diff --git a/.github/workflows/basic-test-proxy.yaml b/.github/workflows/basic-test-proxy.yaml
index a2cd40d3..d0c704c2 100644
--- a/.github/workflows/basic-test-proxy.yaml
+++ b/.github/workflows/basic-test-proxy.yaml
@@ -15,7 +15,8 @@ jobs:
       # setup repository with all necessary dependencies - keep as is
       - name: Check out repository
         uses: actions/checkout@v3
-      - uses: actions/setup-python@v4
+      - id: setup-python
+        uses: actions/setup-python@v4
         with:
           python-version: "3.11"
       - name: Install poetry
diff --git a/.github/workflows/run-bot-aib-tournament.yaml b/.github/workflows/run-bot-aib-tournament.yaml
index d63239d7..2e9fc0f6 100644
--- a/.github/workflows/run-bot-aib-tournament.yaml
+++ b/.github/workflows/run-bot-aib-tournament.yaml
@@ -20,7 +20,8 @@ jobs:
       - name: Check out repository
         uses: actions/checkout@v3
 
-      - uses: actions/setup-python@v4
+      - id: setup-python
+        uses: actions/setup-python@v4
         with:
           python-version: "3.11"
 
diff --git a/.github/workflows/run-bot-launcher.yaml b/.github/workflows/run-bot-launcher.yaml
index d592bf60..3a7f3972 100644
--- a/.github/workflows/run-bot-launcher.yaml
+++ b/.github/workflows/run-bot-launcher.yaml
@@ -43,7 +43,8 @@ jobs:
       - name: Check out repository
         uses: actions/checkout@v3
 
-      - uses: actions/setup-python@v4
+      - id: setup-python
+        uses: actions/setup-python@v4
         with:
           python-version: "3.11"
 
