test

pages/2_Chatbot.py

@@ -1,46 +0,0 @@
-from openai import OpenAI
-import streamlit as st
-
-with st.sidebar:
-    IFC_API_KEY = st.text_input("HF access token", key="chat_bot_api_key", type="password")
-    selected_model = st.selectbox(
-        "Choose a model to chat with",
-        ("meta-llama/Llama-3.3-70B-Instruct", "meta-llama/Llama-3.1-8B-Instruct", "Qwen/QwQ-32B-Preview", "Qwen/Qwen2.5-72B-Instruct", "microsoft/Phi-3.5-mini-instruct"),
-    )
-    temperature = st.slider("Temperature", 0.01, 0.99, 0.5)
-    top_p = st.slider("Top_p", 0.01, 0.99, 0.7)
-    max_tokens = st.slider("Max Tokens", 64, 131072, 2048)
-
-st.title("💬 Chatbot")
-st.caption(" A HF chatbot powered by HF")
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-for msg in st.session_state.messages:
-    with st.chat_message(msg["role"]):
-        st.markdown(msg["content"])
-
-if prompt := st.chat_input():
-    if not IFC_API_KEY:
-        st.info("Please add your access token to continue.")
-        st.stop()
-
-    client = OpenAI(api_key=IFC_API_KEY, base_url="https://api-inference.huggingface.co/v1/")
-    st.session_state.messages.append({"role": "user", "content": prompt})
-    with st.chat_message("user"):
-        st.markdown(prompt)
-
-    with st.chat_message("assistant"):
-        stream = client.chat.completions.create(
-            model = selected_model,
-            messages=[
-                {"role": m["role"], "content": m["content"]}
-                for m in st.session_state.messages
-            ],
-            temperature = temperature,
-            top_p = top_p,
-            max_tokens = max_tokens,
-            stream = True,
-        )
-        response = st.write_stream(stream)
-    st.session_state.messages.append({"role": "assistant", "content": response})