From 62a28ede960230610f76bb29f4a7770ff19941f0 Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Wed, 5 Feb 2025 13:58:04 +0000
Subject: [PATCH 01/11] Initial commit

---
 src/eva/core/interface/interface.py           | 26 ++++++-
 src/eva/core/trainers/functional.py           | 28 +++++++
 src/eva/core/trainers/trainer.py              | 24 ++++++
 src/eva/language/models/module.py             | 75 +++++++++++++++++++
 .../language/models/wrappers/huggingface.py   | 56 ++++++++++++++
 5 files changed, 208 insertions(+), 1 deletion(-)
 create mode 100644 src/eva/language/models/module.py
 create mode 100644 src/eva/language/models/wrappers/huggingface.py

diff --git a/src/eva/core/interface/interface.py b/src/eva/core/interface/interface.py
index af0e9aa7..0a94e384 100644
--- a/src/eva/core/interface/interface.py
+++ b/src/eva/core/interface/interface.py
@@ -51,7 +51,7 @@ def predict(
             model: The model module to use but not modify.
             data: The data module.
         """
-        eva_trainer.infer_model(
+        trainer.infer_model(
             base_trainer=trainer,
             base_model=model,
             datamodule=data,
@@ -77,3 +77,27 @@ def predict_fit(
         """
         self.predict(trainer=trainer, model=model, data=data)
         self.fit(trainer=trainer, model=model, data=data)
+
+    def validate(
+        self,
+        trainer: eva_trainer.Trainer,
+        model: modules.ModelModule,
+        data: datamodules.DataModule,
+    ) -> None:
+        """Perform model validation out-of-place without running fit.
+
+        This method is useful when the model is already trained or does not
+        require further training (e.g., large language models) and you only
+        want to measure performance.
+
+        Args:
+            trainer: The base trainer to use but not modify.
+            model: The model module to use but not modify.
+            data: The data module containing validation data.
+        """
+        trainer.run_validation_only(
+            base_trainer=trainer,
+            base_model=model,
+            datamodule=data,
+            verbose=True,
+        )
\ No newline at end of file
diff --git a/src/eva/core/trainers/functional.py b/src/eva/core/trainers/functional.py
index 4d8bd534..0d53099d 100644
--- a/src/eva/core/trainers/functional.py
+++ b/src/eva/core/trainers/functional.py
@@ -131,3 +131,31 @@ def infer_model(
         datamodule=datamodule,
         return_predictions=return_predictions,
     )
+
+def run_validation_only(
+    base_trainer: eva_trainer.Trainer,
+    base_model: modules.ModelModule,
+    datamodule: datamodules.DataModule,
+    verbose: bool = True,
+) -> _EVALUATE_OUTPUT:
+    """Validates a model out-of-place without fitting first.
+
+    Note:
+        This function clones the base model and trainer, so that the inputs
+        are not modified.
+
+    Args:
+        base_trainer: The base trainer to clone.
+        base_model: The model module to clone.
+        datamodule: The data module to validate on.
+        verbose: Whether to print the validation metrics after validation.
+
+    Returns:
+        The validation metrics produced by `trainer.validate`.
+    """
+    trainer, model = _utils.clone(base_trainer, base_model)
+    return trainer.validate(
+        model=model,
+        datamodule=datamodule,
+        verbose=verbose,
+    )
\ No newline at end of file
diff --git a/src/eva/core/trainers/trainer.py b/src/eva/core/trainers/trainer.py
index beace9db..6ed8b8b4 100644
--- a/src/eva/core/trainers/trainer.py
+++ b/src/eva/core/trainers/trainer.py
@@ -113,3 +113,27 @@ def run_evaluation_session(
             n_runs=self.n_runs,
             verbose=self.n_runs > 1,
         )
+
+    def validate_only(
+        self,
+        model: modules.ModelModule,
+        datamodule: datamodules.DataModule,
+        verbose: bool = True,
+    ) -> None:
+        """
+        Runs validation on the model out-of-place without fitting or test.
+
+        Args:
+            model: The model to validate (cloned, not modified in-place).
+            datamodule: The datamodule for validation.
+            verbose: Whether to print validation metrics to stdout.
+
+        Returns:
+            Validation metrics as returned by trainer.validate.
+        """
+        functional.run_validation_only(
+            base_trainer=self,
+            base_model=model,
+            datamodule=datamodule,
+            verbose=verbose,
+        )
\ No newline at end of file
diff --git a/src/eva/language/models/module.py b/src/eva/language/models/module.py
new file mode 100644
index 00000000..4b508789
--- /dev/null
+++ b/src/eva/language/models/module.py
@@ -0,0 +1,75 @@
+"""LLM Text Module for Inference."""
+
+from typing import Any, Dict, Callable
+import torch
+from torch import nn
+from typing_extensions import override
+from eva.core.metrics import structs as metrics_lib
+from eva.core.models.modules import module
+from eva.core.models.modules.typings import INPUT_BATCH
+from lightning.pytorch.utilities.types import STEP_OUTPUT
+from eva.core.models.modules.utils import batch_postprocess
+from eva.core.models.wrappers.huggingface import HuggingFaceModel
+
+
+class TextModule(module.ModelModule):
+    """Text-based LLM module for inference.
+
+    Uses a Hugging Face wrapper for text generation.
+    Supports evaluation using configurable metrics and post-processing.
+    """
+
+    def __init__(
+        self,
+        model: nn.Module,
+        prompt: str,
+        metrics: metrics_lib.MetricsSchema | None = None,
+        postprocess: batch_postprocess.BatchPostProcess | None = None,
+    ) -> None:
+        """Initializes the text inference module.
+
+        Args:
+            model: A HuggingFace wrapper or another PyTorch-compatible model for text generation.
+            metrics: Metrics schema for evaluation.
+            postprocess: A helper function to post-process model outputs before evaluation.
+        """
+        super().__init__(metrics=metrics, postprocess=postprocess)
+
+        self.model = model
+        self.prompt = prompt
+
+    @override
+    def forward(self, prompts: str, *args: Any, **kwargs: Any) -> list[str]:
+        """Generates text responses for a batch of prompts.
+
+        Args:
+            prompts: List of input texts to generate responses.
+
+        Returns:
+            List of generated responses.
+        """
+        return self.model.generate(prompts)
+
+    @override
+    def validation_step(self, batch: INPUT_BATCH, *args: Any, **kwargs: Any) -> STEP_OUTPUT:
+        """Validation step that runs batch inference and evaluates metrics."""
+        return self._batch_step(batch)
+
+    def _batch_step(self, batch: INPUT_BATCH) -> STEP_OUTPUT:
+        """Runs inference on a batch and evaluates model predictions.
+
+        Args:
+            batch: A batch of input prompts and ground truth labels.
+
+        Returns:
+            Dictionary with predictions, ground truth, and evaluation metrics.
+        """
+        data, targets, metadata = INPUT_BATCH(*batch)
+        message = self.prompt + data + '\nAnswer: '
+        predictions = self.forward(message)
+
+        return {
+            "predictions": predictions,
+            "targets": targets,
+            "metadata": metadata,
+        }
diff --git a/src/eva/language/models/wrappers/huggingface.py b/src/eva/language/models/wrappers/huggingface.py
new file mode 100644
index 00000000..39db9ab7
--- /dev/null
+++ b/src/eva/language/models/wrappers/huggingface.py
@@ -0,0 +1,56 @@
+"""LLM wrapper for HuggingFace `transformers` models."""
+
+from typing import Any, Callable, Dict, Optional
+import transformers
+from typing_extensions import override
+from eva.core.models.wrappers import base
+
+
+class HuggingFaceTextModel(base.BaseModel):
+    """Wrapper class for loading HuggingFace `transformers` models using pipelines."""
+
+    def __init__(
+        self,
+        model_name_or_path: str,
+        task: str = "text-generation",
+        model_kwargs: Optional[Dict[str, Any]] = None,
+    ) -> None:
+        """Initializes the model.
+
+        Args:
+            model_name_or_path: The model name or path to load the model from.
+                This can be a local path or a model name from the `HuggingFace`
+                model hub.
+            task: The pipeline task (e.g., "text-generation", "text-classification").
+                Defaults to "text-generation".
+            model_kwargs: Additional arguments for configuring the pipeline.
+        """
+        super().__init__()
+
+        self._model_name_or_path = model_name_or_path
+        self._task = task
+        self._model_kwargs = model_kwargs or {}
+
+        self.load_model()
+
+    @override
+    def load_model(self) -> None:
+        """Loads the model as a Hugging Face pipeline."""
+        self._pipeline = transformers.pipeline(
+            task=self._task,
+            model=self._model_name_or_path,
+            **self._model_kwargs
+        )
+
+    def generate(self, prompt: str, **generate_kwargs) -> str:
+        """Generates text using the pipeline.
+
+        Args:
+            prompt: The input prompt for the model.
+            generate_kwargs: Additional generation parameters (e.g., max_length).
+
+        Returns:
+            The generated text as a string.
+        """
+        output = self._pipeline(prompt, **generate_kwargs)
+        return output[0]["generated_text"][len(prompt):] if isinstance(output, list) else output

From 67e660ce180fc445632a7ad80c3bb483476312ef Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Wed, 5 Feb 2025 19:43:46 +0000
Subject: [PATCH 02/11] Working validation

