Upload 36 files

AAmain.py

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+import subprocess
+
+# Function to call a script
+def call_script(script_name):
+    try:
+        subprocess.run(['python', f'{script_name}.py'], check=True)
+    except subprocess.CalledProcessError as e:
+        print(f"Error running script {script_name}: {e}")
+
+# Call scripts in order
+call_script('backend1')
+call_script('backend2')
+call_script('breakdown1')
+call_script('textto')
+call_script('mod8')
+call_script('mod8l2')
+call_script('mod8l3')
+call_script('mod8l4')
+call_script('mod8l5')
+call_script('allcombo')
+call_script('allcombo2')
+call_script('allcombo3')
+call_script('allcombo4')
+call_script('allcombo5')
+call_script('allcombo6')
+call_script('allcombo7')
+call_script('allcombo8')
+call_script('allcombo9')
+call_script('allcombo10')
+call_script('space')
+call_script('finalloop2')
+call_script('col')
+call_script('finalloop')
+call_script('looploop2all')

allcombo.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text1combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum1.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo10.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text10combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum10.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo2.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text2combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum2.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo3.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text3combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum3.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo4.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text4combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum4.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo5.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text5combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum5.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo6.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text6combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum6.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo7.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text7combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum7.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo8.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text8combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum8.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

allcombo9.py

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+import csv
+import os
+
+# Function to extract the first column from a CSV file
+def extract_first_column(csv_file):
+    with open(csv_file, 'r') as file:
+        reader = csv.reader(file)
+        first_column = [int(row[0]) for row in reader]
+    return first_column
+
+# Directory containing combo CSV files
+csv_directory = os.path.dirname(os.path.abspath(__file__))
+
+# List to store the first columns from each CSV
+all_first_columns = []
+
+# Loop through each combo CSV file
+for i in range(1, 7):  # Assuming combo files are named combo1.csv to combo6.csv
+    csv_file_path = os.path.join(csv_directory, f'text9combo{i}.csv')
+    first_column = extract_first_column(csv_file_path)
+    all_first_columns.append(first_column)
+
+# Transpose the list of lists to get a list of columns
+all_first_columns_transposed = list(map(list, zip(*all_first_columns)))
+
+# Save the transposed result into a new CSV file
+output_csv_path = os.path.join(csv_directory, 'loopnum9.csv')
+with open(output_csv_path, 'w', newline='') as csvfile:
+    writer = csv.writer(csvfile)
+    writer.writerows(all_first_columns_transposed)
+
+print(f"Combined first columns saved to {output_csv_path}")

app.py

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+# streamlit_app.py
+import streamlit as st
+import requests
+import csv
+from datetime import datetime
+import subprocess
+
+# Define Streamlit app
+st.title("Conversation Generator")
+
+@st.cache(allow_output_mutation=True)
+def generate_conversation(prompt):
+    try:
+        # Introduce slight variations in the prompt
+        prompt_variation = prompt + str(hash(prompt))[:3]
+
+        # Adjust temperature for more diverse responses
+        response = requests.post('https://api-inference.huggingface.co/models/facebook/blenderbot-400M-distill', json={
+            "inputs": prompt_variation,
+            "options": {"temperature": 0.8}  # Adjust as needed
+        })
+
+        conversation = response.json()["generated_text"]
+        return conversation
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+def save_to_csv(prompt, conversation):
+    timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+    filename = f"info.csv"
+
+    with open(filename, mode='w', newline='', encoding='utf-8') as csv_file:
+        csv_writer = csv.writer(csv_file)
+        csv_writer.writerow(['Prompt', 'Generated Conversation'])
+        csv_writer.writerow([prompt, conversation])
+
+    return filename
+
+# Load index.html content
+with open("index.html", "r", encoding="utf-8") as html_file:
+    index_html_content = html_file.read()
+
+# Embed HTML content in Streamlit
+st.markdown(index_html_content, unsafe_allow_html=True)
+
+# Define Streamlit UI
+prompt = st.text_area("Enter prompt:")
+if st.button("Generate and Display"):
+    conversation = generate_conversation(prompt)
+    csv_filename = save_to_csv(prompt, conversation)
+    st.write("Generated Conversation:")
+    st.write(conversation)
+    st.write("CSV file saved:", csv_filename)
+
+if st.button("Run AAMain.py"):
+    try:
+        subprocess.run(["python", "AAmain.py"])
+        st.success("AAmain.py process started successfully.")
+    except Exception as e:
+        st.error(f"Error: {str(e)}")

app2.py

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+from fastapi import FastAPI, Request, Form
+from fastapi.templating import Jinja2Templates
+import gpt_2_simple as gpt2
+from datetime import datetime
+import csv
+
+app = FastAPI()
+templates = Jinja2Templates(directory="templates")
+
+# Download the GPT-2 model if not already downloaded
+gpt2.download_gpt2(model_name="124M")
+
+# Load the GPT-2 model
+sess = gpt2.start_tf_sess()
+gpt2.load_gpt2(sess, model_name="124M")
+
+async def generate_conversation(prompt):
+    try:
+        conversation = gpt2.generate(sess, prefix=prompt, length=300, temperature=0.7, return_as_list=True)[0]
+        return conversation
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+def save_to_csv(prompt, conversation):
+    timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+    filename = f"info.csv"
+
+    with open(filename, mode='w', newline='', encoding='utf-8') as csv_file:
+        csv_writer = csv.writer(csv_file)
+        csv_writer.writerow(['Prompt', 'Generated Conversation'])
+        csv_writer.writerow([prompt, conversation])
+
+    return filename
+
+@app.get("/")
+def read_form(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
+
+@app.post("/")
+async def generate_and_display(request: Request, prompt: str = Form(...)):
+    conversation = await generate_conversation(prompt)
+    csv_filename = save_to_csv(prompt, conversation)
+    return templates.TemplateResponse("index.html", {"request": request, "prompt": prompt, "conversation": conversation, "csv_filename": csv_filename})
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="127.0.0.1", port=8000)

app3.py

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+from fastapi import FastAPI, Request, Form
+from fastapi.templating import Jinja2Templates
+import csv
+from datetime import datetime  # Used for generating unique filenames
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Install these libraries if you haven't already:
+# pip install transformers accelerate
+
+app = FastAPI()
+templates = Jinja2Templates(directory="templates")
+
+# Load GPT-J 6B model and tokenizer
+model_name = "EleutherAI/gpt-j-6B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+async def generate_conversation(prompt):
+    try:
+        # Tokenize the prompt
+        inputs = tokenizer(prompt, return_tensors="pt")
+
+        # Generate response using local model
+        output = model.generate(**inputs)
+        conversation = tokenizer.decode(output[0], skip_special_tokens=True)
+
+        return conversation
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+def save_to_csv(prompt, conversation):
+    timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+    filename = f"info.csv"
+
+    with open(filename, mode='w', newline='', encoding='utf-8') as csv_file:
+        csv_writer = csv.writer(csv_file)
+        csv_writer.writerow(['Prompt', 'Generated Conversation'])
+        csv_writer.writerow([prompt, conversation])
+
+    return filename
+
+@app.get("/")
+def read_form(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
+
+@app.post("/")
+async def generate_and_display(request: Request, prompt: str = Form(...)):
+    conversation = await generate_conversation(prompt)
+    csv_filename = save_to_csv(prompt, conversation)
+    return templates.TemplateResponse("index.html", {"request": request, "prompt": prompt, "conversation": conversation, "csv_filename": csv_filename})
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="127.0.0.1", port=8000)

