Update: Pipeline selector.

* Pipeline selector component,
* methods to load past user submissions, for both bonus and tossup and change logging library to loguru.
* Currently commented out the pipeline loading triggers.

requirements.txt

@@ -25,4 +25,5 @@ langchain-community
 langchain-anthropic
 langchain-openai
 langchain-cohere
-json_repair
+json_repair
+loguru

src/components/model_pipeline/model_pipeline.py

@@ -2,6 +2,7 @@ import gradio as gr
 import yaml
 from loguru import logger
 
+from app_configs import UNSELECTED_VAR_NAME
 from components.model_pipeline.state_manager import (
     ModelStepUIState,
     PipelineState,
@@ -62,9 +63,11 @@ class PipelineInterface:
         ui_state: PipelineUIState | None = None,
         model_options: list[str] = None,
         simple: bool = False,
+        show_pipeline_selector: bool = False,
     ):
         self.model_options = model_options
         self.simple = simple
+        self.show_pipeline_selector = show_pipeline_selector
         if not ui_state:
             ui_state = PipelineUIState.from_workflow(workflow)
         self.ui_state = make_state(ui_state)
@@ -155,16 +158,13 @@ class PipelineInterface:
 
     def _render_output_fields(self, available_variables: list[str], pipeline_state: PipelineState):
         dropdowns = {}
-        UNSET_VALUE = "Choose variable..."
-        variable_options = [UNSET_VALUE] + [v for v in available_variables if v not in self.input_variables]
+        variable_options = [UNSELECTED_VAR_NAME] + [v for v in available_variables if v not in self.input_variables]
         with gr.Column(elem_classes="step-accordion"):
             with gr.Row(elem_classes="output-fields-header"):
                 gr.Markdown("#### Final output variables mapping:")
             with gr.Row(elem_classes="output-fields-row"):
                 for output_field in self.required_output_variables:
-                    value = pipeline_state.workflow.outputs[output_field]
-                    if not value:
-                        value = UNSET_VALUE
+                    value = pipeline_state.workflow.outputs.get(output_field, UNSELECTED_VAR_NAME)
                     dropdown = gr.Dropdown(
                         label=output_field,
                         value=value,
@@ -234,7 +234,7 @@ class PipelineInterface:
         self._render_pipeline_header()
 
         # Function to render all steps
-        @gr.render(inputs=[self.pipeline_state, self.ui_state])
+        @gr.render(inputs=[self.pipeline_state, self.ui_state], concurrency_limit=1, concurrency_id="render_steps")
         def render_steps(state: PipelineState, ui_state: PipelineUIState):
             """Render all steps in the pipeline"""
             logger.info(f"\nRerender triggered! Current UI State:{ui_state.model_dump()}")
@@ -251,21 +251,24 @@ class PipelineInterface:
 
             components.append(step_objects)
 
-        # Bottom buttons
         if not self.simple:
             self._render_add_step_button(-1)
 
-        @gr.render(inputs=[self.variables_state, self.pipeline_state])
+        @gr.render(
+            inputs=[self.variables_state, self.pipeline_state],
+            concurrency_limit=1,
+            concurrency_id="render_output_fields",
+        )
         def render_output_fields(available_variables, pipeline_state):
-            return self._render_output_fields(available_variables, pipeline_state)
+            self._render_output_fields(available_variables, pipeline_state)
 
         export_btn = gr.Button("Export Pipeline", elem_classes="export-button")
         # components.append(export_btn)
 
         # Add a code box to display the workflow JSON
         # with gr.Column(elem_classes="workflow-json-container"):
-        with gr.Accordion("Pipeline Preview", open=False, elem_classes="pipeline-preview") as config_accordion:
-            config_output = gr.Code(
+        with gr.Accordion("Pipeline Preview", open=False, elem_classes="pipeline-preview") as self.config_accordion:
+            self.config_output = gr.Code(
                 label="Workflow Configuration",
                 language="yaml",
                 elem_classes="workflow-json",
@@ -274,21 +277,27 @@ class PipelineInterface:
             )
         # components.append(config_accordion)
 
-        config_output.blur(
+        self.config_output.blur(
             fn=update_workflow_from_code,
-            inputs=[config_output, self.ui_state],
+            inputs=[self.config_output, self.ui_state],
             outputs=[self.pipeline_state],
         )
 
