import logging
from typing import List, Optional, Dict, Any
from db.models import Post, TargetChannel
from db.repository import Repository
from core.llm import LLMClient
from core.dedup import compute_content_hash
from core.metrics import DUPLICATES_DETECTED_TOTAL

logger = logging.getLogger(__name__)

TAG_EXTRACTION_SYSTEM_PROMPT = """
You are an AI news analyst and classifier.
Given a social media/channel post, extract:
1. "subject": A brief, specific headline/subject (3-8 words).
2. "tags": A JSON array of 3 to 6 lowercase keywords/topics/entities (e.g. ["ai", "nvidia", "gpus", "hardware"]).
Respond ONLY in JSON format:
{
  "subject": "...",
  "tags": ["tag1", "tag2", "tag3"]
}
"""

DUPLICATE_CHECK_SYSTEM_PROMPT = """
You are an expert news editor checking for duplicate news stories.
Given a NEW POST and a list of PREVIOUS POSTS, determine if the NEW POST is covering the same exact event, news item, or story as any of the previous posts.

Respond ONLY in JSON format:
{
  "is_duplicate": true/false,
  "duplicate_of_id": <id of matched previous post or null>,
  "similarity_reason": "<short explanation of why it is or is not a duplicate>"
}
"""

POST_REWRITE_SYSTEM_PROMPT = """
You are an expert Telegram content creator and copywriter.
Rewrite the provided post to make it engaging, well-formatted, professional, and clear.
Use appropriate emojis, clear paragraphs, and markdown formatting.
Remove any original promotional links, author credits, or watermarks.

Respond ONLY in JSON format:
{
  "ai_text": "...",
  "suggested_target_id": <optional id of best matching target channel or null>
}
"""

class AIProcessor:
    def __init__(self, repo: Repository, llm: Optional[LLMClient] = None):
        self.repo = repo
        self.llm = llm or LLMClient()

    async def process_post(self, post_id: int) -> Optional[Post]:
        post = await self.repo.get_post_by_id(post_id)
        if not post or not post.raw_text:
            return post

        raw_text = post.raw_text
        is_dup = False
        dup_of_id = None
        sim_reason = None

        # 1. Exact hash duplicate check
        content_hash = post.content_hash or compute_content_hash(raw_text)
        if content_hash:
            exact_dup = await self.repo.find_duplicate_post_by_hash(content_hash)
            if exact_dup and exact_dup.id != post.id:
                is_dup = True
                dup_of_id = exact_dup.id
                sim_reason = "Exact match on normalized text/media hash"
                DUPLICATES_DETECTED_TOTAL.labels(method="hash").inc()

        # 2. Extract Tags and Subject via AI
        tags = []
        subject = "General News"
        try:
            tag_res = await self.llm.generate_json(
                prompt=f"Post content:\n\n{raw_text}",
                system_prompt=TAG_EXTRACTION_SYSTEM_PROMPT,
                action_name="extract_tags"
            )
            subject = tag_res.get("subject", subject)
            tags = [t.lower().strip() for t in tag_res.get("tags", []) if isinstance(t, str)]
            await self.repo.update_post_tags(post.id, tags, subject)
        except Exception as e:
            logger.error(f"Tag extraction failed for post {post.id}: {e}")

        # 3. Candidate search & Semantic AI Deduplication check (if not already exact dup)
        if not is_dup and tags:
            candidates = await self.repo.find_candidate_posts_by_tags(tags, exclude_post_id=post.id, hours_lookback=72, limit=5)
            if candidates:
                cand_texts = "\n---\n".join([f"ID {c.id} (Subject: {c.subject}):\n{c.raw_text}" for c in candidates if c.raw_text])
                prompt = f"NEW POST:\n{raw_text}\n\nPREVIOUS CANDIDATE POSTS:\n{cand_texts}"
                try:
                    dup_res = await self.llm.generate_json(
                        prompt=prompt,
                        system_prompt=DUPLICATE_CHECK_SYSTEM_PROMPT,
                        action_name="check_duplicate"
                    )
                    if dup_res.get("is_duplicate"):
                        is_dup = True
                        dup_of_id = dup_res.get("duplicate_of_id")
                        sim_reason = dup_res.get("similarity_reason", "AI detected duplicate news topic")
                        DUPLICATES_DETECTED_TOTAL.labels(method="ai_semantic").inc()
                except Exception as e:
                    logger.error(f"Semantic duplicate check failed for post {post.id}: {e}")

        # 4. Rewrite post for our channels
        ai_text = raw_text
        suggested_target_id = None
        targets = await self.repo.get_active_targets()
        target_info = "\n".join([f"Target ID {t.id}: {t.title} (@{t.username or 'none'})" for t in targets])
        rewrite_prompt = f"TARGET CHANNELS AVAILABLE:\n{target_info or 'None'}\n\nORIGINAL POST:\n{raw_text}"

        try:
            rewrite_res = await self.llm.generate_json(
                prompt=rewrite_prompt,
                system_prompt=POST_REWRITE_SYSTEM_PROMPT,
                action_name="rewrite_post"
            )
            ai_text = rewrite_res.get("ai_text", raw_text)
            suggested_target_id = rewrite_res.get("suggested_target_id")
        except Exception as e:
            logger.error(f"Post rewrite failed for post {post.id}: {e}")

        # 5. Save AI results into database
        await self.repo.update_ai_result(
            post_id=post.id,
            subject=subject,
            ai_text=ai_text,
            tags=tags,
            suggested_target_id=suggested_target_id,
            is_duplicate=is_dup,
            duplicate_of_id=dup_of_id,
            similarity_reason=sim_reason,
        )

        return await self.repo.get_post_by_id(post.id)