diff --git a/continuous_eval/data_downloader.py b/continuous_eval/data_downloader.py
index 515074b..80dae6d 100644
--- a/continuous_eval/data_downloader.py
+++ b/continuous_eval/data_downloader.py
@@ -69,8 +69,8 @@ def example_data_downloader(
         out_dir = destination_dir / resource
         return _download_and_extract_zip(EXAMPLES_DATA_URL + res["filename"], out_dir, force_download=force_download)
     elif res["type"] == "chromadb":
-        from langchain.embeddings.openai import OpenAIEmbeddings
-        from langchain.vectorstores import Chroma
+        from langchain_chroma import Chroma
+        from langchain_openai import OpenAIEmbeddings
 
         out_dir = destination_dir / resource
         _download_and_extract_zip(EXAMPLES_DATA_URL + res["filename"], out_dir, force_download=force_download)
diff --git a/continuous_eval/eval/__init__.py b/continuous_eval/eval/__init__.py
index 599599f..27691c8 100644
--- a/continuous_eval/eval/__init__.py
+++ b/continuous_eval/eval/__init__.py
@@ -6,3 +6,4 @@
     CalledTools,
 )
 from continuous_eval.eval.dataset import Dataset
+from continuous_eval.eval.runner import EvaluationRunner
diff --git a/continuous_eval/eval/dataset.py b/continuous_eval/eval/dataset.py
index c6285af..71c4eb9 100644
--- a/continuous_eval/eval/dataset.py
+++ b/continuous_eval/eval/dataset.py
@@ -5,11 +5,11 @@
 
 import yaml
 
-from continuous_eval.eval.types import UUID, ToolCall
+from continuous_eval.eval.types import UID, ToolCall
 from continuous_eval.eval.utils import type_hint_to_str
 
 _SAFE_DICT = {k: v for k, v in typing.__dict__.items() if not k.startswith("__")}
-_SAFE_DICT["UUID"] = UUID
+_SAFE_DICT["UID"] = UID
 _SAFE_DICT["ToolCall"] = ToolCall
 
 
diff --git a/continuous_eval/eval/logger.py b/continuous_eval/eval/logger.py
new file mode 100644
index 0000000..fbd3f9a
--- /dev/null
+++ b/continuous_eval/eval/logger.py
@@ -0,0 +1,92 @@
+import json
+import logging
+from enum import Enum
+from pathlib import Path
+from typing import Any, Optional, Union
+
+from continuous_eval.eval.modules import AgentModule
+from continuous_eval.eval.pipeline import Pipeline
+from continuous_eval.eval.result_types import TOOL_PREFIX
+from continuous_eval.eval.utils import instantiate_type
+from continuous_eval.utils.telemetry import telemetry_event
+
+logger = logging.getLogger("eval-manager")
+Serializable = Any
+
+
+class LogMode(Enum):
+    APPEND = 0
+    REPLACE = 1
+
+
+class PipelineLogger:
+    @telemetry_event("logger")
+    def __init__(self, pipeline: Optional[Pipeline] = None):
+        self._pipeline: Optional[Pipeline] = pipeline
+        self.data = dict()
+
+    @property
+    def pipeline(self) -> Pipeline:
+        if self._pipeline is None:
+            raise ValueError("Pipeline not set")
+        return self._pipeline
+
+    def _empty_sample(self):
+        if self._pipeline is None:
+            raise ValueError("Pipeline not set")
+        empty_samples = dict()
+        for module in self._pipeline.modules:
+            empty_samples[module.name] = instantiate_type(module.output)
+            if isinstance(module, AgentModule):
+                empty_samples[f"{TOOL_PREFIX}{module.name}"] = list()
+        return empty_samples
+
+    def log(
+        self,
+        uid: Serializable,
+        module: str,
+        value: Any,
+        mode: LogMode = LogMode.REPLACE,
+        **kwargs,
+    ):
+        # Make sure everything looks good
+        assert uid is not None, "UID cannot be None"
+        if self._pipeline is None:
+            raise ValueError("Pipeline not set")
+        if uid not in self.data:
+            self.data[uid] = self._empty_sample()
+        if kwargs and "tool_args" in kwargs:
+            key = f"{TOOL_PREFIX}{module}"
+            self.data[uid][key].append({"name": value, "kwargs": kwargs["tool_args"]})
+        else:
+            if mode == LogMode.REPLACE:
+                self.data[uid][module] = value
+            elif mode == LogMode.APPEND:
+                if not isinstance(self.data[uid][module], list):
+                    if isinstance(value, list):
+                        self.data[uid][module].extend(value)
+                    else:
+                        self.data[uid][module].append(value)
+                else:
+                    self.data[uid][module].add(value)
+
+    def save(self, filepath: Union[str, Path]):
+        if isinstance(filepath, str):
+            filepath = Path(filepath)
+        assert filepath.suffix == ".jsonl", "File must be a JSONL file"
+        assert self.data, "No samples to save"
+        with open(filepath, "w") as f:
+            for uid, res in self.data.items():
+                line = {**{"__uid": uid}, **res}
+                json_record = json.dumps(line, ensure_ascii=False)
+                f.write(json_record + "\n")
+
+    def load(self, filepath: Union[str, Path]):
+        if isinstance(filepath, str):
+            filepath = Path(filepath)
+        assert filepath.suffix == ".jsonl", "File must be a JSONL file"
+        with open(filepath, "r") as f:
+            for line in f:
+                record = json.loads(line)
+                uid = record.pop("__uid")
+                self.data[uid] = record
diff --git a/continuous_eval/eval/manager.py b/continuous_eval/eval/manager.py
deleted file mode 100644
index 9098f52..0000000
--- a/continuous_eval/eval/manager.py
+++ /dev/null
@@ -1,247 +0,0 @@
-import concurrent.futures
-import logging
-import warnings
-from enum import Enum
-from typing import Any, List, Optional
-
-from continuous_eval.eval.dataset import Dataset, DatasetField
-from continuous_eval.eval.pipeline import CalledTools, ModuleOutput, Pipeline
-from continuous_eval.eval.result_types import TOOL_PREFIX, EvaluationResults, MetricsResults, TestResults
-from continuous_eval.utils.telemetry import telemetry_event
-
-logger = logging.getLogger("eval-manager")
-
-
-class LogMode(Enum):
-    APPEND = 0
-    REPLACE = 1
-
-
-class EvaluationManager:
-    def __init__(self, pipeline: Optional[Pipeline] = None):
-        self._pipeline: Optional[Pipeline] = pipeline
-        self._eval_results: EvaluationResults = EvaluationResults()
-        self._metrics_results: MetricsResults = MetricsResults()
-        self._test_results: TestResults = TestResults()
-        self._is_running: bool = False
-        self._metadata = dict()
-
-        self._metrics_results.pipeline = self._pipeline
-
-        self._idx = 0
-
-    @property
-    def samples(self) -> List[dict]:
-        return self._eval_results.results
-
-    @property
-    def evaluation(self) -> EvaluationResults:
-        return self._eval_results
-
-    @property
-    def metrics(self) -> MetricsResults:
-        return self._metrics_results
-
-    @property
-    def tests(self) -> TestResults:
-        return self._test_results
-
-    @property
-    def metadata(self) -> dict:
-        return self._metadata
-
-    @property
-    def pipeline(self) -> Pipeline:
-        if self._pipeline is None:
-            raise ValueError("Pipeline not set")
-        return self._pipeline
-
-    @property
-    def dataset(self) -> Dataset:
-        if self._pipeline is None:
-            raise ValueError("Pipeline not set")
-        if self._pipeline.dataset is None:
-            raise ValueError("Dataset not set")
-        return self._pipeline.dataset
-
-    def set_pipeline(self, pipeline: Pipeline):
-        self._metrics_results.pipeline = pipeline
-        self._pipeline = pipeline
-
-    def set_metadata(self, metadata: dict):
-        self._metadata = metadata
-
-    def is_running(self) -> bool:
-        return self._is_running
-
-    @telemetry_event("eval_manager")
-    def start_run(self, metadata: dict = dict()):
-        self._idx = 0
-        self._is_running = True
-        self._eval_results = EvaluationResults(self._pipeline)
-        self.set_metadata(metadata)
-
-    @property
-    def curr_sample(self):
-        if self._pipeline is None:
-            raise ValueError("Pipeline not set")
-        if self._idx >= len(self.dataset.data):
-            self._is_running = False
-            return None
-        return self.dataset.data[self._idx]
-
-    def next_sample(self):
-        if self._pipeline is None:
-            raise ValueError("Pipeline not set")
-        if self._idx >= len(self.dataset.data):
-            self._is_running = False
-        else:
-            self._idx += 1
-        return self.curr_sample
-
-    # Context manager
-    @property
-    def experiment(self):
-        class ExperimentContext:
-            def __init__(self, manager):
-                self._manager = manager
-
-            def __enter__(self):
-                # Initialize the session
-                self._manager.start_run()
-                return self  # Return the session object itself to be used as an iterator
-
-            def __exit__(self, exc_type, exc_val, exc_tb):
-                # Clean up the session
-                self._manager._is_running = False
-                # Optional: Handle exceptions
-                if exc_type:
-                    print(f"An error occurred: {exc_val}")
-                return False  # Propagate exceptions
-
-            def __iter__(self):
-                while self._manager.is_running() and self._manager.curr_sample is not None:
-                    yield self._manager.curr_sample
-                    self._manager.next_sample()
-
-        return ExperimentContext(self)
-
-    # Logging results
-
-    def log(
-        self,
-        module: str,
-        value: Any,
-        mode: LogMode = LogMode.REPLACE,
-        **kwargs,
-    ):
-        # Make sure everything looks good
-        if self._pipeline is None:
-            raise ValueError("Pipeline not set")
-        if not self._is_running:
-            raise ValueError("Cannot log when not running")
-        if module not in self._eval_results.results[self._idx]:
-            raise ValueError(f"module {module} not found, review your pipeline")
-
-        if kwargs and "tool_args" in kwargs:
-            key = f"{TOOL_PREFIX}{module}"
-            self._eval_results.results[self._idx][key].append({"name": value, "kwargs": kwargs["tool_args"]})
-        else:
-            if mode == LogMode.REPLACE:
-                self._eval_results.results[self._idx][module] = value
-            elif mode == LogMode.APPEND:
-                if not isinstance(self._eval_results.results[self._idx][module], list):
-                    if isinstance(value, list):
-                        self._eval_results.results[self._idx][module].extend(value)
-                    else:
-                        self._eval_results.results[self._idx][module].append(value)
-                else:
-                    self._eval_results.results[self._idx][module].add(value)
-
-    # Evaluate
-
-    def _prepare(self, module, metric):
-        kwargs = dict()
-        if metric.overloaded_params is not None:
-            for key, val in metric.overloaded_params.items():
-                if isinstance(val, DatasetField):
-                    kwargs[key] = [x[val.name] for x in self.dataset.data]  # type: ignore
-                elif isinstance(val, ModuleOutput):
-                    module_name = module.name if val.module is None else val.module.name
-                    kwargs[key] = [val(x[module_name]) for x in self._eval_results.results]
-                elif isinstance(val, CalledTools):
-                    module_name = module.name if val.module is None else val.module.name
-                    val_key = f"{TOOL_PREFIX}{module_name}"
-                    kwargs[key] = [val(x[val_key]) for x in self._eval_results.results]
-                else:
-                    raise ValueError(f"Invalid promised parameter {key}={val}")
-        return kwargs
-
-    @telemetry_event("eval_manager")
-    def run_metrics(self):
-        logger.info("Running evaluation")
-        assert self._pipeline is not None, "Pipeline not set"
-        assert len(self._eval_results.results) > 0, "No evaluation samples to run the metrics on"
-        if len(self._eval_results.results) != len(self.dataset.data):
-            warnings.warn("The number of samples does not match the dataset size")
-        self._metrics_results.samples = {
-            module.name: {metric.name: metric.batch(**self._prepare(module, metric)) for metric in module.eval}
-            for module in self._pipeline.modules
-            if module.eval is not None
-        }
-        # metrics_results = dict()
-        # # Use ProcessPoolExecutor to parallelize computation
-        # with concurrent.futures.ProcessPoolExecutor() as executor:
-        #     # Prepare tasks for modules that have eval
-        #     tasks = [executor.submit(self.compute_metric_results, module)
-        #             for module in self._pipeline.modules if module.eval is not None]
-        #     # Wait for all tasks to complete and collect results
-        #     for future in concurrent.futures.as_completed(tasks):
-        #         module_name, results = future.result()
-        #         metrics_results[module_name] = results
-        # self._metrics_results.samples = metrics_results
-        return self._metrics_results
-
-    def aggregate_eval_results(self):
-        assert self._pipeline is not None, "Pipeline not set"
-        assert self._eval_results is not None, "Evaluation results not set"
-        assert all(
-            [len(module_res) == len(self.dataset.data) for module_res in self._metrics_results.results.values()]
-        ), "Evaluation is not complete"
-        return self._metrics_results.results
-
-    # Tests
-    @telemetry_event("eval_manager")
-    def run_tests(self):
-        logger.info("Running tests")
-        assert self._pipeline is not None, "Pipeline not set"
-        assert not self._eval_results.is_empty(), "Evaluation results not set"
-        assert all(
-            [len(module_res) == len(self.dataset.data) for module_res in self._metrics_results.results.values()]
-        ), "Evaluation is not complete"
-        self._test_results.results = {
-            module.name: {test.name: test.run(self._metrics_results.results[module.name]) for test in module.tests}
-            for module in self._pipeline.modules
-            if module.tests is not None
-        }
-        return self._test_results
-
-    def test_graph(self):
-        if self._pipeline is None:
-            raise ValueError("Pipeline not set")
-        if self._test_results is None:
-            raise ValueError("Tests not run")
-        pipeline_graph = self._pipeline.graph_repr()
-        tests = "\n    %% Tests\n"
-        for module, results in self._test_results.results.items():
-            metrics_lines = []
-            for metric, passed in results.items():
-                status = "Pass" if passed else "Fail"
-                metrics_lines.append(f"<i>{metric}: {status}</i>")
-            metrics = "<br>".join(metrics_lines)
-            tests += f"    {module}[<b>{module}</b><br>---<br>{metrics}]\n"
-
-        return pipeline_graph + tests
-
-
-eval_manager = EvaluationManager()
diff --git a/continuous_eval/eval/modules.py b/continuous_eval/eval/modules.py
index 7e871a5..b702feb 100644
--- a/continuous_eval/eval/modules.py
+++ b/continuous_eval/eval/modules.py
@@ -1,5 +1,5 @@
 from dataclasses import dataclass, field
-from typing import Any, Dict, List, Optional, Type, Union
+from typing import Any, Callable, Dict, List, Optional, Type, Union
 
 from continuous_eval.eval.dataset import DatasetField
 from continuous_eval.eval.tests import Test
diff --git a/continuous_eval/eval/result_types.py b/continuous_eval/eval/result_types.py
index 9b8a82e..7b88c5c 100644
--- a/continuous_eval/eval/result_types.py
+++ b/continuous_eval/eval/result_types.py
@@ -1,9 +1,11 @@
 import json
 from collections import ChainMap
+from copy import deepcopy
 from functools import cached_property, lru_cache
 from pathlib import Path
-from typing import Dict, List, Optional
+from typing import Dict, List, Optional, Union
 
+from continuous_eval.eval.dataset import Dataset
 from continuous_eval.eval.modules import AgentModule
 from continuous_eval.eval.pipeline import Pipeline
 from continuous_eval.eval.utils import instantiate_type
@@ -11,13 +13,29 @@
 TOOL_PREFIX = "_tool__"
 