         # Connect the export button to show the workflow JSON
+        self.add_triggers_for_pipeline_export([export_btn.click], self.pipeline_state)
         export_btn.click(self.validate_workflow, inputs=[self.pipeline_state], outputs=[self.pipeline_state]).success(
-            fn=lambda: gr.update(visible=True, open=True), outputs=[config_accordion]
+            fn=lambda: gr.update(visible=True, open=True), outputs=[self.config_accordion]
         )
-        export_btn.click(
+
+    def add_triggers_for_pipeline_export(self, triggers: list, input_pipeline_state: gr.State):
+        gr.on(
+            triggers,
+            self.validate_workflow,
+            inputs=[input_pipeline_state],
+            outputs=[self.pipeline_state],
+        ).success(
             fn=self.sm.get_formatted_config,
             inputs=[self.pipeline_state, gr.State("yaml")],
-            outputs=[config_output],
+            outputs=[self.config_output],
             js="() => {document.querySelector('.pipeline-preview').scrollIntoView({behavior: 'smooth'})}",
         )
-
-        # self.all_components = components

src/components/quizbowl/bonus.py

@@ -1,18 +1,19 @@
 import json
-import logging
 from typing import Any
 
 import gradio as gr
 import pandas as pd
 from datasets import Dataset
+from loguru import logger
 
-from components.model_pipeline.model_pipeline import PipelineInterface, PipelineState
+from components.model_pipeline.model_pipeline import PipelineInterface, PipelineState, PipelineUIState
+from display.formatting import styled_error
 from submission import submit
 from workflows.qb.multi_step_agent import MultiStepBonusAgent
 from workflows.qb.simple_agent import SimpleBonusAgent
 from workflows.structs import ModelStep, Workflow
 
-from .commons import get_qid_selector
+from . import commons
 from .plotting import (
     create_bonus_confidence_plot,
     create_bonus_html,
@@ -51,7 +52,7 @@ def initialize_eval_interface(example: dict, model_outputs: list[dict]):
 
         return html_content, plot_data, state
     except Exception as e:
-        logging.error(f"Error initializing interface: {e}", exc_info=True)
+        logger.exception(f"Error initializing interface: {e.args}")
         return f"<div>Error initializing interface: {str(e)}</div>", pd.DataFrame(), "{}"
 
 
@@ -112,7 +113,7 @@ class BonusInterface:
 
     def __init__(self, app: gr.Blocks, dataset: Dataset, model_options: dict, defaults: dict):
         """Initialize the Bonus interface."""
-        logging.info(f"Initializing Bonus interface with dataset size: {len(dataset)}")
+        logger.info(f"Initializing Bonus interface with dataset size: {len(dataset)}")
         self.ds = dataset
         self.model_options = model_options
         self.app = app
@@ -122,6 +123,8 @@ class BonusInterface:
 
     def _render_model_interface(self, workflow: Workflow, simple: bool = True):
         """Render the model interface."""
+        with gr.Row():
+            self.model_selector = commons.get_pipeline_selector([])
         self.pipeline_interface = PipelineInterface(
             workflow,
             simple=simple,
@@ -131,7 +134,7 @@ class BonusInterface:
     def _render_qb_interface(self):
         """Render the quizbowl interface."""
         with gr.Row(elem_classes="bonus-header-row form-inline"):
-            self.qid_selector = get_qid_selector(len(self.ds))
+            self.qid_selector = commons.get_qid_selector(len(self.ds))
             self.run_btn = gr.Button("Run on Bonus Question", variant="secondary")
 
         self.question_display = gr.HTML(label="Question", elem_id="bonus-question-display")
@@ -176,7 +179,7 @@ class BonusInterface:
     def get_new_question_html(self, question_id: int):
         """Get the HTML for a new question."""
         if question_id is None:
-            logging.error("Question ID is None. Setting to 1")
+            logger.error("Question ID is None. Setting to 1")
             question_id = 1
         try:
             question_id = int(question_id) - 1
@@ -190,6 +193,20 @@ class BonusInterface:
         except Exception as e:
             return f"Error loading question: {str(e)}"
 
