main app files

app.py

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+import streamlit as st
+from query_graph import query_graph
+
+# Sidebar configuration
+st.sidebar.title("About")
+st.sidebar.markdown("**Authors:** [The SIGHT Project Team](https://sites.miamioh.edu/sight/)")
+st.sidebar.markdown("**Version:** V. 0.0.1")
+st.sidebar.markdown("**Date:** July 24, 2025")
+st.sidebar.markdown("**Model:** gpt4o")
+
+st.sidebar.markdown("---")
+st.sidebar.markdown(
+    "**Funding:** SIGHT is funded by [OHBWC WSIC](https://info.bwc.ohio.gov/for-employers/safety-services/workplace-safety-innovation-center/wsic-overview)"
+)
+
+# References toggle in sidebar
+st.sidebar.markdown("---")
+show_refs = st.sidebar.checkbox("Show references")
+
+
+
+# Main interface
+st.set_page_config(page_title="Miami University's SIGHT Chatbot")
+st.title("Chat with SIGHT")
+st.write("Ask questions about machine safeguarding, LOTO, and hazard prevention based on OSHA/CFR's corpus.")
+
+# Example questions toggled in main window
+with st.expander("Example Questions", expanded=False):
+    st.markdown(
+        "- What are general machine guarding requirements?  \n"
+        "- How do I perform lockout/tagout?  \n"
+        "- Summarize the definition of machine guarding from 29 CFR 1910.211"
+    )
+
+# Initialize chat history
+if 'history' not in st.session_state:
+    st.session_state.history = []
+
+# User input
+query = st.text_input("Your question:")
+if st.button("Send") and query:
+    answer, sources = query_graph(query)
+    st.session_state.history.append({
+        'query': query,
+        'answer': answer,
+        'sources': sources
+    })
+
+# Display chat history
+for i, entry in enumerate(st.session_state.history):
+    st.markdown(f"**You:** {entry['query']}")
+    st.markdown(f"**Assistant:** {entry['answer']}")
+    # Explanations expander
+    with st.expander("Sources used", expanded=False):
+        for src in entry['sources']:
+            st.markdown(f"- {src}")
+
+# Optionally show references list
+if show_refs:
+    refs = [
+        "29 CFR 1910.211", "29 CFR 1910.212", "29 CFR 1910.213", "29 CFR 1910.215",
+        "OSHA 3170", "OSHA 3120", "NIOSH WP Solutions 2011-156", "NIOSH Robotics (2024)"
+    ]
+    for r in refs:
+        st.sidebar.markdown(f"- {r}")
+
+# Footer
+st.markdown("---")
+st.markdown(
+    "**Disclaimer:** *Powered by a Graph RAG to reduce hallucinations; please verify as it can still make mistakes.*"
+    )
+st.markdown(
+    "**Funding:** *We are thankful for [Ohio BWC/WSIC](https://info.bwc.ohio.gov/for-employers/safety-services/workplace-safety-innovation-center/wsic-overview)'s funding that made this chat bot possible.*"
+    )

preprocess.py

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+# SCRIPT 1: PREPROCESS.PY
+# Run this script one time to build and save your knowledge graph.
+
+import os
+import requests
+import json
+from bs4 import BeautifulSoup
+from urllib.parse import urljoin
+import io
+
+from llama_index.core import Document, Settings, StorageContext, KnowledgeGraphIndex, load_index_from_storage
+from llama_index.core.graph_stores import SimpleGraphStore
+from llama_index.llms.openai_multi_modal import OpenAIMultiModal
+from llama_index.embeddings.openai import OpenAIEmbedding
+from llama_index.readers.file import PyMuPDFReader, ImageReader
+from PIL import Image
+
+# 1. Configuration
+# ---
+if not os.getenv("OPENAI_API_KEY"):
+    raise ValueError("OpenAI API key not found. Please set the OPENAI_API_KEY environment variable.")