 
-class EvaluationResults:
-    def __init__(self, pipeline: Optional[Pipeline] = None) -> None:
-        if pipeline is None:
-            self.results: List[Dict] = list()
-        else:
-            num_samples = len(pipeline.dataset.data)
-            self.results: List[Dict] = [self._build_empty_samples(pipeline) for _ in range(num_samples)]
+class PipelineResults:
+    def __init__(self) -> None:
+        self.results: List[Dict] = list()
+
+    @classmethod
+    def from_dataset(cls, dataset: Dataset):
+        eval_results = cls()
+        eval_results.results = dataset.data
+        return eval_results
+
+    @classmethod
+    def from_logs(cls, logs):
+        eval_results = cls()
+        for datum in logs.pipeline.dataset.data:
+            if datum["uid"] not in logs.data:
+                continue
+            eval_results.results.append({**datum, **logs.data[datum["uid"]]})
+        assert len(eval_results) == len(logs.data), "Could not find some uid in the dataset"
+        return eval_results
+
+    def initialize(self, pipeline: Pipeline):
+        num_samples = len(pipeline.dataset.data)
+        self.results: List[Dict] = [self._build_empty_samples(pipeline) for _ in range(num_samples)]
 
     def __len__(self):
         return len(self.results)
@@ -50,21 +68,34 @@ def load(self, filepath: Path):
 
 
 class MetricsResults:
-    def __init__(self) -> None:
-        self.pipeline: Optional[Pipeline] = None
-        self.samples: Dict = dict()
+    def __init__(self, pipeline: Optional[Pipeline]) -> None:
+        self.pipeline = pipeline
+        self.samples = dict()
 
     def is_empty(self) -> bool:
         return not bool(self.samples)
 
     @cached_property
     def results(self) -> Dict:
+        """
+        Returns a dictionary containing the evaluation results for each module.
+
+        The dictionary is structured as follows:
+        - The keys are the names of the modules.
+        - The values are lists of dictionaries, where each dictionary represents a result.
+        """
         return {
             module_name: [dict(ChainMap(*x)) for x in zip(*eval_res.values())]
             for module_name, eval_res in self.samples.items()
         }
 
     def to_pandas(self):
+        """
+        Converts the results to a pandas DataFrame.
+
+        Returns:
+            pandas.DataFrame: The results as a pandas DataFrame.
+        """
         import pandas as pd
 
         if len(self.results) > 1:
@@ -79,6 +110,12 @@ def to_pandas(self):
 
     @lru_cache(maxsize=1)
     def aggregate(self):
+        """
+        Aggregates the metric values for each module and metric name in the samples.
+
+        Returns:
+            dict: A dictionary containing the aggregated metric values for each module and metric name.
+        """
         if self.pipeline is None:
             raise ValueError("Pipeline not set")
         aggregated_samples = dict()
@@ -92,13 +129,17 @@ def aggregate(self):
         }
         return actual_results
 
-    def save(self, filepath: Path):
+    def save(self, filepath: Union[str, Path]):
+        if isinstance(filepath, str):
+            filepath = Path(filepath)
         assert filepath.suffix == ".json", "File must be a JSON file"
         assert self.samples, "No samples to save"
         with open(filepath, "w") as f:
             json.dump(self.samples, f, ensure_ascii=False)
 
-    def load(self, filepath: Path):
+    def load(self, filepath: Union[str, Path]):
+        if isinstance(filepath, str):
+            filepath = Path(filepath)
         assert filepath.suffix == ".json", "File must be a JSON file"
         with open(filepath, "r") as f:
             self.samples = json.load(f)
diff --git a/continuous_eval/eval/runner.py b/continuous_eval/eval/runner.py
new file mode 100644
index 0000000..4ab4d8f
--- /dev/null
+++ b/continuous_eval/eval/runner.py
@@ -0,0 +1,86 @@
+import logging
+from typing import Optional, Union
+
+from continuous_eval.eval.dataset import Dataset, DatasetField
+from continuous_eval.eval.logger import PipelineLogger
+from continuous_eval.eval.modules import Module
+from continuous_eval.eval.pipeline import CalledTools, ModuleOutput, Pipeline
+from continuous_eval.eval.result_types import TOOL_PREFIX, MetricsResults, PipelineResults, TestResults
+from continuous_eval.metrics import Metric
+from continuous_eval.utils.telemetry import telemetry_event
+
+logger = logging.getLogger("eval-manager")
+
+
+class EvaluationRunner:
+    def __init__(self, pipeline: Pipeline):
+        assert isinstance(pipeline, Pipeline), "Pipeline not set"
+        self._pipeline = pipeline
+
+    @property
+    def pipeline(self) -> Pipeline:
+        return self._pipeline
+
+    @property
+    def dataset(self) -> Dataset:
+        if self._pipeline is None:
+            raise ValueError("Pipeline not set")
+        if self._pipeline.dataset is None:
+            raise ValueError("Dataset not set")
+        return self._pipeline.dataset
+
+    # Evaluate
+
+    def _prepare(self, eval_results: PipelineResults, module: Module, metric: Metric):
+        kwargs = dict()
+        if metric.overloaded_params is not None:
+            for key, val in metric.overloaded_params.items():
+                if isinstance(val, DatasetField):
+                    kwargs[key] = [x[val.name] for x in self.dataset.data]  # type: ignore
+                elif isinstance(val, ModuleOutput):
+                    module_name = module.name if val.module is None else val.module.name
+                    kwargs[key] = [val(x[module_name]) for x in eval_results.results]
+                elif isinstance(val, CalledTools):
+                    module_name = module.name if val.module is None else val.module.name
+                    val_key = f"{TOOL_PREFIX}{module_name}"
+                    kwargs[key] = [val(x[val_key]) for x in eval_results.results]
+                else:
+                    raise ValueError(f"Invalid promised parameter {key}={val}")
+        return kwargs
+
+    @telemetry_event("eval_manager")
+    def evaluate(
+        self,
+        data: Optional[Union[PipelineResults, PipelineLogger, Dataset]] = None,
+    ) -> MetricsResults:
+        logger.info("Running evaluation")
+        if data is None:
+            eval_results = PipelineResults.from_dataset(self.dataset)
+        elif isinstance(data, Dataset):
+            eval_results = PipelineResults.from_dataset(data)
+        elif isinstance(data, PipelineLogger):
+            eval_results = PipelineResults.from_logs(data)
+        else:
+            eval_results = data
+        assert self._pipeline is not None, "Pipeline not set"
+        assert len(eval_results.results) > 0, "No evaluation samples to run the metrics on"
+        metrics_results = MetricsResults(self.pipeline)
+        metrics_results.samples = {
+            module.name: {
+                metric.name: metric.batch(**self._prepare(eval_results, module, metric)) for metric in module.eval
+            }
+            for module in self._pipeline.modules
+            if module.eval is not None
+        }
+        return metrics_results
+
+    @telemetry_event("eval_manager_tests")
+    def test(self, metrics: MetricsResults) -> TestResults:
+        logger.info("Running tests")
+        test_results = TestResults()
+        test_results.results = {
+            module.name: {test.name: test.run(metrics.results[module.name]) for test in module.tests}
+            for module in self._pipeline.modules
+            if module.tests is not None
+        }
+        return test_results
diff --git a/continuous_eval/eval/types.py b/continuous_eval/eval/types.py
index d95887a..602c3d1 100644
--- a/continuous_eval/eval/types.py
+++ b/continuous_eval/eval/types.py
@@ -1,6 +1,13 @@
 from typing import Any, Dict, TypedDict
 
-UUID = str
+UID = str
+
+
+def args_to_dict(*args, **kwargs):
+    arg_dict = dict(kwargs)
+    for index, value in enumerate(args):
+        arg_dict[f'_arg{index}'] = value
+    return arg_dict
 
 
 class ToolCall(TypedDict):
diff --git a/continuous_eval/generators/simple.py b/continuous_eval/generators/simple.py
index 58e295b..ad3d4e3 100644
--- a/continuous_eval/generators/simple.py
+++ b/continuous_eval/generators/simple.py
@@ -3,7 +3,7 @@
 import random
 
 import numpy as np
-from langchain.vectorstores import VectorStore
+from langchain_community.vectorstores import VectorStore
 from tqdm import tqdm
 
 from continuous_eval.llm_factory import LLMFactory, LLMInterface
@@ -12,7 +12,6 @@
 logger = logging.getLogger(__name__)
 logging.basicConfig(level=logging.WARNING)
 
-
 COMMON_RULES = """
 The user is unaware of any specific context, so make sure the question makes sense to those who are not aware of the context.
 Avoid phrases like "According to context / given provided context..."
@@ -276,6 +275,8 @@ def generate(
 
         pbar.close()
         dataset = single_hop_questions + multi_hop_questions
+        for idx, d in enumerate(dataset):
+            d["uid"] = idx
         if len(dataset) < num_questions:
             raise Warning(f"Could not generate enough questions. Generated {len(dataset)} questions.")
 
diff --git a/continuous_eval/metrics/tools/match.py b/continuous_eval/metrics/tools/match.py
index 287f369..4a39ca1 100644
--- a/continuous_eval/metrics/tools/match.py
+++ b/continuous_eval/metrics/tools/match.py
@@ -21,13 +21,21 @@ def __call__(self, tools: List[ToolCall], ground_truths: List[ToolCall], **kwarg
             )
         else:
             # Convert ground_truth to a format that's easy to check for "contains"
-            ground_truth_set = {
-                frozenset(tool.items()) for tool in [{"name": tool["name"], **tool["kwargs"]} for tool in ground_truths]
-            }
+            use_kwargs = all("kwargs" in tool for tool in ground_truths)
+            if use_kwargs:
+                ground_truth_set = {
+                    frozenset(tool.items())
+                    for tool in [{"name": tool["name"], **tool["kwargs"]} for tool in ground_truths]
+                }
+            else:
+                ground_truth_set = {frozenset(tool.items()) for tool in ground_truths}
             # Score
             num_correct, matched_executions = 0, set()
             for tool in tools:
-                tool_set = frozenset({"name": tool["name"], **tool["kwargs"]}.items())
+                if use_kwargs:
+                    tool_set = frozenset({"name": tool["name"], **tool["kwargs"]}.items())
+                else:
+                    tool_set = frozenset({"name": tool["name"]}.items())
                 if tool_set in ground_truth_set and tool_set not in matched_executions:
                     num_correct += 1
                 matched_executions.add(tool_set)
diff --git a/docs/astro.config.mjs b/docs/astro.config.mjs
index 0d82cc7..ff6d9fd 100644
--- a/docs/astro.config.mjs
+++ b/docs/astro.config.mjs
@@ -41,13 +41,15 @@ export default defineConfig({
 					],
 				},
         {
-					label: 'Pipeline',
+					label: 'Orchestration',
 					items: [
 						// Each item here is one entry in the navigation menu.
-						{ label: 'Overview', link: '/pipeline/pipeline'},
-						{ label: 'Evaluators and Tests', link: '/pipeline/eval_and_tests'},
-						{ label: 'Evaluation Manager', link: '/pipeline/eval_manager' },
-						{ label: 'Evaluation Dataset', link: '/pipeline/eval_dataset' },
+						{ label: 'Pipeline', link: '/pipeline/pipeline'},
+						{ label: 'Dataset', link: '/pipeline/eval_dataset' },
+						{ label: 'Metrics and Tests', link: '/pipeline/metrics_and_tests'},
+            { label: 'Pipeline Logger', link: '/pipeline/pipeline_logger' },
+            { label: 'Evaluation Runner', link: '/pipeline/eval_runner' },
+						{ label: 'Evaluation Manager (Deprecated)', link: '/pipeline/eval_manager' },
 					],
 
         },
diff --git a/docs/src/content/docs/pipeline/eval_and_tests.md b/docs/src/content/docs/pipeline/eval_and_tests.md
deleted file mode 100644
index 76f53e1..0000000
--- a/docs/src/content/docs/pipeline/eval_and_tests.md
+++ /dev/null
@@ -1,129 +0,0 @@
----
-title: Evaluators and Tests
-sidebar:
-  badge:
-    text: new
-    variant: tip
----
-
-## Definitions
-
-You can optionally add `eval` and `tests` to the modules you want to measure the performance of.
-
-
-#### `eval`: select relevant evaluation metrics
-- Select the metrics and specify the input according to the data fields required for each metric. `MetricName().use(data_fields)`.
-- Metric inputs can be referenced using items from two sources:
-    -   **From `dataset`**: e.g. `ground_truth_context = dataset.ground_truth_context`
-    -   **From current module**: e.g. `answer = ModuleOutput()`
-    -   **From prior modules**: e.g. `retrieved_context = ModuleOutput(DocumentsContent, module=reranker)`, where
-        `DocumentsContent = ModuleOutput(lambda x: [z["page_content"] for z in x])` to select specific items from the prior module's output
-
-
-#### `tests`: define specific performance criteria
-- Select testing class `GreaterOrEqualThan` or `MeanGreaterOrEqualThan` to run test over each datapoint or the mean of the aggregate dataset
-- Define `test_name`, `metric_name` (must be part of the metric_name that `eval` calculates), and `min_value`.
-
-
-## Example
-
-We will expand the example defined in pipeline with metrics and tests.
-
-Evaluation Metrics:
--   `PrecisionRecallF1` to evaluate the Retriever
--   `RankedRetrievalMetrics` to evaluate the Reranker
--   `FleschKincaidReadability`, `DebertaAnswerScores`, and `LLMBasedFaithfulness` to evaluate the Generator
-
-Tests:
--   Mean of `context_recall`, a metric calculated by `PrecisionRecallF1`, needs to be >= 0.8 to pass
--   Mean of `average_precision`, a metric calculated by `RankedRetrievalMetrics`, needs to be >= 0.7 to pass
--   Mean of `deberta_entailment`, a metric calculated by `DebertaAnswerScores` needs to be >= 0.5 to pass
-
-
-```d2
-direction: right
-Dataset: Eval Dataset
-Dataset.shape: oval
-Dataset -> Retriever
-Retriever -> Reranker -> Generator
-```
-
-
-
-
-```python title="pipeline.py"
-from continuous_eval.eval import Module, Pipeline, Dataset, ModuleOutput
-from continuous_eval.metrics.retrieval import PrecisionRecallF1, RankedRetrievalMetrics # Deterministic metrics
-from continuous_eval.metrics.generation.text import (
-    FleschKincaidReadability, # Deterministic metric
-    DebertaAnswerScores, # Semantic metric
-    LLMBasedFaithfulness, # LLM-based metric
-)
-from typing import List, Dict
-from continuous_eval.eval.tests import MeanGreaterOrEqualThan
-
-dataset = Dataset("data/eval_golden_dataset")
-
-Documents = List[Dict[str, str]]
-DocumentsContent = ModuleOutput(lambda x: [z["page_content"] for z in x])
-
-retriever = Module(
-    name="retriever",
-    input=dataset.question,
-    output=Documents,
-    eval=[
-        PrecisionRecallF1().use(
-            retrieved_context=DocumentsContent,
-            ground_truth_context=dataset.ground_truth_context,
-        ),
-    ],
-    tests=[
-        MeanGreaterOrEqualThan(
-            test_name="Average Precision", metric_name="context_recall", min_value=0.8
-        ),
-    ],
-)
-
-reranker = Module(
-    name="reranker",
-    input=retriever,
-    output=Documents,
-    eval=[
-        RankedRetrievalMetrics().use(
-            retrieved_context=DocumentsContent,
-            ground_truth_context=dataset.ground_truth_context,
-        ),
-    ],
-    tests=[
-        MeanGreaterOrEqualThan(
-            test_name="Context Recall", metric_name="average_precision", min_value=0.7
-        ),
-    ],
-)
-
-llm = Module(
-    name="llm",
-    input=reranker,
-    output=str,
-    eval=[
-        FleschKincaidReadability().use(answer=ModuleOutput()),
-        DebertaAnswerScores().use(
-            answer=ModuleOutput(), ground_truth_answers=dataset.ground_truths
-        ),
-        LLMBasedFaithfulness().use(
-            answer=ModuleOutput(),
-            retrieved_context=ModuleOutput(DocumentsContent, module=reranker),
-            question=dataset.question,
-        ),
-    ],
-    tests=[
-        MeanGreaterOrEqualThan(
-            test_name="Deberta Entailment", metric_name="deberta_answer_entailment", min_value=0.5
-        ),
-    ],
-)
-
-pipeline = Pipeline([retriever, reranker, llm], dataset=dataset)
-
-print(pipeline.graph_repr())
-```
\ No newline at end of file
diff --git a/docs/src/content/docs/pipeline/eval_dataset.md b/docs/src/content/docs/pipeline/eval_dataset.md
index 5c1f14a..7a906e1 100644
--- a/docs/src/content/docs/pipeline/eval_dataset.md
+++ b/docs/src/content/docs/pipeline/eval_dataset.md
@@ -2,25 +2,63 @@
 title: Evaluation Dataset
 ---
 
-### `Dataset` Class 
+## Dataset Class
 
-**The `Dataset` class takes a folder that contains a flexible evaluation dataset tailored to your evaluation pipeline.**
+The `Dataset` class is a convenient class that represent a dataset that can be used for evaluation.
+
+The dataset class can be initialized with a path to a folder or a file.
+The folder should contain the following files:
 
