improved fork

README.md

@@ -1,30 +1,73 @@
+
+#  original idea inspired by 
+https://github.com/Govind-S-B/ppt_generator
+
+# better version
+https://github.com/pleabargain/ppt_generator-1
+
+
 # PPT Generator
-A local LLM assisted ppt generation tool 
+A local LLM assisted powerpoint generation tool 
 
 ## Why  
-Writing presentations for course assignments is just boilerplate work most often, especially when even the lecturers dont even care about it.
-Thats why I automated the boilerplate work, just enter a topic and the tool generates a simple presentation , enough to satisfy the base course requirement.
+Idea generation with Ollama running locally. This will be useful for generating ideas for presentations. It will pull the available local models and let you select one.
+
+# What
+Don't expect a lot of features. 
+
+
+I did add a language option. It's not perfect but it's a start.
+
+It's a simple tool to generate (generic) powerpoint content. It doesn't support images and there is no styling to speak of. It's just a simple tool to generate ppt content. There all kinds of things that can be added to it.
+
+* add image generation
+* add styling
+* add speaker notes
+* add slide numbers
+* add slide layouts
+* reference color palettes
+
+
 
 ## Running Locally
 install [ollama](https://ollama.ai/download)
 and have it up and running with command `ollama serve` ( applicable to some systems only )  
 
-download the required model ( this can be changed in this [line](https://github.com/Govind-S-B/ppt_generator/blob/main/ppt_data_gen.py#L24) )
+
+
 ```
-ollama pull dolphin2.1-mistral
+ollama pull llama3.2
 ```
 
 
 clone the repo and move into the directory
+
+```
+git clone https://github.com/pleabargain/ppt_generator-1
+```
+
+
 ```
-git clone https://github.com/Govind-S-B/ppt_generator.git
 cd ppt_generator
 ```
+
 install the required python dependencies
+
 ```
 pip install -r requirements.txt
 ```
+
+maybe these too
+
+```
+pip install -U langchain-community
+pip install -U langchain-ollama
+```
+
+
 run the streamlit app
+
 ```
-streamlit run main.py
+python -m streamlit run main.py
 ```
+

main.py

@@ -1,20 +1,107 @@
+import subprocess
 import streamlit as st
 from ppt_data_gen import slide_data_gen
 from ppt_gen import ppt_gen
+import random
+from datetime import datetime
+import time
+
+# Define the function to get installed models first
+def get_installed_models():
+    try:
+        # Run ollama list command and capture output
+        result = subprocess.run(['ollama', 'list'], capture_output=True, text=True)
+        # Split output into lines and skip the header line
+        lines = result.stdout.strip().split('\n')[1:]
+        # Extract model names from each line
+        models = [line.split()[0] for line in lines if line]
+        return models
+    except Exception as e:
+        # Fallback to default models if command fails
+        st.warning(f"Could not fetch installed models: {str(e)}")
+        return []
+
+# Function to select Ollama model
+def select_ollama_model():
+    models = get_installed_models()
+    selected_model = st.selectbox("Select Ollama model:", models)
+    return selected_model
 
 st.title("PPT Generator")
 
+# Input for topic
 topic = st.text_input("Enter a topic:")
 
-if st.button("Generate"):
-    data = slide_data_gen(topic)
+# Slider for number of slides
+num_slides = st.slider("Select number of slides:", min_value=3, max_value=20, value=7)
+
+# Add language selection dropdown
+languages = ["English", "French", "Spanish", "German", "Ukrainian", "Arabic"]  # Added Ukrainian and Arabic
+language = st.selectbox("Select Language:", languages, index=0)
+
+# Get selected model and language
+ollama_model = select_ollama_model()
+
+if st.button("Generate") and topic:
+    # Initialize progress bar
+    progress_bar = st.progress(0)
+    status_text = st.empty()
+
+    # List of random status messages
+    messages = [
+        "Hold your horses—better yet, knit them a sweater while you wait",
+        "Time flies when you’re watching cat videos. Try it",
+        "If waiting were a sport, you’d be a gold medalist. Flex those skills",
+        "Patience is a virtue, and so is binge-watching your favorite show",
+        "Why not take a power nap? I’ll wake you up… maybe",
+        "Hang tight—perfect time for a snack break! Got popcorn?",
+        "Waiting is just the universe’s way of saying, “Do a little dance!”",
+        "Hold on—time to practice your air guitar solo",
+        "Think of this as a short intermission. Grab a soda and some popcorn",
+        "While you’re waiting, why not perfect your paper airplane technique?"
+    ]
+
+    # Shuffle messages to ensure randomness
+    random.shuffle(messages)
+
+    # Function to update status message with a dancing cursor
+    def update_status_with_cursor(message):
+        cursor_states = ['|', '/', '-', '\\']
+        for cursor in cursor_states:
+            status_text.text(f"{message} {cursor}")
+            time.sleep(0.25)  # Change cursor every 0.25 seconds
+
+    # Update status with a random message and dancing cursor
+    for _ in range(4):  # Display each message for 4 seconds
+        if messages:
+            update_status_with_cursor(messages.pop())
+
+    # Generate slide data with the selected language
+    data = slide_data_gen(topic, num_slides, ollama_model, language)
+    progress_bar.progress(50)
+
+    # Update status with another random message and dancing cursor
+    for _ in range(4):  # Display each message for 4 seconds
+        if messages:
+            update_status_with_cursor(messages.pop())
+
     ppt_file = ppt_gen(data)
+    progress_bar.progress(100)
+
+    # Reset status
+    status_text.text("Presentation ready for download!")
+    progress_bar.empty()
 
