initial commit

app.py

@@ -0,0 +1,55 @@
+import paddle
+
+import gradio as gr
+from paddlenlp.transformers import (UnifiedTransformerLMHeadModel,
+                                    UnifiedTransformerTokenizer)
+from paddlespeech.cli.asr.infer import ASRExecutor
+from paddlespeech.cli.tts.infer import TTSExecutor
+
+asr = ASRExecutor()
+tts = TTSExecutor()
+# warmup ASR and TTS
+print(tts(text=asr("zh.wav", force_yes=True)))
+model_name_or_path = 'plato-mini'
+model = UnifiedTransformerLMHeadModel.from_pretrained(model_name_or_path)
+tokenizer = UnifiedTransformerTokenizer.from_pretrained(model_name_or_path)
+model.eval()
+
+def chat(audio, history):
+    message = asr(audio, force_yes=True)
+    history = history or []
+    history_input = [text for round in history for text in round]
+    history_input.append(message)
+    inputs = tokenizer.dialogue_encode(history_input,
+                                               add_start_token_as_response=True,
+                                               return_tensors=True,
+                                               is_split_into_words=False)
+    inputs['input_ids'] = inputs['input_ids'].astype('int64')
+    ids, scores = model.generate(
+        input_ids=inputs['input_ids'],
+        token_type_ids=inputs['token_type_ids'],
+        position_ids=inputs['position_ids'],
+        attention_mask=inputs['attention_mask'],
+        decode_strategy="sampling",
+        num_return_sequences=5,
+        top_p=0.95)
+    index = paddle.argmax(scores)
+    response = tokenizer.decode(ids[index], skip_special_tokens=True).replace(" ", "")
+    history.append((message, response))
+    output_file = tts(text=response, output="output.wav")
+    return output_file, history, history
+
+demo = gr.Interface(
+    chat,
+    inputs=[
+        gr.Audio(source="microphone", type="filepath"),
+        "state"],
+    outputs=[
+        gr.Audio(type="filepath"),
+        gr.Chatbot().style(color_map=("green", "pink")),
+        "state"
+        ],
+    allow_flagging="never",
+)
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+paddlepaddle
+paddlenlp
+paddlespeech