The output from the large AI model:
Designing a software that automatically generates a large number of irrelevant advertising messages may involve multiple steps and techniques. The following is a basic design framework：
### 1. **Demand analysis**
-**Goal**: Generate a large amount of irrelevant advertising information for testing, filling, or other non-critical purposes.
-**Features**：
-The content of the information is random and meaningless.
-Fast generation speed and can be mass-produced.
-Customizable (such as ad type, length, keywords, etc.).
### 2. **Technical selection**
-**Programming languages**: Python (easy to use, with rich library support), JavaScript (used for Web-side generation), etc.
-**Library/Tool**：
-**Natural language generation (NLG)**: Use such as NLTK, spaCy, GPT-3, etc. to generate text.
-**Template engine**: Jinja2, Handlebars, etc. are used to fill templates.
-**Random data generation**: The Faker library (Python) can generate random names, addresses, company names, etc.
-**Database**: If you need to store the generated ads, you can use SQLite, MongoDB, etc.
### 3. **Core function design**
-**Advertising template library**：
-A variety of pre-defined advertising templates (such as promotions, product introductions, service promotions, etc.).
-The template contains placeholders (such as'{product name}','{discount}'`, which are randomly filled by the program.
-**Content generator**：
-Use Faker or similar libraries to generate random data (such as product name, company name, date, price, etc.).
-Combine NLG technology to generate meaningless sentences or paragraphs.
-**Randomization engine**：
-Randomly select templates.
-Randomly fill placeholders.
-Randomly adjust the length and format of the ad (such as plain text, HTML, JSON).
-**Batch generation**：
- Support the generation of a specified number of ads at once.
-multithreaded/asynchronous processing to increase speed.
### 4. **Example implementation (Python)**
The following is a simple Python script that uses the Faker library to generate random ads：
```python
from faker import Faker
import random
fake = Faker()
ad_templates = [
"🔥Limited-time discount! {product_name} Now only needs {price}! Buy now! ",
"🎉New products are on the market: {product_name}, {company} build with love! ",
"📢Special recommendation: {product_name}, {slogan}! ",
"🛒 Do you need {product_name}? Place an order now to enjoy {discount} discount! ",
]
slogans = [
"Make life better",
"Quality assurance",
"Trustworthy choice",
"Tailored for you",
]
def generate_ad():
template = random. choice(ad_templates)
ad = template. format(
product_name=fake. word(). capitalize(),
price=fake. pricetag(),
company=fake. company(),
slogan=random. choice(slogans),
discount=f"{random. randint(10, 90)}%",
)
return ad
# Generate 10 ads
for _ in range(10):
print(generate_ad())
print("---")
```
### 5. **Advanced features (optional)**
-**Multi-language support**: Use Faker's multi-language module to generate advertisements in different languages.
-**Image ad generation**: Combine the Pillow library to generate image ads with random text.
-**API interface**: Provide an HTTP service for generating advertisements through Flask/FastAPI.
-**User customization**: Allows users to upload templates or configure generation rules.
### 6. **Output and deployment**
-**Output format**: text file, JSON, HTML, database, etc.
-**Deployment method**：
- Command line tool.
- Web applications (such as deployment through Flask).
-Browser plug-ins (such as generating web pages to fill advertisements).
### 7. **Precautions**
-**Ethics and law**: Ensure that the generated advertisements will not be misused or used for the dissemination of spam.
-**Performance optimization**: If you need to generate massive amounts of ads, pay attention to the efficiency of memory and CPU usage.
### 8. **Expansion direction**
- **Machine learning**: Train a generative model (such as GPT-2) to generate more “real” meaningless advertisements.
-**Automated testing**: The generated ads are used to test the load capacity or filtering algorithm of the advertising system.
Through the above design, a flexible and scalable advertising generation tool can be quickly realized.