File size: 13,574 Bytes
e23ea2d
 
 
 
 
56ece3e
4e5f073
e23ea2d
c16d4f4
e23ea2d
 
689b856
e23ea2d
 
 
239a985
e23ea2d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
239a985
557118e
e0ab507
 
 
 
323ae96
 
 
 
 
e23ea2d
 
540d71c
a102b86
557118e
e23ea2d
323ae96
c285801
323ae96
 
e23ea2d
540d71c
a102b86
557118e
323ae96
e0ab507
 
 
 
 
 
a102b86
557118e
35996b9
 
 
 
 
 
 
 
a102b86
557118e
e23ea2d
 
76f56f9
56ece3e
e23ea2d
56ece3e
ab1b1e7
 
 
 
 
 
 
56ece3e
 
1d8f5b2
70358c4
 
 
e23ea2d
70358c4
 
83e252e
56ece3e
 
70358c4
 
1d8f5b2
c285801
f387b9b
 
 
 
b8afcbf
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c285801
e23ea2d
 
0cde323
0b8e27d
 
40faa53
 
 
0b8e27d
 
40faa53
 
0b8e27d
40faa53
0b8e27d
40faa53
 
 
 
 
 
 
 
0b8e27d
844109c
 
 
 
40faa53
 
 
 
 
844109c
 
 
0b8e27d
0bf7dd6
e23ea2d
 
 
 
 
 
 
 
 
 
 
0ba7762
 
 
 
 
 
 
 
 
 
 
 
 
e23ea2d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9ebf7b6
e23ea2d
 
9ebf7b6
e23ea2d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4194468
e23ea2d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
239a985
 
 
 
 
 
e23ea2d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
import gradio as gr
import requests
import json
import huggingface_hub
from huggingface_hub import HfApi
from gradio_client import Client
import os

HF_TOKEN = os.environ["HF_TOKEN"]
HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}

tulu = "https://tonic1-tulu.hf.space/--replicas/tjvh5/"


welcome_message = """
Hi! I'm using [Tulu from AlenAi](https://huggingface.co/spaces/Tonic1/Tulu) I'll help you **build a GPT**. You can say something like, "make a bot that gives advice on how to grow your startup."

What would you like to make?
"""

welcome_preview_message = """
Welcome to **{}**! Say something like: 
"{}"
"""

# sample_response = """
# Certainly! Here we go:

# Title: Recipe Recommender
# System Prompt: Utilize your language model abilities to suggest delicious recipes based on user preferences such as ingredients, cuisine type, cooking time, etc. Ensure accuracy and variety while maintaining a conversational style with the user. 
# Example User Input: Vegetarian dinner ideas under 30 minutes
# """

system_prompt = """
I am an AI whose job it is to help users create their own chatbots. In particular, I respond using titles and subtiles in a friendly tone, write a system prompt for an LLM, a catchy title for the chatbot, and a very short example user input. I make sure each part is included.
I only respond in the following format :
# Title:
# System prompt:  
# Example input: 
<|user|>
"make a bot that gives advice on how to grow your startup", 

<|assistant|>
I first do a friendly response, then I add the title, system prompt, and example user input. I Immediately STOP after the example input. It should be EXACTLY in this format:

Sure, I'd be happy to help you build a bot! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback!
# Title: Startup Coach
# System prompt: My job as an LLM is to provide good startup advice. Do not provide extraneous comments on other topics. Be succinct but useful. 
# Example input: What are the risks of setting up a non-profit board in my startup?

<|user|>
Make a chatbot that roasts tech ceos

<|assistant|>
Sure, I'd be happy to help you build a bot! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback!
# Title: Tech Roaster
# System prompt: As an LLM, my primary function is to deliver hilarious and biting critiques of technology CEOs. I Keep it witty and entertaining, but also make sure my jokes aren't too mean-spirited or factually incorrect. 
# Example input: Roast Elon Musk for me.

<|user|>
Make an app that producesses assessments

<|assistant|>
Sure, I'd be happy to help you build an app! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback!
# Title: Assessment Genius
# System prompt: My primary function is to provide assessments for users. These assessments are relevant, useful, and accurate. Keep in mind that I am user-friendly and professional. 
# Example input: I would like a Personality Assessment


