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import os
import gradio as gr
import google.generativeai as genai
from markdown_pdf import MarkdownPdf, Section

# ---------- PROMPTS ----------
PROMPTS = {
    "ALIGNMENT_PROMPT": {
        "role": "system",
        "content": """Your Role: You are an expert examiner and transcription specialist.  
Your task is to **align three sources**:
- Question Paper (QP)
- Markscheme (MS)
- Student Answer Sheet (AS)
### Instructions
1. Parse all documents carefully and align them **per question and sub-question**.
2. For each question/sub-question, produce a structured block:
---
## Question X (and sub-question if applicable)  
**QP:** [Insert the exact question text]  
**MS:** [Insert the relevant part of the markscheme]  
**AS:** [Insert the student's final cleaned answer transcription]  
---
3. Formatting Rules:
- Use `##` for main questions and `###` for sub-questions.  
- Write **QP | MS | AS** exactly in that order.  
- Preserve all mathematical expressions inside fenced code blocks.  
- Do not re-create diagrams/graphs. Write `[Graph omitted]`.  
- If part of the student's answer is unreadable, write `[illegible]`.  
- If a student skipped a question, write `[No response]`.  
- Keep MS annotations (M1, A1, R1, etc.) exactly as in the original.  
4. Output must be **clean, deterministic, and consistent** — so that another model can grade directly using this aligned representation.
### Example
## Question 1  
**QP:** Expand `(1+x)^3`  
**MS:** M1 for binomial expansion, A1 for coefficients, A1 for final form  
**AS:**  
"""
    },
    "GRADING_PROMPT": {
        "role": "system",
        "content": """You are an official examiner. Use the following grading rules strictly.
Abbreviations:  
- M: Marks awarded for attempting to use a correct Method.  
- A: Marks awarded for an Answer or for Accuracy; often dependent on preceding M marks.  
- R: Marks awarded for clear Reasoning.  
- AG: Answer given in the question and so no marks are awarded.  
- FT: Follow through. The practice of awarding marks, despite candidate errors in previous parts, for their correct methods/answers using incorrect results.  
--------------------------------------------  
## 1. General  
Award marks using the annotations as noted in the markscheme (e.g., M1, A2).  
## 2. Method and Answer/Accuracy marks  
- Do not automatically award full marks for a correct answer; all working must be checked.  
- It is generally not possible to award M0 followed by A1.  
- Where M and A marks are noted on the same line (M1A1), M is for method, A is for accuracy.  
- Multiple A marks can be independent.  
## 3. Implied marks  
Implied marks (M1) can only be awarded if correct work is seen or implied.  
## 4. Follow through (FT) marks  
- Award FT if an earlier wrong answer is used consistently later.  
- Do not award FT if the result contradicts the question (e.g., probability > 1).  
## 5. Mis-read (MR)  
- Penalize once if the candidate misreads a value.  
- Award other marks as appropriate.  
## 6. Alternative methods  
- Accept valid alternatives unless "Hence" forbids it.  
## 7. Alternative forms  
- Accept equivalent numeric/algebraic forms unless specified otherwise.  
## 8. Format and accuracy of answers  
- Use correct accuracy (3 s.f. if not specified).  
- Arithmetic and algebra should be simplified.  
## 9. Presentation of candidate work  
- Ignore crossed-out work unless indicated.  
- Mark only the first solution unless candidate specifies otherwise.  
## 10. Graph/Diagram Questions  
- If a question requires drawing or interpreting a graph/diagram, assume the student has done it correctly and award full marks for that part.  
--------------------------------------------  
### OUTPUT FORMAT
Produce a GitHub-flavored Markdown table with 3 columns:  
| Student wrote | Marks Awarded | Reason |  
|---------------|---------------|--------|  
Special Formatting Rule:  
- Whenever a mark is lost (M0, A0, R0 etc.), wrap it in red using: `<span style="color:red">M0</span>`.  
- Also wrap the corresponding Reason in red color.
- Keep awarded marks (M1, A1, etc.) in plain text.  
- If mixed (e.g., M1A0A1), only highlight the lost marks (`A0`) and its reason.
After the table, provide:  
### Summary & Final Mark  
- Total marks obtained vs total available  
- Any FT (follow-through) applied  
- Classification of errors (Conceptual, Silly mistake, Misread, etc.)  
"""
    }
}

