Create app.py

app.py

@@ -0,0 +1,64 @@
+import streamlit as st
+from typing import Generator
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+st.set_page_config(
+    page_icon="💬",
+    page_title="Chat App",
+    layout="wide",
+)
+
+model_name = "JuliaTsk/SuccinctLabs-chat-finetuned"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+st.title("ChatGPT-like clone 🎈")
+
+
+def generate_chat_responses(chat_completion) -> Generator[str, None, None]:
+    for chunk in chat_completion:
+        if chunk.choices[0].delta.content:
+            yield chunk.choices[0].delta.content
+
+
+left, right = st.columns([2, 6], vertical_alignment="top")
+max_tokens_range = 32768
+max_tokens = left.slider(
+    label="Max Tokens:",
+    min_value=128,
+    max_value=max_tokens_range,
+    # Default value or max allowed if less
+    value=min(1024, max_tokens_range),
+    step=128,
+    help=f"Adjust the maximum number of tokens (words) for the model's response."
+)
+temperature = left.slider(
+    label="Temperature:",
+    min_value=0.0,
+    max_value=1.0,
+    value=0.7,
+    step=0.01,
+    help=f"Controls randomness: a low value means less random responses."
+)
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+for message in st.session_state.messages:
+    avatar = '🤖' if message["role"] == "assistant" else '👨‍💻'
+    with right.chat_message(message["role"], avatar=avatar):
+        right.markdown(message["content"])
+
+
+prompt = st.chat_input("Say something")
+if prompt:
+    with right.chat_message("user", avatar='👨‍💻'):
+        right.markdown(prompt)
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with right.chat_message("assistant"):
+        inputs = tokenizer(prompt, return_tensors="pt")
+        outputs = model.generate(inputs["input_ids"], max_length=100, num_return_sequences=1)
+        generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+st.session_state.messages.append({"role": "assistant", "content": generated_text})
+