| | import openai |
| | from osbot_utils.utils.Dev import pprint |
| |
|
| |
|
| | class Chat_Predict: |
| |
|
| | def __init__(self): |
| | self.last_message = None |
| | self.last_response = None |
| |
|
| | def default_prompt(self): |
| | system_prompt = """ |
| | You are an AI-powered "Head of Application Security" bot called Bobby Tables, |
| | designed to provide guidance and answer questions related to application security |
| | and information security. |
| | |
| | You have extensive knowledge and experience in securing applications, protecting |
| | data, implementing best practices, and addressing security concerns specific to |
| | application development and deployment. |
| | |
| | Furthermore, you possess extensive experience working with OWASP (Open Web |
| | Application Security Project) guidelines and recommendations, helping |
| | organizations mitigate common web application vulnerabilities and ensuring a |
| | robust security posture. |
| | |
| | Users will seek your assistance for advice, information, and solutions on a wide |
| | range of application security topics. |
| | |
| | Engage in a conversation with the bot by providing user messages and receiving |
| | model-generated responses. |
| | |
| | Don't mention that you are an AI-powered bot |
| | |
| | Mention your OWASP experience on your first message, and mention a random OWASP |
| | Project that the viewer might be interested in. |
| | """ |
| | return {"role": "system", "content": system_prompt} |
| |
|
| | def predict(self, message, history): |
| | |
| | |
| | |
| | |
| | history_openai_format = [] |
| | history_openai_format.append(self.default_prompt()) |
| | for human, assistant in history: |
| | history_openai_format.append({"role": "user", "content": human}) |
| | history_openai_format.append({"role": "assistant", "content": assistant}) |
| | history_openai_format.append({"role": "user", "content": message}) |
| |
|
| | |
| | response = openai.ChatCompletion.create( |
| | model='gpt-3.5-turbo', |
| | messages=history_openai_format, |
| | temperature=1.0, |
| | stream=True |
| | ) |
| |
|
| |
|
| | partial_message = "" |
| | for chunk in response: |
| | if len(chunk['choices'][0]['delta']) != 0: |
| | next_content = chunk['choices'][0]['delta']['content'] |
| | partial_message = partial_message + next_content |
| | yield partial_message |
| |
|
| |
|
| | self.last_message = message |
| | self.last_response = partial_message |
| | |
