"""
Exercise 2 – SOLUTION – Persona, Task, and Data in a Structured Prompt
=======================================================================
AISE501 · Prompting in Coding · Spring Semester 2026
"""

from pathlib import Path

from server_utils import chat, get_client, print_messages, print_separator

client = get_client()

code_to_review = Path("analyze_me.py").read_text()
temperature_value=1

# ── Part A: Persona + Task + Code ─────────────────────────────────────────────
print_separator("Part A – Structured Prompt: Persona / Task / Code")

prompt_a = f"""\
<persona>
  You are a senior Python engineer with 10+ years of experience.
  You are rigorous about correctness, follow PEP-8 strictly, and care
  deeply about defensive programming and readable code.
</persona>

<task>
  Review the Python code provided below.
  Identify every bug and code-quality issue you can find.
  For each issue, state what is wrong and why it is a problem.
</task>

<code language="python" filename="analyze_me.py">
{code_to_review}
</code>"""

messages_a = [
    {"role": "user", "content": prompt_a}
]

print_messages(messages_a)
response_a = chat(client, messages_a, temperature=temperature_value)
print(response_a)


# ── Part B: Refine – Ask for a Prioritised Bug List ───────────────────────────
print_separator("Part B – Refined Prompt: Prioritised Bug List")

system_b = """\
You are a senior Python engineer performing a thorough code review.
Be concise, precise, and always refer to line numbers when available.
"""

prompt_b = f"""\
<persona>
  You are a senior Python engineer with 10+ years of experience.
  You are rigorous about correctness, follow PEP-8, and care about
  defensive programming and readable code.
</persona>

<task>
  Review the Python code below.
  Identify every bug and code-quality issue.
  Classify each finding by severity:
    - Critical  : causes a crash or wrong result under normal use
    - Medium    : bad practice that will cause problems in production
    - Style     : violates PEP-8 or reduces readability
</task>

<output_format>
  For each finding produce exactly this structure (plain text):
    [SEVERITY] Line <N>: <one-sentence problem description>
    Fix hint: <one-sentence suggestion>

  Group findings under headings: ## Critical, ## Medium, ## Style
</output_format>

<code language="python" filename="analyze_me.py">
{code_to_review}
</code>"""

messages_b = [
    {"role": "system", "content": system_b},
    {"role": "user",   "content": prompt_b},
]

print_messages(messages_b)
response_b = chat(client, messages_b, temperature=temperature_value)
print(response_b)


# ── Part C: Request a Corrected Function ──────────────────────────────────────
print_separator("Part C – Ask for a Corrected Function")

followup = """\
<task>
  Rewrite only the `calculate_statistics` function with all bugs fixed.
  Requirements:
    - Handle an empty list gracefully (return None or raise ValueError with a clear message)
    - Use sample variance (divide by N-1)
    - Add full PEP-8 type hints
    - Add a NumPy-style docstring
  Return only the function code, no surrounding explanation.
</task>"""

messages_c = messages_b + [
    {"role": "assistant", "content": response_b},
    {"role": "user",      "content": followup},
]

print_messages(messages_c)
response_c = chat(client, messages_c, temperature=temperature_value)
print(response_c)


# ── Reflection Questions ──────────────────────────────────────────────────────
print_separator("Reflection Questions")
print(
    "1. Did the LLM find all 7 bugs? Which did it miss?\n"
    "2. How did the <output_format> tag change the structure of the answer?\n"
    "3. What is the advantage of continuing a conversation vs. starting fresh?\n"
    "4. How would you scale this pattern to a large codebase (many files)?\n"
)