---
 configs/language/pubmedqa.yaml                | 48 +++++++++++++++++++
 src/eva/core/interface/interface.py           |  5 +-
 .../data/datasets/classification/pubmedqa.py  | 17 ++++---
 src/eva/language/models/module.py             | 13 +++--
 .../language/models/wrappers/huggingface.py   |  6 ++-
 5 files changed, 73 insertions(+), 16 deletions(-)
 create mode 100644 configs/language/pubmedqa.yaml

diff --git a/configs/language/pubmedqa.yaml b/configs/language/pubmedqa.yaml
new file mode 100644
index 00000000..2d0b7959
--- /dev/null
+++ b/configs/language/pubmedqa.yaml
@@ -0,0 +1,48 @@
+# Configuration for validating a model on PubMedQA
+---
+trainer:
+  class_path: eva.Trainer
+  init_args:
+    n_runs: &N_RUNS ${oc.env:N_RUNS, 5}
+    default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:MODEL_NAME, meta-llama/Llama-3.2-1B}/online/pubmedqa}
+    max_steps: &MAX_STEPS ${oc.env:MAX_STEPS, 12500}
+    checkpoint_type: ${oc.env:CHECKPOINT_TYPE, best}
+    callbacks:
+      - class_path: eva.callbacks.ConfigurationLogger
+    logger:
+      - class_path: lightning.pytorch.loggers.TensorBoardLogger
+        init_args:
+          save_dir: *OUTPUT_ROOT
+          name: ""
+model:
+  class_path: eva.language.models.module.TextModule
+  init_args:
+    prompt: "Respond to the question with a single digit only: 0 for no, 1 for yes, or 2 for maybe. Do not include any words, explanations, or additional characters—only the digit."
+    model:
+      class_path: eva.language.models.wrappers.huggingface.HuggingFaceTextModel
+      init_args:
+        model_name_or_path: 'meta-llama/Llama-3.2-1B'
+        model_kwargs:
+          max_new_tokens: 1
+    # metrics:
+    #   common:
+    #     - class_path: eva.metrics.MulticlassClassificationMetrics
+    #       init_args:
+    #         num_classes: 3
+    postprocess: null  # Add if you need postprocessing
+
+data:
+  class_path: eva.DataModule
+  init_args:
+    datasets:
+      val:
+        class_path: eva.language.datasets.PubMedQA
+        init_args: &DATASET_ARGS
+          root: ${oc.env:DATA_ROOT, ./data/pubmedqa}
+          split: null
+          download: true
+    dataloaders:
+      val:
+        batch_size: &BATCH_SIZE ${oc.env:BATCH_SIZE, 1}
+        num_workers: &N_DATA_WORKERS ${oc.env:N_DATA_WORKERS, 1}
+        shuffle: false  # Ensure validation data is not shuffled
diff --git a/src/eva/core/interface/interface.py b/src/eva/core/interface/interface.py
index 0a94e384..cf595703 100644
--- a/src/eva/core/interface/interface.py
+++ b/src/eva/core/interface/interface.py
@@ -95,9 +95,8 @@ def validate(
             model: The model module to use but not modify.
             data: The data module containing validation data.
         """
-        trainer.run_validation_only(
-            base_trainer=trainer,
-            base_model=model,
+        trainer.validate_only(
+            model=model,
             datamodule=data,
             verbose=True,
         )
\ No newline at end of file
diff --git a/src/eva/language/data/datasets/classification/pubmedqa.py b/src/eva/language/data/datasets/classification/pubmedqa.py
index 8f503bf5..d4b76fee 100644
--- a/src/eva/language/data/datasets/classification/pubmedqa.py
+++ b/src/eva/language/data/datasets/classification/pubmedqa.py
@@ -118,15 +118,18 @@ def load_target(self, index: int) -> torch.Tensor:
         )
 
     @override
-    def load_metadata(self, index: int) -> Dict[str, Any]:
+    def load_metadata(self, index: int) -> Dict[str, str]:
         sample = self.dataset[index]
         return {
-            "year": sample["YEAR"],
-            "labels": sample["LABELS"],
-            "meshes": sample["MESHES"],
-            "long_answer": sample["LONG_ANSWER"],
-            "reasoning_required": sample["reasoning_required_pred"],
-            "reasoning_free": sample["reasoning_free_pred"],
+            key: str(value) if value is not None else ""
+            for key, value in {
+                "year": sample.get("YEAR"),
+                "labels": sample.get("LABELS"),
+                "meshes": sample.get("MESHES"),
+                "long_answer": sample.get("LONG_ANSWER"),
+                "reasoning_required": sample.get("reasoning_required_pred"),
+                "reasoning_free": sample.get("reasoning_free_pred"),
+            }.items()
         }
 
     @override
diff --git a/src/eva/language/models/module.py b/src/eva/language/models/module.py
index 4b508789..c6f690d6 100644
--- a/src/eva/language/models/module.py
+++ b/src/eva/language/models/module.py
@@ -55,21 +55,26 @@ def validation_step(self, batch: INPUT_BATCH, *args: Any, **kwargs: Any) -> STEP
         """Validation step that runs batch inference and evaluates metrics."""
         return self._batch_step(batch)
 
-    def _batch_step(self, batch: INPUT_BATCH) -> STEP_OUTPUT:
+    @override
+    def _batch_step(self, batch: Dict[str, Any]) -> STEP_OUTPUT:
         """Runs inference on a batch and evaluates model predictions.
 
         Args:
-            batch: A batch of input prompts and ground truth labels.
+            batch: A batch containing 'QUESTION', 'CONTEXTS', 'final_decision', etc.
 
         Returns:
             Dictionary with predictions, ground truth, and evaluation metrics.
         """
         data, targets, metadata = INPUT_BATCH(*batch)
-        message = self.prompt + data + '\nAnswer: '
+        print('!data:', data)
+        print('!targets:', targets)
+        print('!metadata:', metadata)
+        message = self.prompt + str(data) + '\nAnswer: '
         predictions = self.forward(message)
 
         return {
             "predictions": predictions,
             "targets": targets,
-            "metadata": metadata,
+            "metadata": batch  # Pass the entire batch as metadata
         }
+
diff --git a/src/eva/language/models/wrappers/huggingface.py b/src/eva/language/models/wrappers/huggingface.py
index 39db9ab7..5c38a04e 100644
--- a/src/eva/language/models/wrappers/huggingface.py
+++ b/src/eva/language/models/wrappers/huggingface.py
@@ -52,5 +52,7 @@ def generate(self, prompt: str, **generate_kwargs) -> str:
         Returns:
             The generated text as a string.
         """
-        output = self._pipeline(prompt, **generate_kwargs)
-        return output[0]["generated_text"][len(prompt):] if isinstance(output, list) else output
+        output = self._pipeline(prompt, return_full_text=False, **generate_kwargs)
+        print('!output:', output)
+        print('!prompt:', prompt)
+        return output[0]["generated_text"] if isinstance(output, list) else output

From 3e6f799aa29f3544195d1c2f35fe19f873b65ffd Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Thu, 6 Feb 2025 11:12:19 +0000
Subject: [PATCH 03/11] Fix formatting

---
 configs/language/pubmedqa.yaml                |  9 ++--
 src/eva/core/interface/interface.py           |  2 +-
 src/eva/core/trainers/functional.py           |  3 +-
 src/eva/core/trainers/trainer.py              |  5 +--
 .../data/datasets/classification/pubmedqa.py  |  2 +-
 src/eva/language/models/module.py             | 45 ++++++++++---------
 .../language/models/wrappers/huggingface.py   | 10 ++---
 7 files changed, 38 insertions(+), 38 deletions(-)

diff --git a/configs/language/pubmedqa.yaml b/configs/language/pubmedqa.yaml
index 2d0b7959..e496e480 100644
--- a/configs/language/pubmedqa.yaml
+++ b/configs/language/pubmedqa.yaml
@@ -1,4 +1,3 @@
-# Configuration for validating a model on PubMedQA
 ---
 trainer:
   class_path: eva.Trainer
@@ -21,16 +20,16 @@ model:
     model:
       class_path: eva.language.models.wrappers.huggingface.HuggingFaceTextModel
       init_args:
-        model_name_or_path: 'meta-llama/Llama-3.2-1B'
+        model_name_or_path: "meta-llama/Llama-3.2-1B"
         model_kwargs:
           max_new_tokens: 1
+    # TODO: implement metrics for language models
     # metrics:
     #   common:
     #     - class_path: eva.metrics.MulticlassClassificationMetrics
     #       init_args:
     #         num_classes: 3
-    postprocess: null  # Add if you need postprocessing
-
+    postprocess: null
 data:
   class_path: eva.DataModule
   init_args:
@@ -45,4 +44,4 @@ data:
       val:
         batch_size: &BATCH_SIZE ${oc.env:BATCH_SIZE, 1}
         num_workers: &N_DATA_WORKERS ${oc.env:N_DATA_WORKERS, 1}
-        shuffle: false  # Ensure validation data is not shuffled
+        shuffle: false
\ No newline at end of file
diff --git a/src/eva/core/interface/interface.py b/src/eva/core/interface/interface.py
index cf595703..ce1749e7 100644
--- a/src/eva/core/interface/interface.py
+++ b/src/eva/core/interface/interface.py
@@ -99,4 +99,4 @@ def validate(
             model=model,
             datamodule=data,
             verbose=True,
-        )
\ No newline at end of file
+        )
diff --git a/src/eva/core/trainers/functional.py b/src/eva/core/trainers/functional.py
index 0d53099d..33b8f4d9 100644
--- a/src/eva/core/trainers/functional.py
+++ b/src/eva/core/trainers/functional.py
@@ -132,6 +132,7 @@ def infer_model(
         return_predictions=return_predictions,
     )
 
+
 def run_validation_only(
     base_trainer: eva_trainer.Trainer,
     base_model: modules.ModelModule,
@@ -158,4 +159,4 @@ def run_validation_only(
         model=model,
         datamodule=datamodule,
         verbose=verbose,
-    )
\ No newline at end of file
+    )
diff --git a/src/eva/core/trainers/trainer.py b/src/eva/core/trainers/trainer.py
index 6ed8b8b4..c4428ab0 100644
--- a/src/eva/core/trainers/trainer.py
+++ b/src/eva/core/trainers/trainer.py
@@ -120,8 +120,7 @@ def validate_only(
         datamodule: datamodules.DataModule,
         verbose: bool = True,
     ) -> None:
-        """
-        Runs validation on the model out-of-place without fitting or test.
+        """Runs validation on the model out-of-place without fitting or test.
 