# -------------------- CONFIG --------------------
genai.configure(api_key=os.getenv("GEMINI_API_KEY"))

# ---------- HELPER: Save to PDF ----------
def save_as_pdf(text, filename="output.pdf"):
    pdf = MarkdownPdf()
    pdf.add_section(Section(text, toc=False))
    pdf.save(filename)
    return filename

# ---------- HELPER: Create Model with Fallback ----------
def create_model():
    try:
        print("⚡ Using gemini-2.5-pro model")
        return genai.GenerativeModel("gemini-2.5-pro", generation_config={"temperature": 0})
    except Exception:
        print("⚡ Falling back to gemini-2.5-flash model")
        return genai.GenerativeModel("gemini-2.5-flash", generation_config={"temperature": 0})

# ---------- PIPELINE: ALIGN + GRADE ----------
def align_and_grade(qp_file, ms_file, ans_file):
    try:
        # Uploads
        qp_uploaded = genai.upload_file(path=qp_file, display_name="Question Paper")
        ms_uploaded = genai.upload_file(path=ms_file, display_name="Markscheme")
        ans_uploaded = genai.upload_file(path=ans_file, display_name="Answer Sheet")

        model = create_model()

        # Step 1: Alignment
        resp = model.generate_content([
            PROMPTS["ALIGNMENT_PROMPT"]["content"],
            qp_uploaded,
            ms_uploaded,
            ans_uploaded
        ])
        aligned_text = getattr(resp, "text", None)
        if not aligned_text and resp.candidates:
            aligned_text = resp.candidates[0].content.parts[0].text

        aligned_pdf_path = save_as_pdf(aligned_text, "aligned_qp_ms_as.pdf")

        # Step 2: Grading (automatic)
        response = model.generate_content([
            PROMPTS["GRADING_PROMPT"]["content"],
            aligned_text
        ])
        grading = getattr(response, "text", None)
        if not grading and response.candidates:
            grading = response.candidates[0].content.parts[0].text

        # Save grading report with student's answer filename
        base_name = os.path.splitext(os.path.basename(ans_file))[0]
        grading_pdf_path = save_as_pdf(grading, f"{base_name}_graded.pdf")

        return aligned_text, aligned_pdf_path, grading, grading_pdf_path

    except Exception as e:
        return f"❌ Error: {e}", None, None, None

# ---------- GRADIO APP ----------
with gr.Blocks(title="LeadIB AI Grading (Alignment + Auto-Grading)") as demo:
    gr.Markdown("## LeadIB AI Grading\nUpload Question Paper, Markscheme, and Student Answer Sheet.\nThe system will align and grade automatically.")

    with gr.Row():
        qp_file = gr.File(label="Upload Question Paper (PDF)", type="filepath")
        ms_file = gr.File(label="Upload Markscheme (PDF)", type="filepath")
        ans_file = gr.File(label="Upload Student Answer Sheet (PDF)", type="filepath")

    run_btn = gr.Button("Start Alignment + Auto-Grading")

    with gr.Row():
        aligned_out = gr.Textbox(label="📄 Aligned QP | MS | AS", lines=20)
        aligned_pdf = gr.File(label="⬇️ Download Aligned (PDF)")

    with gr.Row():
        grading_out = gr.Textbox(label="✅ Grading Report", lines=20)
        grading_pdf = gr.File(label="⬇️ Download Grading Report (PDF)")

    run_btn.click(
        fn=align_and_grade,
        inputs=[qp_file, ms_file, ans_file],
        outputs=[aligned_out, aligned_pdf, grading_out, grading_pdf],
        show_progress=True
    )

if __name__ == "__main__":
    demo.launch()

	import os
	import gradio as gr
	import google.generativeai as genai
	from markdown_pdf import MarkdownPdf, Section

