Upload app.py

app.py

@@ -12,6 +12,7 @@ from text import text_to_sequence, _clean_text
 from torch import no_grad, LongTensor
 from gradio_client import utils as client_utils
 import logging
+from langchain
 logging.getLogger('numba').setLevel(logging.WARNING)
 limitation = os.getenv("SYSTEM") == "spaces"  # limit text and audio length in huggingface spaces
 
@@ -19,6 +20,16 @@ hps_ms = utils.get_hparams_from_file(r'config/config.json')
 
 audio_postprocess_ori = gr.Audio.postprocess
 
+def get_chat_model(api_key = None):
+    from langchain_google_genai import ChatGoogleGenerativeAI
+
+    llm = ChatGoogleGenerativeAI(
+        model="gemini-2.5-pro",
+        temperature=0,
+        google_api_key = api_key,
+    )
+    return llm
+
 def audio_postprocess(self, y):
     data = audio_postprocess_ori(self, y)
     if data is None:
@@ -36,6 +47,45 @@ def get_text(text, hps, is_symbol):
     return text_norm, clean_text
 
 def create_tts_fn(net_g_ms, speaker_id):
+    def prompt_to_transcript(model, human_prompt):
+        from langchain.prompts import ChatPromptTemplate
+
+        system_prompt = """
+        You are an AI chatbot roleplaying as {character_name}.
+        Your personality traits are:
+        - {trait_1}
+        - {trait_2}
+        - {trait_3}
+        - {extra_details}
+
+        Stay in character at all times. 
+        Do not break character or mention that you are an AI. 
+        Always respond in a way consistent with {character_name}'s personality, tone, and background.
+
+        Here are examples of how {character_name} responds:
+
+        [Example 1]
+        User: "Hello, how are you?"
+        {character_name}: "{example_1}"
+
+        [Example 2]
+        User: "Tell me a story."
+        {character_name}: "{example_2}"
+
+        [Example 3]
+        User: "What do you think about technology?"
+        {character_name}: "{example_3}"
+
+        Follow this style and tone in every response.
+        """
+
+        # Then build the template with LangChain
+        prompt = ChatPromptTemplate.from_messages([
+            ("system", system_prompt),
+            ("user", "{input}")
+        ])
+
+        
     def tts_fn(text, language, noise_scale, noise_scale_w, length_scale, is_symbol):
         text = text.replace('\n', ' ').replace('\r', '').replace(" ", "")
         if limitation: