updated

app/app.py

@@ -5,21 +5,35 @@ import time
 import os
 from io import StringIO
 import pyperclip
-import nltk
 from openai import OpenAI
 import json
 
-# OpenAI configuration
+# Page Configuration
+st.set_page_config(
+    page_title="Prompt Output Separator",
+    page_icon="✂️",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Initialize session state variables
 if 'openai_api_key' not in st.session_state:
     st.session_state.openai_api_key = None
+if 'history' not in st.session_state:
+    st.session_state.history = []
+if 'prompt' not in st.session_state:
+    st.session_state.prompt = ""
+if 'output' not in st.session_state:
+    st.session_state.output = ""
+if 'title' not in st.session_state:
+    st.session_state.title = ""
+if 'mode' not in st.session_state:
+    st.session_state.mode = 'light'
 
-# Sidebar for API key configuration
-with st.sidebar:
-    st.markdown("## Configuration")
-    api_key = st.text_input("Enter OpenAI API Key", type="password")
-    if api_key:
-        st.session_state.openai_api_key = api_key
-        client = OpenAI(api_key=api_key)
+def count_text_stats(text):
+    words = len(text.split())
+    chars = len(text)
+    return words, chars
 
 def analyze_with_llm(text):
     if not st.session_state.openai_api_key:
@@ -35,14 +49,15 @@ def analyze_with_llm(text):
                 {
                     "role": "system",
                     "content": """You are a text analysis expert. Your task is to separate a conversation into the prompt/question and the response/answer. 
-                    Return ONLY a JSON object with two fields:
+                    Return ONLY a JSON object with three fields:
+                    - title: a short, descriptive title for the conversation (max 6 words)
                     - prompt: the user's question or prompt
                     - output: the response or answer
-                    If you cannot clearly identify both parts, set the unknown part to null."""
+                    If you cannot clearly identify any part, set it to null."""
                 },
                 {
                     "role": "user",
-                    "content": f"Please analyze this text and separate it into prompt and output: {text}"
+                    "content": f"Please analyze this text and separate it into title, prompt and output: {text}"
                 }
             ],
             temperature=0,
@@ -51,162 +66,267 @@ def analyze_with_llm(text):
         
         result = response.choices[0].message.content
         parsed = json.loads(result)
-        return parsed.get("prompt"), parsed.get("output")
+        return parsed.get("title"), parsed.get("prompt"), parsed.get("output")
         
     except Exception as e:
         st.error(f"Error analyzing text: {str(e)}")
-        return None, None
+        return None, None, None
 
-# Processing function
 def separate_prompt_output(text):
     if not text:
-        return "", ""
+        return "", "", ""
     
-    # Use LLM if API key is available
     if st.session_state.openai_api_key:
-        prompt, output = analyze_with_llm(text)
-        if prompt is not None and output is not None:
-            return prompt, output
+        title, prompt, output = analyze_with_llm(text)
+        if all(v is not None for v in [title, prompt, output]):
+            return title, prompt, output
     
-    # Fallback to basic separation if LLM fails or no API key
     parts = text.split('\n\n', 1)
     if len(parts) == 2:
-        return parts[0].strip(), parts[1].strip()
-    return text.strip(), ""
+        return "Untitled Conversation", parts[0].strip(), parts[1].strip()
+    return "Untitled Conversation", text.strip(), ""
 
-# Column processing function
 def process_column(column):
     processed_data = []
     for item in column:
-        prompt, output = separate_prompt_output(str(item))
-        processed_data.append({"Prompt": prompt, "Output": output})
+        title, prompt, output = separate_prompt_output(str(item))
+        processed_data.append({"Title": title, "Prompt": prompt, "Output": output})
     return pd.DataFrame(processed_data)
 
-# Download NLTK resources
-nltk.download('punkt')
+# Sidebar configuration
+with st.sidebar:
+    st.image("https://img.icons8.com/color/96/000000/chat.png", width=50)
+    st.markdown("## 🛠️ Configuration")
+    api_key = st.text_input("Enter OpenAI API Key", type="password")
+    if api_key:
+        st.session_state.openai_api_key = api_key
 
-# Session state management
-if 'history' not in st.session_state:
-    st.session_state.history = []
+    # Dark mode toggle
+    st.markdown("---")
+    st.markdown("## 🎨 Appearance")
+    dark_mode = st.toggle("Dark Mode", value=st.session_state.mode == 'dark')
+    st.session_state.mode = 'dark' if dark_mode else 'light'
+    
+    # Settings section
+    st.markdown("---")
+    st.markdown("## ⚙️ Settings")
+    auto_copy = st.checkbox("Auto-copy results to clipboard", value=False)
+    
+    if st.session_state.openai_api_key:
+        st.success("✓ API Key configured")
+    else:
+        st.warning("⚠ No API Key provided - using basic separation")
 
