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import requests | |
import shutil,os,re | |
import datetime | |
# Searching for the videos | |
def search_pexels(keyword, api_key, orientation='potrait', size='medium', endpoint='videos', num_pages=50): | |
if orientation not in ['potrait', 'landscape', 'square']: | |
raise Exception("Error! orientation must be one of {'square', 'landscape', 'potrait'}") | |
if size not in ['medium', 'small', 'large']: | |
raise Exception("Error! size must be one of ['medium', 'small', 'large']") | |
base_url = 'https://api.pexels.com/' | |
headers = { | |
'Authorization': f'{api_key}' | |
} | |
url = f'{base_url}{endpoint}/search?query={keyword}&per_page={num_pages}&orientation={orientation}&size={size}' | |
response = requests.get(url, headers=headers) | |
# Check if request was successful (status code 200) | |
if response.status_code == 200: | |
data = response.json() | |
return data | |
else: | |
print(f'Error: {response.status_code}') | |
# Video download function | |
def download_video(data, parent_path, height, width, links, i): | |
for x in data['videos'] : | |
if x['id'] in links: | |
continue | |
vid = x['video_files'] | |
for v in vid: | |
if v['height'] == height and v['width'] == width : | |
with open(f"{os.path.join(parent_path,str(i) + '_' + str(v['id']))}.mp4", 'bw') as f: | |
f.write(requests.get(v['link']).content) | |
print("Sucessfully saved video in", os.path.join(parent_path,str(i) + '_' + str(v['id'])) + '.mp4') | |
return x['id'] | |
def generate_voice(text, model, tokenizer): | |
speeches = [] | |
for x in text: | |
inputs = tokenizer(x, return_tensors="pt") | |
with torch.no_grad(): | |
output = model(**inputs).waveform | |
speeches.append(output) | |
return speeches | |
# Utilizing the LLMs to find the relevant videos | |
def generate_videos(text, api_key, orientation, height, width, model, tokenizer): | |
links = [] | |
try : | |
# Split the paragraph by sentences | |
sentences = list(filter(None,[x.strip() for x in re.split(r'[^A-Za-z0-9 -]', text)])) | |
# Create directory with the name | |
di = str(datetime.datetime.now()) | |
if os.path.exists(di): | |
shutil.rmtree(di) | |
os.mkdir(di) | |
# Generate video for every sentence | |
print("Keyword :") | |
for i,s in enumerate(sentences): | |
# keyword = sum_llm_chain.run(s) | |
print(i+1, ":", s) | |
data = search_pexels(s, api_key, orientation.lower()) | |
link = download_video(data, di, height, width, links,i) | |
links.append(link) | |
speeches = generate_voice(sentences, model, tokenizer) | |
sf.write("x.wav", torch.cat(speeches, 1)[0], 16500) | |
print("Success! videos has been generated") | |
except Exception as e : | |
print("Error! Failed generating videos") | |
print(e) | |
return di, sentences | |