         Args:
             model: The model to validate (cloned, not modified in-place).
@@ -136,4 +135,4 @@ def validate_only(
             base_model=model,
             datamodule=datamodule,
             verbose=verbose,
-        )
\ No newline at end of file
+        )
diff --git a/src/eva/language/data/datasets/classification/pubmedqa.py b/src/eva/language/data/datasets/classification/pubmedqa.py
index d4b76fee..76b682f6 100644
--- a/src/eva/language/data/datasets/classification/pubmedqa.py
+++ b/src/eva/language/data/datasets/classification/pubmedqa.py
@@ -1,7 +1,7 @@
 """PubMedQA dataset class."""
 
 import os
-from typing import Any, Dict, List, Literal
+from typing import Dict, List, Literal
 
 import torch
 from datasets import Dataset, load_dataset
diff --git a/src/eva/language/models/module.py b/src/eva/language/models/module.py
index c6f690d6..f17f4084 100644
--- a/src/eva/language/models/module.py
+++ b/src/eva/language/models/module.py
@@ -1,22 +1,22 @@
 """LLM Text Module for Inference."""
 
-from typing import Any, Dict, Callable
-import torch
+from typing import Any
+
+from lightning.pytorch.utilities.types import STEP_OUTPUT
 from torch import nn
 from typing_extensions import override
+
 from eva.core.metrics import structs as metrics_lib
 from eva.core.models.modules import module
 from eva.core.models.modules.typings import INPUT_BATCH
-from lightning.pytorch.utilities.types import STEP_OUTPUT
 from eva.core.models.modules.utils import batch_postprocess
-from eva.core.models.wrappers.huggingface import HuggingFaceModel
 
 
 class TextModule(module.ModelModule):
     """Text-based LLM module for inference.
 
-    Uses a Hugging Face wrapper for text generation.
-    Supports evaluation using configurable metrics and post-processing.
+    Uses LLM wrappers for text generation.
+    Supports evaluation using configurable metrics and post-processing. # TODO: Add support
     """
 
     def __init__(
@@ -29,7 +29,8 @@ def __init__(
         """Initializes the text inference module.
 
         Args:
-            model: A HuggingFace wrapper or another PyTorch-compatible model for text generation.
+            model: An LLM wrapper (PyTorch-compatible) for text generation.
+            prompt: The prompt to use for generating text.
             metrics: Metrics schema for evaluation.
             postprocess: A helper function to post-process model outputs before evaluation.
         """
@@ -44,6 +45,8 @@ def forward(self, prompts: str, *args: Any, **kwargs: Any) -> list[str]:
 
         Args:
             prompts: List of input texts to generate responses.
+            args: Additional arguments.
+            kwargs: Additional keyword arguments.
 
         Returns:
             List of generated responses.
@@ -52,11 +55,19 @@ def forward(self, prompts: str, *args: Any, **kwargs: Any) -> list[str]:
 
     @override
     def validation_step(self, batch: INPUT_BATCH, *args: Any, **kwargs: Any) -> STEP_OUTPUT:
-        """Validation step that runs batch inference and evaluates metrics."""
+        """Validation step that runs batch inference and evaluates metrics.
+
+        Args:
+            batch: An input batch.
+            args: Additional arguments.
+            kwargs: Additional keyword arguments.
+
+        Returns:
+            Dictionary with predictions, ground truth, and evaluation metrics.
+        """
         return self._batch_step(batch)
 
-    @override
-    def _batch_step(self, batch: Dict[str, Any]) -> STEP_OUTPUT:
+    def _batch_step(self, batch: INPUT_BATCH) -> STEP_OUTPUT:
         """Runs inference on a batch and evaluates model predictions.
 
         Args:
@@ -66,15 +77,7 @@ def _batch_step(self, batch: Dict[str, Any]) -> STEP_OUTPUT:
             Dictionary with predictions, ground truth, and evaluation metrics.
         """
         data, targets, metadata = INPUT_BATCH(*batch)
-        print('!data:', data)
-        print('!targets:', targets)
-        print('!metadata:', metadata)
-        message = self.prompt + str(data) + '\nAnswer: '
+        message = self.prompt + str(data) + "\nAnswer: "
         predictions = self.forward(message)
-
-        return {
-            "predictions": predictions,
-            "targets": targets,
-            "metadata": batch  # Pass the entire batch as metadata
-        }
-
+        # TODO: Add support for evaluation metrics
+        return {"predictions": predictions, "targets": targets, "metadata": batch}
diff --git a/src/eva/language/models/wrappers/huggingface.py b/src/eva/language/models/wrappers/huggingface.py
index 5c38a04e..c0623f6a 100644
--- a/src/eva/language/models/wrappers/huggingface.py
+++ b/src/eva/language/models/wrappers/huggingface.py
@@ -1,8 +1,10 @@
 """LLM wrapper for HuggingFace `transformers` models."""
 
-from typing import Any, Callable, Dict, Optional
+from typing import Any, Dict, Optional
+
 import transformers
 from typing_extensions import override
+
 from eva.core.models.wrappers import base
 
 
@@ -37,9 +39,7 @@ def __init__(
     def load_model(self) -> None:
         """Loads the model as a Hugging Face pipeline."""
         self._pipeline = transformers.pipeline(
-            task=self._task,
-            model=self._model_name_or_path,
-            **self._model_kwargs
+            task=self._task, model=self._model_name_or_path, **self._model_kwargs
         )
 
     def generate(self, prompt: str, **generate_kwargs) -> str:
@@ -53,6 +53,4 @@ def generate(self, prompt: str, **generate_kwargs) -> str:
             The generated text as a string.
         """
         output = self._pipeline(prompt, return_full_text=False, **generate_kwargs)
-        print('!output:', output)
-        print('!prompt:', prompt)
         return output[0]["generated_text"] if isinstance(output, list) else output

From efa616a7ac924f5891bfa3ad8791ed0ac43057e1 Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Thu, 6 Feb 2025 11:37:50 +0000
Subject: [PATCH 04/11] Add inits

---
 configs/language/pubmedqa.yaml                   | 4 ++--
 src/eva/language/models/__init__.py              | 7 +++++++
 src/eva/language/models/networks/__init__.py     | 5 +++++
 src/eva/language/models/{ => networks}/module.py | 0
 src/eva/language/models/wrappers/__init__.py     | 5 +++++
 5 files changed, 19 insertions(+), 2 deletions(-)
 create mode 100644 src/eva/language/models/__init__.py
 create mode 100644 src/eva/language/models/networks/__init__.py
 rename src/eva/language/models/{ => networks}/module.py (100%)
 create mode 100644 src/eva/language/models/wrappers/__init__.py

diff --git a/configs/language/pubmedqa.yaml b/configs/language/pubmedqa.yaml
index e496e480..ae7044b1 100644
--- a/configs/language/pubmedqa.yaml
+++ b/configs/language/pubmedqa.yaml
@@ -14,11 +14,11 @@ trainer:
           save_dir: *OUTPUT_ROOT
           name: ""
 model:
-  class_path: eva.language.models.module.TextModule
+  class_path: eva.language.models.TextModule
   init_args:
     prompt: "Respond to the question with a single digit only: 0 for no, 1 for yes, or 2 for maybe. Do not include any words, explanations, or additional characters—only the digit."
     model:
-      class_path: eva.language.models.wrappers.huggingface.HuggingFaceTextModel
+      class_path: eva.language.models.HuggingFaceTextModel
       init_args:
         model_name_or_path: "meta-llama/Llama-3.2-1B"
         model_kwargs:
diff --git a/src/eva/language/models/__init__.py b/src/eva/language/models/__init__.py
new file mode 100644
index 00000000..d4bd1519
--- /dev/null
+++ b/src/eva/language/models/__init__.py
@@ -0,0 +1,7 @@
+"""Language Models API."""
+
+from eva.language.models import networks, wrappers
+from eva.language.models.networks import TextModule
+from eva.language.models.wrappers import HuggingFaceTextModel
+
+__all__ = ["networks", "wrappers", "HuggingFaceTextModel", "TextModule"]
diff --git a/src/eva/language/models/networks/__init__.py b/src/eva/language/models/networks/__init__.py
new file mode 100644
index 00000000..6bf6efae
--- /dev/null
+++ b/src/eva/language/models/networks/__init__.py
@@ -0,0 +1,5 @@
+"""Language Networks API."""
+
+from eva.language.models.networks.module import TextModule
+
+__all__ = ["TextModule"]
diff --git a/src/eva/language/models/module.py b/src/eva/language/models/networks/module.py
similarity index 100%
rename from src/eva/language/models/module.py
rename to src/eva/language/models/networks/module.py
diff --git a/src/eva/language/models/wrappers/__init__.py b/src/eva/language/models/wrappers/__init__.py
new file mode 100644
index 00000000..950501ad
--- /dev/null
+++ b/src/eva/language/models/wrappers/__init__.py
@@ -0,0 +1,5 @@
+"""Language Model Wrappers API."""
+
+from eva.language.models.wrappers.huggingface import HuggingFaceTextModel
+
+__all__ = ["HuggingFaceTextModel"]

From 0ea71b730d5009502785bb403775c5085958945a Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Thu, 6 Feb 2025 11:44:42 +0000
Subject: [PATCH 05/11] Pyright

---
 src/eva/core/interface/interface.py             | 2 +-
 src/eva/language/models/wrappers/huggingface.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/eva/core/interface/interface.py b/src/eva/core/interface/interface.py
index ce1749e7..d23e33fa 100644
--- a/src/eva/core/interface/interface.py
+++ b/src/eva/core/interface/interface.py
@@ -51,7 +51,7 @@ def predict(
             model: The model module to use but not modify.
             data: The data module.
         """
-        trainer.infer_model(
+        eva_trainer.infer_model(
             base_trainer=trainer,
             base_model=model,
             datamodule=data,
diff --git a/src/eva/language/models/wrappers/huggingface.py b/src/eva/language/models/wrappers/huggingface.py
index c0623f6a..69c34299 100644
--- a/src/eva/language/models/wrappers/huggingface.py
+++ b/src/eva/language/models/wrappers/huggingface.py
@@ -42,7 +42,7 @@ def load_model(self) -> None:
             task=self._task, model=self._model_name_or_path, **self._model_kwargs
         )
 
-    def generate(self, prompt: str, **generate_kwargs) -> str:
+    def generate(self, prompt: str, **generate_kwargs) -> Any:
         """Generates text using the pipeline.
 
         Args:

From 8e37c03c88a340093bb0a752f22f8863dec64ebe Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Tue, 11 Feb 2025 14:13:33 +0000
Subject: [PATCH 06/11] Formatting fixes

---
 src/eva/core/trainers/functional.py               |  2 +-
 src/eva/core/trainers/trainer.py                  |  2 +-
 .../data/datasets/classification/pubmedqa.py      | 15 ++++++---------
 src/eva/language/models/__init__.py               |  2 +-
 src/eva/language/models/networks/module.py        |  6 +++---
 src/eva/language/models/wrappers/huggingface.py   |  9 ++++-----
 6 files changed, 16 insertions(+), 20 deletions(-)

diff --git a/src/eva/core/trainers/functional.py b/src/eva/core/trainers/functional.py
index 33b8f4d9..2c29891a 100644
--- a/src/eva/core/trainers/functional.py
+++ b/src/eva/core/trainers/functional.py
@@ -133,7 +133,7 @@ def infer_model(
     )
 
 
-def run_validation_only(
+def run_validation(
     base_trainer: eva_trainer.Trainer,
     base_model: modules.ModelModule,
     datamodule: datamodules.DataModule,
diff --git a/src/eva/core/trainers/trainer.py b/src/eva/core/trainers/trainer.py
index c4428ab0..36654a00 100644
--- a/src/eva/core/trainers/trainer.py
+++ b/src/eva/core/trainers/trainer.py
@@ -130,7 +130,7 @@ def validate_only(
         Returns:
             Validation metrics as returned by trainer.validate.
         """
-        functional.run_validation_only(
+        functional.run_validation(
             base_trainer=self,
             base_model=model,
             datamodule=datamodule,
diff --git a/src/eva/language/data/datasets/classification/pubmedqa.py b/src/eva/language/data/datasets/classification/pubmedqa.py
index 76b682f6..9ae54e46 100644
--- a/src/eva/language/data/datasets/classification/pubmedqa.py
+++ b/src/eva/language/data/datasets/classification/pubmedqa.py
@@ -121,15 +121,12 @@ def load_target(self, index: int) -> torch.Tensor:
     def load_metadata(self, index: int) -> Dict[str, str]:
         sample = self.dataset[index]
         return {
-            key: str(value) if value is not None else ""
-            for key, value in {
-                "year": sample.get("YEAR"),
-                "labels": sample.get("LABELS"),
-                "meshes": sample.get("MESHES"),
-                "long_answer": sample.get("LONG_ANSWER"),
-                "reasoning_required": sample.get("reasoning_required_pred"),
-                "reasoning_free": sample.get("reasoning_free_pred"),
-            }.items()
+            "year": sample.get("YEAR", ""),
+            "labels": sample.get("LABELS", ""),
+            "meshes": sample.get("MESHES", ""),
+            "long_answer": sample.get("LONG_ANSWER", ""),
+            "reasoning_required": sample.get("reasoning_required_pred", ""),
+            "reasoning_free": sample.get("reasoning_free_pred", ""),
         }
 
     @override
diff --git a/src/eva/language/models/__init__.py b/src/eva/language/models/__init__.py
index d4bd1519..d6f09bd2 100644
--- a/src/eva/language/models/__init__.py
+++ b/src/eva/language/models/__init__.py
@@ -4,4 +4,4 @@
 from eva.language.models.networks import TextModule
 from eva.language.models.wrappers import HuggingFaceTextModel
 
-__all__ = ["networks", "wrappers", "HuggingFaceTextModel", "TextModule"]
+__all__ = ["networks", "wrappers", "TextModule", "HuggingFaceTextModel"]
diff --git a/src/eva/language/models/networks/module.py b/src/eva/language/models/networks/module.py
index f17f4084..2c6602ab 100644
--- a/src/eva/language/models/networks/module.py
+++ b/src/eva/language/models/networks/module.py
@@ -1,6 +1,6 @@
 """LLM Text Module for Inference."""
 
-from typing import Any
+from typing import Any, List
 
 from lightning.pytorch.utilities.types import STEP_OUTPUT
 from torch import nn
@@ -40,7 +40,7 @@ def __init__(
         self.prompt = prompt
 
     @override
-    def forward(self, prompts: str, *args: Any, **kwargs: Any) -> list[str]:
+    def forward(self, prompts: str, *args: Any, **kwargs: Any) -> List[str]:
         """Generates text responses for a batch of prompts.
 
         Args:
@@ -78,6 +78,6 @@ def _batch_step(self, batch: INPUT_BATCH) -> STEP_OUTPUT:
         """
         data, targets, metadata = INPUT_BATCH(*batch)
         message = self.prompt + str(data) + "\nAnswer: "
-        predictions = self.forward(message)
+        predictions = self(message)
         # TODO: Add support for evaluation metrics
         return {"predictions": predictions, "targets": targets, "metadata": batch}
diff --git a/src/eva/language/models/wrappers/huggingface.py b/src/eva/language/models/wrappers/huggingface.py
index 69c34299..67c343b3 100644
--- a/src/eva/language/models/wrappers/huggingface.py
+++ b/src/eva/language/models/wrappers/huggingface.py
@@ -1,6 +1,6 @@
 """LLM wrapper for HuggingFace `transformers` models."""
 
-from typing import Any, Dict, Optional
+from typing import Any, Dict, Literal
 
 import transformers
 from typing_extensions import override
@@ -14,8 +14,8 @@ class HuggingFaceTextModel(base.BaseModel):
     def __init__(
         self,
         model_name_or_path: str,
-        task: str = "text-generation",
-        model_kwargs: Optional[Dict[str, Any]] = None,
+        task: Literal["text-generation", "text-classification"] = "text-generation",
+        model_kwargs: Dict[str, Any] | None = None,
     ) -> None:
         """Initializes the model.
 
@@ -23,8 +23,7 @@ def __init__(
             model_name_or_path: The model name or path to load the model from.
                 This can be a local path or a model name from the `HuggingFace`
                 model hub.
-            task: The pipeline task (e.g., "text-generation", "text-classification").
-                Defaults to "text-generation".
+            task: The pipeline task. Defaults to "text-generation".
             model_kwargs: Additional arguments for configuring the pipeline.
         """
         super().__init__()

From f62a0010a2f1bf855691e14c13e2cf28abc6c13b Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Tue, 11 Feb 2025 14:24:35 +0000
Subject: [PATCH 07/11] Minor fix

---
 .../data/datasets/classification/pubmedqa.py         | 12 ++++++------
 src/eva/language/models/networks/module.py           |  2 +-
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/eva/language/data/datasets/classification/pubmedqa.py b/src/eva/language/data/datasets/classification/pubmedqa.py
index 9ae54e46..7b123bed 100644
--- a/src/eva/language/data/datasets/classification/pubmedqa.py
+++ b/src/eva/language/data/datasets/classification/pubmedqa.py
@@ -121,12 +121,12 @@ def load_target(self, index: int) -> torch.Tensor:
     def load_metadata(self, index: int) -> Dict[str, str]:
         sample = self.dataset[index]
         return {
-            "year": sample.get("YEAR", ""),
-            "labels": sample.get("LABELS", ""),
-            "meshes": sample.get("MESHES", ""),
-            "long_answer": sample.get("LONG_ANSWER", ""),
-            "reasoning_required": sample.get("reasoning_required_pred", ""),
-            "reasoning_free": sample.get("reasoning_free_pred", ""),
+            "year": sample.get("YEAR") or "",
+            "labels": sample.get("LABELS") or "",
+            "meshes": sample.get("MESHES") or "",
+            "long_answer": sample.get("LONG_ANSWER") or "",
+            "reasoning_required": sample.get("reasoning_required_pred") or "",
+            "reasoning_free": sample.get("reasoning_free_pred") or "",
         }
 
     @override
diff --git a/src/eva/language/models/networks/module.py b/src/eva/language/models/networks/module.py
index 2c6602ab..3441d562 100644
--- a/src/eva/language/models/networks/module.py
+++ b/src/eva/language/models/networks/module.py
@@ -80,4 +80,4 @@ def _batch_step(self, batch: INPUT_BATCH) -> STEP_OUTPUT:
         message = self.prompt + str(data) + "\nAnswer: "
         predictions = self(message)
         # TODO: Add support for evaluation metrics
-        return {"predictions": predictions, "targets": targets, "metadata": batch}
+        return {"predictions": predictions, "targets": targets, "metadata": metadata}

From 99c78431e4d9ca86f677f78869fe91ac0fb357ec Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Tue, 18 Feb 2025 15:51:28 +0000
Subject: [PATCH 08/11] Add tests

---
 tests/eva/language/models/__init__.py         |  1 +
 .../eva/language/models/networks/__init__.py  |  1 +
 .../language/models/networks/test_module.py   | 63 +++++++++++++++++++
 .../eva/language/models/wrappers/__init__.py  |  1 +
 .../models/wrappers/test_huggingface.py       | 46 ++++++++++++++
 5 files changed, 112 insertions(+)
 create mode 100644 tests/eva/language/models/__init__.py
 create mode 100644 tests/eva/language/models/networks/__init__.py
 create mode 100644 tests/eva/language/models/networks/test_module.py
 create mode 100644 tests/eva/language/models/wrappers/__init__.py
 create mode 100644 tests/eva/language/models/wrappers/test_huggingface.py

diff --git a/tests/eva/language/models/__init__.py b/tests/eva/language/models/__init__.py
new file mode 100644
index 00000000..9746940d
--- /dev/null
+++ b/tests/eva/language/models/__init__.py
@@ -0,0 +1 @@
+"""Tests for the models submodule."""
diff --git a/tests/eva/language/models/networks/__init__.py b/tests/eva/language/models/networks/__init__.py
new file mode 100644
index 00000000..dd4d6422
--- /dev/null
+++ b/tests/eva/language/models/networks/__init__.py
@@ -0,0 +1 @@
+"""Model networks related tests."""
diff --git a/tests/eva/language/models/networks/test_module.py b/tests/eva/language/models/networks/test_module.py
new file mode 100644
index 00000000..dd490da8
--- /dev/null
+++ b/tests/eva/language/models/networks/test_module.py
@@ -0,0 +1,63 @@
+"""Tests the TextModule module."""
+
+import pytest
+from torch import nn
+
+from eva.language.models import TextModule
+
+
+def test_forward(text_module, text_model):
+    """Test the forward method of the TextModule class."""
+    input_text = "Hello world"
+    expected = text_model.generate(input_text)
+    result = text_module.forward(input_text)
+    assert result == expected
+
+
+def test_validation_step(text_module, text_model):
+    """Test the validation_step method of the TextModule class."""
+    data = "What is the capital of France?"
+    targets = "Paris"
+    metadata = {"id": 1}
+    batch = (data, targets, metadata)
+
+    expected_message = text_module.prompt + str(data) + "\nAnswer: "
+    expected_predictions = text_model.generate(expected_message)
+
+    output = text_module.validation_step(batch)
+
+    assert "predictions" in output
+    assert "targets" in output
+    assert "metadata" in output
+    assert output["predictions"] == expected_predictions
+    assert output["targets"] == targets
+    assert output["metadata"] == metadata
+
+
+def test_init_attributes(text_model):
+    """Test the attributes of the TextModule class."""
+    prompt = "Initialization Prompt: "
+    module_instance = TextModule(model=text_model, prompt=prompt)
+    assert module_instance.model is text_model
+    assert module_instance.prompt == prompt
+
+
+class TextModel(nn.Module):
+    """A simple text model for testing purposes."""
+
+    def generate(self, prompts: str):
+        """Generate some text based on the input prompt."""
+        return [f"Generated: {prompts}"]
+
+
+@pytest.fixture
+def text_model():
+    """Return a TextModel instance."""
+    return TextModel()
+
+
+@pytest.fixture
+def text_module(text_model):
+    """Return a TextModule instance."""
+    prompt = "Test Prompt: "
+    return TextModule(model=text_model, prompt=prompt)
diff --git a/tests/eva/language/models/wrappers/__init__.py b/tests/eva/language/models/wrappers/__init__.py
new file mode 100644
index 00000000..436e4f37
--- /dev/null
+++ b/tests/eva/language/models/wrappers/__init__.py
@@ -0,0 +1 @@
+"""Model wrapper related tests."""
diff --git a/tests/eva/language/models/wrappers/test_huggingface.py b/tests/eva/language/models/wrappers/test_huggingface.py
new file mode 100644
index 00000000..18c91fa0
--- /dev/null
+++ b/tests/eva/language/models/wrappers/test_huggingface.py
@@ -0,0 +1,46 @@
+"""HuggingFaceModel wrapper tests."""
+
+import pytest
+
+from eva.language.models import HuggingFaceTextModel
+
+
+@pytest.mark.parametrize(
+    "model_name_or_path, prompt, generate_kwargs, expect_deterministic",
+    [
+        (
+            "sshleifer/tiny-gpt2",
+            "Once upon a time",
+            {"max_length": 30, "do_sample": False},
+            True,
+        ),
+        (
+            "sshleifer/tiny-gpt2",
+            "In a galaxy far, far away",
+            {"max_length": 30, "do_sample": True},
+            False,
+        ),
+    ],
+)
+def test_real_small_hf_model_generation(
+    model_name_or_path: str,
+    prompt: str,
+    generate_kwargs: dict,
+    expect_deterministic: bool,
+):
+    """Integration test using a real, small Hugging Face model for text generation.
+
+    The test instantiates the HuggingFaceTextModel, generates text for a given prompt,
+    and asserts that the output is a non-empty string. If sampling is disabled,
+    repeated calls should return identical outputs.
+    """
+    model = HuggingFaceTextModel(model_name_or_path=model_name_or_path, task="text-generation")
+
+    output1 = model.generate(prompt, **generate_kwargs)
+    output2 = model.generate(prompt, **generate_kwargs)
+
+    assert isinstance(output1, str) and output1, "First output should be a non-empty string."
+    assert isinstance(output2, str) and output2, "Second output should be a non-empty string."
+
+    if expect_deterministic:
+        assert output1 == output2, "Outputs should be identical when do_sample is False."

From 3f1e239f8fc16275f54c40c6cec7247d339a72d1 Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Wed, 19 Feb 2025 15:06:41 +0000
Subject: [PATCH 09/11] Add litellm

---
 pdm.lock                                     | 497 ++++++++++++++++++-
 pyproject.toml                               |   1 +
 src/eva/language/models/wrappers/__init__.py |   3 +-
 3 files changed, 493 insertions(+), 8 deletions(-)

diff --git a/pdm.lock b/pdm.lock
index 3b64ba9f..2a0532c0 100644
--- a/pdm.lock
+++ b/pdm.lock
@@ -5,7 +5,7 @@
 groups = ["default", "all", "dev", "docs", "lint", "test", "typecheck", "vision"]
 strategy = ["inherit_metadata"]
 lock_version = "4.5.0"
-content_hash = "sha256:631e12e6ff397a3efac65fd4d1b612d96bf89cbd327f8df4806b2b9e89f69f4a"
+content_hash = "sha256:48cb0dfe80b45fc1318c0aed21ce1ea7146a857ba076b32c9c8f5d8fa01d54f1"
 
 [[metadata.targets]]
 requires_python = ">=3.10"
@@ -110,6 +110,20 @@ files = [
     {file = "aiosignal-1.3.1.tar.gz", hash = "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc"},
 ]
 
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+requires_python = ">=3.8"
+summary = "Reusable constraint types to use with typing.Annotated"
+groups = ["all"]
+dependencies = [
+    "typing-extensions>=4.0.0; python_version < \"3.9\"",
+]
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
 [[package]]
 name = "antlr4-python3-runtime"
 version = "4.9.3"
@@ -122,6 +136,23 @@ files = [
     {file = "antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b"},
 ]
 
+[[package]]
+name = "anyio"
+version = "4.8.0"
+requires_python = ">=3.9"
+summary = "High level compatibility layer for multiple asynchronous event loop implementations"
+groups = ["all"]
+dependencies = [
+    "exceptiongroup>=1.0.2; python_version < \"3.11\"",
+    "idna>=2.8",
+    "sniffio>=1.1",
+    "typing-extensions>=4.5; python_version < \"3.13\"",
+]
+files = [
+    {file = "anyio-4.8.0-py3-none-any.whl", hash = "sha256:b5011f270ab5eb0abf13385f851315585cc37ef330dd88e27ec3d34d651fd47a"},
+    {file = "anyio-4.8.0.tar.gz", hash = "sha256:1d9fe889df5212298c0c0723fa20479d1b94883a2df44bd3897aa91083316f7a"},
+]
+
 [[package]]
 name = "argcomplete"
 version = "3.5.0"
@@ -323,7 +354,7 @@ name = "click"
 version = "8.1.7"
 requires_python = ">=3.7"
 summary = "Composable command line interface toolkit"
-groups = ["dev", "docs", "lint"]
+groups = ["all", "dev", "docs", "lint"]
 dependencies = [
     "colorama; platform_system == \"Windows\"",
     "importlib-metadata; python_version < \"3.8\"",
@@ -547,12 +578,23 @@ files = [
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 ]
 
+[[package]]
+name = "distro"
+version = "1.9.0"
+requires_python = ">=3.6"
+summary = "Distro - an OS platform information API"
+groups = ["all"]
+files = [
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+]
+
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 version = "1.2.2"
 requires_python = ">=3.7"
 summary = "Backport of PEP 654 (exception groups)"
-groups = ["dev", "test", "typecheck"]
+groups = ["all", "dev", "test", "typecheck"]
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@@ -746,6 +788,20 @@ files = [
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 ]
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+requires_python = ">=3.7"
+summary = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+groups = ["all"]
+dependencies = [
+    "typing-extensions; python_version < \"3.8\"",
+]
+files = [
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+]
+
 [[package]]
 name = "h5py"
 version = "3.11.0"
@@ -771,6 +827,38 @@ files = [
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 ]
 
