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Added GPT4All Mistral

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mount
2024-02-07 22:41:14 +01:00
parent 716567c50b
commit 56ad3a50a1
4 changed files with 134 additions and 104 deletions
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reverie/backend_server/persona/prompt_template/gpt_structure.py
+119 -98
View File
@@ -1,123 +1,134 @@
"""
Author: Joon Sung Park (joonspk@stanford.edu)
Editor: Andreas Fruhwirt (afruhwirt@student.tugraz.at)
File: gpt_structure.py
Description: Wrapper functions for calling OpenAI APIs.
Description: Wrapper functions for executing GPT requests
"""
import json
import random
import openai
import time
from gpt4all import GPT4All, Embed4All
from utils import *
openai.api_key = openai_api_key
if use_openai:
openai.api_key = openai_api_key
else:
model = GPT4All("mistral-7b-instruct-v0.1.Q4_0.gguf", device="gpu", n_threads=4)
embedder = Embed4All()
def temp_sleep(seconds=0.1):
time.sleep(seconds)
def ChatGPT_single_request(prompt):
def GPT_single_request(prompt):
temp_sleep()
completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": prompt}]
)
return completion["choices"][0]["message"]["content"]
if use_openai:
completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": prompt}]
)
return completion["choices"][0]["message"]["content"]
else:
with model.chat_session():
response = model.generate(prompt)
return response
# ============================================================================
# #####################[SECTION 1: CHATGPT-3 STRUCTURE] ######################
# ============================================================================
def GPT4_request(prompt):
#def GPT4_request(prompt):
# """
# Given a prompt and a dictionary of GPT parameters, make a request to OpenAI
# server and returns the response.
# ARGS:
# prompt: a str prompt
# gpt_parameter: a python dictionary with the keys indicating the names of
# the parameter and the values indicating the parameter
# values.
# RETURNS:
# a str of GPT-3's response.
# """
# temp_sleep()
#
# try:
# completion = openai.ChatCompletion.create(
# model="gpt-4",
# messages=[{"role": "user", "content": prompt}]
# )
# return completion["choices"][0]["message"]["content"]
#
# except:
# print ("ChatGPT ERROR")
# return "ChatGPT ERROR"
def GPT_request(prompt):
"""
Given a prompt and a dictionary of GPT parameters, make a request to OpenAI
server and returns the response.
Given a prompt and a dictionary of GPT parameters, fetch the response of the LLM
ARGS:
prompt: a str prompt
gpt_parameter: a python dictionary with the keys indicating the names of
the parameter and the values indicating the parameter
values.
RETURNS:
a str of GPT-3's response.
"""
temp_sleep()
try:
completion = openai.ChatCompletion.create(
model="gpt-4",
messages=[{"role": "user", "content": prompt}]
)
return completion["choices"][0]["message"]["content"]
except:
print ("ChatGPT ERROR")
return "ChatGPT ERROR"
def ChatGPT_request(prompt):
"""
Given a prompt and a dictionary of GPT parameters, make a request to OpenAI
server and returns the response.
ARGS:
prompt: a str prompt
gpt_parameter: a python dictionary with the keys indicating the names of
the parameter and the values indicating the parameter
values.
RETURNS:
a str of GPT-3's response.
a str of the LLM's response.
