puuuuush
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@@ -1,7 +1,9 @@
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import os, pymupdf, whisper, json
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import cv2
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import psycopg2
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import pytesseract
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import ollama
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def read_files(path, output, filetypes=None):
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@@ -40,3 +42,20 @@ def extract_image_content(path):
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pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
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img = cv2.imread(path)
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return pytesseract.image_to_string(img)
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def prompt_embedding(prompt):
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embedding = ollama.embeddings(model="mxbai-embed-large", prompt=prompt)
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conn = psycopg2.connect(
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dbname="embeddings",
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user="python",
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password="PasswordPassword123",
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host="localhost",
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port="5555"
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)
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cur = conn.cursor()
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cur.execute(f"select id, filepath, embedding, embedding <-> {embedding} as distance from dbtable order by distance limit 1;")
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result = cur.fetchall()
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print(result)
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@@ -0,0 +1,60 @@
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import pymupdf
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import os
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import lib
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import json
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def retrieve_file_contents(path):
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file_extraction_functions = {
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"pdf": lambda path: lib.extract_pdf_content(path),
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"jpg": lambda path: lib.extract_image_content(path),
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"png": lambda path: lib.extract_image_content(path),
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"txt": lambda path: lib.extract_pdf_content(path),
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"mp3": lambda path: lib.extract_mp3_content(path),
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}
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lib.read_files(path, files := [])
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contents = []
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for file in files:
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content = file_extraction_functions[file[0]](file[1])
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contents.append({
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"type": file[0],
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"path": file[1],
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"filename": file[2],
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"content": content
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})
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return contents
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def reload_files():
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path = input("Please provider path to folder: ")
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pass
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def add_files():
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path = input("Please provider path to folder: ")
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pass
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def prompt_cycle():
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while True:
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prompt = input("Please enter prompt: ")
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lib.prompt_embedding(prompt)
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def get_user_action():
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user_action = input("Reload Files (r), Add Files (a), Prompt (p): ")
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{
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"r": lambda: reload_files(),
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"a": lambda: add_files(),
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"p": lambda: prompt_cycle()
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}[user_action]()
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# contents = retrieve_file_contents("C:\\SoftwareEng")
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# print(json.dumps(contents, indent="\t"))
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get_user_action()
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