update

app.py

@@ -3,6 +3,8 @@ from huggingface_hub import InferenceClient
 from sentence_transformers import SentenceTransformer
 import torch
 
+
+
 # Theme
 theme = gr.themes.Soft(
    primary_hue="rose",
@@ -10,19 +12,25 @@ theme = gr.themes.Soft(
    neutral_hue="pink"
 )
 
+
+
 custom_css = """
 :root {
-  --background-fill-primary: #FFB6C2 !important;
+   --background-fill-primary: #FFB6C2 !important;
 }
 .dark {
-  --background-fill-primary: #FFB6C1 !important;
+   --background-fill-primary: #FFB6C1 !important;
 }
 """
 
+
+
 # Load research file
 with open("research.txt", "r", encoding="utf-8") as file:
    research_text = file.read()
 
+
+
 # Preprocess text
 def preprocess_text(text):
    cleaned_text = text.strip()
@@ -30,17 +38,27 @@ def preprocess_text(text):
    cleaned_chunks = [chunk.strip() for chunk in chunks if chunk.strip() != ""]
    return cleaned_chunks
 
+
+
 cleaned_chunks = preprocess_text(research_text)
 
+
+
 # Create embeddings
 model = SentenceTransformer('all-MiniLM-L6-v2')
 
+
+
 def create_embeddings(text_chunks):
    chunk_embeddings = model.encode(text_chunks, convert_to_tensor=True)
    return chunk_embeddings
 
+
+
 chunk_embeddings = create_embeddings(cleaned_chunks)
 
+
+
 # Get top chunks
 def get_top_chunks(query, chunk_embeddings, text_chunks):
    query_embedding = model.encode(query, convert_to_tensor=True)
@@ -51,9 +69,13 @@ def get_top_chunks(query, chunk_embeddings, text_chunks):
    top_chunks = [text_chunks[i] for i in top_indices]
    return top_chunks
 
+
+
 # Inference client
 client = InferenceClient("Qwen/Qwen2.5-72B-Instruct")
 
+
+
 def respond(message, history):
    top_results = get_top_chunks(message, chunk_embeddings, cleaned_chunks)
    str_top_results = '\n'.join(top_results)
@@ -63,6 +85,9 @@ def respond(message, history):
    if history:
        messages.extend(history)
    messages.append({'role': 'user', 'content': message})
+
+
+
    response = client.chat_completion(
        messages,
        max_tokens=1000,
@@ -70,9 +95,13 @@ def respond(message, history):
    )
    return response['choices'][0]['message']['content'].strip()
 
+
+
 def display_image():
    return "KWKbanner.png"
 
+
+
 # Explore Page Info
 def show_info(topic):
    responses = {
@@ -84,53 +113,377 @@ def show_info(topic):
    }
    return responses.get(topic, "Select a category to see the corresponding careers.")
 
-# Embedded resource data directly here
-career_resources = {
-    "Data Scientist": {
-        "skills": [
-            ("Python Basics", "https://www.learnpython.org/"),
-            ("Kaggle for Practice", "https://www.kaggle.com/")
-        ],
-        "major": "Computer Science, Statistics, Data Science",
-        "classes": ["Statistics", "Machine Learning", "Data Structures"],
-        "youtube": "<iframe width='100%' height='315' src='https://www.youtube.com/embed/xC-c7E5PK0Y' frameborder='0' allowfullscreen></iframe>"
-    },
-    "Software Developer": {
-        "skills": [
-            ("W3Schools HTML/CSS", "https://www.w3schools.com/"),
-            ("freeCodeCamp", "https://www.freecodecamp.org/")
-        ],
-        "major": "Computer Science, Software Engineering",
-        "classes": ["Intro to Programming", "Operating Systems", "Algorithms"],
-        "youtube": "<iframe width='100%' height='315' src='https://www.youtube.com/embed/bSrm9RXwBaI' frameborder='0' allowfullscreen></iframe>"
-    },
-    # Add more careers similarly...
-}
 
