diff --git a/.github/workflows/prek.yml b/.github/workflows/prek.yml
index 1f3d52b4a..bb4e129ba 100644
--- a/.github/workflows/prek.yml
+++ b/.github/workflows/prek.yml
@@ -3,34 +3,34 @@ name: Prek
 on:
   pull_request:
   push:
-    branches: [ main ]
+    branches: [main]
 
 jobs:
   quality-checks:
     runs-on: ubuntu-latest
-    
+
     steps:
-    - name: Checkout code
-      uses: actions/checkout@v4
-    
-    - name: Set up Python
-      uses: actions/setup-python@v5
-      with:
-        python-version: '3.10'
-    
-    - name: Install uv
-      run: |
-        curl -LsSf https://astral.sh/uv/install.sh | sh
-        echo "$HOME/.cargo/bin" >> $GITHUB_PATH
-
-    - name: Install dependencies
-      run: |
-        uv sync --all-extras
-    
-    - name: Run prek hooks (lint, format, typecheck, uv.lock, tests)
-      run: |
-        uv run prek run --all-files
-
-    - name: Run unit tests (via prek)
-      run: |
-        uv run prek run pytest
\ No newline at end of file
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install uv
+        run: |
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          echo "$HOME/.cargo/bin" >> $GITHUB_PATH
+
+      - name: Install dependencies (with all optional extras for complete type checking)
+        run: |
+          uv sync --all-extras
+
+      - name: Run prek hooks (lint, format, typecheck, uv.lock, tests)
+        run: |
+          uv run prek run --all-files
+
+      - name: Run unit tests (via prek)
+        run: |
+          uv run prek run pytest
\ No newline at end of file
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index b5be17686..622254ac5 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -7,9 +7,9 @@ repos:
 
   - repo: local
     hooks:
-      - id: pyright
-        name: Pyright type checking
-        entry: uv run pyright src tests
+      - id: ty
+        name: ty type checking
+        entry: uv run ty check src tests
         language: system
         pass_filenames: false
 
diff --git a/pyproject.toml b/pyproject.toml
index 4d0f4bf23..1a50198af 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -102,6 +102,53 @@ asyncio_mode = "auto"
 [tool.uv]
 required-version = ">=0.6.15"
 
+[tool.ty.environment]
+python-version = "3.11"
+
+[tool.ty.rules]
+# Ignore unused-ignore-comment warnings because they vary depending on whether
+# optional deps are installed. The ty:ignore comments are needed in CI (with all deps)
+# but become unused locally (without all deps).
+unused-ignore-comment = "ignore"
+
+[tool.ty.analysis]
+# Allow unresolved imports for optional dependencies that may not be installed locally.
+# In CI, we install all optional deps so these will be resolved and type-checked.
+allowed-unresolved-imports = [
+    # backend deps
+    "accelerate.**",
+    "awscli.**",
+    "bitsandbytes.**",
+    "duckdb.**",
+    "fastapi.**",
+    "gql.**",
+    "hf_xet.**",
+    "nbclient.**",
+    "nbmake.**",
+    "peft.**",
+    "pyarrow.**",
+    "torch.**",
+    "torchao.**",
+    "transformers.**",
+    "trl.**",
+    "unsloth.**",
+    "unsloth_zoo.**",
+    "uvicorn.**",
+    "vllm.**",
+    "wandb.**",
+    # skypilot deps
+    "semver.**",
+    "sky.**",
+    "skypilot.**",
+    # langgraph deps
+    "langchain_core.**",
+    "langchain_openai.**",
+    "langgraph.**",
+    # plotting deps
+    "matplotlib.**",
+    "seaborn.**",
+]
+
 [dependency-groups]
 dev = [
     "black>=25.1.0",
@@ -112,7 +159,7 @@ dev = [
     "pytest>=8.4.1",
     "nbval>=0.11.0",
     "pytest-xdist>=3.8.0",
-    "pyright[nodejs]>=1.1.403",
+    "ty>=0.0.14",
     "pytest-asyncio>=1.1.0",
     "duckdb>=1.0.0",
     "pyarrow>=15.0.0",
diff --git a/src/art/__init__.py b/src/art/__init__.py
index 75957e176..b6948f514 100644
--- a/src/art/__init__.py
+++ b/src/art/__init__.py
@@ -34,10 +34,10 @@ def __init__(self, **kwargs):
 
 # Import unsloth before transformers, peft, and trl to maximize Unsloth optimizations
 if os.environ.get("IMPORT_UNSLOTH", "0") == "1":
-    import unsloth  # type: ignore # noqa: F401
+    import unsloth  # noqa: F401
 
 try:
-    import transformers  # type: ignore
+    import transformers
 
     try:
         from .transformers.patches import patch_preprocess_mask_arguments
diff --git a/src/art/auto_trajectory.py b/src/art/auto_trajectory.py
index 4979602f7..a22d0be7c 100644
--- a/src/art/auto_trajectory.py
+++ b/src/art/auto_trajectory.py
@@ -177,10 +177,10 @@ async def patched_aclose(self: httpx._models.Response) -> None:
         if context := auto_trajectory_context_var.get(None):
             context.handle_httpx_response(self)
 
