"""
Comprehensive demo of the RAG system showing all integrated features.

⚠️  IMPORTANT: This test requires the virtual environment to be activated:
    source .venv/bin/activate
    PYTHONPATH=. python tests/01_basic_integration_test.py

Or run directly with venv:
    source .venv/bin/activate && PYTHONPATH=. python tests/01_basic_integration_test.py
"""

import os
import sys
import tempfile
from pathlib import Path

from mini_rag.chunker import CodeChunker
from mini_rag.indexer import ProjectIndexer
from mini_rag.ollama_embeddings import OllamaEmbedder as CodeEmbedder
from mini_rag.search import CodeSearcher

# Check if virtual environment is activated


def check_venv():
    if "VIRTUAL_ENV" not in os.environ:
        print("⚠️  WARNING: Virtual environment not detected!")
        print("   This test requires the virtual environment to be activated.")
        print(
            "   Run: source .venv/bin/activate && PYTHONPATH=. python tests/01_basic_integration_test.py"
        )
        print("   Continuing anyway...\n")


check_venv()

# Fix Windows encoding
if sys.platform == "win32":
    os.environ["PYTHONUTF8"] = "1"
    sys.stdout.reconfigure(encoding="utf-8")


def main():
    print("=" * 60)
    print("RAG System Integration Demo")
    print("=" * 60)

    with tempfile.TemporaryDirectory() as tmpdir:
        project_path = Path(tmpdir)

        # Create sample project files
        print("\n1. Creating sample project files...")

        # Main calculator module
        (project_path / "calculator.py").write_text(
            '''"""
Advanced calculator module with various mathematical operations.
"""

import math
from typing import List, Union


class BasicCalculator:
    """Basic calculator with fundamental operations."""

    def __init__(self):
        """Initialize calculator with result history."""
        self.history = []
        self.last_result = 0

    def add(self, a: float, b: float) -> float:
        """Add two numbers and store result."""
        result = a + b
        self.history.append(f"{a} + {b} = {result}")
        self.last_result = result
        return result

    def subtract(self, a: float, b: float) -> float:
        """Subtract b from a."""
        result = a - b
        self.history.append(f"{a} - {b} = {result}")
        self.last_result = result
        return result

    def multiply(self, a: float, b: float) -> float:
        """Multiply two numbers."""
        result = a * b
        self.history.append(f"{a} * {b} = {result}")
        self.last_result = result
        return result

    def divide(self, a: float, b: float) -> float:
        """Divide a by b with zero check."""
        if b == 0:
            raise ValueError("Cannot divide by zero")
        result = a / b
        self.history.append(f"{a} / {b} = {result}")
        self.last_result = result
        return result


class ScientificCalculator(BasicCalculator):
    """Scientific calculator extending basic operations."""

    def power(self, base: float, exponent: float) -> float:
        """Calculate base raised to exponent."""
        result = math.pow(base, exponent)
        self.history.append(f"{base} ^ {exponent} = {result}")
        self.last_result = result
        return result

    def sqrt(self, n: float) -> float:
        """Calculate square root."""
        if n < 0:
            raise ValueError("Cannot take square root of negative number")
        result = math.sqrt(n)
        self.history.append(f"sqrt({n}) = {result}")
        self.last_result = result
        return result

    def logarithm(self, n: float, base: float = 10) -> float:
        """Calculate logarithm with specified base."""
        result = math.log(n, base)
        self.history.append(f"log_{base}({n}) = {result}")
        self.last_result = result
        return result

def calculate_mean(numbers: List[float]) -> float:
    """Calculate arithmetic mean of a list of numbers."""
    if not numbers:
        return 0.0
    return sum(numbers) / len(numbers)


def calculate_median(numbers: List[float]) -> float:
    """Calculate median of a list of numbers."""
    if not numbers:
        return 0.0
    sorted_nums = sorted(numbers)
    n = len(sorted_nums)
    if n % 2 == 0:
        return (sorted_nums[n//2-1] + sorted_nums[n//2]) / 2
    return sorted_nums[n//2]


def calculate_mode(numbers: List[float]) -> float:
    """Calculate mode (most frequent value)."""
    if not numbers:
        return 0.0
    frequency = {}
    for num in numbers:
        frequency[num] = frequency.get(num, 0) + 1
    mode = max(frequency.keys(), key=frequency.get)
    return mode
'''
        )