+
+# Resources Page Info - UPDATED
 def resource_block(career):
-   content = career_resources.get(career)
+   resources = {
+       "AI/Machine Learning Engineer": {
+           "links": [
+               ("Neural Networks – DeepLearning.AI", "https://www.deeplearning.ai"),
+               ("Build ML Models – Fast.ai", "https://www.fast.ai"),
+               ("Machine Learning – Stanford CS229", "https://cs229.stanford.edu/")
+           ],
+           "college": {
+               "major": "Computer Science, Data Science",
+               "classes": [
+                   "CS50: Introduction to Computer Science (Harvard)",
+                   "Linear Algebra",
+                   "Probability and Statistics",
+                   "Machine Learning (Stanford CS229)",
+                   "Algorithms"
+               ]
+           }
+       },
+       "Data Scientist": {
+           "links": [
+               ("Python & Pandas – Kaggle Learn", "https://www.kaggle.com/learn"),
+               ("R Programming – Harvard Data Science", "https://online-learning.harvard.edu/series/data-science"),
+               ("Project Practice – DataCamp", "https://www.datacamp.com")
+           ],
+           "college": {
+               "major": "Data Science, Statistics, Computer Science",
+               "classes": [
+                   "Introduction to Data Science",
+                   "Statistics and Probability",
+                   "Data Mining",
+                   "Machine Learning",
+                   "Database Systems"
+               ]
+           }
+       },
+       "Cloud Solutions Architect": {
+           "links": [
+               ("AWS Skills – AWS Training", "https://aws.amazon.com/training/"),
+               ("Azure Certifications – Microsoft Learn", "https://learn.microsoft.com/en-us/certifications/"),
+               ("Google Cloud Labs – Google Cloud Boost", "https://cloudskillsboost.google/")
+           ],
+           "college": {
+               "major": "Computer Science, Information Technology",
+               "classes": [
+                   "Cloud Computing Fundamentals",
+                   "Computer Networks",
+                   "Systems Design",
+                   "Information Security",
+                   "Operating Systems"
+               ]
+           }
+       },
+       "Cybersecurity Analyst": {
+           "links": [
+               ("Network Security – Cybrary", "https://www.cybrary.it"),
+               ("Threat Intelligence – MITRE ATT&CK", "https://attack.mitre.org/"),
+               ("Ethical Hacking – TryHackMe", "https://tryhackme.com")
+           ],
+           "college": {
+               "major": "Cybersecurity, Computer Science, Information Security",
+               "classes": [
+                   "Network Security",
+                   "Cryptography",
+                   "Ethical Hacking",
+                   "Operating Systems",
+                   "Incident Response"
+               ]
+           }
+       },
+       "Statistician": {
+           "links": [
+               ("Intro to Statistics – Coursera (R)", "https://www.coursera.org/specializations/statistics"),
+               ("Probability – Khan Academy", "https://www.khanacademy.org/math/statistics-probability"),
+               ("Statistical Tools – OpenIntro", "https://www.openintro.org/book/os/")
+           ],
+           "college": {
+               "major": "Statistics, Mathematics",
+               "classes": [
+                   "Probability Theory",
+                   "Statistical Inference",
+                   "Regression Analysis",
+                   "Experimental Design",
+                   "Data Analysis with R"
+               ]
+           }
+       },
+       "Biomedical Engineer": {
+           "links": [
+               ("Biomedical Research – JHU BME", "https://www.bme.jhu.edu/"),
+               ("Medical Devices – edX Courses", "https://www.edx.org/learn/biomedical-engineering"),
+               ("Clinical Trials – NIH", "https://www.nih.gov/")
+           ],
+           "college": {
+               "major": "Biomedical Engineering, Bioengineering",
+               "classes": [
+                   "Biomaterials",
+                   "Human Physiology",
+                   "Medical Instrumentation",
+                   "Biomechanics",
+                   "Tissue Engineering"
+               ]
+           }
+       },
+       "Mechanical Engineer": {
+           "links": [
+               ("CAD Design – Coursera", "https://www.coursera.org/learn/cad-design"),
+               ("Thermodynamics – MIT OpenCourseWare", "https://ocw.mit.edu/courses/thermodynamics"),