-    httpx._models.Response.iter_bytes = patched_iter_bytes
-    httpx._models.Response.aiter_bytes = patched_aiter_bytes
-    httpx._models.Response.close = patched_close
-    httpx._models.Response.aclose = patched_aclose
+    httpx._models.Response.iter_bytes = patched_iter_bytes  # ty:ignore[invalid-assignment]
+    httpx._models.Response.aiter_bytes = patched_aiter_bytes  # ty:ignore[invalid-assignment]
+    httpx._models.Response.close = patched_close  # ty:ignore[invalid-assignment]
+    httpx._models.Response.aclose = patched_aclose  # ty:ignore[invalid-assignment]
 
 
 patch_httpx()
diff --git a/src/art/cli.py b/src/art/cli.py
index dd64fc634..09b32e9de 100644
--- a/src/art/cli.py
+++ b/src/art/cli.py
@@ -159,7 +159,7 @@ def __init__(self, *args: Any, **kwargs: Any) -> None:
         return pydantic.BaseModel.__init__(self, *args, **kwargs)
 
     TrajectoryGroup.__new__ = __new__  # type: ignore
-    TrajectoryGroup.__init__ = __init__
+    TrajectoryGroup.__init__ = __init__  # ty:ignore[invalid-assignment]
 
     backend = LocalBackend()
     app = FastAPI()
diff --git a/src/art/gather.py b/src/art/gather.py
index 3461107c2..3a72df637 100644
--- a/src/art/gather.py
+++ b/src/art/gather.py
@@ -134,7 +134,7 @@ async def gather_trajectories(
         )
     if context.pbar is not None:
         context.pbar.close()
-    return results  # type: ignore
+    return results
 
 
 async def wrap_group_awaitable(
@@ -193,7 +193,7 @@ def record_metrics(context: "GatherContext", trajectory: Trajectory) -> None:
             len(l.content or l.refusal or [])
             for l in logprobs  # noqa: E741
         ) / len(logprobs)
-    context.metric_sums["reward"] += trajectory.reward  # type: ignore
+    context.metric_sums["reward"] += trajectory.reward
     context.metric_divisors["reward"] += 1
     context.metric_sums.update(trajectory.metrics)
     context.metric_divisors.update(trajectory.metrics.keys())
@@ -229,7 +229,7 @@ def too_many_exceptions(self) -> bool:
         if (
             0 < self.max_exceptions < 1
             and self.pbar is not None
-            and self.metric_sums["exceptions"] / self.pbar.total <= self.max_exceptions
+            and self.metric_sums["exceptions"] / self.pbar.total <= self.max_exceptions  # ty:ignore[unsupported-operator]
         ) or self.metric_sums["exceptions"] <= self.max_exceptions:
             return False
         return True
diff --git a/src/art/guided_completion.py b/src/art/guided_completion.py
index 6599f486f..c1feff6bc 100644
--- a/src/art/guided_completion.py
+++ b/src/art/guided_completion.py
@@ -19,11 +19,11 @@ def freeze_tool_schema(tool: dict, fixed_args: dict) -> ChatCompletionToolParam:
     Each field is cast to typing.Literal[value] so Pydantic emits an
     enum-of-one in the JSON schema, which vLLM's `guided_json` accepts.
     """
-    fields = {k: (Literal[v], ...) for k, v in fixed_args.items()}
+    fields = {k: (Literal[v], ...) for k, v in fixed_args.items()}  # ty:ignore[invalid-type-form]
     FrozenModel = create_model(
         f"{tool['function']['name'].title()}FrozenArgs",
-        **fields,  # type: ignore
-    )
+        **fields,
+    )  # ty:ignore[no-matching-overload]
 
     locked = deepcopy(tool)
     locked["function"]["parameters"] = FrozenModel.model_json_schema()
@@ -71,7 +71,7 @@ def get_guided_completion_params(
         }
         chosen_tool = next(t for t in base_tools if t["function"]["name"] == tool_name)
         tool_params = [
-            freeze_tool_schema(chosen_tool, json.loads(tool_call.function.arguments))  # type: ignore
+            freeze_tool_schema(chosen_tool, json.loads(tool_call.function.arguments))
         ]
     else:
         content = completion.choices[0].message.content
diff --git a/src/art/langgraph/llm_wrapper.py b/src/art/langgraph/llm_wrapper.py
index 11f2bbee6..36b5314b3 100644
--- a/src/art/langgraph/llm_wrapper.py
+++ b/src/art/langgraph/llm_wrapper.py
@@ -118,9 +118,9 @@ def init_chat_model(
     config = CURRENT_CONFIG.get()
     return LoggingLLM(
         ChatOpenAI(
-            base_url=config["base_url"],
-            api_key=config["api_key"],
-            model=config["model"],
+            base_url=config["base_url"],  # ty:ignore[unknown-argument]
+            api_key=config["api_key"],  # ty:ignore[unknown-argument]
+            model=config["model"],  # ty:ignore[unknown-argument]
             temperature=1.0,
         ),
         config["logger"],
@@ -222,17 +222,17 @@ def with_config(
                 self.llm,
                 "bound",
                 ChatOpenAI(
-                    base_url=art_config["base_url"],
-                    api_key=art_config["api_key"],
-                    model=art_config["model"],
+                    base_url=art_config["base_url"],  # ty:ignore[unknown-argument]
+                    api_key=art_config["api_key"],  # ty:ignore[unknown-argument]
+                    model=art_config["model"],  # ty:ignore[unknown-argument]
                     temperature=1.0,
                 ),
             )
         else:
             self.llm = ChatOpenAI(
-                base_url=art_config["base_url"],
-                api_key=art_config["api_key"],
-                model=art_config["model"],
+                base_url=art_config["base_url"],  # ty:ignore[unknown-argument]
+                api_key=art_config["api_key"],  # ty:ignore[unknown-argument]
+                model=art_config["model"],  # ty:ignore[unknown-argument]
                 temperature=1.0,
             )
 
