Create main.py

main.py

@@ -0,0 +1,60 @@
+import streamlit as st 
+import requests
+# Streamlit page configuration
+st.title("Chatlytic")
+
+# Initialize session state for model and messages if not already present
+if "openai_model" not in st.session_state:
+    st.session_state["openai_model"] = "mixtral-8x7b"
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Function to clear the chat
+def clear_chat():
+    st.session_state.messages = []
+
+# Button to clear the chat
+if st.button('Clear Chat'):
+    clear_chat()
+
+# Display previous messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Input for new message
+if prompt := st.chat_input("What is up?"):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Define the API endpoint
+    api_endpoint = "https://ka1kuk-llm-api.hf.space/api/v1/chat/completions"
+
+    # Prepare the data for the POST request
+    data = {
+        "model": st.session_state["openai_model"],
+        "messages": st.session_state.messages,
+        "temperature": 0.5,
+        "top_p": 0.95,
+        "max_tokens": -1,
+        "use_cache": False,
+        "stream": False
+    }
+
+    # Send the POST request to the custom API
+    response = requests.post(api_endpoint, json=data)
+
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Get the response content
+        response_data = response.json()
+        # Append the assistant's response to the messages
+        st.session_state.messages.append({"role": "assistant", "content": response_data["choices"][0]["message"]["content"]})
+        # Display the assistant's response
+        with st.chat_message("assistant"):
+            st.markdown(response_data["choices"][0]["message"]["content"])
+    else:
+        # Display an error message if the request failed
+        st.error("Failed to get a response from the custom API.")