# app.py
import streamlit as st
import requests
from datetime import datetime
from fpdf import FPDF

# Replace with your actual OpenRouter or Hugging Face endpoint and key
API_URL = "https://openrouter.ai/api/v1/chat/completions"
API_KEY = "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"
MODEL = "mistralai/mistral-7b-instruct"

# ------------------------- AI QUERY FUNCTION -------------------------
def query_ai(prompt):
    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Content-Type": "application/json"
    }
    data = {
        "model": MODEL,
        "messages": [{"role": "user", "content": prompt}],
        "temperature": 0.7
    }
    try:
        response = requests.post(API_URL, headers=headers, json=data)
        response.raise_for_status()
        return response.json()['choices'][0]['message']['content']
    except Exception as e:
        return f"❌ API Error: {str(e)}"

# ---------------------- EXPERIMENT TEMPLATES ------------------------
experiments = {
    "Vinegar + Baking Soda": {
        "hypothesis": "Mixing vinegar and baking soda will produce bubbles due to a chemical reaction.",
        "concept": "Acid-base reaction producing carbon dioxide."
    },
    "Floating Egg": {
        "hypothesis": "An egg will float in salt water but sink in plain water.",
        "concept": "Density difference between saltwater and freshwater."
    },
    "Lemon Battery": {
        "hypothesis": "A lemon can produce electricity to power a small LED.",
        "concept": "Chemical energy conversion to electrical energy."
    }
}

# -------------------------- PDF REPORT ------------------------------
def generate_pdf_report(exp_name, hypo, explanation, result):
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", size=12)
    pdf.cell(200, 10, txt="Science Lab Report", ln=True, align='C')
    pdf.ln(10)
    pdf.multi_cell(0, 10, txt=f"Experiment: {exp_name}\n\nHypothesis: {hypo}\n\nAI Explanation: {explanation}\n\nExpected Result: {result}")
    filename = f"report_{datetime.now().strftime('%Y%m%d%H%M%S')}.pdf"
    pdf.output(filename)
    return filename

# --------------------------- STREAMLIT UI ---------------------------
st.set_page_config(page_title="🧪 Science Lab Assistant", layout="centered")
st.title("🧪 Science Lab Assistant")
st.markdown("Helping students understand, hypothesize, and explain science experiments.")

exp_choice = st.selectbox("Choose an experiment or enter your own:", list(experiments.keys()) + ["Custom Experiment"])

if exp_choice != "Custom Experiment":
    default_hypo = experiments[exp_choice]["hypothesis"]
    concept = experiments[exp_choice]["concept"]
else:
    default_hypo = ""
    concept = ""

with st.form("experiment_form"):
    exp_name = st.text_input("Experiment Name", value=exp_choice)
    hypo = st.text_area("Your Hypothesis", value=default_hypo)
    submit = st.form_submit_button("🔍 Explain Experiment")

if submit:
    with st.spinner("Thinking like a scientist..."):
        prompt = f"Explain the following school science experiment clearly for a student.\n\nExperiment: {exp_name}\nHypothesis: {hypo}\nExplain what happens, why it happens, and what the expected result is."
        explanation = query_ai(prompt)

    st.success("AI Explanation")
    st.write(explanation)

    # Generate expected result
    with st.spinner("Predicting result..."):
        result = query_ai(f"What is the expected result of this experiment: {exp_name}?")
    st.info(f"**Expected Result:** {result}")

    # Conceptual Science
    if concept:
        st.caption(f"🧠 Science Concept: {concept}")

    # PDF Download
    pdf_file = generate_pdf_report(exp_name, hypo, explanation, result)
    with open(pdf_file, "rb") as file:
        st.download_button("📄 Download Lab Report (PDF)", file, file_name=pdf_file)

# --------------------- OPTIONAL FILE UPLOAD -------------------------
st.markdown("---")
st.subheader("📸 Upload Your Lab Report Image (optional)")
uploaded_file = st.file_uploader("Upload an image for feedback", type=["jpg", "png", "jpeg"])
if uploaded_file:
    st.image(uploaded_file, caption="Uploaded Report", use_column_width=True)
    st.markdown("✅ Received. AI feedback coming soon (future feature).")

# ------------------------ GLOSSARY HELPER ---------------------------
st.markdown("---")
st.subheader("📘 Ask About a Science Term")
term = st.text_input("Enter a science term (e.g., osmosis, catalyst)")
if term:
    st.write(query_ai(f"Explain the term '{term}' in simple words for a student."))

# ---------------------- FEEDBACK SECTION ----------------------------
st.markdown("---")
st.subheader("💬 Feedback")
user_feedback = st.text_area("What can we improve in this app?")
if user_feedback:
    st.success("Thanks! Your feedback was recorded (simulated). 📨")