appp.py

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+from fastapi import FastAPI, Request, Form
+from fastapi.templating import Jinja2Templates
+import httpx
+import csv
+from datetime import datetime
+import subprocess
+
+app = FastAPI()
+templates = Jinja2Templates(directory="templates")
+
+async def generate_conversation(prompt):
+    try:
+        # Introduce slight variations in the prompt
+        prompt_variation = prompt + str(hash(prompt))[:3]
+
+        # Adjust temperature for more diverse responses
+        async with httpx.AsyncClient() as client:
+            response = await client.post('https://api-inference.huggingface.co/models/facebook/blenderbot-400M-distill', json={
+                "inputs": prompt_variation,
+                "options": {"temperature": 0.8}  # Adjust as needed
+            })
+
+        conversation = response.json()["generated_text"]
+        return conversation
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+
+def save_to_csv(prompt, conversation):
+    timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+    filename = f"info.csv"
+
+    with open(filename, mode='w', newline='', encoding='utf-8') as csv_file:
+        csv_writer = csv.writer(csv_file)
+        csv_writer.writerow(['Prompt', 'Generated Conversation'])
+        csv_writer.writerow([prompt, conversation])
+
+    return filename
+
+
+def run_aamain_script():
+    try:
+        # Run the AAmain.py script
+        subprocess.run(["python", "AAmain.py"], check=True)
+        return "AAmain.py script executed successfully"
+    except subprocess.CalledProcessError as e:
+        return f"Error executing AAmain.py script: {str(e)}"
+
+
+@app.get("/")
+def read_form(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
+
+@app.post("/generate_ai")
+async def generate_ai(request: Request, ai_prompt: str = Form(...)):
+    # Handle generation logic
+    conversation = await generate_conversation(ai_prompt)
+    csv_filename = save_to_csv(ai_prompt, conversation)
+    return templates.TemplateResponse("index.html", {"request": request, "prompt": ai_prompt, "conversation": conversation, "csv_filename": csv_filename})
+
+@app.post("/run_aamain")
+async def run_aamain(request: Request):
+    # Handle running AAmain.py script
+    result = run_aamain_script()
+    return templates.TemplateResponse("index.html", {"request": request, "aamain_result": result})
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="127.0.0.1", port=8000)

appself.py

@@ -0,0 +1,75 @@
+from fastapi import FastAPI, Request, Form
+from fastapi.templating import Jinja2Templates
+import httpx
+import csv
+from datetime import datetime
+from fastapi.staticfiles import StaticFiles
+import subprocess
+
+app = FastAPI()
+
+CSV_FILE_PATH0 = 'info.csv'
+PYTHON_SCRIPT_PATH0 = 'AAmain.py'
+
+# Set up static files
+app.mount("/static", StaticFiles(directory="."), name="static")
+
+templates = Jinja2Templates(directory="templates")
+
+def generate_conversation(prompt):
+    try:
+        # Introduce slight variations in the prompt
+        prompt_variation = prompt + str(hash(prompt))[:3]
+
+        # Adjust temperature for more diverse responses
+        with httpx.Client() as client:
+            response = client.post('https://api-inference.huggingface.co/models/facebook/blenderbot-400M-distill', json={
+                "inputs": prompt_variation,
+                "options": {"temperature": 0.8}  # Adjust as needed
+            })
+
+        conversation = response.json()["generated_text"]
+        return conversation
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+def save_to_csv(prompt, conversation):
+    timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+    filename = f"info.csv"
+
+    with open(filename, mode='w', newline='', encoding='utf-8') as csv_file:
+        csv_writer = csv.writer(csv_file)
+        csv_writer.writerow(['Prompt', 'Generated Conversation'])
+        csv_writer.writerow([prompt, conversation])
+
+    return filename
+
+@app.get("/")
+def read_form(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
+
+@app.post("/")
+async def generate_and_display(request: Request, prompt: str = Form(...)):
+    conversation = generate_conversation(prompt)
+    csv_filename = save_to_csv(prompt, conversation)
+    
+    return templates.TemplateResponse("index.html", {"request": request, "prompt": prompt, "conversation": conversation, "csv_filename": csv_filename})
+
+# New route for running AAmain.py
+@app.post("/run_aamain")
+async def run_aamain(csv_filename: str = Form(...)):
+    subprocess.run(["python", "AAmain.py", csv_filename])  # Adjust arguments as needed
+    return {"message": "AAmain.py process started successfully."}
+
+# New route for generating AI
+@app.post("/generate_ai")
+async def generate_ai(prompt: str = Form(...)):
+    conversation = generate_conversation(prompt)
+    csv_filename = save_to_csv(prompt, conversation)
+    
+    return {"prompt": prompt, "conversation": conversation, "csv_filename": csv_filename}
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="127.0.0.1", port=8000)

backend1.py

@@ -0,0 +1,43 @@
+import csv
+
+def load_word_database(database_filename):
+    with open(database_filename, mode='r', encoding='utf-8') as database_file:
+        return set(word.strip().lower() for word in database_file)
+
+def check_generated_conversation_for_words(csv_filename, word_database):
+    words_scores = []
+    
+    with open(csv_filename, mode='r', newline='', encoding='utf-8') as csv_file:
+        csv_reader = csv.DictReader(csv_file)
+        
+        for row in csv_reader:
+            generated_conversation = row.get('Generated Conversation', '').lower()
+            word_scores = []
+
+            for word in generated_conversation.split():
+                score = 1 if word in word_database else 0
+                word_scores.append({'Word': word, 'Score': score})
+
+            words_scores.extend(word_scores)
+
+    return words_scores
+
+def save_word_scores_to_csv(word_scores, output_csv_filename):
+    with open(output_csv_filename, mode='w', newline='', encoding='utf-8') as output_csv_file:
+        csv_writer = csv.DictWriter(output_csv_file, fieldnames=['Word', 'Score'])
+        csv_writer.writeheader()
+
+        for word_score in word_scores:
+            csv_writer.writerow(word_score)
+
+def main():
+    database_filename = 'word_database.txt'
+    csv_filename = 'info.csv'  # Replace with your CSV file
+    output_csv_filename = 'word_scores.csv'
+
+    word_database = load_word_database(database_filename)
+    words_scores = check_generated_conversation_for_words(csv_filename, word_database)
+    save_word_scores_to_csv(words_scores, output_csv_filename)
+
+if __name__ == "__main__":
+    main()

backend2.py

@@ -0,0 +1,30 @@
+import csv
+
+def load_word_database(database_filename):
+    with open(database_filename, mode='r', encoding='utf-8') as database_file:
+        return set(word.strip().lower() for word in database_file)
+
+def check_generated_conversation_for_words(csv_filename, word_database):
+    with open(csv_filename, mode='r', newline='', encoding='utf-8') as csv_file:
+        csv_reader = csv.DictReader(csv_file)
+        words = []
+        for row in csv_reader:
+            generated_conversation = row.get('Generated Conversation', '').lower()
+            words.extend(word for word in generated_conversation.split() if word in word_database)
+        save_words_to_csv(words)
+
+def save_words_to_csv(words):
+    output_csv_filename = "text.csv"
+    with open(output_csv_filename, mode='w', newline='', encoding='utf-8') as output_csv_file:
+        csv_writer = csv.writer(output_csv_file)
+        csv_writer.writerows([[word] for word in words])
+
+def main():
+    database_filename = 'word_database.txt'
+    csv_filename = 'info.csv'  # Replace with your CSV file
+
+    word_database = load_word_database(database_filename)
+    check_generated_conversation_for_words(csv_filename, word_database)
+
+if __name__ == "__main__":
+    main()