diff --git a/src/art/local/backend.py b/src/art/local/backend.py
index c017ad5f9..19f26afbe 100644
--- a/src/art/local/backend.py
+++ b/src/art/local/backend.py
@@ -215,7 +215,7 @@ def _get_packed_tensors(
         packed_tensors = packed_tensors_from_tokenized_results(
             tokenized_results,
             sequence_length,
-            pad_token_id=tokenizer.eos_token_id,  # type: ignore
+            pad_token_id=tokenizer.eos_token_id,
             advantage_balance=advantage_balance,
         )
         if (
@@ -360,7 +360,7 @@ def _trajectory_log(self, trajectory: Trajectory) -> str:
             if isinstance(message_or_choice, dict):
                 message = message_or_choice
             else:
-                message = cast(Message, message_or_choice.message.model_dump())
+                message = cast(Message, message_or_choice.message.model_dump())  # ty:ignore[possibly-missing-attribute]
             formatted_messages.append(format_message(message))
         return header + "\n".join(formatted_messages)
 
diff --git a/src/art/loss.py b/src/art/loss.py
index dda539585..79154fde9 100644
--- a/src/art/loss.py
+++ b/src/art/loss.py
@@ -106,7 +106,7 @@ def loss_fn(
         )
     if upper_bound := experimental_config.get("truncated_importance_sampling", None):
         if "original_logprobs" in inputs:
-            original_logprobs = shift_tensor(inputs["original_logprobs"], 0.0)
+            original_logprobs = shift_tensor(inputs["original_logprobs"], 0.0)  # ty:ignore[invalid-key]
             original_logprobs = torch.where(
                 torch.isnan(original_logprobs),
                 new_logprobs.detach(),
diff --git a/src/art/mcp/generate_scenarios.py b/src/art/mcp/generate_scenarios.py
index df92ea3c4..6932d9c2e 100644
--- a/src/art/mcp/generate_scenarios.py
+++ b/src/art/mcp/generate_scenarios.py
@@ -75,13 +75,13 @@ async def generate_scenarios(
         # Assume it's already a list of dictionaries
         tools_info = [
             {
-                "name": tool.get("name", "")
+                "name": tool.get("name", "")  # ty:ignore[no-matching-overload]
                 if isinstance(tool, dict)
                 else getattr(tool, "name", ""),
-                "description": tool.get("description", "")
+                "description": tool.get("description", "")  # ty:ignore[no-matching-overload]
                 if isinstance(tool, dict)
                 else getattr(tool, "description", ""),
-                "parameters": tool.get("parameters", {})
+                "parameters": tool.get("parameters", {})  # ty:ignore[no-matching-overload]
                 if isinstance(tool, dict)
                 else getattr(tool, "parameters", {}),
             }
diff --git a/src/art/model.py b/src/art/model.py
index 1afd407e2..2fc38640b 100644
--- a/src/art/model.py
+++ b/src/art/model.py
@@ -153,7 +153,7 @@ def __new__(  # pyright: ignore[reportInconsistentOverload]
         *args,
         **kwargs,
     ) -> "Model[ModelConfig, StateType]":
-        return super().__new__(cls)  # type: ignore[return-value]
+        return super().__new__(cls)
 
     def safe_model_dump(self, *args, **kwargs) -> dict:
         """
@@ -174,7 +174,7 @@ def backend(self) -> "Backend":
     async def register(self, backend: "Backend") -> None:
         if self.config is not None:
             try:
-                self.config.model_dump_json()
+                self.config.model_dump_json()  # ty:ignore[invalid-argument-type, possibly-missing-attribute]
             except Exception as e:
                 raise ValueError(
                     "The model config cannot be serialized to JSON. Please ensure that all fields are JSON serializable and try again."
@@ -500,7 +500,7 @@ def __init__(
             entity=entity,
             id=id,
             config=config,
-            base_model=base_model,  # type: ignore
+            base_model=base_model,
             base_path=base_path,
             report_metrics=report_metrics,
             **kwargs,
@@ -544,7 +544,7 @@ def __new__(  # pyright: ignore[reportInconsistentOverload]
         *args,
         **kwargs,
     ) -> "TrainableModel[ModelConfig, StateType]":
-        return super().__new__(cls)  # type: ignore
+        return super().__new__(cls)
 
     def model_dump(self, *args, **kwargs) -> dict:
         data = super().model_dump(*args, **kwargs)
@@ -649,7 +649,7 @@ async def train(
             stacklevel=2,
         )
         groups_list = list(trajectory_groups)
-        _config = _config or {}
+        _config = _config or {}  # ty:ignore[invalid-assignment]
 