+[[package]]
+name = "httpcore"
+version = "1.0.7"
+requires_python = ">=3.8"
+summary = "A minimal low-level HTTP client."
+groups = ["all"]
+dependencies = [
+    "certifi",
+    "h11<0.15,>=0.13",
+]
+files = [
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+]
+
+[[package]]
+name = "httpx"
+version = "0.28.1"
+requires_python = ">=3.8"
+summary = "The next generation HTTP client."
+groups = ["all"]
+dependencies = [
+    "anyio",
+    "certifi",
+    "httpcore==1.*",
+    "idna",
+]
+files = [
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+]
+
 [[package]]
 name = "huggingface-hub"
 version = "0.24.5"
@@ -849,7 +937,7 @@ name = "importlib-metadata"
 version = "8.2.0"
 requires_python = ">=3.8"
 summary = "Read metadata from Python packages"
-groups = ["dev", "docs"]
+groups = ["all", "dev", "docs"]
 dependencies = [
     "typing-extensions>=3.6.4; python_version < \"3.8\"",
     "zipp>=0.5",
@@ -923,6 +1011,67 @@ files = [
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 ]
 
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+requires_python = ">=3.8"
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+groups = ["all"]
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+]
+
 [[package]]
 name = "jsonargparse"
 version = "4.31.0"
@@ -953,6 +1102,39 @@ files = [
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 ]
 
+[[package]]
+name = "jsonschema"
+version = "4.23.0"
+requires_python = ">=3.8"
+summary = "An implementation of JSON Schema validation for Python"
+groups = ["all"]
+dependencies = [
+    "attrs>=22.2.0",
+    "importlib-resources>=1.4.0; python_version < \"3.9\"",
+    "jsonschema-specifications>=2023.03.6",
+    "pkgutil-resolve-name>=1.3.10; python_version < \"3.9\"",
+    "referencing>=0.28.4",
+    "rpds-py>=0.7.1",
+]
+files = [
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+]
+
+[[package]]
+name = "jsonschema-specifications"
+version = "2024.10.1"
+requires_python = ">=3.9"
+summary = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
+groups = ["all"]
+dependencies = [
+    "referencing>=0.31.0",
+]
+files = [
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+]
+
 [[package]]
 name = "lazy-loader"
 version = "0.4"
@@ -1007,6 +1189,30 @@ files = [
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 ]
 
+[[package]]
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+requires_python = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
+summary = "Library to easily interface with LLM API providers"
+groups = ["all"]
+dependencies = [
+    "aiohttp",
+    "click",
+    "httpx>=0.23.0",
+    "importlib-metadata>=6.8.0",
+    "jinja2<4.0.0,>=3.1.2",
+    "jsonschema<5.0.0,>=4.22.0",
+    "openai>=1.61.0",
+    "pydantic<3.0.0,>=2.0.0",
+    "python-dotenv>=0.2.0",
+    "tiktoken>=0.7.0",
+    "tokenizers",
+]
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+
 [[package]]
 name = "loguru"
 version = "0.7.2"
@@ -1775,6 +1981,27 @@ files = [
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 ]
 
+[[package]]
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+version = "1.63.2"
+requires_python = ">=3.8"
+summary = "The official Python library for the openai API"
+groups = ["all"]
+dependencies = [
+    "anyio<5,>=3.5.0",
+    "distro<2,>=1.7.0",
+    "httpx<1,>=0.23.0",
+    "jiter<1,>=0.4.0",
+    "pydantic<3,>=1.9.0",
+    "sniffio",
+    "tqdm>4",
+    "typing-extensions<5,>=4.11",
+]
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+]
+
 [[package]]
 name = "opencv-python-headless"
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+    {file = "tiktoken-0.9.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:a6600660f2f72369acb13a57fb3e212434ed38b045fd8cc6cdd74947b4b5d210"},
+    {file = "tiktoken-0.9.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:95e811743b5dfa74f4b227927ed86cbc57cad4df859cb3b643be797914e41794"},
+    {file = "tiktoken-0.9.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:99376e1370d59bcf6935c933cb9ba64adc29033b7e73f5f7569f3aad86552b22"},
+    {file = "tiktoken-0.9.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:badb947c32739fb6ddde173e14885fb3de4d32ab9d8c591cbd013c22b4c31dd2"},
+    {file = "tiktoken-0.9.0-cp312-cp312-win_amd64.whl", hash = "sha256:5a62d7a25225bafed786a524c1b9f0910a1128f4232615bf3f8257a73aaa3b16"},
+    {file = "tiktoken-0.9.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:2b0e8e05a26eda1249e824156d537015480af7ae222ccb798e5234ae0285dbdb"},
+    {file = "tiktoken-0.9.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:27d457f096f87685195eea0165a1807fae87b97b2161fe8c9b1df5bd74ca6f63"},
+    {file = "tiktoken-0.9.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2cf8ded49cddf825390e36dd1ad35cd49589e8161fdcb52aa25f0583e90a3e01"},
+    {file = "tiktoken-0.9.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cc156cb314119a8bb9748257a2eaebd5cc0753b6cb491d26694ed42fc7cb3139"},
+    {file = "tiktoken-0.9.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:cd69372e8c9dd761f0ab873112aba55a0e3e506332dd9f7522ca466e817b1b7a"},
+    {file = "tiktoken-0.9.0-cp313-cp313-win_amd64.whl", hash = "sha256:5ea0edb6f83dc56d794723286215918c1cde03712cbbafa0348b33448faf5b95"},
+    {file = "tiktoken-0.9.0.tar.gz", hash = "sha256:d02a5ca6a938e0490e1ff957bc48c8b078c88cb83977be1625b1fd8aac792c5d"},
+]
+
 [[package]]
 name = "timm"
 version = "1.0.9"
@@ -2706,7 +3189,7 @@ name = "tokenizers"
 version = "0.19.1"
 requires_python = ">=3.7"
 summary = ""
-groups = ["default"]
+groups = ["default", "all"]
 dependencies = [
     "huggingface-hub<1.0,>=0.16.4",
 ]
@@ -3218,7 +3701,7 @@ name = "zipp"
 version = "3.20.0"
 requires_python = ">=3.8"
 summary = "Backport of pathlib-compatible object wrapper for zip files"
-groups = ["dev", "docs"]
+groups = ["all", "dev", "docs"]
 files = [
     {file = "zipp-3.20.0-py3-none-any.whl", hash = "sha256:58da6168be89f0be59beb194da1250516fdaa062ccebd30127ac65d30045e10d"},
     {file = "zipp-3.20.0.tar.gz", hash = "sha256:0145e43d89664cfe1a2e533adc75adafed82fe2da404b4bbb6b026c0157bdb31"},
diff --git a/pyproject.toml b/pyproject.toml
index 1c625b5e..ff4c48ab 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -84,6 +84,7 @@ all = [
     "scipy>=1.14.0",
     "monai>=1.3.2",
     "datasets>=3.2.0",
+    "litellm>=1.61.8",
 ]
 
 [project.scripts]
diff --git a/src/eva/language/models/wrappers/__init__.py b/src/eva/language/models/wrappers/__init__.py
index 950501ad..f4ac5416 100644
--- a/src/eva/language/models/wrappers/__init__.py
+++ b/src/eva/language/models/wrappers/__init__.py
@@ -1,5 +1,6 @@
 """Language Model Wrappers API."""
 
 from eva.language.models.wrappers.huggingface import HuggingFaceTextModel
+from eva.language.models.wrappers.litellm import LiteLLMTextModel
 
-__all__ = ["HuggingFaceTextModel"]
+__all__ = ["HuggingFaceTextModel", "LiteLLMTextModel"]

From 1dabe916a216293dcc4d170f589beec7d392d0af Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Wed, 19 Feb 2025 15:27:28 +0000
Subject: [PATCH 10/11] Formatting

---
 src/eva/language/models/__init__.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/eva/language/models/__init__.py b/src/eva/language/models/__init__.py
index d6f09bd2..a25acd79 100644
--- a/src/eva/language/models/__init__.py
+++ b/src/eva/language/models/__init__.py
@@ -2,6 +2,6 @@
 
 from eva.language.models import networks, wrappers
 from eva.language.models.networks import TextModule
-from eva.language.models.wrappers import HuggingFaceTextModel
+from eva.language.models.wrappers import HuggingFaceTextModel, LiteLLMTextModel
 
-__all__ = ["networks", "wrappers", "TextModule", "HuggingFaceTextModel"]
+__all__ = ["networks", "wrappers", "TextModule", "HuggingFaceTextModel", "LiteLLMTextModel"]

From 784997f01f64764cf3343d124cbc2440fd99a7df Mon Sep 17 00:00:00 2001
From: Rita <ritakurban@Ritas-Mac.local>
Date: Fri, 21 Feb 2025 15:44:25 +0000
Subject: [PATCH 11/11] Add wrapper drafts

---
 pdm.lock                                     | 763 ++++++++++++++++++-
 pyproject.toml                               |   1 +
 src/eva/language/models/__init__.py          |   9 +-
 src/eva/language/models/wrappers/__init__.py |   3 +-
 src/eva/language/models/wrappers/litellm.py  |  56 ++
 src/eva/language/models/wrappers/vllm.py     |  90 +++
 6 files changed, 916 insertions(+), 6 deletions(-)
 create mode 100644 src/eva/language/models/wrappers/litellm.py
 create mode 100644 src/eva/language/models/wrappers/vllm.py

diff --git a/pdm.lock b/pdm.lock
index 2a0532c0..fc7ab6e5 100644
--- a/pdm.lock
+++ b/pdm.lock
@@ -5,7 +5,7 @@
 groups = ["default", "all", "dev", "docs", "lint", "test", "typecheck", "vision"]
 strategy = ["inherit_metadata"]
 lock_version = "4.5.0"
-content_hash = "sha256:48cb0dfe80b45fc1318c0aed21ce1ea7146a857ba076b32c9c8f5d8fa01d54f1"
+content_hash = "sha256:777b3becf5fa0aa7241d69f7345cf222c016e2d7bc8bbf7cc427397449a155dc"
 