+               ("Materials Science Basics – edX", "https://www.edx.org/course/material-science")
+           ],
+           "college": {
+               "major": "Mechanical Engineering",
+               "classes": [
+                   "Thermodynamics",
+                   "Fluid Mechanics",
+                   "Materials Science",
+                   "Computer-Aided Design (CAD)",
+                   "Dynamics and Control"
+               ]
+           }
+       },
+       "Environmental Scientist": {
+           "links": [
+               ("Environmental Science – Khan Academy", "https://www.khanacademy.org/science/biology/ecology"),
+               ("GIS Basics – Esri Training", "https://www.esri.com/training/catalog/57630435851d31e02a43f1c5/gis-basics/"),
+               ("Data Analysis – Coursera", "https://www.coursera.org/learn/data-analysis")
+           ],
+           "college": {
+               "major": "Environmental Science, Ecology",
+               "classes": [
+                   "Ecology",
+                   "Environmental Chemistry",
+                   "Geographic Information Systems (GIS)",
+                   "Data Analysis",
+                   "Environmental Policy"
+               ]
+           }
+       },
+       "Operations Research Analyst": {
+           "links": [
+               ("Linear Programming – Khan Academy", "https://www.khanacademy.org/computing/computer-science/algorithms"),
+               ("Optimization – MIT OpenCourseWare", "https://ocw.mit.edu/courses/optimization-methods"),
+               ("Statistics – Harvard Online", "https://online-learning.harvard.edu/course/statistics-and-r")
+           ],
+           "college": {
+               "major": "Operations Research, Applied Mathematics",
+               "classes": [
+                   "Optimization Theory",
+                   "Linear Programming",
+                   "Probability",
+                   "Statistics",
+                   "Simulation Modeling"
+               ]
+           }
+       },
+       "Mathematician": {
+           "links": [
+               ("Abstract Algebra – MIT OpenCourseWare", "https://ocw.mit.edu/courses/abstract-algebra"),
+               ("Calculus – Khan Academy", "https://www.khanacademy.org/math/calculus-1"),
+               ("Proof Techniques – Coursera", "https://www.coursera.org/learn/proofs")
+           ],
+           "college": {
+               "major": "Mathematics",
+               "classes": [
+                   "Algebra",
+                   "Calculus",
+                   "Real Analysis",
+                   "Abstract Algebra",
+                   "Proof Writing"
+               ]
+           }
+       },
+       "Chemical Engineer": {
+           "links": [
+               ("Chemical Process Principles – MIT OCW", "https://ocw.mit.edu/courses/chemical-engineering"),
+               ("Organic Chemistry – Khan Academy", "https://www.khanacademy.org/science/organic-chemistry"),
+               ("Thermodynamics – Coursera", "https://www.coursera.org/learn/thermodynamics")
+           ],
+           "college": {
+               "major": "Chemical Engineering",
+               "classes": [
+                   "Organic Chemistry",
+                   "Thermodynamics",
+                   "Process Design",
+                   "Fluid Mechanics",
+                   "Chemical Reaction Engineering"
+               ]
+           }
+       },
+       "Civil Engineer": {
+           "links": [
+               ("Structural Analysis – Coursera", "https://www.coursera.org/learn/structural-analysis"),
+               ("Construction Management – edX", "https://www.edx.org/course/construction-management"),
+               ("AutoCAD – LinkedIn Learning", "https://www.linkedin.com/learning/topics/autocad")
+           ],
+           "college": {
+               "major": "Civil Engineering",
+               "classes": [
+                   "Structural Analysis",
+                   "Construction Materials",
+                   "Soil Mechanics",
+                   "AutoCAD",
+                   "Hydraulics"
+               ]
+           }
+       },
+       "Electrical Engineer": {
+           "links": [
+               ("Circuits and Electronics – MIT OCW", "https://ocw.mit.edu/courses/electrical-engineering-and-computer-science"),
+               ("Signals and Systems – Coursera", "https://www.coursera.org/learn/signals-systems"),
+               ("Electromagnetics – Khan Academy", "https://www.khanacademy.org/science/electrical-engineering")
+           ],
+           "college": {
+               "major": "Electrical Engineering",
+               "classes": [