diff --git a/.github/workflows/stress-test_proxy.yaml b/.github/workflows/stress-test_proxy.yaml
index 2836ae46..1a62c955 100644
--- a/.github/workflows/stress-test_proxy.yaml
+++ b/.github/workflows/stress-test_proxy.yaml
@@ -14,7 +14,8 @@ jobs:
       # setup repository with all necessary dependencies - keep as is
       - name: Check out repository
         uses: actions/checkout@v3
-      - uses: actions/setup-python@v4
+      - id: setup-python
+        uses: actions/setup-python@v4
         with:
           python-version: "3.11"
       - name: Install poetry
diff --git a/code_tests/unit_tests/test_data_models/test_aggregate_edge_cases.py b/code_tests/unit_tests/test_data_models/test_aggregate_edge_cases.py
new file mode 100644
index 00000000..8c36eea8
--- /dev/null
+++ b/code_tests/unit_tests/test_data_models/test_aggregate_edge_cases.py
@@ -0,0 +1,169 @@
+"""
+This  file is AI Generated. If it causes problems for a human we can probably just delete it.
+"""
+
+import numpy as np
+import pytest
+
+from forecasting_tools.data_models.numeric_report import (
+    NumericDistribution,
+    NumericReport,
+    Percentile,
+)
+from forecasting_tools.data_models.questions import NumericQuestion, QuestionState
+
+
+def _make_question(
+    lower_bound: float = 0.0,
+    upper_bound: float = 100e9,
+    open_lower_bound: bool = True,
+    open_upper_bound: bool = True,
+) -> NumericQuestion:
+    return NumericQuestion(
+        id_of_post=1,
+        id_of_question=1,
+        question_text="Test question",
+        background_info="",
+        resolution_criteria="",
+        fine_print="",
+        state=QuestionState.OPEN,
+        upper_bound=upper_bound,
+        lower_bound=lower_bound,
+        open_upper_bound=open_upper_bound,
+        open_lower_bound=open_lower_bound,
+        zero_point=None,
+    )
+
+
+def _make_distribution(
+    percentile_value_pairs: list[tuple[float, float]],
+    question: NumericQuestion,
+) -> NumericDistribution:
+    percentiles = [Percentile(percentile=p, value=v) for p, v in percentile_value_pairs]
+    return NumericDistribution.from_question(percentiles, question)
+
+
+CENTERED_DISTRIBUTION = [
+    (0.1, 30e9),
+    (0.2, 40e9),
+    (0.4, 50e9),
+    (0.6, 60e9),
+    (0.8, 70e9),
+    (0.9, 80e9),
+]
+SHIFTED_DISTRIBUTION = [
+    (0.1, 35e9),
+    (0.2, 45e9),
+    (0.4, 55e9),
+    (0.6, 65e9),
+    (0.8, 75e9),
+    (0.9, 85e9),
+]
+
+
+async def test_aggregate_shows_six_lines() -> None:
+    question = _make_question()
+    predictions = [
+        _make_distribution(CENTERED_DISTRIBUTION, question),
+        _make_distribution(SHIFTED_DISTRIBUTION, question),
+    ]
+    aggregated = await NumericReport.aggregate_predictions(predictions, question)
+    readable = NumericReport.make_readable_prediction(aggregated)
+    assert readable.count("chance of value below") == 6
+
+
+async def test_single_forecaster_aggregate() -> None:
+    question = _make_question()
+    predictions = [_make_distribution(CENTERED_DISTRIBUTION, question)]
+    aggregated = await NumericReport.aggregate_predictions(predictions, question)
+    readable = NumericReport.make_readable_prediction(aggregated)
+    assert "10.00%" in readable
+    assert "90.00%" in readable
+    result = aggregated.get_percentiles_at_target_heights()
+    assert result[0].value == pytest.approx(30e9, rel=0.1)
+    assert result[5].value == pytest.approx(80e9, rel=0.1)
+
+
+async def test_values_monotonically_increasing() -> None:
+    question = _make_question()
+    predictions = [
+        _make_distribution(CENTERED_DISTRIBUTION, question),
+        _make_distribution(SHIFTED_DISTRIBUTION, question),
+    ]
+    aggregated = await NumericReport.aggregate_predictions(predictions, question)
+    result = aggregated.get_percentiles_at_target_heights()
+    for i in range(len(result) - 1):
+        assert result[i].value < result[i + 1].value
+
+
+async def test_closed_bounds() -> None:
+    question = _make_question(open_lower_bound=False, open_upper_bound=False)
+    predictions = [
+        _make_distribution(CENTERED_DISTRIBUTION, question),
+        _make_distribution(SHIFTED_DISTRIBUTION, question),
+    ]
+    aggregated = await NumericReport.aggregate_predictions(predictions, question)
+    readable = NumericReport.make_readable_prediction(aggregated)
+    assert "10.00%" in readable
+
+
+async def test_nvidia_values_near_median() -> None:
+    question = _make_question()
+    forecaster_percentile_values = [
+        [(0.1, 55e9), (0.2, 58e9), (0.4, 61e9), (0.6, 63e9), (0.8, 66e9), (0.9, 70e9)],
+        [
+            (0.1, 54e9),
+            (0.2, 57e9),
+            (0.4, 60e9),
+            (0.6, 62.5e9),
+            (0.8, 65.5e9),
+            (0.9, 69e9),
+        ],
+        [
+            (0.1, 55e9),
+            (0.2, 58e9),
+            (0.4, 61e9),
+            (0.6, 62.5e9),
+            (0.8, 65e9),
+            (0.9, 68e9),
+        ],
+        [(0.1, 55e9), (0.2, 58e9), (0.4, 60e9), (0.6, 62e9), (0.8, 65e9), (0.9, 68e9)],
+    ]
+    predictions = [
+        _make_distribution(pvs, question) for pvs in forecaster_percentile_values
+    ]
+    aggregated = await NumericReport.aggregate_predictions(predictions, question)
+    result = aggregated.get_percentiles_at_target_heights()
+    for i in range(6):
+        expected = np.median([pvs[i][1] for pvs in forecaster_percentile_values])
+        assert result[i].value == pytest.approx(expected, rel=0.15)
+
+
+async def test_asymmetric_skew() -> None:
+    question = _make_question()
+    right_skewed_a = [
+        (0.1, 5e9),
+        (0.2, 8e9),
+        (0.4, 10e9),
+        (0.6, 12e9),
+        (0.8, 20e9),
+        (0.9, 50e9),
+    ]
+    right_skewed_b = [
+        (0.1, 6e9),
+        (0.2, 9e9),
+        (0.4, 11e9),
+        (0.6, 13e9),
+        (0.8, 22e9),
+        (0.9, 55e9),
+    ]
+    predictions = [
+        _make_distribution(right_skewed_a, question),
+        _make_distribution(right_skewed_b, question),
+    ]
+    aggregated = await NumericReport.aggregate_predictions(predictions, question)
+    readable = NumericReport.make_readable_prediction(aggregated)
+    assert "10.00%" in readable
+    result = aggregated.get_percentiles_at_target_heights()
+    for i in range(len(result) - 1):
+        assert result[i].value < result[i + 1].value
diff --git a/code_tests/unit_tests/test_data_models/test_numeric_report.py b/code_tests/unit_tests/test_data_models/test_numeric_report.py
index 3464929c..01028d71 100644
--- a/code_tests/unit_tests/test_data_models/test_numeric_report.py
+++ b/code_tests/unit_tests/test_data_models/test_numeric_report.py
@@ -569,3 +569,321 @@ def check_distribution_variations(
     )
     # Let the model validator do most the asserts
     assert cdf_distribution.cdf_size == cdf_size
+
+
+class TestGetPercentilesAtTargetHeights:
+    def _make_distribution(
+        self,
+        percentiles: list[Percentile],
+        lower_bound: float = 0.0,
+        upper_bound: float = 100.0,
+        open_lower_bound: bool = False,
+        open_upper_bound: bool = False,
+    ) -> NumericDistribution:
+        return NumericDistribution(
+            declared_percentiles=percentiles,
+            open_upper_bound=open_upper_bound,
+            open_lower_bound=open_lower_bound,
+            upper_bound=upper_bound,
+            lower_bound=lower_bound,
+            zero_point=None,
+            standardize_cdf=False,
+        )
+
+    def test_basic_interpolation(self) -> None:
+        percentiles = [
+            Percentile(value=10.0, percentile=0.1),
+            Percentile(value=50.0, percentile=0.5),
+            Percentile(value=90.0, percentile=0.9),
+        ]
+        dist = self._make_distribution(percentiles)
+        result = dist.get_percentiles_at_target_heights([0.1, 0.5, 0.9])
+        assert result[0].value == pytest.approx(10.0)
+        assert result[1].value == pytest.approx(50.0)
+        assert result[2].value == pytest.approx(90.0)
+        assert result[0].percentile == pytest.approx(0.1)
+        assert result[1].percentile == pytest.approx(0.5)
+        assert result[2].percentile == pytest.approx(0.9)
+
+    def test_interpolation_between_declared_points(self) -> None:
+        percentiles = [
+            Percentile(value=0.0, percentile=0.0),
+            Percentile(value=100.0, percentile=1.0),
+        ]
+        dist = self._make_distribution(percentiles)
+        result = dist.get_percentiles_at_target_heights([0.25, 0.5, 0.75])
+        assert result[0].value == pytest.approx(25.0)
+        assert result[1].value == pytest.approx(50.0)
+        assert result[2].value == pytest.approx(75.0)
+
+    def test_default_target_heights(self) -> None:
+        percentiles = [
+            Percentile(value=0.0, percentile=0.0),
+            Percentile(value=100.0, percentile=1.0),
+        ]
+        dist = self._make_distribution(percentiles)
+        result = dist.get_percentiles_at_target_heights()
+        assert len(result) == 6
+        expected_heights = [0.1, 0.2, 0.4, 0.6, 0.8, 0.9]
+        for r, h in zip(result, expected_heights):
+            assert r.percentile == pytest.approx(h)
+
+    def test_clamping_beyond_range(self) -> None:
+        percentiles = [
+            Percentile(value=30.0, percentile=0.3),
+            Percentile(value=70.0, percentile=0.7),
+        ]
+        dist = self._make_distribution(percentiles)
+        result = dist.get_percentiles_at_target_heights([0.1, 0.5, 0.9])
+        assert result[0].value == pytest.approx(30.0)
+        assert result[1].value == pytest.approx(50.0)
+        assert result[2].value == pytest.approx(70.0)
+
+
+class TestAggregateReadablePrediction:
+    def _make_question(
+        self,
+        lower_bound: float = 0.0,
+        upper_bound: float = 100_000_000_000.0,
+        open_lower_bound: bool = True,
+        open_upper_bound: bool = True,
+    ) -> NumericQuestion:
+        return NumericQuestion(
+            id_of_post=1,
+            id_of_question=1,
+            question_text="Test question",
+            background_info="Test background",
+            resolution_criteria="Test criteria",
+            fine_print="Test fine print",
+            state=QuestionState.OPEN,
+            upper_bound=upper_bound,
+            lower_bound=lower_bound,
+            open_upper_bound=open_upper_bound,
+            open_lower_bound=open_lower_bound,
+            zero_point=None,
+        )
+
+    def _make_forecaster_distribution(
+        self,
+        percentile_values: list[tuple[float, float]],
+        question: NumericQuestion,
+    ) -> NumericDistribution:
+        percentiles = [Percentile(percentile=p, value=v) for p, v in percentile_values]
+        return NumericDistribution.from_question(percentiles, question)
+
+    async def test_aggregate_readable_matches_forecaster_format(self) -> None:
+        """
+        Reproduces the bug from NVIDIA forward guidance question where
+        the aggregate showed weird percentile values like 5.04%, 78.24%
+        instead of clean values like 10%, 20%, 40%, 60%, 80%, 90%.
+        """
+        question = self._make_question()
+        forecaster_percentile_values = [
+            [
+                (0.1, 55e9),
+                (0.2, 58e9),
+                (0.4, 61e9),
+                (0.6, 63e9),
+                (0.8, 66e9),
+                (0.9, 70e9),
+            ],
+            [
+                (0.1, 54e9),
+                (0.2, 57e9),
+                (0.4, 60e9),
+                (0.6, 62.5e9),
+                (0.8, 65.5e9),
+                (0.9, 69e9),
+            ],
+            [
+                (0.1, 55e9),
+                (0.2, 58e9),
+                (0.4, 61e9),
+                (0.6, 62.5e9),
+                (0.8, 65e9),
+                (0.9, 68e9),
+            ],
+            [
+                (0.1, 55e9),
+                (0.2, 58e9),
+                (0.4, 60e9),
+                (0.6, 62e9),
+                (0.8, 65e9),
+                (0.9, 68e9),
+            ],
+        ]
+        predictions = [
+            self._make_forecaster_distribution(pvs, question)
+            for pvs in forecaster_percentile_values
+        ]
+
+        aggregated = await NumericReport.aggregate_predictions(predictions, question)
+        readable = NumericReport.make_readable_prediction(aggregated)
+
+        assert "10.00%" in readable
+        assert "20.00%" in readable
+        assert "40.00%" in readable
+        assert "60.00%" in readable
+        assert "80.00%" in readable
+        assert "90.00%" in readable
+        assert "5.04%" not in readable
+
+    async def test_aggregate_readable_values_are_reasonable(self) -> None:
+        """
+        The interpolated values at standard percentile heights should be
+        close to the median of individual forecasters' values at those heights.
+        """
+        question = self._make_question()
+        predictions = [
+            self._make_forecaster_distribution(
+                [
+                    (0.1, 10e9),
+                    (0.2, 20e9),
+                    (0.4, 40e9),
+                    (0.6, 60e9),
+                    (0.8, 80e9),
+                    (0.9, 90e9),
+                ],
+                question,
+            ),
+            self._make_forecaster_distribution(
+                [
+                    (0.1, 12e9),
+                    (0.2, 22e9),
+                    (0.4, 42e9),
+                    (0.6, 62e9),
+                    (0.8, 82e9),
+                    (0.9, 92e9),
+                ],
+                question,
+            ),
+        ]
+
+        aggregated = await NumericReport.aggregate_predictions(predictions, question)
+        result = aggregated.get_percentiles_at_target_heights()
+        for p in result:
+            assert p.percentile in [
+                pytest.approx(h) for h in [0.1, 0.2, 0.4, 0.6, 0.8, 0.9]
+            ]
+        tenth_percentile_value = result[0].value
+        assert 9e9 < tenth_percentile_value < 15e9
+
+    async def test_aggregate_with_identical_forecasters(self) -> None:
+        question = self._make_question()
+        same_pvs = [
+            (0.1, 30e9),
+            (0.2, 40e9),
+            (0.4, 50e9),
+            (0.6, 60e9),
+            (0.8, 70e9),
+            (0.9, 80e9),
+        ]
+        predictions = [
+            self._make_forecaster_distribution(same_pvs, question) for _ in range(4)
+        ]
+
+        aggregated = await NumericReport.aggregate_predictions(predictions, question)
+        result = aggregated.get_percentiles_at_target_heights()
+        assert result[0].value == pytest.approx(30e9, rel=0.1)
+        assert result[2].value == pytest.approx(50e9, rel=0.1)
+        assert result[5].value == pytest.approx(80e9, rel=0.1)
+
+    async def test_aggregate_with_spread_out_forecasters(self) -> None:
+        """
+        Even with very different forecasters, the aggregate should display
+        with clean percentile heights.
+        """
+        question = self._make_question()
+        predictions = [
+            self._make_forecaster_distribution(
+                [
+                    (0.1, 5e9),
+                    (0.2, 10e9),
+                    (0.4, 20e9),
+                    (0.6, 30e9),
+                    (0.8, 40e9),
+                    (0.9, 50e9),
+                ],
+                question,
+            ),
+            self._make_forecaster_distribution(
+                [
+                    (0.1, 50e9),
+                    (0.2, 60e9),
+                    (0.4, 70e9),
+                    (0.6, 80e9),
+                    (0.8, 90e9),
+                    (0.9, 95e9),
+                ],
+                question,
+            ),
+        ]
+
+        aggregated = await NumericReport.aggregate_predictions(predictions, question)
+        readable = NumericReport.make_readable_prediction(aggregated)
+        assert "10.00%" in readable
+        assert "90.00%" in readable
+
+    def test_individual_forecaster_readable_unchanged(self) -> None:
+        """Individual forecasters with <=10 percentiles still show all their values."""
+        percentiles = [
+            Percentile(value=10.0, percentile=0.1),
+            Percentile(value=20.0, percentile=0.2),
+            Percentile(value=40.0, percentile=0.4),
+            Percentile(value=60.0, percentile=0.6),
+            Percentile(value=80.0, percentile=0.8),
+            Percentile(value=90.0, percentile=0.9),
+        ]
+        dist = NumericDistribution(
+            declared_percentiles=percentiles,
+            open_upper_bound=False,
+            open_lower_bound=False,
+            upper_bound=100.0,
+            lower_bound=0.0,
+            zero_point=None,
+            standardize_cdf=False,
+        )
+        readable = NumericReport.make_readable_prediction(dist)
+        assert "10.00%" in readable
+        assert "20.00%" in readable
+        assert "40.00%" in readable
+        assert "60.00%" in readable
+        assert "80.00%" in readable
+        assert "90.00%" in readable
+        assert readable.count("chance of value below") == 6
+
+    async def test_aggregate_readable_with_narrow_distribution(self) -> None:
+        """
+        When all forecasters predict a very narrow range relative to the question bounds,
+        the aggregate should still show clean percentiles (not weird values from x-axis spacing).
+        """
+        question = self._make_question(lower_bound=0.0, upper_bound=1_000_000_000_000.0)
+        predictions = [
+            self._make_forecaster_distribution(
+                [
+                    (0.1, 99e9),
+                    (0.2, 99.5e9),
+                    (0.4, 100e9),
+                    (0.6, 100.5e9),
+                    (0.8, 101e9),
+                    (0.9, 101.5e9),
+                ],
+                question,
+            ),
+            self._make_forecaster_distribution(
+                [
+                    (0.1, 99e9),
+                    (0.2, 99.5e9),
+                    (0.4, 100e9),
+                    (0.6, 100.5e9),
+                    (0.8, 101e9),
+                    (0.9, 101.5e9),
+                ],
+                question,
+            ),
+        ]
+
+        aggregated = await NumericReport.aggregate_predictions(predictions, question)
+        readable = NumericReport.make_readable_prediction(aggregated)
+        assert "10.00%" in readable
+        assert "90.00%" in readable
diff --git a/conftest.py b/conftest.py
index ca91cd9c..439162df 100644
--- a/conftest.py
+++ b/conftest.py
@@ -1,11 +1,8 @@
 # This file is run before any tests are run in order to configure tests
 