-A custom dataset needs to contain:
 - `dataset.jsonl` which contains a collection of query / instructions and corresponding reference outputs by the modules in the pipeline.
-- `manifest.yaml` which declares the structure and fields of the dataset to be used by `Pipeline` and `EvaluationManager` instances.
+- an optional `manifest.yaml` which declares the structure and fields of the dataset, the license and other metadata.
 
 ```python
 from continuous_eval.eval import Dataset
 
-dataset = Dataset.from_jsonl("data_folder")
+dataset = Dataset("path_to_folder") # or Dataset("path_to_file.jsonl")
+```
+
+Alternatively, you can also create a dataset from a list of dictionaries:
+
+```python
+dataset = Dataset.from_data([
+    {"question": "What is the capital of France?", "answer": "Paris"},
+    {"question": "What is the capital of Germany?", "answer": "Berlin"},
+])
+```
+
+To access the raw data, you can use the `data` attribute:
+
+```python
+print(dataset.data[0])
+```
+
+### Dataset fields
+
+Suppose you want to reference a dataset field, you can use the `DatasetField` class:
+
+```python
+class DatasetField:
+    name: str
+    type: type = typing.Any  # type: ignore
+    description: str = ""
+    is_ground_truth: bool = False
 ```
 
+When you load the dataset, the `Dataset` class will automatically infer the fields from the data.
+
+```python
+type(dataset.question)  # DatasetField
+```
+
+this will be particularly useful when defining the input and output of the modules in the pipeline.
+
 ### Example Data Folder
 
-Here's an example golden dataset that contains `uuid`, `question`, `answer` (ground truth answers), and `tool_calls` (the tools that are supposed to be used).
+Here's an example golden dataset that contains `uid`, `question`, `answer` (ground truth answers), and `tool_calls` (the tools that are supposed to be used).
+
+#### Dataset File
 
-#### dataset.jsonl
 ```json title="data_folder/dataset.jsonl"
 {
   "uuid": "1",
@@ -63,7 +101,9 @@ Here's an example golden dataset that contains `uuid`, `question`, `answer` (gro
   ]
 }
 ```
-#### manifest.yaml
+
+#### Manifest (optional)
+
 ```yaml title="data_folder/manifest.yaml"
 name: Uber 10Q
 description: Uber 10Q filings from 2022
diff --git a/docs/src/content/docs/pipeline/eval_manager.mdx b/docs/src/content/docs/pipeline/eval_manager.mdx
index bf8b456..fb5b16f 100644
--- a/docs/src/content/docs/pipeline/eval_manager.mdx
+++ b/docs/src/content/docs/pipeline/eval_manager.mdx
@@ -1,5 +1,5 @@
 ---
-title: Eval Manager
+title: Evaluation Runner
 sidebar:
   badge:
     text: new
@@ -10,6 +10,10 @@ sidebar:
 ## Definition
 `eval_manager` manages the evaluation process for a pipeline. Add `eval_manager` to your application and log the module outputs for evaluation.
 
+:::caution
+The evaluation manager is not supported from version 0.3.8 onwards. Please use the `EvaluationRunner` module instead.
+:::
+
 ## Logging data in evaluation runs
 
 
diff --git a/docs/src/content/docs/pipeline/eval_runner.mdx b/docs/src/content/docs/pipeline/eval_runner.mdx
new file mode 100644
index 0000000..151968e
--- /dev/null
+++ b/docs/src/content/docs/pipeline/eval_runner.mdx
@@ -0,0 +1,46 @@
+---
+title: Evaluation Runner
+sidebar:
+  badge:
+    text: new
+    variant: tip
+---
+
+The `EvaluationRunner` manages the evaluation process for a pipeline.
+
+To evaluate on the dataset defined in the pipeline you can run
+
+```python
+runner = EvaluationRunner(pipeline)
+eval_results = runner.evaluate()
+```
+
+The evaluate method will run each metric and return a `MetricsResults` object with the results.
+
+```python
+metrics = evalrunner.evaluate(pipelog)
+metrics.results() # returns a dictionary with the results
+```
+
+### Evaluate on pipeline logs
+
+If you use the `PipelineLogger` to log your pipeline outputs, you can evaluate on the logs directly.
+
+```python
+pipelog = PipelineLogger(pipeline=pipeline)
+# ... log or load logs
+
+# Run the evaluation...
+evalrunner = EvaluationRunner(pipeline)
+metrics = evalrunner.evaluate(pipelog)
+```
+
+### Evaluate on other data
+
+You can also evaluate on other data by passing a `Dataset` object to the `evaluate` method.
+
+```python
+dataset = Dataset(...)
+evalrunner = EvaluationRunner(pipeline)
+metrics = evalrunner.evaluate(dataset)
+```
diff --git a/docs/src/content/docs/pipeline/metrics_and_tests.md b/docs/src/content/docs/pipeline/metrics_and_tests.md
new file mode 100644
index 0000000..61ab1b5
--- /dev/null
+++ b/docs/src/content/docs/pipeline/metrics_and_tests.md
@@ -0,0 +1,101 @@
+---
+title: Metrics and Tests
+sidebar:
+  badge:
+    text: new
+    variant: tip
+---
+
+## Metrics
+
+When defining modules in the pipeline you can also specify metrics to evaluate the module outputs. The metrics are defined in the `eval` attribute of the module definition.
+
+To specify the input to each metric you can use the `use` method.
+For example, suppose we have a retriever on which we want to use the `PrecisionRecallF1` metric.
+We can define the retriever as follows:
+
+```python
+from continuous_eval.eval import Module, ModuleOutput
+from continuous_eval.metrics.retrieval import PrecisionRecallF1
+
+retriever = Module(
+    name="retriever",
+    input=dataset.question,
+    output=Documents,
+    eval=[
+        PrecisionRecallF1().use(
+            retrieved_context=ModuleOutput(),
+            ground_truth_context=dataset.ground_truth_context,
+        ),
+    ],
+)
+```
+
+The `PrecisionRecallF1` metric expects two inputs: `retrieved_context` and `ground_truth_context`.
+To use it to evaluate the module we specify that the `retrieved_context` is the module's output while the `ground_truth_context` is the dataset's ground truth context (here we used the dataset field).
+
+The ModuleOutput class is flexible and allows for custom selectors.
+Since `PrecisionRecallF1` expect a `List[str]` as input for both arguments, by specifying `ModuleOutput` we assume the module is actually returning a list of strings. Suppose instead that it returns a list of dictionaries where `"page_content"` is the key for the text we want to evaluate.
+We could specify the output as follows:
+
+```python
+PrecisionRecallF1().use(
+    retrieved_context=ModuleOutput(lambda x: [z["page_content"] for z in x]),
+    ground_truth_context=dataset.ground_truth_context,
+),
+```
+
+the evaluation runner will take care of extracting the relevant data from the module output and the dataset.
+
+## Tests
+
+Each module can also have tests to ensure the module is working as expected.
+The tests are defined in the `tests` attribute of the module definition.
+
+Suppose we want to make sure the average precision of the retriever is greater than 0.8.
+
+```python
+from continuous_eval.eval import Module, ModuleOutput
+from continuous_eval.metrics.retrieval import PrecisionRecallF1
+from continuous_eval.eval.tests import MeanGreaterOrEqualThan
+
+retriever = Module(
+    name="retriever",
+    input=dataset.question,
+    output=Documents,
+    eval=[
+        PrecisionRecallF1().use(
+            retrieved_context=DocumentsContent,
+            ground_truth_context=dataset.ground_truth_context,
+        ),
+    ],
+    tests=[
+        MeanGreaterOrEqualThan(
+            test_name="Average Precision", metric_name="context_recall", min_value=0.8
+        ),
+    ],
+)
+```
+
+The `MeanGreaterOrEqualThan` test expects the name of the metric to test, the minimum value, and the name of the test.
+The evaluation runner will run the test and report the results.
+
+```python
+evalrunner = EvaluationRunner(pipeline)
+metrics = evalrunner.evaluate()
+
+print("\nTests results:")
+tests = evalrunner.test(metrics)
+for module_name, test_results in tests.results.items():
+    print(f"{module_name}")
+    for test_name in test_results:
+        print(f" - {test_name}: {'PASS' if test_results[test_name] else 'FAIL'}")
+```
+
+The output will be:
+
+```text
+Tests results:
+retriever
+ - Average Precision: PASS
+```
diff --git a/docs/src/content/docs/pipeline/pipeline.md b/docs/src/content/docs/pipeline/pipeline.md
index 7b87f68..0796500 100644
--- a/docs/src/content/docs/pipeline/pipeline.md
+++ b/docs/src/content/docs/pipeline/pipeline.md
@@ -13,9 +13,22 @@ To evaluate your custom AI application pipeline, you first need to define it in
 
 A pipeline is a sequence of steps that transform data from one format to another. In a typical AI application, it usually starts with a user instruction, then goes through a series of steps (`Module`) to return an answer.
 
-The basic component of a pipeline is a `Module`. A module is a named component with specific inputs and outputs.
+The basic component of a pipeline is a `Module`.
+A module is a named component with specific inputs and outputs.
+It can be a simple function or a complex model that takes some input and returns some output.
 
-## Example
+To define a module you need to specify the following:
+
+- `name`: a unique name for the module
+- `input`: the input of the module, can be a dataset field (`DatasetField`, see dataset page) another module or nothing (`None`)
+- `output` the output type (e.g., `str`, `List[str]`, `Dict[str, str]`, etc.)
+- `description`: Optional string describing the field
+- `eval`: an optional list of metrics (see next page)
+- `tests`: an optional list of tests (see next page)
+
+Through the `Pipeline` class, you can define a sequence of modules that represent your application pipeline.
+
+### Example
 
 Consider the following pipeline example:
 
@@ -27,15 +40,13 @@ Dataset -> Retriever
 Retriever -> Reranker -> Generator
 ```
 
-
-
 This Retrieval-Augmented Generation (RAG) pipeline consists of three simple modules. A Retriever that fetches the relevant documents, a Reranker that reorders and filters the documents, and a Generator that uses LLM to generate a response based on information in the documents.
 
 ```python title="pipeline.py"
 from continuous_eval.eval import Module, Pipeline, Dataset
 from typing import List, Dict
 
-dataset = Dataset("dataset_folder") # Evaluation dataset that contains all the questions and optionall the expected module outputs
+dataset = Dataset("dataset_folder") # Evaluation dataset that contains all the questions and optional the expected module outputs
 
 retriever = Module(
     name="Retriever",
@@ -58,4 +69,3 @@ llm = Module(
 pipeline = Pipeline([retriever, reranker, llm], dataset=dataset)
 print(pipeline.graph_repr()) # visualize the pipeline in Mermaid graph format
 ```
-
diff --git a/docs/src/content/docs/pipeline/pipeline_logger.mdx b/docs/src/content/docs/pipeline/pipeline_logger.mdx
new file mode 100644
index 0000000..faa943a
--- /dev/null
+++ b/docs/src/content/docs/pipeline/pipeline_logger.mdx
@@ -0,0 +1,51 @@
+---
+title: Pipeline Logger
+sidebar:
+  badge:
+    text: new
+    variant: tip
+---
+
+
+## Definition
+
+The `PipelineLogger` allows to store the output of each module in a format that is evaluation-ready.
+
+To create a pipeline logger you need a pipeline first.
+
+```python
+from continuous_eval.eval.logger import PipelineLogger
+
+pipelog = PipelineLogger(pipeline=pipeline)
+```
+
+now you can log the output of each module in the pipeline.
+
+```python
+pipelog.log(uid=sample_uid, module="module_name", value=data)
+```
+
+keep in mind that the `uid` is a unique identifier for the sample, and the `module` is the name of the module you are logging.
+Datasets should have a unique identifier for each sample, so you can use that as the `uid`.
+
+With the pipeline logger you can also save/load logs from a file.
+
+```python
+pipelog.save("logs.jsonl")
+# ... later
+pipelog.load("logs.jsonl")
+```
+
+to use it in the evaluation runner, you can pass it as an argument to the `evaluate` method.
+
+```python
+metrics = evalrunner.evaluate(pipelog)
+```
+
+### Log tools use
+
+To log the use of a tool in a module, should just specify the `tool_args` method.
+
+```python
+pipelog.log(uid=sample_uid, module="module_name", value="tool_name", tool_args={"a": a, "b": b})
+```
diff --git a/examples/ensemble_metric.py b/examples/ensemble_metric.py
index 3e40e9c..9f9240f 100644
--- a/examples/ensemble_metric.py
+++ b/examples/ensemble_metric.py
@@ -6,19 +6,16 @@
 from continuous_eval.classifiers.utils import eval_prediction
 from continuous_eval.data_downloader import example_data_downloader
 from continuous_eval.datatypes import DataSplit, SplitRatios
-from continuous_eval.eval import Dataset, SingleModulePipeline
-from continuous_eval.eval.manager import eval_manager
+from continuous_eval.eval import Dataset, EvaluationRunner, SingleModulePipeline
 from continuous_eval.llm_factory import LLMFactory
 from continuous_eval.metrics.generation.text import (
-    DebertaAnswerScores,
     DeterministicAnswerCorrectness,
     FleschKincaidReadability,
     LLMBasedAnswerCorrectness,
 )
 
 # Download the correctness dataset and remove examples where the LLL refused to answer (i.e., said "I don't know")
-dataset_jsonl = example_data_downloader("correctness")
-dataset = Dataset(dataset_jsonl)
+dataset = Dataset(example_data_downloader("correctness")).sample(100)
 dataset.filter(lambda x: x["annotation"] != "refuse-to-answer")
 
 # Let's define the system under evaluation
@@ -31,22 +28,20 @@
         DeterministicAnswerCorrectness().use(
             answer=dataset.answer, ground_truth_answers=dataset.ground_truths  # type: ignore
         ),
-        DebertaAnswerScores().use(answer=dataset.answer, ground_truth_answers=dataset.ground_truths),  # type: ignore
         FleschKincaidReadability().use(answer=dataset.answer),  # type: ignore
     ],
 )
 
 # We start the evaluation manager and run the metrics
-eval_manager.set_pipeline(pipeline)
-eval_manager.evaluation.results = dataset.data
-eval_manager.run_metrics()
-eval_manager.metrics.save(Path("metrics_results.json"))
+runner = EvaluationRunner(pipeline)
+eval_results = runner.evaluate()
+eval_results.save(Path("metrics_results.json"))
 
 # Now we building the data for the ensemble classifier
 # X is the input the classifier can use
 # y is the target the classifier should predict (1 for correct, 0 for incorrect)
-X = eval_manager.metrics.to_pandas()
-y = map(lambda x: 1 if x == "correct" else 0, dataset["annotation"])
+X = eval_results.to_pandas()
+y = list(map(lambda x: 1 if x == "correct" else 0, dataset["annotation"]))
 
 # We split the data into train, test, and calibration sets
 # We also specify the features we want to use for the classifier
@@ -57,8 +52,8 @@
     split_ratios=SplitRatios(train=0.6, test=0.2, calibration=0.2),
     features=[
         "token_overlap_recall",
-        "deberta_answer_entailment",
-        "deberta_answer_contradiction",
+        # "deberta_answer_entailment",
+        # "deberta_answer_contradiction",
         "flesch_reading_ease",
     ],
     oversample=True,
diff --git a/examples/evaluation_on_dataset.py b/examples/evaluation_on_dataset.py
index ef5fdb8..2fa57c1 100644
--- a/examples/evaluation_on_dataset.py
+++ b/examples/evaluation_on_dataset.py
@@ -1,32 +1,36 @@
 from pathlib import Path
+from time import perf_counter
 
 from continuous_eval.data_downloader import example_data_downloader
-from continuous_eval.eval import Dataset, SingleModulePipeline
-from continuous_eval.eval.manager import eval_manager
+from continuous_eval.eval import Dataset, EvaluationRunner, SingleModulePipeline
+from continuous_eval.eval.tests import GreaterOrEqualThan
 from continuous_eval.metrics.retrieval import PrecisionRecallF1, RankedRetrievalMetrics
 