-if 'mode' not in st.session_state:
-    st.session_state.mode = 'light'
+# Main interface
+st.title("✂️ Prompt Output Separator")
+st.markdown("Utility to assist with separating prompts and outputs when they are recorded in a unified block of text. For cost-optimisation, uses GPT 3.5.")
+
+# Tabs with icons
+tabs = st.tabs(["📝 Paste Text", "📁 File Processing", "📊 History"])
+
+# Paste Text Tab
+with tabs[0]:
+    st.subheader("Paste Prompt and Output")
+    
+    # Input area with placeholder
+    input_container = st.container()
+    with input_container:
+        input_text = st.text_area(
+            "Paste your conversation here...",
+            height=200,
+            placeholder="Paste your conversation here. The tool will automatically separate the prompt from the output.",
+            help="Enter the text you want to separate into prompt and output."
+        )
+
+    # Process button
+    if st.button("🔄 Process", use_container_width=True) and input_text:
+        with st.spinner("Processing..."):
+            title, prompt, output = separate_prompt_output(input_text)
+            st.session_state.title = title
+            st.session_state.prompt = prompt
+            st.session_state.output = output
+            st.session_state.history.append(input_text)
 
-# Styling
-st.markdown("""
-<style>
-body {
-    font-family: Arial, sans-serif;
-    color: #333;
-    background-color: #f4f4f9;
-}
-.stTextInput > div > div > input {
-    font-size: 16px;
-}
-.stButton > button {
-    font-size: 16px;
-    padding: 0.5rem 1rem;
-}
-.stMarkdown {
-    font-size: 14px;
-}
-</style>
-""", unsafe_allow_html=True)
-
-# Dark mode toggle
-if st.sidebar.button("Toggle Dark Mode"):
-    st.session_state.mode = 'dark' if st.session_state.mode == 'light' else 'light'
+    # Suggested Title Section
+    st.markdown("### 📌 Suggested Title")
+    title_area = st.text_area(
+        "",
+        value=st.session_state.get('title', ""),
+        height=70,
+        key="title_area",
+        help="AI-generated title based on the conversation content"
+    )
 