	# ---------- PROMPTS ----------
	PROMPTS = {
	"ALIGNMENT_PROMPT": {
	"role": "system",
	"content": """Your Role: You are an expert examiner and transcription specialist.
	Your task is to align three sources:
	- Question Paper (QP)
	- Markscheme (MS)
	- Student Answer Sheet (AS)

	### Instructions
	1. Parse all documents carefully and align them per question and sub-question.
	2. For each question/sub-question, produce a structured block:

	---
	## Question X (and sub-question if applicable)
	QP: [Insert the exact question text]
	MS: [Insert the relevant part of the markscheme]
	AS: [Insert the student's final cleaned answer transcription]
	---

	3. Formatting Rules:
	- Use `##` for main questions and `###` for sub-questions.
	- Write QP \| MS \| AS exactly in that order.
	- Preserve all mathematical expressions inside fenced code blocks.
	- Do not re-create diagrams/graphs. Write `[Graph omitted]`.
	- If part of the student's answer is unreadable, write `[illegible]`.
	- If a student skipped a question, write `[No response]`.
	- Keep MS annotations (M1, A1, R1, etc.) exactly as in the original.

	4. Output must be clean, deterministic, and consistent — so that another model can grade directly using this aligned representation.

	### Example
	## Question 1
	QP: Expand `(1+x)^3`
	MS: M1 for binomial expansion, A1 for coefficients, A1 for final form
	AS:
	"""
	},
	"GRADING_PROMPT": {
	"role": "system",
	"content": """You are an official examiner. Use the following grading rules strictly.
	Abbreviations:
	- M: Marks awarded for attempting to use a correct Method.
	- A: Marks awarded for an Answer or for Accuracy; often dependent on preceding M marks.
	- R: Marks awarded for clear Reasoning.
	- AG: Answer given in the question and so no marks are awarded.
	- FT: Follow through. The practice of awarding marks, despite candidate errors in previous parts, for their correct methods/answers using incorrect results.
	--------------------------------------------
	## 1. General
	Award marks using the annotations as noted in the markscheme (e.g., M1, A2).
	## 2. Method and Answer/Accuracy marks
	- Do not automatically award full marks for a correct answer; all working must be checked.
	- It is generally not possible to award M0 followed by A1.
	- Where M and A marks are noted on the same line (M1A1), M is for method, A is for accuracy.
	- Multiple A marks can be independent.
	## 3. Implied marks
	Implied marks (M1) can only be awarded if correct work is seen or implied.
	## 4. Follow through (FT) marks
	- Award FT if an earlier wrong answer is used consistently later.
	- Do not award FT if the result contradicts the question (e.g., probability > 1).
	## 5. Mis-read (MR)
	- Penalize once if the candidate misreads a value.
	- Award other marks as appropriate.
	## 6. Alternative methods
	- Accept valid alternatives unless "Hence" forbids it.
	## 7. Alternative forms
	- Accept equivalent numeric/algebraic forms unless specified otherwise.
	## 8. Format and accuracy of answers
	- Use correct accuracy (3 s.f. if not specified).
	- Arithmetic and algebra should be simplified.
	## 9. Presentation of candidate work
	- Ignore crossed-out work unless indicated.
	- Mark only the first solution unless candidate specifies otherwise.
	## 10. Graph/Diagram Questions
	- If a question requires drawing or interpreting a graph/diagram, assume the student has done it correctly and award full marks for that part.
	--------------------------------------------
	### OUTPUT FORMAT
	Produce a GitHub-flavored Markdown table with 3 columns:
	\| Student wrote \| Marks Awarded \| Reason \|
	\|---------------\|---------------\|--------\|
	Special Formatting Rule:
	- Whenever a mark is lost (M0, A0, R0 etc.), wrap it in red using: `<span style="color:red">M0</span>`.
	- Also wrap the corresponding Reason in red color.
	- Keep awarded marks (M1, A1, etc.) in plain text.
	- If mixed (e.g., M1A0A1), only highlight the lost marks (`A0`) and its reason.
	After the table, provide:
	### Summary & Final Mark
	- Total marks obtained vs total available
	- Any FT (follow-through) applied
	- Classification of errors (Conceptual, Silly mistake, Misread, etc.)
	"""
	}
	}

