Spaces:
Running
Running
Commit
Β·
dce9e22
1
Parent(s):
122f288
update inference logic
Browse files
app.py
CHANGED
@@ -6,30 +6,57 @@ import glob
|
|
6 |
import os
|
7 |
import uuid
|
8 |
from pathlib import Path
|
9 |
-
import
|
10 |
-
import
|
11 |
-
import
|
12 |
from huggingface_hub import CommitScheduler, hf_hub_download, login
|
13 |
-
from transformers import AutoTokenizer, AutoModelForCausalLM
|
14 |
-
from outlines import models, generate
|
15 |
-
from gradio import update
|
16 |
|
17 |
-
|
18 |
-
|
19 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
20 |
|
21 |
-
@spaces.GPU(duration=120)
|
22 |
-
def generate_blurb(history):
|
23 |
-
model = models.transformers(model_id)
|
24 |
-
generator = generate.text(model)
|
25 |
-
resp = generator("Write a blurb for a book")
|
26 |
-
return resp
|
27 |
|
28 |
# Function to log blurb and vote
|
29 |
def log_blurb_and_vote(blurb, vote):
|
30 |
log_entry = {"timestamp": datetime.now().isoformat(), "blurb": blurb, "vote": vote}
|
31 |
with open("blurb_log.jsonl", "a") as f:
|
32 |
f.write(json.dumps(log_entry) + "\n")
|
|
|
33 |
return f"Logged: {vote}"
|
34 |
|
35 |
|
@@ -38,19 +65,28 @@ tufte_theme = TufteInspired()
|
|
38 |
|
39 |
# Create Gradio interface
|
40 |
with gr.Blocks(theme=tufte_theme) as demo:
|
41 |
-
gr.Markdown("<h1 style='text-align: center;'>Would you read
|
42 |
gr.Markdown(
|
43 |
-
"
|
|
|
|
|
44 |
)
|
|
|
|
|
45 |
with gr.Row():
|
46 |
-
generate_btn = gr.Button("
|
47 |
-
blurb_output = gr.
|
48 |
-
with gr.Row():
|
49 |
upvote_btn = gr.Button("π would read")
|
50 |
downvote_btn = gr.Button("π wouldn't read")
|
51 |
-
vote_output = gr.Textbox(label="Vote Status", interactive=False)
|
|
|
|
|
|
|
52 |
|
53 |
-
generate_btn.click(generate_blurb, outputs=blurb_output)
|
|
|
|
|
54 |
upvote_btn.click(
|
55 |
lambda x: log_blurb_and_vote(x, "upvote"),
|
56 |
inputs=blurb_output,
|
@@ -62,5 +98,6 @@ with gr.Blocks(theme=tufte_theme) as demo:
|
|
62 |
outputs=vote_output,
|
63 |
)
|
64 |
|
|
|
65 |
if __name__ == "__main__":
|
66 |
demo.launch()
|
|
|
6 |
import os
|
7 |
import uuid
|
8 |
from pathlib import Path
|
9 |
+
from huggingface_hub import InferenceClient
|
10 |
+
from openai import OpenAI
|
11 |
+
from huggingface_hub import get_token
|
12 |
from huggingface_hub import CommitScheduler, hf_hub_download, login
|
|
|
|
|
|
|
13 |
|
14 |
+
from prompts import detailed_genre_description_prompt, basic_prompt
|
15 |
+
import random
|
16 |
|
17 |
+
# TODOs
|
18 |
+
# 1. Add a login button
|
19 |
+
# 2. Prompt library expand
|
20 |
+
# 3. log user if logged in
|
21 |
+
|
22 |
+
|
23 |
+
client = OpenAI(
|
24 |
+
base_url="https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct/v1",
|
25 |
+
api_key=get_token(),
|
26 |
+
)
|
27 |
+
|
28 |
+
|
29 |
+
def generate_prompt():
|
30 |
+
if random.choice([True, False]):
|
31 |
+
return detailed_genre_description_prompt()
|
32 |
+
else:
|
33 |
+
return basic_prompt()
|
34 |
+
|
35 |
+
|
36 |
+
def generate_blurb():
|
37 |
+
max_tokens = random.randint(100, 1000)
|
38 |
+
prompt = generate_prompt()
|
39 |
+
print(prompt)
|
40 |
+
chat_completion = client.chat.completions.create(
|
41 |
+
model="tgi",
|
42 |
+
messages=[
|
43 |
+
{"role": "user", "content": prompt},
|
44 |
+
],
|
45 |
+
stream=True,
|
46 |
+
max_tokens=max_tokens,
|
47 |
+
)
|
48 |
+
full_text = ""
|
49 |
+
for message in chat_completion:
|
50 |
+
full_text += message.choices[0].delta.content
|
51 |
+
yield full_text
|
52 |
|
|
|
|
|
|
|
|
|
|
|
|
|
53 |
|
54 |
# Function to log blurb and vote
|
55 |
def log_blurb_and_vote(blurb, vote):
|
56 |
log_entry = {"timestamp": datetime.now().isoformat(), "blurb": blurb, "vote": vote}
|
57 |
with open("blurb_log.jsonl", "a") as f:
|
58 |
f.write(json.dumps(log_entry) + "\n")
|
59 |
+
gr.Info("Thank you for voting!")
|
60 |
return f"Logged: {vote}"
|
61 |
|
62 |
|
|
|
65 |
|
66 |
# Create Gradio interface
|
67 |
with gr.Blocks(theme=tufte_theme) as demo:
|
68 |
+
gr.Markdown("<h1 style='text-align: center;'>Would you read this book?</h1>")
|
69 |
gr.Markdown(
|
70 |
+
"""<p style='text-align: center;'>Looking for your next summer read?
|
71 |
+
Would you read a book based on this LLM generated blurb? <br> Your vote will be added to <a href="https://example.com">this</a> Hugging Face dataset</p>"""
|
72 |
+
+ """"""
|
73 |
)
|
74 |
+
# gr.LoginButton(size="sm")
|
75 |
+
user_name = gr.Textbox(label="User Name", placeholder="Enter your name")
|
76 |
with gr.Row():
|
77 |
+
generate_btn = gr.Button("Create a book", variant="primary")
|
78 |
+
blurb_output = gr.Markdown(label="Book blurb")
|
79 |
+
with gr.Row(visible=False) as voting_row:
|
80 |
upvote_btn = gr.Button("π would read")
|
81 |
downvote_btn = gr.Button("π wouldn't read")
|
82 |
+
vote_output = gr.Textbox(label="Vote Status", interactive=False, visible=False)
|
83 |
+
|
84 |
+
def show_voting_buttons(blurb):
|
85 |
+
return blurb, gr.Row(visible=True)
|
86 |
|
87 |
+
generate_btn.click(generate_blurb, outputs=blurb_output).then(
|
88 |
+
show_voting_buttons, inputs=blurb_output, outputs=[blurb_output, voting_row]
|
89 |
+
)
|
90 |
upvote_btn.click(
|
91 |
lambda x: log_blurb_and_vote(x, "upvote"),
|
92 |
inputs=blurb_output,
|
|
|
98 |
outputs=vote_output,
|
99 |
)
|
100 |
|
101 |
+
|
102 |
if __name__ == "__main__":
|
103 |
demo.launch()
|