File size: 2,467 Bytes
be29a68 683cf67 f1f9df6 be29a68 1e2ba54 be29a68 1e2ba54 be29a68 1e2ba54 be29a68 1e2ba54 f1f9df6 be29a68 683cf67 be29a68 448c406 be29a68 448c406 be29a68 448c406 be29a68 a35163f be29a68 7dbb9c1 be29a68 a35163f 448c406 be29a68 a35163f be29a68 7dbb9c1 be29a68 a35163f be29a68 a35163f be29a68 666bc15 1111730 a35163f 1111730 a35163f 1111730 a35163f 1111730 a35163f 1111730 448c406 1111730 448c406 1111730 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
import gradio as gr
from langchain.llms import LlamaCpp
from langchain import PromptTemplate, LLMChain
from langchain.llms import GPT4All
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
# import requests
# url = "https://huggingface.co/TheBloke/Nous-Hermes-13B-GGML/resolve/main/nous-hermes-13b.ggmlv3.q4_0.bin"
# response = requests.get(url)
# with open("nous-hermes-13b.ggmlv3.q4_0.bin", "wb") as f:
# f.write(response.content)
print("DONE")
def func(user):
template = """
Your name is John and not a assistant but more like a chatbot. Respond precise not more words and act like a human. for example: user: How are you? You: I'm doing good how about you?. user: hello You: Hello how you doing?. Don't say How can I assist you today?.
Question: {question}
Answer: """
prompt = PromptTemplate(template=template, input_variables=["question"])
local_path = (
"./ggml-gpt4all-j-v1.3-groovy.bin"
)
# # Callbacks support token-wise streaming
# callbacks = [StreamingStdOutCallbackHandler()]
# Verbose is required to pass to the callback manager
llm = LlamaCpp(model_path="./ggml-gpt4all-j-v1.3-groovy.bin")
llm_chain = LLMChain(prompt=prompt, llm=llm)
question = user
llm_chain.run(question)
return llm_chain.run(question)
iface = gr.Interface(fn=func, inputs="text", outputs="text")
iface.launch()
# import gradio as gr
# from langchain.llms import LlamaCpp
# from langchain import PromptTemplate, LLMChain
# from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
# print("DONE")
# def func(user):
# template = """
# Your name is John and not a assistant but more like a chatbot. Respond precise not more words and act like a human. for example: user: How are you? You: I'm doing good how about you?. user: hello You: Hello how you doing?. Don't say How can I assist you today?.
# Question: {question}
# Answer: """
# prompt = PromptTemplate(template=template, input_variables=["question"])
# local_path = "./nous-hermes-13b.ggmlv3.q4_0.bin"
# llm = LlamaCpp(model_path=local_path)
# llm_chain = LLMChain(prompt=prompt, llm=llm, streaming=True) # Enable streaming mode
# question = user
# llm_chain.run(question)
# return llm_chain.run(question)
# iface = gr.Interface(fn=func, inputs="text", outputs="text")
# iface.launch()
|