+
+# Directories for storing data and the final index
+IMAGE_DIR = "image_data"
+STORAGE_DIR = "storage"
+os.makedirs(IMAGE_DIR, exist_ok=True)
+os.makedirs(STORAGE_DIR, exist_ok=True)
+
+# The JSON data you provided (ensure you have the full list here)
+source_data = [
+  {
+    "title": "29 CFR § 1910.211 - Definitions",
+    "url": "https://www.ecfr.gov/current/title-29/part-1910/subpart-O/section-1910.211",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "Provides key legal definitions for terms used throughout Subpart O, such as 'point of operation,' 'guard,' and 'power press,' which are foundational for understanding and applying machine safeguarding rules.",
+    "format": "HTML"
+  },
+  {
+    "title": "29 CFR § 1910.212 - General requirements for all machines",
+    "url": "https://www.ecfr.gov/current/title-29/part-1910/subpart-O/section-1910.212",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "This is the core machine guarding standard, mandating that one or more safeguarding methods be used to protect operators from point-of-operation hazards, ingoing nip points, and other machinery dangers.",
+    "format": "HTML"
+  },
+  {
+    "title": "29 CFR § 1910.213 - Woodworking machinery requirements",
+    "url": "https://www.ecfr.gov/current/title-29/part-1910/subpart-O/section-1910.213",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "Details specific guarding requirements for various woodworking machines, including circular saws, band saws, and jointers, to prevent lacerations and amputations from blade contact.",
+    "format": "HTML"
+  },
+  {
+    "title": "29 CFR § 1910.215 - Abrasive wheel machinery",
+    "url": "https://www.ecfr.gov/current/title-29/part-1910/subpart-O/section-1910.215",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "Specifies safety requirements for abrasive wheel grinders, including guards, flanges, and work rests, to protect workers from wheel breakage, projectiles, and contact with the wheel.",
+    "format": "HTML"
+  },
+  {
+    "title": "29 CFR § 1910.217 - Mechanical power presses",
+    "url": "https://www.ecfr.gov/current/title-29/part-1910/subpart-O/section-1910.217",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "Outlines extensive requirements for mechanical power presses to prevent injuries to hands and fingers, covering guards, devices, clutch/brake mechanisms, and inspection procedures.",
+    "format": "HTML"
+  },
+  {
+    "title": "29 CFR § 1910.219 - Mechanical power-transmission apparatus",
+    "url": "https://www.ecfr.gov/current/title-29/part-1910/subpart-O/section-1910.219",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "Mandates the guarding of mechanical power-transmission components like belts, pulleys, gears, and shafts to prevent caught-in/between injuries from entanglement.",
+    "format": "HTML"
+  },
+  {
+    "title": "Safeguarding Equipment and Protecting Workers from Amputations (OSHA 3170)",
+    "url": "https://www.osha.gov/sites/default/files/publications/osha3170.pdf",
+    "source": "OSHA",
+    "year": 2007,
+    "category": "Technical Guide",
+    "summary": "This guide helps identify and manage amputation hazards from various machines by explaining hazard analysis, machine safeguarding methods, and the importance of hazardous energy control.",
+    "format": "PDF"
+  },
+  {
+    "title": "The Control of Hazardous Energy (Lockout/Tagout) (OSHA 3120)",
+    "url": "https://www.osha.gov/sites/default/files/publications/osha3120.pdf",
+    "source": "OSHA",
+    "year": 2002,
+    "category": "Technical Guide",
+    "summary": "Provides a detailed explanation of the Lockout/Tagout standard (1910.147), offering guidance on energy control procedures, training, and periodic inspections to prevent unexpected machine startup.",
+    "format": "PDF"
+  },
+  {
+    "title": "29 CFR § 1910.147 - The control of hazardous energy (lockout/tagout)",
+    "url": "https://www.ecfr.gov/current/title-29/section-1910.147",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "This regulation establishes the employer's responsibility to protect workers from hazardous energy sources during machine servicing and maintenance by requiring energy isolation and lockout/tagout procedures.",
+    "format": "HTML"
+  },
+  {
+    "title": "29 CFR § 1910.178 - Powered Industrial Trucks",
+    "url": "https://www.ecfr.gov/current/title-29/section-1910.178",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Regulation",
+    "summary": "Covers safety requirements for forklifts and other powered industrial trucks, addressing design, maintenance, and operation to prevent struck-by, caught-in, and crushing incidents.",
+    "format": "HTML"
+  },
+  {
+    "title": "NIOSH Workplace Solutions: Preventing Worker Injuries from Industrial Machines",
+    "url": "https://www.cdc.gov/niosh/docs/wp-solutions/2012-116/",
+    "source": "NIOSH",
+    "year": 2012,
+    "category": "Technical Guide",
