BREAKING CHANGE: Remove Console Apps

console_app/brain.py

@@ -1,73 +0,0 @@
-import openai
-import numpy as np
-import textwrap
-import utilities
-
-openai.api_key = utilities.open_file(r'.user\API-KEYS.txt').strip()
-BRAIN_DATA = utilities.read_json_file(r'.user\brain-data.json')
-
-# this function compare similarity between two vectors. 
-# The higher value the dot product have, the more alike between these vectors
-def similarity(v1, v2):
-    return np.dot(v1, v2)
-
-def search_chunks(text, data, count=1):
-    vector = utilities.embedding(text)
-    points = []
-
-    for item in data:
-        # compare search terms with brain-data
-        point = similarity(vector, item['vector'])
-        points.append({
-            'content': item['content'],
-            'point': point
-        })
-    # sort points base on decendent order
-    ordered = sorted(points, key=lambda d: d['point'], reverse=True)
-
-    return ordered[0:count]
-
-def gpt3(prompt, model='text-davinci-003'):
-    response = openai.Completion.create(
-        model= model,
-        prompt=prompt,
-        temperature=0.1,
-        max_tokens=1000,
-        top_p=1,
-        frequency_penalty=0,
-        presence_penalty=0
-    )
-    text = response['choices'][0]['text'].strip()
-    return text
-
-def main():
-    while True:
-
-        query = input('\n\nAsk brain: ')
-        results = search_chunks(query, BRAIN_DATA)
-        answers = []
-        answers_count = 0
-        for result in results:
-            my_info = utilities.open_file(r'prompt\my-info.txt')
-
-            prompt = utilities.open_file(r'prompt\question.txt')
-            prompt = prompt.replace('<<INFO>>', result['content'])
-            prompt = prompt.replace('<<QS>>', query)
-            prompt = prompt.replace('<<MY-INFO>>', my_info)
-
-            answer = gpt3(prompt, model='text-davinci-003')
-            answers.append(answer)
-            answers_count += 1
-
-        all_answers = '\n\n'.join(answers)
-        print('\n\n============ANSWER============\n\n', all_answers)
-
-        chunks = textwrap.wrap(all_answers, 10000)
-        end = []
-        for chunk in chunks:
-            prompt = utilities.open_file(r'prompt\summarize.txt').replace('<<SUM>>', chunk)
-            summary = gpt3(prompt, model='text-curie-001')
-            end.append(summary)
-        print('\n\n============SUMMRY============\n\n', '\n\n'.join(end))
-if __name__ == '__main__':
-    main()

console_app/build_brain.py

@@ -1,25 +0,0 @@
-import openai
-import textwrap
-import utilities
-
-
-openai.api_key = utilities.open_file(r'.user\API-KEYS.txt').strip()
-
-def main():
-    all_text = utilities.open_file(r'.user\input.txt')
-
-    # split text into smaller chunk of 4000 char each
-    chunks = textwrap.wrap(all_text, 4000)
-
-    result = []
-
-    for chunk in chunks:
-        embedding = utilities.embedding(chunk.encode(encoding='ASCII', errors='ignore').decode())
-        info = {'content':chunk, 'vector':embedding}
-        print(info, '\n\n\n')
-        result.append(info)
-
-    utilities.write_json_file(result, r'.user\brain-data.json')
-
-if __name__ == '__main__':
-    main()

console_app/check_update.py

@@ -1,44 +0,0 @@
-import os
-import time
-import utilities
-
-file_path = r'.user\input.txt'
-temp_file = r'.user\input_last-run.temp'
-sig_file = r'.user\input_sig.temp'
-
-def compare_time(t1, t2):
-    return t1 == t2
-
-def write_sig(bool):
-    utilities.write_file(bool, sig_file)
-
-def check():
-    if os.path.exists(file_path):
-        # get modification time of the file
-        mod_time = os.path.getmtime(file_path)
-
-        # convert the modification time to readable format
-        read_mod_time = time.ctime(mod_time)
-
-        if os.path.exists(temp_file):
-            temp_info = utilities.open_file(temp_file)
-            if compare_time(read_mod_time, temp_info):
-                write_sig('not updated')
-                print('File has not been updated.')
-            else:
-                print('File has been updated.')
-                utilities.write_file(read_mod_time, temp_file)
-                write_sig('updated')
-        else:
-            print('Temp file not exist, writing temp file...')
-            # write to temp file
-            utilities.write_file(read_mod_time, temp_file)
-            write_sig('not updated')
-    else:
-        raise FileNotFoundError(f'File: {file_path} does not exist.')
-
-def main():
-    check()
-    
-if __name__ == '__main__':
-    main()

console_app/run-brain.bat

@@ -1,27 +0,0 @@
-@echo off
-cd..
-echo Activating Virtural environment...
-call .\venv\Scripts\activate
-
-rem checking if input.txt is updated
-python console_app\check_update.py
-
-setlocal enabledelayedexpansion
-set "tempFile=.user\input_sig.temp"
-
-for /f "usebackq delims=" %%a in ("%tempFile%") do (
-    set "tempValue=%%a"
-)
-
-if "%tempValue%" == "not updated" (
-    goto end
-) else (
-    call batch-programs\run-build-brain.bat
-    cls
-    echo Brain updated!
-)
-
-
-:end
-echo running brain...
-python console_app\brain.py

console_app/utilities.py

@@ -1,24 +0,0 @@
-import json
-import openai
-
-def open_file(filepath):
-    with open(filepath, 'r', encoding='utf-8') as file:
-        return file.read()
-
-def write_file(content, filepath):
-    with open(filepath, 'w') as file:
-        file.write(content)
-
-def write_json_file(content, filepath):
-    with open(filepath, 'w') as file:
-        json.dump(content, file, indent=2)
-
-def read_json_file(filepath):
-    with open(filepath, 'r') as file:
-        return json.load(file)
-
-# return a list of vectors
-def embedding(content, engine='text-embedding-ada-002'):
-    response = openai.Embedding.create(input=content, engine=engine)
-    vector = response['data'][0]['embedding']
-    return vector