Update app.py

app.py

@@ -1,51 +1,11 @@
-from huggingface_hub import InferenceClient
 
-client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
+huggingface-cli login
 
-def format_prompt(message, history, system_prompt=None):
-    prompt = "<s>"
-    for user_prompt, bot_response in history:
-        prompt += f"[INST] {user_prompt} [/INST]"
-        prompt += f" {bot_response}</s> "
-    if system_prompt:
-        prompt += f"[SYS] {system_prompt} [/SYS]"
-    prompt += f"[INST] {message} [/INST]"
-    return prompt
+# Use a pipeline as a high-level helper
+from transformers import pipeline
 
-def generate(
-    prompt, history, system_prompt=None, temperature=0.2, max_new_tokens=1024, 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, system_prompt)
-
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-    output = ""
-
-    for response in stream:
-        output += response.token.text
-        print(output, end='', flush=True)
-    return output
-
-if __name__ == "__main__":
-    history = []
-    system_prompt = None
-    while True:
-        user_input = input("You: ")
-        if user_input.lower() in ["exit", "quit"]:
-            break
-        response = generate(user_input, history, system_prompt)
-        history.append((user_input, response))
-        print(f"\nBot: {response}\n")
+messages = [
+    {"role": "user", "content": "Who are you?"},
+]
+pipe = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.3")
+pipe(messages)