Spaces:
Sleeping
Sleeping
File size: 4,000 Bytes
34f575a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 |
import streamlit as st
import pandas as pd
from datetime import datetime, timedelta
from unsloth import FastLanguageModel
import torch
# Cargar el modelo y el tokenizador
model_path = "/home/roser97/MarketAI/lora_model"
model, tokenizer = FastLanguageModel.from_pretrained(
model_name=model_path,
max_seq_length=800, # Ajusta según tus necesidades
load_in_4bit=True,
)
# Configurar el modelo para inferencia
FastLanguageModel.for_inference(model)
def generate_marketing_content(instruction, input_context):
inputs = tokenizer(
[f"### Instruction:\n{instruction}\n### Input:\n{input_context}\n### Response:"],
return_tensors="pt"
).to("cuda" if torch.cuda.is_available() else "cpu")
output = model.generate(**inputs, max_new_tokens=128)
return tokenizer.decode(output[0], skip_special_tokens=True)
def main():
st.set_page_config(page_title="Compass AI", layout="wide")
st.title("Compass AI")
# Sidebar for navigation
page = st.sidebar.selectbox("Choose a page", ["Home", "Campaign Creation", "Strategy", "Scheduling", "Analytics"])
if page == "Home":
show_home()
elif page == "Campaign Creation":
show_campaign_creation()
elif page == "Strategy":
show_strategy()
elif page == "Scheduling":
show_scheduling()
elif page == "Analytics":
show_analytics()
def show_home():
st.header("Welcome to AI Marketing Campaign Agent")
st.write("This tool helps you create, manage, and analyze your marketing campaigns using AI.")
st.write("Use the sidebar to navigate through different features.")
def show_campaign_creation():
st.header("Campaign Creation")
# Brand Questionnaire
st.subheader("Brand Questionnaire")
brand_name = st.text_input("Brand Name")
industry = st.selectbox("Industry", ["Technology", "Fashion", "Food & Beverage", "Other"])
target_audience = st.text_area("Describe your target audience")
campaign_objective = st.selectbox("Campaign Objective", ["Brand Awareness", "Lead Generation", "Sales", "Other"])
# Content Generation
st.subheader("Content Generation")
content_type = st.selectbox("Content Type", ["Social Media Post", "Ad Copy", "Email"])
content_prompt = st.text_area("Describe the content you want to generate")
if st.button("Generate Content"):
with st.spinner("Generating content..."):
generated_content = generate_marketing_content(content_prompt, f"{brand_name}, {industry}, {target_audience}, {campaign_objective}")
st.text_area("Generated Content", generated_content, height=200)
def show_strategy():
st.header("Marketing Strategy")
start_date = st.date_input("Campaign Start Date")
duration = st.number_input("Campaign Duration (days)", min_value=1, value=30)
if st.button("Generate Strategy"):
with st.spinner("Generating strategy..."):
strategy = generate_marketing_content("Generate a marketing strategy", f"Start Date: {start_date}, Duration: {duration} days")
st.subheader("Generated Marketing Strategy")
st.text(strategy)
if st.button("Generate PDF Proposal"):
st.write("PDF generation functionality to be implemented.")
def show_scheduling():
st.header("Content Scheduling")
platforms = st.multiselect("Select Platforms", ["Facebook", "Instagram", "Twitter"])
post_content = st.text_area("Post Content")
post_date = st.date_input("Post Date")
post_time = st.time_input("Post Time")
if st.button("Schedule Post"):
scheduled_datetime = datetime.combine(post_date, post_time)
for platform in platforms:
st.success(f"Post scheduled for {platform} at {scheduled_datetime}")
def show_analytics():
st.header("Campaign Analytics")
st.write("This feature is under development. It will show campaign performance metrics and insights.")
if __name__ == "__main__":
main()
|