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| #!/usr/bin/env python3 | |
| import os | |
| import re | |
| import glob | |
| import json | |
| import base64 | |
| import zipfile | |
| import random | |
| import requests | |
| import openai | |
| from PIL import Image | |
| from urllib.parse import quote | |
| import streamlit as st | |
| import streamlit.components.v1 as components | |
| # If you do model inference via huggingface_hub: | |
| from huggingface_hub import InferenceClient | |
| # ---------------------------- | |
| # Configurable BASE_URL | |
| # ---------------------------- | |
| BASE_URL = "https://huggingface.co/spaces/awacke1/MermaidMarkdownDiagramEditor" | |
| # Example placeholders for prompt prefixes | |
| PromptPrefix = "AI-Search: " | |
| PromptPrefix2 = "AI-Refine: " | |
| PromptPrefix3 = "AI-JS: " | |
| # Example roleplaying glossary | |
| roleplaying_glossary = { | |
| "Core Rulebooks": { | |
| "Dungeons and Dragons": ["Player's Handbook", "Dungeon Master's Guide", "Monster Manual"], | |
| "GURPS": ["Basic Set Characters", "Basic Set Campaigns"] | |
| }, | |
| "Campaigns & Adventures": { | |
| "Pathfinder": ["Rise of the Runelords", "Curse of the Crimson Throne"] | |
| } | |
| } | |
| # Example transhuman glossary | |
| transhuman_glossary = { | |
| "Neural Interfaces": ["Cortex Jack", "Mind-Machine Fusion"], | |
| "Cybernetics": ["Robotic Limbs", "Augmented Eyes"], | |
| } | |
| # Simple function stubs | |
| def process_text(text): | |
| st.write(f"process_text called with: {text}") | |
| def search_arxiv(text): | |
| st.write(f"search_arxiv called with: {text}") | |
| def SpeechSynthesis(text): | |
| st.write(f"SpeechSynthesis called with: {text}") | |
| def process_image(image_file, prompt): | |
| return f"[process_image placeholder] Processing {image_file} with prompt: {prompt}" | |
| def process_video(video_file, seconds_per_frame): | |
| st.write(f"[process_video placeholder] Video: {video_file}, seconds/frame: {seconds_per_frame}") | |
| # Stub if you have a Hugging Face endpoint | |
| API_URL = "https://huggingface-inference-endpoint-placeholder" | |
| API_KEY = "hf_XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX" | |
| def InferenceLLM(prompt): | |
| return f"[InferenceLLM placeholder response to prompt: {prompt}]" | |
| # ------------------------------------------ | |
| # Glossary & File Utility | |
| # ------------------------------------------ | |
| def display_glossary_entity(k): | |
| """ | |
| Creates multiple link emojis for a single entity. | |
| """ | |
| search_urls = { | |
| "🚀🌌ArXiv": lambda x: f"/?q={quote(x)}", | |
| "🃏Analyst": lambda x: f"/?q={quote(x)}-{quote(PromptPrefix)}", | |
| "📚PyCoder": lambda x: f"/?q={quote(x)}-{quote(PromptPrefix2)}", | |
| "🔬JSCoder": lambda x: f"/?q={quote(x)}-{quote(PromptPrefix3)}", | |
| "📖": lambda x: f"https://en.wikipedia.org/wiki/{quote(x)}", | |
| "🔍": lambda x: f"https://www.google.com/search?q={quote(x)}", | |
| "🔎": lambda x: f"https://www.bing.com/search?q={quote(x)}", | |
| "🎥": lambda x: f"https://www.youtube.com/results?search_query={quote(x)}", | |
| "🐦": lambda x: f"https://twitter.com/search?q={quote(x)}", | |
| } | |
| links_md = ' '.join([f"[{emoji}]({url(k)})" for emoji, url in search_urls.items()]) | |
| st.markdown(f"**{k}** <small>{links_md}</small>", unsafe_allow_html=True) | |
| def display_content_or_image(query): | |
| """ | |
| If a query matches something in transhuman_glossary or a local image, show it. | |
| """ | |
| for category, term_list in transhuman_glossary.items(): | |
| for term in term_list: | |