+    # Prompt Section
+    st.markdown("### 📝 Prompt")
+    prompt_area = st.text_area(
+        "",
+        value=st.session_state.get('prompt', ""),
+        height=200,
+        key="prompt_area",
+        help="The extracted prompt will appear here"
+    )
+    # Display prompt stats
+    prompt_words, prompt_chars = count_text_stats(st.session_state.get('prompt', ""))
+    st.markdown(f"<p class='stats-text'>Words: {prompt_words} | Characters: {prompt_chars}</p>", unsafe_allow_html=True)
+    
+    if st.button("📋 Copy Prompt", use_container_width=True):
+        pyperclip.copy(st.session_state.get('prompt', ""))
+        st.success("Copied prompt to clipboard!")
+
+    # Output Section
+    st.markdown("### 🤖 Output")
+    output_area = st.text_area(
+        "",
+        value=st.session_state.get('output', ""),
+        height=200,
+        key="output_area",
+        help="The extracted output will appear here"
+    )
+    # Display output stats
+    output_words, output_chars = count_text_stats(st.session_state.get('output', ""))
+    st.markdown(f"<p class='stats-text'>Words: {output_words} | Characters: {output_chars}</p>", unsafe_allow_html=True)
+    
+    if st.button("📋 Copy Output", use_container_width=True):
+        pyperclip.copy(st.session_state.get('output', ""))
+        st.success("Copied output to clipboard!")
+
+# File Processing Tab
+with tabs[1]:
+    st.subheader("File Processing")
+    uploaded_files = st.file_uploader(
+        "Upload files",
+        type=["txt", "md", "csv"],
+        accept_multiple_files=True,
+        help="Upload text files to process multiple conversations at once"
+    )
+
+    if uploaded_files:
+        for file in uploaded_files:
+            with st.expander(f"📄 {file.name}", expanded=True):
+                file_content = file.read().decode("utf-8")
+                if file.name.endswith(".csv"):
+                    df = pd.read_csv(StringIO(file_content))
+                    for col in df.columns:
+                        processed_df = process_column(df[col])
+                        st.write(f"Processed column: {col}")
+                        st.dataframe(
+                            processed_df,
+                            use_container_width=True,
+                            hide_index=True
+                        )
+                else:
+                    title, prompt, output = separate_prompt_output(file_content)
+                    st.json({
+                        "Title": title,
+                        "Prompt": prompt,
+                        "Output": output
+                    })
+
+# History Tab
+with tabs[2]:
+    st.subheader("Processing History")
+    if st.session_state.history:
+        if st.button("🗑️ Clear History", type="secondary"):
+            st.session_state.history = []
+            st.experimental_rerun()
+            
+        for idx, item in enumerate(reversed(st.session_state.history)):
+            with st.expander(f"Entry {len(st.session_state.history) - idx}", expanded=False):
+                st.text_area(
+                    "Content",
+                    value=item,
+                    height=150,
+                    key=f"history_{idx}",
+                    disabled=True
+                )
+    else:
+        st.info("💡 No processing history available yet. Process some text to see it here.")
+
+# Footer
+st.markdown("---")
+st.markdown(
+    """
+    <div style='text-align: center'>
+        <p>Created by <a href="https://github.com/danielrosehill/Prompt-And-Output-Separator">Daniel Rosehill</a></p>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
+
+# Apply theme
 if st.session_state.mode == 'dark':
     st.markdown("""
     <style>
     body {
         color: #fff;
-        background-color: #121212;
+        background-color: #0e1117;
     }
-    .stTextInput > div > div > input {
+    .stTextInput > div > div > input, .stTextArea > div > div > textarea {
         color: #fff;
-        background-color: #333;
+        background-color: #262730;
+        border-radius: 8px;
+        border: 1px solid #464646;
+        padding: 15px;
+        font-family: 'Courier New', monospace;
     }
     .stButton > button {