backend2later.py

@@ -0,0 +1,32 @@
+import csv
+
+def load_word_database(database_filename):
+    with open(database_filename, mode='r', encoding='utf-8') as database_file:
+        return set(word.strip().lower() for word in database_file)
+
+def check_generated_conversation_for_words(csv_filename, word_database):
+    with open(csv_filename, mode='r', newline='', encoding='utf-8') as csv_file:
+        csv_reader = csv.DictReader(csv_file)
+        for row in csv_reader:
+            generated_conversation = row.get('Generated Conversation', '').lower()
+            for word in generated_conversation.split():
+                if word in word_database:
+                    save_word_to_csv(word)
+
+def save_word_to_csv(word):
+    output_csv_filename = "text.csv"
+    with open(output_csv_filename, mode='w', newline='', encoding='utf-8') as output_csv_file:
+        csv_writer = csv.writer(output_csv_file)
+        csv_writer.writerow([word])
+
+def main():
+    database_filename = 'word_database.txt'
+    csv_filename = 'info.csv'  # Replace with your CSV file
+
+    word_database = load_word_database(database_filename)
+    check_generated_conversation_for_words(csv_filename, word_database)
+
+if __name__ == "__main__":
+    main()
+
+

breakdown1.py

@@ -0,0 +1,29 @@
+import csv
+
+def process_csv(input_file, output_file):
+    with open(input_file, 'r') as csvfile:
+        reader = csv.reader(csvfile)
+        next(reader)  # Skip header row
+
+        output_data = []
+
+        for row in reader:
+            word, score = row[0], int(row[1])
+            if score == 1:
+                # Break down the word into letters and append each letter with ,1
+                for letter in word:
+                    output_data.append([letter, '1'])
+            else:
+                output_data.append([word, str(score)])
+
+    with open(output_file, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        writer.writerow(['Letter', 'Score'])
+        writer.writerows(output_data)
+
+if __name__ == "__main__":
+    input_csv = "word_scores.csv"
+    output_csv = "word_scores2.csv"
+
+    process_csv(input_csv, output_csv)
+    print(f"Conversion complete. Output saved to {output_csv}")

col.py

@@ -0,0 +1,42 @@
+import csv
+import numpy as np
+import random  # Import the random module
+
+def change_fourth_occurrence(matrix):
+    for col in range(len(matrix[0])):
+        count = 1
+        for row in range(1, len(matrix)):
+            if matrix[row][col] == matrix[row - 1][col]:
+                count += 1
+            else:
+                count = 1
+
+            if count == 4:
+                current_number = matrix[row][col]
+                
+                # Generate a random number within the range [current_number-1, current_number+1]
+                next_number = random.choice([current_number - 1, current_number + 1])
+
+                matrix[row][col] = next_number
+                count = 1
+
+    # Post-processing: Ensure there are no negative numbers in the matrix
+    matrix[matrix < 0] = 0
+
+# Read the matrix from CSV
+input_matrix = []
+with open('matrix2.csv', 'r') as file:
+    csv_reader = csv.reader(file)
+    for row in csv_reader:
+        input_matrix.append([int(num) for num in row])
+
+# Convert the matrix to a NumPy array for easy column indexing
+input_matrix = np.array(input_matrix)
+
+# Call the function to modify the matrix
+change_fourth_occurrence(input_matrix)
+
+# Write the modified matrix back to CSV
+with open('matrix5.csv', 'w', newline='') as file:
+    csv_writer = csv.writer(file)
+    csv_writer.writerows(input_matrix)

col2.py

@@ -0,0 +1,37 @@
+import csv
+
+def change_fourth_occurrence(matrix):
+    for col in range(len(matrix[0])):
+        count = 1
+        for row in range(1, len(matrix)):
+            if matrix[row][col] == matrix[row - 1][col]:
+                count += 1
+            else:
+                count = 1
+
+            if count == 4:
+                next_number = matrix[row][col] + 1
+                while next_number in matrix[:, col]:
+                    next_number += 1
+
+                matrix[row][col] = next_number
+                count = 1
+
+# Read the matrix from CSV
+input_matrix = []
+with open('matrix2.csv', 'r') as file:
+    csv_reader = csv.reader(file)
+    for row in csv_reader:
+        input_matrix.append([int(num) for num in row])
+
+# Convert the matrix to a NumPy array for easy column indexing
+import numpy as np
+input_matrix = np.array(input_matrix)
+
+# Call the function to modify the matrix
+change_fourth_occurrence(input_matrix)
+
+# Write the modified matrix back to CSV
+with open('matrix5.csv', 'w', newline='') as file:
+    csv_writer = csv.writer(file)
+    csv_writer.writerows(input_matrix)

data.py

@@ -0,0 +1,75 @@
+# Define a list of font sizes
+font_sizes = ["17px", "19px", "21px", "23px", "25px", "27px",]
+# Define a list of font sizes
+font_tops = ["11px", "11px", "13px", "13px", "15px", "15px",]
+
+# Define a list of letter spacings
+letter_spacing = [" -3px", " -2px", "-4px", "-4px", " -2px", "-4px", " -6px", " -4px", " -4px", "-2px", "6px"]
+
+# Define a list of text shadow combinations
+text_shadow = [
+    "0px 0px 1px",
+    "0px 0px 2px",
+    "1px 0px 0px",
+    "0px 0px 0px",
+    "0px 1px 0px",
+    "0px 2px 0px",
+    "0px 1px 1px",
+    "1px 1px 0px",
+    "1px 0px 1px",
+    "0px 1px 0px",
+    "0px 1px 0px"
+]
+
+# Define a list of skew options
+skew_options = [
+    "(0deg, 0deg)",
+    "(-0deg, 0deg)",
+    "(-5deg, 0deg)",
+    "(-20deg, 0deg)",
+    "(-0deg, 0deg)",
+    "(-0deg, 0deg)",
+    "(-0deg, 0deg)",
+    "(10deg, 0deg)",
+    "(15deg, 0deg)",
+    "(20deg, 0deg)",
+    "(0deg, 0deg)",
+    "(0deg, 0deg)",
+    "(0deg, 0deg)"
+]
+
+# Define a list of font styles
+font_styles = [
+    "Raleway, sans-serif",
+    "'Open Sans Condensed', sans-serif",
+    "'Roboto Condensed', sans-serif",
+    "'Poiret One', sans-serif",
+    "'Dosis', sans-serif",
+    "'Fjalla One', sans-serif",
+    "'Indie Flower', sans-serif",
+    "'Josefin Sans', sans-serif",
+    "'Roboto Slab', sans-serif",
+    "'Annie Use Your Telescope', sans-serif",
+
+]
+
+
+color_values = [
+    "#000000",  # Blue
+    "#000000",  # Blue
+    "#000000",  # Blue
+    "#000000",  # Blue
+    "#000000",  # Blue
+    "#000000",  # Orange
+    "#000000",  # Orange
+    "#5afc87",  # Orange
+    "#5afc87",  # Orange
+    "#5afc87",  # Orange
+    "#5afc87",  # Orange
+    "#5afc87",  # Orange
+    "#5afc87",  # Orange
+    "#000000",  # Orange
+    "#000000",  # Orange
+    "#000000",  # Orange
+]
+