+    def get_user_submission_names(self, profile: gr.OAuthProfile | None) -> list[str]:
+        if profile is None:
+            logger.error("Authentication required. Please log in to view your submissions.")
+            return []
+        model_names = submit.get_user_submission_names("bonus", profile)
+        logger.info("Loaded model names: {model_names}")
+        return gr.update(choices=model_names, value=None)
+
+    def load_user_submission(self, model_name: str, profile: gr.OAuthProfile | None) -> PipelineState:
+        if profile is None:
+            return styled_error("Authentication required. Please log in to view your submissions.")
+        submission = submit.load_submission(model_name, "tossup", profile)
+        return PipelineState(workflow=submission.workflow, ui_state=PipelineUIState.from_workflow(submission.workflow))
+
     def get_model_outputs(self, example: dict, pipeline_state: PipelineState):
         """Get the model outputs for a given question ID."""
         outputs = []
@@ -281,10 +298,8 @@ class BonusInterface:
                 gr.update(value=df, label="Scores on Sample Set"),
                 gr.update(value=plot_data, label="Part Scores on Sample Set"),
             )
-        except Exception:
-            import traceback
-
-            logging.error(f"Error evaluating bonus: {traceback.format_exc()}")
+        except Exception as e:
+            logger.exception(f"Error evaluating bonus: {e.args}")
             return "Error evaluating bonus", None, None
 
     def submit_model(
@@ -303,6 +318,22 @@ class BonusInterface:
             outputs=[self.question_display],
         )
 
+        gr.on(
+            triggers=[self.app.load],
+            fn=self.get_user_submission_names,
+            outputs=[self.model_selector],
+        )
+
+        # self.new_loaded_pipeline_state = gr.State(value=None)
+        # self.model_selector.change(
+        #     fn=self.load_user_submission,
+        #     inputs=[self.model_selector],
+        #     outputs=[self.new_loaded_pipeline_state],
+        # )
+        # self.pipeline_interface.add_triggers_for_pipeline_export(
+        #     [self.new_loaded_pipeline_state.change], self.new_loaded_pipeline_state
+        # )
+
         self.run_btn.click(
             self.pipeline_interface.validate_workflow,
             inputs=[self.pipeline_interface.pipeline_state],

src/components/quizbowl/commons.py

@@ -13,3 +13,12 @@ def get_qid_selector(dataset_size: int):
         container=False,
         elem_classes="qid-selector",
     )
+
+
+def get_pipeline_selector(model_options: list[str]):
+    return gr.Dropdown(
+        label="User Submissions and Examples",
+        choices=model_options,
+        value="",
+        interactive=True,
+    )

src/components/quizbowl/tossup.py

@@ -1,19 +1,20 @@
 import json
-import logging
 from typing import Any
 
 import gradio as gr
 import numpy as np
 import pandas as pd
 from datasets import Dataset
+from loguru import logger
 
-from components.model_pipeline.model_pipeline import PipelineInterface, PipelineState
+from components.model_pipeline.model_pipeline import PipelineInterface, PipelineState, PipelineUIState
+from display.formatting import styled_error
 from submission import submit
 from workflows.qb.multi_step_agent import MultiStepTossupAgent
 from workflows.qb.simple_agent import SimpleTossupAgent
 from workflows.structs import ModelStep, Workflow
 
-from .commons import get_qid_selector
+from . import commons
 from .plotting import (
     create_scatter_pyplot,
     create_tossup_confidence_pyplot,
@@ -39,7 +40,7 @@ def prepare_buzz_evals(
 ) -> tuple[list[str], list[tuple[int, float, bool]]]:
     """Process text into tokens and assign random values for demonstration."""
     if not run_indices:
-        logging.warning("No run indices provided, returning empty results")
+        logger.warning("No run indices provided, returning empty results")
         return [], []
     eval_points = []
     for i, v in zip(run_indices, model_outputs):
@@ -68,7 +69,7 @@ def initialize_eval_interface(example, model_outputs: list[dict]):
 
         return html_content, plot_data, state
     except Exception as e:
-        logging.error(f"Error initializing interface: {e}", exc_info=True)
+        logger.exception(f"Error initializing interface: {e.args}")
         return f"<div>Error initializing interface: {str(e)}</div>", pd.DataFrame(), "{}"
 
 
@@ -164,9 +165,15 @@ def validate_model_step(model_step: ModelStep):
 class TossupInterface:
     """Gradio interface for the Tossup mode."""
 