         color: #fff;
-        background-color: #6200ea;
+        background-color: #4c4cff;
+        border-radius: 8px;
+        padding: 10px 20px;
+        transition: all 0.3s ease;
+        border: none;
+        width: 100%;
+    }
+    .stButton > button:hover {
+        background-color: #6b6bff;
+        transform: translateY(-2px);
+        box-shadow: 0 4px 12px rgba(76, 76, 255, 0.3);
     }
     .stMarkdown {
         color: #fff;
     }
+    .stats-text {
+        color: #999;
+        font-size: 0.8em;
+        margin-top: 5px;
+    }
     </style>
     """, unsafe_allow_html=True)
-
-# Header
-st.title("Prompt Output Separator")
-st.markdown("A utility to separate user prompts from AI responses")
-
-# Add API key status indicator
-if st.session_state.openai_api_key:
-    st.sidebar.success("✓ API Key configured")
 else:
-    st.sidebar.warning("⚠ No API Key provided - using basic separation")
-
-# GitHub badge
-st.sidebar.markdown("[![GitHub](https://img.shields.io/badge/GitHub-danielrosehill-blue?style=flat-square)](https://github.com/danielrosehill)")
-
-# Tabs
-tabs = st.tabs(["Manual Input", "File Processing"])
-
-# Manual Input Tab
-with tabs[0]:
-    st.subheader("Manual Input")
-    input_text = st.text_area("Enter text here", height=300)
-
-    col1, col2 = st.columns(2)
-
-    with col1:
-        if st.button("Separate Now"):
-            if input_text:
-                st.session_state.history.append(input_text)
-                prompt, output = separate_prompt_output(input_text)
-                st.session_state.prompt = prompt
-                st.session_state.output = output
-            else:
-                st.error("Please enter some text")
-
-        if st.button("Clear"):
-            st.session_state.prompt = ""
-            st.session_state.output = ""
-            input_text = ""
-
-    with col2:
-        st.text_area("Prompt", value=st.session_state.get('prompt', ""), height=150)
-        st.text_area("Output", value=st.session_state.get('output', ""), height=150)
-
-        if st.button("Copy Prompt to Clipboard"):
-            pyperclip.copy(st.session_state.get('prompt', ""))
-            st.success("Copied to clipboard")
-
-        if st.button("Copy Output to Clipboard"):
-            pyperclip.copy(st.session_state.get('output', ""))
-            st.success("Copied to clipboard")
-
-# File Processing Tab
-with tabs[1]:
-    st.subheader("File Processing")
-    uploaded_files = st.file_uploader("Upload files", type=["txt", "md", "csv"], accept_multiple_files=True)
-
-    if uploaded_files:
-        for file in uploaded_files:
-            file_content = file.read().decode("utf-8")
-            if file.name.endswith(".csv"):
-                df = pd.read_csv(StringIO(file_content))
-                for col in df.columns:
-                    processed_df = process_column(df[col])
-                    st.write(f"Processed column: {col}")
-                    st.write(processed_df)
-            else:
-                processed_text = separate_prompt_output(file_content)
-                st.write("Processed text file:")
-                st.write({"Prompt": processed_text[0], "Output": processed_text[1]})
-
-# Footer
-st.markdown("---")
-st.write("Version 1.0.0")
+    st.markdown("""
+    <style>
+    body {
+        color: #333;
+        background-color: #fff;
+    }
+    .stTextInput > div > div > input, .stTextArea > div > div > textarea {
+        color: #333;
+        background-color: #f8f9fa;
+        border-radius: 8px;
+        border: 1px solid #e0e0e0;
+        padding: 15px;
+        font-family: 'Courier New', monospace;
+    }
+    .stButton > button {
+        color: #fff;
+        background-color: #4c4cff;
+        border-radius: 8px;
+        padding: 10px 20px;
+        transition: all 0.3s ease;
+        border: none;
+        width: 100%;
+    }
+    .stButton > button:hover {
+        background-color: #6b6bff;
+        transform: translateY(-2px);
+        box-shadow: 0 4px 12px rgba(76, 76, 255, 0.3);
+    }
+    .stats-text {
+        color: #666;
+        font-size: 0.8em;
+        margin-top: 5px;
+    }
+    </style>
+    """, unsafe_allow_html=True)