-from typing import Generator
-
 import dotenv
 import pytest
 
-from forecasting_tools.ai_models.agent_wrappers import general_trace_or_span
 from forecasting_tools.util.custom_logger import CustomLogger
 
 
@@ -13,9 +10,3 @@
 def setup_logging() -> None:
     dotenv.load_dotenv()
     CustomLogger.setup_logging()
-
-
-@pytest.fixture(scope="session", autouse=True)
-def wrap_all_tests_in_trace() -> Generator[None, None, None]:
-    with general_trace_or_span("Running tests"):
-        yield  # Run all tests
diff --git a/forecasting_tools/agents_and_tools/other/data_analyzer.py b/forecasting_tools/agents_and_tools/other/data_analyzer.py
index 320a68e8..a380ce72 100644
--- a/forecasting_tools/agents_and_tools/other/data_analyzer.py
+++ b/forecasting_tools/agents_and_tools/other/data_analyzer.py
@@ -12,7 +12,6 @@
     CodingTool,
     agent_tool,
     event_to_tool_message,
-    general_trace_or_span,
 )
 from forecasting_tools.util.misc import clean_indents
 
@@ -119,10 +118,9 @@ def data_analysis_tool(
 
 
 if __name__ == "__main__":
-    with general_trace_or_span("Test Span 1"):
-        answer = asyncio.run(
-            DataAnalyzer().run_data_analysis(
-                instructions="Please multiple 52.675 x 6.547 x 9867.5476 x 4356.5",
-            )
+    answer = asyncio.run(
+        DataAnalyzer().run_data_analysis(
+            instructions="Please multiple 52.675 x 6.547 x 9867.5476 x 4356.5",
         )
+    )
     print(answer)
diff --git a/forecasting_tools/ai_models/agent_wrappers.py b/forecasting_tools/ai_models/agent_wrappers.py
index 0c05541a..1d93263b 100644
--- a/forecasting_tools/ai_models/agent_wrappers.py
+++ b/forecasting_tools/ai_models/agent_wrappers.py
@@ -1,27 +1,11 @@
 import asyncio
 import logging
-import os
-import time
-from typing import Any
 
 import nest_asyncio
-from agents import (
-    Agent,
-    CodeInterpreterTool,
-    FunctionTool,
-    Runner,
-    Span,
-    Trace,
-    custom_span,
-)
+from agents import Agent, CodeInterpreterTool, FunctionTool, Runner
 from agents import function_tool as ft
-from agents import generation_span, trace
 from agents.extensions.models.litellm_model import LitellmModel
-from agents.run import RunConfig
 from agents.stream_events import StreamEvent
-from agents.tracing.setup import GLOBAL_TRACE_PROVIDER
-from agents.tracing.span_data import CustomSpanData, GenerationSpanData
-from agents.tracing.traces import TraceImpl
 
 from forecasting_tools.ai_models.model_tracker import ModelTracker
 
@@ -45,66 +29,11 @@ async def get_response(self, *args, **kwargs):  # NOSONAR
         return response
 