        # Test file for the calculator
        (project_path / "test_calculator.py").write_text(
            '''"""
Unit tests for calculator module.
"""

import unittest
from calculator import BasicCalculator, ScientificCalculator, calculate_mean


class TestBasicCalculator(unittest.TestCase):
    """Test cases for BasicCalculator."""

    def setUp(self):
        """Set up test calculator."""
        self.calc = BasicCalculator()

    def test_addition(self):
        """Test addition operation."""
        result = self.calc.add(5, 3)
        self.assertEqual(result, 8)
        self.assertEqual(self.calc.last_result, 8)

    def test_division_by_zero(self):
        """Test division by zero raises error."""
        with self.assertRaises(ValueError):
            self.calc.divide(10, 0)


class TestStatistics(unittest.TestCase):
    """Test statistical functions."""

    def test_mean(self):
        """Test mean calculation."""
        numbers = [1, 2, 3, 4, 5]
        self.assertEqual(calculate_mean(numbers), 3.0)

    def test_empty_list(self):
        """Test mean of empty list."""
        self.assertEqual(calculate_mean([]), 0.0)

if __name__ == "__main__":
    unittest.main()
'''
        )

        print("    Created 2 Python files")

        # 2. Index the project
        print("\n2. Indexing project with intelligent chunking...")

        # Use realistic chunk size
        chunker = CodeChunker(min_chunk_size=10, max_chunk_size=100)
        indexer = ProjectIndexer(project_path, chunker=chunker)
        stats = indexer.index_project()

        print(f"    Indexed {stats['files_indexed']} files")
        print(f"    Created {stats['chunks_created']} chunks")
        print(f"    Time: {stats['time_taken']:.2f} seconds")

        # 3. Demonstrate search capabilities
        print("\n3. Testing search capabilities...")
        searcher = CodeSearcher(project_path)

        # Test different search types
        print("\n   a) Semantic search for 'calculate average':")
        results = searcher.search("calculate average", top_k=3)
        for i, result in enumerate(results, 1):
            print(
                f"      {i}. {result.chunk_type} '{result.name}' in {result.file_path} (score: {result.score:.3f})"
            )

        print("\n   b) BM25-weighted search for 'divide zero':")
        results = searcher.search("divide zero", top_k=3, semantic_weight=0.2, bm25_weight=0.8)
        for i, result in enumerate(results, 1):
            print(
                f"      {i}. {result.chunk_type} '{result.name}' in {result.file_path} (score: {result.score:.3f})"
            )

        print("\n   c) Search with context for 'test addition':")
        results = searcher.search("test addition", top_k=2, include_context=True)
        for i, result in enumerate(results, 1):
            print(f"      {i}. {result.chunk_type} '{result.name}'")
            if result.parent_chunk:
                print(f"         Parent: {result.parent_chunk.name}")
            if result.context_before:
                print(f"         Has previous context: {len(result.context_before)} chars")
            if result.context_after:
                print(f"         Has next context: {len(result.context_after)} chars")

        # 4. Test chunk navigation
        print("\n4. Testing chunk navigation...")

        # Get all chunks to find a method
        df = searcher.table.to_pandas()
        method_chunks = df[df["chunk_type"] == "method"]

        if len(method_chunks) > 0:
            # Pick a method in the middle
            mid_idx = len(method_chunks) // 2
            chunk_id = method_chunks.iloc[mid_idx]["chunk_id"]
            chunk_name = method_chunks.iloc[mid_idx]["name"]

            print(f"\n   Getting context for method '{chunk_name}':")
            context = searcher.get_chunk_context(chunk_id)

            if context["chunk"]:
                print(f"    Current: {context['chunk'].name}")
            if context["prev"]:
                print(f"    Previous: {context['prev'].name}")
            if context["next"]:
                print(f"    Next: {context['next'].name}")
            if context["parent"]:
                print(f"    Parent class: {context['parent'].name}")

        # 5. Show statistics
        print("\n5. Index Statistics:")
        stats = searcher.get_statistics()
        print(f"   - Total chunks: {stats['total_chunks']}")
        print(f"   - Unique files: {stats['unique_files']}")
        print(f"   - Chunk types: {stats['chunk_types']}")

        print("\n" + "=" * 60)
        print(" All features working correctly!")
        print("=" * 60)
        print("\nKey features demonstrated:")
        print("- AST-based intelligent chunking preserving code structure")
        print("- Chunk metadata (prev/next links, parent class, indices)")
        print("- Hybrid search combining BM25 and semantic similarity")
        print("- Context-aware search with adjacent chunks")
        print("- Chunk navigation following code relationships")


if __name__ == "__main__":
    main()