versions/v1.py

@@ -0,0 +1,212 @@
+import streamlit as st
+import pandas as pd
+import re
+import time
+import os
+from io import StringIO
+import pyperclip
+import nltk
+from openai import OpenAI
+import json
+
+# OpenAI configuration
+if 'openai_api_key' not in st.session_state:
+    st.session_state.openai_api_key = None
+
+# Sidebar for API key configuration
+with st.sidebar:
+    st.markdown("## Configuration")
+    api_key = st.text_input("Enter OpenAI API Key", type="password")
+    if api_key:
+        st.session_state.openai_api_key = api_key
+        client = OpenAI(api_key=api_key)
+
+def analyze_with_llm(text):
+    if not st.session_state.openai_api_key:
+        st.error("Please provide an OpenAI API key in the sidebar")
+        return None, None
+        
+    try:
+        client = OpenAI(api_key=st.session_state.openai_api_key)
+        
+        response = client.chat.completions.create(
+            model="gpt-3.5-turbo-1106",
+            messages=[
+                {
+                    "role": "system",
+                    "content": """You are a text analysis expert. Your task is to separate a conversation into the prompt/question and the response/answer. 
+                    Return ONLY a JSON object with two fields:
+                    - prompt: the user's question or prompt
+                    - output: the response or answer
+                    If you cannot clearly identify both parts, set the unknown part to null."""
+                },
+                {
+                    "role": "user",
+                    "content": f"Please analyze this text and separate it into prompt and output: {text}"
+                }
+            ],
+            temperature=0,
+            response_format={ "type": "json_object" }
+        )
+        
+        result = response.choices[0].message.content
+        parsed = json.loads(result)
+        return parsed.get("prompt"), parsed.get("output")
+        
+    except Exception as e:
+        st.error(f"Error analyzing text: {str(e)}")
+        return None, None
+
+# Processing function
+def separate_prompt_output(text):
+    if not text:
+        return "", ""
+    
+    # Use LLM if API key is available
+    if st.session_state.openai_api_key:
+        prompt, output = analyze_with_llm(text)
+        if prompt is not None and output is not None:
+            return prompt, output
+    
+    # Fallback to basic separation if LLM fails or no API key
+    parts = text.split('\n\n', 1)
+    if len(parts) == 2:
+        return parts[0].strip(), parts[1].strip()
+    return text.strip(), ""
+
+# Column processing function
+def process_column(column):
+    processed_data = []
+    for item in column:
+        prompt, output = separate_prompt_output(str(item))
+        processed_data.append({"Prompt": prompt, "Output": output})
+    return pd.DataFrame(processed_data)
+
+# Download NLTK resources
+nltk.download('punkt')
+
+# Session state management
+if 'history' not in st.session_state:
+    st.session_state.history = []
+
+if 'mode' not in st.session_state:
+    st.session_state.mode = 'light'
+
+# Styling
+st.markdown("""
+<style>
+body {
+    font-family: Arial, sans-serif;
+    color: #333;
+    background-color: #f4f4f9;
+}
+.stTextInput > div > div > input {
+    font-size: 16px;
+}
+.stButton > button {
+    font-size: 16px;
+    padding: 0.5rem 1rem;
+}
+.stMarkdown {
+    font-size: 14px;
+}
+</style>
+""", unsafe_allow_html=True)
+
+# Dark mode toggle
+if st.sidebar.button("Toggle Dark Mode"):
+    st.session_state.mode = 'dark' if st.session_state.mode == 'light' else 'light'
+
+if st.session_state.mode == 'dark':
+    st.markdown("""
+    <style>
+    body {
+        color: #fff;
+        background-color: #121212;
+    }
+    .stTextInput > div > div > input {
+        color: #fff;
+        background-color: #333;
+    }
+    .stButton > button {
+        color: #fff;
+        background-color: #6200ea;
+    }
+    .stMarkdown {
+        color: #fff;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+# Header
+st.title("Prompt Output Separator")
+st.markdown("A utility to separate user prompts from AI responses")
+
+# Add API key status indicator
+if st.session_state.openai_api_key:
+    st.sidebar.success("✓ API Key configured")
+else:
+    st.sidebar.warning("⚠ No API Key provided - using basic separation")
+
+# GitHub badge
+st.sidebar.markdown("[![GitHub](https://img.shields.io/badge/GitHub-danielrosehill-blue?style=flat-square)](https://github.com/danielrosehill)")
+
+# Tabs
+tabs = st.tabs(["Manual Input", "File Processing"])
+
+# Manual Input Tab
+with tabs[0]:
+    st.subheader("Manual Input")
+    input_text = st.text_area("Enter text here", height=300)
+
+    col1, col2 = st.columns(2)
+
+    with col1:
+        if st.button("Separate Now"):
+            if input_text:
+                st.session_state.history.append(input_text)
+                prompt, output = separate_prompt_output(input_text)
+                st.session_state.prompt = prompt
+                st.session_state.output = output
+            else:
+                st.error("Please enter some text")
+
+        if st.button("Clear"):
+            st.session_state.prompt = ""
+            st.session_state.output = ""
+            input_text = ""
+
+    with col2:
+        st.text_area("Prompt", value=st.session_state.get('prompt', ""), height=150)
+        st.text_area("Output", value=st.session_state.get('output', ""), height=150)
+
+        if st.button("Copy Prompt to Clipboard"):
+            pyperclip.copy(st.session_state.get('prompt', ""))
+            st.success("Copied to clipboard")
+
+        if st.button("Copy Output to Clipboard"):
+            pyperclip.copy(st.session_state.get('output', ""))
+            st.success("Copied to clipboard")
+
+# File Processing Tab
+with tabs[1]:
+    st.subheader("File Processing")
+    uploaded_files = st.file_uploader("Upload files", type=["txt", "md", "csv"], accept_multiple_files=True)
+
+    if uploaded_files:
+        for file in uploaded_files:
+            file_content = file.read().decode("utf-8")
+            if file.name.endswith(".csv"):
+                df = pd.read_csv(StringIO(file_content))
+                for col in df.columns:
+                    processed_df = process_column(df[col])
+                    st.write(f"Processed column: {col}")
+                    st.write(processed_df)
+            else:
+                processed_text = separate_prompt_output(file_content)
+                st.write("Processed text file:")
+                st.write({"Prompt": processed_text[0], "Output": processed_text[1]})
+
+# Footer
+st.markdown("---")
+st.write("Version 1.0.0")

