear History"):
+    if 'history' in st.session_state:
+        st.session_state.history = []
+    st.success("History cleared!")
+
+# Display history of queries and responses
+if 'history' in st.session_state:
+    st.subheader("📜 Scroll of Spells Cast")
+    for query, response_mistral, response_llama3 in st.session_state.history:
+        st.write(f"**Query:** {query}")
+        col1, col2 = st.columns(2)
+        with col1:
+            st.markdown(f"<span class='response'>**Response from Mistral-7B-Instruct-v0.3:** {response_mistral}</span>", unsafe_allow_html=True)
+        with col2:
+            st.markdown(f"<span class='response'>**Response from Llama3:** {response_llama3}</span>", unsafe_allow_html=True)
+        st.write("---")