 # Let's download the retrieval dataset example
 dataset_jsonl = example_data_downloader("retrieval")
-dataset = Dataset(dataset_jsonl)
+dataset = Dataset(dataset_jsonl).sample(10)
 
 pipeline = SingleModulePipeline(
     dataset=dataset,
     eval=[
         PrecisionRecallF1().use(
-            retrieved_context=dataset.retrieved_contexts,
-            ground_truth_context=dataset.ground_truth_contexts,
+            retrieved_context=dataset.retrieved_context,  # type: ignore
+            ground_truth_context=dataset.ground_truth_contexts,  # type: ignore
         ),
         RankedRetrievalMetrics().use(
-            retrieved_context=dataset.retrieved_contexts,
-            ground_truth_context=dataset.ground_truth_contexts,
+            retrieved_context=dataset.retrieved_context,  # type: ignore
+            ground_truth_context=dataset.ground_truth_contexts,  # type: ignore
         ),
     ],
+    tests=[
+        GreaterOrEqualThan(test_name="Recall", metric_name="rouge_l_recall", min_value=0.8),
+    ],
 )
 
 # We start the evaluation manager and run the metrics
-eval_manager.set_pipeline(pipeline)
-eval_manager.evaluation.results = dataset.data
-eval_manager.run_metrics()
-eval_manager.metrics.save(Path("metrics_results_retr.json"))
-
-print(eval_manager.metrics.aggregate())
+tic = perf_counter()
+runner = EvaluationRunner(pipeline)
+eval_results = runner.evaluate()
+toc = perf_counter()
+print(eval_results.aggregate())
+print(f"Elapsed time: {toc - tic:.2f} seconds")
diff --git a/examples/simple_dataset_generation.py b/examples/simple_dataset_generation.py
index 24e35b3..b2ba227 100644
--- a/examples/simple_dataset_generation.py
+++ b/examples/simple_dataset_generation.py
@@ -17,9 +17,9 @@ def main():
     logging.basicConfig(level=logging.INFO)
 
     generator_llm = "gpt-4-0125-preview"
-    num_questions = 10
-    multi_hop_precentage = 0.2
-    max_try_ratio = 3
+    num_questions = 2
+    multi_hop_precentage = 0.0
+    max_try_ratio = 5
 
     print(f"Generating a {num_questions}-questions dataset with {generator_llm}...")
     db = example_data_downloader("graham_essays/small/chromadb", Path("temp"), force_download=False)
@@ -36,7 +36,7 @@ def main():
         max_try_ratio=max_try_ratio,
     )
     toc = perf_counter()
-    print(f"Finished generating dataset in {tic-toc:.2f}sec.")
+    print(f"Finished generating dataset in {toc-tic:.2f}sec.")
 
     current_datetime = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
     output_directory = Path("generated_dataset")
diff --git a/poetry.lock b/poetry.lock
index 2fd589b..0851278 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,87 +2,87 @@
 
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 name = "aiohttp"
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+version = "3.9.5"
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 ]
 
 [package.dependencies]
@@ -143,24 +143,25 @@ typing-extensions = ">=4.5,<5"
 
 [[package]]
 name = "anyio"
-version = "3.7.1"
+version = "4.3.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
 ]
 
 [package.dependencies]
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
-test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (<0.22)"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
 
 [[package]]
 name = "appdirs"
@@ -175,13 +176,13 @@ files = [
 
 [[package]]
 name = "asgiref"
-version = "3.8.0"
+version = "3.8.1"
 description = "ASGI specs, helper code, and adapters"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -224,7 +225,7 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p
 name = "backoff"
 version = "2.2.1"
 description = "Function decoration for backoff and retry"
-optional = true
+optional = false
 python-versions = ">=3.7,<4.0"
 files = [
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@@ -233,38 +234,38 @@ files = [
 
 [[package]]
 name = "bcrypt"
-version = "4.1.2"
+version = "4.1.3"
 description = "Modern password hashing for your software and your servers"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "bcrypt-4.1.3.tar.gz", hash = "sha256:2ee15dd749f5952fe3f0430d0ff6b74082e159c50332a1413d51b5689cf06623"},
 ]
 
 [package.extras]
@@ -275,7 +276,7 @@ typecheck = ["mypy"]
 name = "beautifulsoup4"
 version = "4.12.3"
 description = "Screen-scraping library"
-optional = true
+optional = false
 python-versions = ">=3.6.0"
 files = [
     {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
@@ -292,6 +293,17 @@ charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
+[[package]]
+name = "bidict"
+version = "0.23.1"
+description = "The bidirectional mapping library for Python."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "bidict-0.23.1-py3-none-any.whl", hash = "sha256:5dae8d4d79b552a71cbabc7deb25dfe8ce710b17ff41711e13010ead2abfc3e5"},
+    {file = "bidict-0.23.1.tar.gz", hash = "sha256:03069d763bc387bbd20e7d49914e75fc4132a41937fa3405417e1a5a2d006d71"},
+]
+
 [[package]]
 name = "black"
 version = "23.12.1"
@@ -340,17 +352,17 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "boto3"
-version = "1.34.70"
+version = "1.34.107"
 description = "The AWS SDK for Python"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.34.70-py3-none-any.whl", hash = "sha256:8d7902e2c0c62837457ba18146e3feaf1dec62018617edc5c0336b65b305b682"},
-    {file = "boto3-1.34.70.tar.gz", hash = "sha256:54150a52eb93028b8e09df00319e8dcb68be7459333d5da00d706d75ba5130d6"},
+    {file = "boto3-1.34.107-py3-none-any.whl", hash = "sha256:a7280f54babc8e285d85d2558dd6167e4deb069e03abe43a55b643e10c03952b"},
+    {file = "boto3-1.34.107.tar.gz", hash = "sha256:2500963ddd7fee0c891db596ed73f203a62e8ee6faf1543c7a14169b1d557bc3"},
 ]
 
 [package.dependencies]
-botocore = ">=1.34.70,<1.35.0"
+botocore = ">=1.34.107,<1.35.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -359,13 +371,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.34.70"
+version = "1.34.107"
 description = "Low-level, data-driven core of boto 3."
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.34.70-py3-none-any.whl", hash = "sha256:c86944114e85c8a8d5da06fb84f2609ed3bd23cd2fc06b30250bef7e37e8c589"},
-    {file = "botocore-1.34.70.tar.gz", hash = "sha256:fa03d4972cd57d505e6c0eb5d7c7a1caeb7dd49e84f963f7ebeca41fe8ab736e"},
+    {file = "botocore-1.34.107-py3-none-any.whl", hash = "sha256:98bfab930391a21d24ed7a7bc86ec2ec076607318ab8de0c37d2587f73a88d89"},
+    {file = "botocore-1.34.107.tar.gz", hash = "sha256:4620286a814c3c8abc59145203650a6b2a4f538e887552fa1bc6896b6d11b28b"},
 ]
 
 [package.dependencies]
@@ -377,37 +389,38 @@ urllib3 = [
 ]
 
 [package.extras]
-crt = ["awscrt (==0.19.19)"]
+crt = ["awscrt (==0.20.9)"]
 
 [[package]]
 name = "build"
-version = "1.1.1"
+version = "1.2.1"
 description = "A simple, correct Python build frontend"
-optional = true
-python-versions = ">= 3.7"
+optional = false
+python-versions = ">=3.8"
 files = [
-    {file = "build-1.1.1-py3-none-any.whl", hash = "sha256:8ed0851ee76e6e38adce47e4bee3b51c771d86c64cf578d0c2245567ee200e73"},
-    {file = "build-1.1.1.tar.gz", hash = "sha256:8eea65bb45b1aac2e734ba2cc8dad3a6d97d97901a395bd0ed3e7b46953d2a31"},
+    {file = "build-1.2.1-py3-none-any.whl", hash = "sha256:75e10f767a433d9a86e50d83f418e83efc18ede923ee5ff7df93b6cb0306c5d4"},
+    {file = "build-1.2.1.tar.gz", hash = "sha256:526263f4870c26f26c433545579475377b2b7588b6f1eac76a001e873ae3e19d"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "os_name == \"nt\""}
 importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""}
-packaging = ">=19.0"
+packaging = ">=19.1"
 pyproject_hooks = "*"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
-test = ["filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
-typing = ["importlib-metadata (>=5.1)", "mypy (>=1.5.0,<1.6.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
+typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+uv = ["uv (>=0.1.18)"]
 virtualenv = ["virtualenv (>=20.0.35)"]
 
 [[package]]
 name = "cachetools"
 version = "5.3.3"
 description = "Extensible memoizing collections and decorators"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "cachetools-5.3.3-py3-none-any.whl", hash = "sha256:0abad1021d3f8325b2fc1d2e9c8b9c9d57b04c3932657a72465447332c24d945"},
@@ -440,7 +453,7 @@ files = [
 name = "chardet"
 version = "5.2.0"
 description = "Universal encoding detector for Python 3"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "chardet-5.2.0-py3-none-any.whl", hash = "sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970"},
@@ -550,7 +563,7 @@ files = [
 name = "chroma-hnswlib"
 version = "0.7.3"
 description = "Chromas fork of hnswlib"
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "chroma-hnswlib-0.7.3.tar.gz", hash = "sha256:b6137bedde49fffda6af93b0297fe00429fc61e5a072b1ed9377f909ed95a932"},
@@ -585,13 +598,13 @@ numpy = "*"
 
 [[package]]
 name = "chromadb"
-version = "0.4.24"
+version = "0.5.0"
 description = "Chroma."
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "chromadb-0.4.24-py3-none-any.whl", hash = "sha256:3a08e237a4ad28b5d176685bd22429a03717fe09d35022fb230d516108da01da"},
-    {file = "chromadb-0.4.24.tar.gz", hash = "sha256:a5c80b4e4ad9b236ed2d4899a5b9e8002b489293f2881cb2cadab5b199ee1c72"},
+    {file = "chromadb-0.5.0-py3-none-any.whl", hash = "sha256:8193dc65c143b61d8faf87f02c44ecfa778d471febd70de517f51c5d88a06009"},
+    {file = "chromadb-0.5.0.tar.gz", hash = "sha256:7954af614a9ff7b2902ddbd0a162f33f7ec0669e2429903905c4f7876d1f766f"},
 ]
 
 [package.dependencies]
@@ -612,7 +625,6 @@ opentelemetry-sdk = ">=1.2.0"
 orjson = ">=3.9.12"
 overrides = ">=7.3.1"
 posthog = ">=2.4.0"
-pulsar-client = ">=3.1.0"
 pydantic = ">=1.9"
 pypika = ">=0.48.9"
 PyYAML = ">=6.0.0"
@@ -672,7 +684,7 @@ files = [
 name = "coloredlogs"
 version = "15.0.1"
 description = "Colored terminal output for Python's logging module"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 files = [
     {file = "coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934"},
@@ -687,13 +699,13 @@ cron = ["capturer (>=2.4)"]
 
 [[package]]
 name = "dataclasses-json"
-version = "0.6.4"
+version = "0.6.6"
 description = "Easily serialize dataclasses to and from JSON."
-optional = true
-python-versions = ">=3.7,<4.0"
+optional = false
+python-versions = "<4.0,>=3.7"
 files = [
-    {file = "dataclasses_json-0.6.4-py3-none-any.whl", hash = "sha256:f90578b8a3177f7552f4e1a6e535e84293cd5da421fcce0642d49c0d7bdf8df2"},
-    {file = "dataclasses_json-0.6.4.tar.gz", hash = "sha256:73696ebf24936560cca79a2430cbc4f3dd23ac7bf46ed17f38e5e5e7657a6377"},
+    {file = "dataclasses_json-0.6.6-py3-none-any.whl", hash = "sha256:e54c5c87497741ad454070ba0ed411523d46beb5da102e221efb873801b0ba85"},
+    {file = "dataclasses_json-0.6.6.tar.gz", hash = "sha256:0c09827d26fffda27f1be2fed7a7a01a29c5ddcd2eb6393ad5ebf9d77e9deae8"},
 ]
 
 [package.dependencies]
@@ -702,27 +714,27 @@ typing-inspect = ">=0.4.0,<1"
 
 [[package]]
 name = "deepdiff"
-version = "6.7.1"
+version = "7.0.1"
 description = "Deep Difference and Search of any Python object/data. Recreate objects by adding adding deltas to each other."
-optional = true
-python-versions = ">=3.7"
+optional = false
+python-versions = ">=3.8"
 files = [
-    {file = "deepdiff-6.7.1-py3-none-any.whl", hash = "sha256:58396bb7a863cbb4ed5193f548c56f18218060362311aa1dc36397b2f25108bd"},
-    {file = "deepdiff-6.7.1.tar.gz", hash = "sha256:b367e6fa6caac1c9f500adc79ada1b5b1242c50d5f716a1a4362030197847d30"},
+    {file = "deepdiff-7.0.1-py3-none-any.whl", hash = "sha256:447760081918216aa4fd4ca78a4b6a848b81307b2ea94c810255334b759e1dc3"},
+    {file = "deepdiff-7.0.1.tar.gz", hash = "sha256:260c16f052d4badbf60351b4f77e8390bee03a0b516246f6839bc813fb429ddf"},
 ]
 
 [package.dependencies]
-ordered-set = ">=4.0.2,<4.2.0"
+ordered-set = ">=4.1.0,<4.2.0"
 
 [package.extras]
-cli = ["click (==8.1.3)", "pyyaml (==6.0.1)"]
+cli = ["click (==8.1.7)", "pyyaml (==6.0.1)"]
 optimize = ["orjson"]
 
 [[package]]
 name = "deprecated"
 version = "1.2.14"
 description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
     {file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
@@ -761,7 +773,7 @@ files = [
 name = "dnspython"
 version = "2.6.1"
 description = "DNS toolkit"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "dnspython-2.6.1-py3-none-any.whl", hash = "sha256:5ef3b9680161f6fa89daf8ad451b5f1a33b18ae8a1c6778cdf4b43f08c0a6e50"},
@@ -777,15 +789,30 @@ idna = ["idna (>=3.6)"]
 trio = ["trio (>=0.23)"]
 wmi = ["wmi (>=1.5.1)"]
 
+[[package]]
+name = "email-validator"
+version = "2.1.1"
+description = "A robust email address syntax and deliverability validation library."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "email_validator-2.1.1-py3-none-any.whl", hash = "sha256:97d882d174e2a65732fb43bfce81a3a834cbc1bde8bf419e30ef5ea976370a05"},
+    {file = "email_validator-2.1.1.tar.gz", hash = "sha256:200a70680ba08904be6d1eef729205cc0d687634399a5924d842533efb824b84"},
+]
+
+[package.dependencies]
+dnspython = ">=2.0.0"
+idna = ">=2.0.0"
+
 [[package]]
 name = "emoji"
-version = "2.10.1"
+version = "2.11.1"
 description = "Emoji for Python"
-optional = true
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
 files = [
-    {file = "emoji-2.10.1-py2.py3-none-any.whl", hash = "sha256:11fb369ea79d20c14efa4362c732d67126df294a7959a2c98bfd7447c12a218e"},
-    {file = "emoji-2.10.1.tar.gz", hash = "sha256:16287283518fb7141bde00198f9ffff4e1c1cb570efb68b2f1ec50975c3a581d"},
+    {file = "emoji-2.11.1-py2.py3-none-any.whl", hash = "sha256:b7ba25299bbf520cc8727848ae66b986da32aee27dc2887eaea2bff07226ce49"},
+    {file = "emoji-2.11.1.tar.gz", hash = "sha256:062ff0b3154b6219143f8b9f4b3e5c64c35bc2b146e6e2349ab5f29e218ce1ee"},
 ]
 
 [package.extras]
@@ -793,13 +820,13 @@ dev = ["coverage", "coveralls", "pytest"]
 
 [[package]]
 name = "exceptiongroup"
-version = "1.2.0"
+version = "1.2.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"},
-    {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
+    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
+    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
 ]
 
 [package.extras]
@@ -807,22 +834,46 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "fastapi"
-version = "0.110.0"
+version = "0.111.0"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fastapi-0.110.0-py3-none-any.whl", hash = "sha256:87a1f6fb632a218222c5984be540055346a8f5d8a68e8f6fb647b1dc9934de4b"},
-    {file = "fastapi-0.110.0.tar.gz", hash = "sha256:266775f0dcc95af9d3ef39bad55cff525329a931d5fd51930aadd4f428bf7ff3"},
+    {file = "fastapi-0.111.0-py3-none-any.whl", hash = "sha256:97ecbf994be0bcbdadedf88c3150252bed7b2087075ac99735403b1b76cc8fc0"},
+    {file = "fastapi-0.111.0.tar.gz", hash = "sha256:b9db9dd147c91cb8b769f7183535773d8741dd46f9dc6676cd82eab510228cd7"},
 ]
 