 
-class NoOpContextManager:
-    """A context manager that does nothing when used in with statements"""
-
-    def __enter__(self):
-        return self
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        return False
-
-    @property
-    def trace_id(self) -> str:
-        return "no-op-trace-id"
-
-
-def _current_trace_exists() -> bool:
-    try:
-        if GLOBAL_TRACE_PROVIDER is not None:
-            current_trace = GLOBAL_TRACE_PROVIDER.get_current_trace()
-        else:
-            raise ValueError("GLOBAL_TRACE_PROVIDER is not set")
-    except Exception as e:
-        logger.warning(f"Error getting current trace: {e}")
-        current_trace = None
-    return current_trace is not None
-
-
-def _disable_tracing_based_if_not_configured() -> None:
-    if not os.getenv("OPENAI_API_KEY") and not os.getenv(
-        "OPENAI_AGENTS_DISABLE_TRACING"
-    ):
-        disable_value = "1"
-        os.environ["OPENAI_AGENTS_DISABLE_TRACING"] = disable_value
-        RunConfig.tracing_disabled = True
-
-
-def general_trace_or_span(
-    name: str, data: dict[str, Any] | None = None, **kwargs
-) -> Span[CustomSpanData] | Trace:
-    _disable_tracing_based_if_not_configured()
-    if _current_trace_exists():
-        return custom_span(name, data, **kwargs)
-    else:
-        return trace(workflow_name=name, metadata=data, **kwargs)
-
-
-def track_generation(*args, **kwargs) -> Span[GenerationSpanData]:
-    _disable_tracing_based_if_not_configured()
-    if _current_trace_exists():
-        return generation_span(*args, **kwargs)
-    else:
-        with trace("One Off Generation"):
-            return generation_span(*args, **kwargs)
-
-
 AgentRunner = Runner  # Alias for Runner for later extension
 AgentTool = FunctionTool  # Alias for FunctionTool for later extension
 AiAgent = Agent  # Alias for Agent for later extension
 CodingTool = CodeInterpreterTool  # Alias for CodeInterpreterTool for later extension
 agent_tool = ft  # Alias for function_tool for later extension
-ImplementedTrace = TraceImpl  # Alias for TraceImpl for later extension
 
 
 def event_to_tool_message(event: StreamEvent) -> str | None:
@@ -144,69 +73,3 @@ def event_to_tool_message(event: StreamEvent) -> str | None:
     if text == "":
         return None
     return text
-
-
-if __name__ == "__main__":
-    # Test tracing/spans. See https://platform.openai.com/traces for visual confirmation
-    with trace("Test Trace A"):
-        with track_generation(
-            model="gpt-4o-mini",
-            input=[{"role": "user", "content": "Test Input"}],
-        ):
-            time.sleep(1)
-        with track_generation(
-            model="gpt-4o-mini",
-            input=[{"role": "user", "content": "Test Input"}],
-        ):
-            time.sleep(1)
-            with track_generation(
-                model="gpt-4o-mini",
-                input=[{"role": "user", "content": "Test Input"}],
-            ):
-                time.sleep(1)
-        with custom_span("Test Span 2"):
-            time.sleep(1)
-
-    with custom_span("Test Span 3"):
-        with track_generation(
-            model="gpt-4o-mini",
-            input=[{"role": "user", "content": "Test Input"}],
-        ):
-            time.sleep(1)
-
-    with general_trace_or_span("Test Trace B"):
-        with track_generation(
-            model="gpt-4o-mini",
-            input=[{"role": "user", "content": "Test Input"}],
-        ):
-            time.sleep(1)
-        with track_generation(
-            model="gpt-4o-mini",
-            input=[{"role": "user", "content": "Test Input"}],
-        ):
-            time.sleep(1)
-            with track_generation(
-                model="gpt-4o-mini",
-                input=[{"role": "user", "content": "Test Input"}],
-            ):
-                time.sleep(1)
-                with general_trace_or_span("Test Span 2"):
-                    time.sleep(1)
-
-    with trace("Test Trace C"):
-        with general_trace_or_span("Test Span 1"):
-            with track_generation(
-                model="gpt-4o-mini",
-                input=[{"role": "user", "content": "Test Input"}],
-            ):
-                time.sleep(1)
-            with track_generation(
-                model="gpt-4o-mini",
-                input=[{"role": "user", "content": "Test Input"}],
-            ):
-                time.sleep(1)
-                with track_generation(
-                    model="gpt-4o-mini",
-                    input=[{"role": "user", "content": "Test Input"}],
-                ):
-                    time.sleep(1)
diff --git a/forecasting_tools/ai_models/general_llm.py b/forecasting_tools/ai_models/general_llm.py
index 74c3c66d..681fc7c2 100644
--- a/forecasting_tools/ai_models/general_llm.py
+++ b/forecasting_tools/ai_models/general_llm.py
@@ -21,7 +21,6 @@
     ResponseReasoningItem,
 )
 
-from forecasting_tools.ai_models.agent_wrappers import track_generation
 from forecasting_tools.ai_models.ai_utils.openai_utils import (
     OpenAiUtils,
     VisionMessageData,
@@ -251,16 +250,7 @@ async def _invoke_with_request_cost_time_and_token_limits_and_retry(
     ) -> Any:
         logger.debug(f"Invoking model with prompt: {prompt}")
 
-        with track_generation(
-            input=self.model_input_to_message(prompt),
-            model=self.model,
-        ) as span:
-            direct_call_response = await self._mockable_direct_call_to_model(prompt)
-            answer = direct_call_response.data
-            span.span_data.output = [{"role": "assistant", "content": answer}]
-            # span.span_data.usage = usage.model_dump()
-            span.span_data.model = self.model
-            span.span_data.model_config = self.litellm_kwargs
+        direct_call_response = await self._mockable_direct_call_to_model(prompt)
 
         logger.debug(f"Model responded with: {direct_call_response}")
         return direct_call_response
diff --git a/forecasting_tools/auto_optimizers/prompt_optimizer.py b/forecasting_tools/auto_optimizers/prompt_optimizer.py
index 8adeecc5..e8968f33 100644
--- a/forecasting_tools/auto_optimizers/prompt_optimizer.py
+++ b/forecasting_tools/auto_optimizers/prompt_optimizer.py
@@ -9,12 +9,7 @@
 from forecasting_tools.agents_and_tools.minor_tools import (
     perplexity_reasoning_pro_search,
 )
-from forecasting_tools.ai_models.agent_wrappers import (
-    AgentRunner,
-    AgentSdkLlm,
-    AiAgent,
-    general_trace_or_span,
-)
+from forecasting_tools.ai_models.agent_wrappers import AgentRunner, AgentSdkLlm, AiAgent
 from forecasting_tools.auto_optimizers.prompt_data_models import PromptIdea
 from forecasting_tools.helpers.structure_output import structure_output
 from forecasting_tools.util.misc import clean_indents, retry_async_function
@@ -112,63 +107,57 @@ def __init__(
             )
 
     async def create_optimized_prompt(self) -> OptimizationRun:
-        with general_trace_or_span("Prompt Optimizer"):
-            return await self._create_optimized_prompt()
+        return await self._create_optimized_prompt()
 
     async def _create_optimized_prompt(self) -> OptimizationRun:
         iteration_num = 0
-        with general_trace_or_span("Initial Population Generation (Iteration 1)"):
-            iteration_num += 1
-            logger.info(
-                f"Generating initial prompt population of size {self.initial_prompt_population_size}"
-            )
-            seed_prompt = ImplementedPrompt(
-                text=self.initial_prompt,
-                idea=PromptIdea(
-                    short_name="Initial Seed",
-                    full_text="The user-provided initial prompt",
-                ),
-                originating_ideas=[],
-            )
-            starting_prompts: list[ImplementedPrompt] = [seed_prompt]
-            prompts_still_needed = self.initial_prompt_population_size - len(
-                starting_prompts
-            )
-            if prompts_still_needed > 0:
-                additional_initial_prompts = await self._mutate_prompt(
-                    starting_prompts[0],
-                    prompts_still_needed,
-                )
-                starting_prompts.extend(additional_initial_prompts)
-
-            offspring_prompts: list[ImplementedPrompt] = starting_prompts
-            assert (
-                seed_prompt in offspring_prompts
-            ), "Seed prompt not found in offspring prompts"
-            all_evaluated_prompts: list[ScoredPrompt] = (
-                await self._evaluate_new_members(offspring_prompts)
+        iteration_num += 1
+        logger.info(
+            f"Generating initial prompt population of size {self.initial_prompt_population_size}"
+        )
+        seed_prompt = ImplementedPrompt(
+            text=self.initial_prompt,
+            idea=PromptIdea(
+                short_name="Initial Seed",
+                full_text="The user-provided initial prompt",
+            ),
+            originating_ideas=[],
+        )
+        starting_prompts: list[ImplementedPrompt] = [seed_prompt]
+        prompts_still_needed = self.initial_prompt_population_size - len(
+            starting_prompts
+        )
+        if prompts_still_needed > 0:
+            additional_initial_prompts = await self._mutate_prompt(
+                starting_prompts[0],
+                prompts_still_needed,
             )
-            survivors = await self._kill_the_weak(all_evaluated_prompts)
+            starting_prompts.extend(additional_initial_prompts)
+
+        offspring_prompts: list[ImplementedPrompt] = starting_prompts
+        assert (
+            seed_prompt in offspring_prompts
+        ), "Seed prompt not found in offspring prompts"
+        all_evaluated_prompts: list[ScoredPrompt] = await self._evaluate_new_members(
+            offspring_prompts
+        )
+        survivors = await self._kill_the_weak(all_evaluated_prompts)
 