         # 1. Log trajectories first (frontend handles this now)
         await self.log(groups_list, split="train")
@@ -657,7 +657,11 @@ async def train(
         # 2. Train (backend no longer logs internally)
         training_metrics: list[dict[str, float]] = []
         async for metrics in self.backend()._train_model(
-            self, groups_list, config, _config, verbose
+            self,
+            groups_list,
+            config,
+            _config,  # ty:ignore[invalid-argument-type]
+            verbose,
         ):
             training_metrics.append(metrics)
 
diff --git a/src/art/preprocessing/inputs.py b/src/art/preprocessing/inputs.py
index 78d9710bb..996c15f20 100644
--- a/src/art/preprocessing/inputs.py
+++ b/src/art/preprocessing/inputs.py
@@ -24,7 +24,7 @@ def create_train_inputs(
     warmup: bool,
 ) -> TrainInputs:
     """Create TrainInputs for a single batch offset."""
-    return TrainInputs(
+    return TrainInputs(  # ty:ignore[missing-typed-dict-key]
         **{
             k: (
                 v[offset : offset + 1, :1024]
diff --git a/src/art/preprocessing/pack.py b/src/art/preprocessing/pack.py
index 0e99176af..e943a4306 100644
--- a/src/art/preprocessing/pack.py
+++ b/src/art/preprocessing/pack.py
@@ -194,8 +194,8 @@ def packed_tensors_from_dir(**kwargs: Unpack[DiskPackedTensors]) -> PackedTensor
             "weights": torch.float32,
         }.items()
     }
-    _add_tensor_list(packed_tensors, kwargs, "pixel_values", torch.float32)
-    _add_tensor_list(packed_tensors, kwargs, "image_grid_thw", torch.long)
+    _add_tensor_list(packed_tensors, kwargs, "pixel_values", torch.float32)  # ty:ignore[invalid-argument-type]
+    _add_tensor_list(packed_tensors, kwargs, "image_grid_thw", torch.long)  # ty:ignore[invalid-argument-type]
     return cast(PackedTensors, packed_tensors)
 
 
@@ -237,7 +237,7 @@ def packed_tensors_to_dir(tensors: PackedTensors, dir: str) -> DiskPackedTensors
         if isinstance(tensor, list):
             for i, t in enumerate(tensor):
                 if t is not None:
-                    t.copy_(tensors[key][i])
+                    t.copy_(tensors[key][i])  # ty:ignore[invalid-key, unresolved-attribute]
         else:
             tensor.copy_(tensors[key])  # type: ignore
     return disk_packed_tensors
@@ -288,7 +288,7 @@ def plot_packed_tensors(
             tensor.numpy(),
             cmap="viridis",
             cbar_kws={"label": label},
-            xticklabels=False,  # type: ignore
+            xticklabels=False,
         )
         plt.title(title)
         plt.xlabel("Sequence Position")
diff --git a/src/art/preprocessing/tokenize.py b/src/art/preprocessing/tokenize.py
index 1b4230960..f146e5ca0 100644
--- a/src/art/preprocessing/tokenize.py
+++ b/src/art/preprocessing/tokenize.py
@@ -165,7 +165,7 @@ def tokenize_trajectory(
         ):
             last_assistant_index = i
         elif not isinstance(message, dict) and (
-            message.logprobs or allow_training_without_logprobs
+            message.logprobs or allow_training_without_logprobs  # ty:ignore[possibly-missing-attribute]
         ):
             last_assistant_index = i
     # If there are no trainable assistant messages, return None
@@ -182,7 +182,7 @@ def tokenize_trajectory(
         str,
         tokenizer.apply_chat_template(
             cast(list[dict], messages),
-            tools=tools,  # type: ignore
+            tools=tools,
             continue_final_message=True,
             tokenize=False,
         ),
@@ -191,7 +191,7 @@ def tokenize_trajectory(
         list[int],
         tokenizer.apply_chat_template(
             cast(list[dict], messages),
-            tools=tools,  # type: ignore
+            tools=tools,
             continue_final_message=True,
         ),
     )
@@ -214,8 +214,8 @@ def tokenize_trajectory(
                     "role": "assistant",
                     "content": sentinal_token,
                     **(
-                        {"tool_calls": message.get("tool_calls")}  # type: ignore[call-overload]
-                        if message.get("tool_calls")  # type: ignore[call-overload]
+                        {"tool_calls": message.get("tool_calls")}
+                        if message.get("tool_calls")
                         else {}
                     ),
                 }
@@ -226,7 +226,7 @@ def tokenize_trajectory(
         list[int],
         tokenizer.apply_chat_template(
             cast(list[dict], token_template_messages),
-            tools=tools,  # type: ignore
+            tools=tools,
             continue_final_message=True,
         ),
     )
@@ -238,7 +238,7 @@ def tokenize_trajectory(
                 continue
             if not allow_training_without_logprobs:
                 continue
-        elif message.logprobs is None and not allow_training_without_logprobs:
+        elif message.logprobs is None and not allow_training_without_logprobs:  # ty:ignore[possibly-missing-attribute]
             continue
         start = token_ids.index(sentinal_token_id)
         end = start + 1
@@ -263,12 +263,12 @@ def tokenize_trajectory(
             assistant_mask[start:end] = [1] * len(content_token_ids)
         else:
             choice = message
-            assert choice.logprobs or allow_training_without_logprobs, (
+            assert choice.logprobs or allow_training_without_logprobs, (  # ty:ignore[possibly-missing-attribute]
                 "Chat completion choices must have logprobs"
             )
-            if not choice.logprobs:
+            if not choice.logprobs:  # ty:ignore[possibly-missing-attribute]
                 continue
-            token_logprobs = choice.logprobs.content or choice.logprobs.refusal or []
+            token_logprobs = choice.logprobs.content or choice.logprobs.refusal or []  # ty:ignore[possibly-missing-attribute]
             if (
                 bytes(token_logprobs[0].bytes or []).decode("utf-8")
                 == "<think>"
@@ -281,14 +281,14 @@ def tokenize_trajectory(
                     for token_logprob in token_logprobs
                 )
             except (IndexError, ValueError):
-                token_ids[start:end] = [  # type: ignore
+                token_ids[start:end] = [
                     token_id if token_id is not None else tokenizer.eos_token_id
                     for token_id in tokenizer.convert_tokens_to_ids(
                         [
                             token_logprob.token or tokenizer.eos_token
                             for token_logprob in token_logprobs
                         ]
-                    )  # type: ignore
+                    )
                 ]
             logprobs[start:end] = (
                 token_logprob.logprob for token_logprob in token_logprobs
@@ -313,7 +313,7 @@ def tokenize_trajectory(
         image_token_id = cast(
             int,
             getattr(image_processor, "image_token_id", None)
-            or tokenizer.convert_tokens_to_ids(  # type: ignore
+            or tokenizer.convert_tokens_to_ids(
                 getattr(image_processor, "image_token", "<|image_pad|>")
             ),
         )
diff --git a/src/art/rewards/ruler.py b/src/art/rewards/ruler.py
index 2ea333124..84d41f4de 100644
--- a/src/art/rewards/ruler.py
+++ b/src/art/rewards/ruler.py
@@ -186,7 +186,7 @@ async def ruler(
     first_choice = response.choices[0]
 