+                   "Circuits",
+                   "Signals and Systems",
+                   "Electromagnetics",
+                   "Control Systems",
+                   "Digital Logic Design"
+               ]
+           }
+       },
+       "Software Developer": {
+           "links": [
+               ("CS50 – Harvard", "https://cs50.harvard.edu"),
+               ("Learn to Code – Codecademy", "https://www.codecademy.com/catalog/subject/all"),
+               ("Algorithms – Coursera", "https://www.coursera.org/learn/algorithms-part1")
+           ],
+           "college": {
+               "major": "Computer Science, Software Engineering",
+               "classes": [
+                   "Introduction to Computer Science (CS50)",
+                   "Data Structures and Algorithms",
+                   "Operating Systems",
+                   "Software Engineering",
+                   "Databases"
+               ]
+           }
+       },
+       "Pharmacist": {
+           "links": [
+               ("Pharmacology Basics – Coursera", "https://www.coursera.org/learn/pharmacology"),
+               ("Drug Development – edX", "https://www.edx.org/course/drug-development"),
+               ("Pharmacy Practice – FutureLearn", "https://www.futurelearn.com/courses/pharmacy-practice")
+           ],
+           "college": {
+               "major": "Pharmacy, Pharmaceutical Sciences",
+               "classes": [
+                   "Pharmacology",
+                   "Medicinal Chemistry",
+                   "Pharmaceutical Calculations",
+                   "Pharmaceutics",
+                   "Clinical Pharmacy"
+               ]
+           }
+       },
+       "Physicist": {
+           "links": [
+               ("Classical Mechanics – MIT OCW", "https://ocw.mit.edu/courses/physics"),
+               ("Quantum Mechanics – edX", "https://www.edx.org/course/quantum-mechanics"),
+               ("Thermodynamics – Khan Academy", "https://www.khanacademy.org/science/physics/thermodynamics")
+           ],
+           "college": {
+               "major": "Physics",
+               "classes": [
+                   "Classical Mechanics",
+                   "Quantum Mechanics",
+                   "Thermodynamics",
+                   "Electromagnetism",
+                   "Mathematical Methods for Physicists"
+               ]
+           }
+       },
+       "Astronomer": {
+           "links": [
+               ("Introduction to Astronomy – Coursera", "https://www.coursera.org/learn/astronomy"),
+               ("Astrophysics – edX", "https://www.edx.org/course/astrophysics"),
+               ("Cosmology – Khan Academy", "https://www.khanacademy.org/science/cosmology-and-astronomy")
+           ],
+           "college": {
+               "major": "Astronomy, Astrophysics, Physics",
+               "classes": [
+                   "Introduction to Astronomy",
+                   "Astrophysics",
+                   "Cosmology",
+                   "Observational Astronomy",
+                   "Data Analysis in Astronomy"
+               ]
+           }
+       },
+       "Geologist": {
+           "links": [
+               ("Physical Geology – OpenStax", "https://openstax.org/details/books/physical-geology"),
+               ("Geochemistry – Coursera", "https://www.coursera.org/learn/geochemistry"),
+               ("GIS Mapping – Esri Training", "https://www.esri.com/training/catalog/57630435851d31e02a43f1c5/gis-basics/")
+           ],
+           "college": {
+               "major": "Geology, Earth Science",
+               "classes": [
+                   "Physical Geology",
+                   "Mineralogy and Petrology",
+                   "Geochemistry",
+                   "GIS and Remote Sensing",
+                   "Structural Geology"
+               ]
+           }
+       },
+       "Biochemist": {
+           "links": [
+               ("Biochemistry – MIT OCW", "https://ocw.mit.edu/courses/biochemistry"),
+               ("Molecular Biology – Coursera", "https://www.coursera.org/learn/molecular-biology"),
+               ("Enzymology – Khan Academy", "https://www.khanacademy.org/science/biology")
+           ],
+           "college": {
+               "major": "Biochemistry, Molecular Biology",
+               "classes": [
+                   "General Biochemistry",
+                   "Molecular Biology",
+                   "Enzymology",
+                   "Cell Biology",
+                   "Genetics"
+               ]
+           }
+       }
+   }
+
+
+
+   content = resources.get(career)
    if not content:
        return "Select a career to see resources.", ""
 