data2.py

@@ -0,0 +1,77 @@
+
+
+
+
+# Define a list of font sizes
+font_sizes = ["17px", "19px", "21px", "23px", "25px", "27px",]
+# Define a list of font sizes
+font_tops = ["11px", "11px", "13px", "13px", "15px", "15px",]
+
+# Define a list of letter spacings
+letter_spacing = ["-6px", "-5px", "-4px", "-3px", "-2px", "-1px", "0px", "1px", "2px", "6px"]
+
+# Define a list of text shadow combinations
+text_shadow = [
+    "0px 0px 1px",
+    "0px 0px 2px",
+    "1px 0px 0px",
+    "2px 0px 0px",
+    "0px 1px 0px",
+    "0px 2px 0px",
+    "2px 1px 1px",
+    "1px 1px 2px",
+    "1px 2px 1px",
+    "2px 1px 0px",
+    "2px 2px 1px"
+]
+
+# Define a list of skew options
+skew_options = [
+    "(0deg, 0deg)",
+    "(-10deg, 0deg)",
+    "(-15deg, 0deg)",
+    "(-20deg, 0deg)",
+    "(-25deg, 0deg)",
+    "(-30deg, 0deg)",
+    "(-35deg, 0deg)",
+    "(10deg, 0deg)",
+    "(15deg, 0deg)",
+    "(20deg, 0deg)",
+    "(25deg, 0deg)",
+    "(30deg, 0deg)",
+    "(35deg, 0deg)"
+]
+
+# Define a list of font styles
+font_styles = [
+    "Raleway, sans-serif",
+    "'Open Sans Condensed', sans-serif",
+    "'Roboto Condensed', sans-serif",
+    "'Poiret One', sans-serif",
+    "'Dosis', sans-serif",
+    "'Fjalla One', sans-serif",
+    "'Indie Flower', sans-serif",
+    "'Josefin Sans', sans-serif",
+    "'Roboto Slab', sans-serif",
+    "'Righteous', sans-serif",
+    "'Yellowtail', sans-serif",
+    "'Annie Use Your Telescope', sans-serif",
+    "'Just Me Again Down Here', sans-serif",
+    "'Nixie One', sans-serif",
+    "'Unkempt', sans-serif",
+]
+
+
+color_values = [
+    "#FF0000",  # Red
+    "#00FF00",  # Green
+    "#0000FF",  # Blue
+    "#FFFF00",  # Yellow
+    "#FF00FF",  # Magenta
+    "#00FFFF",  # Cyan
+    "#FFA500",  # Orange
+    "#800080",  # Purple
+    "#008000",  # Dark Green
+    "#808080",   # Gray
+    "#000000"   # Gray
+]

finalloop.py

@@ -0,0 +1,31 @@
+import pandas as pd
+
+# Read word_scores2.csv
+word_scores = pd.read_csv('word_scores2.csv')
+
+# Read matrix5.csv
+matrix5 = pd.read_csv('matrix5.csv', header=None)
+
+# Initialize an empty matrix
+output_matrix = []
+
+# Initialize a variable to keep track of the position in matrix5
+matrix_position = 0
+
+# Iterate through each row in word_scores
+for index, row in word_scores.iterrows():
+    score = row['Score']
+    
+    # If the score is 0, add a row of zeros to the output matrix
+    if score == 0:
+        output_matrix.append([0] * 6)
+    # If the score is 1, use the corresponding row from matrix5.csv and update position
+    elif score == 1:
+        output_matrix.append(matrix5.iloc[matrix_position % len(matrix5)].tolist())
+        matrix_position += 1
+
+# Convert the output_matrix to a DataFrame
+result_output_matrix = pd.DataFrame(output_matrix, columns=['Col1', 'Col2', 'Col3', 'Col4', 'Col5', 'Col6'])
+
+# Save the result_output_matrix to a CSV file without a header
+result_output_matrix.to_csv('loopnumber.csv', header=False, index=False)

finalloop2.py

@@ -0,0 +1,26 @@
+import os
+import pandas as pd
+
+# Initialize an empty list to store loopnum dataframes
+loopnum_dataframes = []
+
+# Iterate through loopnum1 to loopnum6
+for i in range(1, 11):
+    loopnum_file = f'loopnum{i}.csv'
+    
+    # Check if the loopnum file exists before trying to read it
+    if not os.path.exists(loopnum_file):
+        print(f"Warning: {loopnum_file} not found. Skipping.")
+    else:
+        loopnum_data = pd.read_csv(loopnum_file, header=None)
+        loopnum_dataframes.append(loopnum_data)
+
+# Check if any valid loopnum files were found
+if loopnum_dataframes:
+    # Concatenate the loopnum dataframes into one dataframe
+    result_matrix2 = pd.concat(loopnum_dataframes, ignore_index=True)
+
+    # Save the result_matrix2 to a CSV file without a header
+    result_matrix2.to_csv('matrix2.csv', header=False, index=False)
+else:
+    print("No valid loopnum files found.")

finalloopneedfix.py

@@ -0,0 +1,27 @@
+import pandas as pd
+
+# Read word_scores2.csv
+word_scores = pd.read_csv('word_scores2.csv')
+
+# Read matrix2.csv
+matrix2 = pd.read_csv('matrix5.csv', header=None)
+
+# Initialize an empty matrix
+output_matrix = []
+
+# Iterate through each row in word_scores
+for index, row in word_scores.iterrows():
+    score = row['Score']
+    
+    # If the score is 0, add a row of zeros to the output matrix
+    if score == 0:
+        output_matrix.append([0] * 6)
+    # If the score is 1, use the corresponding row from matrix2.csv
+    elif score == 1:
+        output_matrix.append(matrix2.iloc[index % len(matrix2)].tolist())
+
+# Convert the output_matrix to a DataFrame
+result_output_matrix = pd.DataFrame(output_matrix, columns=['Col1', 'Col2', 'Col3', 'Col4', 'Col5', 'Col6'])
+
+# Save the result_output_matrix to a CSV file without a header
+result_output_matrix.to_csv('loopnum.csv', header=False, index=False)

first.html

@@ -0,0 +1,19 @@
+<html><head></head><body><span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -3px; text-shadow: 0px 0px 1px; font-family: Raleway, sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #5afc87;">b</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -3px; text-shadow: 0px 0px 1px; font-family: Raleway, sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #000000;">a</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -3px; text-shadow: 0px 0px 1px; font-family: Raleway, sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #000000;">s</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -2px; text-shadow: 0px 0px 1px; font-family: 'Open Sans Condensed', sans-serif; font-size: 19px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(15deg, 0deg); color: #000000;">k</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -3px; text-shadow: 0px 0px 1px; font-family: Raleway, sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #000000;">e</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -3px; text-shadow: 0px 0px 1px; font-family: Raleway, sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #5afc87;">t</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -3px; text-shadow: 0px 0px 1px; font-family: Raleway, sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #000000;">b</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing:  -2px; text-shadow: 0px 0px 2px; font-family: 'Poiret One', sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(-0deg, 0deg); color: #5afc87;">a</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing: -4px; text-shadow: 0px 0px 0px; font-family: 'Open Sans Condensed', sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #000000;">l</div></div></span> 
+<span class="css-1dbjc4n r-xoduu5x"><div id="div1" class="relative"><div id="ddiv10" class="CIRCDosis_SZ18_SP-3_SH1_SK0_MA0" style="letter-spacing: 6px; text-shadow: 0px 0px 1px; font-family: 'Poiret One', sans-serif; font-size: 17px; top: 11px; margin-top: -0.08cm; line-height: 118%; transform: skew(10deg, 0deg); color: #5afc87;">l</div></div></span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">was</span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">invented</span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">in</span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">1891</span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">by</span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">dr.</span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">james</span> 
+<span class="css-901oao2sx" style="color: #a8dab5; letter-spacing: 2px; font-size: 21px; font-family: 'Oswald', sans-serif; font-weight: 600;">naismith.</span> 
+</body></html>

