Delete model.py

model.py

@@ -1,57 +0,0 @@
-import os
-from typing import Iterator
-
-from text_generation import Client
-
-model_id = 'mistralai/Mistral-7B-Instruct-v0.1'
-
-API_URL = "https://api-inference.huggingface.co/models/" + model_id
-HF_TOKEN = os.environ.get("HF_READ_TOKEN", None)
-
-client = Client(
-    API_URL,
-    headers={"Authorization": f"Bearer {HF_TOKEN}"},
-)
-EOS_STRING = "</s>"
-EOT_STRING = "<EOT>"
-
-
-def get_prompt(message: str, chat_history: list[tuple[str, str]],
-               system_prompt: str) -> str:
-    texts = [f'<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n']
-    # The first user input is _not_ stripped
-    do_strip = False
-    for user_input, response in chat_history:
-        user_input = user_input.strip() if do_strip else user_input
-        do_strip = True
-        texts.append(f'{user_input} [/INST] {response.strip()} </s><s>[INST] ')
-    message = message.strip() if do_strip else message
-    texts.append(f'{message} [/INST]')
-    return ''.join(texts)
-
-
-def run(message: str,
-        chat_history: list[tuple[str, str]],
-        system_prompt: str,
-        max_new_tokens: int = 1024,
-        temperature: float = 0.1,
-        top_p: float = 0.9,
-        top_k: int = 50) -> Iterator[str]:
-    prompt = get_prompt(message, chat_history, system_prompt)
-
-    generate_kwargs = dict(
-        max_new_tokens=max_new_tokens,
-        do_sample=True,
-        top_p=top_p,
-        top_k=top_k,
-        temperature=temperature,
-    )
-    stream = client.generate_stream(prompt, **generate_kwargs)
-    output = ""
-    for response in stream:
-        if any([end_token in response.token.text for end_token in [EOS_STRING, EOT_STRING]]):
-            return output
-        else:
-            output += response.token.text
-        yield output
-    return output