versions/v2.py

@@ -0,0 +1,232 @@
+import streamlit as st
+import pandas as pd
+from io import StringIO
+import pyperclip
+import openai
+
+# Initialize session state variables
+if 'history' not in st.session_state:
+    st.session_state.history = []
+if 'prompt' not in st.session_state:
+    st.session_state.prompt = ""
+if 'output' not in st.session_state:
+    st.session_state.output = ""
+if 'title' not in st.session_state:
+    st.session_state.title = ""
+
+# Custom CSS
+st.markdown("""
+    <style>
+    .stats-text {
+        font-size: 0.8rem;
+        color: #666;
+    }
+    </style>
+""", unsafe_allow_html=True)
+
+def count_text_stats(text):
+    words = len(text.split())
+    chars = len(text)
+    return words, chars
+
+def separate_prompt_output(text):
+    if not text:
+        return "", "", ""
+    
+    if st.session_state.get('openai_api_key'):
+        prompt, output = analyze_with_llm(text)
+        if prompt is not None and output is not None:
+            suggested_title = generate_title_with_llm(prompt, output)
+            return suggested_title, prompt, output
+    
+    parts = text.split('\n\n', 1)
+    if len(parts) == 2:
+        return "Untitled Conversation", parts[0].strip(), parts[1].strip()
+    return "Untitled Conversation", text.strip(), ""
+
+def generate_title_with_llm(prompt, output):
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {
+                    "role": "system",
+                    "content": "Generate a short, concise title (max 6 words) that captures the main topic of this conversation."
+                },
+                {
+                    "role": "user",
+                    "content": f"Prompt: {prompt}\nOutput: {output}"
+                }
+            ],
+            max_tokens=20,
+            temperature=0.7
+        )
+        return response.choices[0].message['content'].strip()
+    except Exception as e:
+        return "Untitled Conversation"
+
+def process_column(column):
+    processed_data = []
+    for item in column:
+        title, prompt, output = separate_prompt_output(str(item))
+        processed_data.append({"Title": title, "Prompt": prompt, "Output": output})
+    return pd.DataFrame(processed_data)
+
+# Main interface
+st.title("✂️ Prompt Output Separator")
+st.markdown("Utility to assist with separating prompts and outputs when they are recorded in a unified block of text. For cost-optimisation, uses GPT 3.5.")
+
+# Tabs with icons
+tabs = st.tabs(["📝 Paste Text", "📁 File Processing", "📊 History"])
+
+# Paste Text Tab
+with tabs[0]:
+    st.subheader("Paste Prompt and Output")
+    
+    # Settings
+    with st.expander("⚙️ Settings", expanded=False):
+        auto_copy = st.checkbox("Automatically copy prompt to clipboard", value=False)
+        st.text_input("OpenAI API Key (optional)", type="password", key="openai_api_key")
+    
+    # Input area with placeholder
+    input_container = st.container()
+    with input_container:
+        input_text = st.text_area(
+            "Paste your conversation here...",
+            height=200,
+            placeholder="Paste your conversation here. The tool will automatically separate the prompt from the output.",
+            help="Enter the text you want to separate into prompt and output."
+        )
+
+    # Action buttons
+    col1, col2 = st.columns(2)
+    with col1:
+        if st.button("🔄 Separate Now", use_container_width=True):
+            if input_text:
+                with st.spinner("Processing..."):
+                    st.session_state.history.append(input_text)
+                    title, prompt, output = separate_prompt_output(input_text)
+                    st.session_state.title = title
+                    st.session_state.prompt = prompt
+                    st.session_state.output = output
+                    if auto_copy:
+                        pyperclip.copy(prompt)
+            else:
+                st.error("Please enter some text")
+    
+    with col2:
+        if st.button("🗑️ Clear All", use_container_width=True):
+            st.session_state.title = ""
+            st.session_state.prompt = ""
+            st.session_state.output = ""
+            input_text = ""
+
+    # Suggested Title Section
+    st.markdown("### 📌 Suggested Title")
+    title_area = st.text_area(
+        "",
+        value=st.session_state.get('title', ""),
+        height=50,
+        key="title_area",
+        help="A suggested title based on the content"
+    )
+
+    # Prompt Section
+    st.markdown("### 📝 Prompt")
+    prompt_area = st.text_area(
+        "",
+        value=st.session_state.get('prompt', ""),
+        height=200,
+        key="prompt_area",
+        help="The extracted prompt will appear here"
+    )
+    # Display prompt stats
+    prompt_words, prompt_chars = count_text_stats(st.session_state.get('prompt', ""))
+    st.markdown(f"<p class='stats-text'>Words: {prompt_words} | Characters: {prompt_chars}</p>", unsafe_allow_html=True)
+    
+    if st.button("📋 Copy Prompt", use_container_width=True):
+        pyperclip.copy(st.session_state.get('prompt', ""))
+        st.success("Copied prompt to clipboard!")
+
+    # Output Section
+    st.markdown("### 🤖 Output")
+    output_area = st.text_area(
+        "",
+        value=st.session_state.get('output', ""),
+        height=200,
+        key="output_area",
+        help="The extracted output will appear here"
+    )
+    # Display output stats
+    output_words, output_chars = count_text_stats(st.session_state.get('output', ""))
+    st.markdown(f"<p class='stats-text'>Words: {output_words} | Characters: {output_chars}</p>", unsafe_allow_html=True)
+    
+    if st.button("📋 Copy Output", use_container_width=True):
+        pyperclip.copy(st.session_state.get('output', ""))
+        st.success("Copied output to clipboard!")
+
+# File Processing Tab
+with tabs[1]:
+    st.subheader("File Processing")
+    uploaded_files = st.file_uploader(
+        "Upload files",
+        type=["txt", "md", "csv"],
+        accept_multiple_files=True,
+        help="Upload text files to process multiple conversations at once"
+    )
+
+    if uploaded_files:
+        for file in uploaded_files:
+            with st.expander(f"📄 {file.name}", expanded=True):
+                file_content = file.read().decode("utf-8")
+                if file.name.endswith(".csv"):
+                    df = pd.read_csv(StringIO(file_content))
+                    for col in df.columns:
+                        processed_df = process_column(df[col])
+                        st.write(f"Processed column: {col}")
+                        st.dataframe(
+                            processed_df,
+                            use_container_width=True,
+                            hide_index=True
+                        )
+                else:
+                    title, prompt, output = separate_prompt_output(file_content)
+                    st.json({
+                        "Title": title,
+                        "Prompt": prompt,
+                        "Output": output
+                    })
+
+# History Tab
+with tabs[2]:
+    st.subheader("Processing History")
+    if st.session_state.history:
+        if st.button("🗑️ Clear History", type="secondary"):
+            st.session_state.history = []
+            st.experimental_rerun()
+            
+        for idx, item in enumerate(reversed(st.session_state.history)):
+            with st.expander(f"Entry {len(st.session_state.history) - idx}", expanded=False):
+                st.text_area(
+                    "Content",
+                    value=item,
+                    height=150,
+                    key=f"history_{idx}",
+                    disabled=True
+                )
+    else:
+        st.info("💡 No processing history available yet. Process some text to see it here.")
+
+# Footer
+st.markdown("---")
+st.markdown(
+    """
+    <div style='text-align: center'>
+        <p>Created by <a href="https://github.com/danielrosehill/Prompt-And-Output-Separator">Daniel Rosehill</a> and Claude Sonnet 3.5</p>
+        <p><a href="https://github.com/danielrosehill/Prompt-And-Output-Separator" target="_blank">
+            <img src="https://img.shields.io/github/stars/danielrosehill/Prompt-And-Output-Separator?style=social" alt="GitHub stars">
+        </a></p>
+    </div>
+    """,
+    unsafe_allow_html=True
+)

