Update app.py

app.py

@@ -3,131 +3,91 @@ import streamlit as st
 from langchain_huggingface import HuggingFaceEndpoint
 
 # Set the environment variable "m_token" to the value of sec_key
-sec_key = ""
+sec_key = "YOUR_HUGGING_FACE_API_TOKEN_HERE"
 os.environ["m_token"] = sec_key
 
-# Specify the repository IDs of the Hugging Face models you want to use
+# Specify the repository ID of the Hugging Face model 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("🤖 Mistral-7B-Instruct-v0.3 تجربة نموذج  🧙")
 
-# 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.
-    """
+  "✨ 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.
-    """
+  "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.
-    """
+  "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
-        )'''
+  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
+      )
 
-        # Invoke both models with the user's query
-        response_mistral = llm_mistral.invoke(user_query)
-        #response_llama3 = llm_llama3.invoke(user_query)
+      # Invoke the model with the user's query
+      response_mistral = llm_mistral.invoke(user_query)
 
-        # Display the responses side by side
-        col1 = st.columns(1)
+      # Display the response
+      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 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))
-    else:
-        st.write("🚨 Please enter a query to cast your spell.")
+      # Save query and response to session state
+      if 'history' not in st.session_state:
+          st.session_state.history = []
+      st.session_state.history.append((user_query, response_mistral))
+  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!")
+  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 = st.columns(1)
-        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("---")
+  st.subheader("📜 Scroll of Spells Cast")
+  for query, response_mistral in st.session_state.history:
+      st.write(f"**Query:** {query}")
+      st.markdown(f"<span class='response'>**Response from Mistral-7B-Instruct-v0.3:** {response_mistral}</span>", unsafe_allow_html=True)
+      st.write("---")