         while iteration_num < self.iterations:
             iteration_num += 1
-            with general_trace_or_span(
-                f"Prompt Optimizer Iteration {iteration_num + 1}",
-                data={"survivors": [s.model_dump() for s in survivors]},
-            ):
-                logger.info(
-                    f"Starting iteration {iteration_num + 1}/{self.iterations} - Current population size: {len(offspring_prompts)}"
-                )
+            logger.info(
+                f"Starting iteration {iteration_num + 1}/{self.iterations} - Current population size: {len(offspring_prompts)}"
+            )
 
-                offspring_prompts = await self._generate_new_prompts(survivors)
+            offspring_prompts = await self._generate_new_prompts(survivors)
 
-                evaluated_prompts = await self._evaluate_new_members(offspring_prompts)
-                all_evaluated_prompts.extend(evaluated_prompts)
-                updated_population = survivors + evaluated_prompts
+            evaluated_prompts = await self._evaluate_new_members(offspring_prompts)
+            all_evaluated_prompts.extend(evaluated_prompts)
+            updated_population = survivors + evaluated_prompts
 
-                survivors = await self._kill_the_weak(updated_population)
+            survivors = await self._kill_the_weak(updated_population)
 
-                self._log_duplicate_prompts(all_evaluated_prompts)
+            self._log_duplicate_prompts(all_evaluated_prompts)
 
         return OptimizationRun(scored_prompts=all_evaluated_prompts)
 
diff --git a/forecasting_tools/cp_benchmarking/benchmarker.py b/forecasting_tools/cp_benchmarking/benchmarker.py
index 9bb81d0b..759f1432 100644
--- a/forecasting_tools/cp_benchmarking/benchmarker.py
+++ b/forecasting_tools/cp_benchmarking/benchmarker.py
@@ -5,7 +5,6 @@
 
 import typeguard
 
-from forecasting_tools.ai_models.agent_wrappers import general_trace_or_span
 from forecasting_tools.ai_models.resource_managers.monetary_cost_manager import (
     MonetaryCostManager,
 )
@@ -80,50 +79,44 @@ def __init__(
         self.code_to_snapshot = additional_code_to_snapshot
 
     async def run_benchmark(self) -> list[BenchmarkForBot]:
-        with general_trace_or_span("Benchmarker"):
-            if self.questions_to_use is None:
-                assert (
-                    self.number_of_questions_to_use is not None
-                ), "number_of_questions_to_use must be provided if questions_to_use is not provided"
-                chosen_questions = MetaculusApi.get_benchmark_questions(
-                    self.number_of_questions_to_use,
-                )
-            else:
-                chosen_questions = self.questions_to_use
-
-            chosen_questions = typeguard.check_type(
-                chosen_questions, list[MetaculusQuestion]
-            )
-
-            if self.number_of_questions_to_use is not None:
-                assert len(chosen_questions) == self.number_of_questions_to_use
-
-            benchmarks: list[BenchmarkForBot] = self._initialize_benchmarks(
-                self.forecast_bots, chosen_questions
+        if self.questions_to_use is None:
+            assert (
+                self.number_of_questions_to_use is not None
+            ), "number_of_questions_to_use must be provided if questions_to_use is not provided"
+            chosen_questions = MetaculusApi.get_benchmark_questions(
+                self.number_of_questions_to_use,
             )
-
-            batches = self._batch_questions(
-                self.forecast_bots,
-                benchmarks,
-                chosen_questions,
-                self.concurrent_question_batch_size,
+        else:
+            chosen_questions = self.questions_to_use
+
+        chosen_questions = typeguard.check_type(
+            chosen_questions, list[MetaculusQuestion]
+        )
+
+        if self.number_of_questions_to_use is not None:
+            assert len(chosen_questions) == self.number_of_questions_to_use
+
+        benchmarks: list[BenchmarkForBot] = self._initialize_benchmarks(
+            self.forecast_bots, chosen_questions
+        )
+
+        batches = self._batch_questions(
+            self.forecast_bots,
+            benchmarks,
+            chosen_questions,
+            self.concurrent_question_batch_size,
+        )
+        try:
+            for i, batch in enumerate(batches):
+                await self._run_a_batch(batch)
+                if batch.is_last_batch_for_benchmark:
+                    self._append_benchmarks_to_jsonl_if_configured([batch.benchmark])
+        except KeyboardInterrupt:
+            logger.warning(
+                "KeyboardInterrupt detected, saving current benchmark progress."
             )
-            try:
-                for i, batch in enumerate(batches):
-                    with general_trace_or_span(
-                        f"{batch.benchmark.name} - Batch {i+1} of {len(batches)}"
-                    ):
-                        await self._run_a_batch(batch)
-                    if batch.is_last_batch_for_benchmark:
-                        self._append_benchmarks_to_jsonl_if_configured(
-                            [batch.benchmark]
-                        )
-            except KeyboardInterrupt:
-                logger.warning(
-                    "KeyboardInterrupt detected, saving current benchmark progress."
-                )
-                self._append_benchmarks_to_jsonl_if_configured([batch.benchmark])
-                raise
+            self._append_benchmarks_to_jsonl_if_configured([batch.benchmark])
+            raise
         return benchmarks
 
     async def _run_a_batch(self, batch: QuestionBatch) -> None:
diff --git a/forecasting_tools/data_models/numeric_report.py b/forecasting_tools/data_models/numeric_report.py
index b99f3c2c..7e12dbed 100644
--- a/forecasting_tools/data_models/numeric_report.py
+++ b/forecasting_tools/data_models/numeric_report.py
@@ -314,6 +314,22 @@ def get_representative_percentiles(
         ]
         return representative_percentiles
 
+    def get_percentiles_at_target_heights(
+        self, target_heights: list[float] | None = None
+    ) -> list[Percentile]:
+        if target_heights is None:
+            target_heights = [0.1, 0.2, 0.4, 0.6, 0.8, 0.9]
+
+        heights = [p.percentile for p in self.declared_percentiles]
+        values = [p.value for p in self.declared_percentiles]
+
+        result = []
+        for target in target_heights:
+            interpolated_value = float(np.interp(target, heights, values))
+            result.append(Percentile(percentile=target, value=interpolated_value))
+
+        return result
+
     @property
     @typing_extensions.deprecated(
         "NumericDistribution.cdf (property) will be replaced with NumericDistribution.get_cdf (method). Please switch.",
@@ -633,12 +649,9 @@ async def aggregate_predictions(
     def make_readable_prediction(cls, prediction: NumericDistribution) -> str:
         num_percentiles = len(prediction.declared_percentiles)
         if num_percentiles > 10:
-            num_display_percentiles = 5
+            representative_percentiles = prediction.get_percentiles_at_target_heights()
         else:
-            num_display_percentiles = num_percentiles
-        representative_percentiles = prediction.get_representative_percentiles(
-            num_display_percentiles
-        )
+            representative_percentiles = prediction.declared_percentiles
         readable = "Probability distribution:\n"
         for percentile in representative_percentiles:
             if prediction.is_date:
diff --git a/forecasting_tools/forecast_bots/forecast_bot.py b/forecasting_tools/forecast_bots/forecast_bot.py
index 8a720c38..2f71ed16 100644
--- a/forecasting_tools/forecast_bots/forecast_bot.py
+++ b/forecasting_tools/forecast_bots/forecast_bot.py
@@ -12,7 +12,6 @@
 from exceptiongroup import ExceptionGroup
 from pydantic import BaseModel
 