versions/v3.py

@@ -0,0 +1,332 @@
+import streamlit as st
+import pandas as pd
+import re
+import time
+import os
+from io import StringIO
+import pyperclip
+from openai import OpenAI
+import json
+
+# Page Configuration
+st.set_page_config(
+    page_title="Prompt Output Separator",
+    page_icon="✂️",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Initialize session state variables
+if 'openai_api_key' not in st.session_state:
+    st.session_state.openai_api_key = None
+if 'history' not in st.session_state:
+    st.session_state.history = []
+if 'prompt' not in st.session_state:
+    st.session_state.prompt = ""
+if 'output' not in st.session_state:
+    st.session_state.output = ""
+if 'title' not in st.session_state:
+    st.session_state.title = ""
+if 'mode' not in st.session_state:
+    st.session_state.mode = 'light'
+
+def count_text_stats(text):
+    words = len(text.split())
+    chars = len(text)
+    return words, chars
+
+def analyze_with_llm(text):
+    if not st.session_state.openai_api_key:
+        st.error("Please provide an OpenAI API key in the sidebar")
+        return None, None
+        
+    try:
+        client = OpenAI(api_key=st.session_state.openai_api_key)
+        
+        response = client.chat.completions.create(
+            model="gpt-3.5-turbo-1106",
+            messages=[
+                {
+                    "role": "system",
+                    "content": """You are a text analysis expert. Your task is to separate a conversation into the prompt/question and the response/answer. 
+                    Return ONLY a JSON object with three fields:
+                    - title: a short, descriptive title for the conversation (max 6 words)
+                    - prompt: the user's question or prompt
+                    - output: the response or answer
+                    If you cannot clearly identify any part, set it to null."""
+                },
+                {
+                    "role": "user",
+                    "content": f"Please analyze this text and separate it into title, prompt and output: {text}"
+                }
+            ],
+            temperature=0,
+            response_format={ "type": "json_object" }
+        )
+        
+        result = response.choices[0].message.content
+        parsed = json.loads(result)
+        return parsed.get("title"), parsed.get("prompt"), parsed.get("output")
+        
+    except Exception as e:
+        st.error(f"Error analyzing text: {str(e)}")
+        return None, None, None
+
+def separate_prompt_output(text):
+    if not text:
+        return "", "", ""
+    
+    if st.session_state.openai_api_key:
+        title, prompt, output = analyze_with_llm(text)
+        if all(v is not None for v in [title, prompt, output]):
+            return title, prompt, output
+    
+    parts = text.split('\n\n', 1)
+    if len(parts) == 2:
+        return "Untitled Conversation", parts[0].strip(), parts[1].strip()
+    return "Untitled Conversation", text.strip(), ""
+
+def process_column(column):
+    processed_data = []
+    for item in column:
+        title, prompt, output = separate_prompt_output(str(item))
+        processed_data.append({"Title": title, "Prompt": prompt, "Output": output})
+    return pd.DataFrame(processed_data)
+
+# Sidebar configuration
+with st.sidebar:
+    st.image("https://img.icons8.com/color/96/000000/chat.png", width=50)
+    st.markdown("## 🛠️ Configuration")
+    api_key = st.text_input("Enter OpenAI API Key", type="password")
+    if api_key:
+        st.session_state.openai_api_key = api_key
+
+    # Dark mode toggle
+    st.markdown("---")
+    st.markdown("## 🎨 Appearance")
+    dark_mode = st.toggle("Dark Mode", value=st.session_state.mode == 'dark')
+    st.session_state.mode = 'dark' if dark_mode else 'light'
+    
+    # Settings section
+    st.markdown("---")
+    st.markdown("## ⚙️ Settings")
+    auto_copy = st.checkbox("Auto-copy results to clipboard", value=False)
+    
+    if st.session_state.openai_api_key:
+        st.success("✓ API Key configured")
+    else:
+        st.warning("⚠ No API Key provided - using basic separation")
+
+# Main interface
+st.title("✂️ Prompt Output Separator")
+st.markdown("Utility to assist with separating prompts and outputs when they are recorded in a unified block of text. For cost-optimisation, uses GPT 3.5.")
+
+# Tabs with icons
+tabs = st.tabs(["📝 Paste Text", "📁 File Processing", "📊 History"])
+
+# Paste Text Tab
+with tabs[0]:
+    st.subheader("Paste Prompt and Output")
+    
+    # Input area with placeholder
+    input_container = st.container()
+    with input_container:
+        input_text = st.text_area(
+            "Paste your conversation here...",
+            height=200,
+            placeholder="Paste your conversation here. The tool will automatically separate the prompt from the output.",
+            help="Enter the text you want to separate into prompt and output."
+        )
+
+    # Process button
+    if st.button("🔄 Process", use_container_width=True) and input_text:
+        with st.spinner("Processing..."):
+            title, prompt, output = separate_prompt_output(input_text)
+            st.session_state.title = title
+            st.session_state.prompt = prompt
+            st.session_state.output = output
+            st.session_state.history.append(input_text)
+
+    # Suggested Title Section
+    st.markdown("### 📌 Suggested Title")
+    title_area = st.text_area(
+        "",
+        value=st.session_state.get('title', ""),
+        height=70,
+        key="title_area",
+        help="AI-generated title based on the conversation content"