-    def __init__(self, app: gr.Blocks, dataset: Dataset, model_options: dict, defaults: dict):
+    def __init__(
+        self,
+        app: gr.Blocks,
+        dataset: Dataset,
+        model_options: dict,
+        defaults: dict,
+    ):
         """Initialize the Tossup interface."""
-        logging.info(f"Initializing Tossup interface with dataset size: {len(dataset)}")
+        logger.info(f"Initializing Tossup interface with dataset size: {len(dataset)}")
         self.ds = dataset
         self.model_options = model_options
         self.app = app
@@ -176,6 +183,8 @@ class TossupInterface:
 
     def _render_model_interface(self, workflow: Workflow, simple: bool = True):
         """Render the model interface."""
+        with gr.Row():
+            self.model_selector = commons.get_pipeline_selector([])
         self.pipeline_interface = PipelineInterface(
             workflow,
             simple=simple,
@@ -198,7 +207,7 @@ class TossupInterface:
     def _render_qb_interface(self):
         """Render the quizbowl interface."""
         with gr.Row(elem_classes="bonus-header-row form-inline"):
-            self.qid_selector = get_qid_selector(len(self.ds))
+            self.qid_selector = commons.get_qid_selector(len(self.ds))
             self.run_btn = gr.Button("Run on Tossup Question", variant="secondary")
         self.question_display = gr.HTML(label="Question", elem_id="tossup-question-display")
         with gr.Row():
@@ -249,7 +258,7 @@ class TossupInterface:
     def get_new_question_html(self, question_id: int) -> str:
         """Get the HTML for a new question."""
         if question_id is None:
-            logging.error("Question ID is None. Setting to 1")
+            logger.error("Question ID is None. Setting to 1")
             question_id = 1
         try:
             example = self.ds[question_id - 1]
@@ -276,6 +285,20 @@ class TossupInterface:
         outputs = add_model_scores(outputs, example["clean_answers"], example["run_indices"])
         return outputs
 
+    def get_user_submission_names(self, profile: gr.OAuthProfile | None) -> list[str]:
+        if profile is None:
+            logger.error("Authentication required. Please log in to view your submissions.")
+            return []
+        model_names = submit.get_user_submission_names("tossup", profile)
+        logger.info("Loaded model names: {model_names}")
+        return gr.update(choices=model_names, value=None)
+
+    def load_user_submission(self, model_name: str, profile: gr.OAuthProfile | None) -> PipelineState:
+        if profile is None:
+            return styled_error("Authentication required. Please log in to view your submissions.")
+        submission = submit.load_submission(model_name, "tossup", profile)
+        return PipelineState(workflow=submission.workflow, ui_state=PipelineUIState.from_workflow(submission.workflow))
+
     def single_run(
         self,
         question_id: int,
@@ -341,10 +364,8 @@ class TossupInterface:
                 gr.update(value=df, label="Scores on Sample Set"),
                 gr.update(value=plot_data, label="Buzz Positions on Sample Set"),
             )
-        except Exception:
-            import traceback
-
-            logging.error(f"Error evaluating tossups: {traceback.format_exc()}")
+        except Exception as e:
+            logger.exception(f"Error evaluating tossups: {e.args}")
             return "Error evaluating tossups", None, None
 
     def submit_model(
@@ -361,6 +382,22 @@ class TossupInterface:
             outputs=[self.question_display],
         )
 
+        gr.on(
+            triggers=[self.app.load],
+            fn=self.get_user_submission_names,
+            outputs=[self.model_selector],
+        )
+
+        # self.new_loaded_pipeline_state = gr.State(value=None)
+        # self.model_selector.change(
+        #     fn=self.load_user_submission,
+        #     inputs=[self.model_selector],
+        #     outputs=[self.new_loaded_pipeline_state],
+        # )
+        # self.pipeline_interface.add_triggers_for_pipeline_export(
+        #     [self.new_loaded_pipeline_state.change], self.new_loaded_pipeline_state
+        # )
+
         self.run_btn.click(
             self.pipeline_interface.validate_workflow,
             inputs=[self.pipeline_interface.pipeline_state],