 [package.dependencies]
+email_validator = ">=2.0.0"
+fastapi-cli = ">=0.0.2"
+httpx = ">=0.23.0"
+jinja2 = ">=2.11.2"
+orjson = ">=3.2.1"
 pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
-starlette = ">=0.36.3,<0.37.0"
+python-multipart = ">=0.0.7"
+starlette = ">=0.37.2,<0.38.0"
 typing-extensions = ">=4.8.0"
+ujson = ">=4.0.1,<4.0.2 || >4.0.2,<4.1.0 || >4.1.0,<4.2.0 || >4.2.0,<4.3.0 || >4.3.0,<5.0.0 || >5.0.0,<5.1.0 || >5.1.0"
+uvicorn = {version = ">=0.12.0", extras = ["standard"]}
 
 [package.extras]
-all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+all = ["email_validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+
+[[package]]
+name = "fastapi-cli"
+version = "0.0.3"
+description = "Run and manage FastAPI apps from the command line with FastAPI CLI. 🚀"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fastapi_cli-0.0.3-py3-none-any.whl", hash = "sha256:ae233115f729945479044917d949095e829d2d84f56f55ce1ca17627872825a5"},
+    {file = "fastapi_cli-0.0.3.tar.gz", hash = "sha256:3b6e4d2c4daee940fb8db59ebbfd60a72c4b962bcf593e263e4cc69da4ea3d7f"},
+]
+
+[package.dependencies]
+fastapi = "*"
+typer = ">=0.12.3"
+uvicorn = {version = ">=0.15.0", extras = ["standard"]}
 
 [[package]]
 name = "fastavro"
@@ -872,25 +923,25 @@ zstandard = ["zstandard"]
 
 [[package]]
 name = "filelock"
-version = "3.13.1"
+version = "3.14.0"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "filelock-3.13.1-py3-none-any.whl", hash = "sha256:57dbda9b35157b05fb3e58ee91448612eb674172fab98ee235ccb0b5bee19a1c"},
-    {file = "filelock-3.13.1.tar.gz", hash = "sha256:521f5f56c50f8426f5e03ad3b281b490a87ef15bc6c526f168290f0c7148d44e"},
+    {file = "filelock-3.14.0-py3-none-any.whl", hash = "sha256:43339835842f110ca7ae60f1e1c160714c5a6afd15a2873419ab185334975c0f"},
+    {file = "filelock-3.14.0.tar.gz", hash = "sha256:6ea72da3be9b8c82afd3edcf99f2fffbb5076335a5ae4d03248bb5b6c3eae78a"},
 ]
 
 [package.extras]
-docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.24)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
+docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
 typing = ["typing-extensions (>=4.8)"]
 
 [[package]]
 name = "filetype"
 version = "1.2.0"
 description = "Infer file type and MIME type of any file/buffer. No external dependencies."
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "filetype-1.2.0-py2.py3-none-any.whl", hash = "sha256:7ce71b6880181241cf7ac8697a2f1eb6a8bd9b429f7ad6d27b8db9ba5f1c2d25"},
@@ -899,13 +950,13 @@ files = [
 
 [[package]]
 name = "flatbuffers"
-version = "24.3.7"
+version = "24.3.25"
 description = "The FlatBuffers serialization format for Python"
-optional = true
+optional = false
 python-versions = "*"
 files = [
-    {file = "flatbuffers-24.3.7-py2.py3-none-any.whl", hash = "sha256:80c4f5dcad0ee76b7e349671a0d657f2fbba927a0244f88dd3f5ed6a3694e1fc"},
-    {file = "flatbuffers-24.3.7.tar.gz", hash = "sha256:0895c22b9a6019ff2f4de2e5e2f7cd15914043e6e7033a94c0c6369422690f22"},
+    {file = "flatbuffers-24.3.25-py2.py3-none-any.whl", hash = "sha256:8dbdec58f935f3765e4f7f3cf635ac3a77f83568138d6a2311f524ec96364812"},
+    {file = "flatbuffers-24.3.25.tar.gz", hash = "sha256:de2ec5b203f21441716617f38443e0a8ebf3d25bf0d9c0bb0ce68fa00ad546a4"},
 ]
 
 [[package]]
@@ -996,13 +1047,13 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2024.3.1"
+version = "2024.5.0"
 description = "File-system specification"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fsspec-2024.3.1-py3-none-any.whl", hash = "sha256:918d18d41bf73f0e2b261824baeb1b124bcf771767e3a26425cd7dec3332f512"},
-    {file = "fsspec-2024.3.1.tar.gz", hash = "sha256:f39780e282d7d117ffb42bb96992f8a90795e4d0fb0f661a70ca39fe9c43ded9"},
+    {file = "fsspec-2024.5.0-py3-none-any.whl", hash = "sha256:e0fdbc446d67e182f49a70b82cf7889028a63588fde6b222521f10937b2b670c"},
+    {file = "fsspec-2024.5.0.tar.gz", hash = "sha256:1d021b0b0f933e3b3029ed808eb400c08ba101ca2de4b3483fbc9ca23fcee94a"},
 ]
 
 [package.extras]
@@ -1010,7 +1061,7 @@ abfs = ["adlfs"]
 adl = ["adlfs"]
 arrow = ["pyarrow (>=1)"]
 dask = ["dask", "distributed"]
-devel = ["pytest", "pytest-cov"]
+dev = ["pre-commit", "ruff"]
 dropbox = ["dropbox", "dropboxdrivefs", "requests"]
 full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
 fuse = ["fusepy"]
@@ -1027,6 +1078,9 @@ s3 = ["s3fs"]
 sftp = ["paramiko"]
 smb = ["smbprotocol"]
 ssh = ["paramiko"]
+test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
+test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
+test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
 tqdm = ["tqdm"]
 
 [[package]]
@@ -1047,13 +1101,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 
 [[package]]
 name = "google-api-core"
-version = "2.18.0"
+version = "2.19.0"
 description = "Google API client core library"
 optional = true
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.18.0.tar.gz", hash = "sha256:62d97417bfc674d6cef251e5c4d639a9655e00c45528c4364fbfebb478ce72a9"},
-    {file = "google_api_core-2.18.0-py3-none-any.whl", hash = "sha256:5a63aa102e0049abe85b5b88cb9409234c1f70afcda21ce1e40b285b9629c1d6"},
+    {file = "google-api-core-2.19.0.tar.gz", hash = "sha256:cf1b7c2694047886d2af1128a03ae99e391108a08804f87cfd35970e49c9cd10"},
+    {file = "google_api_core-2.19.0-py3-none-any.whl", hash = "sha256:8661eec4078c35428fd3f69a2c7ee29e342896b70f01d1a1cbcb334372dd6251"},
 ]
 
 [package.dependencies]
@@ -1080,7 +1134,7 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 name = "google-auth"
 version = "2.29.0"
 description = "Google Authentication Library"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "google-auth-2.29.0.tar.gz", hash = "sha256:672dff332d073227550ffc7457868ac4218d6c500b155fe6cc17d2b13602c360"},
@@ -1124,7 +1178,7 @@ dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "py
 name = "googleapis-common-protos"
 version = "1.63.0"
 description = "Common protobufs used in Google APIs"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "googleapis-common-protos-1.63.0.tar.gz", hash = "sha256:17ad01b11d5f1d0171c06d3ba5c04c54474e883b66b949722b4938ee2694ef4e"},
@@ -1210,84 +1264,76 @@ test = ["objgraph", "psutil"]
 
 [[package]]
 name = "grpcio"
-version = "1.62.1"
+version = "1.63.0"
 description = "HTTP/2-based RPC framework"
-optional = true
-python-versions = ">=3.7"
+optional = false
+python-versions = ">=3.8"
 files = [
-    {file = "grpcio-1.62.1-cp310-cp310-linux_armv7l.whl", hash = "sha256:179bee6f5ed7b5f618844f760b6acf7e910988de77a4f75b95bbfaa8106f3c1e"},
-    {file = "grpcio-1.62.1-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:48611e4fa010e823ba2de8fd3f77c1322dd60cb0d180dc6630a7e157b205f7ea"},
-    {file = "grpcio-1.62.1-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:b2a0e71b0a2158aa4bce48be9f8f9eb45cbd17c78c7443616d00abbe2a509f6d"},
-    {file = "grpcio-1.62.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:fbe80577c7880911d3ad65e5ecc997416c98f354efeba2f8d0f9112a67ed65a5"},
-    {file = "grpcio-1.62.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58f6c693d446964e3292425e1d16e21a97a48ba9172f2d0df9d7b640acb99243"},
-    {file = "grpcio-1.62.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:77c339403db5a20ef4fed02e4d1a9a3d9866bf9c0afc77a42234677313ea22f3"},
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-    {file = "grpcio-1.62.1-cp310-cp310-win32.whl", hash = "sha256:4187201a53f8561c015bc745b81a1b2d278967b8de35f3399b84b0695e281d5f"},
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 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.62.1)"]
+protobuf = ["grpcio-tools (>=1.63.0)"]
 
 [[package]]
 name = "grpcio-status"
-version = "1.62.1"
+version = "1.62.2"
 description = "Status proto mapping for gRPC"
 optional = true
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
 googleapis-common-protos = ">=1.5.5"
-grpcio = ">=1.62.1"
+grpcio = ">=1.62.2"
 protobuf = ">=4.21.6"
 
 [[package]]
@@ -1303,13 +1349,13 @@ files = [
 
 [[package]]
 name = "httpcore"
-version = "1.0.4"
+version = "1.0.5"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1320,13 +1366,13 @@ h11 = ">=0.13,<0.15"
 asyncio = ["anyio (>=4.0,<5.0)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
-trio = ["trio (>=0.22.0,<0.25.0)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
 
 [[package]]
 name = "httptools"
 version = "0.6.1"
 description = "A collection of framework independent HTTP protocol utils."
-optional = true
+optional = false
 python-versions = ">=3.8.0"
 files = [
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@@ -1396,13 +1442,13 @@ socks = ["socksio (==1.*)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.21.4"
+version = "0.23.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
-optional = true
+optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "huggingface_hub-0.21.4-py3-none-any.whl", hash = "sha256:df37c2c37fc6c82163cdd8a67ede261687d80d1e262526d6c0ce73b6b3630a7b"},
-    {file = "huggingface_hub-0.21.4.tar.gz", hash = "sha256:e1f4968c93726565a80edf6dc309763c7b546d0cfe79aa221206034d50155531"},
+    {file = "huggingface_hub-0.23.0-py3-none-any.whl", hash = "sha256:075c30d48ee7db2bba779190dc526d2c11d422aed6f9044c5e2fdc2c432fdb91"},
+    {file = "huggingface_hub-0.23.0.tar.gz", hash = "sha256:7126dedd10a4c6fac796ced4d87a8cf004efc722a5125c2c09299017fa366fa9"},
 ]
 
 [package.dependencies]
@@ -1415,15 +1461,16 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
 [package.extras]
-all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 cli = ["InquirerPy (==0.3.4)"]
-dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
 hf-transfer = ["hf-transfer (>=0.1.4)"]
-inference = ["aiohttp", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)"]
-quality = ["mypy (==1.5.1)", "ruff (>=0.1.3)"]
+inference = ["aiohttp", "minijinja (>=1.0)"]
+quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
 tensorflow = ["graphviz", "pydot", "tensorflow"]
-testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+tensorflow-testing = ["keras (<3.0)", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
 torch = ["safetensors", "torch"]
 typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
 
@@ -1431,7 +1478,7 @@ typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "t
 name = "humanfriendly"
 version = "10.0"
 description = "Human friendly output for text interfaces using Python"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 files = [
     {file = "humanfriendly-10.0-py2.py3-none-any.whl", hash = "sha256:1697e1a8a8f550fd43c2865cd84542fc175a61dcb779b6fee18cf6b6ccba1477"},
@@ -1443,13 +1490,13 @@ pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_ve
 
 [[package]]
 name = "identify"
-version = "2.5.35"
+version = "2.5.36"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "identify-2.5.35-py2.py3-none-any.whl", hash = "sha256:c4de0081837b211594f8e877a6b4fad7ca32bbfc1a9307fdd61c28bfe923f13e"},
-    {file = "identify-2.5.35.tar.gz", hash = "sha256:10a7ca245cfcd756a554a7288159f72ff105ad233c7c4b9c6f0f4d108f5f6791"},
+    {file = "identify-2.5.36-py2.py3-none-any.whl", hash = "sha256:37d93f380f4de590500d9dba7db359d0d3da95ffe7f9de1753faa159e71e7dfa"},
+    {file = "identify-2.5.36.tar.gz", hash = "sha256:e5e00f54165f9047fbebeb4a560f9acfb8af4c88232be60a488e9b68d122745d"},
 ]
 
 [package.extras]
@@ -1457,13 +1504,13 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
-version = "3.6"
+version = "3.7"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
-    {file = "idna-3.6-py3-none-any.whl", hash = "sha256:c05567e9c24a6b9faaa835c4821bad0590fbb9d5779e7caa6e1cc4978e7eb24f"},
-    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
+    {file = "idna-3.7-py3-none-any.whl", hash = "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"},
+    {file = "idna-3.7.tar.gz", hash = "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc"},
 ]
 
 [[package]]
@@ -1494,7 +1541,7 @@ tests = ["black (>=23.3.0)", "flake8 (>=3.8.2)", "keras (>=2.4.3)", "mypy (>=1.3
 name = "importlib-metadata"
 version = "6.11.0"
 description = "Read metadata from Python packages"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "importlib_metadata-6.11.0-py3-none-any.whl", hash = "sha256:f0afba6205ad8f8947c7d338b5342d5db2afbfd82f9cbef7879a9539cc12eb9b"},
@@ -1513,7 +1560,7 @@ testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs
 name = "importlib-resources"
 version = "6.4.0"
 description = "Read resources from Python packages"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "importlib_resources-6.4.0-py3-none-any.whl", hash = "sha256:50d10f043df931902d4194ea07ec57960f66a80449ff867bfe782b4c486ba78c"},
@@ -1538,6 +1585,20 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
+[[package]]
+name = "intel-openmp"
+version = "2021.4.0"
+description = "Intel OpenMP* Runtime Library"
+optional = false
+python-versions = "*"
+files = [
+    {file = "intel_openmp-2021.4.0-py2.py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.whl", hash = "sha256:41c01e266a7fdb631a7609191709322da2bbf24b252ba763f125dd651bcc7675"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-manylinux1_i686.whl", hash = "sha256:3b921236a38384e2016f0f3d65af6732cf2c12918087128a9163225451e776f2"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-manylinux1_x86_64.whl", hash = "sha256:e2240ab8d01472fed04f3544a878cda5da16c26232b7ea1b59132dbfb48b186e"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-win32.whl", hash = "sha256:6e863d8fd3d7e8ef389d52cf97a50fe2afe1a19247e8c0d168ce021546f96fc9"},
+    {file = "intel_openmp-2021.4.0-py2.py3-none-win_amd64.whl", hash = "sha256:eef4c8bcc8acefd7f5cd3b9384dbf73d59e2c99fc56545712ded913f43c4a94f"},
+]
+
 [[package]]
 name = "isort"
 version = "5.13.2"
@@ -1554,13 +1615,13 @@ colors = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.3"
+version = "3.1.4"
 description = "A very fast and expressive template engine."
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "Jinja2-3.1.3-py3-none-any.whl", hash = "sha256:7d6d50dd97d52cbc355597bd845fabfbac3f551e1f99619e39a35ce8c370b5fa"},
-    {file = "Jinja2-3.1.3.tar.gz", hash = "sha256:ac8bd6544d4bb2c9792bf3a159e80bba8fda7f07e81bc3aed565432d5925ba90"},
+    {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
+    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
 ]
 
 [package.dependencies]
@@ -1582,20 +1643,20 @@ files = [
 
 [[package]]
 name = "joblib"
-version = "1.3.2"
+version = "1.4.2"
 description = "Lightweight pipelining with Python functions"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "joblib-1.3.2-py3-none-any.whl", hash = "sha256:ef4331c65f239985f3f2220ecc87db222f08fd22097a3dd5698f693875f8cbb9"},
-    {file = "joblib-1.3.2.tar.gz", hash = "sha256:92f865e621e17784e7955080b6d042489e3b8e294949cc44c6eac304f59772b1"},
+    {file = "joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6"},
+    {file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"},
 ]
 