-   link_html = "<h4>🧠 Skills</h4><ul>"
-   for label, url in content["skills"]:
-       link_html += f"<li><strong>{label}</strong>: <a href='{url}' target='_blank'>{url}</a></li>"
-   link_html += "</ul><br>"
 
-   college_html = "<h4>🎓 College & Classes</h4><ul>"
-   college_html += f"<li><strong>Majors:</strong> {content['major']}</li>"
-   college_html += "<li><strong>Helpful Classes:</strong><ul>"
-   for course in content["classes"]:
-       college_html += f"<li>{course}</li>"
-   college_html += "</ul></li></ul><hr>"
 
-   video_embed = content.get("youtube", "")
-   return link_html + "<br>" + college_html, video_embed
+   link_html = "<ul>"
+   for label, url in content["links"]:
+       link_html += f'<li><strong>{label}</strong>: <a href="{url}" target="_blank">{url}</a></li>'
+   link_html += "</ul>"
+
+
+
+   college_html = ""
+   if "college" in content:
+       college = content["college"]
+       college_html += "<p><strong>College & Classes</strong></p><ul>"
+       college_html += f"<li><em>Common Major(s):</em> {college['major']}</li>"
+       classes_list = college.get("classes", [])
+       if isinstance(classes_list, list):
+           classes_html = ", ".join(classes_list)
+       else:
+           classes_html = str(classes_list)
+       college_html += f"<li><em>Helpful College Classes:</em> {classes_html}</li>"
+       college_html += "</ul>"
+
+
+
+   # No video iframe, just empty string for second output
+   return link_html + college_html, ""
+
+
 
 # UI Layout
 with gr.Blocks(theme=theme, css=custom_css) as chatbot:
    gr.Image(display_image)
 
+
+
    with gr.Tab("ChatBot"):
        gr.ChatInterface(
            respond,
@@ -140,7 +493,12 @@ with gr.Blocks(theme=theme, css=custom_css) as chatbot:
            description='This tool provides information on STEM Careers. All information is sourced from [census.gov](https://www.census.gov/).'
        )
 
-   with gr.Tab("Explore Now"):
+
+
+
+
+
+   with gr.Tab("Explore Now"):  # ✅ Changed title
        gr.Markdown("### Explore STEM Career Categories")
        dropdown_explore = gr.Dropdown(
            choices=[
@@ -153,16 +511,52 @@ with gr.Blocks(theme=theme, css=custom_css) as chatbot:
            label="Choose a Category"
        )
        output_explore = gr.Markdown()
+
+
+
        dropdown_explore.change(fn=show_info, inputs=dropdown_explore, outputs=output_explore)
 
+
+
+
+
+
    with gr.Tab("Resources"):
        gr.Markdown("### Career-Specific Educational Resources")
        dropdown_resources = gr.Dropdown(
-           choices=list(career_resources.keys()),
+           choices=[
+               "AI/Machine Learning Engineer",
+               "Data Scientist",
+               "Cloud Solutions Architect",
+               "Cybersecurity Analyst",
+               "Statistician",
+               "Biomedical Engineer",
+               "Mechanical Engineer",
+               "Environmental Scientist",
+               "Operations Research Analyst",
+               "Mathematician",
+               "Chemical Engineer",
+               "Civil Engineer",
+               "Electrical Engineer",
+               "Software Developer",
+               "Pharmacist",
+               "Physicist",
+               "Astronomer",
+               "Geologist",
+               "Biochemist"
+           ],
            label="Choose a Career"
        )
        output_links = gr.HTML()
        output_video = gr.HTML()
-       dropdown_resources.change(fn=resource_block, inputs=dropdown_resources, outputs=[output_links, output_video])
+       dropdown_resources.change(
+           fn=resource_block,
+           inputs=dropdown_resources,
+           outputs=[output_links, output_video]
+       )
+
+
 
 chatbot.launch()
+
+