Update app.py

app.py

@@ -1,9 +1,23 @@
 # app.py
 
-from typing import Optional, Dict, List, Tuple
-import gradio as gr
+"""
+Main application file for SHASHA AI, a Gradio-based AI code generation tool.
+
+Provides a UI for generating code in many languages using various AI models.
+Supports text prompts, file uploads, website scraping, optional web search,
+and live previews of HTML output.
+"""
 
-from constants import HTML_SYSTEM_PROMPT, AVAILABLE_MODELS, DEMO_LIST
+import gradio as gr
+from typing import Optional, Dict, List, Tuple, Any
+
+# --- Local module 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 (
@@ -14,122 +28,174 @@ from utils import (
     history_to_chatbot_messages,
     remove_code_block,
     parse_transformers_js_output,
-    format_transformers_js_output
+    format_transformers_js_output,
 )
-from deploy import send_to_sandbox, handle_load_project
+from deploy import send_to_sandbox
 
-# Type aliases
+# --- Type aliases ---
 History = List[Tuple[str, str]]
+Model = Dict[str, Any]
+
+# --- Supported languages for dropdown ---
+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]:
+    for m in AVAILABLE_MODELS:
+        if m["name"] == name:
+            return m
+    return None
 
-# Core generation function
 def generation_code(
     query: Optional[str],
-    image: Optional[gr.Image],
     file: Optional[str],
     website_url: Optional[str],
-    _setting: Dict[str, str],
-    _history: Optional[History],
-    _current_model: Dict,
+    current_model: Model,
     enable_search: bool,
     language: str,
-    provider: str
+    history: Optional[History],
 ) -> Tuple[str, History, str, List[Dict[str, str]]]:
-
-    if query is None:
-        query = ''
-    if _history is None:
-        _history = []
-
-    system_prompt = _setting.get('system', HTML_SYSTEM_PROMPT)
-    messages = history_to_messages(_history, system_prompt)
-
-    if file:
-        file_text = extract_text_from_file(file)
-        if file_text:
-            query += f"\n\n[Reference file content below]\n{file_text[:5000]}"
-
-    if website_url:
-        website_text = extract_website_content(website_url)
-        if not website_text.startswith("Error"):
-            query += f"\n\n[Website content below]\n{website_text[:8000]}"
-
-    final_query = enhance_query_with_search(query, enable_search)
-    messages.append({'role': 'user', 'content': final_query})
-
-    client = get_inference_client(_current_model['id'], provider)
-    completion = client.chat.completions.create(
-        model=_current_model['id'],
-        messages=messages,
-        max_tokens=10000
-    )
-    content = completion.choices[0].message.content
-
-    has_existing = bool(_history and _history[-1][1])
-    if language == 'transformers.js':
+    query = query or ""
+    history = history or []
+    try:
+        # Choose system prompt based on language
+        if language == "html":
+            system_prompt = HTML_SYSTEM_PROMPT
+        elif language == "transformers.js":
+            system_prompt = TRANSFORMERS_JS_SYSTEM_PROMPT
+        else:
+            # Generic fallback prompt
+            system_prompt = (
+                f"You are an expert {language} developer. "
+                f"Write clean, idiomatic {language} code based on the user's request."
+            )
+
+        model_id = current_model["id"]
+        # Determine provider
+        if model_id.startswith("openai/") or model_id in {"gpt-4", "gpt-3.5-turbo"}:
+            provider = "openai"
+        elif model_id.startswith("gemini/") or model_id.startswith("google/"):
+            provider = "gemini"
+        elif model_id.startswith("fireworks-ai/"):
+            provider = "fireworks-ai"
+        else:
+            provider = "auto"
+
+        # Build message history
+        msgs = history_to_messages(history, system_prompt)
+        context = query
+        if file:
+            ftext = extract_text_from_file(file)
+            context += f"\n\n[Attached file]\n{ftext[:5000]}"
+        if website_url:
+            wtext = extract_website_content(website_url)
+            if not wtext.startswith("Error"):
+                context += f"\n\n[Website content]\n{wtext[:8000]}"
+        final_q = enhance_query_with_search(context, enable_search)