index.html

@@ -1,19 +1,323 @@
 <!DOCTYPE html>
-<html>
-	<head>
-		<meta charset="utf-8" />
-		<meta name="viewport" content="width=device-width" />
-		<title>My static Space</title>
-		<link rel="stylesheet" href="style.css" />
-	</head>
-	<body>
-		<div class="card">
-			<h1>Welcome to your static Space!</h1>
-			<p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
-			<p>
-				Also don't forget to check the
-				<a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
-			</p>
-		</div>
-	</body>
+<html><meta charset="utf-8" />
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<meta name="format-detection" content="telephone=no" />
+<meta name="msapplication-tap-highlight" content="no" />
+<meta name="viewport" content="user-scalable=no, initial-scale=1, maximum-scale=1, minimum-scale=1, width=device-width" />
+<link href='http://fonts.googleapis.com/css?family=Raleway:500' rel='stylesheet' type='text/css'>
+<link href='http://fonts.googleapis.com/css?family=Open+Sans+Condensed:700|Oswald:300' rel='stylesheet' type='text/css'>
+<link href='http://fonts.googleapis.com/css?family=Open+Sans+Condensed:300' rel='stylesheet' type='text/css'>
+<link href='http://fonts.googleapis.com/css?family=Roboto+Condensed' rel='stylesheet' type='text/css'>
+<link href='https://fonts.googleapis.com/css?family=Poiret+One|Dosis:300|Fjalla+One' rel='stylesheet' type='text/css'>
+<link href='https://fonts.googleapis.com/css?family=Indie+Flower|Lobster' rel='stylesheet' type='text/css'>
+<link href='https://fonts.googleapis.com/css?family=Pacifico|Shadows+Into+Light|Dancing+Script|Amatic+SC' rel='stylesheet' type='text/css'>
+<link href='https://fonts.googleapis.com/css?family=Teko' rel='stylesheet' type='text/css'>
+<link href="https://fonts.googleapis.com/css?family=Abril+Fatface|Josefin+Sans|Gloria+Hallelujah|Roboto Slab|Righteous|Sacramento|Yellowtail" rel="stylesheet">
+<link href="https://fonts.googleapis.com/css?family=Annie+Use+Your+Telescope|Just+Me+Again+Down+Here|Nixie+One|Six+Caps|Unkempt" rel="stylesheet">
+<style>
+
+
+
+    
+.css-1dbjc4n {
+    -ms-flex-align: stretch;
+    -ms-flex-direction: column;
+    -ms-flex-negative: 0;
+    -ms-flex-preferred-size: auto;
+    -webkit-align-items: stretch;
+    -webkit-box-align: stretch;
+    -webkit-box-direction: normal;
+    -webkit-box-orient: vertical;
+    -webkit-flex-basis: auto;
+    -webkit-flex-direction: column;
+    -webkit-flex-shrink: 0;
+    align-items: stretch;
+    border: 0 solid black;
+    box-sizing: border-box;
+    display: -webkit-box;
+    display: -moz-box;
+    display: -ms-flexbox;
+    display: -webkit-flex;
+    display: flex;
+    flex-basis: auto;
+    flex-direction: column;
+    flex-shrink: 0;
+    margin-bottom: 0px;
+    margin-left: 0px;
+    margin-right: 2px;
+    margin-top: 0px;
+    min-height: 0px;
+    min-width: 0px;
+    padding-bottom: 0px;
+    padding-left: 0px;
+    padding-right: 0px;
+    padding-top: 0px;
+    position: relative;
+    z-index: 0;
+}
+
+.r-xoduu5zo {
+    display: inline-flex;
+	top: 10px;
+	background-color: #000000;
+}
+
+.r-xoduu5xxx {
+    display: inline-flex;
+    top: 5px;
+}
+.hagh1 {
+    height: 125px;
+    width: 390px;
+    position: absolute;
+    left: 500px;
+    top: 57px;
+    text-align: center;
+}
+
+div.relative {
+    position: relative;
+    top: -16px ;
+  
+    text-align: center;
+   
+}
+
+.r-xoduu5xoooo {
+    display: inline-flex;
+	top: -7px;
+}
+
+
+
+.CIRCDosis_SZ18_SP-3_SH1_SK0_MA0{
+ 
+ font-family: 'Dosis', sans-serif;
+ line-height: 110%;
+ font-size: 18px;      
+ letter-spacing: -3px;
+ text-shadow: 0px 0px 1px;
+ transform: skew(0deg, 0deg);
+ margin-top: 0.00cm;
+ position: relative;        
+ top: 11px;
+ float: left; 
+ 
+ 
+}
+.CIRCDosis_SZ18_SP-3_SH1_SK0_MA0 a:link, 
+.CIRCDosis_SZ18_SP-3_SH1_SK0_MA0 a:visited, 
+.CIRCDosis_SZ18_SP-3_SH1_SK0_MA0 a:hover { 
+ color: #000000; 
+ text-decoration: none; 
+ transition: all 0.2s ease-in-out;
+}
+
+.wordCIRCTEXT{
+	
+	
+	position: absolute;
+	 background-color: #b400ff;
+	width: 15px;
+	height: 10px;
+	border: 1px solid #000000;
+	
+	
+}
+
+.r-xoduu5xo {
+    display: inline-flex;
+	top: -2px;
+}
+
+.r-xoduu5xoo {
+    display: inline-flex;
+	top: -4px;
+}
+	.css-901oaoS {
+    border: 0 solid black;
+    box-sizing: border-box;
+    color: #ffffff;
+    display: inline;
+    font-size: 14px;
+    margin-bottom: 0px;
+    margin-left: 0px;
+    margin-right: 3px;
+    margin-top: 0px;
+    padding-bottom: 0px;
+    padding-left: 7px;
+	letter-spacing: 3px;
+    padding-right: 0px;
+    padding-top: 0px;
+    white-space: pre-wrap;
+    word-wrap: break-word;
+	font-family: 'Oswald', sans-serif;
+	font-weight: 300;
+
+	}
+			.css-901oao2sx {
+    border: 0 solid black;
+    box-sizing: border-box;
+    color: #000000;
+    display: inline;
+	font-weight: 600;
+    font-size: 20px;
+    margin-bottom: 0px;
+    margin-left: 0px;
+    margin-right: 0px;
+    margin-top: 0px;
+    padding-bottom: 0px;
+    padding-left: 0px;
+	letter-spacing: 3px;
+    padding-right: 0px;
+    padding-top: 0px;
+    white-space: pre-wrap;
+    word-wrap: break-word;
+	font-family: 'Oswald', sans-serif;
+
+	}
+
+	.write2 {
+		
+	background-color: #000000;
+	 
+    word-wrap: break-word;
+    border: 1px solid black;
+    box-sizing: border-box;
+
+	
+	
+		
+		
+	}
+
+.r-xoduu5x {
+    display: inline-flex;
+    top: 8px;
+}
+
+	.css-901oao2sx {
+    border: 0 solid black;
+    box-sizing: border-box;
+    color: #000000;
+    display: inline;
+	font-weight: 600;
+    font-size: 20px;
+    margin-bottom: 0px;
+    margin-left: 0px;
+    margin-right: 3px;
+    margin-top: 0px;
+    padding-bottom: 0px;
+    padding-left: 0px;
+	letter-spacing: 3px;
+    padding-right: 0px;
+    padding-top: 0px;
+    white-space: pre-wrap;
+    word-wrap: break-word;
+	font-family: 'Oswald', sans-serif;
+
+	}
+    .css-901oao2sx   {
+    border: 0 solid black;
+    box-sizing: border-box;
+    color: #000000;
+    display: inline;
+	font-weight: 600;
+    font-size: 20px;
+    margin-bottom: 0px;
+    margin-left: 0px;
+    margin-right: 2px;
+    margin-top: 0px;
+    padding-bottom: 0px;
+    padding-left: 0px;
+	letter-spacing: 3px;
+    padding-right: 0px;
+    padding-top: -5px;
+    white-space: pre-wrap;
+    word-wrap: break-word;
+	font-family: 'Oswald', sans-serif;
+
+	}
+
+
+</style>
+
+</head>
+
+<body>
+
+    <body>
+        <h1>Conversation Generator + circulartext A.I</h1>
+        <form method="post">
+            <label for="prompt">Enter Prompt:</label>
+            <input type="text" name="prompt" id="prompt" required>
+            <button type="submit">Generate Conversation</button>
+        </form>
+        {% if conversation %}
+            <h2>Generated Conversation:</h2>
+            <p>{{ conversation }}</p>
+        {% endif %}
+    
+        {% include 'first.html' %}
+    
+    <!-- Form for running backend script -->
+    <form method="post" onsubmit="runAAMain(); return false;">
+        <button type="submit">Run Backend Script</button>
+    </form>
+    
+    <script>
+        async function generateAndDisplay() {
+            const prompt = document.getElementById('prompt').value;
+            const response = await fetch('/', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({
+                    prompt: prompt,
+                }),
+            });
+
+            const result = await response.json();
+            document.getElementById('conversation-container').innerHTML = `<h2>Generated Conversation:</h2><p>${result.conversation}</p>`;
+        }
+
+        async function runAAMain() {
+            const response = await fetch('/run_aamain', {
+                method: 'POST',
+            });
+
+            const result = await response.json();
+            alert(result.message);  // You can handle the result as needed
+
+            // Reload the conversation container after running the backend script
+            loadConversation();
+        }
+
+        // Function to reload the conversation container every 10 seconds
+        function autoRefresh() {
+            setInterval(loadConversation, 10000); // 10,000 milliseconds = 10 seconds
+        }
+
+        // Call the function when the page loads
+        window.onload = function () {
+            autoRefresh();
+            loadConversation(); // Initial load
+        };
+
+        // Function to fetch and load the conversation into the container
+        async function loadConversation() {
+            const response = await fetch('/');
+            const html = await response.text();
+            
+            // Extract the content of the conversation container
+            const conversationContainer = document.getElementById('conversation-container');
+            const newContent = new DOMParser().parseFromString(html, 'text/html').getElementById('conversation-container').innerHTML;
+
+            // Replace the content of the conversation container
+            conversationContainer.innerHTML = newContent;
+        }
+    </script>
+</body>
 </html>

