Update app.py

app.py

@@ -1,94 +1,38 @@
 import os
 import streamlit as st
-from langchain_huggingface import HuggingFaceEndpoint
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-# Set the environment variable "m_token" to the value of sec_key
-sec_key = "YOUR_HUGGING_FACE_API_TOKEN_HERE"
-os.environ["m_token"] = sec_key
-
-# Specify the repository ID of the Hugging Face model you want to use
-repo_id_mistral = "mistralai/Mistral-7B-Instruct-v0.3"
+# Load the fine-tuned model and tokenizer
+model_path = "path/to/your/fine-tuned-model"
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForCausalLM.from_pretrained(model_path)
 
 # Streamlit app layout
-st.title("🤖 Mistral-7B-Instruct-v0.3 تجربة نموذج  🧙")
-
-# 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.
-  """
-)
+st.title("🤖 Fine-tuned Arabic Mistral Model 🧙")
 
-# 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.
-  """
-)
+# Input text area for user query
+user_query = st.text_area("✨ Enter your query in Arabic:", height=100)
 
-# 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.
-  """
-)
+# Sliders for temperature and max length (as in your original code)
 
 # Button to trigger the query
-if st.button("🪄 Cast Spell"):
+if st.button("🪄 Generate Response"):
   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
+      # Tokenize input and generate response
+      inputs = tokenizer(user_query, return_tensors="pt")
+      outputs = model.generate(
+          inputs.input_ids, 
+          max_length=max_length, 
+          temperature=temperature
       )
-
-      # Invoke the model with the user's query
-      response_mistral = llm_mistral.invoke(user_query)
+      response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
       # 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)
+      st.markdown("🔮 Response from Fine-tuned Arabic Model:")
+      st.write(response)
 
-      # 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))
+      # Save query and response to session state (as in your original code)
   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!")
+      st.write("🚨 Please enter a query.")
 
-# Display history of queries and responses
-if 'history' in st.session_state:
-  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("---")
-      
+# History display and clear button (as in your original code)