-from forecasting_tools.ai_models.agent_wrappers import general_trace_or_span
 from forecasting_tools.ai_models.general_llm import GeneralLlm
 from forecasting_tools.ai_models.resource_managers.monetary_cost_manager import (
     MonetaryCostManager,
@@ -338,20 +337,17 @@ def make_llm_dict(self) -> dict[str, str | dict[str, Any] | None]:
     async def _run_individual_question_with_error_propagation(
         self, question: MetaculusQuestion
     ) -> ForecastReport:
-        with general_trace_or_span(
-            f"{self.__class__.__name__} - Question: {question.page_url}"
-        ):
-            try:
-                return await self._run_individual_question(question)
-            except Exception as e:
-                error_message = (
-                    f"Error while processing question url: '{question.page_url}'"
-                )
-                logger.error(f"{error_message}: {e}")
-                self._reraise_exception_with_prepended_message(e, error_message)
-                assert (
-                    False
-                ), "This is to satisfy type checker. The previous function should raise an exception"
+        try:
+            return await self._run_individual_question(question)
+        except Exception as e:
+            error_message = (
+                f"Error while processing question url: '{question.page_url}'"
+            )
+            logger.error(f"{error_message}: {e}")
+            self._reraise_exception_with_prepended_message(e, error_message)
+            assert (
+                False
+            ), "This is to satisfy type checker. The previous function should raise an exception"
 
     async def _run_individual_question(
         self, question: MetaculusQuestion
diff --git a/forecasting_tools/front_end/app_pages/chat_page.py b/forecasting_tools/front_end/app_pages/chat_page.py
index f550f8b5..26fe98ac 100644
--- a/forecasting_tools/front_end/app_pages/chat_page.py
+++ b/forecasting_tools/front_end/app_pages/chat_page.py
@@ -43,7 +43,6 @@
     AgentTool,
     AiAgent,
     event_to_tool_message,
-    general_trace_or_span,
 )
 from forecasting_tools.ai_models.resource_managers.monetary_cost_manager import (
     MonetaryCostManager,
@@ -84,7 +83,6 @@ class ChatSession(BaseModel, Jsonable):
     name: str
     messages: list[dict]
     model_choice: str = DEFAULT_MODEL
-    trace_id: str | None = None
     last_chat_cost: float | None = None
     last_chat_duration: float | None = None
     time_stamp: datetime = Field(default_factory=datetime.now)
@@ -235,11 +233,6 @@ def display_chat_metadata(cls) -> None:
                 st.markdown(
                     f"**Last Chat Duration:** {st.session_state.last_chat_duration:.2f} seconds"
                 )
-            if "trace_id" in st.session_state.keys():
-                trace_id = st.session_state.trace_id
-                st.markdown(
-                    f"**Conversation in Foresight Project:** [link](https://platform.openai.com/traces/trace?trace_id={trace_id})"
-                )
 
     @classmethod
     def display_premade_examples(cls) -> None:
@@ -265,8 +258,6 @@ def display_premade_examples(cls) -> None:
                     if st.button(session.name, key=session.name):
                         st.session_state.messages = session.messages
                         st.session_state.model_choice = session.model_choice
-                        if session.trace_id:
-                            st.session_state.trace_id = session.trace_id
                         if session.last_chat_cost:
                             st.session_state.last_chat_cost = session.last_chat_cost
                         if session.last_chat_duration:
@@ -299,7 +290,6 @@ def display_premade_examples(cls) -> None:
                         name=st.session_state["chat_save_name"],
                         model_choice=st.session_state["model_choice"],
                         messages=st.session_state.messages,
-                        trace_id=st.session_state.trace_id,
                         last_chat_cost=st.session_state.last_chat_cost,
                         last_chat_duration=st.session_state.last_chat_duration,
                     )
@@ -464,29 +454,27 @@ async def generate_response(
             handoffs=[],
         )
 
-        with general_trace_or_span("Chat App") as chat_trace:
-            result = AgentRunner.run_streamed(
-                agent, st.session_state.messages, max_turns=20
-            )
-            streamed_text = ""
-            with st.chat_message("assistant"):
-                placeholder = st.empty()
-            with st.spinner("Thinking..."):
-                async for event in result.stream_events():
-                    if event.type == "raw_response_event" and isinstance(
-                        event.data, ResponseTextDeltaEvent
-                    ):
-                        streamed_text += event.data.delta
-                    placeholder.write(streamed_text)
-
-                    new_reasoning = event_to_tool_message(event)
-                    if new_reasoning:
-                        st.sidebar.write(new_reasoning)
-
-            # logger.info(f"Chat finished with output: {streamed_text}")
-            st.session_state.messages = result.to_input_list()
-            st.session_state.trace_id = chat_trace.trace_id
-            cls._update_last_message_if_gemini_bug(model_choice)
+        result = AgentRunner.run_streamed(
+            agent, st.session_state.messages, max_turns=20
+        )
+        streamed_text = ""
+        with st.chat_message("assistant"):
+            placeholder = st.empty()
+        with st.spinner("Thinking..."):
+            async for event in result.stream_events():
+                if event.type == "raw_response_event" and isinstance(
+                    event.data, ResponseTextDeltaEvent
+                ):
+                    streamed_text += event.data.delta
+                placeholder.write(streamed_text)
+
+                new_reasoning = event_to_tool_message(event)
+                if new_reasoning:
+                    st.sidebar.write(new_reasoning)
+
+        # logger.info(f"Chat finished with output: {streamed_text}")
+        st.session_state.messages = result.to_input_list()
+        cls._update_last_message_if_gemini_bug(model_choice)
 
         ForecastDatabaseManager.add_general_report_to_database(
             question_text=prompt_input,
@@ -519,7 +507,6 @@ def _update_last_message_if_gemini_bug(cls, model_choice: str) -> None:
     @classmethod
     def clear_chat_history(cls) -> None:
         st.session_state.messages = [cls.DEFAULT_MESSAGE]
-        st.session_state.trace_id = None
         st.session_state.chat_files = []
 
 
diff --git a/poetry.lock b/poetry.lock
index 2a649ca2..1ab5b773 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -245,14 +245,14 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.12.1"
+version = "4.13.0"
 description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main", "dev"]
 files = [
-    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
-    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
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+    {file = "anyio-4.13.0.tar.gz", hash = "sha256:334b70e641fd2221c1505b3890c69882fe4a2df910cba14d97019b90b24439dc"},
 ]
 
 [package.dependencies]
@@ -260,7 +260,7 @@ idna = ">=2.8"
 typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
 
 [package.extras]
-trio = ["trio (>=0.31.0) ; python_version < \"3.10\"", "trio (>=0.32.0) ; python_version >= \"3.10\""]
+trio = ["trio (>=0.32.0)"]
 
 [[package]]
 name = "appnope"
@@ -369,13 +369,13 @@ tests = ["mypy (>=1.14.0)", "pytest", "pytest-asyncio"]
 
 [[package]]
 name = "asknews"
-version = "0.13.19"
+version = "0.13.34"
 description = "Python SDK for AskNews"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
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+    {file = "asknews-0.13.34-py3-none-any.whl", hash = "sha256:73806377804fa03a4a40d7618466ad546893bac417bb377476099e03ed6f3036"},
 ]
 
 [package.dependencies]
@@ -404,14 +404,14 @@ test = ["astroid (>=2,<5)", "pytest (<9.0)", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "async-lru"
-version = "2.2.0"
+version = "2.3.0"
 description = "Simple LRU cache for asyncio"
 optional = false
 python-versions = ">=3.10"
 groups = ["dev"]
 files = [
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-    {file = "async_lru-2.2.0.tar.gz", hash = "sha256:80abae2a237dbc6c60861d621619af39f0d920aea306de34cb992c879e01370c"},
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+    {file = "async_lru-2.3.0.tar.gz", hash = "sha256:89bdb258a0140d7313cf8f4031d816a042202faa61d0ab310a0a538baa1c24b6"},
 ]
 
 [[package]]
@@ -428,14 +428,14 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "25.4.0"
+version = "26.1.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.9"
 groups = ["main", "dev"]
 files = [
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+    {file = "attrs-26.1.0.tar.gz", hash = "sha256:d03ceb89cb322a8fd706d4fb91940737b6642aa36998fe130a9bc96c985eff32"},
 ]
 
