Create app.py

app.py

@@ -0,0 +1,49 @@
+import streamlit as st
+from huggingface_hub import InferenceClient
+
+client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.1")
+
+def format_prompt(message, history):
+    prompt = "<s>"
+    for user_prompt, bot_response in history:
+        prompt += f"[INST] {user_prompt} [/INST]"
+        prompt += f" {bot_response}</s> "
+    prompt += f"[INST] {message} [/INST]"
+    return prompt
+
+def generate(prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+    response = client.text_generation(formatted_prompt, **generate_kwargs)
+    return response.choices[0].text
+
+def main():
+    st.title("Mistral 7B")
+    prompt = st.text_input("User Input:", "")
+    history = []  # You need to manage the conversation history here
+
+    temperature = st.slider("Temperature", 0.0, 1.0, 0.9, step=0.05)
+    max_new_tokens = st.slider("Max new tokens", 0, 1048, 256, step=64)
+    top_p = st.slider("Top-p (nucleus sampling)", 0.0, 1.0, 0.90, step=0.05)
+    repetition_penalty = st.slider("Repetition penalty", 1.0, 2.0, 1.2, step=0.05)
+
+    if st.button("Generate"):
+        output = generate(prompt, history, temperature, max_new_tokens, top_p, repetition_penalty)
+        st.text("Bot Output:")
+        st.write(output)
+
+if __name__ == "__main__":
+    main()