+    )
+
+    # Prompt Section
+    st.markdown("### 📝 Prompt")
+    prompt_area = st.text_area(
+        "",
+        value=st.session_state.get('prompt', ""),
+        height=200,
+        key="prompt_area",
+        help="The extracted prompt will appear here"
+    )
+    # Display prompt stats
+    prompt_words, prompt_chars = count_text_stats(st.session_state.get('prompt', ""))
+    st.markdown(f"<p class='stats-text'>Words: {prompt_words} | Characters: {prompt_chars}</p>", unsafe_allow_html=True)
+    
+    if st.button("📋 Copy Prompt", use_container_width=True):
+        pyperclip.copy(st.session_state.get('prompt', ""))
+        st.success("Copied prompt to clipboard!")
+
+    # Output Section
+    st.markdown("### 🤖 Output")
+    output_area = st.text_area(
+        "",
+        value=st.session_state.get('output', ""),
+        height=200,
+        key="output_area",
+        help="The extracted output will appear here"
+    )
+    # Display output stats
+    output_words, output_chars = count_text_stats(st.session_state.get('output', ""))
+    st.markdown(f"<p class='stats-text'>Words: {output_words} | Characters: {output_chars}</p>", unsafe_allow_html=True)
+    
+    if st.button("📋 Copy Output", use_container_width=True):
+        pyperclip.copy(st.session_state.get('output', ""))
+        st.success("Copied output to clipboard!")
+
+# File Processing Tab
+with tabs[1]:
+    st.subheader("File Processing")
+    uploaded_files = st.file_uploader(
+        "Upload files",
+        type=["txt", "md", "csv"],
+        accept_multiple_files=True,
+        help="Upload text files to process multiple conversations at once"
+    )
+
+    if uploaded_files:
+        for file in uploaded_files:
+            with st.expander(f"📄 {file.name}", expanded=True):
+                file_content = file.read().decode("utf-8")
+                if file.name.endswith(".csv"):
+                    df = pd.read_csv(StringIO(file_content))
+                    for col in df.columns:
+                        processed_df = process_column(df[col])
+                        st.write(f"Processed column: {col}")
+                        st.dataframe(
+                            processed_df,
+                            use_container_width=True,
+                            hide_index=True
+                        )
+                else:
+                    title, prompt, output = separate_prompt_output(file_content)
+                    st.json({
+                        "Title": title,
+                        "Prompt": prompt,
+                        "Output": output
+                    })
+
+# History Tab
+with tabs[2]:
+    st.subheader("Processing History")
+    if st.session_state.history:
+        if st.button("🗑️ Clear History", type="secondary"):
+            st.session_state.history = []
+            st.experimental_rerun()
+            
+        for idx, item in enumerate(reversed(st.session_state.history)):
+            with st.expander(f"Entry {len(st.session_state.history) - idx}", expanded=False):
+                st.text_area(
+                    "Content",
+                    value=item,
+                    height=150,
+                    key=f"history_{idx}",
+                    disabled=True
+                )
+    else:
+        st.info("💡 No processing history available yet. Process some text to see it here.")
+
+# Footer
+st.markdown("---")
+st.markdown(
+    """
+    <div style='text-align: center'>
+        <p>Created by <a href="https://github.com/danielrosehill/Prompt-And-Output-Separator">Daniel Rosehill</a></p>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
+
+# Apply theme
+if st.session_state.mode == 'dark':
+    st.markdown("""
+    <style>
+    body {
+        color: #fff;
+        background-color: #0e1117;
+    }
+    .stTextInput > div > div > input, .stTextArea > div > div > textarea {
+        color: #fff;
+        background-color: #262730;
+        border-radius: 8px;
+        border: 1px solid #464646;
+        padding: 15px;
+        font-family: 'Courier New', monospace;
+    }
+    .stButton > button {
+        color: #fff;
+        background-color: #4c4cff;
+        border-radius: 8px;
+        padding: 10px 20px;
+        transition: all 0.3s ease;
+        border: none;
+        width: 100%;
+    }
+    .stButton > button:hover {
+        background-color: #6b6bff;
+        transform: translateY(-2px);
+        box-shadow: 0 4px 12px rgba(76, 76, 255, 0.3);
+    }
+    .stMarkdown {
+        color: #fff;
+    }
+    .stats-text {
+        color: #999;
+        font-size: 0.8em;
+        margin-top: 5px;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+else:
+    st.markdown("""
+    <style>
+    body {
+        color: #333;
+        background-color: #fff;
+    }
+    .stTextInput > div > div > input, .stTextArea > div > div > textarea {
+        color: #333;
+        background-color: #f8f9fa;
+        border-radius: 8px;
+        border: 1px solid #e0e0e0;
+        padding: 15px;
+        font-family: 'Courier New', monospace;
+    }
+    .stButton > button {
+        color: #fff;
+        background-color: #4c4cff;
+        border-radius: 8px;
+        padding: 10px 20px;
+        transition: all 0.3s ease;
+        border: none;
+        width: 100%;
+    }
+    .stButton > button:hover {
+        background-color: #6b6bff;
+        transform: translateY(-2px);
+        box-shadow: 0 4px 12px rgba(76, 76, 255, 0.3);
+    }
+    .stats-text {
+        color: #666;
+        font-size: 0.8em;
+        margin-top: 5px;
+    }
+    </style>
+    """, unsafe_allow_html=True)