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# 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(): | |
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 | |
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 | |