Spaces:
Runtime error
Runtime error
peter szemraj
commited on
Commit
•
e770698
1
Parent(s):
5c43041
:construction: continue removing gramformer stuff
Browse files
app.py
CHANGED
@@ -12,8 +12,6 @@ import time
|
|
12 |
import warnings
|
13 |
from pathlib import Path
|
14 |
from cleantext import clean
|
15 |
-
from transformers import pipeline
|
16 |
-
from datetime import datetime
|
17 |
from ai_single_response import query_gpt_model
|
18 |
from utils import correct_phrase_load
|
19 |
|
@@ -24,30 +22,6 @@ cwd = Path.cwd()
|
|
24 |
my_cwd = str(cwd.resolve()) # string so it can be passed to os.path() objects
|
25 |
|
26 |
|
27 |
-
def gramformer_correct(corrector, qphrase: str):
|
28 |
-
"""
|
29 |
-
gramformer_correct - correct a string using a text2textgen pipeline model from transformers
|
30 |
-
|
31 |
-
Args:
|
32 |
-
corrector (transformers.pipeline): [transformers pipeline object, already created w/ relevant model]
|
33 |
-
qphrase (str): [text to be corrected]
|
34 |
-
|
35 |
-
Returns:
|
36 |
-
[str]: [corrected text]
|
37 |
-
"""
|
38 |
-
|
39 |
-
try:
|
40 |
-
corrected = corrector(
|
41 |
-
clean(qphrase), return_text=True, clean_up_tokenization_spaces=True
|
42 |
-
)
|
43 |
-
return corrected[0]["generated_text"]
|
44 |
-
except:
|
45 |
-
print("NOTE - failed to correct with gramformer")
|
46 |
-
return clean(
|
47 |
-
qphrase
|
48 |
-
) # fallback is to return the cleaned up version of the message
|
49 |
-
|
50 |
-
|
51 |
def ask_gpt(message: str):
|
52 |
"""
|
53 |
ask_gpt - queries the relevant model with a prompt message and returns the response.
|
@@ -107,7 +81,6 @@ if __name__ == "__main__":
|
|
107 |
default_model = "Ballpark-Trivia-L"
|
108 |
model_loc = cwd.parent / default_model
|
109 |
model_loc = str(model_loc.resolve())
|
110 |
-
gram_model = "prithivida/grammar_error_correcter_v1"
|
111 |
|
112 |
# init items for the pipeline
|
113 |
iface = gr.Interface(
|
@@ -115,8 +88,9 @@ if __name__ == "__main__":
|
|
115 |
inputs=["text"],
|
116 |
outputs="html",
|
117 |
title=f"Ballpark Trivia: {default_model} Model",
|
118 |
-
description=f"Are you frequently asked google-able Trivia questions and annoyed by it? Well, this is the app for you! Ballpark Trivia Bot answers any trivia question with something that sounds plausible but is probably not 100% correct. \n\n One might say.. the answers are in the right ballpark.
|
119 |
-
article="
|
|
|
120 |
"1. the model can take up to 60 seconds to respond sometimes, patience is a virtue.\n"
|
121 |
"2. the model started from a pretrained checkpoint, and was trained on several different datasets. Anything it says be fact-checked before being regarded as a true statement.\n ",
|
122 |
css="""
|
@@ -137,8 +111,6 @@ if __name__ == "__main__":
|
|
137 |
theme="darkhuggingface",
|
138 |
)
|
139 |
|
140 |
-
corrector = pipeline("text2text-generation", model=gram_model, device=-1)
|
141 |
-
print("Finished loading the gramformer model - ", datetime.now())
|
142 |
print(f"using model stored here: \n {model_loc} \n")
|
143 |
|
144 |
# launch the gradio interface and start the server
|
|
|
12 |
import warnings
|
13 |
from pathlib import Path
|
14 |
from cleantext import clean
|
|
|
|
|
15 |
from ai_single_response import query_gpt_model
|
16 |
from utils import correct_phrase_load
|
17 |
|
|
|
22 |
my_cwd = str(cwd.resolve()) # string so it can be passed to os.path() objects
|
23 |
|
24 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
25 |
def ask_gpt(message: str):
|
26 |
"""
|
27 |
ask_gpt - queries the relevant model with a prompt message and returns the response.
|
|
|
81 |
default_model = "Ballpark-Trivia-L"
|
82 |
model_loc = cwd.parent / default_model
|
83 |
model_loc = str(model_loc.resolve())
|
|
|
84 |
|
85 |
# init items for the pipeline
|
86 |
iface = gr.Interface(
|
|
|
88 |
inputs=["text"],
|
89 |
outputs="html",
|
90 |
title=f"Ballpark Trivia: {default_model} Model",
|
91 |
+
description=f"Are you frequently asked google-able Trivia questions and annoyed by it? Well, this is the app for you! Ballpark Trivia Bot answers any trivia question with something that sounds plausible but is probably not 100% correct. \n\n One might say.. the answers are in the right ballpark.",
|
92 |
+
article="Further details can be found in the[model card](https: // huggingface.co/pszemraj/Ballpark-Trivia-L), and there is also an XL-size model.\n\n"
|
93 |
+
"**Important Notes & About:**\n"
|
94 |
"1. the model can take up to 60 seconds to respond sometimes, patience is a virtue.\n"
|
95 |
"2. the model started from a pretrained checkpoint, and was trained on several different datasets. Anything it says be fact-checked before being regarded as a true statement.\n ",
|
96 |
css="""
|
|
|
111 |
theme="darkhuggingface",
|
112 |
)
|
113 |
|
|
|
|
|
114 |
print(f"using model stored here: \n {model_loc} \n")
|
115 |
|
116 |
# launch the gradio interface and start the server
|