Update app.py
Browse files
app.py
CHANGED
@@ -26,15 +26,6 @@ from llama_cpp import Llama
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SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им."
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SYSTEM_TOKEN = 1788
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USER_TOKEN = 1404
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BOT_TOKEN = 9225
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LINEBREAK_TOKEN = 13
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ROLE_TOKENS = {
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"user": USER_TOKEN,
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"bot": BOT_TOKEN,
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"system": SYSTEM_TOKEN
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}
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LOADER_MAPPING = {
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".csv": (CSVLoader, {}),
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@@ -76,7 +67,6 @@ def load_model(
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return model
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MAX_NEW_TOKENS = 1500
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EMBEDDER = SentenceTransformer("sentence-transformers/paraphrase-multilingual-mpnet-base-v2")
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MODEL = load_model()
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@@ -94,11 +84,9 @@ def load_single_document(file_path: str) -> Document:
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def get_message_tokens(model, role, content):
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message_tokens.append(model.token_eos())
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return message_tokens
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def get_system_tokens(model):
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@@ -168,28 +156,28 @@ def bot(
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top_k,
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temp
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):
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if not history:
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return
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tokens = get_system_tokens(
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tokens.append(LINEBREAK_TOKEN)
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for user_message, bot_message in history[:-1]:
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message_tokens = get_message_tokens(model=
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tokens.extend(message_tokens)
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if bot_message:
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message_tokens = get_message_tokens(model=
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tokens.extend(message_tokens)
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last_user_message = history[-1][0]
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if retrieved_docs:
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last_user_message = f"Контекст: {retrieved_docs}\n\nИспользуя контекст, ответь на вопрос: {last_user_message}"
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message_tokens = get_message_tokens(model=
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tokens.extend(message_tokens)
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role_tokens =
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tokens.extend(role_tokens)
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generator =
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tokens,
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top_k=top_k,
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top_p=top_p,
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@@ -198,9 +186,9 @@ def bot(
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partial_text = ""
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for i, token in enumerate(generator):
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if token ==
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break
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partial_text +=
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history[-1][1] = partial_text
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yield history
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SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им."
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LOADER_MAPPING = {
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".csv": (CSVLoader, {}),
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return model
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EMBEDDER = SentenceTransformer("sentence-transformers/paraphrase-multilingual-mpnet-base-v2")
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MODEL = load_model()
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def get_message_tokens(model, role, content):
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content = f"{role}\n{content}\n</s>"
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content = content.encode("utf-8")
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return model.tokenize(content, special=True)
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def get_system_tokens(model):
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top_k,
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temp
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):
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model = MODEL
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if not history:
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return
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tokens = get_system_tokens(model)[:]
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for user_message, bot_message in history[:-1]:
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message_tokens = get_message_tokens(model=model, role="user", content=user_message)
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tokens.extend(message_tokens)
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if bot_message:
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message_tokens = get_message_tokens(model=model, role="bot", content=bot_message)
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tokens.extend(message_tokens)
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last_user_message = history[-1][0]
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if retrieved_docs:
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last_user_message = f"Контекст: {retrieved_docs}\n\nИспользуя контекст, ответь на вопрос: {last_user_message}"
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message_tokens = get_message_tokens(model=model, role="user", content=last_user_message)
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tokens.extend(message_tokens)
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role_tokens = model.tokenize("bot\n".encode("utf-8"), special=True)
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tokens.extend(role_tokens)
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generator = model.generate(
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tokens,
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top_k=top_k,
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top_p=top_p,
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partial_text = ""
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for i, token in enumerate(generator):
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if token == model.token_eos():
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break
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partial_text += model.detokenize([token]).decode("utf-8", "ignore")
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history[-1][1] = partial_text
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yield history
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