| import datetime | |
| from chat_anything.chatbot.personality import generate_personality_prompt | |
| from langchain.prompts import PromptTemplate | |
| from langchain import ConversationChain | |
| from langchain.chains.conversation.memory import ConversationBufferMemory | |
| from langchain.chat_models import ChatOpenAI | |
| from langchain.embeddings.openai import OpenAIEmbeddings | |
| import os | |
| import random | |
| import string | |
| def load_chain(llm, class_concept=None): | |
| chain = None | |
| memory = None | |
| personality_text = None | |
| print(llm) | |
| if llm: | |
| print("class_concept", class_concept) | |
| if class_concept is None: | |
| class_concept = 'AI assistant' | |
| person_template, personality_text = generate_personality_prompt(llm, class_concept) | |
| PROMPT_TEMPLATE = PromptTemplate( | |
| input_variables=["history", "input"], | |
| template=person_template, | |
| ) | |
| chain = ConversationChain( | |
| prompt=PROMPT_TEMPLATE, | |
| llm=llm, | |
| verbose=False, | |
| memory=ConversationBufferMemory(ai_prefix="You"), | |
| ) | |
| print("New concept done for ", class_concept) | |
| return chain, memory, personality_text | |
| def set_openai_api_key(api_key, use_gpt4, history=None, max_tokens=1024, use_local_llm=True): | |
| """Set the api key and return chain. | |
| If no api_key, then None is returned. | |
| """ | |
| if (api_key and api_key.startswith("sk-") and len(api_key) > 50): | |
| os.environ["OPENAI_API_KEY"] = api_key | |
| print("\n\n ++++++++++++++ Setting OpenAI API key ++++++++++++++ \n\n") | |
| print(str(datetime.datetime.now()) + ": Before OpenAI, OPENAI_API_KEY length: " + str( | |
| len(os.environ["OPENAI_API_KEY"]))) | |
| if use_gpt4: | |
| llm = ChatOpenAI( | |
| temperature=0, max_tokens=max_tokens, model_name="gpt-4") | |
| print("Trying to use llm ChatOpenAI with gpt-4") | |
| else: | |
| print("Trying to use llm ChatOpenAI with gpt-3.5-turbo") | |
| llm = ChatOpenAI(temperature=0, max_tokens=max_tokens, | |
| model_name="gpt-3.5-turbo") | |
| print(str(datetime.datetime.now()) + ": After OpenAI, OPENAI_API_KEY length: " + str( | |
| len(os.environ["OPENAI_API_KEY"]))) | |
| print(str(datetime.datetime.now()) + ": After load_chain, OPENAI_API_KEY length: " + str( | |
| len(os.environ["OPENAI_API_KEY"]))) | |
| os.environ["OPENAI_API_KEY"] = "" | |
| history = history or [] | |
| history.append(['', '[SYSTEM] OPENAI_API_KEY has been set, you can generate your object and talk to it now!']) | |
| uid = ''.join(random.sample(string.ascii_lowercase + string.ascii_uppercase, 5)) | |
| video_file_path = os.path.join('tmp', uid, 'videos/tempfile.mp4') | |
| audio_file_path = os.path.join('tmp', uid, 'audio/tempfile.mp3') | |
| return llm, use_gpt4, history, uid, video_file_path, audio_file_path | |
| elif use_local_llm: | |
| os.environ["OPENAI_API_KEY"] = 'EMPTY' | |
| print("\n\n ++++++++++++++ Using local LLM ++++++++++++++ \n\n") | |
| llm = ChatOpenAI(temperature=0, max_tokens=max_tokens, | |
| model_name="gpt-3.5-turbo") | |
| history = history or [] | |
| history.append(['', '[SYSTEM] You are using free local LLM, you can generate your object and talk to it now!']) | |
| uid = ''.join(random.sample(string.ascii_lowercase + string.ascii_uppercase, 5)) | |
| video_file_path = os.path.join('tmp', uid, 'videos/tempfile.mp4') | |
| audio_file_path = os.path.join('tmp', uid, 'audio/tempfile.mp3') | |
| return llm, use_gpt4, history, uid, video_file_path, audio_file_path | |
| return None, None, None, None, None, None |