| if query.lower() in term.lower(): | |
| st.subheader(f"Found in {category}:") | |
| st.write(term) | |
| return True | |
| image_path = f"images/{query}.png" | |
| if os.path.exists(image_path): | |
| st.image(image_path, caption=f"Image for {query}") | |
| return True | |
| st.warning("No matching content or image found.") | |
| return False | |
| def clear_query_params(): | |
| """ | |
| For clearing URL params, you'd typically use a new link or st.experimental_set_query_params(). | |
| Here, we just warn the user. | |
| """ | |
| st.warning("Define a redirect or link without query params if you want to truly clear them.") | |
| # ----------------------- | |
| # File Handling | |
| # ----------------------- | |
| def load_file(file_path): | |
| try: | |
| with open(file_path, "r", encoding='utf-8') as f: | |
| return f.read() | |
| except: | |
| return "" | |
| def create_zip_of_files(files): | |
| zip_name = "Arxiv-Paper-Search-QA-RAG-Streamlit-Gradio-AP.zip" | |
| with zipfile.ZipFile(zip_name, 'w') as zipf: | |
| for file in files: | |
| zipf.write(file) | |
| return zip_name | |
| def get_zip_download_link(zip_file): | |
| with open(zip_file, 'rb') as f: | |
| data = f.read() | |
| b64 = base64.b64encode(data).decode() | |
| return f'<a href="data:application/zip;base64,{b64}" download="{zip_file}">Download All</a>' | |
| def get_table_download_link(file_path): | |
| """ | |
| Creates a download link for a single file from your snippet. | |
| """ | |
| try: | |
| with open(file_path, 'r', encoding='utf-8') as file: | |
| data = file.read() | |
| b64 = base64.b64encode(data.encode()).decode() | |
| file_name = os.path.basename(file_path) | |
| ext = os.path.splitext(file_name)[1] | |
| mime_map = { | |
| '.txt': 'text/plain', | |
| '.py': 'text/plain', | |
| '.xlsx': 'text/plain', | |
| '.csv': 'text/plain', | |
| '.htm': 'text/html', | |
| '.md': 'text/markdown', | |
| '.wav': 'audio/wav' | |
| } | |
| mime_type = mime_map.get(ext, 'application/octet-stream') | |
| return f'<a href="data:{mime_type};base64,{b64}" target="_blank" download="{file_name}">{file_name}</a>' | |
| except: | |
| return '' | |
| def get_file_size(file_path): | |
| return os.path.getsize(file_path) | |
| def FileSidebar(): | |
| """ | |
| Renders .md files, providing open/view/delete/run logic in the sidebar. | |
| """ | |
| all_files = glob.glob("*.md") | |
| # Exclude short-named or special files if needed | |
| all_files = [f for f in all_files if len(os.path.splitext(f)[0]) >= 5] | |
| all_files.sort(key=lambda x: (os.path.splitext(x)[1], x), reverse=True) | |
| Files1, Files2 = st.sidebar.columns(2) | |
| with Files1: | |
| if st.button("🗑 Delete All"): | |
| for file in all_files: | |
| os.remove(file) | |
| st.rerun() | |
| with Files2: | |
| if st.button("⬇️ Download"): | |
| zip_file = create_zip_of_files(all_files) | |
| st.sidebar.markdown(get_zip_download_link(zip_file), unsafe_allow_html=True) | |
| file_contents = '' | |
| file_name = '' | |
| next_action = '' | |
| for file in all_files: | |
| col1, col2, col3, col4, col5 = st.sidebar.columns([1, 6, 1, 1, 1]) | |
| with col1: | |
| if st.button("🌐", key="md_" + file): | |
| file_contents = load_file(file) | |
| file_name = file | |
| next_action = 'md' | |
| st.session_state['next_action'] = next_action | |
| with col2: | |
| st.markdown(get_table_download_link(file), unsafe_allow_html=True) | |
| with col3: | |
| if st.button("📂", key="open_" + file): | |
| file_contents = load_file(file) | |
| file_name = file | |
| next_action = 'open' | |