     if debug:
-        raw_content = first_choice.message.content or "{}"  # type: ignore[attr-defined]
+        raw_content = first_choice.message.content or "{}"
         try:
             print("\n[RULER] Pretty-printed LLM choice JSON:")
             print(json.loads(raw_content))
@@ -194,7 +194,7 @@ async def ruler(
             print(f"[RULER] Could not parse choice content as JSON: {e}")
             print(f"[RULER] Raw choice content: {raw_content}")
 
-    content = first_choice.message.content or "{}"  # type: ignore[attr-defined]
+    content = first_choice.message.content or "{}"
     parsed = Response.model_validate_json(content)
 
     # If all trajectories were identical, we only sent one to the judge
diff --git a/src/art/serverless/backend.py b/src/art/serverless/backend.py
index 53e427aef..f431d4b17 100644
--- a/src/art/serverless/backend.py
+++ b/src/art/serverless/backend.py
@@ -25,7 +25,7 @@ def __init__(
         self._client = client
 
     async def close(self) -> None:
-        await self._client.close()
+        await self._client.close()  # ty:ignore[possibly-missing-attribute]
 
     async def register(
         self,
@@ -44,7 +44,7 @@ async def register(
                 "Registering a non-trainable model with the Serverless backend is not supported."
             )
             return
-        client_model = await self._client.models.create(
+        client_model = await self._client.models.create(  # ty:ignore[possibly-missing-attribute]
             entity=model.entity,
             project=model.project,
             name=model.name,
@@ -72,7 +72,7 @@ async def delete(
             )
             return
         assert model.id is not None, "Model ID is required"
-        await self._client.models.delete(model_id=model.id)
+        await self._client.models.delete(model_id=model.id)  # ty:ignore[possibly-missing-attribute]
 
     def _model_inference_name(self, model: "Model", step: int | None = None) -> str:
         """Return the inference name for a model checkpoint.
@@ -92,7 +92,7 @@ def _model_inference_name(self, model: "Model", step: int | None = None) -> str:
     async def _get_step(self, model: "Model") -> int:
         if model.trainable:
             assert model.id is not None, "Model ID is required"
-            async for checkpoint in self._client.models.checkpoints.list(
+            async for checkpoint in self._client.models.checkpoints.list(  # ty:ignore[possibly-missing-attribute]
                 limit=1, order="desc", model_id=model.id
             ):
                 return checkpoint.step
@@ -108,11 +108,11 @@ async def _delete_checkpoint_files(
         assert model.id is not None, "Model ID is required"
         # Get all checkpoint steps
         all_steps: list[int] = []
-        async for checkpoint in self._client.models.checkpoints.list(model_id=model.id):
+        async for checkpoint in self._client.models.checkpoints.list(model_id=model.id):  # ty:ignore[possibly-missing-attribute]
             all_steps.append(checkpoint.step)
         # Delete all steps not in steps_to_keep
         if steps_to_delete := [step for step in all_steps if step not in steps_to_keep]:
-            await self._client.models.checkpoints.delete(
+            await self._client.models.checkpoints.delete(  # ty:ignore[possibly-missing-attribute]
                 model_id=model.id,
                 steps=steps_to_delete,
             )
@@ -122,7 +122,7 @@ async def _prepare_backend_for_training(
         model: "TrainableModel",
         config: dev.OpenAIServerConfig | None,
     ) -> tuple[str, str]:
-        return str(self._base_url), self._client.api_key
+        return str(self._base_url), self._client.api_key  # ty:ignore[possibly-missing-attribute]
 
