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import json
import logging
import time
import requests
from langchain.llms import Clarifai
from global_config import GlobalConfig
logging.basicConfig(
level=GlobalConfig.LOG_LEVEL,
format='%(asctime)s - %(message)s',
)
llm = None
def get_llm(use_gpt: bool) -> Clarifai:
"""
Get a large language model.
:param use_gpt: True if GPT-3.5 is required; False is Llama 2 is required
"""
if use_gpt:
_ = Clarifai(
pat=GlobalConfig.CLARIFAI_PAT,
user_id=GlobalConfig.CLARIFAI_USER_ID_GPT,
app_id=GlobalConfig.CLARIFAI_APP_ID_GPT,
model_id=GlobalConfig.CLARIFAI_MODEL_ID_GPT,
verbose=True,
# temperature=0.1,
)
else:
_ = Clarifai(
pat=GlobalConfig.CLARIFAI_PAT,
user_id=GlobalConfig.CLARIFAI_USER_ID,
app_id=GlobalConfig.CLARIFAI_APP_ID,
model_id=GlobalConfig.CLARIFAI_MODEL_ID,
verbose=True,
# temperature=0.1,
)
# print(llm)
return _
def generate_slides_content(topic: str) -> str:
"""
Generate the outline/contents of slides for a presentation on a given topic.
:param topic: Topic/subject matter/idea on which slides are to be generated
:return: The content in JSON format
"""
# global prompt
global llm
with open(GlobalConfig.SLIDES_TEMPLATE_FILE, 'r') as in_file:
template_txt = in_file.read().strip()
template_txt = template_txt.replace('<REPLACE_PLACEHOLDER>', topic)
if llm is None:
llm = get_llm(use_gpt=True)
slides_content = llm(template_txt, verbose=True)
return slides_content
def get_ai_image(text: str) -> str:
"""
Get a Stable Diffusion-generated image based on a given text.
:param text: The input text
:return: The Base 64-encoded image
"""
url = f'''https://api.clarifai.com/v2/users/{GlobalConfig.CLARIFAI_USER_ID_SD}/apps/{GlobalConfig.CLARIFAI_APP_ID_SD}/models/{GlobalConfig.CLARIFAI_MODEL_ID_SD}/versions/{GlobalConfig.CLARIFAI_MODEL_VERSION_ID_SD}/outputs'''
headers = {
"Content-Type": "application/json",
"Authorization": f'Key {GlobalConfig.CLARIFAI_PAT}'
}
data = {
"inputs": [
{
"data": {
"text": {
"raw": text
}
}
}
]
}
# print('*** AI image generator...')
# print(url)
start = time.time()
response = requests.post(
url=url,
headers=headers,
data=json.dumps(data)
)
stop = time.time()
# print('Response:', response, response.status_code)
logging.debug('Image generation took', stop - start, 'seconds')
img_data = ''
if response.ok:
# print('*** Clarifai SDXL request: Response OK')
json_data = json.loads(response.text)
img_data = json_data['outputs'][0]['data']['image']['base64']
else:
logging.error('*** Image generation failed:', response.text)
return img_data
if __name__ == '__main__':
# results = get_related_websites('5G AI WiFi 6')
#
# for a_result in results.results:
# print(a_result.title, a_result.url, a_result.extract)
# get_ai_image('A talk on AI, covering pros and cons')
pass
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