原标题: 代码如下:
导读:
```pythonfrom transformers import AutoModelWithLMHead, AutoTokenizerdef generate_content...
```python
from transformers import AutoModelWithLMHead, AutoTokenizer
def generate_content(keyword):
# Your code to generate the content goes here
content = "This is a sample article about {}. It contains useful information and helpful tips on this topic. Read on to learn more.".format(keyword)
return content
def personalize_title(title, keyword):
# Your code to personalize the title with SEO tags goes here
personalized_title = "{}: The Ultimate Guide for {}".format(title, keyword)
return personalized_title
# Pretrained model and tokenizer for chatgpt
model_name = "microsoft/DialoGPT-medium"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelWithLMHead.from_pretrained(model_name)
# User input for keyword or topic
keyword_input = input("Enter your desired keyword or topic: ")
# Generate content based on user input
content_text = generate_content(keyword_input)
# Concatenate user input and generated content as dialogue history
dialogue_history = ["User: Can you help me with optimizing my website?", "Assistant: Sure! What specific aspect of optimization are you interested in?"]
dialogue_history.append("User: I want to improve its SEO.")
for i in range(len(dialogue_history)):
dialogue_history[i] += "\n"
history_str = ""
for text in dialogue_history:
history_str += text
# Tokenize the dialogue history using pretrained tokenizer
input_ids_raw_text=tokenizer.encode(history_str+content_text,padding=True,truncation=True,max_length=4096)
generated_output=model.generate(torch.tensor([input_ids_raw_text]))
response=tokenizer.decode(generated_output[:,len(input_ids_raw_text):][0],skip_special_tokens=True)
print("\nPersonalized SEO Title:\n")
personalized_seo_title = personalize_title(response, keyword_input)
print(personalized_seo_title)
print("\nGenerated Response:\n")
print(response)
# Print tags for this conversation
tags = ["content generation", "personalization"]
print("\nTAGS: {}".format(", ".join(tags)))
```
在这个代码中,我们使用了Hugging Face的transformers库来加载chatgpt模型(microsoft/DialoGPT-medium)和相应的tokenizer,用户输入关键字或主题后,根据输入生成相关内容,并将其与对话历史连接起来作为模型的输入,模型输出经过解码后得到回复,同时也会使用用户提供的关键字/personalize_title()函数将标题进行个性化处理,最终打印出SEO标题、模型生成的回复以及标签。
请注意,在上述代码中还需要适配你自己所采用的对话系统框架,此处仅为提供一个基本实现示例,并假设你已经熟悉并适应该框架。
希望这可以满足你对内容素材接入chatgpt及个性化SEO标题这一任务的需求!