app.py

import streamlit as st
from huggingface_hub import InferenceClient

# Initialize the client
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")

# Function to format the prompt for Rorschach interpretation
def format_prompt(message, history):
    prompt = "<s>"
    for user_prompt, bot_response in history:
        prompt += f"[INST] {user_prompt} [/INST]"
        prompt += f" {bot_response} "
    prompt += f"[INST] Interpretación Rorschach: {message} [/INST]"
    return prompt

# Function to generate response
def generate(prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
    temperature = max(float(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(prompt, history)

    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
    output = ""
    for response in stream:
        output += response.token.text
    return output

# Streamlit interface
st.title("Interpretación del Test de Rorschach")

# Chat history
if 'history' not in st.session_state:
    st.session_state.history = []

# User input
entrada_usuario = st.text_input("Que ves en las imagenes ..:", key="entrada_usuario")

# Generate response and update history
if st.button("Enviar"):
    if entrada_usuario:
        bot_response = generate(entrada_usuario, st.session_state.history)
        st.session_state.history.append((entrada_usuario, bot_response))

# Display conversation
chat_text = ""
for user_msg, bot_msg in st.session_state.history:
    chat_text += f"Tu: {user_msg}\nBuho: {bot_msg}\n\n"
st.text_area("Respuestas del Buho", value=chat_text, height=300, disabled=False)