Create app.py

app.py

@@ -0,0 +1,39 @@
+import streamlit as st
+from ctransformers import AutoModelForCausalLM
+
+# Load the model
+llm = AutoModelForCausalLM.from_pretrained(
+    model_path_or_repo_id="mistral-7b-instruct-v0.2.Q2_K.gguf",
+    model_type="mistral",
+)
+
+st.title("Conversational Chat with Mistral 🦙🗨️")
+
+
+# Function to generate response
+def generate_response(user_query):
+    prompt = f"""The user query is '{user_query}'"""
+    args = {
+        "prompt": prompt,
+        "stream": True,
+        "max_new_tokens": 2048,
+        "temperature": 0,
+    }
+
+    response_placeholder = st.empty()  # Placeholder for displaying response chunks
+
+    response_so_far = ""  # Initialize empty string to store cumulative response
+
+    for chunk in llm(**args):
+        response_so_far += chunk  # Append current chunk to cumulative response
+        response_placeholder.write(response_so_far)  # Display cumulative response
+
+    return  # No need to return anything
+
+
+# User input
+user_query = st.text_input("Enter your query:", "")
+
+if user_query:
+    # Generate and display response
+    generate_response(user_query)