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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()
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