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# app.py
"""
Main application file for SHASHA AI (Gradio).  
Only change: enlarge logo to 120 × 120 px.
"""

import gradio as gr
from typing import Optional, Dict, List, Tuple, Any
import os

# --- Local imports ---
from constants import (
    HTML_SYSTEM_PROMPT,
    TRANSFORMERS_JS_SYSTEM_PROMPT,
    AVAILABLE_MODELS,
    DEMO_LIST,
)
from hf_client import get_inference_client
from tavily_search import enhance_query_with_search
from utils import (
    extract_text_from_file,
    extract_website_content,
    apply_search_replace_changes,
    history_to_messages,
    history_to_chatbot_messages,
    remove_code_block,
    parse_transformers_js_output,
    format_transformers_js_output,
)
from deploy import send_to_sandbox

History = List[Tuple[str, str]]
Model   = Dict[str, Any]

SUPPORTED_LANGUAGES = [
    "python","c","cpp","markdown","latex","json","html","css","javascript","jinja2",
    "typescript","yaml","dockerfile","shell","r","sql","sql-msSQL","sql-mySQL",
    "sql-mariaDB","sql-sqlite","sql-cassandra","sql-plSQL","sql-hive","sql-pgSQL",
    "sql-gql","sql-gpSQL","sql-sparkSQL","sql-esper"
]

def get_model_details(name:str)->Optional[Model]:
    return next((m for m in AVAILABLE_MODELS if m["name"]==name), None)

def generation_code(
    query:Optional[str],
    file:Optional[str],
    website_url:Optional[str],
    current_model:Model,
    enable_search:bool,
    language:str,
    history:Optional[History],
)->Tuple[str,History,str,List[Dict[str,str]]]:
    query   = query or ""
    history = history or []
    try:
        system_prompt = (
            HTML_SYSTEM_PROMPT                if language=="html"          else
            TRANSFORMERS_JS_SYSTEM_PROMPT     if language=="transformers.js"
            else f"You are an expert {language} developer. Write clean, idiomatic {language} code."
        )
        model_id = current_model["id"]
        provider = (
            "openai" if model_id.startswith("openai/") or model_id in {"gpt-4","gpt-3.5-turbo"}
            else "gemini" if model_id.startswith(("gemini/","google/"))
            else "fireworks-ai" if model_id.startswith("fireworks-ai/")
            else "auto"
        )

        msgs    = history_to_messages(history, system_prompt)
        context = query
        if file:
            context += f"\n\n[Attached file]\n{extract_text_from_file(file)[:5000]}"
        if website_url:
            wtext = extract_website_content(website_url)
            if not wtext.startswith("Error"):
                context += f"\n\n[Website content]\n{wtext[:8000]}"
        msgs.append({"role":"user","content":enhance_query_with_search(context, enable_search)})

        client  = get_inference_client(model_id, provider)
        resp    = client.chat.completions.create(model=model_id, messages=msgs,max_tokens=16000,temperature=0.1)
        content = resp.choices[0].message.content

    except Exception as e:
        err = f"❌ **Error:**\n```\n{e}\n```"
        history.append((query, err))
        return "", history, "", history_to_chatbot_messages(history)

    if language=="transformers.js":
        files   = parse_transformers_js_output(content)
        code    = format_transformers_js_output(files)
        preview = send_to_sandbox(files.get("index.html",""))
    else:
        cleaned = remove_code_block(content)
        code    = apply_search_replace_changes(history[-1][1], cleaned) if history and not history[-1][1].startswith("❌") else cleaned
        preview = send_to_sandbox(code) if language=="html" else ""

    new_hist = history + [(query, code)]
    return code, new_hist, preview, history_to_chatbot_messages(new_hist)

# --- CSS ---
CUSTOM_CSS = """
body{font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,sans-serif;}
#main_title{text-align:center;font-size:2.5rem;margin-top:.5rem;}
#subtitle{text-align:center;color:#4a5568;margin-bottom:2rem;}
.gradio-container{background-color:#f7fafc;}
#gen_btn{box-shadow:0 4px 6px rgba(0,0,0,0.1);}
"""

LOGO_PATH = "assets/logo.png"

with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue"),
               css=CUSTOM_CSS,
               title="Shasha AI") as demo:
    history_state = gr.State([])
    initial_model = AVAILABLE_MODELS[0]
    model_state   = gr.State(initial_model)

    # enlarged logo (120×120 px)
    if os.path.exists(LOGO_PATH):
        gr.Image(value=LOGO_PATH, height=120, width=120,
                 show_label=False, container=False)

    gr.Markdown("# 🚀 Shasha AI", elem_id="main_title")
    gr.Markdown("Your AI partner for generating, modifying, and understanding code.", elem_id="subtitle")

    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### 1. Select Model")
            model_dd = gr.Dropdown([m["name"] for m in AVAILABLE_MODELS],
                                   value=initial_model["name"], label="AI Model")

            gr.Markdown("### 2. Provide Context")
            with gr.Tabs():
                with gr.Tab("📝 Prompt"):
                    prompt_in = gr.Textbox(lines=7, placeholder="Describe your request...", show_label=False)
                with gr.Tab("📄 File"):
                    file_in = gr.File(type="filepath")
                with gr.Tab("🌐 Website"):
                    url_in = gr.Textbox(placeholder="https://example.com")

            gr.Markdown("### 3. Configure Output")
            lang_dd    = gr.Dropdown(SUPPORTED_LANGUAGES, value="html", label="Target Language")
            search_chk = gr.Checkbox(label="Enable Web Search")
            with gr.Row():
                clr_btn = gr.Button("Clear Session", variant="secondary")
                gen_btn = gr.Button("Generate Code", variant="primary", elem_id="gen_btn")

        with gr.Column(scale=2):
            with gr.Tabs():
                with gr.Tab("💻 Code"):
                    code_out = gr.Code(language="html", interactive=True)
                with gr.Tab("👁️ Live Preview"):
                    preview_out = gr.HTML()
                with gr.Tab("📜 History"):
                    chat_out = gr.Chatbot(type="messages")

    model_dd.change(lambda n: get_model_details(n) or initial_model,
                    inputs=[model_dd], outputs=[model_state])

    gen_btn.click(
        fn=generation_code,
        inputs=[prompt_in, file_in, url_in, model_state, search_chk, lang_dd, history_state],
        outputs=[code_out, history_state, preview_out, chat_out],
    )

    clr_btn.click(
        lambda: ("", None, "", [], "", "", []),
        outputs=[prompt_in, file_in, url_in, history_state, code_out, preview_out, chat_out],
        queue=False,
    )

if __name__ == "__main__":
    demo.queue().launch()