 [[package]]
@@ -509,26 +509,26 @@ files = [
 
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-version = "6.2.6"
+version = "7.0.5"
 description = "Extensible memoizing collections and decorators"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
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 [[package]]
 name = "certifi"
-version = "2026.1.4"
+version = "2026.2.25"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.7"
 groups = ["main", "dev"]
 files = [
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-    {file = "certifi-2026.1.4.tar.gz", hash = "sha256:ac726dd470482006e014ad384921ed6438c457018f4b3d204aea4281258b2120"},
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 ]
 
 [[package]]
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+version = "3.4.6"
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 python-versions = ">=3.7"
 groups = ["main", "dev"]
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 ]
 
 [package.extras]
@@ -1773,37 +1792,36 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "1.4.1"
+version = "1.8.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.9.0"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
-filelock = "*"
+filelock = ">=3.10.0"
 fsspec = ">=2023.5.0"
-hf-xet = {version = ">=1.2.0,<2.0.0", markers = "platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"arm64\" or platform_machine == \"aarch64\""}
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 httpx = ">=0.23.0,<1"
 packaging = ">=20.9"
 pyyaml = ">=5.1"
-shellingham = "*"
 tqdm = ">=4.42.1"
-typer-slim = "*"
+typer = "*"
 typing-extensions = ">=4.1.0"
 
 [package.extras]
-all = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
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+dev = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "duckdb", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0)", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
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-hf-xet = ["hf-xet (>=1.2.0,<2.0.0)"]
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 oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
 quality = ["libcst (>=1.4.0)", "mypy (==1.15.0)", "ruff (>=0.9.0)", "ty"]
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+testing = ["Jinja2", "Pillow", "authlib (>=1.3.2)", "duckdb", "fastapi", "fastapi", "httpx", "itsdangerous", "jedi", "numpy", "pytest (>=8.4.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
 torch = ["safetensors[torch]", "torch"]
 typing = ["types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
 
@@ -1826,14 +1844,14 @@ pydantic = ">=2.0,<3"
 
 [[package]]
 name = "identify"
-version = "2.6.16"
+version = "2.6.18"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.10"
 groups = ["dev"]
 files = [
-    {file = "identify-2.6.16-py2.py3-none-any.whl", hash = "sha256:391ee4d77741d994189522896270b787aed8670389bfd60f326d677d64a6dfb0"},
-    {file = "identify-2.6.16.tar.gz", hash = "sha256:846857203b5511bbe94d5a352a48ef2359532bc8f6727b5544077a0dcfb24980"},
+    {file = "identify-2.6.18-py2.py3-none-any.whl", hash = "sha256:8db9d3c8ea9079db92cafb0ebf97abdc09d52e97f4dcf773a2e694048b7cd737"},
+    {file = "identify-2.6.18.tar.gz", hash = "sha256:873ac56a5e3fd63e7438a7ecbc4d91aca692eb3fefa4534db2b7913f3fc352fd"},
 ]
 
 [package.extras]
@@ -1856,27 +1874,27 @@ all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2
 
 [[package]]
 name = "importlib-metadata"
-version = "8.7.1"
+version = "9.0.0"
 description = "Read metadata from Python packages"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "importlib_metadata-8.7.1-py3-none-any.whl", hash = "sha256:5a1f80bf1daa489495071efbb095d75a634cf28a8bc299581244063b53176151"},
-    {file = "importlib_metadata-8.7.1.tar.gz", hash = "sha256:49fef1ae6440c182052f407c8d34a68f72efc36db9ca90dc0113398f2fdde8bb"},
+    {file = "importlib_metadata-9.0.0-py3-none-any.whl", hash = "sha256:2d21d1cc5a017bd0559e36150c21c830ab1dc304dedd1b7ea85d20f45ef3edd7"},
+    {file = "importlib_metadata-9.0.0.tar.gz", hash = "sha256:a4f57ab599e6a2e3016d7595cfd72eb4661a5106e787a95bcc90c7105b831efc"},
 ]
 
 [package.dependencies]
 zipp = ">=3.20"
 
 [package.extras]
-check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
+check = ["pytest-checkdocs (>=2.14)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
 cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 enabler = ["pytest-enabler (>=3.4)"]
 perf = ["ipython"]
-test = ["flufl.flake8", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
-type = ["mypy (<1.19) ; platform_python_implementation == \"PyPy\"", "pytest-mypy (>=1.0.1)"]
+test = ["packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
+type = ["pytest-mypy (>=1.0.1) ; platform_python_implementation != \"PyPy\""]
 
 [[package]]
 name = "iniconfig"
@@ -1926,14 +1944,15 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0,<9)", "pytest-async
 
 [[package]]
 name = "ipython"
-version = "9.10.0"
+version = "9.10.1"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.11"
 groups = ["dev"]
+markers = "python_version == \"3.11\""
 files = [
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 ]
 
 [package.dependencies]
@@ -1957,6 +1976,39 @@ matplotlib = ["matplotlib (>3.9)"]
 test = ["packaging (>=20.1.0)", "pytest (>=7.0.0)", "pytest-asyncio (>=1.0.0)", "setuptools (>=61.2)", "testpath (>=0.2)"]
 test-extra = ["curio", "ipykernel (>6.30)", "ipython[matplotlib]", "ipython[test]", "jupyter_ai", "nbclient", "nbformat", "numpy (>=1.27)", "pandas (>2.1)", "trio (>=0.1.0)"]
 
+[[package]]
+name = "ipython"
+version = "9.12.0"
+description = "IPython: Productive Interactive Computing"
+optional = false
+python-versions = ">=3.12"
+groups = ["dev"]
+markers = "python_version >= \"3.12\""
+files = [
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+]
+
+[package.dependencies]
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+decorator = ">=5.1.0"
+ipython-pygments-lexers = ">=1.0.0"
+jedi = ">=0.18.2"
+matplotlib-inline = ">=0.1.6"
+pexpect = {version = ">4.6", markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\""}
+prompt_toolkit = ">=3.0.41,<3.1.0"
+pygments = ">=2.14.0"
+stack_data = ">=0.6.0"
+traitlets = ">=5.13.0"
+
+[package.extras]
+all = ["argcomplete (>=3.0)", "ipython[doc,matplotlib,terminal,test,test-extra]", "types-decorator"]
+black = ["black"]
+doc = ["docrepr", "exceptiongroup", "intersphinx_registry", "ipykernel", "ipython[matplotlib,test]", "setuptools (>=80.0)", "sphinx (>=8.0)", "sphinx-rtd-theme (>=0.1.8)", "sphinx_toml (==0.0.4)", "typing_extensions"]
+matplotlib = ["matplotlib (>3.9)"]
+test = ["packaging (>=23.0.0)", "pytest (>=7.0.0)", "pytest-asyncio (>=1.0.0)", "setuptools (>=80.0)", "testpath (>=0.2)"]
+test-extra = ["curio", "ipykernel (>6.30)", "ipython[matplotlib]", "ipython[test]", "jupyter_ai", "nbclient", "nbformat", "numpy (>=2.0)", "pandas (>2.1)", "trio (>=0.22.0)"]
+
 [[package]]
 name = "ipython-pygments-lexers"
 version = "1.1.1"
@@ -2163,14 +2215,14 @@ files = [
 
 [[package]]
 name = "jsonpointer"
-version = "3.0.0"
-description = "Identify specific nodes in a JSON document (RFC 6901)"
+version = "3.1.1"
+description = "Identify specific nodes in a JSON document (RFC 6901) "
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.10"
 groups = ["dev"]
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 ]
 
 [[package]]
@@ -2376,14 +2428,14 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.5.5"
+version = "4.5.6"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
@@ -2448,113 +2500,129 @@ test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-v
 
 [[package]]
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 [[package]]
@@ -2577,14 +2645,14 @@ regex = ["regex"]
 
 [[package]]
 name = "litellm"
-version = "1.81.14"
+version = "1.82.2"
 description = "Library to easily interface with LLM API providers"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -2603,11 +2671,11 @@ tokenizers = "*"
 
 [package.extras]
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 ]
 