+        msgs.append({"role": "user", "content": final_q})
+
+        # Call the model
+        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)
+
+    # Process model output
+    if language == "transformers.js":
         files = parse_transformers_js_output(content)
-        code_str = format_transformers_js_output(files)
-        sandbox_html = send_to_sandbox(files['index.html'])
+        code = format_transformers_js_output(files)
+        preview = send_to_sandbox(files.get("index.html", ""))
     else:
-        clean = remove_code_block(content)
-        if has_existing and not clean.strip().startswith('<!DOCTYPE'):
-            clean = apply_search_replace_changes(_history[-1][1], clean)
-        code_str = clean
-        sandbox_html = send_to_sandbox(clean) if language == 'html' else ''
-
-    new_history = _history + [(query, code_str)]
-    chat_msgs = history_to_chatbot_messages(new_history)
-
-    return code_str, new_history, sandbox_html, chat_msgs
-
-with gr.Blocks(
-    theme=gr.themes.Base(),
-    title="AnyCoder - AI Code Generator"
-) as demo:
+        cleaned = remove_code_block(content)
+        if history and history[-1][1] and not history[-1][1].startswith("❌"):
+            code = apply_search_replace_changes(history[-1][1], cleaned)
+        else:
+            code = cleaned
+        preview = send_to_sandbox(code) if language == "html" else ""
+
+    new_hist = history + [(query, code)]
+    chat = history_to_chatbot_messages(new_hist)
+    return code, new_hist, preview, chat
+
+# --- Custom 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: 1.5rem; }
+#subtitle { text-align: center; color: #4a5568; margin-bottom: 2.5rem; }
+.gradio-container { background-color: #f7fafc; }
+#gen_btn { box-shadow: 0 4px 6px rgba(0,0,0,0.1); }
+"""
+
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue"), css=CUSTOM_CSS, title="Shasha AI") as demo:
     history_state = gr.State([])
-    setting_state = gr.State({'system': HTML_SYSTEM_PROMPT})
-    current_model = gr.State(AVAILABLE_MODELS[9])
-
-    with gr.Sidebar():
-        gr.LoginButton()
-        load_project_url = gr.Textbox(label="Hugging Face Space URL")
-        load_project_btn = gr.Button("Import Project")
-        load_project_status = gr.Markdown(visible=False)
-
-        input_box = gr.Textbox(label="What to build?", lines=3)
-        language_dropdown = gr.Dropdown(choices=["html", "python", "transformers.js"], value="html")
-        website_input = gr.Textbox(label="Website URL")
-        file_input = gr.File(label="Reference file")
-        image_input = gr.Image(label="Design image")
-        search_toggle = gr.Checkbox(label="Web search")
-        model_dropdown = gr.Dropdown(choices=[m['name'] for m in AVAILABLE_MODELS], value=AVAILABLE_MODELS[9]['name'])
-
-        generate_btn = gr.Button("Generate")
-        clear_btn = gr.Button("Clear")
-
-    with gr.Column():
-        with gr.Tabs():
-            with gr.Tab("Code"):
-                code_output = gr.Code(label="Generated code")
-            with gr.Tab("Preview"):
-                preview = gr.HTML(label="Live preview")
-            with gr.Tab("History"):
-                history_output = gr.Chatbot()
-
-    load_project_btn.click(
-        fn=handle_load_project,
-        inputs=[load_project_url],
-        outputs=[load_project_status, code_output, preview, load_project_url, history_state, history_output]
-    )
-
-    generate_btn.click(
+    initial_model = AVAILABLE_MODELS[0]
+    model_state = gr.State(initial_model)
+
+    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(
+                choices=[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=[input_box, image_input, file_input, website_input,
-                setting_state, history_state, current_model,
-                search_toggle, language_dropdown, gr.State('auto')],
-        outputs=[code_output, history_state, preview, history_output]
+        inputs=[prompt_in, file_in, url_in, model_state, search_chk, lang_dd, history_state],
+        outputs=[code_out, history_state, preview_out, chat_out],
     )
 
-    clear_btn.click(lambda: ([], [], "", []), outputs=[history_state, history_output, preview, code_output])
+    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()