Update app.py

app.py

@@ -4,21 +4,20 @@ import gradio as gr
 import openai
 from prompts import SYSTEM_PROMPT
 
-# 📥 Load environment variables
+# Load environment variables
 load_dotenv()
 
 client = openai.OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 
-# 🔁 Transcribe audio input using OpenAI Whisper API
+# Ensure all outputs are returned as string
 def transcribe_audio(audio_file: str) -> str:
     with open(audio_file, "rb") as f:
         transcript = client.audio.transcriptions.create(
             model="whisper-1",
             file=f
         )
-    return transcript.text
+    return str(transcript.text)
 
-# 💬 Call OpenAI chat with the transcribed or text input
 def call_openai(event_details: str) -> str:
     prompt = SYSTEM_PROMPT.format(event_details)
     response = client.chat.completions.create(
@@ -27,33 +26,26 @@ def call_openai(event_details: str) -> str:
         temperature=0.5,
         max_tokens=1024,
     )
-    return response.choices[0].message.content
+    return str(response.choices[0].message.content)
+
+def case_study_generator(event_details: str) -> str:
+    return call_openai(event_details)
 
-# 🔄 New function to handle audio input and route to existing pipeline
 def case_study_from_audio(audio: str) -> str:
     text = transcribe_audio(audio)
     return case_study_generator(text)
 
-# 🎛️ Original function — unchanged but now typed
-def case_study_generator(event_details: str) -> str:
-    return call_openai(event_details)
-
-# 🚀 Gradio interface with two modes: Text or Audio
 with gr.Blocks() as demo:
     gr.Markdown("## 📄 iBoothMe Case Study Generator\nWrite a description or record audio.")
-    
+
     with gr.Tab("Text Input"):
-        text_input = gr.Textbox(
-            label="Event Description",
-            lines=10,
-            placeholder="Paste informal event description here...",
-        )
+        text_input = gr.Textbox(label="Event Description", lines=10)
         text_button = gr.Button("Generate from Text")
         text_output = gr.Textbox(label="Generated Case Study", lines=15)
         text_button.click(fn=case_study_generator, inputs=text_input, outputs=text_output)
 
     with gr.Tab("Audio Input"):
-        audio_input = gr.Audio(type="filepath", label="Upload or Record your event description")
+        audio_input = gr.Audio(type="filepath", label="Upload or Record audio")
         audio_button = gr.Button("Generate from Audio")
         audio_output = gr.Textbox(label="Generated Case Study", lines=15)
         audio_button.click(fn=case_study_from_audio, inputs=audio_input, outputs=audio_output)