+    "summary": "Describes how to prevent machine-related injuries using a combination of engineering controls, administrative controls like LOTO, and personal protective equipment, focusing on the hierarchy of controls.",
+    "format": "HTML",
+    "status": "link broken"
+  },
+  {
+    "title": "Engineering Control Guidelines for Safety in Manufacturing",
+    "url": "https://www.cdc.gov/niosh/docs/2001-123/",
+    "source": "NIOSH",
+    "year": 2001,
+    "category": "Technical Guide",
+    "summary": "Provides guidance on applying engineering controls—the most effective way to reduce workplace hazards—to manufacturing processes, directly supporting the prevention of machine-related incidents.",
+    "format": "HTML"
+  },
+  {
+    "title": "OSHA eTool: Machine Guarding",
+    "url": "https://www.osha.gov/etools/machine-guarding",
+    "source": "OSHA",
+    "year": 2023,
+    "category": "eTool",
+    "summary": "This interactive web tool illustrates the hazards and safeguarding methods for a wide range of machinery, providing visual examples and explanations relevant to preventing struck-by and caught-in injuries.",
+    "format": "HTML"
+  },
+  {
+    "title": "OSHA eTool: Powered Industrial Trucks (Forklifts)",
+    "url": "https://www.osha.gov/etools/powered-industrial-trucks",
+    "source": "OSHA",
+    "year": 2023,
+    "category": "eTool",
+    "summary": "An interactive resource detailing forklift hazards and controls, covering topics like operating procedures, workplace conditions, and stability, which are critical for preventing struck-by incidents.",
+    "format": "HTML"
+  },
+  {
+    "title": "Fact Sheet: Lockout/Tagout",
+    "url": "https://www.osha.gov/sites/default/files/publications/factsheet_lockout-tagout.pdf",
+    "source": "OSHA",
+    "year": 2022,
+    "category": "Fact Sheet",
+    "summary": "A concise summary of the Lockout/Tagout standard, highlighting the purpose and key components of energy control programs to prevent injuries during machine servicing.",
+    "format": "PDF"
+  },
+  {
+    "title": "OSHA Technical Manual (OTM) Section IV: Chapter 5 - Industrial Robots and Robot System Safety",
+    "url": "https://www.osha.gov/otm/section-4/chapter-5",
+    "source": "OSHA",
+    "year": 2017,
+    "category": "Technical Guide",
+    "summary": "Details hazards associated with industrial robots, such as struck-by and caught-between incidents, and outlines safeguarding requirements including guards, presence-sensing devices, and proper work procedures.",
+    "format": "HTML"
+  },
+  {
+    "title": "Safety and Health Topics: Robotics",
+    "url": "https://www.osha.gov/robotics",
+    "source": "OSHA",
+    "year": 2024,
+    "category": "Technical Guide",
+    "summary": "This page provides a comprehensive overview of robotic system hazards and control methods, referencing key consensus standards (like ANSI/RIA R15.06) for preventing injuries.",
+    "format": "HTML"
+  },
+  {
+    "title": "Directive: National Emphasis Program on Amputations in Manufacturing Industries",
+    "url": "https://www.osha.gov/enforcement/directives/cpl-03-00-022",
+    "source": "OSHA",
+    "year": 2019,
+    "category": "Directive",
+    "summary": "Establishes an enforcement program for inspecting workplaces with machinery that poses amputation hazards, focusing on compliance with standards for machine guarding and Lockout/Tagout.",
+    "format": "HTML"
+  },
+  {
+    "title": "NIOSH Topic: Human-Robot Collaboration",
+    "url": "https://www.cdc.gov/niosh/topics/robot/hrc.html",
+    "source": "NIOSH",
+    "year": 2024,
+    "category": "Technical Guide",
+    "summary": "Addresses the unique safety challenges of collaborative robots (cobots), focusing on research to prevent struck-by injuries through better sensor technology, risk assessments, and safety standards.",
+    "format": "HTML"
+  },
+  {
+    "title": "ANSI B11.0-2020: Safety of Machinery",
+    "url": "https://www.assp.org/standards/standards-descriptions/ansi-b11.0-2020-safety-of-machinery",
+    "source": "ANSI",
+    "year": 2020,
+    "category": "Technical Guide",
+    "summary": "This foundational US standard provides the framework for assessing risk and applying safeguarding measures to machinery to achieve an acceptable level of risk, heavily influencing OSHA's approach.",
+    "format": "HTML"
+  },
+  {
+    "title": "ANSI B11.19-2019: Performance Requirements for Safeguarding",
+    "url": "https://webstore.ansi.org/Standards/B11/ANSIB112019",
+    "source": "ANSI",
+    "year": 2019,
+    "category": "Technical Guide",
+    "summary": "Specifies performance requirements for the design, construction, installation, and operation of machine safeguarding methods, including guards, interlocking devices, and safety circuits.",
+    "format": "HTML"
+  }
+]
+
+
+# 2. Helper Functions (Scraping and Processing)
+# ---
+def scrape_and_process_url(item):
+    """Scrapes a URL, extracts text, and downloads images."""
