File size: 7,248 Bytes
193db9d
633b045
193db9d
 
 
 
 
 
633b045
 
 
 
193db9d
 
 
633b045
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
193db9d
633b045
193db9d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
633b045
193db9d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
633b045
 
 
 
 
 
 
 
 
 
 
193db9d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
633b045
 
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
import json
import logging
import os
import traceback
from datetime import datetime, timedelta, timezone

import gradio as gr

from app_configs import DAILY_SUBMISSION_LIMIT_PER_USER
from display.formatting import styled_error, styled_message
from envs import API, EVAL_REQUESTS_PATH, QUEUE_REPO
from submission.structs import CompetitionType, Submission, SubmissionStatus
from workflows.structs import Workflow


def get_user_submissions(username: str, competition_type: str, pattern: str = None) -> list[Submission]:
    """Get all submissions for a user."""
    out_dir = f"{EVAL_REQUESTS_PATH}/{username}"
    submissions = []
    if not os.path.exists(out_dir):
        return submissions
    for file in os.listdir(out_dir):
        if not file.startswith(f"{competition_type}_"):
            continue
        if pattern is not None and pattern not in file:
            continue
        with open(os.path.join(out_dir, file), "r") as f:
            submission = Submission.from_dict(json.load(f))
            submissions.append(submission)
    return submissions


def get_user_submission_names(competition_type: str, profile: gr.OAuthProfile | None) -> list[str]:
    """Get all submission model names for a user."""
    if profile is None:
        return []
    submissions = get_user_submissions(profile.username, competition_type)
    return [s.model_name for s in submissions]


def get_user_submissions_today(username: str, competition_type: str) -> list[Submission]:
    """Get all submissions for a user for a given competition type."""
    today = datetime.now(timezone.utc).strftime("%Y%m%d")
    if username is None:
        raise gr.Error("Authentication required. Please log in to view your submissions.")
    out_dir = f"{EVAL_REQUESTS_PATH}/{username}"
    submissions = []
    if not os.path.exists(out_dir):
        return submissions
    for file in os.listdir(out_dir):
        if not file.startswith(f"{competition_type}_"):
            continue
        with open(os.path.join(out_dir, file), "r") as f:
            submission = Submission.from_dict(json.load(f))
            if submission.created_at.startswith(today):
                submissions.append(submission)
    return submissions


def get_time_until_next_submission(tz: timezone = timezone.utc) -> str:
    next_day_00 = datetime.now(tz) + timedelta(days=1)
    next_day_00 = next_day_00.replace(hour=0, minute=0, second=0, microsecond=0)
    remaining_time = next_day_00 - datetime.now(tz)
    hours = remaining_time.seconds // 3600
    minutes = (remaining_time.seconds % 3600) // 60
    remaining_time_str = f"{hours} hours {minutes} mins"
    return remaining_time_str


def create_submission(
    username: str,
    model_name: str,
    description: str,
    workflow: Workflow,
    competition_type: CompetitionType,
) -> Submission:
    """
    Create a submission for a tossup model.

    Args:
        name: Display name of the submission
        description: Detailed description of what the submission does
        user_email: Email of the user who created the submission
        workflow: The workflow configuration for the tossup model

    Returns:
        Submission object if successful, None if validation fails
    """
    # Create the submission
    dt = datetime.now(timezone.utc)
    submission = Submission(
        id=f"{competition_type}_{dt.strftime('%Y%m%d_%H%M%S')}_{model_name.lower().replace(' ', '_')}",
        model_name=model_name,
        username=username,
        description=description,
        competition_type=competition_type,
        submission_type="simple_workflow",
        workflow=workflow,
        status="submitted",
        created_at=dt.isoformat(),
        updated_at=dt.isoformat(),
    )

    return submission


def submit_model(
    model_name: str,
    description: str,
    workflow: Workflow,
    competition_type: CompetitionType,
    profile: gr.OAuthProfile | None,
) -> str:
    """
    Submit a tossup model for evaluation.

    Args:
        name: Display name of the submission
        description: Detailed description of what the submission does
        user_email: Email of the user who created the submission
        workflow: The workflow configuration for the tossup model

    Returns:
        Status message
    """

    if profile is None:
        return styled_error("Authentication required. Please log in first to submit your model.")

    username = profile.username

    if len(get_user_submissions_today(username, competition_type)) >= DAILY_SUBMISSION_LIMIT_PER_USER:
        time_str = get_time_until_next_submission()
        return styled_error(
            f"Daily submission limit of {DAILY_SUBMISSION_LIMIT_PER_USER} reached. Please try again in \n {time_str}."
        )
    try:
        submission = create_submission(
            username=username,
            model_name=model_name,
            description=description,
            workflow=workflow,
            competition_type=competition_type,
        )
        # Convert to dictionary format
        submission_dict = submission.to_dict()

        # Create output directory path
        out_dir = f"{EVAL_REQUESTS_PATH}/{username}"
        out_path = f"{out_dir}/{submission.id}.json"

        # Upload to HuggingFace dataset
        API.upload_file(
            path_or_fileobj=json.dumps(submission_dict, indent=2).encode(),
            path_in_repo=out_path.split("eval-queue/")[1],
            repo_id=QUEUE_REPO,
            repo_type="dataset",
            commit_message=f"Add tossup submission {submission.id}",
        )

        return styled_message(
            f"Successfully submitted tossup model!\n"
            f"Submission ID: {submission.id}\n"
            f"Name: {username}/{model_name}\n"
            f"Please wait for up to an hour for the model to show in the PENDING list."
        )

    except Exception as e:
        traceback.print_exc()
        return styled_error(f"Error submitting model: {str(e)}")


def load_submission(model_name: str, competition_type: CompetitionType, profile: gr.OAuthProfile | None) -> Submission:
    if profile is None:
        logging.error("Authentication required. Please log in to view your submissions.")
        return styled_error("Authentication required. Please log in to view your submissions.")
    username = profile.username
    submissions = get_user_submissions(username, competition_type, model_name)
    if len(submissions) == 0:
        return styled_error(f"Submission {model_name} not found.")
    return submissions[0]


if __name__ == "__main__":
    # Example usage
    from workflows.factory import create_quizbowl_simple_step_initial_setup

    # Create workflow
    model_step = create_quizbowl_simple_step_initial_setup()
    model_step.model = "gpt-4"
    model_step.provider = "openai"
    model_step.temperature = 0.7

    workflow = Workflow(
        inputs=["question_text"],
        outputs={"answer": "A.answer", "confidence": "A.confidence"},
        steps={"A": model_step},
    )

    # Submit model
    result = submit_model(
        model_name="GPT-4 Tossup",
        description="A simple GPT-4 model for tossup questions",
        workflow=workflow,
        competition_type="tossup",
    )
    print(result)

# %%