import httpx
import json
import logging
import re
from app.config import settings

logger = logging.getLogger(__name__)

PROMPTS = {
    "minutes": (
        "Voce e um assistente especializado em reunioes corporativas. "
        "Com base na transcricao a seguir, gere uma ata estruturada em JSON contendo: "
        "title (string), participants (array de objetos com name e role), "
        "agenda (array de strings), decisions (array de strings), "
        "action_items (array de objetos com description, responsible e deadline), "
        "next_steps (array de strings), open_points (array de strings). "
        "Retorne APENAS o JSON valido, sem texto adicional. "
        "Transcricao: {transcription}"
    ),
    "sentiment": (
        "Analise o tom emocional desta reuniao e retorne um JSON com: "
        "overall_sentiment (positive/neutral/negative), "
        "timeline (array de objetos com time_range, sentiment e notes), "
        "participants_sentiment (array de objetos com speaker, sentiment e details), "
        "tension_moments (array de strings), "
        "consensus_moments (array de strings), "
        "participation_metrics (array de objetos com speaker, talk_percentage e interventions_count). "
        "Retorne APENAS o JSON valido. "
        "Transcricao: {transcription}"
    ),
    "psychological": (
        "Analise os padroes comportamentais dos participantes e retorne um JSON com: "
        "participants_profiles (array de objetos com speaker, name, communication_style, "
        "leadership_tendencies, disengagement_signs, power_dynamics_role), "
        "group_dynamics (string), "
        "key_observations (array de strings). "
        "Retorne APENAS o JSON valido. "
        "Transcricao: {transcription}"
    ),
    "communication": (
        "Avalie a comunicacao dos participantes nesta reuniao e retorne um JSON com: "
        "overall_score (numero de 1 a 10), "
        "dimensions (objeto com clarity, active_listening, assertiveness, meeting_facilitation, "
        "cada um com score e notes), "
        "strengths (array de objetos com description e example), "
        "improvement_areas (array de objetos com description e suggestion), "
        "general_feedback (string). "
        "Retorne APENAS o JSON valido. "
        "Transcricao: {transcription}"
    ),
    "summary": (
        "Gere um resumo executivo desta reuniao em JSON com: "
        "summary (string), "
        "key_points (array de strings), "
        "duration_minutes (number), "
        "total_participants (number). "
        "Retorne APENAS o JSON valido. "
        "Transcricao: {transcription}"
    ),
}


async def run_analysis(analysis_type: str, transcription: dict) -> dict:
    """Run AI analysis on transcription using Ollama"""
    transcription_text = json.dumps(transcription, ensure_ascii=False)
    prompt_template = PROMPTS.get(analysis_type, PROMPTS["summary"])
    prompt = prompt_template.replace("{transcription}", transcription_text[:8000])

    logger.info(f"Running {analysis_type} analysis with Ollama model {settings.OLLAMA_MODEL}")

    try:
        headers = {}
        if settings.OLLAMA_API_KEY:
            headers["X-API-Key"] = settings.OLLAMA_API_KEY
        async with httpx.AsyncClient(timeout=180.0) as client:
            response = await client.post(
                f"{settings.OLLAMA_URL}/api/generate",
                headers=headers,
                json={
                    "model": settings.OLLAMA_MODEL,
                    "prompt": prompt,
                    "stream": False,
                    "format": "json",
                    "options": {"temperature": 0.3},
                },
            )
            response.raise_for_status()
            result = response.json()
            response_text = result.get("response", "{}")
            try:
                return json.loads(response_text)
            except json.JSONDecodeError:
                json_match = re.search(r"\{.*\}", response_text, re.DOTALL)
                if json_match:
                    try:
                        return json.loads(json_match.group())
                    except json.JSONDecodeError:
                        pass
                return {"raw_response": response_text, "parse_error": "Could not parse JSON"}
    except httpx.ConnectError as e:
        logger.error(f"Cannot connect to Ollama at {settings.OLLAMA_URL}: {e}")
        return {"error": "Ollama unavailable", "analysis_type": analysis_type}
    except Exception as e:
        logger.error(f"Ollama analysis error for {analysis_type}: {e}")
        return {"error": str(e), "analysis_type": analysis_type}