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Blogen-V.000.0.1 Added features,Cleanup. WIP

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This commit is contained in:
AjaySi
2023-12-09 18:07:18 +05:30
parent edc468f4aa
commit eaf13c2d16
164 changed files with 1859 additions and 71990 deletions
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89
lib/gpt_providers/openai_gpt_provider.py
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@@ -20,7 +20,12 @@ import tempfile
from html2image import Html2Image
import datetime
from PIL import Image
import moviepy.editor as mp
import requests
from moviepy.editor import AudioFileClip
from concurrent.futures import ThreadPoolExecutor
from ..gpt_online_researcher import do_online_research
from loguru import logger
logger.remove()
@@ -29,8 +34,6 @@ logger.add(sys.stdout,
format="<level>{level}</level>|<green>{file}:{line}:{function}</green>| {message}"
)
def analyze_and_extract_details_from_image(image_path):
"""
Analyzes an image using OpenAI's Vision API and extracts Alt Text, Description, Title, and Caption.
@@ -103,12 +106,14 @@ def analyze_and_extract_details_from_image(image_path):
return image_details
except requests.RequestException as e:
sys.exit(f"Error: Failed to communicate with OpenAI API. Error: {e}")
#sys.exit(f"Error: GPT-Vision: Failed to communicate with OpenAI API. Error: {e}")
logger.error(f"Error: GPT-Vision: Failed to communicate with OpenAI API. Error: {e}")
except Exception as e:
sys.exit(f"Error occurred: {e}")
#sys.exit(f"Error occurred- GPT-Vision: {e}")
logger.error(f"Error occurred- GPT-Vision: {e}")
def openai_chatgpt(prompt, model="gpt-3.5-turbo-16k", temperature=0.2, max_tokens=8192, top_p=0.9, n=1):
def openai_chatgpt(prompt, model="gpt-4-1106-preview", temperature=0.2, max_tokens=4096, top_p=0.9, n=1):
"""
Wrapper function for openai chat Completion
"""
@@ -119,6 +124,10 @@ def openai_chatgpt(prompt, model="gpt-3.5-turbo-16k", temperature=0.2, max_token
try:
client = OpenAI()
except Exception as err:
print("Error: OpenAI Client.")
exit(1)
try:
# using OpenAI's Completion module that helps execute any tasks involving text
response = client.chat.completions.create(
# model name used, there are many other models available under the umbrella of GPT-3
@@ -142,6 +151,8 @@ def openai_chatgpt(prompt, model="gpt-3.5-turbo-16k", temperature=0.2, max_token
except openai.RateLimitError as e:
#Handle rate limit error (we recommend using exponential backoff)
SystemError(f"OpenAI API request exceeded rate limit: {e}")
except Exception as err:
SystemError(f"OpenAI client Error: {err}")
return response.choices[0].message.content
@@ -231,39 +242,57 @@ def generate_dalle3_images(img_prompt, image_dir, size="1024x1024", quality="hd"
return img_path
def speech_to_text(video_url):
""" Common openai function for speech to text. """
client = OpenAI()
def speech_to_text(video_url, output_path='.'):
""" Transcribes speech to text from a YouTube video URL. """
try:
# Download YouTube video
logger.info(f"Download YouTube video: {video_url}")
# Create a YouTube object
print(f"Accessing YouTube URL: {video_url}")
yt = YouTube(video_url)
stream = yt.streams.filter(only_audio=True).first()
# Save the video in a temporary file
logger.info(f"Finished Downloading, Saving video for transcription.")
with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as temp_file:
temp_file_name = temp_file.name
# Select the highest quality audio stream
print("Fetching audio stream. Select the highest quality audio stream")
audio_stream = yt.streams.filter(only_audio=True).first()
stream.download(output_path=os.path.dirname(temp_file_name), filename=os.path.basename(temp_file_name))
try:
# Transcribe the video using OpenAI's Whisper API
logger.info(f"Transcribe the video using OpenAI's Whisper API")
with open(temp_file_name, "rb") as audio_file:
if audio_stream is None:
print("No audio stream found for this video.")
return
else:
# Download the audio stream
print(f"Downloading audio for: {yt.title}")
audio_file = audio_stream.download(output_path)
print(f"Downloaded: {yt.title} to {output_path}")
try:
# Check if the audio file size is less than 24MB
max_file_size = 24 * 1024 * 1024 # 24MB in bytes
file_size = os.path.getsize(audio_file)
if file_size > max_file_size:
print("Error: File size exceeds 24MB limit.")
exit(1)
# File uploads are currently limited to 25 MB and the following input
# file types are supported: mp3, mp4, mpeg, mpga, m4a, wav, and webm.
try:
client = OpenAI()
except Exception as err:
SystemExit("Unable to get openai client object: {err}")
print("Transcribing using Openai whisper.")
transcript = client.audio.transcriptions.create(
model="whisper-1",
file=audio_file
model="whisper-1",
file=open(audio_file, "rb"),
response_format="text"
)
except Exception as err:
logger.error(f"Failed to transcribe using whisper model: {err}")
logger.info("Finished Transcribing. Creating a blog from the transcript.")
# Remove the temporary file after transcription
os.remove(temp_file_name)
return(transcript)
return transcript
except Exception as err:
print(f"Failed in whisper transcription: {err}")
exit(1)
except Exception as e:
logger.error(f"Error: speech-to-text, Failed to transcribe url: {video_url} with error: {e}")
print(f"YT video download, An error occurred: {e}")
exit(1)
os.remove(audio_file)
# The idea is to download images from other blogs and recreate from it.