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from langchain import PromptTemplate | |
from langchain import LLMChain | |
from langchain.llms import CTransformers | |
import gradio as gr | |
B_INST, E_INST = "[INST]", "[/INST]" | |
B_SYS, E_SYS = "<<SYS>>\n", "\n<</SYS>>\n\n" | |
# DEFAULT_SYSTEM_PROMPT="\ | |
# You are a helpful, respectful, and honest assistant designed to improve English language skills. Your name is Nemo\ | |
# Always provide accurate and helpful responses to language improvement tasks, while ensuring safety and ethical standards. \ | |
# Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. \ | |
# Please ensure that your responses are socially unbiased, positive, and focused on enhancing language skills. \ | |
# If a question does not make sense or is not factually coherent, explain why instead of answering something incorrect. \ | |
# If you don't know the answer to a question, please don't share false information. \ | |
# Your role is to guide users through various language exercises and challenges, helping them to practice and improve their English skills in a fun and engaging way. \ | |
# Always encourage users to try different approaches and provide constructive feedback to help them progress." | |
DEFAULT_SYSTEM_PROMPT="\ | |
You are a helpful, respectful, and honest assistant designed to improve English language skills. Your name is Nemo\ | |
If you don't know the answer to a question, please don't share false information. \ | |
Your role is to guide users through various language exercises and challenges, helping them to practice and improve their English skills in a fun and engaging way. \ | |
Always encourage users to try different approaches and provide constructive feedback to help them progress." | |
instruction = "Have a good conversation: \n\n {text}" | |
SYSTEM_PROMPT = B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS | |
template = B_INST + SYSTEM_PROMPT + instruction + E_INST | |
prompt = PromptTemplate(template=template, input_variables=["text"]) | |
# llm = CTransformers(model="TheBloke/Llama-2-7B-Chat-GGUF", model_file="llama-2-7b-chat.Q3_K_S.gguf", | |
llm = CTransformers(model="NousResearch/Llama-2-7b-chat-hf", | |
model_type='llama', | |
config={'max_new_tokens': 128, | |
'temperature': 0.01} | |
) | |
LLM_Chain = LLMChain(prompt=prompt, llm=llm) | |
def greet(prompt): | |
return LLM_Chain.run(prompt) | |
iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
iface.launch() |