| st.session_state['lastfilename'] = file | |
| st.session_state['filename'] = file | |
| st.session_state['filetext'] = file_contents | |
| st.session_state['next_action'] = next_action | |
| with col4: | |
| if st.button("▶️", key="read_" + file): | |
| file_contents = load_file(file) | |
| file_name = file | |
| next_action = 'search' | |
| st.session_state['next_action'] = next_action | |
| with col5: | |
| if st.button("🗑", key="delete_" + file): | |
| os.remove(file) | |
| st.rerun() | |
| # If we loaded a file | |
| if file_contents: | |
| if next_action == 'open': | |
| open1, open2 = st.columns([0.8, 0.2]) | |
| with open1: | |
| file_name_input = st.text_input('File Name:', file_name, key='file_name_input') | |
| file_content_area = st.text_area('File Contents:', file_contents, height=300, key='file_content_area') | |
| if st.button('💾 Save File'): | |
| with open(file_name_input, 'w', encoding='utf-8') as f: | |
| f.write(file_content_area) | |
| st.markdown(f'Saved {file_name_input} successfully.') | |
| elif next_action == 'search': | |
| file_content_area = st.text_area("File Contents:", file_contents, height=500) | |
| user_prompt = PromptPrefix2 + file_contents | |
| st.markdown(user_prompt) | |
| if st.button('🔍Re-Code'): | |
| search_arxiv(file_contents) | |
| elif next_action == 'md': | |
| st.markdown(file_contents) | |
| SpeechSynthesis(file_contents) | |
| if st.button("🔍Run"): | |
| st.write("Running GPT logic placeholder...") | |
| # --------------------------- | |
| # Scoring / Glossaries | |
| # --------------------------- | |
| score_dir = "scores" | |
| os.makedirs(score_dir, exist_ok=True) | |
| def generate_key(label, header, idx): | |
| return f"{header}_{label}_{idx}_key" | |
| def update_score(key, increment=1): | |
| """ | |
| Track a 'score' for each glossary item or term, saved in JSON per key. | |
| """ | |
| score_file = os.path.join(score_dir, f"{key}.json") | |
| if os.path.exists(score_file): | |
| with open(score_file, "r") as file: | |
| score_data = json.load(file) | |
| else: | |
| score_data = {"clicks": 0, "score": 0} | |
| score_data["clicks"] += increment | |
| score_data["score"] += increment | |
| with open(score_file, "w") as file: | |
| json.dump(score_data, file) | |
| return score_data["score"] | |
| def load_score(key): | |
| file_path = os.path.join(score_dir, f"{key}.json") | |
| if os.path.exists(file_path): | |
| with open(file_path, "r") as file: | |
| score_data = json.load(file) | |
| return score_data["score"] | |
| return 0 | |
| def display_buttons_with_scores(num_columns_text): | |
| """ | |
| Show glossary items as clickable buttons that increment a 'score'. | |
| """ | |
| game_emojis = { | |
| "Dungeons and Dragons": "🐉", | |
| "Call of Cthulhu": "🐙", | |
| "GURPS": "🎲", | |
| "Pathfinder": "🗺️", | |
| "Kindred of the East": "🌅", | |
| "Changeling": "🍃", | |
| } | |
| topic_emojis = { | |
| "Core Rulebooks": "📚", | |
| "Maps & Settings": "🗺️", | |
| "Game Mechanics & Tools": "⚙️", | |
| "Monsters & Adversaries": "👹", | |
| "Campaigns & Adventures": "📜", | |
| "Creatives & Assets": "🎨", | |
| "Game Master Resources": "🛠️", | |
| "Lore & Background": "📖", | |
| "Character Development": "🧍", | |
| "Homebrew Content": "🔧", | |
| "General Topics": "🌍", | |
| } | |
| for category, games in roleplaying_glossary.items(): | |
| category_emoji = topic_emojis.get(category, "🔍") | |
| st.markdown(f"## {category_emoji} {category}") | |
| for game, terms in games.items(): | |
| game_emoji = game_emojis.get(game, "🎮") | |
| for term in terms: | |
| key = f"{category}_{game}_{term}".replace(' ', '_').lower() | |
