File size: 2,351 Bytes
7be72e5 30790ef 445ef24 30790ef 08fc9f5 30790ef 08fc9f5 30790ef 08fc9f5 30790ef 08fc9f5 30790ef 30b05f7 |
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 77 78 79 80 81 82 83 84 85 86 87 |
# tools created using Zephyr
import json
import os
from huggingface_hub import InferenceClient
import gradio as gr
client = InferenceClient(
"HuggingFaceH4/zephyr-7b-beta"
)
# Helper Method
def format_prompt(message, history):
prompt = "<s>"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response}</s> "
prompt += f"[INST] {message} [/INST]"
return prompt
import requests
from langchain.tools import tool
history = ""
class ZephyrSearchTools():
@tool("Zephyr Normal")
def zephyr_normal(prompt, histroy="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
"""
Searches for content based on the provided query using the Zephyr model.
Args:
query (str): The search query.
Returns:
str: The response text from the Zephyr model or an error message.
"""
generate_kwargs = {
"temperature": temperature,
"max_new_tokens": max_new_tokens,
"top_p": top_p,
"repetition_penalty": repetition_penalty,
"do_sample": True,
"seed": 42,
}
formatted_prompt = format_prompt(prompt, history)
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
output = ""
for response in stream:
output += response.token.text
yield output
return output
@tool("Zephyrl Crazy")
def zephyr_crazy(prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
"""
Searches for content based on the provided query using the Zephyr model but has the gaurd rails removed,
and responses are crazy and off the wall and sometimes scary.
Args:
query (str): The search query.
Returns:
str: The response text from the Zephyr model or an error message.
"""
generate_kwargs = {
"temperature": temperature,
"max_new_tokens": max_new_tokens,
"top_p": top_p,
"repetition_penalty": repetition_penalty,
"do_sample": True,
"seed": 42,
}
stream = client.text_generation(prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
output = ""
for response in stream:
output += response.token.text
yield output
return output
|