-    file_name = f"Presentation.pptx"
+    # Create a file name using the topic, model, and current date
+    date_stamp = datetime.now().strftime("%Y%m%d")
+    sanitized_topic = topic.replace(" ", "_")[:10]  # Truncate topic to 10 characters
+    file_name = f"{sanitized_topic}_{ollama_model}_{date_stamp}.pptx"
 
     st.download_button(
         label="Download Presentation",
         data=ppt_file,
         file_name=file_name,
         mime="application/vnd.openxmlformats-officedocument.presentationml.presentation",
     )
+else:
+    st.warning("Please enter a topic to generate the presentation.")

ppt_data_gen.py

@@ -1,5 +1,5 @@
 import re
-from langchain.llms import Ollama
+from langchain_ollama import OllamaLLM
 
 
 def extract_items(input_string):
@@ -20,61 +20,52 @@ def extract_items(input_string):
     return items
 
 
-def slide_data_gen(topic):
-    llm = Ollama(model="dolphin2.1-mistral",
-                 temperature="0.4")
+def slide_data_gen(topic, num_slides, model, language="English"):
+    llm = OllamaLLM(model=model, temperature="0.4")
 
     slide_data = []
 
     point_count = 5
 
-    slide_data.append(extract_items(llm(f"""
+    # Generate title and subtitle
+    title_subtitle = extract_items(llm.invoke(f"""
     You are a text summarization and formatting specialized model that fetches relevant information
+    For the topic "{topic}" suggest a presentation title and a presentation subtitle in {language}. It should be returned in the format :
+    << "title" | "subtitle" >>
+    """))
 
-    For the topic "{topic}" suggest a presentation title and a presentation subtitle it should be returned in the format :
-    << "title" | "subtitle >>
+    # Check if title and subtitle were extracted correctly
+    if len(title_subtitle) < 2:
+        raise ValueError("Failed to extract title and subtitle from the model's response.")
 
-    example :
-    << "Ethics in Design" | "Integrating Ethics into Design Processes" >>
-    """)))
+    slide_data.append(title_subtitle)
 
-    slide_data.append(extract_items(llm(f"""
+    # Generate table of contents
+    toc = extract_items(llm.invoke(f"""
     You are a text summarization and formatting specialized model that fetches relevant information
-
     For the presentation titled "{slide_data[0][0]}" and with subtitle "{slide_data[0][1]}" for the topic "{topic}"
-    Write a table of contents containing the title of each slide for a 7 slide presentation
+    Write a table of contents containing the title of each slide for a {num_slides} slide presentation in {language}.
     It should be of the format :
     << "slide1" | "slide2" | "slide3" | ... | >>
-
-    example :
-    << "Introduction to Design Ethics" | "User-Centered Design" | "Transparency and Honesty" | "Data Privacy and Security" | "Accessibility and Inclusion" | "Social Impact and Sustainability" | "Ethical AI and Automation" | "Collaboration and Professional Ethics" >>          
-    """)))
+    """))
 
-    for subtopic in slide_data[1]:
+    slide_data.append(toc)
 
-        data_to_clean = llm(f"""
+    for subtopic in slide_data[1]:
+        data_to_clean = llm.invoke(f"""
         You are a content generation specialized model that fetches relevant information and presents it in clear concise manner
-
         For the presentation titled "{slide_data[0][0]}" and with subtitle "{slide_data[0][1]}" for the topic "{topic}"
-        Write the contents for a slide with the subtopic {subtopic}
+        Write the contents for a slide with the subtopic {subtopic} in {language}.
         Write {point_count} points. Each point 10 words maximum.
         Make the points short, concise and to the point.
         """)
 
-        cleaned_data = llm(f"""
+        cleaned_data = llm.invoke(f"""
         You are a text summarization and formatting specialized model that fetches relevant information and formats it into user specified formats
-        Given below is a text draft for a presentation slide containing {point_count} points , extract the {point_count} sentences and format it as :
-
+        Given below is a text draft for a presentation slide containing {point_count} points, extract the {point_count} sentences and format it as:
         << "point1" | "point2" | "point3" | ... | >>
-
-        example :
-        << "Foster a collaborative and inclusive work environment." | "Respect intellectual property rights and avoid plagiarism." | "Uphold professional standards and codes of ethics." | "Be open to feedback and continuous learning." >>
-
-        -- Beginning of the text --
-        {data_to_clean}
-        -- End of the text --         
         """)
-
+        
         slide_data.append([subtopic] + extract_items(cleaned_data))
 
     return slide_data

requirements.txt

@@ -0,0 +1,2 @@
+streamlit
+python-pptx