import requests import xbmcaddon import xbmc import time from wcs.ai.DialogAIDebugRequest import show_api_request_debug, show_api_response_debug from wcs.ai.model_catalog import DEFAULT_MODEL, model_or_default # Reasoning models (GPT-5+, o-series) take reasoning.effort and reject temperature/top_p REASONING_PREFIXES = ("gpt-5", "gpt-6", "o1", "o3", "o4") def get_current_model(): """Vrací aktuálně vybraný OpenAI model z nastavení.""" addon = xbmcaddon.Addon() return model_or_default('openai', addon.getSetting("openai_model") or DEFAULT_MODEL['openai']) # Funkce pro odeslání promptu na OpenAI def send_prompt(prompt: str, model: str = None, use_tools: bool = False, **kwargs) -> (str, dict): # Načtení nastavení addonu addon = xbmcaddon.Addon() API_KEY = addon.getSetting("openai_api_key") # Extra data pro debug context_titles = kwargs.get('context_titles') context_limit = kwargs.get('context_limit') system_prompt = kwargs.get('system_prompt') if not API_KEY: raise ValueError("OpenAI API klíč není nastaven.") # Pokud není model specifikován, použij model z nastavení if model is None: model = get_current_model() # Načtení parametrů z nastavení temperature = float(addon.getSetting("openai_temperature") or "1.0") top_p = float(addon.getSetting("openai_top_p") or "1.0") max_output_tokens = int(kwargs.get("max_output_tokens") or addon.getSetting("openai_max_output_tokens") or "16000") reasoning_effort = addon.getSetting("openai_reasoning_effort") or "medium" url = "https://api.openai.com/v1/responses" headers = { "Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json", } # === SESTAVENÍ STANDARDNÍCH MESSAGES === # Standardní formát: [{role, content}] - stejný jako Groq/Mistral/Anthropic messages = [] json_mode = kwargs.get('json_mode', False) messages_list = kwargs.get('messages', None) if messages_list: # Zkontrolovat jestli už messages obsahují system roli has_system = any(msg.get('role') == 'system' for msg in messages_list) # Přidat system prompt jako první, pokud není v messages a máme ho if system_prompt and not has_system: messages.append({"role": "system", "content": system_prompt}) for i, msg in enumerate(messages_list): content = msg['content'] # OpenAI Responses API vyžaduje slovo 'json' v input messages pro json_mode # Přidáme instrukci k první user zprávě if json_mode and i == 0 and msg['role'] == 'user': content = f"{content}\n\n[Odpověz ve formátu JSON.]" messages.append({"role": msg['role'], "content": content}) else: # Jednoduchý prompt bez multi-turn if system_prompt: messages.append({"role": "system", "content": system_prompt}) content = prompt if json_mode: content = f"{prompt}\n\n[Odpověz ve formátu JSON.]" messages.append({"role": "user", "content": content}) # === TRANSFORMACE NA OPENAI RESPONSES API FORMÁT === # OpenAI Responses API používá 'input' místo 'messages' a 'instructions' místo system role input_messages = [ {"type": "message", "role": msg['role'], "content": msg['content']} for msg in messages if msg['role'] != 'system' ] is_reasoning_model = model.startswith(REASONING_PREFIXES) if is_reasoning_model: payload = { "model": model, "input": input_messages, "text": {"verbosity": "low"}, "reasoning": {"effort": reasoning_effort}, "max_output_tokens": max_output_tokens } else: payload = { "model": model, "input": input_messages, "temperature": temperature, "top_p": top_p, "max_output_tokens": max_output_tokens } # Přidat system prompt (instructions) pokud je definován if system_prompt: payload["instructions"] = system_prompt # JSON mode - vynutit JSON response formát json_mode = kwargs.get('json_mode', False) if json_mode: if "text" not in payload: payload["text"] = {} payload["text"]["format"] = {"type": "json_object"} # Přidat tools pouze pokud je to požadováno if use_tools: payload["tools"] = [{"type": "web_search"}] xbmc.log(f"[wcs][openai] URL: {url}", getattr(xbmc, 'LOGNOTICE', xbmc.LOGINFO)) xbmc.log(f"[wcs][openai] Model: {model}", getattr(xbmc, 'LOGNOTICE', xbmc.LOGINFO)) # === DEBUG PAYLOAD - messages už obsahují system pokud existuje === debug_payload = { "messages": messages, "model": model, "temperature": temperature if not is_reasoning_model else None, "reasoning_effort": reasoning_effort if is_reasoning_model else None, "max_tokens": max_output_tokens } # Debug: Zobrazí standardní request před odesláním if not kwargs.get('private_content', False) and not show_api_request_debug("OpenAI", model, debug_payload, context_titles=context_titles, context_limit=context_limit): raise Exception("Odeslání API requestu bylo zrušeno uživatelem.") start_time = time.time() response = requests.post(url, headers=headers, json=payload, timeout=kwargs.get('request_timeout', 120)) end_time = time.time() latency = end_time - start_time # Debug: Zobrazí raw response po obdržení try: response_data = response.json() if not kwargs.get('private_content', False): show_api_response_debug("OpenAI", model, response_data, latency=latency) except: if not kwargs.get('private_content', False): show_api_response_debug("OpenAI", model, {"raw_text": response.text}, latency=latency) response.raise_for_status() data = response.json() # Extract usage data usage = data.get("usage", {}) # Build content from output events outputs = data.get("output", []) content = "" if isinstance(outputs, list): for evt in outputs: if isinstance(evt, dict) and evt.get("type") == "message": cont = evt.get("content") if isinstance(cont, list): content = "".join(seg.get("text", "") for seg in cont if isinstance(seg, dict)) else: content = cont or evt.get("text", "") break # Fallback to 'choices' if no output events if not content: content = data.get("choices", [{}])[0].get("message", {}).get("content", "") if kwargs.get('include_raw', False): return content, usage, data, latency return content, usage def validate_api_key(): """ Ověří platnost API klíče. Returns: bool: True pokud je klíč platný, False jinak """ addon = xbmcaddon.Addon() API_KEY = addon.getSetting("openai_api_key") if not API_KEY: return False try: url = "https://api.openai.com/v1/models" headers = { "Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json", } response = requests.get(url, headers=headers, timeout=10) response.raise_for_status() return True except requests.exceptions.HTTPError as e: if e.response.status_code == 401: xbmc.log("[wcs][openai_api] validate_api_key: Neplatný API klíč (401)", xbmc.LOGWARNING) return False else: xbmc.log(f"[wcs][openai_api] validate_api_key: HTTP chyba {e.response.status_code}", xbmc.LOGWARNING) return False except requests.exceptions.RequestException as e: xbmc.log(f"[wcs][openai_api] validate_api_key: Síťová chyba - {e}", xbmc.LOGWARNING) return False except Exception as e: xbmc.log(f"[wcs][openai_api] validate_api_key: Neočekávaná chyba - {e}", xbmc.LOGWARNING) return False