Backend: @main.py egy yaml fájlba lehessen konfigurálni az l...
Prompt
Backend: @main.py egy yaml fájlba lehessen konfigurálni az llm eket Mind openai kompstibilis szoval glm 5.2-t integráld bele mint fő model import os from openai import OpenAI client = OpenAI( api_key=os.environ["REQUESTY_API_KEY"], base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="zai/glm-5.2", messages=[{"role": "user", "content": "hello!"}], temperature=0, max_tokens=131072, reasoning_effort="max", ) print(response.choices[0].message.content) a Gpt 5.6 sol xhigh pro -t ha a felhasználó kód hiba keresést vagy javítást kér import os from openai import OpenAI client = OpenAI( api_key=os.environ["LLMAPI_KEY"], base_url="https://api.llmapi.ai/v1", ) res = client.responses.create( model="gpt-5.6-sol", reasoning={ "mode": "pro", "effort": "xhigh", }, input="helo", ) print(res.output_text) Frontend: @index.html ehhez írd a backendet Ne szabály alapú legyen a routing modellek kozott hanem az itt leírtakat le kell írni az fogadó modelnek is aki mindig fogadja az user üzeneteit és ő dönt arról hogy melyik modelt hívja meg: Fogadó model: from cerebras.cloud.sdk import Cerebras import base64 import mimetypes import os from pathlib import Path api_key = os.environ["CEREBRAS_API_KEY"] image_path = Path("screenshot.png") if not image_path.is_file(): raise FileNotFoundError(f"Image file not found: {image_path}") mime_type, _ = mimetypes.guess_type(image_path.name) if mime_type not in {"image/png", "image/jpeg"}: raise ValueError(f"Unsupported image type: {mime_type}. Only PNG and JPEG are supported.") with image_path.open("rb") as image_file: base64_image = base64.b64encode(image_file.read()).decode("utf-8") client = Cerebras(api_key=api_key) response = client.chat.completions.create( model="gemma-4-31b", messages=[ { "role": "user", "content": [ {"type": "text", "text": "Describe this image in one concise sentence."}, { "type": "image_url", "image_url": { "url": f"{mime_type};base64,{base64_image}" }, }, ], } ], ) content = response.choices[0].message.content if isinstance(content, list): print("".join(part.get("text", "") if isinstance(part, dict) else str(part) for part in content).strip()) else: print(str(content).strip()) A fogadó modell ezen kívűl SEMMI mást nem csinál Only complete files and comments are allowed! I forbid any simplified, mock, placeholder, dummy, simulated, incomplete, or unoptimized production-ready code. It must not be truncated, and there must be no instances of … or similar. 50 xy must not be a dummy, "to do," or "sorry" placeholder. You must provide the complete code for every file; do not write anything else besides that. App bezarasa utan is tud mukodni es valaszolni Frontenden természetesen ezt hide tehat nem ír ki modelneveket
A system prompt was added to support web rendering