 [[package]]
 name = "jsonpatch"
 version = "1.33"
 description = "Apply JSON-Patches (RFC 6902)"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
     {file = "jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade"},
@@ -1609,7 +1670,7 @@ jsonpointer = ">=1.9"
 name = "jsonpath-python"
 version = "1.0.6"
 description = "A more powerful JSONPath implementation in modern python"
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
     {file = "jsonpath-python-1.0.6.tar.gz", hash = "sha256:dd5be4a72d8a2995c3f583cf82bf3cd1a9544cfdabf2d22595b67aff07349666"},
@@ -1620,7 +1681,7 @@ files = [
 name = "jsonpointer"
 version = "2.4"
 description = "Identify specific nodes in a JSON document (RFC 6901)"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
     {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
@@ -1631,7 +1692,7 @@ files = [
 name = "kubernetes"
 version = "29.0.0"
 description = "Kubernetes python client"
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
     {file = "kubernetes-29.0.0-py2.py3-none-any.whl", hash = "sha256:ab8cb0e0576ccdfb71886366efb102c6a20f268d817be065ce7f9909c631e43e"},
@@ -1681,13 +1742,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
 
 [[package]]
 name = "langchain-core"
-version = "0.1.34"
+version = "0.1.52"
 description = "Building applications with LLMs through composability"
-optional = true
+optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.1.34-py3-none-any.whl", hash = "sha256:9b4882e9dd3b612fc967acd1253a9bcb6a880b77433d20b8b87a60325b611920"},
-    {file = "langchain_core-0.1.34.tar.gz", hash = "sha256:f50612f292166f2c4ebfe76a94c4cbee310b4eb3da475fb252f3cd5d78935bff"},
+    {file = "langchain_core-0.1.52-py3-none-any.whl", hash = "sha256:62566749c92e8a1181c255c788548dc16dbc319d896cd6b9c95dc17af9b2a6db"},
+    {file = "langchain_core-0.1.52.tar.gz", hash = "sha256:084c3fc452f5a6966c28ab3ec5dbc8b8d26fc3f63378073928f4e29d90b6393f"},
 ]
 
 [package.dependencies]
@@ -1696,17 +1757,32 @@ langsmith = ">=0.1.0,<0.2.0"
 packaging = ">=23.2,<24.0"
 pydantic = ">=1,<3"
 PyYAML = ">=5.3"
-requests = ">=2,<3"
 tenacity = ">=8.1.0,<9.0.0"
 
 [package.extras]
 extended-testing = ["jinja2 (>=3,<4)"]
 
+[[package]]
+name = "langchain-openai"
+version = "0.1.7"
+description = "An integration package connecting OpenAI and LangChain"
+optional = false
+python-versions = "<4.0,>=3.8.1"
+files = [
+    {file = "langchain_openai-0.1.7-py3-none-any.whl", hash = "sha256:39c3cb22bb739900ae8294d4d9939a6138c0ca7ad11198e57038eb14c08d04ec"},
+    {file = "langchain_openai-0.1.7.tar.gz", hash = "sha256:fd7e1c33ba8e2cab4b2154f3a2fd4a0d9cc6518b41cf49bb87255f9f732a4896"},
+]
+
+[package.dependencies]
+langchain-core = ">=0.1.46,<0.3"
+openai = ">=1.24.0,<2.0.0"
+tiktoken = ">=0.7,<1"
+
 [[package]]
 name = "langdetect"
 version = "1.0.9"
 description = "Language detection library ported from Google's language-detection."
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "langdetect-1.0.9-py2-none-any.whl", hash = "sha256:7cbc0746252f19e76f77c0b1690aadf01963be835ef0cd4b56dddf2a8f1dfc2a"},
@@ -1718,13 +1794,13 @@ six = "*"
 
 [[package]]
 name = "langsmith"
-version = "0.1.33"
+version = "0.1.59"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
-optional = true
+optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.33-py3-none-any.whl", hash = "sha256:b84642d854b8f13ab6f540bb6d1c2b0e3e897add34b6d0880f3c3682c1a657fe"},
-    {file = "langsmith-0.1.33.tar.gz", hash = "sha256:d368b7817c5a871f5ef8ca73435498aec1cbe1b13419417c91a34cffa49767ad"},
+    {file = "langsmith-0.1.59-py3-none-any.whl", hash = "sha256:445e3bc1d3baa1e5340cd979907a19483b9763a2ed37b863a01113d406f69345"},
+    {file = "langsmith-0.1.59.tar.gz", hash = "sha256:e748a89f4dd6aa441349143e49e546c03b5dfb43376a25bfef6a5ca792fe1437"},
 ]
 
 [package.dependencies]
@@ -1732,116 +1808,159 @@ orjson = ">=3.9.14,<4.0.0"
 pydantic = ">=1,<3"
 requests = ">=2,<3"
 
-[[package]]
-name = "loguru"
-version = "0.7.2"
-description = "Python logging made (stupidly) simple"
-optional = true
-python-versions = ">=3.5"
-files = [
-    {file = "loguru-0.7.2-py3-none-any.whl", hash = "sha256:003d71e3d3ed35f0f8984898359d65b79e5b21943f78af86aa5491210429b8eb"},
-    {file = "loguru-0.7.2.tar.gz", hash = "sha256:e671a53522515f34fd406340ee968cb9ecafbc4b36c679da03c18fd8d0bd51ac"},
-]
-
-[package.dependencies]
-colorama = {version = ">=0.3.4", markers = "sys_platform == \"win32\""}
-win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""}
-
-[package.extras]
-dev = ["Sphinx (==7.2.5)", "colorama (==0.4.5)", "colorama (==0.4.6)", "exceptiongroup (==1.1.3)", "freezegun (==1.1.0)", "freezegun (==1.2.2)", "mypy (==v0.910)", "mypy (==v0.971)", "mypy (==v1.4.1)", "mypy (==v1.5.1)", "pre-commit (==3.4.0)", "pytest (==6.1.2)", "pytest (==7.4.0)", "pytest-cov (==2.12.1)", "pytest-cov (==4.1.0)", "pytest-mypy-plugins (==1.9.3)", "pytest-mypy-plugins (==3.0.0)", "sphinx-autobuild (==2021.3.14)", "sphinx-rtd-theme (==1.3.0)", "tox (==3.27.1)", "tox (==4.11.0)"]
-
 [[package]]
 name = "lxml"
-version = "5.1.0"
+version = "5.2.2"
 description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "lxml-5.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:704f5572ff473a5f897745abebc6df40f22d4133c1e0a1f124e4f2bd3330ff7e"},
-    {file = "lxml-5.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9d3c0f8567ffe7502d969c2c1b809892dc793b5d0665f602aad19895f8d508da"},
-    {file = "lxml-5.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:5fcfbebdb0c5d8d18b84118842f31965d59ee3e66996ac842e21f957eb76138c"},
-    {file = "lxml-5.1.0-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2f37c6d7106a9d6f0708d4e164b707037b7380fcd0b04c5bd9cae1fb46a856fb"},
-    {file = "lxml-5.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2befa20a13f1a75c751f47e00929fb3433d67eb9923c2c0b364de449121f447c"},
-    {file = "lxml-5.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:22b7ee4c35f374e2c20337a95502057964d7e35b996b1c667b5c65c567d2252a"},
-    {file = "lxml-5.1.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:bf8443781533b8d37b295016a4b53c1494fa9a03573c09ca5104550c138d5c05"},
-    {file = "lxml-5.1.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:82bddf0e72cb2af3cbba7cec1d2fd11fda0de6be8f4492223d4a268713ef2147"},
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+    {file = "lxml-5.2.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:ff69a9a0b4b17d78170c73abe2ab12084bdf1691550c5629ad1fe7849433f324"},
+    {file = "lxml-5.2.2.tar.gz", hash = "sha256:bb2dc4898180bea79863d5487e5f9c7c34297414bad54bcd0f0852aee9cfdb87"},
 ]
 
 [package.extras]
 cssselect = ["cssselect (>=0.7)"]
+html-clean = ["lxml-html-clean"]
 html5 = ["html5lib"]
 htmlsoup = ["BeautifulSoup4"]
-source = ["Cython (>=3.0.7)"]
+source = ["Cython (>=3.0.10)"]
 
 [[package]]
 name = "mapie"
@@ -1860,11 +1979,35 @@ packaging = "*"
 scikit-learn = "*"
 scipy = "*"
 
+[[package]]
+name = "markdown-it-py"
+version = "3.0.0"
+description = "Python port of markdown-it. Markdown parsing, done right!"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"},
+    {file = "markdown_it_py-3.0.0-py3-none-any.whl", hash = "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1"},
+]
+
+[package.dependencies]
+mdurl = ">=0.1,<1.0"
+
+[package.extras]
+benchmarking = ["psutil", "pytest", "pytest-benchmark"]
+code-style = ["pre-commit (>=3.0,<4.0)"]
+compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
+linkify = ["linkify-it-py (>=1,<3)"]
+plugins = ["mdit-py-plugins"]
+profiling = ["gprof2dot"]
+rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
+
 [[package]]
 name = "markupsafe"
 version = "2.1.5"
 description = "Safely add untrusted strings to HTML/XML markup."
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "MarkupSafe-2.1.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a17a92de5231666cfbe003f0e4b9b3a7ae3afb1ec2845aadc2bacc93ff85febc"},
@@ -1931,13 +2074,13 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.21.1"
+version = "3.21.2"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "marshmallow-3.21.1-py3-none-any.whl", hash = "sha256:f085493f79efb0644f270a9bf2892843142d80d7174bbbd2f3713f2a589dc633"},
-    {file = "marshmallow-3.21.1.tar.gz", hash = "sha256:4e65e9e0d80fc9e609574b9983cf32579f305c718afb30d7233ab818571768c3"},
+    {file = "marshmallow-3.21.2-py3-none-any.whl", hash = "sha256:70b54a6282f4704d12c0a41599682c5c5450e843b9ec406308653b47c59648a1"},
+    {file = "marshmallow-3.21.2.tar.gz", hash = "sha256:82408deadd8b33d56338d2182d455db632c6313aa2af61916672146bb32edc56"},
 ]
 
 [package.dependencies]
@@ -1945,14 +2088,43 @@ packaging = ">=17.0"
 
 [package.extras]
 dev = ["marshmallow[tests]", "pre-commit (>=3.5,<4.0)", "tox"]
-docs = ["alabaster (==0.7.16)", "autodocsumm (==0.2.12)", "sphinx (==7.2.6)", "sphinx-issues (==4.0.0)", "sphinx-version-warning (==1.1.2)"]
+docs = ["alabaster (==0.7.16)", "autodocsumm (==0.2.12)", "sphinx (==7.3.7)", "sphinx-issues (==4.1.0)", "sphinx-version-warning (==1.1.2)"]
 tests = ["pytest", "pytz", "simplejson"]
 
+[[package]]
+name = "mdurl"
+version = "0.1.2"
+description = "Markdown URL utilities"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"},
+    {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
+]
+
+[[package]]
+name = "mkl"
+version = "2021.4.0"
+description = "Intel® oneAPI Math Kernel Library"
+optional = false
+python-versions = "*"
+files = [
+    {file = "mkl-2021.4.0-py2.py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.whl", hash = "sha256:67460f5cd7e30e405b54d70d1ed3ca78118370b65f7327d495e9c8847705e2fb"},
+    {file = "mkl-2021.4.0-py2.py3-none-manylinux1_i686.whl", hash = "sha256:636d07d90e68ccc9630c654d47ce9fdeb036bb46e2b193b3a9ac8cfea683cce5"},
+    {file = "mkl-2021.4.0-py2.py3-none-manylinux1_x86_64.whl", hash = "sha256:398dbf2b0d12acaf54117a5210e8f191827f373d362d796091d161f610c1ebfb"},
+    {file = "mkl-2021.4.0-py2.py3-none-win32.whl", hash = "sha256:439c640b269a5668134e3dcbcea4350459c4a8bc46469669b2d67e07e3d330e8"},
+    {file = "mkl-2021.4.0-py2.py3-none-win_amd64.whl", hash = "sha256:ceef3cafce4c009dd25f65d7ad0d833a0fbadc3d8903991ec92351fe5de1e718"},
+]
+
+[package.dependencies]
+intel-openmp = "==2021.*"
+tbb = "==2021.*"
+
 [[package]]
 name = "mmh3"
 version = "4.1.0"
 description = "Python extension for MurmurHash (MurmurHash3), a set of fast and robust hash functions."
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "mmh3-4.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:be5ac76a8b0cd8095784e51e4c1c9c318c19edcd1709a06eb14979c8d850c31a"},
@@ -2044,7 +2216,7 @@ test = ["mypy (>=1.0)", "pytest (>=7.0.0)"]
 name = "monotonic"
 version = "1.6"
 description = "An implementation of time.monotonic() for Python 2 & < 3.3"
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "monotonic-1.6-py2.py3-none-any.whl", hash = "sha256:68687e19a14f11f26d140dd5c86f3dba4bf5df58003000ed467e0e2a69bca96c"},
@@ -2055,7 +2227,7 @@ files = [
 name = "mpmath"
 version = "1.3.0"
 description = "Python library for arbitrary-precision floating-point arithmetic"
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c"},
@@ -2193,7 +2365,7 @@ files = [
 name = "networkx"
 version = "3.2.1"
 description = "Python package for creating and manipulating graphs and networks"
-optional = true
+optional = false
 python-versions = ">=3.9"
 files = [
     {file = "networkx-3.2.1-py3-none-any.whl", hash = "sha256:f18c69adc97877c42332c170849c96cefa91881c99a7cb3e95b7c659ebdc1ec2"},
@@ -2295,7 +2467,7 @@ files = [
 name = "nvidia-cublas-cu12"
 version = "12.1.3.1"
 description = "CUBLAS native runtime libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:ee53ccca76a6fc08fb9701aa95b6ceb242cdaab118c3bb152af4e579af792728"},
@@ -2306,7 +2478,7 @@ files = [
 name = "nvidia-cuda-cupti-cu12"
 version = "12.1.105"
 description = "CUDA profiling tools runtime libs."
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:e54fde3983165c624cb79254ae9818a456eb6e87a7fd4d56a2352c24ee542d7e"},
@@ -2317,7 +2489,7 @@ files = [
 name = "nvidia-cuda-nvrtc-cu12"
 version = "12.1.105"
 description = "NVRTC native runtime libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:339b385f50c309763ca65456ec75e17bbefcbbf2893f462cb8b90584cd27a1c2"},
@@ -2328,7 +2500,7 @@ files = [
 name = "nvidia-cuda-runtime-cu12"
 version = "12.1.105"
 description = "CUDA Runtime native Libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:6e258468ddf5796e25f1dc591a31029fa317d97a0a94ed93468fc86301d61e40"},
@@ -2339,7 +2511,7 @@ files = [
 name = "nvidia-cudnn-cu12"
 version = "8.9.2.26"
 description = "cuDNN runtime libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl", hash = "sha256:5ccb288774fdfb07a7e7025ffec286971c06d8d7b4fb162525334616d7629ff9"},
@@ -2352,7 +2524,7 @@ nvidia-cublas-cu12 = "*"
 name = "nvidia-cufft-cu12"
 version = "11.0.2.54"
 description = "CUFFT native runtime libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl", hash = "sha256:794e3948a1aa71fd817c3775866943936774d1c14e7628c74f6f7417224cdf56"},
@@ -2363,7 +2535,7 @@ files = [
 name = "nvidia-curand-cu12"
 version = "10.3.2.106"
 description = "CURAND native runtime libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:9d264c5036dde4e64f1de8c50ae753237c12e0b1348738169cd0f8a536c0e1e0"},
@@ -2374,7 +2546,7 @@ files = [
 name = "nvidia-cusolver-cu12"
 version = "11.4.5.107"
 description = "CUDA solver native runtime libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd"},
@@ -2390,7 +2562,7 @@ nvidia-nvjitlink-cu12 = "*"
 name = "nvidia-cusparse-cu12"
 version = "12.1.0.106"
 description = "CUSPARSE native runtime libraries"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c"},
@@ -2402,30 +2574,31 @@ nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
 name = "nvidia-nccl-cu12"
-version = "2.19.3"
+version = "2.20.5"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl", hash = "sha256:a9734707a2c96443331c1e48c717024aa6678a0e2a4cb66b2c364d18cee6b48d"},
+    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1fc150d5c3250b170b29410ba682384b14581db722b2531b0d8d33c595f33d01"},
+    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56"},
 ]
 