 [[metadata.targets]]
 requires_python = ">=3.10"
@@ -110,6 +110,17 @@ files = [
     {file = "aiosignal-1.3.1.tar.gz", hash = "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc"},
 ]
 
+[[package]]
+name = "airportsdata"
+version = "20241001"
+requires_python = ">=3.9"
+summary = "Extensive database of location and timezone data for nearly every airport and landing strip in the world."
+groups = ["all"]
+files = [
+    {file = "airportsdata-20241001-py3-none-any.whl", hash = "sha256:67d71cf2c5378cc17ff66b62b1e11aa2444043949c894543ac8fd8dafce192fd"},
+    {file = "airportsdata-20241001.tar.gz", hash = "sha256:fa0bd143b4f4be3557cb892fa0612ef210fd91a92bd720b4d8221de576a4fa00"},
+]
+
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -364,6 +375,48 @@ files = [
     {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
 ]
 
+[[package]]
+name = "cloudpickle"
+version = "3.1.1"
+requires_python = ">=3.8"
+summary = "Pickler class to extend the standard pickle.Pickler functionality"
+groups = ["all"]
+files = [
+    {file = "cloudpickle-3.1.1-py3-none-any.whl", hash = "sha256:c8c5a44295039331ee9dad40ba100a9c7297b6f988e50e87ccdf3765a668350e"},
+    {file = "cloudpickle-3.1.1.tar.gz", hash = "sha256:b216fa8ae4019d5482a8ac3c95d8f6346115d8835911fd4aefd1a445e4242c64"},
+]
+
+[[package]]
+name = "cmake"
+version = "3.31.4"
+requires_python = ">=3.7"
+summary = "CMake is an open-source, cross-platform family of tools designed to build, test and package software"
+groups = ["all"]
+dependencies = [
+    "importlib-metadata>=1.4; python_version < \"3.8\"",
+]
+files = [
+    {file = "cmake-3.31.4-py3-none-macosx_10_10_universal2.whl", hash = "sha256:fc048b4b70facd16699a43c737f6782b4eff56e8e6093090db5979532d9db0f6"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_12_i686.manylinux2010_i686.whl", hash = "sha256:2a37be93534df04513f0845492d71bc80899c3f87b77e3b01c95aff1a7fc9bde"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:c9f5f8289c5e7bd2ed654cbac164021fa7723064fee0443a2f0068bc08413d81"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:926d91cae2ba7d2f3df857d0fc066bdac4f3904bf5c95e99b60435e85aabedb4"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:929a8d8d289d69e43784661748ddd08933ce1ec5db8f9bcfce6ee817a48f8787"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b463efdf5b92f3b290235aa9f8da092b3dac19b7636c563fd156022dab580649"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:225d9a643b0b60ffce0399ff0cabd7a4820e0dbcb794e97d3aacfcf7c0589ae6"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89143a5e2a5916061f2cfc5012e9fe6281aaf7c0dae7930bdc68d105d22ddc39"},
+    {file = "cmake-3.31.4-py3-none-manylinux_2_31_armv7l.whl", hash = "sha256:f96127bf663168accd29d5a50ee68ea80f26bcd37f96c7a14ef2378781f19936"},
+    {file = "cmake-3.31.4-py3-none-musllinux_1_1_aarch64.whl", hash = "sha256:25c5094394f0cee21130b5678e5b4552f72470e266df6d6fb1d5c505100f0eaa"},
+    {file = "cmake-3.31.4-py3-none-musllinux_1_1_i686.whl", hash = "sha256:466c9295af440bb4a47cc5e1af10576cf2227620528afd0fd0b3effa1d513b49"},
+    {file = "cmake-3.31.4-py3-none-musllinux_1_1_ppc64le.whl", hash = "sha256:f6af3b83a1b1fc1d990d18b6a566ee9c95c0393f986c6df15f2505dda8ad1bcc"},
+    {file = "cmake-3.31.4-py3-none-musllinux_1_1_s390x.whl", hash = "sha256:23781e17563693a68b0cef85749746894b8a61488e56e96fc6649b73652e8236"},
+    {file = "cmake-3.31.4-py3-none-musllinux_1_1_x86_64.whl", hash = "sha256:838a388b559137f3654d8cf30f62bbdec10f8d1c3624f0d289614d33cdf4fba1"},
+    {file = "cmake-3.31.4-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:a6a3b0b9557f41c955a6b25c94205f2ca9c3a46edca809ad87507c5ef6bc4274"},
+    {file = "cmake-3.31.4-py3-none-win32.whl", hash = "sha256:d378c9e58eac906bddafd673c7571262dcd5a9946bb1e8f9e3902572a8fa95ca"},
+    {file = "cmake-3.31.4-py3-none-win_amd64.whl", hash = "sha256:20be7cdb41903edf85e8a498c4beff8d6854acbb087abfb07c362c738bdf0018"},
+    {file = "cmake-3.31.4-py3-none-win_arm64.whl", hash = "sha256:9479a9255197c49e135df039d8484c69aa63158a06ae9c2d0eb939da2f0f7dff"},
+    {file = "cmake-3.31.4.tar.gz", hash = "sha256:a6ac2242e0b16ad7d94c9f8572d6f232e6169747be50e5cdf497f206c4819ce1"},
+]
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -568,6 +621,17 @@ files = [
     {file = "dill-0.3.8.tar.gz", hash = "sha256:3ebe3c479ad625c4553aca177444d89b486b1d84982eeacded644afc0cf797ca"},
 ]
 
+[[package]]
+name = "diskcache"
+version = "5.6.3"
+requires_python = ">=3"
+summary = "Disk Cache -- Disk and file backed persistent cache."
+groups = ["all"]
+files = [
+    {file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"},
+    {file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"},
+]
+
 [[package]]
 name = "distlib"
 version = "0.3.8"
@@ -601,6 +665,22 @@ files = [
     {file = "exceptiongroup-1.2.2.tar.gz", hash = "sha256:47c2edf7c6738fafb49fd34290706d1a1a2f4d1c6df275526b62cbb4aa5393cc"},
 ]
 
+[[package]]
+name = "fastapi"
+version = "0.115.8"
+requires_python = ">=3.8"
+summary = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
+groups = ["all"]
+dependencies = [
+    "pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4",
+    "starlette<0.46.0,>=0.40.0",
+    "typing-extensions>=4.8.0",
+]
+files = [
+    {file = "fastapi-0.115.8-py3-none-any.whl", hash = "sha256:753a96dd7e036b34eeef8babdfcfe3f28ff79648f86551eb36bfc1b0bf4a8cbf"},
+    {file = "fastapi-0.115.8.tar.gz", hash = "sha256:0ce9111231720190473e222cdf0f07f7206ad7e53ea02beb1d2dc36e2f0741e9"},
+]
+
 [[package]]
 name = "filelock"
 version = "3.15.4"
@@ -722,6 +802,16 @@ files = [
     {file = "gdown-5.2.0.tar.gz", hash = "sha256:2145165062d85520a3cd98b356c9ed522c5e7984d408535409fd46f94defc787"},
 ]
 
+[[package]]
+name = "genson"
+version = "1.3.0"
+summary = "GenSON is a powerful, user-friendly JSON Schema generator."
+groups = ["all"]
+files = [
+    {file = "genson-1.3.0-py3-none-any.whl", hash = "sha256:468feccd00274cc7e4c09e84b08704270ba8d95232aa280f65b986139cec67f7"},
+    {file = "genson-1.3.0.tar.gz", hash = "sha256:e02db9ac2e3fd29e65b5286f7135762e2cd8a986537c075b06fc5f1517308e37"},
+]
+
 [[package]]
 name = "ghp-import"
 version = "2.1.0"
@@ -842,6 +932,44 @@ files = [
     {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"},
 ]
 
+[[package]]
+name = "httptools"
+version = "0.6.4"
+requires_python = ">=3.8.0"
+summary = "A collection of framework independent HTTP protocol utils."
+groups = ["all"]
+files = [
+    {file = "httptools-0.6.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:3c73ce323711a6ffb0d247dcd5a550b8babf0f757e86a52558fe5b86d6fefcc0"},
+    {file = "httptools-0.6.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:345c288418f0944a6fe67be8e6afa9262b18c7626c3ef3c28adc5eabc06a68da"},
+    {file = "httptools-0.6.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:deee0e3343f98ee8047e9f4c5bc7cedbf69f5734454a94c38ee829fb2d5fa3c1"},
+    {file = "httptools-0.6.4-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ca80b7485c76f768a3bc83ea58373f8db7b015551117375e4918e2aa77ea9b50"},
+    {file = "httptools-0.6.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:90d96a385fa941283ebd231464045187a31ad932ebfa541be8edf5b3c2328959"},
+    {file = "httptools-0.6.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:59e724f8b332319e2875efd360e61ac07f33b492889284a3e05e6d13746876f4"},
+    {file = "httptools-0.6.4-cp310-cp310-win_amd64.whl", hash = "sha256:c26f313951f6e26147833fc923f78f95604bbec812a43e5ee37f26dc9e5a686c"},
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+    {file = "httptools-0.6.4-cp312-cp312-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:16e603a3bff50db08cd578d54f07032ca1631450ceb972c2f834c2b860c28ea2"},
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+groups = ["all"]
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 [[package]]
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 version = "3.3"
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+    "frozenlist",
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 version = "0.1.0"
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+    "ray>=2.9",
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 version = "4.0.2"
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+    {file = "websockets-15.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:8561c48b0090993e3b2a54db480cab1d23eb2c5735067213bb90f402806339f5"},
+    {file = "websockets-15.0-py3-none-any.whl", hash = "sha256:51ffd53c53c4442415b613497a34ba0aa7b99ac07f1e4a62db5dcd640ae6c3c3"},
+    {file = "websockets-15.0.tar.gz", hash = "sha256:ca36151289a15b39d8d683fd8b7abbe26fc50be311066c5f8dcf3cb8cee107ab"},
+]
+
 [[package]]
 name = "werkzeug"
 version = "3.0.3"
@@ -3545,6 +4284,24 @@ files = [
     {file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"},
 ]
 
