Create app.py

app.py

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+#!/usr/bin/env python3
+import os
+import shutil
+import glob
+import base64
+import streamlit as st
+import pandas as pd
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from torch.utils.data import Dataset, DataLoader
+import csv
+import time
+from dataclasses import dataclass
+from typing import Optional, Tuple
+import zipfile
+import math
+from PIL import Image
+import random
+import logging
+
+# Set up logging for feedback
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Page Configuration with Humor
+st.set_page_config(
+    page_title="SFT Tiny Titans 🚀",
+    page_icon="🤖",
+    layout="wide",
+    initial_sidebar_state="expanded",
+    menu_items={
+        'Get Help': 'https://huggingface.co/awacke1',
+        'Report a bug': 'https://huggingface.co/spaces/awacke1',
+        'About': "Tiny Titans: Small models, big dreams, and a sprinkle of chaos! 🌌"
+    }
+)
+
+# [Previous sections like ModelConfig, SFTDataset, ModelBuilder, Utility Functions remain unchanged...]
+
+# Cargo Travel Time Tool (Now a Proper smolagents Tool)
+from smolagents import tool
+
+@tool
+def calculate_cargo_travel_time(origin_coords: Tuple[float, float], destination_coords: Tuple[float, float], cruising_speed_kmh: float = 750.0) -> float:
+    """Calculate cargo plane travel time between two coordinates."""
+    def to_radians(degrees: float) -> float:
+        return degrees * (math.pi / 180)
+    lat1, lon1 = map(to_radians, origin_coords)
+    lat2, lon2 = map(to_radians, destination_coords)
+    EARTH_RADIUS_KM = 6371.0
+    dlon = lon2 - lon1
+    dlat = lat2 - lat1
+    a = (math.sin(dlat / 2) ** 2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon / 2) ** 2)
+    c = 2 * math.asin(math.sqrt(a))
+    distance = EARTH_RADIUS_KM * c
+    actual_distance = distance * 1.1
+    flight_time = (actual_distance / cruising_speed_kmh) + 1.0
+    return round(flight_time, 2)
+
+# Main App
+st.title("SFT Tiny Titans 🚀 (Small but Mighty!)")
+
+# Sidebar with Galleries (unchanged)
+st.sidebar.header("Galleries & Shenanigans 🎨")
+st.sidebar.subheader("Image Gallery 📸")
+img_files = get_gallery_files(["png", "jpg", "jpeg"])
+if img_files:
+    img_cols = st.sidebar.slider("Image Columns 📸", 1, 5, 3)
+    cols = st.sidebar.columns(img_cols)
+    for idx, img_file in enumerate(img_files[:img_cols * 2]):
+        with cols[idx % img_cols]:
+            st.image(Image.open(img_file), caption=f"{img_file} 🖼", use_column_width=True)
+
+st.sidebar.subheader("CSV Gallery 📊")
+csv_files = get_gallery_files(["csv"])
+if csv_files:
+    for csv_file in csv_files[:5]:
+        st.sidebar.markdown(get_download_link(csv_file, "text/csv", f"{csv_file} 📊"), unsafe_allow_html=True)
+
+st.sidebar.subheader("Model Management 🗂️")
+model_dirs = get_model_files()
+selected_model = st.sidebar.selectbox("Select Saved Model", ["None"] + model_dirs)
+if selected_model != "None" and st.sidebar.button("Load Model 📂"):
+    if 'builder' not in st.session_state:
+        st.session_state['builder'] = ModelBuilder()
+    config = ModelConfig(name=os.path.basename(selected_model), base_model="unknown", size="small", domain="general")
+    st.session_state['builder'].load_model(selected_model, config)
+    st.session_state['model_loaded'] = True
+    st.rerun()
+
+# Main UI with Tabs (only Tab 4 updated here)
+tab1, tab2, tab3, tab4 = st.tabs(["Build Tiny Titan 🌱", "Fine-Tune Titan 🔧", "Test Titan 🧪", "Agentic RAG Party 🌐"])
+
+# [Tab 1, Tab 2, Tab 3 remain unchanged...]
+
+with tab4:
+    st.header("Agentic RAG Party 🌐 (Party Like It’s 2099!)")
+    st.write("This demo uses Tiny Titans with Agentic RAG to plan a superhero party, powered by DuckDuckGo retrieval!")
+
+    if st.button("Run Agentic RAG Demo 🎉"):
+        try:
+            from smolagents import CodeAgent, DuckDuckGoSearchTool, VisitWebpageTool
+            from transformers import AutoModelForCausalLM
+
+            # Load the model
+            with st.spinner("Loading SmolLM-135M... ⏳ (Titan’s suiting up!)"):
+                model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolLM-135M")
+                st.write("Model loaded! 🦸‍♂️ (Ready to party!)")
+
+            # Initialize agent with proper tools
+            agent = CodeAgent(
+                model=model,
+                tools=[DuckDuckGoSearchTool(), VisitWebpageTool(), calculate_cargo_travel_time],
+                additional_authorized_imports=["pandas"],
+                planning_interval=5,
+                verbosity_level=2,
+                max_steps=15,
+            )
+            
+            task = """
+Plan a luxury superhero-themed party at Wayne Manor (42.3601° N, 71.0589° W). Use DuckDuckGo to search for the latest superhero party trends,
+refine results for luxury elements (decorations, entertainment, catering), and calculate cargo travel times from key locations 
+(New York: 40.7128° N, 74.0060° W; LA: 34.0522° N, 118.2437° W; London: 51.5074° N, 0.1278° W) to Wayne Manor. 
+Synthesize a plan with at least 6 entries in a pandas dataframe, including locations, travel times, and luxury ideas.
+Add a random superhero catchphrase to each entry for fun!
+"""
+            with st.spinner("Planning the ultimate superhero bash... ⏳ (Calling all caped crusaders!)"):
+                result = agent.run(task)
+                st.write("Agentic RAG Party Plan:")
+                st.write(result)
+                st.write("Party on, Wayne! 🦸‍♂️🎉")
+        except ImportError:
+            st.error("Please install required packages: `pip install smolagents pandas transformers`")
+        except TypeError as e:
+            st.error(f"Agent setup failed: {str(e)} (Looks like the Titans need a tune-up!)")
+        except Exception as e:
+            st.error(f"Error running demo: {str(e)} (Even Batman has off days!)")