import random
import numpy as np
import torch
import os
import streamlit as st


def get_theme_colors():
    """Return a dict of CSS color values for the current theme (dark / light)."""
    is_light = st.session_state.get("theme_mode", "dark") == "light"
    if is_light:
        return {
            # Card / box backgrounds
            "card_bg":        "#f0f1f5",
            "card_bg_alt":    "#e9ebf0",
            "card_bg_deep":   "#e2e4ea",
            "surface":        "#ffffff",
            # Text
            "text":           "#1b1b2f",
            "text_secondary": "#4a5568",
            "text_muted":     "#6b7280",
            # Borders
            "border":         "#d1d5db",
            "border_light":   "#e5e7eb",
            # Accent banner
            "banner_bg":      "#e8ecf6",
            "banner_text":    "#1b1b2f",
            # Verification
            "verify_bg":      "#f0f2f6",
            # Code / monospace
            "code_bg":        "#ecedf2",
            "code_text":      "#1b1b2f",
            # Graph / circuit
            "graph_edge":     "#b0b8c4",
            "node_outline":   "rgba(0,0,0,0)",
            "layer_label":    "#2f3f70",
            "grid_color":     "rgba(200,200,210,0.15)",
        }
    else:
        return {
            "card_bg":        "#2b2b2b",
            "card_bg_alt":    "#1a1a1a",
            "card_bg_deep":   "#0E1117",
            "surface":        "#0E1117",
            "text":           "#ffffff",
            "text_secondary": "#DCDCDC",
            "text_muted":     "#888888",
            "border":         "#444",
            "border_light":   "#262730",
            "banner_bg":      "#2f3f70",
            "banner_text":    "#f5f7fb",
            "verify_bg":      "#1a1a1a",
            "code_bg":        "#1a1a1a",
            "code_text":      "#DCDCDC",
            # Graph / circuit
            "graph_edge":     "gray",
            "node_outline":   "black",
            "layer_label":    "#dcae36",
            "grid_color":     "rgba(200,200,200,0.3)",
        }

def set_seed(seed_value=42):
    # Set a seed for reproducibility.
    random.seed(seed_value)
    np.random.seed(seed_value)
    torch.manual_seed(seed_value)
    if torch.cuda.is_available():
        torch.cuda.manual_seed_all(seed_value) 

def init_qwen_api():
    # Set up the API configuration for Qwen.
    api_key = os.environ.get("QWEN_API_KEY")
    
    if not api_key:
        # Fallback for local testing if env var is missing
        api_key = "fd89601072073b34725b18a36333c805"
        
    return {
        "api_key": api_key,
        "api_endpoint": "https://chat-ai.academiccloud.de/v1",
        "model": "qwen3-vl-30b-a3b-instruct"
    }