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utils.py
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utils.py
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from datetime import datetime
import base64
import yaml
import requests
from dotenv import load_dotenv
import streamlit as st
import os
import aiohttp
import asyncio
import time
load_dotenv()
def load_config(file_path = "config.yaml"):
with open(file_path, "r") as f:
return yaml.safe_load(f)
config = load_config()
def convert_ns_to_seconds(ns_value):
return ns_value / 1_000_000_000
def timeit(func):
def wrapper(*args, **kwargs):
start_time = time.time()
result = func(*args, **kwargs)
end_time = time.time()
execution_time = end_time - start_time
print(f"Function '{func.__name__}' executed in {execution_time:.4f} seconds")
return result
return wrapper
def command(user_input):
splitted_input = user_input.split(" ")
if splitted_input[0] == "/pull":
return pull_model_in_background(splitted_input[1])
elif splitted_input[0] == "/help":
return "Possible commands:\n- /pull <model_name>"
else:
return """Invalid command, please use one of the following:\n
- /help\n
- /pull <model_name>"""
def pull_ollama_model(model_name):
json_response = requests.post(url = config["ollama"]["base_url"] + "/api/pull", json = {"model": model_name}).json()
print(json_response)
if "error" in json_response.keys():
return json_response["error"]["message"]
else:
st.session_state.model_options = list_ollama_models()
st.warning(f"Pulling {model_name} finished.")
return json_response
async def pull_ollama_model_async(model_name, stream=True, retries=1):
url = config["ollama"]["base_url"] + "/api/pull"
json_data = {"model": model_name, "stream": stream}
for attempt in range(retries):
try:
async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=1800)) as session: # Increased timeout for model pulling
async with session.post(url, json=json_data) as response:
if stream:
# Handle streaming response
async for chunk in response.content.iter_chunked(1024):
if chunk:
st.info(f"Received chunk: {chunk.decode('utf-8')}")
else:
json_response = await response.json()
print(json_response)
if json_response.get("error", False):
return json_response["error"]
else:
st.session_state.model_options = list_ollama_models()
return f"Pull of {model_name} finished."
return "Pulled"
except asyncio.TimeoutError:
st.warning(f"Timeout on attempt {attempt + 1}. Retrying...")
except Exception as e:
st.error(f"Error: {str(e)}")
break # Break on non-timeout errors
return f"Failed to pull {model_name} after {retries} attempts."
# Function to trigger the async pull (can be run in the event loop)
def pull_model_in_background(model_name, stream=False):
try:
# Check if there's already an event loop running
loop = asyncio.get_running_loop()
except RuntimeError: # If no loop is running, start a new one
loop = None
#st.info(f"Pulling {model_name}...")
if loop and loop.is_running():
# If an event loop is already running, create a task for the async function
return asyncio.create_task(pull_ollama_model_async(model_name, stream=stream))
else:
# Otherwise, use asyncio.run() to run it synchronously
return asyncio.run(pull_ollama_model_async(model_name, stream=stream))
def list_openai_models():
openai_api_key = os.getenv("OPENAI_API_KEY")
response = requests.get("https://api.openai.com/v1/models", headers={"Authorization": f"Bearer {openai_api_key}"}).json()
if response.get("error", False):
st.warning("Openai Error: " + response["error"]["message"])
return []
else:
return [item["id"] for item in response["data"]]
def list_ollama_models():
json_response = requests.get(url = config["ollama"]["base_url"] + "/api/tags").json()
if json_response.get("error", False):
return []
models = [model["name"] for model in json_response["models"] if "embed" not in model["name"]]
return models
def convert_bytes_to_base64(image_bytes):
return base64.b64encode(image_bytes).decode("utf-8")
def convert_bytes_to_base64_with_prefix(image_bytes):
return "data:image/jpeg;base64," + convert_bytes_to_base64(image_bytes)
def get_timestamp():
return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
def get_avatar(sender_type):
if sender_type == "user":
return "chat_icons/user_image.png"
else:
return "chat_icons/bot_image.png"