mod8.py

@@ -0,0 +1,101 @@
+import csv
+import os
+import random
+
+def print_matrix(matrix):
+    for row in matrix:
+        print(','.join(map(str, row)))
+
+def generate_random_values(num_values):
+    return [random.randint(0, 8) for _ in range(num_values)]
+
+def randomize_l1(matrix, random_values, identical_positions, combination_positions):
+    for i in range(len(matrix)):
+        if (i, i + 1) in identical_positions or (i + 1, i) in identical_positions:
+            # Use the same random value for identical positions
+            matrix[i][0] = random_values[i]
+            matrix[i + 1][0] = random_values[i]
+        elif (i, i) in combination_positions:
+            # Use the same random value for each letter within the combination
+            matrix[i][0] = random_values[i]
+        else:
+            # Use a common random value for non-identical and non-combination positions
+            matrix[i][0] = random_values[0]
+
+# Function to find positions of the same letters in the text
+def find_same_letter_positions(text):
+    same_letter_positions = []
+    for i in range(len(text)):
+        for j in range(i + 1, len(text)):
+            if text[i] == text[j]:
+                same_letter_positions.append((i, j))
+                same_letter_positions.append((j, i))  # Include (j, i) as well
+    return same_letter_positions
+
+# Function to find positions of the specified combinations in the text
+def find_combination_positions(text, combinations):
+    combination_positions = []
+    for combination in combinations:
+        i = 0
+        while i < len(text) - len(combination) + 1:
+            if text[i:i+len(combination)] == combination:
+                for j in range(i, i+len(combination)):
+                    combination_positions.append((j, j))
+                i += len(combination)  # Move to the next position after the combination
+            else:
+                i += 1
+    return combination_positions
+
+# Function to create a matrix from the text
+def create_matrix_from_text(text):
+    num_rows = len(text)
+    num_columns = num_rows
+
+    # Initialize a matrix with zeros
+    matrix = [[0] * num_columns for _ in range(num_rows)]
+
+    # Fill the matrix with data
+    for i in range(num_rows):
+        matrix[i][0] = text[i]  # Assign letters to the first column
+
+    return matrix
+
+# Process all text files from text1.csv to text5.csv
+for i in range(1, 20):
+    csv_filename = f'text{i}.csv'
+    combo_filename = f'text{i}combo1.csv'
+
+    # Read the text from the CSV file
+    with open(csv_filename, 'r') as file:
+        reader = csv.reader(file)
+        text = next(reader)[0]
+
+    # Find positions of the same letters
+    same_letter_positions = find_same_letter_positions(text)
+    print(f"\n{text} - Same Letter Positions:", same_letter_positions)
+
+    # Specify the combinations to find
+    combinations_to_find = ["bl", "wh", "sa", "wo", "no", "ve", "ab", "gro", "pu", "lo", "co", "bus", "pla", "ac", "at", "pr", "fa", "gr", "to", "or", "fa", "fr", "ki", "qu", "cl", "ok", "fig", "run", "ee", "BL", "WH", "SA", "WO", "NO", "VE", "AB", "GRO", "PU", "LO", "CO", "BUS", "PLA", "AC", "AT", "PR", "FA", "GR", "TO", "OR", "FA", "FR", "KI", "QU", "CL", "OK", "FIG", "RUN", "EE"]
+
+    # Find positions of the specified combinations
+    combination_positions = find_combination_positions(text, combinations_to_find)
+    print(f"{text} - Combination Positions:", combination_positions)
+
+    # Create a matrix based on the number of letters in the text
+    matrix = create_matrix_from_text(text)
+
+    # Generate random values for each letter position
+    random_values = generate_random_values(len(text))
+
+    # Randomly set values for the L1 column
+    randomize_l1(matrix, random_values, same_letter_positions, combination_positions)
+
+    # Print the matrix after the first modifications
+    print(f"{text} - Matrix After Randomization:")
+    print_matrix(matrix)
+
+    # Save the matrix to the combo file
+    with open(combo_filename, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        for row in matrix:
+            writer.writerow(row)

