mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
58 lines
1.3 KiB
Python
58 lines
1.3 KiB
Python
import requests
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import spacy
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# Enter the Machine where the LLM is hosted
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LLM_MACHINE_IP = ""
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# This is the URL of text-generation-webui
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URL = f"http://{LLM_MACHINE_IP}:5000/api/v1/generate"
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headers = {
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"Content-Type": "application/json"
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}
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def split_text_file(filename, token_count):
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nlp = spacy.load('en_core_web_md')
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with open(filename, 'r') as file:
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text = file.read()
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doc = nlp(text)
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total_tokens = len(doc)
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parts = []
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start_index = 0
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while start_index < total_tokens:
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end_index = start_index + token_count
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part_tokens = doc[start_index:end_index - 5]
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part = ' '.join(token.text for token in part_tokens)
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parts.append(part)
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start_index = end_index
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return parts
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final_summary = ""
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parts = split_text_file("transcript.txt", 1600)
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for part in parts:
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prompt = f"""
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### Human:
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Given the following text, distill the most important information
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into a short summary: {part}
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### Assistant:
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"""
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data = {
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"prompt": prompt
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}
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try:
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response = requests.post(URL, headers=headers, json=data)
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print(response.json())
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except Exception as e:
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print(str(e))
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with open("summary.txt", "w") as sum:
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sum.write(" ".join(final_summary))
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