Spaces:
Running
Running
import hashlib | |
import re | |
import time | |
import uuid | |
from datetime import timedelta | |
from pathlib import Path | |
from typing import Callable, Optional | |
def get_messages_content(messages: list[dict]) -> str: | |
return "\n".join( | |
[ | |
f"{message['role'].upper()}: {get_content_from_message(message)}" | |
for message in messages | |
] | |
) | |
def get_last_user_message_item(messages: list[dict]) -> Optional[dict]: | |
for message in reversed(messages): | |
if message["role"] == "user": | |
return message | |
return None | |
def get_content_from_message(message: dict) -> Optional[str]: | |
if isinstance(message["content"], list): | |
for item in message["content"]: | |
if item["type"] == "text": | |
return item["text"] | |
else: | |
return message["content"] | |
return None | |
def get_last_user_message(messages: list[dict]) -> Optional[str]: | |
message = get_last_user_message_item(messages) | |
if message is None: | |
return None | |
return get_content_from_message(message) | |
def get_last_assistant_message(messages: list[dict]) -> Optional[str]: | |
for message in reversed(messages): | |
if message["role"] == "assistant": | |
return get_content_from_message(message) | |
return None | |
def get_system_message(messages: list[dict]) -> Optional[dict]: | |
for message in messages: | |
if message["role"] == "system": | |
return message | |
return None | |
def remove_system_message(messages: list[dict]) -> list[dict]: | |
return [message for message in messages if message["role"] != "system"] | |
def pop_system_message(messages: list[dict]) -> tuple[Optional[dict], list[dict]]: | |
return get_system_message(messages), remove_system_message(messages) | |
def prepend_to_first_user_message_content( | |
content: str, messages: list[dict] | |
) -> list[dict]: | |
for message in messages: | |
if message["role"] == "user": | |
if isinstance(message["content"], list): | |
for item in message["content"]: | |
if item["type"] == "text": | |
item["text"] = f"{content}\n{item['text']}" | |
else: | |
message["content"] = f"{content}\n{message['content']}" | |
break | |
return messages | |
def add_or_update_system_message(content: str, messages: list[dict]): | |
""" | |
Adds a new system message at the beginning of the messages list | |
or updates the existing system message at the beginning. | |
:param msg: The message to be added or appended. | |
:param messages: The list of message dictionaries. | |
:return: The updated list of message dictionaries. | |
""" | |
if messages and messages[0].get("role") == "system": | |
messages[0]["content"] = f"{content}\n{messages[0]['content']}" | |
else: | |
# Insert at the beginning | |
messages.insert(0, {"role": "system", "content": content}) | |
return messages | |
def openai_chat_message_template(model: str): | |
return { | |
"id": f"{model}-{str(uuid.uuid4())}", | |
"created": int(time.time()), | |
"model": model, | |
"choices": [{"index": 0, "logprobs": None, "finish_reason": None}], | |
} | |
def openai_chat_chunk_message_template( | |
model: str, message: Optional[str] = None | |
) -> dict: | |
template = openai_chat_message_template(model) | |
template["object"] = "chat.completion.chunk" | |
if message: | |
template["choices"][0]["delta"] = {"content": message} | |
else: | |
template["choices"][0]["finish_reason"] = "stop" | |
return template | |
def openai_chat_completion_message_template( | |
model: str, message: Optional[str] = None | |
) -> dict: | |
template = openai_chat_message_template(model) | |
template["object"] = "chat.completion" | |
if message is not None: | |
template["choices"][0]["message"] = {"content": message, "role": "assistant"} | |
template["choices"][0]["finish_reason"] = "stop" | |
return template | |
def get_gravatar_url(email): | |
# Trim leading and trailing whitespace from | |
# an email address and force all characters | |
# to lower case | |
address = str(email).strip().lower() | |
# Create a SHA256 hash of the final string | |
hash_object = hashlib.sha256(address.encode()) | |
hash_hex = hash_object.hexdigest() | |
# Grab the actual image URL | |
return f"https://www.gravatar.com/avatar/{hash_hex}?d=mp" | |
def calculate_sha256(file): | |
sha256 = hashlib.sha256() | |
# Read the file in chunks to efficiently handle large files | |
for chunk in iter(lambda: file.read(8192), b""): | |
sha256.update(chunk) | |
return sha256.hexdigest() | |
def calculate_sha256_string(string): | |
# Create a new SHA-256 hash object | |
sha256_hash = hashlib.sha256() | |
# Update the hash object with the bytes of the input string | |
sha256_hash.update(string.encode("utf-8")) | |
# Get the hexadecimal representation of the hash | |
hashed_string = sha256_hash.hexdigest() | |