mod8l2.py

@@ -0,0 +1,108 @@
+import random
+import csv
+
+def print_matrix(matrix):
+    for row in matrix:
+        print(','.join(map(str, row)))
+
+def generate_random_values(num_values, zero_weight=0.5):
+    # Generate random values with 50% chance of being 0 in the first position
+    values = [0] + [random.randint(1, 11) for _ in range(num_values - 1)]
+    return [random.choice([0, val]) for val in values]
+
+def randomize_l1(matrix, random_values, identical_positions, combination_positions):
+    # If there are no matches or combination positions, set all numbers to the same value
+    if not identical_positions and not combination_positions:
+        common_random_value = random_values[0]
+        for i in range(len(matrix)):
+            matrix[i][0] = common_random_value
+    else:
+        for i in range(len(matrix)):
+            if (i, i + 1) in identical_positions or (i + 1, i) in identical_positions:
+                # Use the same random value for identical positions
+                matrix[i][0] = random_values[i]
+                matrix[i + 1][0] = random_values[i]
+            elif (i, i) in combination_positions:
+                # Use the same random value for each letter within the combination
+                matrix[i][0] = random_values[i]
+            else:
+                # Use a common random value for non-identical and non-combination positions
+                matrix[i][0] = random_values[0]
+
+# Function to find positions of the same letters in the text
+def find_same_letter_positions(text):
+    same_letter_positions = []
+    for i in range(len(text)):
+        for j in range(i + 1, len(text)):
+            if text[i] == text[j]:
+                same_letter_positions.append((i, j))
+                same_letter_positions.append((j, i))  # Include (j, i) as well
+    return same_letter_positions
+
+# Function to find positions of the specified combinations in the text
+def find_combination_positions(text, combinations):
+    combination_positions = []
+    for combination in combinations:
+        i = 0
+        while i < len(text) - len(combination) + 1:
+            if text[i:i+len(combination)] == combination:
+                for j in range(i, i+len(combination)):
+                    combination_positions.append((j, j))
+                i += len(combination)  # Move to the next position after the combination
+            else:
+                i += 1
+    return combination_positions
+
+# Function to create a matrix from the text
+def create_matrix_from_text(text):
+    num_rows = len(text)
+    num_columns = num_rows
+
+    # Initialize a matrix with zeros
+    matrix = [[0] * num_columns for _ in range(num_rows)]
+
+    # Fill the matrix with data
+    for i in range(num_rows):
+        matrix[i][0] = text[i]  # Assign letters to the first column
+
+    return matrix
+
+# Process all text files from text1.csv to text5.csv
+for i in range(1, 20):
+    csv_filename = f'text{i}.csv'
+    combo_filename = f'text{i}combo2.csv'
+
+    # Read the text from the CSV file
+    with open(csv_filename, 'r') as file:
+        reader = csv.reader(file)
+        text = next(reader)[0]
+
+    # Find positions of the same letters
+    same_letter_positions = find_same_letter_positions(text)
+    print(f"\n{text} - Same Letter Positions:", same_letter_positions)
+
+    # Specify the combinations to find
+    combinations_to_find = ["bl", "wh", "sa", "wo", "no", "ve", "ab", "gro", "pu", "lo", "co", "bus", "pla", "ac", "at", "pr", "fa", "gr", "to", "or", "fa", "fr", "ki", "qu", "cl", "ok", "fig", "run", "ee", "BL", "WH", "SA", "WO", "NO", "VE", "AB", "GRO", "PU", "LO", "CO", "BUS", "PLA", "AC", "AT", "PR", "FA", "GR", "TO", "OR", "FA", "FR", "KI", "QU", "CL", "OK", "FIG", "RUN", "EE"]
+
+    # Find positions of the specified combinations
+    combination_positions = find_combination_positions(text, combinations_to_find)
+    print(f"{text} - Combination Positions:", combination_positions)
+
+    # Create a matrix based on the number of letters in the text
+    matrix = create_matrix_from_text(text)
+
+    # Generate random values for each letter position with 50% chance of being 0
+    random_values = generate_random_values(len(text), zero_weight=0.5)
+
+    # Randomly set values for the L1 column
+    randomize_l1(matrix, random_values, same_letter_positions, combination_positions)
+
+    # Print the matrix after the first modifications
+    print(f"{text} - Matrix After Randomization:")
+    print_matrix(matrix)
+
+    # Save the matrix to the combo file
+    with open(combo_filename, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        for row in matrix:
+            writer.writerow(row)

mod8l3.py

@@ -0,0 +1,79 @@
+import random
+import csv
+
+def print_matrix(matrix):
+    for row in matrix:
+        print(','.join(map(str, row)))
+
+def generate_random_values(num_values):
+    return [random.randint(0, 14) for _ in range(num_values)]
+
+def randomize_l1(matrix, random_values, identical_positions, combination_positions):
+    for i in range(len(matrix)):
+        if (i, i + 1) in identical_positions or (i + 1, i) in identical_positions:
+            matrix[i][0] = random_values[i]
+            matrix[i + 1][0] = random_values[i]
+        elif (i, i) in combination_positions:
+            matrix[i][0] = random_values[i]
+        else:
+            matrix[i][0] = random_values[0]
+
+def find_same_letter_positions(text):
+    same_letter_positions = []
+    for i in range(len(text)):
+        for j in range(i + 1, len(text)):
+            if text[i] == text[j]:
+                same_letter_positions.append((i, j))
+                same_letter_positions.append((j, i))
+    return same_letter_positions
+
+def find_combination_positions(text, combinations):
+    combination_positions = []
+    for combination in combinations:
+        i = 0
+        while i < len(text) - len(combination) + 1:
+            if text[i:i+len(combination)] == combination:
+                for j in range(i, i+len(combination)):
+                    combination_positions.append((j, j))
+                i += len(combination)
+            else:
+                i += 1
+    return combination_positions
+
+def create_matrix_from_text(text):
+    num_rows = len(text)
+    num_columns = num_rows
+    matrix = [[0] * num_columns for _ in range(num_rows)]
+
+    for i in range(num_rows):
+        matrix[i][0] = text[i]
+
+    return matrix
+
+for i in range(1, 20):
+    csv_filename = f'text{i}.csv'
+    combo_filename = f'text{i}combo3.csv'
+
+    with open(csv_filename, 'r') as file:
+        reader = csv.reader(file)
+        text = next(reader)[0]
+
+    same_letter_positions = find_same_letter_positions(text)
+    print(f"\n{text} - Same Letter Positions:", same_letter_positions)
+
+    combinations_to_find = ["BL", "WH", "SA", "WO", "NO", "VE", "AB", "GRO", "PU", "LO", "CO", "BUS", "PLA", "AC", "AT", "PR", "FA", "GR", "TO", "OR", "FA", "FR", "KI", "QU", "CL", "OK", "FIG", "RUN", "EE", "GH", "SI", "OX", "LAB", "ALL", "PRO", "gh","si", "ox", "lab", "all", "pro","ro", "to", "ra", "ho", "ge", "ve", "gr", "ab", "gro", "pu", "lo", "co", "bus", "pla", "ac", "at", "pr", "fa", "gr", "to", "or", "fa", "fr", "ki", "qu", "cl", "ok", "fig", "run", "ee"]
+
+    combination_positions = find_combination_positions(text, combinations_to_find)
+    print(f"{text} - Combination Positions:", combination_positions)
+
+    matrix = create_matrix_from_text(text)
+    random_values = generate_random_values(len(text))
+    randomize_l1(matrix, random_values, same_letter_positions, combination_positions)
+
+    print(f"{text} - Matrix After Randomization:")
+    print_matrix(matrix)
+
+    with open(combo_filename, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        for row in matrix:
+            writer.writerow(row)

