Update app.py

app.py

@@ -8,6 +8,8 @@ from langchain.llms import OpenAI
 from gradio_client import Client
 eleven = Client("https://elevenlabs-tts.hf.space/")
 
+import wave
+
 openai_api_key = os.environ.get("OPENAI_API_KEY")
 
 llm = OpenAI(temperature=0.9)
@@ -29,6 +31,21 @@ def split_text(text, max_length):
 
     return chunks
 
+def join_wav_files(input_files, output_file):
+    # Open the first input file to get its parameters
+    with wave.open(input_files[0], 'rb') as first_file:
+        # Get the audio parameters from the first file
+        params = first_file.getparams()
+
+        # Create a new wave file for writing the joined audio
+        with wave.open(output_file, 'wb') as output:
+            output.setparams(params)
+
+            # Iterate over the input files and write their audio data to the output file
+            for input_file in input_files:
+                with wave.open(input_file, 'rb') as input:
+                    output.writeframes(input.readframes(input.getnframes()))
+
 def generate_story(text):
     """Generate a story using the langchain library and OpenAI's GPT-3 model."""
     prompt = PromptTemplate(
@@ -46,12 +63,24 @@ def generate_story(text):
     Cutting text in chunks
     —
     """)
+    input_waves = []
     max_length = 250
     text_chunks = split_text(story_result, max_length)
     for chunk in text_chunks:
         print(chunk)
+        result = eleven.predict(
+				chunk,	# str representing input in 'Input Text (250 characters max)' Textbox component
+				"Bella",	# str representing input in 'Voice' Dropdown component
+				"eleven_monolingual_v1",	# str representing input in 'Model' Radio component
+				fn_index=0
+        )
+        print(result)
+        input_waves.append(result)
     
-    return story_result
+    output_file = 'output.wav'
+
+    join_wav_files(input_waves, output_wav)
+    return story_result, 'output_wav'
 
 def app(text):
     story = generate_story(text)
@@ -64,6 +93,6 @@ with gr.Blocks() as demo:
         audio = gr.Audio()
         story = gr.Textbox()
 
-    submit_btn.click(fn=app, inputs=[text], outputs=[story])
+    submit_btn.click(fn=app, inputs=[text], outputs=[story, audio])
         
 demo.launch()