<|user|>
make a gpt that helps to create mutants and masterminds characters

<|assistant|>
Sure, I'd be happy to help you build a bot! I'm generating a title, system prompt, and an example input. How do they sound? Feel free to give me feedback!
# Title: Mutants and Masterminds Character Creator
# System prompt: As an LLM, my job is to help users create characters for the Mutants and Masterminds tabletop RPG. My prompts should be clear and concise, and should help users make characters that are both fun and balanced. 
# Example input: I would like to create a character with the Power Level 10
"""

def predict_beta(message, chatbot=[], system_prompt=system_prompt, max_new_tokens=500, temperature=0.4, top_p=0.90, repetition_penalty=0.90, advanced=False):
    client = Client(tulu)
    try:
        result = client.predict(
            message,  
            system_prompt,  
            max_new_tokens,  
            temperature, 
            top_p,  
            repetition_penalty,  
            advanced,  
            fn_index=0
        )
        print("Raw API Response:", result)  # Debugging print
        if result is not None:
            print("Processed bot_message:", result)  # Debugging print
            return result
        else:
            print("No response or empty response from the model.")  # Debugging print
            return None
            
    except Exception as e:
        error_msg = f"An error occurred: {str(e)}"
        print(error_msg)  # Debugging print
        return None
        
def extract_title_prompt_example(text):
    default_title = "Custom GPT Agent"
    default_system_prompt = "This is a custom GPT agent."
    default_example_input = "Type your query here."

    # Split the text into lines and reverse it to start from the end
    lines = text.split('\n')
    lines.reverse()

    title = default_title
    system_prompt = default_system_prompt
    example_input = default_example_input

    # Flags to check if we have found the sections
    found_title, found_prompt, found_example = False, False, False

    for line in lines:
        if not found_example and line.startswith("# Example input:"):
            example_input = line.replace("# Example input:", "").strip()
            found_example = True
        elif not found_prompt and line.startswith("# System prompt:"):
            system_prompt = line.replace("# System prompt:", "").strip()
            found_prompt = True
        elif not found_title and line.startswith("# Title:"):
            title = line.replace("# Title:", "").strip()
            found_title = True

        # Break the loop if all sections are found
        if found_title and found_prompt and found_example:
            break

    return text, title, system_prompt, example_input

def make_open_gpt(message, history, current_title, current_system_prompt, current_example_input, system_prompt=system_prompt):
    try:
        response = predict_beta(message, history, system_prompt)
        if not response:
            raise ValueError("Empty response from predict_beta")
        print("Response from predict_beta:", response)  # Debugging print
    except Exception as e:
        response = f"Error in predict_beta: {str(e)}"
        print("Error in predict_beta:", response)  # Debugging print
        # Set error values
        title = "Error"
        system_prompt = "Error in predict_beta"
        example_input = "Error"
    else:
        try:
            _, title, system_prompt, example_input = extract_title_prompt_example(response)
        except Exception as e:
            title = "Error"
            system_prompt = "Error in extraction"
            example_input = "Error"
            print(f"Error in extract_title_prompt_example: {str(e)}")

    # Ensure all expected outputs are returned
    return (
        "",  # Placeholder for textbox
        history + [(message, response)],  # Updated chatbot history
        title or current_title,  # Extracted or default title
        system_prompt or current_system_prompt,  # Extracted or default system prompt
        example_input or current_example_input,  # Extracted or default example input
        [(None, welcome_preview_message.format(title or current_title, example_input or current_example_input))],  # Updated chatbot preview
        example_input or current_example_input,  # Example input for textbox_preview
        gr.Column(visible=True),  # Column visibility control
        gr.Group(visible=True)  # Group visibility control
    )

    
def set_title_example(title, example):
    return [(None, welcome_preview_message.format(title, example))], example, gr.Column(visible=True), gr.Group(visible=True)

chatbot_preview = gr.Chatbot(layout="panel")
textbox_preview = gr.Textbox(scale=7, container=False)

def test_preview_chatbot(message, history, system_prompt):
    response = predict_beta(message, history, system_prompt)
    return response


def strip_invalid_filename_characters(filename: str, max_bytes: int = 200) -> str:
    """Strips invalid characters from a filename and ensures that the file_length is less than `max_bytes` bytes."""
    filename = filename.replace(" ", "-")
    filename = "".join([char for char in filename if char.isalnum() or char in "_-"])
    filename_len = len(filename.encode())
    if filename_len > max_bytes:
        while filename_len > max_bytes:
            if len(filename) == 0:
                break
            filename = filename[:-1]
            filename_len = len(filename.encode())
    return filename


constants = """
SYSTEM_PROMPT = "{}"
TITLE = "{}"
EXAMPLE_INPUT = "{}"
"""