return hashed_string | |
def validate_email_format(email: str) -> bool: | |
if email.endswith("@localhost"): | |
return True | |
return bool(re.match(r"[^@]+@[^@]+\.[^@]+", email)) | |
def sanitize_filename(file_name): | |
# Convert to lowercase | |
lower_case_file_name = file_name.lower() | |
# Remove special characters using regular expression | |
sanitized_file_name = re.sub(r"[^\w\s]", "", lower_case_file_name) | |
# Replace spaces with dashes | |
final_file_name = re.sub(r"\s+", "-", sanitized_file_name) | |
return final_file_name | |
def extract_folders_after_data_docs(path): | |
# Convert the path to a Path object if it's not already | |
path = Path(path) | |
# Extract parts of the path | |
parts = path.parts | |
# Find the index of '/data/docs' in the path | |
try: | |
index_data_docs = parts.index("data") + 1 | |
index_docs = parts.index("docs", index_data_docs) + 1 | |
except ValueError: | |
return [] | |
# Exclude the filename and accumulate folder names | |
tags = [] | |
folders = parts[index_docs:-1] | |
for idx, _ in enumerate(folders): | |
tags.append("/".join(folders[: idx + 1])) | |
return tags | |
def parse_duration(duration: str) -> Optional[timedelta]: | |
if duration == "-1" or duration == "0": | |
return None | |
# Regular expression to find number and unit pairs | |
pattern = r"(-?\d+(\.\d+)?)(ms|s|m|h|d|w)" | |
matches = re.findall(pattern, duration) | |
if not matches: | |
raise ValueError("Invalid duration string") | |
total_duration = timedelta() | |
for number, _, unit in matches: | |
number = float(number) | |
if unit == "ms": | |
total_duration += timedelta(milliseconds=number) | |
elif unit == "s": | |
total_duration += timedelta(seconds=number) | |
elif unit == "m": | |
total_duration += timedelta(minutes=number) | |
elif unit == "h": | |
total_duration += timedelta(hours=number) | |
elif unit == "d": | |
total_duration += timedelta(days=number) | |
elif unit == "w": | |
total_duration += timedelta(weeks=number) | |
return total_duration | |
def parse_ollama_modelfile(model_text): | |
parameters_meta = { | |
"mirostat": int, | |
"mirostat_eta": float, | |
"mirostat_tau": float, | |
"num_ctx": int, | |
"repeat_last_n": int, | |
"repeat_penalty": float, | |
"temperature": float, | |
"seed": int, | |
"tfs_z": float, | |
"num_predict": int, | |
"top_k": int, | |
"top_p": float, | |
"num_keep": int, | |
"typical_p": float, | |
"presence_penalty": float, | |
"frequency_penalty": float, | |
"penalize_newline": bool, | |
"numa": bool, | |
"num_batch": int, | |
"num_gpu": int, | |
"main_gpu": int, | |
"low_vram": bool, | |
"f16_kv": bool, | |
"vocab_only": bool, | |
"use_mmap": bool, | |
"use_mlock": bool, | |
"num_thread": int, | |
} | |
data = {"base_model_id": None, "params": {}} | |
# Parse base model | |
base_model_match = re.search( | |
r"^FROM\s+(\w+)", model_text, re.MULTILINE | re.IGNORECASE | |
) | |
if base_model_match: | |
data["base_model_id"] = base_model_match.group(1) | |
# Parse template | |
template_match = re.search( | |
r'TEMPLATE\s+"""(.+?)"""', model_text, re.DOTALL | re.IGNORECASE | |
) | |
if template_match: | |
data["params"] = {"template": template_match.group(1).strip()} | |
# Parse stops | |
stops = re.findall(r'PARAMETER stop "(.*?)"', model_text, re.IGNORECASE) | |
if stops: | |
data["params"]["stop"] = stops | |
# Parse other parameters from the provided list | |
for param, param_type in parameters_meta.items(): | |
param_match = re.search(rf"PARAMETER {param} (.+)", model_text, re.IGNORECASE) | |
if param_match: | |
value = param_match.group(1) | |
try: | |
if param_type is int: | |
value = int(value) | |
elif param_type is float: | |
value = float(value) | |
elif param_type is bool: | |
value = value.lower() == "true" | |
except Exception as e: | |
print(e) | |
continue | |
data["params"][param] = value | |
# Parse adapter | |
adapter_match = re.search(r"ADAPTER (.+)", model_text, re.IGNORECASE) | |
if adapter_match: | |
data["params"]["adapter"] = adapter_match.group(1) | |
# Parse system description | |
system_desc_match = re.search( | |
r'SYSTEM\s+"""(.+?)"""', model_text, re.DOTALL | re.IGNORECASE | |
) | |
system_desc_match_single = re.search( | |
r"SYSTEM\s+([^\n]+)", model_text, re.IGNORECASE | |
) | |
if system_desc_match: | |
data["params"]["system"] = system_desc_match.group(1).strip() | |
elif system_desc_match_single: | |
data["params"]["system"] = system_desc_match_single.group(1).strip() | |
# Parse messages | |
messages = [] | |
message_matches = re.findall(r"MESSAGE (\w+) (.+)", model_text, re.IGNORECASE) | |
for role, content in message_matches: | |
messages.append({"role": role, "content": content}) | |
if messages: | |
data["params"]["messages"] = messages | |
return data | |