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"""
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LLM service.
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Wraps OpenRouter API calls and robust JSON parsing.
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Kept separate from AnalysisService to avoid circular imports.
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"""
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import json
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import requests
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from typing import Dict, Any, Optional, List
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from app.utils.logger import get_logger
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from app.config import APIKeys
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from app.utils.config_loader import load_addon_config
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logger = get_logger(__name__)
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class LLMService:
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"""LLM provider wrapper."""
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def __init__(self):
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# Config may not be loaded yet during import time; we resolve lazily via properties.
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pass
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@property
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def api_key(self):
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return APIKeys.OPENROUTER_API_KEY
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@property
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def base_url(self):
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config = load_addon_config()
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# Keep compatible with old/new config keys.
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import os
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return config.get('openrouter', {}).get('base_url') or os.getenv('OPENROUTER_BASE_URL', "https://openrouter.ai/api/v1")
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def call_openrouter_api(self, messages: list, model: str = None, temperature: float = 0.7, use_fallback: bool = True) -> str:
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"""Call OpenRouter API, with optional fallback models."""
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config = load_addon_config()
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openrouter_config = config.get('openrouter', {})
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default_model = openrouter_config.get('model', 'google/gemini-3-pro-preview')
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if model is None:
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model = default_model
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url = f"{self.base_url}/chat/completions"
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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"HTTP-Referer": "https://quantdinger.com",
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"X-Title": "QuantDinger Analysis"
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}
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# Build model candidates (primary + optional fallbacks).
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models_to_try = [model]
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# Fallback models are currently hard-coded for local mode.
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fallback_models = ["openai/gpt-4o-mini"]
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if use_fallback and model == default_model:
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models_to_try.extend(fallback_models)
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last_error = None
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timeout = int(openrouter_config.get('timeout', 120))
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for current_model in models_to_try:
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try:
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data = {
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"model": current_model,
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"messages": messages,
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"temperature": temperature,
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"response_format": {"type": "json_object"}
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}
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# logger.debug(f"Trying model: {current_model}")
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response = requests.post(url, headers=headers, json=data, timeout=timeout)
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if response.status_code == 402:
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logger.warning(f"OpenRouter returned 402 for model {current_model}; trying fallback model...")
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last_error = f"402 Payment Required for model {current_model}"
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continue
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response.raise_for_status()
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result = response.json()
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if "choices" in result and len(result["choices"]) > 0:
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content = result["choices"][0]["message"]["content"]
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if not content:
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raise ValueError(f"Model {current_model} returned empty content")
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if current_model != model:
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logger.info(f"Fallback model succeeded: {current_model}")
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return content
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else:
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logger.error(f"OpenRouter API returned unexpected structure ({current_model}): {json.dumps(result)}")
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raise ValueError("OpenRouter API response is missing 'choices'")
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except requests.exceptions.HTTPError as e:
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logger.error(f"OpenRouter API HTTP error ({current_model}): {e.response.text if e.response else str(e)}")
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last_error = str(e)
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if not use_fallback or current_model == models_to_try[-1]:
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raise
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except requests.exceptions.RequestException as e:
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logger.error(f"OpenRouter API request error ({current_model}): {str(e)}")
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last_error = str(e)
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if not use_fallback or current_model == models_to_try[-1]:
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raise
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except ValueError as e:
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logger.warning(f"Model {current_model} returned invalid data: {str(e)}")
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last_error = str(e)
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# If this is not the last candidate model, try the next one
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if current_model == models_to_try[-1]:
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raise
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error_msg = f"All model calls failed. Last error: {last_error}"
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logger.error(error_msg)
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raise Exception(error_msg)
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def safe_call_llm(self, system_prompt: str, user_prompt: str, default_structure: Dict[str, Any], model: str = None) -> Dict[str, Any]:
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"""Safe LLM call with robust JSON parsing and fallback structure."""
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response_text = ""
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try:
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response_text = self.call_openrouter_api([
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt}
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], model=model)
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# Strip markdown fences if present
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clean_text = response_text.strip()
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if clean_text.startswith("```"):
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first_newline = clean_text.find("\n")
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if first_newline != -1:
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clean_text = clean_text[first_newline+1:]
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if clean_text.endswith("```"):
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clean_text = clean_text[:-3]
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clean_text = clean_text.strip()
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# Parse JSON
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result = json.loads(clean_text)
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return result
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except json.JSONDecodeError:
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logger.error(f"JSON parse failed. Raw text: {response_text[:200] if response_text else 'N/A'}")
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# Try extracting JSON substring
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try:
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if response_text:
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start = response_text.find('{')
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end = response_text.rfind('}') + 1
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if start >= 0 and end > start:
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result = json.loads(response_text[start:end])
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return result
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except:
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pass
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default_structure['report'] = f"Failed to parse analysis result JSON. Raw output (partial): {response_text[:500] if response_text else 'N/A'}"
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return default_structure
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except Exception as e:
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logger.error(f"LLM call failed: {str(e)}")
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default_structure['report'] = f"Analysis failed: {str(e)}"
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return default_structure
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