+    url = item.get("url")
+    if not url or item.get("status") == "link broken":
+        print(f"⚠️ Skipping broken or missing URL for: {item['title']}")
+        return [Document(text=item["summary"], metadata=item)]
+
+    print(f"⚙️ Processing URL: {url}")
+    try:
+        headers = {'User-Agent': 'Mozilla/5.0'}
+        response = requests.get(url, headers=headers, timeout=20)
+        response.raise_for_status()
+        content_type = response.headers.get("content-type", "").lower()
+        documents = []
+        metadata = {"source_url": url, "title": item["title"], "category": item["category"]}
+
+        if "pdf" in content_type:
+            pdf_docs = PyMuPDFReader().load(file_path=io.BytesIO(response.content), metadata=metadata)
+            documents.extend(pdf_docs)
+        else:
+            soup = BeautifulSoup(response.content, 'html.parser')
+            text_content = soup.get_text(separator='\n', strip=True)
+            documents.append(Document(text=text_content, metadata=metadata))
+            for img_tag in soup.find_all('img'):
+                img_src = img_tag.get('src')
+                if not img_src: continue
+                img_url = urljoin(url, img_src)
+                try:
+                    img_response = requests.get(img_url, headers=headers, timeout=10)
+                    img_response.raise_for_status()
+                    img_filename = os.path.join(IMAGE_DIR, f"{item['source']}_{len(os.listdir(IMAGE_DIR))}.png")
+                    Image.open(io.BytesIO(img_response.content)).convert("RGB").save(img_filename)
+                except Exception as e: print(f"  ❌ Could not download image {img_url}: {e}")
+        return documents
+    except requests.RequestException as e:
+        print(f"❌ Failed to scrape {url}: {e}")
+        return [Document(text=item["summary"], metadata=item)]
+
+# 3. Execution: Scrape, Build, and Save
+# ---
+print("--- Starting Data Pre-processing ---")
+# Configure LlamaIndex Settings
+Settings.llm = OpenAIMultiModal(model="gpt-4o", max_new_tokens=1000)
+Settings.embed_model = OpenAIEmbedding(model="text-embedding-3-small")
+
+# Scrape all text
+all_documents = []
+for item in source_data:
+    all_documents.extend(scrape_and_process_url(item))
+
+# Process all images and generate descriptions
+image_documents = ImageReader(text_parser=Settings.llm).load_data(IMAGE_DIR)
+all_documents.extend(image_documents)
+print(f"\n✅ Total documents loaded: {len(all_documents)}")
+
+# Build the Knowledge Graph Index
+print("\n--- Building Knowledge Graph ---")
+graph_store = SimpleGraphStore()
+storage_context = StorageContext.from_defaults(graph_store=graph_store)
+index = KnowledgeGraphIndex.from_documents(
+    documents=all_documents,
+    storage_context=storage_context,
+    max_triplets_per_chunk=5,
+    include_embeddings=True,
+    show_progress=True,
+)
+
+# Persist the index to disk
+index.storage_context.persist(persist_dir=STORAGE_DIR)
+print(f"\n✅✅✅ Graph built and saved to disk at '{STORAGE_DIR}'! You can now run query.py. ✅✅✅")

query_graph.py

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+import os
+import numpy as np
+from dotenv import load_dotenv
+from openai import OpenAI
+import networkx as nx
+from sklearn.metrics.pairwise import cosine_similarity
+
+# Initialize OpenAI client
+load_dotenv(override=True)
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+# Load graph from GML
+G = nx.read_gml("graph.gml")
+enodes = list(G.nodes)
+embeddings = np.array([G.nodes[n]['embedding'] for n in enodes])
+
+def query_graph(question, top_k=5):
+    # Embed question
+    emb_resp = client.embeddings.create(
+        model="text-embedding-3-large",
+        input=question
+    )
+    q_vec = emb_resp.data[0].embedding
+    sims = cosine_similarity([q_vec], embeddings)[0]
+    idxs = sims.argsort()[::-1][:top_k]
+
+    # Gather context and sources
+    context = [G.nodes[enodes[i]]['text'] for i in idxs]
+    sources = list({G.nodes[enodes[i]]['source'] for i in idxs})
+
+    # Generate answer
+    prompt = (
+        "Use the following context to answer the question:\n\n"
+        + "\n\n---\n\n".join(context)
+        + f"\n\nQuestion: {question}\nAnswer:")
+    chat_resp = client.chat.completions.create(
+        model="gpt-4o-mini",
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant for XR safety training."},
+            {"role": "user", "content": prompt}
+        ]
+    )
+    answer = chat_resp.choices[0].message.content
+    return answer, sources
+
+
+# Test queries
+test_questions = [
+    "What are general machine guarding requirements?",
+    "Explain the key steps in lockout/tagout procedures."
+]
+
+for q in test_questions:
+    ans, srcs = query_graph(q)
+    print(f"Q: {q}\nA: {ans}\nSources: {srcs}\n")