import requests
import json

class LLMAnalyzer:
    """Analyzes text for secrets using a local LLM via Ollama."""

    def __init__(self, endpoint: str, model: str, system_prompt: str):
        self.endpoint = endpoint
        self.model = model
        self.system_prompt = system_prompt

    def analyze(self, text: str) -> dict:
        """
        Sends text to the Ollama API for analysis and returns a structured JSON response.

        Returns:
            A dictionary like:
            {
                "secret_found": bool,
                "secret_type": str,
                "confidence_score": float,
                "severity": str
            }
            Returns a default "not found" response on error.
        """
        prompt = f"Log entry: \"{text}\"\n\nAnalyze this for secrets and respond with only the required JSON."
        payload = {
            "model": self.model,
            "system": self.system_prompt,
            "prompt": prompt,
            "format": "json",
            "stream": False
        }
        try:
            response = requests.post(self.endpoint, json=payload, timeout=15)
            response.raise_for_status()
            # The response from Ollama is a JSON string, which needs to be parsed.
            analysis = json.loads(response.json().get("response", "{}"))
            return analysis
        except (requests.exceptions.RequestException, json.JSONDecodeError) as e:
            print(f"[ERROR] LLMAnalyzer failed: {e}")
            # Fallback: If LLM fails, assume no secret was found to avoid blocking the pipeline.
            return {"secret_found": False}