mod8l4.py

@@ -0,0 +1,92 @@
+import random
+import csv
+
+def print_matrix(matrix):
+    for row in matrix:
+        print(','.join(map(str, row)))
+
+def generate_random_values(num_values, zero_weight=0.5):
+    values = [3] + [random.randint(1, 7) for _ in range(num_values - 1)]
+    return [random.choice([0, val]) for val in values]
+
+def randomize_l1(matrix, random_values, identical_positions, combination_positions):
+    if not identical_positions and not combination_positions:
+        common_random_value = random_values[0]
+        for i in range(len(matrix)):
+            matrix[i][0] = common_random_value
+    else:
+        for i in range(len(matrix)):
+            if (i, i + 1) in identical_positions or (i + 1, i) in identical_positions:
+                matrix[i][0] = random_values[i]
+                matrix[i + 1][0] = random_values[i]
+            elif (i, i) in combination_positions:
+                matrix[i][0] = random_values[i]
+            else:
+                matrix[i][0] = random_values[0]
+
+def find_same_letter_positions(text):
+    same_letter_positions = []
+    for i in range(len(text)):
+        for j in range(i + 1, len(text)):
+            if text[i] == text[j]:
+                same_letter_positions.append((i, j))
+                same_letter_positions.append((j, i))
+    return same_letter_positions
+
+def find_combination_positions(text, combinations):
+    combination_positions = []
+    for combination in combinations:
+        i = 0
+        while i < len(text) - len(combination) + 1:
+            if text[i:i+len(combination)] == combination:
+                for j in range(i, i+len(combination)):
+                    combination_positions.append((j, j))
+                i += len(combination)
+            else:
+                i += 1
+    return combination_positions
+
+def create_matrix_from_text(text):
+    num_rows = len(text)
+    num_columns = num_rows
+    matrix = [[0] * num_columns for _ in range(num_rows)]
+
+    for i in range(num_rows):
+        matrix[i][0] = text[i]
+
+    return matrix
+
+for i in range(1, 20):
+    csv_filename = f'text{i}.csv'
+    combo4_filename = f'text{i}combo4.csv'
+    combo5_filename = f'text{i}combo5.csv'
+
+    with open(csv_filename, 'r') as file:
+        reader = csv.reader(file)
+        text = next(reader)[0]
+
+    same_letter_positions = find_same_letter_positions(text)
+    print(f"\n{text} - Same Letter Positions:", same_letter_positions)
+
+    combinations_to_find = ["ve", "ab", "gro", "pu", "lo", "co", "bus", "pla", "ac", "at", "pr", "fa", "gr", "to", "or", "fa", "fr", "ki", "qu", "cl", "ok", "fig", "run"]
+
+    combination_positions = find_combination_positions(text, combinations_to_find)
+    print(f"{text} - Combination Positions:", combination_positions)
+
+    matrix = create_matrix_from_text(text)
+    random_values = generate_random_values(len(text), zero_weight=0.5)
+
+    randomize_l1(matrix, random_values, same_letter_positions, combination_positions)
+
+    print(f"{text} - Matrix After Randomization:")
+    print_matrix(matrix)
+
+    with open(combo4_filename, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        for row in matrix:
+            writer.writerow(row)
+
+    with open(combo5_filename, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        for row in matrix:
+            writer.writerow(row)

mod8l5.py

@@ -0,0 +1,80 @@
+import random
+import csv
+
+def print_matrix(matrix):
+    for row in matrix:
+        print(','.join(map(str, row)))
+
+def generate_random_values(num_values):
+    return [random.randint(0, 12) for _ in range(num_values)]
+
+def randomize_l1(matrix, random_values, identical_positions, combination_positions):
+    for i in range(len(matrix)):
+        if (i, i + 1) in identical_positions or (i + 1, i) in identical_positions:
+            matrix[i][0] = random_values[i]
+            matrix[i + 1][0] = random_values[i]
+        elif (i, i) in combination_positions:
+            matrix[i][0] = random_values[i]
+        else:
+            matrix[i][0] = random_values[0]
+
+def find_same_letter_positions(text):
+    same_letter_positions = []
+    for i in range(len(text)):
+        for j in range(i + 1, len(text)):
+            if text[i] == text[j]:
+                same_letter_positions.append((i, j))
+                same_letter_positions.append((j, i))
+    return same_letter_positions
+
+def find_combination_positions(text, combinations):
+    combination_positions = []
+    for combination in combinations:
+        i = 0
+        while i < len(text) - len(combination) + 1:
+            if text[i:i+len(combination)] == combination:
+                for j in range(i, i+len(combination)):
+                    combination_positions.append((j, j))
+                i += len(combination)
+            else:
+                i += 1
+    return combination_positions
+
+def create_matrix_from_text(text):
+    num_rows = len(text)
+    num_columns = num_rows
+    matrix = [[0] * num_columns for _ in range(num_rows)]
+
+    for i in range(num_rows):
+        matrix[i][0] = text[i]
+
+    return matrix
+
+for i in range(1, 20):
+    csv_filename = f'text{i}.csv'
+    combo6_filename = f'text{i}combo6.csv'
+
+    with open(csv_filename, 'r') as file:
+        reader = csv.reader(file)
+        text = next(reader)[0]
+
+    same_letter_positions = find_same_letter_positions(text)
+    print(f"\n{text} - Same Letter Positions:", same_letter_positions)
+
+    combinations_to_find = ["ya", "te", "co", "wa", "pr", "pi", "act", "pa", "ja", "sa", "ve", "ab", "gro", "pu", "lo", "co", "bus", "pla", "ac", "at", "pr", "fa", "gr", "to", "or", "fa", "fr", "ki", "qu", "cl", "ok", "fig", "run", "ee"]
+
+    combination_positions = find_combination_positions(text, combinations_to_find)
+    print(f"{text} - Combination Positions:", combination_positions)
+
+    matrix = create_matrix_from_text(text)
+    random_values = generate_random_values(len(text))
+
+    randomize_l1(matrix, random_values, same_letter_positions, combination_positions)
+
+    print(f"{text} - Matrix After Randomization:")
+    print_matrix(matrix)
+
+    with open(combo6_filename, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        for row in matrix:
+            writer.writerow(row)

textto.py

@@ -0,0 +1,19 @@
+import csv
+import os
+
+def separate_words(input_csv):
+    with open(input_csv, 'r', newline='', encoding='utf-8') as csvfile:
+        reader = csv.reader(csvfile)
+
+        for row_index, row in enumerate(reader):
+            for col_index, word in enumerate(row):
+                # Create a separate file for each word
+                output_file = f'text{row_index + 1}.csv'
+                
+                with open(output_file, 'w', newline='', encoding='utf-8') as word_file:
+                    writer = csv.writer(word_file)
+                    writer.writerow([word])
+
+if __name__ == "__main__":
+    input_csv = "text.csv"
+    separate_words(input_csv)

word_database.txt

@@ -0,0 +1,143 @@
+movie
+excited
+waiting
+long
+time
+production
+real
+coded
+digital
+favorite
+asking
+doing
+basketball
+soccer
+football
+baseball
+soup
+food
+burgers
+pizza
+fruit
+pinapple
+milk
+jello
+canddy
+candy
+rice
+greens
+lettuce
+outmeal
+cereal
+dogs
+cats
+animals
+goats
+sheeps
+movies
+money
+bank
+account
+keeping
+looking
+moving
+boxes
+elephants
+movement
+coding
+developing
+going
+cruise
+ship
+boat
+bahamas
+cats
+foods
+healthy
+eating
+important
+pennylvania
+alanta
+north carolina 
+new york
+france
+paris
+work
+jobs
+computers
+commputer
+grocery
+glamorous
+version
+truck
+pickup
+play
+types
+games
+applications
+quantum
+speeds
+advancements
+technological
+glimpse
+countless
+technology
+future
+walking
+hello
+fuck
+going
+work
+about
+jordan
+Jordan's
+Jordan
+1993
+season
+superstar
+NBA
+championship
+leading
+points
+assist
+career
+chicago
+scared
+tongue
+energy
+disguise
+business
+older
+grown
+call
+bills
+garden
+house
+fallen
+blossoms
+lawn
+love
+forever
+most 
+big
+fan
+clout
+space
+team
+doing
+today
+woke
+work
+relax
+fart
+Grrah
+quicker
+thicker
+richer
+bics
+computer.
+football,
+baseball,
+basketball,
+data
+the