| score_val = load_score(key) | |
| if st.button(f"{game_emoji} {category} {game} {term} {score_val}", key=key): | |
| newscore = update_score(key.replace('?', '')) | |
| st.markdown(f"Scored **{category} - {game} - {term}** -> {newscore}") | |
| # ------------------------------- | |
| # Image & Video | |
| # ------------------------------- | |
| def display_images_and_wikipedia_summaries(num_columns=4): | |
| image_files = [f for f in os.listdir('.') if f.endswith('.png')] | |
| if not image_files: | |
| st.write("No PNG images found in the current directory.") | |
| return | |
| image_files_sorted = sorted(image_files, key=lambda x: len(x.split('.')[0])) | |
| cols = st.columns(num_columns) | |
| col_index = 0 | |
| for image_file in image_files_sorted: | |
| with cols[col_index % num_columns]: | |
| try: | |
| image = Image.open(image_file) | |
| st.image(image, use_column_width=True) | |
| k = image_file.split('.')[0] | |
| display_glossary_entity(k) | |
| image_text_input = st.text_input(f"Prompt for {image_file}", key=f"image_prompt_{image_file}") | |
| if image_text_input: | |
| response = process_image(image_file, image_text_input) | |
| st.markdown(response) | |
| except: | |
| st.write(f"Could not open {image_file}") | |
| col_index += 1 | |
| def display_videos_and_links(num_columns=4): | |
| video_files = [f for f in os.listdir('.') if f.endswith(('.mp4', '.webm'))] | |
| if not video_files: | |
| st.write("No MP4 or WEBM videos found in the current directory.") | |
| return | |
| video_files_sorted = sorted(video_files, key=lambda x: len(x.split('.')[0])) | |
| cols = st.columns(num_columns) | |
| col_index = 0 | |
| for video_file in video_files_sorted: | |
| with cols[col_index % num_columns]: | |
| k = video_file.split('.')[0] | |
| st.video(video_file, format='video/mp4', start_time=0) | |
| display_glossary_entity(k) | |
| video_text_input = st.text_input(f"Video Prompt for {video_file}", key=f"video_prompt_{video_file}") | |
| if video_text_input: | |
| try: | |
| seconds_per_frame = 10 | |
| process_video(video_file, seconds_per_frame) | |
| except ValueError: | |
| st.error("Invalid input for seconds per frame!") | |
| col_index += 1 | |
| # -------------------------------- | |
| # MERMAID DIAGRAM | |
| # -------------------------------- | |
| def generate_mermaid_html(mermaid_code: str) -> str: | |
| """ | |
| Returns HTML that centers the Mermaid diagram, loading from a CDN. | |
| """ | |
| return f""" | |
| <html> | |
| <head> | |
| <script src="https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js"></script> | |
| <style> | |
| .centered-mermaid {{ | |
| display: flex; | |
| justify-content: center; | |
| margin: 20px auto; | |
| }} | |
| .mermaid {{ | |
| max-width: 800px; | |
| }} | |
| </style> | |
| </head> | |
| <body> | |
| <div class="mermaid centered-mermaid"> | |
| {mermaid_code} | |
| </div> | |
| <script> | |
| mermaid.initialize({{ startOnLoad: true }}); | |
| </script> | |
| </body> | |
| </html> | |
| """ | |
| def append_model_param(url: str, model_selected: bool) -> str: | |
| """ | |
| If user checks 'Append ?model=1', we append &model=1 or ?model=1 if not present. | |
| """ | |
| if not model_selected: | |
| return url | |
| delimiter = "&" if "?" in url else "?" | |
| return f"{url}{delimiter}model=1" | |
| def inject_base_url(url: str) -> str: | |
| """ | |
| If a link does not start with http, prepend your BASE_URL | |
| so it becomes an absolute link to huggingface.co/spaces/... | |
| """ | |
| if url.startswith("http"): | |
| return url | |