     # Note: _log() method has been moved to the Model class (frontend)
     # Trajectories are now saved locally by the Model.log() method
@@ -256,7 +256,7 @@ async def _train_model(
         verbose: bool = False,
     ) -> AsyncIterator[dict[str, float]]:
         assert model.id is not None, "Model ID is required"
-        training_job = await self._client.training_jobs.create(
+        training_job = await self._client.training_jobs.create(  # ty:ignore[possibly-missing-attribute]
             model_id=model.id,
             trajectory_groups=trajectory_groups,
             experimental_config=ExperimentalTrainingConfig(
@@ -280,7 +280,7 @@ async def _train_model(
         pbar: tqdm.tqdm | None = None
         while True:
             await asyncio.sleep(1)
-            async for event in self._client.training_jobs.events.list(
+            async for event in self._client.training_jobs.events.list(  # ty:ignore[possibly-missing-attribute]
                 training_job_id=training_job.id, after=after or NOT_GIVEN
             ):
                 if event.type == "gradient_step":
@@ -336,7 +336,7 @@ async def _experimental_pull_model_checkpoint(
         assert model.id is not None, "Model ID is required"
 
         # If entity is not set, use the user's default entity from W&B
-        api = wandb.Api(api_key=self._client.api_key)
+        api = wandb.Api(api_key=self._client.api_key)  # ty:ignore[possibly-missing-attribute]
         if model.entity is None:
             model.entity = api.default_entity
             if verbose:
@@ -346,7 +346,7 @@ async def _experimental_pull_model_checkpoint(
         resolved_step: int
         if step is None or step == "latest":
             # Get latest checkpoint from API
-            async for checkpoint in self._client.models.checkpoints.list(
+            async for checkpoint in self._client.models.checkpoints.list(  # ty:ignore[possibly-missing-attribute]
                 limit=1, order="desc", model_id=model.id
             ):
                 resolved_step = checkpoint.step
diff --git a/src/art/serverless/client.py b/src/art/serverless/client.py
index b28e9df9e..076418f39 100644
--- a/src/art/serverless/client.py
+++ b/src/art/serverless/client.py
@@ -132,7 +132,7 @@ async def delete(self, *, model_id: str) -> None:
 
     @cached_property
     def checkpoints(self) -> "Checkpoints":
-        return Checkpoints(cast(AsyncOpenAI, self._client))
+        return Checkpoints(cast(AsyncOpenAI, self._client))  # ty:ignore[redundant-cast]
 
 
 class Checkpoints(AsyncAPIResource):
@@ -193,7 +193,7 @@ async def create(
 
     @cached_property
     def events(self) -> "TrainingJobEvents":
-        return TrainingJobEvents(cast(AsyncOpenAI, self._client))
+        return TrainingJobEvents(cast(AsyncOpenAI, self._client))  # ty:ignore[redundant-cast]
 
 
 class TrainingJobEvents(AsyncAPIResource):
@@ -241,7 +241,7 @@ def __init__(
         )
 
     @override
-    async def request(  # type: ignore[reportIncompatibleMethodOverride]
+    async def request(
         self,
         cast_to: Type[ResponseT],
         options: FinalRequestOptions,
diff --git a/src/art/tinker/server.py b/src/art/tinker/server.py
index 9781880f5..6be096ad4 100644
--- a/src/art/tinker/server.py
+++ b/src/art/tinker/server.py
@@ -31,7 +31,7 @@ def _patched_parse_tool_call(
     return _parse_tool_call(self, tool_call_str.replace('"arguments": ', '"args": '))
 
 
-renderers.Qwen3InstructRenderer._parse_tool_call = _patched_parse_tool_call
+renderers.Qwen3InstructRenderer._parse_tool_call = _patched_parse_tool_call  # ty:ignore[invalid-assignment]
 