def publish(textbox_system_prompt, textbox_title, textbox_example, textbox_token):
    source_file = 'app_template.py'
    destination_file = 'app.py'
    constants_formatted = constants.format(textbox_system_prompt, textbox_title, textbox_example)
    with open(source_file, 'r') as file:
        original_content = file.read()
    with open(destination_file, 'w') as file:
        file.write(constants_formatted + original_content)
    title = strip_invalid_filename_characters(textbox_title, max_bytes=30)
    api = HfApi(token=textbox_token)
    new_space = api.create_repo(
        repo_id=f"open-gpt-{title}",
        repo_type="space",
        exist_ok=True,
        private=False,
        space_sdk="gradio",
        token=textbox_token,
    )
    api.upload_file(
        repo_id=new_space.repo_id,
        path_or_fileobj='app.py',
        path_in_repo='app.py',
        token=textbox_token,
        repo_type="space",
    )
    api.upload_file(
        repo_id=new_space.repo_id,
        path_or_fileobj='README_template.md',
        path_in_repo='README.md',
        token=textbox_token,
        repo_type="space",
    )
    huggingface_hub.add_space_secret(
        new_space.repo_id, "HF_TOKEN", textbox_token, token=textbox_token
    )

    return gr.Markdown(f"Published to https://huggingface.co/spaces/{new_space.repo_id} ✅", visible=True), gr.Button("Publish", interactive=True)
    
    
css = """
#preview-tab-button{
    font-weight: bold;
}
"""

with gr.Blocks(css=css) as demo:
    gr.Markdown(""" # 👋🏻Welcome to 🕵🏻‍♂️Agent🌷Tulu
    **A🕵🏻‍♂️Agent🌷Tulu** lets you create your own **open-source GPTs** using [allenai/tulu-2-dpo-13b](https://huggingface.co/allenai/tulu-2-dpo-13b). Start chatting to automatically below to automatically bake your GPT (or you can manually configure the recipe in the second tab). You can build and test them for free & publish them on Spaces (as Open GPTs are powered by the [Tulu DPO model](https://huggingface.co/allenai/tulu-2-dpo-70b) ).
    You think this is cool + want to make your own ? check out [GPTBaker](https://huggingface.co/abidlabs/GPT-Baker) from [AbidLabs](https://huggingface.co/abidlabs) of 🤗[Gradio](https://www.gradio.app/)
    ### Join us: 
    TeamTonic is always making cool demos! Join our active builder's community on Discord: [Discord](https://discord.gg/GWpVpekp) On Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On Github: [Polytonic](https://github.com/tonic-ai) & contribute to [PolyGPT](https://github.com/tonic-ai/polygpt-alpha) """
               )
    with gr.Row():
        with gr.Column(scale=3):
            with gr.Tab("Create"):
                chatbot_maker = gr.Chatbot([(None, welcome_message)], layout="panel", elem_id="chatbot-maker")
                with gr.Group():
                    with gr.Row():
                        textbox_maker = gr.Textbox(placeholder="Make a bot that roasts tech CEOs", scale=7, container=False, autofocus=True)
                        submit_btn = gr.Button("Bake 👩‍🍳", variant="secondary")
            with gr.Tab("Configure Recipe"):
                textbox_title = gr.Textbox("GPT Preview", label="Title")
                textbox_system_prompt = gr.Textbox(label="System prompt", lines=6)
                textbox_example = gr.Textbox(label="Placeholder example", lines=2)
            with gr.Tab("Files"):
                gr.Markdown("RAG coming soon!")
        with gr.Column(visible=False, scale=5) as preview_column:
            with gr.Tab("🪄 Preview of your Open GPT", elem_id="preview-tab") as preview_tab:
                gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview, autofocus=False, submit_btn="Test", additional_inputs=[textbox_system_prompt])
    with gr.Group(visible=False) as publish_row:
        with gr.Row():
            textbox_token = gr.Textbox(show_label=False, placeholder="Ready to publish to Spaces? Enter your HF token here", scale=7)
            publish_btn = gr.Button("Publish", variant="primary")

    published_status = gr.Markdown(visible=False)
    
    gr.on([submit_btn.click, textbox_maker.submit], make_open_gpt, [textbox_maker, chatbot_maker, textbox_title, textbox_system_prompt, textbox_example], [textbox_maker, chatbot_maker, textbox_title, textbox_system_prompt, textbox_example, chatbot_preview, textbox_preview, preview_column, publish_row])
    gr.on([textbox_title.blur, textbox_example.blur], set_title_example, [textbox_title, textbox_example], [chatbot_preview, textbox_preview, preview_column, publish_row])

    publish_btn.click(lambda : gr.Button("Publishing...", interactive=False), None, publish_btn).then(publish, [textbox_system_prompt, textbox_title, textbox_example, textbox_token], [published_status, publish_btn])

demo.launch()