 [[package]]
 name = "nvidia-nvjitlink-cu12"
-version = "12.4.99"
+version = "12.4.127"
 description = "Nvidia JIT LTO Library"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nvjitlink_cu12-12.4.99-py3-none-manylinux2014_x86_64.whl", hash = "sha256:c6428836d20fe7e327191c175791d38570e10762edc588fb46749217cd444c74"},
-    {file = "nvidia_nvjitlink_cu12-12.4.99-py3-none-win_amd64.whl", hash = "sha256:991905ffa2144cb603d8ca7962d75c35334ae82bf92820b6ba78157277da1ad2"},
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:06b3b9b25bf3f8af351d664978ca26a16d2c5127dbd53c0497e28d1fb9611d57"},
+    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:fd9020c501d27d135f983c6d3e244b197a7ccad769e34df53a42e276b0e25fa1"},
 ]
 
 [[package]]
 name = "nvidia-nvtx-cu12"
 version = "12.1.105"
 description = "NVIDIA Tools Extension"
-optional = true
+optional = false
 python-versions = ">=3"
 files = [
     {file = "nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:dc21cf308ca5691e7c04d962e213f8a4aa9bbfa23d95412f452254c2caeb09e5"},
@@ -2436,7 +2609,7 @@ files = [
 name = "oauthlib"
 version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
     {file = "oauthlib-3.2.2-py3-none-any.whl", hash = "sha256:8139f29aac13e25d502680e9e19963e83f16838d48a0d71c287fe40e7067fbca"},
@@ -2450,36 +2623,36 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 
 [[package]]
 name = "onnxruntime"
-version = "1.17.1"
+version = "1.17.3"
 description = "ONNX Runtime is a runtime accelerator for Machine Learning models"
-optional = true
+optional = false
 python-versions = "*"
 files = [
-    {file = "onnxruntime-1.17.1-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:d43ac17ac4fa3c9096ad3c0e5255bb41fd134560212dc124e7f52c3159af5d21"},
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 ]
 
 [package.dependencies]
@@ -2492,13 +2665,13 @@ sympy = "*"
 
 [[package]]
 name = "openai"
-version = "1.14.2"
+version = "1.30.1"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -2515,42 +2688,42 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 
 [[package]]
 name = "opentelemetry-api"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Python API"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 deprecated = ">=1.2.6"
-importlib-metadata = ">=6.0,<7.0"
+importlib-metadata = ">=6.0,<=7.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-common"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Protobuf encoding"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-opentelemetry-proto = "1.23.0"
+opentelemetry-proto = "1.24.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-grpc"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2558,22 +2731,22 @@ deprecated = ">=1.2.6"
 googleapis-common-protos = ">=1.52,<2.0"
 grpcio = ">=1.0.0,<2.0.0"
 opentelemetry-api = ">=1.15,<2.0"
-opentelemetry-exporter-otlp-proto-common = "1.23.0"
-opentelemetry-proto = "1.23.0"
-opentelemetry-sdk = ">=1.23.0,<1.24.0"
+opentelemetry-exporter-otlp-proto-common = "1.24.0"
+opentelemetry-proto = "1.24.0"
+opentelemetry-sdk = ">=1.24.0,<1.25.0"
 
 [package.extras]
 test = ["pytest-grpc"]
 
 [[package]]
 name = "opentelemetry-instrumentation"
-version = "0.44b0"
+version = "0.45b0"
 description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "opentelemetry_instrumentation-0.45b0-py3-none-any.whl", hash = "sha256:06c02e2c952c1b076e8eaedf1b82f715e2937ba7eeacab55913dd434fbcec258"},
+    {file = "opentelemetry_instrumentation-0.45b0.tar.gz", hash = "sha256:6c47120a7970bbeb458e6a73686ee9ba84b106329a79e4a4a66761f933709c7e"},
 ]
 
 [package.dependencies]
@@ -2583,57 +2756,55 @@ wrapt = ">=1.0.0,<2.0.0"
 
 [[package]]
 name = "opentelemetry-instrumentation-asgi"
-version = "0.44b0"
+version = "0.45b0"
 description = "ASGI instrumentation for OpenTelemetry"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "opentelemetry_instrumentation_asgi-0.45b0-py3-none-any.whl", hash = "sha256:8be1157ed62f0db24e45fdf7933c530c4338bd025c5d4af7830e903c0756021b"},
+    {file = "opentelemetry_instrumentation_asgi-0.45b0.tar.gz", hash = "sha256:97f55620f163fd3d20323e9fd8dc3aacc826c03397213ff36b877e0f4b6b08a6"},
 ]
 
 [package.dependencies]
 asgiref = ">=3.0,<4.0"
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.44b0"
-opentelemetry-semantic-conventions = "0.44b0"
-opentelemetry-util-http = "0.44b0"
+opentelemetry-instrumentation = "0.45b0"
+opentelemetry-semantic-conventions = "0.45b0"
+opentelemetry-util-http = "0.45b0"
 
 [package.extras]
 instruments = ["asgiref (>=3.0,<4.0)"]
-test = ["opentelemetry-instrumentation-asgi[instruments]", "opentelemetry-test-utils (==0.44b0)"]
 
 [[package]]
 name = "opentelemetry-instrumentation-fastapi"
-version = "0.44b0"
+version = "0.45b0"
 description = "OpenTelemetry FastAPI Instrumentation"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation_fastapi-0.44b0-py3-none-any.whl", hash = "sha256:4441482944bea6676816668d56deb94af990e8c6e9582c581047e5d84c91d3c9"},
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+    {file = "opentelemetry_instrumentation_fastapi-0.45b0-py3-none-any.whl", hash = "sha256:77d9c123a363129148f5f66d44094f3d67aaaa2b201396d94782b4a7f9ce4314"},
+    {file = "opentelemetry_instrumentation_fastapi-0.45b0.tar.gz", hash = "sha256:5a6b91e1c08a01601845fcfcfdefd0a2aecdb3c356d4a436a3210cb58c21487e"},
 ]
 
 [package.dependencies]
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.44b0"
-opentelemetry-instrumentation-asgi = "0.44b0"
-opentelemetry-semantic-conventions = "0.44b0"
-opentelemetry-util-http = "0.44b0"
+opentelemetry-instrumentation = "0.45b0"
+opentelemetry-instrumentation-asgi = "0.45b0"
+opentelemetry-semantic-conventions = "0.45b0"
+opentelemetry-util-http = "0.45b0"
 
 [package.extras]
 instruments = ["fastapi (>=0.58,<1.0)"]
-test = ["httpx (>=0.22,<1.0)", "opentelemetry-instrumentation-fastapi[instruments]", "opentelemetry-test-utils (==0.44b0)", "requests (>=2.23,<3.0)"]
 
 [[package]]
 name = "opentelemetry-proto"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Python Proto"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "opentelemetry_proto-1.24.0-py3-none-any.whl", hash = "sha256:bcb80e1e78a003040db71ccf83f2ad2019273d1e0828089d183b18a1476527ce"},
+    {file = "opentelemetry_proto-1.24.0.tar.gz", hash = "sha256:ff551b8ad63c6cabb1845ce217a6709358dfaba0f75ea1fa21a61ceddc78cab8"},
 ]
 
 [package.dependencies]
@@ -2641,47 +2812,47 @@ protobuf = ">=3.19,<5.0"
 
 [[package]]
 name = "opentelemetry-sdk"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Python SDK"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "opentelemetry_sdk-1.24.0.tar.gz", hash = "sha256:75bc0563affffa827700e0f4f4a68e1e257db0df13372344aebc6f8a64cde2e5"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.23.0"
-opentelemetry-semantic-conventions = "0.44b0"
+opentelemetry-api = "1.24.0"
+opentelemetry-semantic-conventions = "0.45b0"
 typing-extensions = ">=3.7.4"
 
 [[package]]
 name = "opentelemetry-semantic-conventions"
-version = "0.44b0"
+version = "0.45b0"
 description = "OpenTelemetry Semantic Conventions"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "opentelemetry-util-http"
-version = "0.44b0"
+version = "0.45b0"
 description = "Web util for OpenTelemetry"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "opentelemetry_util_http-0.45b0.tar.gz", hash = "sha256:4ce08b6a7d52dd7c96b7705b5b4f06fdb6aa3eac1233b3b0bfef8a0cab9a92cd"},
 ]
 
 [[package]]
 name = "ordered-set"
 version = "4.1.0"
 description = "An OrderedSet is a custom MutableSet that remembers its order, so that every"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "ordered-set-4.1.0.tar.gz", hash = "sha256:694a8e44c87657c59292ede72891eb91d34131f6531463aab3009191c77364a8"},
@@ -2693,68 +2864,64 @@ dev = ["black", "mypy", "pytest"]
 
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 name = "orjson"
-version = "3.9.15"
+version = "3.10.3"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
-optional = true
+optional = false
 python-versions = ">=3.8"
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 [[package]]
 name = "overrides"
 version = "7.7.0"
 description = "A decorator to automatically detect mismatch when overriding a method."
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
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+version = "2.2.2"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
 python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
 numpy = [
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-    {version = ">=1.23.2,<2", markers = "python_version == \"3.11\""},
-    {version = ">=1.26.0,<2", markers = "python_version >= \"3.12\""},
+    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
+    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -2858,79 +3024,80 @@ files = [
 
 [[package]]
 name = "pillow"
-version = "10.2.0"
+version = "10.3.0"
 description = "Python Imaging Library (Fork)"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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@@ -2941,55 +3108,31 @@ tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "pa
 typing = ["typing-extensions"]
 xmp = ["defusedxml"]
 
-[[package]]
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-
 [[package]]
 name = "platformdirs"
-version = "4.2.0"
-description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
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+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
 files = [
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 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
+type = ["mypy (>=1.8)"]
 
 [[package]]
 name = "pluggy"
-version = "1.4.0"
+version = "1.5.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -3000,7 +3143,7 @@ testing = ["pytest", "pytest-benchmark"]
 name = "posthog"
 version = "3.5.0"
 description = "Integrate PostHog into any python application."
-optional = true
+optional = false
 python-versions = "*"
 files = [
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 [[package]]
 name = "pre-commit"
-version = "3.6.2"
+version = "3.7.1"
 description = "A framework for managing and maintaining multi-language pre-commit hooks."
 optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
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 ]
 
 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[package]]
+name = "pygments"
+version = "2.18.0"
+description = "Pygments is a syntax highlighting package written in Python."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pygments-2.18.0-py3-none-any.whl", hash = "sha256:b8e6aca0523f3ab76fee51799c488e38782ac06eafcf95e7ba832985c8e7b13a"},
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+]
+
+[package.extras]
+windows-terminal = ["colorama (>=0.4.6)"]
+
 [[package]]
 name = "pypdf"
-version = "4.1.0"
+version = "4.2.0"
 description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files"
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
-typing_extensions = {version = ">=3.7.4.3", markers = "python_version < \"3.10\""}
+typing_extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 crypto = ["PyCryptodome", "cryptography"]
@@ -3281,7 +3391,7 @@ image = ["Pillow (>=8.0.0)"]
 name = "pypika"
 version = "0.48.9"
 description = "A SQL query builder API for Python"
-optional = true
+optional = false
 python-versions = "*"
 files = [
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@@ -3289,23 +3399,20 @@ files = [
 
 [[package]]
 name = "pyproject-hooks"
-version = "1.0.0"
+version = "1.1.0"
 description = "Wrappers to call pyproject.toml-based build backend hooks."
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
-[package.dependencies]
-tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
-
 [[package]]
 name = "pyreadline3"
 version = "3.4.1"
 description = "A python implementation of GNU readline."
-optional = true
+optional = false
 python-versions = "*"
 files = [
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@@ -3364,29 +3471,43 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "python-iso639"
-version = "2024.2.7"
-description = "Look-up utilities for ISO 639 language codes and names"
-optional = true
+version = "2024.4.27"
+description = "ISO 639 language codes, names, and other associated information"
+optional = false
 python-versions = ">=3.8"
 files = [
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 [[package]]
 name = "python-magic"
 version = "0.4.27"
 description = "File type identification using libmagic"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 files = [
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 ]
 
+[[package]]
+name = "python-multipart"
+version = "0.0.9"
+description = "A streaming multipart parser for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
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+
 [[package]]
 name = "pytz"
 version = "2024.1"
@@ -3460,101 +3581,101 @@ files = [
 
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 [package.extras]
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 [[package]]
@@ -3685,13 +3792,13 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
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 [package.dependencies]
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 [package.extras]
 rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 
+[[package]]
+name = "rich"
+version = "13.7.1"
+description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
+optional = false
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+
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+jupyter = ["ipywidgets (>=7.5.1,<9)"]
+
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 name = "rouge"
 version = "1.0.1"
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 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
-optional = true
+optional = false
 python-versions = ">=3.6,<4"
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 scipy = ">=1.6.0"
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 [package.dependencies]
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 [[package]]
 name = "sentence-transformers"
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 description = "Multilingual text embeddings"
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 [package.dependencies]
@@ -3981,7 +4096,10 @@ scikit-learn = "*"
 scipy = "*"
 torch = ">=1.11.0"
 tqdm = "*"
-transformers = ">=4.32.0,<5.0.0"
+transformers = ">=4.34.0,<5.0.0"
+
+[package.extras]
+dev = ["pre-commit", "pytest", "ruff (>=0.3.0)"]
 
 [[package]]
 name = "sentencepiece"
@@ -4047,20 +4165,31 @@ files = [
 
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+[[package]]
+name = "shellingham"
+version = "1.5.4"
+description = "Tool to Detect Surrounding Shell"
+optional = false
+python-versions = ">=3.7"
+files = [
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 name = "six"
 version = "1.16.0"
@@ -4087,7 +4216,7 @@ files = [
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 version = "2.5"
 description = "A modern CSS selector implementation for Beautiful Soup."
-optional = true
+optional = false
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 [package.dependencies]
@@ -4183,13 +4312,13 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
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-version = "0.36.3"
+version = "0.37.2"
 description = "The little ASGI library that shines."
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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@@ -4203,7 +4332,7 @@ full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7
 name = "sympy"
 version = "1.12"
 description = "Computer algebra system (CAS) in Python"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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 version = "0.9.0"
 description = "Pretty-print tabular data"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
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 [package.extras]
 widechars = ["wcwidth"]
 
+[[package]]
+name = "tbb"
+version = "2021.12.0"
+description = "Intel® oneAPI Threading Building Blocks (oneTBB)"
+optional = false
+python-versions = "*"
+files = [
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 [[package]]
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+version = "8.3.0"
 description = "Retry code until it succeeds"
 optional = false
-python-versions = ">=3.7"
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 files = [
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 [package.extras]
-doc = ["reno", "sphinx", "tornado (>=4.5)"]
+doc = ["reno", "sphinx"]
+test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
 [[package]]
 name = "thefuzz"
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 [[package]]
 name = "threadpoolctl"
-version = "3.4.0"
+version = "3.5.0"
 description = "threadpoolctl"
 optional = false
 python-versions = ">=3.8"
 files = [
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 name = "tiktoken"
-version = "0.5.2"
+version = "0.7.0"
 description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
-optional = true
+optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -4320,130 +4463,120 @@ blobfile = ["blobfile (>=2)"]
 
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 description = ""
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 ]
 
 [package.dependencies]
-huggingface_hub = ">=0.16.4,<1.0"
+huggingface-hub = ">=0.16.4,<1.0"
 
 [package.extras]
 dev = ["tokenizers[testing]"]
-docs = ["setuptools_rust", "sphinx", "sphinx_rtd_theme"]
-testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests"]
+docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
+testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
 
 [[package]]
 name = "tomli"
@@ -4458,42 +4591,38 @@ files = [
 
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 name = "torch"
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 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
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+    {file = "torch-2.3.0-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:760f8bedff506ce9e6e103498f9b1e9e15809e008368594c3a66bf74a8a51380"},
 ]
 
 [package.dependencies]
 filelock = "*"
 fsspec = "*"
 jinja2 = "*"
+mkl = {version = ">=2021.1.1,<=2021.4.0", markers = "platform_system == \"Windows\""}
 networkx = "*"
 nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
@@ -4504,10 +4633,10 @@ nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linu
 nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
-triton = {version = "2.2.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
+triton = {version = "2.3.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
@@ -4516,13 +4645,13 @@ optree = ["optree (>=0.9.1)"]
 
 [[package]]
 name = "tqdm"
-version = "4.66.2"
+version = "4.66.4"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "tqdm-4.66.4-py3-none-any.whl", hash = "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644"},
+    {file = "tqdm-4.66.4.tar.gz", hash = "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb"},
 ]
 