+[[package]]
+name = "xformers"
+version = "0.0.26.post1"
+requires_python = ">=3.7"
+summary = "XFormers: A collection of composable Transformer building blocks."
+groups = ["all"]
+dependencies = [
+    "numpy",
+    "torch==2.3.0",
+]
+files = [
+    {file = "xformers-0.0.26.post1-cp310-cp310-manylinux2014_x86_64.whl", hash = "sha256:1fe0f9a3dddb7f6175c2e34de2f318d6742eec28c068b8334b093016b2c9c2c8"},
+    {file = "xformers-0.0.26.post1-cp310-cp310-win_amd64.whl", hash = "sha256:e34b8dd6982077bee0c8eb2db8bc1513177201bfe0af890a4db42d8d31c966a5"},
+    {file = "xformers-0.0.26.post1-cp311-cp311-manylinux2014_x86_64.whl", hash = "sha256:0d35615870b9237077aec51802a5a821f9e9d2708730c8914d5cff301fb29558"},
+    {file = "xformers-0.0.26.post1-cp311-cp311-win_amd64.whl", hash = "sha256:d05c547b4ba603fc8e21fad03a342138eaaece35fe0a1692e6ee0d061ddd21ac"},
+    {file = "xformers-0.0.26.post1.tar.gz", hash = "sha256:1d14b5f999ede649198379b0470ebdd25007ba224ae336ef958124158a6de8b1"},
+]
+
 [[package]]
 name = "xxhash"
 version = "3.5.0"
diff --git a/pyproject.toml b/pyproject.toml
index ff4c48ab..6a1a6bec 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -85,6 +85,7 @@ all = [
     "monai>=1.3.2",
     "datasets>=3.2.0",
     "litellm>=1.61.8",
+    "vllm>=0.5.1",
 ]
 
 [project.scripts]
diff --git a/src/eva/language/models/__init__.py b/src/eva/language/models/__init__.py
index a25acd79..4ef1db27 100644
--- a/src/eva/language/models/__init__.py
+++ b/src/eva/language/models/__init__.py
@@ -2,6 +2,11 @@
 
 from eva.language.models import networks, wrappers
 from eva.language.models.networks import TextModule
-from eva.language.models.wrappers import HuggingFaceTextModel, LiteLLMTextModel
+from eva.language.models.wrappers import HuggingFaceTextModel, LiteLLMTextModel, VLLMTextModel
 
-__all__ = ["networks", "wrappers", "TextModule", "HuggingFaceTextModel", "LiteLLMTextModel"]
+__all__ = ["networks",
+           "wrappers",
+           "TextModule",
+           "HuggingFaceTextModel",
+           "LiteLLMTextModel",
+           'VLLMTextModel']
diff --git a/src/eva/language/models/wrappers/__init__.py b/src/eva/language/models/wrappers/__init__.py
index f4ac5416..66f498d1 100644
--- a/src/eva/language/models/wrappers/__init__.py
+++ b/src/eva/language/models/wrappers/__init__.py
@@ -2,5 +2,6 @@
 
 from eva.language.models.wrappers.huggingface import HuggingFaceTextModel
 from eva.language.models.wrappers.litellm import LiteLLMTextModel
+from eva.language.models.wrappers.vllm import VLLMTextModel
 
-__all__ = ["HuggingFaceTextModel", "LiteLLMTextModel"]
+__all__ = ["HuggingFaceTextModel", "LiteLLMTextModel", "VLLMTextModel"]
diff --git a/src/eva/language/models/wrappers/litellm.py b/src/eva/language/models/wrappers/litellm.py
new file mode 100644
index 00000000..8fb641b2
--- /dev/null
+++ b/src/eva/language/models/wrappers/litellm.py
@@ -0,0 +1,56 @@
+"""LLM wrapper for litellm models."""
+
+from typing import Any, Dict, Optional
+
+from litellm import completion
+from typing_extensions import override
+
+from eva.core.models.wrappers import base
+
+
+class LiteLLMTextModel(base.BaseModel):
+    """Wrapper class for using litellm for chat-based text generation.
+
+    This wrapper uses litellm's `completion` function which accepts a list of
+    message dictionaries. The `generate` method converts a string prompt into a chat
+    message with a default role of "user", optionally prepends a system message, and
+    includes an API key if provided.
+    """
+
+    def __init__(
+        self,
+        model_name_or_path: str,
+    ) -> None:
+        """Initializes the litellm chat model wrapper.
+
+        Args:
+            model_name_or_path: The model identifier (or name) for litellm (e.g.,
+                "openai/gpt-4o" or "anthropic/claude-3-sonnet-20240229").
+        """
+        super().__init__()
+        self._model_name_or_path = model_name_or_path
+        self.load_model()
+
+    @override
+    def load_model(self) -> None:
+        """Prepares the litellm model.
+
+        Note:
+            litellm does not require an explicit loading step; models are invoked
+            directly during generation. This method exists for API consistency.
+        """
+        pass
+
+    def generate(self, prompt: str, **generate_kwargs) -> str:
+        """Generates text using litellm.
+
+        Args:
+            prompt: A string prompt that will be converted into a "user" chat message.
+            generate_kwargs: Additional parameters for generation (e.g., max_tokens).
+
+        Returns:
+            The generated text response.
+        """
+        messages = [{"role": "user", "content": prompt}]
+        response = completion(model=self._model_name_or_path, messages=messages, **generate_kwargs)
+        return response["choices"][0]["message"]["content"]
diff --git a/src/eva/language/models/wrappers/vllm.py b/src/eva/language/models/wrappers/vllm.py
new file mode 100644
index 00000000..cf4681a0
--- /dev/null
+++ b/src/eva/language/models/wrappers/vllm.py
@@ -0,0 +1,90 @@
+"""LLM wrapper for vLLM models."""
+
+from typing import Any, Dict
+import time
+
+from typing_extensions import override
+
+from vllm import LLM, SamplingParams
+from vllm.inputs import TokensPrompt
+
+from eva.core.models.wrappers import base
+
+
+class VLLMTextModel(base.BaseModel):
+    """
+    Wrapper class for using vLLM for text generation.
+
+    This wrapper loads a vLLM model, sets up the tokenizer and sampling parameters,
+    and uses a chat template to convert a plain string prompt into the proper input
+    format for vLLM generation. It then returns the generated text response.
+    """
+
+    def __init__(
+        self,
+        model_name_or_path: str,
+        model_kwargs: Dict[str, Any] | None = None,
+    ) -> None:
+        """
+        Initializes the vLLM model wrapper.
+
+        Args:
+            model_name_or_path: The model identifier (e.g., a Hugging Face repo ID or local path).
+            model_kwargs: Additional keyword arguments for initializing the vLLM model.
+            generation_kwargs: Additional keyword arguments for the sampling parameters.
+        """
+        super().__init__()
+        self._model_name_or_path = model_name_or_path
+        self._model_kwargs = model_kwargs or {}
+        self.load_model()
+
+    @override
+    def load_model(self) -> None:
+        """
+        Loads the vLLM model and sets up the tokenizer and sampling parameters.
+        """
+        self._model = LLM(model=self._model_name_or_path, **self._model_kwargs)
+        self._tokenizer = self._model.get_tokenizer()
+
+    def _apply_chat_template(self, prompt: str) -> TokensPrompt:
+        """
+        Converts a prompt string into a TokensPrompt using the tokenizer's chat template.
+
+        Args:
+            prompt: The input prompt as a string.
+
+        Returns:
+            A TokensPrompt object ready for generation.
+
+        Raises:
+            ValueError: If the tokenizer does not support a chat template.
+        """
+        messages = [{"role": "user", "content": prompt}]
+        if self._tokenizer.chat_template is None:
+            raise ValueError("Tokenizer does not have a chat template.")
+        encoded_messages = self._tokenizer.apply_chat_template(
+            [messages],
+            tokenize=True,
+            add_generation_prompt=True,
+        )
+        if len(encoded_messages[0]) >= 2 and (
+            encoded_messages[0][0] == self._tokenizer.bos_token_id
+            and encoded_messages[0][1] == self._tokenizer.bos_token_id
+        ):
+            encoded_messages[0] = encoded_messages[0][1:]
+        return [TokensPrompt(prompt_token_ids=encoded_messages[0])]
+
+    def generate(self, prompt: str, **generate_kwargs) -> str:
+        """
+        Generates text for the given prompt using the vLLM model.
+
+        Args:
+            prompt: A string prompt for generation.
+            generate_kwargs: Additional parameters for generation (e.g., max_tokens).
+
+        Returns:
+            The generated text response.
+        """
+        tokens_prompt = self._apply_chat_template(prompt)
+        outputs = self._model.generate(tokens_prompt, SamplingParams(**generate_kwargs))
+        return outputs[0].outputs[0].text