	# -------------------- CONFIG --------------------
	genai.configure(api_key=os.getenv("GEMINI_API_KEY"))

	# ---------- HELPER: Save to PDF ----------
	def save_as_pdf(text, filename="output.pdf"):
	pdf = MarkdownPdf()
	pdf.add_section(Section(text, toc=False))
	pdf.save(filename)
	return filename

	# ---------- HELPER: Create Model with Fallback ----------
	def create_model():
	try:
	print("⚡ Using gemini-2.5-pro model")
	return genai.GenerativeModel("gemini-2.5-pro", generation_config={"temperature": 0})
	except Exception:
	print("⚡ Falling back to gemini-2.5-flash model")
	return genai.GenerativeModel("gemini-2.5-flash", generation_config={"temperature": 0})

	# ---------- PIPELINE: ALIGN + GRADE ----------
	def align_and_grade(qp_file, ms_file, ans_file):
	try:
	# Uploads
	qp_uploaded = genai.upload_file(path=qp_file, display_name="Question Paper")
	ms_uploaded = genai.upload_file(path=ms_file, display_name="Markscheme")
	ans_uploaded = genai.upload_file(path=ans_file, display_name="Answer Sheet")

	model = create_model()

	# Step 1: Alignment
	resp = model.generate_content([
	PROMPTS["ALIGNMENT_PROMPT"]["content"],
	qp_uploaded,
	ms_uploaded,
	ans_uploaded
	])
	aligned_text = getattr(resp, "text", None)
	if not aligned_text and resp.candidates:
	aligned_text = resp.candidates[0].content.parts[0].text

	aligned_pdf_path = save_as_pdf(aligned_text, "aligned_qp_ms_as.pdf")

	# Step 2: Grading (automatic)
	response = model.generate_content([
	PROMPTS["GRADING_PROMPT"]["content"],
	aligned_text
	])
	grading = getattr(response, "text", None)
	if not grading and response.candidates:
	grading = response.candidates[0].content.parts[0].text

	# Save grading report with student's answer filename
	base_name = os.path.splitext(os.path.basename(ans_file))[0]
	grading_pdf_path = save_as_pdf(grading, f"{base_name}_graded.pdf")

	return aligned_text, aligned_pdf_path, grading, grading_pdf_path

	except Exception as e:
	return f"❌ Error: {e}", None, None, None

	# ---------- GRADIO APP ----------
	with gr.Blocks(title="LeadIB AI Grading (Alignment + Auto-Grading)") as demo:
	gr.Markdown("## LeadIB AI Grading\nUpload Question Paper, Markscheme, and Student Answer Sheet.\nThe system will align and grade automatically.")

	with gr.Row():
	qp_file = gr.File(label="Upload Question Paper (PDF)", type="filepath")
	ms_file = gr.File(label="Upload Markscheme (PDF)", type="filepath")
	ans_file = gr.File(label="Upload Student Answer Sheet (PDF)", type="filepath")

	run_btn = gr.Button("Start Alignment + Auto-Grading")

	with gr.Row():
	aligned_out = gr.Textbox(label="📄 Aligned QP \| MS \| AS", lines=20)
	aligned_pdf = gr.File(label="⬇️ Download Aligned (PDF)")

	with gr.Row():
	grading_out = gr.Textbox(label="✅ Grading Report", lines=20)
	grading_pdf = gr.File(label="⬇️ Download Grading Report (PDF)")

	run_btn.click(
	fn=align_and_grade,
	inputs=[qp_file, ms_file, ans_file],
	outputs=[aligned_out, aligned_pdf, grading_out, grading_pdf],
	show_progress=True
	)

	if __name__ == "__main__":
	demo.launch()