 
 @dataclass
@@ -102,7 +102,7 @@ async def chat_completions(
                     list(body["messages"]),  # type: ignore
                     tools=body.get("tools"),  # type: ignore
                     add_generation_prompt=True,
-                )
+                )  # ty:ignore[invalid-argument-type]
             )
             try:
                 sample_response = await sampler_client.sample_async(
@@ -122,7 +122,7 @@ async def chat_completions(
             except tinker.APIStatusError as e:
                 error_body = e.body
                 if isinstance(error_body, dict) and "detail" in error_body:
-                    detail = error_body["detail"]
+                    detail = error_body["detail"]  # ty:ignore[invalid-argument-type]
                 elif error_body is not None:
                     detail = error_body
                 else:
diff --git a/src/art/trajectories.py b/src/art/trajectories.py
index 69ab17db9..f74fb3039 100644
--- a/src/art/trajectories.py
+++ b/src/art/trajectories.py
@@ -87,9 +87,9 @@ def for_logging(self) -> dict[str, Any]:
         for message_or_choice in self.messages_and_choices:
             trainable = isinstance(message_or_choice, Choice)
             message = (
-                message_or_choice.message.to_dict() if trainable else message_or_choice
+                message_or_choice.message.to_dict() if trainable else message_or_choice  # ty:ignore[possibly-missing-attribute]
             )
-            loggable_dict["messages"].append({**message, "trainable": trainable})
+            loggable_dict["messages"].append({**message, "trainable": trainable})  # ty:ignore[invalid-argument-type, possibly-missing-attribute]
         return loggable_dict
 
 
@@ -112,7 +112,7 @@ def get_messages(messages_and_choices: MessagesAndChoices) -> Messages:
                         }
                         if tool_calls
                         else {}
-                    ),  # type: ignore
+                    ),
                 }
             )
         else:
diff --git a/src/art/transformers/patches.py b/src/art/transformers/patches.py
index 6b16424fe..97e09f6c8 100644
--- a/src/art/transformers/patches.py
+++ b/src/art/transformers/patches.py
@@ -34,4 +34,4 @@ def _patched_preprocess_mask_arguments(
 
 
 def patch_preprocess_mask_arguments() -> None:
-    masking_utils._preprocess_mask_arguments = _patched_preprocess_mask_arguments
+    masking_utils._preprocess_mask_arguments = _patched_preprocess_mask_arguments  # ty:ignore[invalid-assignment]
diff --git a/src/art/unsloth/service.py b/src/art/unsloth/service.py
index 18c1b9027..d42941357 100644
--- a/src/art/unsloth/service.py
+++ b/src/art/unsloth/service.py
@@ -57,7 +57,7 @@ def precalculate_new_logprobs(
         [
             trainer.compute_loss(
                 peft_model,
-                TrainInputs(
+                TrainInputs(  # ty:ignore[missing-typed-dict-key]
                     **{
                         k: v[_offset : _offset + 1]
                         for k, v in packed_tensors.items()
@@ -70,7 +70,7 @@ def precalculate_new_logprobs(
                     config=config,
                     _config=_config,
                     return_new_logprobs=True,
-                ),  # type: ignore
+                ),
             )
             for _offset in range(0, packed_tensors["tokens"].shape[0])
         ]
@@ -471,7 +471,7 @@ def _state(self) -> UnslothState:
         trainer = GRPOTrainer(
             model=peft_model,  # type: ignore
             reward_funcs=[],
-            args=GRPOConfig(**self.config.get("trainer_args", {})),  # type: ignore
+            args=GRPOConfig(**self.config.get("trainer_args", {})),
             train_dataset=Dataset.from_list([data for _ in range(10_000_000)]),
             processing_class=tokenizer,
         )
@@ -513,7 +513,7 @@ def llm(self) -> asyncio.Task[AsyncLLM]:
         # Remove boolean flags that vLLM's argparse doesn't accept as =False
         for key in ["enable_log_requests", "disable_log_requests"]:
             engine_args.pop(key, None)
-        return asyncio.create_task(get_llm(AsyncEngineArgs(**engine_args)))
+        return asyncio.create_task(get_llm(AsyncEngineArgs(**engine_args)))  # ty:ignore[invalid-argument-type]
 
 
 # ============================================================================
@@ -576,7 +576,7 @@ def do_sleep(*, level: int) -> None:
                 pin_memory=is_pin_memory_available(),
             )
             cpu_ptr = cpu_backup_tensor.data_ptr()
-            libcudart.cudaMemcpy(
+            libcudart.cudaMemcpy(  # ty:ignore[possibly-missing-attribute]
                 ctypes.c_void_p(cpu_ptr), ctypes.c_void_p(ptr), size_in_bytes
             )
             data.cpu_backup_tensor = cpu_backup_tensor
@@ -612,7 +612,7 @@ def do_wake_up() -> None:
             cpu_backup_tensor = data.cpu_backup_tensor
             size_in_bytes = cpu_backup_tensor.numel() * cpu_backup_tensor.element_size()
             cpu_ptr = cpu_backup_tensor.data_ptr()
-            libcudart.cudaMemcpy(
+            libcudart.cudaMemcpy(  # ty:ignore[possibly-missing-attribute]
                 ctypes.c_void_p(ptr),
                 ctypes.c_void_p(cpu_ptr),
                 size_in_bytes,
diff --git a/src/art/unsloth/train.py b/src/art/unsloth/train.py
index fba02d22e..e5d229537 100644
--- a/src/art/unsloth/train.py
+++ b/src/art/unsloth/train.py
@@ -27,7 +27,7 @@ async def train(
     _compute_loss = trainer.compute_loss
     _log = trainer.log
     trainer.compute_loss = get_compute_loss_fn(trainer)
-    trainer.log = get_log_fn(trainer, results_queue)
+    trainer.log = get_log_fn(trainer, results_queue)  # ty:ignore[invalid-assignment]
     # Ensure we have a metrics container in the expected format
     try:
         is_dict = isinstance(getattr(trainer, "_metrics", None), dict)
@@ -40,7 +40,7 @@ async def train(
         trainer.train()
     finally:
         trainer.compute_loss = _compute_loss
-        trainer.log = _log
+        trainer.log = _log  # ty:ignore[invalid-assignment]
 