 [package.dependencies]
@@ -4536,13 +4665,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "transformers"
-version = "4.39.0"
+version = "4.40.2"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
-optional = true
+optional = false
 python-versions = ">=3.8.0"
 files = [
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+    {file = "transformers-4.40.2-py3-none-any.whl", hash = "sha256:71cb94301ec211a2e1d4b8c8d18dcfaa902dfa00a089dceca167a8aa265d6f2d"},
+    {file = "transformers-4.40.2.tar.gz", hash = "sha256:657b6054a2097671398d976ad46e60836e7e15f9ea9551631a96e33cb9240649"},
 ]
 
 [package.dependencies]
@@ -4554,21 +4683,21 @@ pyyaml = ">=5.1"
 regex = "!=2019.12.17"
 requests = "*"
 safetensors = ">=0.4.1"
-tokenizers = ">=0.14,<0.19"
+tokenizers = ">=0.19,<0.20"
 tqdm = ">=4.27"
 
 [package.extras]
 accelerate = ["accelerate (>=0.21.0)"]
 agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
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 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 codecarbon = ["codecarbon (==1.2.0)"]
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 docs-specific = ["hf-doc-builder"]
 flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)"]
 flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
@@ -4589,32 +4718,32 @@ serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
 sigopt = ["sigopt"]
 sklearn = ["scikit-learn"]
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 [package.dependencies]
@@ -4627,41 +4756,37 @@ tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
 
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+version = "0.12.3"
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 typing-extensions = ">=3.7.4.3"
 
-[package.extras]
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-
 [[package]]
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 description = "Backported and Experimental Type Hints for Python 3.8+"
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 version = "0.9.0"
 description = "Runtime inspection utilities for typing module."
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+optional = false
 python-versions = "*"
 files = [
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 ]
 
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+]
+
 [[package]]
 name = "unstructured"
-version = "0.11.8"
+version = "0.13.7"
 description = "A library that prepares raw documents for downstream ML tasks."
-optional = true
-python-versions = ">=3.7.0"
+optional = false
+python-versions = "<3.12,>=3.9.0"
 files = [
-    {file = "unstructured-0.11.8-py3-none-any.whl", hash = "sha256:71e8d135a723d8c692a0a43683e3dca4a9b3e0fd8a1d255f57689591ed3860c0"},
-    {file = "unstructured-0.11.8.tar.gz", hash = "sha256:dba8b2d54fdc781acef6c9590510e1f55e7467abaaf00403031331903d415f07"},
+    {file = "unstructured-0.13.7-py3-none-any.whl", hash = "sha256:a3d8f3037cb3063661531c6ecc04aca6df93c293ba06e36d67ffc70857a6f208"},
+    {file = "unstructured-0.13.7.tar.gz", hash = "sha256:5d59161d353b7006d8c6ee6f1a39154a5a11a5aaa258aac3fe90a8d44016aa6c"},
 ]
 
 [package.dependencies]
@@ -4716,54 +4928,61 @@ wrapt = "*"
 
 [package.extras]
 airtable = ["pyairtable"]
-all-docs = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.0)", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.18)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
-azure = ["adlfs", "fsspec (==2023.9.1)"]
+all-docs = ["google-cloud-vision", "markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypandoc", "pypdf", "python-docx", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.31)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
+astra = ["astrapy"]
+azure = ["adlfs", "fsspec"]
 azure-cognitive-search = ["azure-search-documents"]
-bedrock = ["boto3", "langchain"]
+bedrock = ["boto3", "langchain-community"]
 biomed = ["bs4"]
-box = ["boxfs", "fsspec (==2023.9.1)"]
-chroma = ["chromadb"]
+box = ["boxfs", "fsspec"]
+chroma = ["chromadb", "importlib-metadata (>=7.1.0)", "typer (<=0.9.0)"]
+clarifai = ["clarifai"]
 confluence = ["atlassian-python-api"]
 csv = ["pandas"]
-delta-table = ["deltalake", "fsspec (==2023.9.1)"]
+databricks-volumes = ["databricks-sdk"]
+delta-table = ["deltalake", "fsspec"]
 discord = ["discord-py"]
-doc = ["python-docx (>=1.1.0)"]
-docx = ["python-docx (>=1.1.0)"]
-dropbox = ["dropboxdrivefs", "fsspec (==2023.9.1)"]
+doc = ["python-docx"]
+docx = ["python-docx"]
+dropbox = ["dropboxdrivefs", "fsspec"]
 elasticsearch = ["elasticsearch"]
-embed-huggingface = ["huggingface", "langchain", "sentence-transformers"]
+embed-huggingface = ["huggingface", "langchain-community", "sentence-transformers"]
+embed-octoai = ["openai", "tiktoken"]
+embed-vertexai = ["langchain", "langchain-community", "langchain-google-vertexai"]
 epub = ["pypandoc"]
-gcs = ["bs4", "fsspec (==2023.9.1)", "gcsfs"]
+gcs = ["bs4", "fsspec", "gcsfs"]
 github = ["pygithub (>1.58.0)"]
 gitlab = ["python-gitlab"]
 google-drive = ["google-api-python-client"]
-hubspot = ["hubspot-api-client", "urllib3 (>=1.26.17)"]
+hubspot = ["hubspot-api-client", "urllib3"]
 huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"]
-image = ["onnx", "pdf2image", "pdfminer.six", "pikepdf", "pypdf", "unstructured-inference (==0.7.18)", "unstructured.pytesseract (>=0.3.12)"]
+image = ["google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypdf", "unstructured-inference (==0.7.31)", "unstructured.pytesseract (>=0.3.12)"]
 jira = ["atlassian-python-api"]
-local-inference = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.0)", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.18)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
+local-inference = ["google-cloud-vision", "markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypandoc", "pypdf", "python-docx", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.31)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
 md = ["markdown"]
 mongodb = ["pymongo"]
 msg = ["msg-parser"]
 notion = ["htmlBuilder", "notion-client"]
-odt = ["pypandoc", "python-docx (>=1.1.0)"]
-onedrive = ["Office365-REST-Python-Client (<2.4.3)", "bs4", "msal"]
-openai = ["langchain", "openai", "tiktoken"]
+odt = ["pypandoc", "python-docx"]
+onedrive = ["Office365-REST-Python-Client", "bs4", "msal"]
+openai = ["langchain-community", "openai", "tiktoken"]
+opensearch = ["opensearch-py"]
 org = ["pypandoc"]
-outlook = ["Office365-REST-Python-Client (<2.4.3)", "msal"]
+outlook = ["Office365-REST-Python-Client", "msal"]
 paddleocr = ["unstructured.paddleocr (==2.6.1.3)"]
-pdf = ["onnx", "pdf2image", "pdfminer.six", "pikepdf", "pypdf", "unstructured-inference (==0.7.18)", "unstructured.pytesseract (>=0.3.12)"]
-pinecone = ["pinecone-client"]
+pdf = ["google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypdf", "unstructured-inference (==0.7.31)", "unstructured.pytesseract (>=0.3.12)"]
+pinecone = ["pinecone-client (==2.2.4)"]
+postgres = ["psycopg2-binary"]
 ppt = ["python-pptx (<=0.6.23)"]
 pptx = ["python-pptx (<=0.6.23)"]
 qdrant = ["qdrant-client"]
 reddit = ["praw"]
 rst = ["pypandoc"]
 rtf = ["pypandoc"]
-s3 = ["fsspec (==2023.9.1)", "s3fs"]
+s3 = ["fsspec", "s3fs"]
 salesforce = ["simple-salesforce"]
 sftp = ["fsspec", "paramiko"]
-sharepoint = ["Office365-REST-Python-Client (<2.4.3)", "msal"]
+sharepoint = ["Office365-REST-Python-Client", "msal"]
 slack = ["slack-sdk"]
 tsv = ["pandas"]
 weaviate = ["weaviate-client"]
@@ -4774,7 +4993,7 @@ xlsx = ["networkx", "openpyxl", "pandas", "xlrd"]
 name = "unstructured-client"
 version = "0.22.0"
 description = "Python Client SDK for Unstructured API"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "unstructured-client-0.22.0.tar.gz", hash = "sha256:d76351c456fcf4067f59135c09a35008a120103621a1ac94cf9448db28ef2e1e"},
@@ -4839,7 +5058,7 @@ zstd = ["zstandard (>=0.18.0)"]
 name = "uvicorn"
 version = "0.29.0"
 description = "The lightning-fast ASGI server."
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "uvicorn-0.29.0-py3-none-any.whl", hash = "sha256:2c2aac7ff4f4365c206fd773a39bf4ebd1047c238f8b8268ad996829323473de"},
@@ -4865,7 +5084,7 @@ standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)",
 name = "uvloop"
 version = "0.19.0"
 description = "Fast implementation of asyncio event loop on top of libuv"
-optional = true
+optional = false
 python-versions = ">=3.8.0"
 files = [
     {file = "uvloop-0.19.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:de4313d7f575474c8f5a12e163f6d89c0a878bc49219641d49e6f1444369a90e"},
@@ -4907,13 +5126,13 @@ test = ["Cython (>=0.29.36,<0.30.0)", "aiohttp (==3.9.0b0)", "aiohttp (>=3.8.1)"
 
 [[package]]
 name = "virtualenv"
-version = "20.25.1"
+version = "20.26.2"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
-    {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
+    {file = "virtualenv-20.26.2-py3-none-any.whl", hash = "sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b"},
+    {file = "virtualenv-20.26.2.tar.gz", hash = "sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c"},
 ]
 
 [package.dependencies]
@@ -4922,14 +5141,14 @@ filelock = ">=3.12.2,<4"
 platformdirs = ">=3.9.1,<5"
 
 [package.extras]
-docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
 name = "watchfiles"
 version = "0.21.0"
 description = "Simple, modern and high performance file watching and code reload in python."
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "watchfiles-0.21.0-cp310-cp310-macosx_10_7_x86_64.whl", hash = "sha256:27b4035013f1ea49c6c0b42d983133b136637a527e48c132d368eb19bf1ac6aa"},
@@ -5014,17 +5233,17 @@ anyio = ">=3.0.0"
 
 [[package]]
 name = "websocket-client"
-version = "1.7.0"
+version = "1.8.0"
 description = "WebSocket client for Python with low level API options"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "websocket-client-1.7.0.tar.gz", hash = "sha256:10e511ea3a8c744631d3bd77e61eb17ed09304c413ad42cf6ddfa4c7787e8fe6"},
-    {file = "websocket_client-1.7.0-py3-none-any.whl", hash = "sha256:f4c3d22fec12a2461427a29957ff07d35098ee2d976d3ba244e688b8b4057588"},
+    {file = "websocket_client-1.8.0-py3-none-any.whl", hash = "sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526"},
+    {file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"},
 ]
 
 [package.extras]
-docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
+docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
@@ -5032,7 +5251,7 @@ test = ["websockets"]
 name = "websockets"
 version = "12.0"
 description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "websockets-12.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:d554236b2a2006e0ce16315c16eaa0d628dab009c33b63ea03f41c6107958374"},
@@ -5109,25 +5328,11 @@ files = [
     {file = "websockets-12.0.tar.gz", hash = "sha256:81df9cbcbb6c260de1e007e58c011bfebe2dafc8435107b0537f393dd38c8b1b"},
 ]
 
-[[package]]
-name = "win32-setctime"
-version = "1.1.0"
-description = "A small Python utility to set file creation time on Windows"
-optional = true
-python-versions = ">=3.5"
-files = [
-    {file = "win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad"},
-    {file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"},
-]
-
-[package.extras]
-dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
-
 [[package]]
 name = "wrapt"
 version = "1.16.0"
 description = "Module for decorators, wrappers and monkey patching."
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
     {file = "wrapt-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ffa565331890b90056c01db69c0fe634a776f8019c143a5ae265f9c6bc4bd6d4"},
@@ -5307,29 +5512,27 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.18.1"
+version = "3.18.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"},
-    {file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"},
+    {file = "zipp-3.18.2-py3-none-any.whl", hash = "sha256:dce197b859eb796242b0622af1b8beb0a722d52aa2f57133ead08edd5bf5374e"},
+    {file = "zipp-3.18.2.tar.gz", hash = "sha256:6278d9ddbcfb1f1089a88fde84481528b07b0e10474e09dcfe53dad4069fa059"},
 ]
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
 [extras]
 anthropic = ["anthropic"]
 bedrock = ["boto3"]
 cohere = ["cohere"]
 gemini = ["google-generativeai"]
-generators = ["chromadb", "langchain-community", "pinecone-client", "tiktoken", "unstructured"]
 langchain = ["langchain-community"]
-semantic = ["sentence-transformers", "torch", "transformers"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.9,<4.0"
-content-hash = "4ce10ecb0438f9b6b41ea44db73fba3c9ce38de33ab23d5d65f096a9de1aa4da"
+python-versions = ">=3.9,<3.12"
+content-hash = "893b2c7e785564deb85fb26ca6b40ce39dd6ee04ab6914ee6d4d57d3fa3f0abc"
diff --git a/pyproject.toml b/pyproject.toml
index cf088e3..e784d44 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "continuous-eval"
-version = "0.3.7"
+version = "0.3.8"
 description = "Open-Source Evaluation for GenAI Application Pipelines."
 authors = ["Yi Zhang <yi@relari.ai>", "Pasquale Antonante <pasquale@relari.ai>"]
 readme = "README.md"
@@ -8,50 +8,58 @@ license = "Apache-2.0"
 packages = [{include = "continuous_eval"}]
 
 [tool.poetry.dependencies]
-python = ">=3.9,<4.0"
+python = ">=3.9,<3.12"
 python-dotenv = "^1.0.0"
 nltk = "^3.8.1"
 rouge = "^1.0.1"
 openai = "^1.3.7"
-transformers = {version = "^4.35.2", optional = true}
-sentence-transformers = {version = "^2.2.2", optional = true}
-torch = {version = "^2.1.1", optional = true}
-anthropic = {version = "^0.7.7", optional = true}
-google-generativeai = {version = "^0.3.1", optional = true}
 mapie = "^0.7.0"
 imbalanced-learn = "^0.11.0"
 pandas = "^2.1.4"
 protobuf = "^4.23.4"
 tqdm = "^4.66.1"
 requests = "^2.31.0"
-pinecone-client = {version = "^2.2.4", optional = true}
-chromadb = {version = "^0.4.21", optional = true}
-tiktoken = {version = "^0.5.2", optional = true}
-unstructured = {version = "^0.11.6", optional = true}
+pyyaml = "^6.0.1"
 appdirs = "^1.4.4"
 munkres = "^1.1.4"
 thefuzz = "^0.22.1"
 sentencepiece = "^0.2.0"
-cohere = {version = "^4.54", optional = true}
 tenacity = "^8.2.3"
-boto3 = {version = "^1.34.70", optional = true}
+
 langchain-community = {version = "^0.0.29", optional = true}
-pyyaml = "^6.0.1"
+cohere = {version = "^4.54", optional = true}
+boto3 = {version = "^1.34.70", optional = true}
+google-generativeai = {version = "^0.3.1", optional = true}
+anthropic = {version = "^0.7.7", optional = true}
+
+[tool.poetry.group.semantic]
+optional = true
+[tool.poetry.group.semantic.dependencies]
+torch = "^2.1.1"
+transformers = "^4.35.2"
+sentence-transformers = "^2.2.2"
+
+[tool.poetry.group.generators]
+optional = true
+[tool.poetry.group.generators.dependencies]
+unstructured ="^0.13.7"
+tiktoken = "^0.7.0"
+chromadb = "^0.5.0"
+langchain-openai = "^0.1.7"
+
+[tool.poetry.group.dev.dependencies]
+black = "^23.11.0"
+isort = "^5.12.0"
+pytest = "^7.4.3"
+pre-commit = "^3.6.0"
 
 [tool.poetry.extras]
 langchain = ["langchain-community"]
-semantic = ["transformers", "sentence-transformers", "torch"]
 anthropic = ["anthropic"]
 bedrock = ["boto3"]
 gemini = ["google-generativeai"]
 cohere = ["cohere"]
-generators = ["unstructured", "tiktoken", "pinecone-client", "chromadb", "langchain-community"]
 
-[tool.poetry.group.dev.dependencies]
-black = "^23.11.0"
-isort = "^5.12.0"
-pytest = "^7.4.3"
-pre-commit = "^3.6.0"
 
 [tool.isort]
 profile = "black"