 [[package]]
@@ -4483,14 +4551,14 @@ windows-terminal = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "pyjwt"
-version = "2.11.0"
+version = "2.12.1"
 description = "JSON Web Token implementation in Python"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -4696,15 +4764,35 @@ files = [
 six = ">=1.5"
 
 [[package]]
-name = "python-dotenv"
+name = "python-discovery"
 version = "1.2.1"
+description = "Python interpreter discovery"
+optional = false
+python-versions = ">=3.8"
+groups = ["dev"]
+files = [
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+]
+
+[package.dependencies]
+filelock = ">=3.15.4"
+platformdirs = ">=4.3.6,<5"
+
+[package.extras]
+docs = ["furo (>=2025.12.19)", "sphinx (>=9.1)", "sphinx-autodoc-typehints (>=3.6.3)", "sphinxcontrib-mermaid (>=2)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.5.4)", "pytest (>=8.3.5)", "pytest-mock (>=3.14)", "setuptools (>=75.1)"]
+
+[[package]]
+name = "python-dotenv"
+version = "1.2.2"
 description = "Read key-value pairs from a .env file and set them as environment variables"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.extras]
@@ -4757,14 +4845,14 @@ unidecode = ["Unidecode (>=1.1.1)"]
 
 [[package]]
 name = "pytz"
-version = "2025.2"
+version = "2026.1.post1"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
 groups = ["main", "dev"]
 files = [
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+    {file = "pytz-2026.1.post1-py2.py3-none-any.whl", hash = "sha256:f2fd16142fda348286a75e1a524be810bb05d444e5a081f37f7affc635035f7a"},
+    {file = "pytz-2026.1.post1.tar.gz", hash = "sha256:3378dde6a0c3d26719182142c56e60c7f9af7e968076f31aae569d72a0358ee1"},
 ]
 
 [[package]]
@@ -5157,25 +5245,26 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.32.5"
+version = "2.33.0"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main", "dev"]
 files = [
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+    {file = "requests-2.33.0.tar.gz", hash = "sha256:c7ebc5e8b0f21837386ad0e1c8fe8b829fa5f544d8df3b2253bff14ef29d7652"},
 ]
 
 [package.dependencies]
-certifi = ">=2017.4.17"
+certifi = ">=2023.5.7"
 charset_normalizer = ">=2,<4"
 idna = ">=2.5,<4"
-urllib3 = ">=1.21.1,<3"
+urllib3 = ">=1.26,<3"
 
 [package.extras]
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
-use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
+test = ["PySocks (>=1.5.6,!=1.5.7)", "pytest (>=3)", "pytest-cov", "pytest-httpbin (==2.1.0)", "pytest-mock", "pytest-xdist"]
+use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"]
 
 [[package]]
 name = "rfc3339-validator"
@@ -5525,19 +5614,19 @@ test = ["pytest (>=8)"]
 
 [[package]]
 name = "setuptools"
-version = "82.0.0"
-description = "Easily download, build, install, upgrade, and uninstall Python packages"
+version = "82.0.1"
+description = "Most extensible Python build backend with support for C/C++ extension modules"
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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+    {file = "setuptools-82.0.1-py3-none-any.whl", hash = "sha256:a59e362652f08dcd477c78bb6e7bd9d80a7995bc73ce773050228a348ce2e5bb"},
+    {file = "setuptools-82.0.1.tar.gz", hash = "sha256:7d872682c5d01cfde07da7bccc7b65469d3dca203318515ada1de5eda35efbf9"},
 ]
 
 [package.extras]
 check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\"", "ruff (>=0.13.0) ; sys_platform != \"cygwin\""]
-core = ["importlib_metadata (>=6) ; python_version < \"3.10\"", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1) ; python_version < \"3.11\"", "wheel (>=0.43.0)"]
+core = ["importlib_metadata (>=6) ; python_version < \"3.10\"", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "tomli (>=2.0.1) ; python_version < \"3.11\"", "wheel (>=0.43.0)"]
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 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
 enabler = ["pytest-enabler (>=2.2)"]
@@ -5570,14 +5659,14 @@ files = [
 
 [[package]]
 name = "smmap"
-version = "5.0.2"
+version = "5.0.3"
 description = "A pure Python implementation of a sliding window memory map manager"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
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 ]
 
 [[package]]
@@ -5606,14 +5695,14 @@ files = [
 
 [[package]]
 name = "sse-starlette"
-version = "3.2.0"
+version = "3.3.3"
 description = "SSE plugin for Starlette"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -5648,14 +5737,14 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "starlette"
-version = "0.52.1"
+version = "1.0.0"
 description = "The little ASGI library that shines."
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -5667,20 +5756,20 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "streamlit"
-version = "1.54.0"
+version = "1.55.0"
 description = "A faster way to build and share data apps"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 [package.dependencies]
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 blinker = ">=1.5.0,<2"
-cachetools = ">=5.5,<7"
+cachetools = ">=5.5,<8"
 click = ">=7.0,<9"
 gitpython = ">=3.0.7,<3.1.19 || >3.1.19,<4"
 numpy = ">=1.23,<3"
@@ -6058,50 +6147,63 @@ files = [
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 ]
 
+[[package]]
+name = "tomli-w"
+version = "1.2.0"
+description = "A lil' TOML writer"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
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+]
+
 [[package]]
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-version = "6.5.4"
+version = "6.5.5"
 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
 optional = false
 python-versions = ">=3.9"
 groups = ["main", "dev"]
 files = [
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 ]
 
 [[package]]
 name = "tox"
-version = "4.35.0"
+version = "4.50.3"
 description = "tox is a generic virtualenv management and test command line tool"
 optional = false
 python-versions = ">=3.10"
 groups = ["dev"]
 files = [
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 [package.dependencies]
-cachetools = ">=6.2.5"
-chardet = ">=5.2"
+cachetools = ">=7.0.3"
 colorama = ">=0.4.6"
-filelock = ">=3.20.3"
+filelock = ">=3.25"
 packaging = ">=26"
-platformdirs = ">=4.5.1"
+platformdirs = ">=4.9.4"
 pluggy = ">=1.6"
 pyproject-api = ">=1.10"
-virtualenv = ">=20.36.1"
+tomli-w = ">=1.2"
+virtualenv = ">=21.1"
+
+[package.extras]
+completion = ["argcomplete (>=3.6.3)"]
 
 [[package]]
 name = "tqdm"
@@ -6196,31 +6298,16 @@ click = ">=8.2.1"
 rich = ">=12.3.0"
 shellingham = ">=1.3.0"
 
-[[package]]
-name = "typer-slim"
-version = "0.24.0"
-description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
-optional = false
-python-versions = ">=3.10"
-groups = ["main"]
-files = [
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-]
-
-[package.dependencies]
-typer = ">=0.24.0"
-
 [[package]]
 name = "types-requests"
-version = "2.32.4.20260107"
+version = "2.33.0.20260327"
 description = "Typing stubs for requests"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -6312,15 +6399,15 @@ zstd = ["backports-zstd (>=1.0.0) ; python_version < \"3.14\""]
 
 [[package]]
 name = "uvicorn"
-version = "0.41.0"
+version = "0.42.0"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 markers = "sys_platform != \"emscripten\""
 files = [
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 ]
 
 [package.dependencies]
@@ -6332,20 +6419,21 @@ standard = ["colorama (>=0.4) ; sys_platform == \"win32\"", "httptools (>=0.6.3)
 
 [[package]]
 name = "virtualenv"
-version = "20.39.0"
+version = "21.2.0"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
 files = [
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+    {file = "virtualenv-21.2.0.tar.gz", hash = "sha256:1720dc3a62ef5b443092e3f499228599045d7fea4c79199770499df8becf9098"},
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 [package.dependencies]
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 filelock = {version = ">=3.24.2,<4", markers = "python_version >= \"3.10\""}
 platformdirs = ">=3.9.1,<5"
+python-discovery = ">=1"
 
 [[package]]
 name = "watchdog"
@@ -6446,142 +6534,140 @@ test = ["pytest", "websockets"]
 
 [[package]]
 name = "yarl"
-version = "1.22.0"
+version = "1.23.0"
 description = "Yet another URL library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
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