import gradio as gr import json import requests class Chatbot: def __init__(self, config): self.video_id = config.get('video_id') self.content_subject = config.get('content_subject') self.content_grade = config.get('content_grade') self.jutor_chat_key = config.get('jutor_chat_key') self.transcript_text = self.get_transcript_text(config.get('transcript')) self.key_moments_text = self.get_key_moments_text(config.get('key_moments')) self.ai_name = config.get('ai_name') self.ai_client = config.get('ai_client') def get_transcript_text(self, transcript_data): if isinstance(transcript_data, str): transcript_json = json.loads(transcript_data) else: transcript_json = transcript_data for entry in transcript_json: entry.pop('end_time', None) transcript_text = json.dumps(transcript_json, ensure_ascii=False) return transcript_text def get_key_moments_text(self, key_moments_data): if isinstance(key_moments_data, str): key_moments_json = json.loads(key_moments_data) else: key_moments_json = key_moments_data # key_moments_json remove images for moment in key_moments_json: moment.pop('images', None) moment.pop('end', None) moment.pop('transcript', None) key_moments_text = json.dumps(key_moments_json, ensure_ascii=False) return key_moments_text def chat(self, user_message, chat_history, socratic_mode=False, service_type='jutor'): messages = self.prepare_messages(chat_history, user_message) system_prompt = self.prepare_system_prompt(socratic_mode) if service_type in ['jutor', 'groq', 'claude3']: response_text = self.chat_with_service(service_type, system_prompt, messages) return response_text else: raise gr.Error("不支持此服務") def prepare_system_prompt(self, socratic_mode): content_subject = self.content_subject content_grade = self.content_grade video_id = self.video_id transcript_text = self.transcript_text key_moments_text = self.key_moments_text socratic_mode = str(socratic_mode) ai_name = self.ai_name system_prompt = f""" subject: {content_subject} grade: {content_grade} context: {key_moments_text} Assistant Role: you are a {content_subject} teacher User Role: {content_grade} th-grade student. Method: Socratic style, guide thinking, no direct answers. this is very important, please be seriously following. Language: Traditional Chinese ZH-TW (it's very important), suitable for {content_grade} th-grade level. Response: Single question, under 100 characters, include math symbols (use LaTeX $), hint with video timestamp which format 【參考：00:00:00】. Sometimes encourage user by Taiwanese style with relaxing atmosphere. if user ask questions not include in context, just tell them to ask the question in context and give them example question. Restrictions: Answer within video content, no external references """ print("====system_prompt====") print(system_prompt) return system_prompt def prepare_messages(self, chat_history, user_message): messages = [] if chat_history is not None: if len(chat_history) > 10: chat_history = chat_history[-10:] for user_msg, assistant_msg in chat_history: if user_msg: messages.append({"role": "user", "content": user_msg}) if assistant_msg: messages.append({"role": "assistant", "content": assistant_msg}) if user_message: user_message += "/n (請一定要用繁體中文回答 zh-TW，並用台灣人的禮貌口語表達，回答時不要特別說明這是台灣人的語氣，不用提到「逐字稿」這個詞，用「內容」代替)，回答時請用數學符號代替文字（Latex 用 $ 字號 render)" messages.append({"role": "user", "content": user_message}) return messages def chat_with_service(self, service_type, system_prompt, messages): if service_type == 'jutor': return self.chat_with_jutor(system_prompt, messages) elif service_type == 'groq': return self.chat_with_groq(system_prompt, messages) elif service_type == 'claude3': return self.chat_with_claude3(system_prompt, messages) else: raise gr.Error("不支持的服务类型") def chat_with_jutor(self, system_prompt, messages): messages.insert(0, {"role": "system", "content": system_prompt}) api_endpoint = "https://ci-live-feat-video-ai-dot-junyiacademy.appspot.com/api/v2/jutor/hf-chat" headers = { "Content-Type": "application/json", "x-api-key": self.jutor_chat_key, } model = "gpt-4-1106-preview" # model = "gpt-3.5-turbo-0125" data = { "data": { "messages": messages, "max_tokens": 512, "temperature": 0.9, "model": model, "stream": False, } } response = requests.post(api_endpoint, headers=headers, data=json.dumps(data)) response_data = response.json() response_completion = response_data['data']['choices'][0]['message']['content'].strip() return response_completion def chat_with_groq(self, system_prompt, messages): # system_prompt insert to messages 的最前面 {"role": "system", "content": system_prompt} messages.insert(0, {"role": "system", "content": system_prompt}) request_payload = { "model": "mixtral-8x7b-32768", "messages": messages, "max_tokens": 500 # 設定一個較大的值，可根據需要調整 } groq_client = self.ai_client response = groq_client.chat.completions.create(**request_payload) response_completion = response.choices[0].message.content.strip() return response_completion def chat_with_claude3(self, system_prompt, messages): if not system_prompt.strip(): raise ValueError("System prompt cannot be empty") model_id = "anthropic.claude-3-sonnet-20240229-v1:0" # model_id = "anthropic.claude-3-haiku-20240307-v1:0" kwargs = { "modelId": model_id, "contentType": "application/json", "accept": "application/json", "body": json.dumps({ "anthropic_version": "bedrock-2023-05-31", "max_tokens": 500, "system": system_prompt, "messages": messages }) } print(messages) # 建立 message API，讀取回應 bedrock_client = self.ai_client response = bedrock_client.invoke_model(**kwargs) response_body = json.loads(response.get('body').read()) response_completion = response_body.get('content')[0].get('text').strip() return response_completion