Update deployer/gradio_generator.py

deployer/gradio_generator.py

@@ -1,99 +1,121 @@
-# gradio_generator.py - CPU & Spaces-compatible Gradio interface with voice recording for RoboSage
+# gradio_generator.py - CPU & Spaces-compatible Gradio interface with full monetization & artifact management for RoboSage
 
 import os
+import json
 import gradio as gr
+from transformers import pipeline
 from deployer.simulator_interface import VirtualRobot
-from openai import OpenAI
-
-# Initialize OpenAI client for transcription
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-if not OPENAI_API_KEY:
-    raise EnvironmentError("Please set the OPENAI_API_KEY environment variable for audio transcription.")
-openai_client = OpenAI(api_key=OPENAI_API_KEY)
-
-
-def transcribe_audio(audio_file: str) -> str:
-    """
-    Transcribe recorded audio using OpenAI Whisper API.
-    Returns the transcribed text.
-    """
-    with open(audio_file, "rb") as f:
-        response = openai_client.audio.transcriptions.create(
-            file=f,
-            model="whisper-1"
-        )
-    return response.text
-
-
+from deployer.revenue_tracker import get_revenue_stats, package_artifacts
+from core_creator.voice_to_app import VoiceToAppCreator
+
+# Initialize Hugging Face ASR pipeline
+HK_API_KEY = os.getenv("HK_API_KEY")
+if not HK_API_KEY:
+    raise EnvironmentError("Please set the HK_API_KEY environment variable for audio transcription via HuggingFace API.")
+asr = pipeline(
+    task="automatic-speech-recognition",
+    model="openai/whisper-small",
+    use_auth_token=HK_API_KEY
+)
+
+# Core actions
 def robot_behavior(user_input: str) -> str:
-    """
-    Bridge between user input and VirtualRobot actions with basic NLU.
-    """
     bot = VirtualRobot()
     text = user_input.strip().lower()
-
-    # Greeting detection
     if any(greet in text for greet in ["hello", "hi", "hey", "welcome"]):
         return bot.perform_action("wave") + "\n" + bot.perform_action("say Hello there!")
-
-    # Direct speech command
     if text.startswith("say "):
         return bot.perform_action(text)
-
-    # Fallback for unrecognized commands
     return bot.perform_action("say I'm sorry, I didn't understand that.")
 
+# Transcription helper
+def transcribe_audio(audio_file: str) -> str:
+    result = asr(audio_file)
+    return result.get("text", "")
 
 def transcribe_and_respond(audio_file: str) -> str:
-    """
-    Transcribe audio input and run robot_behavior.
-    """
     text = transcribe_audio(audio_file)
     return robot_behavior(text)
 
-
+# Generation & packaging pipeline
+def generate_and_package_app(idea: str):
+    creator = VoiceToAppCreator(idea)
+    assets = creator.run_pipeline()
+    # Package code & config into zip and return path
+    zip_path = package_artifacts(assets)
+    # Prepare blueprint and code previews
+    blueprint = assets.get("blueprint", {})
+    code_files = assets.get("code", {})  # dict of {filename: code_str}
+    # Concatenate code files for preview
+    code_preview = "\n\n".join([f"# {fname}\n{content}" for fname, content in code_files.items()])
+    return zip_path, blueprint, code_preview
+
+# Build full-featured Gradio app
 def launch_gradio_app(
     title: str = "RoboSage App",
-    description: str = "Your robot, your voice."
+    description: str = "Your robot, your voice, monetized."
 ) -> gr.Blocks:
-    """
-    Constructs and returns a Gradio Blocks app with voice and text input for simulation.
-    """
     with gr.Blocks() as demo:
-        gr.Markdown(f"# 🤖 {title}\n\n{description}")
-
-        with gr.Accordion("🤖 Test your robot", open=True):
-            # Text input section
-            text_input = gr.Textbox(
-                label="Text Command",
-                placeholder="Type 'hello' or 'say Have a great day!'"
+        gr.Markdown(f"# 🚀 {title}\n\n{description}")
+
+        # 1️⃣ Generate & Download Artifacts
+        with gr.Accordion("🎨 Generate App & Download Artifacts", open=True):
+            idea = gr.Textbox(label="Robot Idea", placeholder="e.g. A friendly greeting robot.")
+            gen_btn = gr.Button("Generate & Package", key="gen-app-btn")
+            status = gr.Textbox(label="Generation Status", interactive=False)
+            download_zip = gr.File(label="Download Artifacts (.zip)")
+            blueprint_view = gr.JSON(label="App Blueprint")
+            code_view = gr.Code(label="Generated Code Preview", language="python")
+
+            def on_generate(i):
+                zip_path, blueprint, code_preview = generate_and_package_app(i)
+                return (
+                    "✅ App generated successfully!", 
+                    zip_path, 
+                    blueprint, 
+                    code_preview
+                )
+
+            gen_btn.click(
+                fn=on_generate,
+                inputs=[idea],
+                outputs=[status, download_zip, blueprint_view, code_view]
             )
+
+        # 2️⃣ Robot Simulation
+        with gr.Accordion("🤖 Test Your Robot (Text & Voice)", open=False):
+            # Text command
+            text_input = gr.Textbox(label="Text Command", placeholder="Type 'hello' or 'say Great job!'" )
             text_btn = gr.Button("Send Text", key="send-text-btn")
-            text_output = gr.Textbox(label="Robot Response", lines=4, interactive=False)
-            text_btn.click(
-                fn=robot_behavior,
-                inputs=[text_input],
-                outputs=[text_output]
-            )
+            text_output = gr.Textbox(label="Robot Response", lines=3, interactive=False)
+            text_btn.click(fn=robot_behavior, inputs=[text_input], outputs=[text_output])
 
             gr.Markdown("---")
-
-            # Voice input section
-            audio_input = gr.Audio(
-                source="microphone",
-                type="filepath",
-                label="Record Command"
-            )
+            # Voice command
+            audio_input = gr.Audio(source="microphone", type="filepath", label="Record Command")
             audio_btn = gr.Button("Send Audio", key="send-audio-btn")
-            audio_output = gr.Textbox(label="Robot Response (via voice)", lines=4, interactive=False)
-            audio_btn.click(
-                fn=transcribe_and_respond,
-                inputs=[audio_input],
-                outputs=[audio_output]
-            )
+            audio_output = gr.Textbox(label="Robot Response (via voice)", lines=3, interactive=False)
+            audio_btn.click(fn=transcribe_and_respond, inputs=[audio_input], outputs=[audio_output])
 
-    return demo
+        # 3️⃣ Monetization & Revenue
+        with gr.Accordion("💰 Monetization Dashboard", open=False):
+            subscribe_btn = gr.Button("Subscribe to Pro Plan", key="subscribe-btn")
+            subscribe_msg = gr.Textbox(label="Subscription Status", interactive=False)
+            rev_btn = gr.Button("View Revenue Stats", key="rev-stats-btn")
+            rev_table = gr.Dataframe(label="Revenue & Usage Metrics")
+
+            def on_subscribe():
+                # Stubbed subscription activation
+                return "✅ Subscribed! You now have access to premium features."
+
+            def on_view_revenue():
+                df = get_revenue_stats()
+                return df
 
+            subscribe_btn.click(fn=on_subscribe, inputs=None, outputs=[subscribe_msg])
+            rev_btn.click(fn=on_view_revenue, inputs=None, outputs=[rev_table])
+
+    return demo
 
 if __name__ == "__main__":
     app = launch_gradio_app()