# knowledge/context.py — Context Builder for Compact CAG Prompting
from typing import List, Set
from knowledge.models import Chunk


class ContextBuilder:
    """Aggregates, deduplicates, and formats retrieved chunks into a compact LLM context."""

    def __init__(self, max_context_chars: int = 3500):
        self.max_context_chars = max_context_chars

    def build_context(self, chunks: List[Chunk]) -> str:
        """Format retrieved chunks into a compact, structured context block."""
        if not chunks:
            return "لا توجد سياقات مسترجعة."

        formatted_blocks = []
        seen_texts: Set[str] = set()
        total_chars = 0

        for chunk in chunks:
            # Deduplicate identical or near-identical text snippets
            clean_text = chunk.text.strip()
            if clean_text in seen_texts:
                continue
            seen_texts.add(clean_text)

            chunk_block = chunk.formatted_for_context()
            
            if total_chars + len(chunk_block) > self.max_context_chars and formatted_blocks:
                # Cap context size to avoid bloating prompt payload
                break

            formatted_blocks.append(chunk_block)
            total_chars += len(chunk_block)

        return "\n".join(formatted_blocks)