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96 lines
3.3 KiB
Python
96 lines
3.3 KiB
Python
import openai
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import textwrap
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import streamlit as st
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import modules.utilities as util
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import modules.language as language
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import GPT
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import modules.INFO as INFO
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API_KEY = util.read_file(r'.user\API-KEYS.txt').strip()
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openai.api_key = API_KEY
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SESSION_LANG = st.session_state['SESSION_LANGUAGE']
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_ = language.set_language()
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def build(chunk_size=4000):
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openai.api_key = API_KEY
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all_text = util.read_file(r'.user\input.txt')
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# split text into smaller chunk of 4000 char each
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chunks = textwrap.wrap(all_text, chunk_size)
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chunk_count = len(chunks)
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result = []
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for idx, chunk in enumerate(chunks):
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embedding = GPT.gpt_tools.embedding(chunk.encode(encoding='ASCII', errors='ignore').decode())
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info = {'content': chunk, 'vector': embedding}
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print(info, '\n\n\n')
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result.append(info)
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# return index one at the time
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yield idx, chunk_count
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util.write_json(result, r'.user\brain-data.json')
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def run(query, model, prompt_file, isQuestion, params, info_file=None):
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if isQuestion:
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data = util.read_json(INFO.BRAIN_DATA)
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results = GPT.gpt_tools.search_chunks(query, data, params.chunk_count)
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answers = []
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for result in results:
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my_info = util.read_file(info_file)
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prompt = util.read_file(prompt_file)
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prompt = prompt.replace('<<INFO>>', result['content'])
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prompt = prompt.replace('<<QS>>', query)
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prompt = prompt.replace('<<MY-INFO>>', my_info)
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if model == 'gpt-3.5-turbo':
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answer = GPT.gpt_tools.gpt35(prompt, params)
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else:
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answer = GPT.gpt_tools.gpt3(prompt, model, params)
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answers.append(answer)
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all_response = '\n\n'.join(answers)
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else:
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chunks = textwrap.wrap(query, 10000)
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responses = []
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for chunk in chunks:
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prompt = util.read_file(prompt_file).replace('<<DATA>>', chunk)
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if model == 'gpt-3.5-turbo':
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response = GPT.gpt_tools.gpt35(prompt, params)
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else:
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response = GPT.gpt_tools.gpt3(prompt, model, params)
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responses.append(response)
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all_response = '\n\n'.join(responses)
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return all_response
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def get_stream_prompt(query, prompt_file, isQuestion, info_file=None):
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openai.api_key = API_KEY
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if isQuestion:
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data = util.read_json(INFO.BRAIN_DATA)
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if data:
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result = GPT.gpt_tools.search_chunks(query, data, count=1)
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my_info = util.read_file(info_file)
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prompt = util.read_file(prompt_file)
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prompt = prompt.replace('<<INFO>>', result[0]['content'])
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prompt = prompt.replace('<<QS>>', query)
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prompt = prompt.replace('<<MY-INFO>>', my_info)
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else:
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prompt = ''
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else:
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chunk = textwrap.wrap(query, 10000)[0]
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prompt = util.read_file(prompt_file).replace('<<DATA>>', chunk)
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return prompt
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def run_stream(query, model, prompt_file, isQuestion, params, info_file=None):
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prompt = get_stream_prompt(query, prompt_file, isQuestion, info_file)
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if model == 'gpt-3.5-turbo':
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client = GPT.gpt_tools.gpt35_stream(prompt, params)
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else:
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client = GPT.gpt_tools.gpt3_stream(prompt, model, params)
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return client
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