"""
# temp_sleep()
try:
completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": prompt}]
)
return completion["choices"][0]["message"]["content"]
if use_openai:
completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": prompt}]
)
return completion["choices"][0]["message"]["content"]
else:
with model.chat_session():
response = model.generate(prompt)
return response
except:
print ("ChatGPT ERROR")
return "ChatGPT ERROR"
print ("GPT ERROR")
return "GPT ERROR"
def GPT4_safe_generate_response(prompt,
example_output,
special_instruction,
repeat=3,
fail_safe_response="error",
func_validate=None,
func_clean_up=None,
verbose=False):
prompt = 'GPT-3 Prompt:\n"""\n' + prompt + '\n"""\n'
prompt += f"Output the response to the prompt above in json. {special_instruction}\n"
prompt += "Example output json:\n"
prompt += '{"output": "' + str(example_output) + '"}'
if verbose:
print ("CHAT GPT PROMPT")
print (prompt)
for i in range(repeat):
try:
curr_gpt_response = GPT4_request(prompt).strip()
end_index = curr_gpt_response.rfind('}') + 1
curr_gpt_response = curr_gpt_response[:end_index]
curr_gpt_response = json.loads(curr_gpt_response)["output"]
if func_validate(curr_gpt_response, prompt=prompt):
return func_clean_up(curr_gpt_response, prompt=prompt)
if verbose:
print ("---- repeat count: \n", i, curr_gpt_response)
print (curr_gpt_response)
print ("~~~~")
except:
pass
return False
#def GPT4_safe_generate_response(prompt,
# example_output,
# special_instruction,
# repeat=3,
# fail_safe_response="error",
# func_validate=None,
# func_clean_up=None,
# verbose=False):
# prompt = 'GPT-3 Prompt:\n"""\n' + prompt + '\n"""\n'
# prompt += f"Output the response to the prompt above in json. {special_instruction}\n"
# prompt += "Example output json:\n"
# prompt += '{"output": "' + str(example_output) + '"}'
#
# if verbose:
# print ("CHAT GPT PROMPT")
# print (prompt)
#
# for i in range(repeat):
#
# try:
# curr_gpt_response = GPT4_request(prompt).strip()
# end_index = curr_gpt_response.rfind('}') + 1
# curr_gpt_response = curr_gpt_response[:end_index]
# curr_gpt_response = json.loads(curr_gpt_response)["output"]
#
# if func_validate(curr_gpt_response, prompt=prompt):
# return func_clean_up(curr_gpt_response, prompt=prompt)
#
# if verbose:
# print ("---- repeat count: \n", i, curr_gpt_response)
# print (curr_gpt_response)
# print ("~~~~")
#
# except:
# pass
#
# return False
def ChatGPT_safe_generate_response(prompt,
@@ -127,7 +138,7 @@ def ChatGPT_safe_generate_response(prompt,
fail_safe_response="error",
func_validate=None,
func_clean_up=None,
verbose=False):
verbose=True):
# prompt = 'GPT-3 Prompt:\n"""\n' + prompt + '\n"""\n'
prompt = '"""\n' + prompt + '\n"""\n'
prompt += f"Output the response to the prompt above in json. {special_instruction}\n"
@@ -141,7 +152,7 @@ def ChatGPT_safe_generate_response(prompt,
for i in range(repeat):
try:
curr_gpt_response = ChatGPT_request(prompt).strip()
curr_gpt_response = GPT_request(prompt).strip()
end_index = curr_gpt_response.rfind('}') + 1
curr_gpt_response = curr_gpt_response[:end_index]
curr_gpt_response = json.loads(curr_gpt_response)["output"]
@@ -169,14 +180,14 @@ def ChatGPT_safe_generate_response_OLD(prompt,
fail_safe_response="error",
func_validate=None,
func_clean_up=None,
verbose=False):
verbose=True):
if verbose:
print ("CHAT GPT PROMPT")
print (prompt)
for i in range(repeat):
try:
curr_gpt_response = ChatGPT_request(prompt).strip()
curr_gpt_response = GPT_request(prompt).strip()
if func_validate(curr_gpt_response, prompt=prompt):
return func_clean_up(curr_gpt_response, prompt=prompt)
if verbose:
@@ -207,7 +218,7 @@ def GPT_request(prompt, gpt_parameter):
a str of GPT-3's response.
"""
temp_sleep()
try:
if use_openai:
response = openai.Completion.create(
model=gpt_parameter["engine"],
prompt=prompt,
@@ -219,10 +230,17 @@ def GPT_request(prompt, gpt_parameter):
stream=gpt_parameter["stream"],
stop=gpt_parameter["stop"],)
return response.choices[0].text
except:
print ("TOKEN LIMIT EXCEEDED")
return "TOKEN LIMIT EXCEEDED"
else:
def callback(token_id, response):
if gpt_parameter["stop"] is None:
return True
for param in gpt_parameter["stop"]:
if param in response:
return False
return True
response = model.generate(prompt, max_tokens=gpt_parameter["max_tokens"], temp=gpt_parameter["temperature"], top_p=gpt_parameter["top_p"],
streaming=gpt_parameter["stream"], callback=callback)
return response
def generate_prompt(curr_input, prompt_lib_file):
"""
@@ -258,7 +276,7 @@ def safe_generate_response(prompt,
fail_safe_response="error",
func_validate=None,
func_clean_up=None,
verbose=False):
verbose=True):
if verbose:
print (prompt)
@@ -277,8 +295,11 @@ def get_embedding(text, model="text-embedding-ada-002"):
text = text.replace("\n", " ")
if not text:
text = "this is blank"
return openai.Embedding.create(
input=[text], model=model)['data'][0]['embedding']
if use_openai:
return openai.Embedding.create(
input=[text], model=model)['data'][0]['embedding']
else:
return embedder.embed(text)
if __name__ == '__main__':