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| import streamlit as st | |
| from huggingface_hub import InferenceClient | |
| from gtts import gTTS | |
| import base64 | |
| from pydub import AudioSegment | |
| from pydub.playback import play | |
| client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") | |
| system_prompt = "Tu nombre será Chaman 3.0 una IA conductual, hablaras español tu rol es la bioética y el existencialismo estóico, holísticamente." | |
| system_prompt_sent = False | |
| def format_prompt(message, history): | |
| global system_prompt_sent | |
| prompt = "<s>" | |
| if history is not None and isinstance(history, list): | |
| if not any(f"[INST] {system_prompt} [/INST]" in user_prompt for user_prompt, _ in history): | |
| prompt += f"[INST] {system_prompt} [/INST]" | |
| system_prompt_sent = True | |
| for user_prompt, bot_response in history: | |
| prompt += f"[INST] {user_prompt} [/INST]" | |
| prompt += f" {bot_response}</s> " | |
| prompt += f"[INST] {message} [/INST]" | |
| return prompt | |
| def text_to_speech(text, speed=1.3): | |
| tts = gTTS(text=text, lang='es') | |
| audio_file_path = 'output.mp3' | |
| tts.save(audio_file_path) | |
| sound = AudioSegment.from_mp3(audio_file_path) | |
| sound = sound.speedup(playback_speed=speed) | |
| sound.export(audio_file_path, format="mp3") | |
| return audio_file_path | |
| def generate(user_input, history, temperature=None, max_new_tokens=1024, top_p=0.95, repetition_penalty=1.0): | |
| global system_prompt_sent | |
| temperature = float(temperature) if temperature is not None else 0.9 | |
| if temperature < 1e-2: | |
| temperature = 1e-2 | |
| top_p = float(top_p) | |
| generate_kwargs = dict( | |
| temperature=temperature, | |
| max_new_tokens=max_new_tokens, | |
| top_p=top_p, | |
| repetition_penalty=repetition_penalty, | |
| do_sample=True, | |
| seed=42, | |
| ) | |
| formatted_prompt = format_prompt(user_input, history) | |
| stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True) | |
| response = "" | |
| for response_token in stream: | |
| response += response_token.token.text | |
| response = ' '.join(response.split()).replace('</s>', '') | |
| audio_file_path = text_to_speech(response, speed=1.3) | |
| audio_file = open(audio_file_path, 'rb') | |
| audio_bytes = audio_file.read() | |
| return response, audio_bytes | |
| if "history" not in st.session_state: | |
| st.session_state.history = [] | |
| user_input = st.text_input(label="Usuario", value="") | |
| output, audio_bytes = generate(user_input, history=st.session_state.history) | |
| if user_input: | |
| st.session_state.history.append((user_input, output)) | |
| st.text_area("Salida del Chatbot", value=output, height=400, max_chars=900, key="output_text", disabled=True) | |
| st.markdown( | |
| f""" | |
| <audio autoplay="autoplay" controls="controls" src="data:audio/mp3;base64,{base64.b64encode(audio_bytes).decode()}" type="audio/mp3" id="audio_player"></audio> | |
| """, | |
| unsafe_allow_html=True | |
| ) |