| return f"{BASE_URL}{url}" | |
| # Our default diagram, containing the "click" lines with /?q=... | |
| DEFAULT_MERMAID = """ | |
| flowchart LR | |
| U((User 😎)) -- "Talk 🗣️" --> LLM[LLM Agent 🤖\\nExtract Info] | |
| click U "/?q=User%20😎" _self | |
| click LLM "/?q=LLM%20Agent%20Extract%20Info" _blank | |
| LLM -- "Query 🔍" --> HS[Hybrid Search 🔎\\nVector+NER+Lexical] | |
| click HS "/?q=Hybrid%20Search%20Vector+NER+Lexical" _blank | |
| HS -- "Reason 🤔" --> RE[Reasoning Engine 🛠️\\nNeuralNetwork+Medical] | |
| click RE "/?q=Reasoning%20Engine%20NeuralNetwork+Medical" _blank | |
| RE -- "Link 📡" --> KG((Knowledge Graph 📚\\nOntology+GAR+RAG)) | |
| click KG "/?q=Knowledge%20Graph%20Ontology+GAR+RAG" _blank | |
| """ | |
| def main(): | |
| st.set_page_config(page_title="Mermaid + Clickable Links with Base URL", layout="wide") | |
| # --------------------------------------------- | |
| # Query Param Parsing (non-experimental) | |
| # --------------------------------------------- | |
| query_params = st.query_params | |
| query_list = (query_params.get('q') or query_params.get('query') or ['']) | |
| q_or_query = query_list[0] if query_list else '' | |
| if q_or_query.strip(): | |
| # If there's a q= or query= param, do some processing | |
| search_payload = PromptPrefix + q_or_query | |
| st.markdown(search_payload) | |
| process_text(search_payload) | |
| # If an 'action' param is present | |
| if 'action' in query_params: | |
| action_list = query_params['action'] | |
| if action_list: | |
| action = action_list[0] | |
| if action == 'show_message': | |
| st.success("Showing a message because 'action=show_message' was found in the URL.") | |
| elif action == 'clear': | |
| clear_query_params() | |
| # If a 'query' param is present, show content or image | |
| if 'query' in query_params: | |
| query_val = query_params['query'][0] | |
| display_content_or_image(query_val) | |
| # --------------------------------------------- | |
| # Let user pick if we want ?model=1 | |
| # --------------------------------------------- | |
| st.sidebar.write("## Diagram Link Settings") | |
| model_selected = st.sidebar.checkbox("Append ?model=1 to each link?") | |
| # --------------------------------------------- | |
| # Rebuild the clickable lines in the Mermaid code | |
| # --------------------------------------------- | |
| base_diagram = DEFAULT_MERMAID | |
| lines = base_diagram.strip().split("\n") | |
| new_lines = [] | |
| for line in lines: | |
| # We look for lines like: click SOMENODE "/?q=Something" _self | |
| if "click " in line and '"/?' in line: | |
| # Try to extract the URL part | |
| parts = re.split(r'click\s+\S+\s+"([^"]+)"\s+("_self")', line) | |
| if len(parts) == 4: | |
| # Example: | |
| # parts[0] -> 'click LLM ' | |
| # parts[1] -> '/?q=LLM%20Agent%20Extract%20Info' | |
| # parts[2] -> ' _self' | |
| # parts[3] -> '' or trailing | |
| old_url = parts[1] | |
| # 1) Prepend base if needed | |
| new_url = inject_base_url(old_url) | |
| # 2) Possibly add &model=1 | |
| new_url = append_model_param(new_url, model_selected) | |
| # Recombine | |
| new_line = f"{parts[0]}\"{new_url}\" {parts[2]}" | |
| new_lines.append(new_line) | |
| else: | |
| # If we can't parse it, keep it as is | |
| new_lines.append(line) | |
| else: | |
| new_lines.append(line) | |
| mermaid_code = "\n".join(new_lines) | |
| # --------------------------------------------- | |
| # Render the top-centered Mermaid diagram | |
| # --------------------------------------------- | |
| st.sidebar.markdown("Mermaid Diagram with Base URL Injection") | |
| diagram_html = generate_mermaid_html(mermaid_code) | |
| components.html(diagram_html, height=400, scrolling=True) | |
| # --------------------------------------------- | |
| # Two-column interface: Markdown & Mermaid | |
| # --------------------------------------------- | |
| left_col, right_col = st.columns(2) | |
| # --- Left: Markdown Editor | |
| with left_col: | |
| st.subheader("Markdown Side 📝") | |
| if "markdown_text" not in st.session_state: | |
| st.session_state["markdown_text"] = "## Hello!\nType some *Markdown* here.\n" | |
| markdown_text = st.text_area( | |
| "Edit Markdown:", | |
| value=st.session_state["markdown_text"], | |
| height=300 | |
| ) | |
| st.session_state["markdown_text"] = markdown_text | |
| colA, colB = st.columns(2) | |
| with colA: | |
| if st.button("🔄 Refresh Markdown"): | |
| st.write("**Markdown** content refreshed! 🍿") | |
| with colB: | |
| if st.button("❌ Clear Markdown"): | |
| st.session_state["markdown_text"] = "" | |
| st.rerun() | |
| st.markdown("---") | |
| st.markdown("**Preview:**") | |
| st.markdown(markdown_text) | |
| # --- Right: Mermaid Editor | |
| with right_col: | |
| st.subheader("Mermaid Side 🧜♂️") | |
| # We store the final code in session state, so user can edit | |
| if "current_mermaid" not in st.session_state: | |
| st.session_state["current_mermaid"] = mermaid_code | |
| mermaid_input = st.text_area( | |
| "Edit Mermaid Code:", | |
| value=st.session_state["current_mermaid"], | |
| height=300 | |
| ) | |
| colC, colD = st.columns(2) | |
| with colC: | |
| if st.button("🎨 Refresh Diagram"): | |
| st.session_state["current_mermaid"] = mermaid_input | |
| st.write("**Mermaid** diagram refreshed! 🌈") | |
| st.rerun() | |
| with colD: | |
| if st.button("❌ Clear Mermaid"): | |
| st.session_state["current_mermaid"] = "" | |
| st.rerun() | |
| st.markdown("---") | |
| st.markdown("**Mermaid Source:**") | |
| st.code(mermaid_input, language="python", line_numbers=True) | |
| # --------------------------------------------- | |
| # Media Galleries | |
| # --------------------------------------------- | |
| st.markdown("---") | |
| st.header("Media Galleries") | |
| num_columns_images = st.slider("Choose Number of Image Columns", 1, 15, 5, key="num_columns_images") | |
| display_images_and_wikipedia_summaries(num_columns_images) | |
| num_columns_video = st.slider("Choose Number of Video Columns", 1, 15, 5, key="num_columns_video") | |
| display_videos_and_links(num_columns_video) | |
| # (Optionally) Extended text interface | |
| showExtendedTextInterface = False | |
| if showExtendedTextInterface: | |
| # For example: | |
| # display_glossary_grid(roleplaying_glossary) | |
| # num_columns_text = st.slider("Choose Number of Text Columns", 1, 15, 4) | |
| # display_buttons_with_scores(num_columns_text) | |
| pass | |
| # --------------------------------------------- | |
| # File Sidebar | |
| # --------------------------------------------- | |
| FileSidebar() | |
| # --------------------------------------------- | |
| # Random Title at the bottom | |
| # --------------------------------------------- | |
| titles = [ | |
| "🧠🎭 Semantic Symphonies & Episodic Encores", | |
| "🌌🎼 AI Rhythms of Memory Lane", | |
| "🎭🎉 Cognitive Crescendos & Neural Harmonies", | |
| "🧠🎺 Mnemonic Melodies & Synaptic Grooves", | |
| "🎼🎸 Straight Outta Cognition", | |
| "🥁🎻 Jazzy Jambalaya of AI Memories", | |
| "🏰 Semantic Soul & Episodic Essence", | |
| "🥁🎻 The Music Of AI's Mind" | |
| ] | |
| st.markdown(f"**{random.choice(titles)}**") | |
| if __name__ == "__main__": | |
| main() | |