 
 def get_compute_loss_fn(trainer: "GRPOTrainer") -> Callable[..., torch.Tensor]:
@@ -82,7 +82,7 @@ def compute_loss(
         inputs = {
             key: tensor.to(trainer.accelerator.device)  # type: ignore
             for key, tensor in inputs.items()
-        }
+        }  # ty:ignore[invalid-assignment]
 
         accelerate_mixed_precision = os.environ.get("ACCELERATE_MIXED_PRECISION")
         force_float32 = os.environ.get("UNSLOTH_FORCE_FLOAT32")
@@ -120,9 +120,9 @@ def compute_loss(
         os.environ["UNSLOTH_RETURN_HIDDEN_STATES"] = "1"
         forward_kwargs = {}
         if "pixel_values" in inputs:
-            forward_kwargs["pixel_values"] = inputs["pixel_values"]  # type: ignore
+            forward_kwargs["pixel_values"] = inputs["pixel_values"]
         if "image_grid_thw" in inputs:
-            forward_kwargs["image_grid_thw"] = inputs["image_grid_thw"]  # type: ignore
+            forward_kwargs["image_grid_thw"] = inputs["image_grid_thw"]
         new_logprobs, entropies = calculate_logprobs(
             dtype_for_autocasting,
             trainer,
@@ -167,10 +167,10 @@ def compute_loss(
         trainer._metrics["train"]["learning_rate"].append(config.learning_rate)
         trainer._metrics["train"]["policy_loss"].append(loss.mean_policy_loss.item())
         if loss.mean_entropy is not None:
-            trainer._metrics["train"]["entropy"].append(loss.mean_entropy.item())  # type: ignore
+            trainer._metrics["train"]["entropy"].append(loss.mean_entropy.item())
         if config.beta > 0.0:
             trainer._metrics["train"]["kl_div"].append(loss.mean_kl.item())
-        return loss.mean_policy_loss + config.beta * loss.mean_kl  # type: ignore
+        return loss.mean_policy_loss + config.beta * loss.mean_kl
 
     return compute_loss
 
diff --git a/src/art/utils/benchmark_rollout.py b/src/art/utils/benchmark_rollout.py
index c8ef57d70..4ff1cfc0e 100644
--- a/src/art/utils/benchmark_rollout.py
+++ b/src/art/utils/benchmark_rollout.py
@@ -11,7 +11,7 @@ async def benchmark_rollout(
     rollout: Callable[[str, int, bool], Coroutine[Any, Any, Trajectory]],
 ) -> float:
     trajectory_groups = await art.gather_trajectory_groups(
-        [TrajectoryGroup(rollout(model, i, False) for i in range(num_rollouts))],
+        [TrajectoryGroup(rollout(model, i, False) for i in range(num_rollouts))],  # ty:ignore[invalid-argument-type]
         pbar_desc="Benchmarking rollout",
     )
 
diff --git a/src/art/utils/benchmarking/charts/training_progress_chart.py b/src/art/utils/benchmarking/charts/training_progress_chart.py
index 5a41bce1e..1f03507c6 100644
--- a/src/art/utils/benchmarking/charts/training_progress_chart.py
+++ b/src/art/utils/benchmarking/charts/training_progress_chart.py
@@ -187,7 +187,7 @@ def training_progress_chart(
 
     ordered_for_palette = trained_first + comparison_last
     palette = sns.color_palette(n_colors=len(ordered_for_palette))
-    model_colors = {m: c for m, c in zip(ordered_for_palette, palette)}  # type: ignore
+    model_colors = {m: c for m, c in zip(ordered_for_palette, palette)}
 
     # Track scores of comparison models to adjust linestyle for overlaps
     plotted_comparison_scores: set[float] = set()
diff --git a/src/art/utils/benchmarking/load_trajectories.py b/src/art/utils/benchmarking/load_trajectories.py
index 961e2c12d..2b494ffe4 100644
--- a/src/art/utils/benchmarking/load_trajectories.py
+++ b/src/art/utils/benchmarking/load_trajectories.py
@@ -239,7 +239,7 @@ async def load_trajectories(
                 }
                 if msg_dict.get("tool_calls"):
                     try:
-                        processed_msg["tool_calls"] = json.loads(msg_dict["tool_calls"])
+                        processed_msg["tool_calls"] = json.loads(msg_dict["tool_calls"])  # ty:ignore[invalid-argument-type]
                     except (json.JSONDecodeError, TypeError):
                         pass
 
diff --git a/src/art/utils/format_message.py b/src/art/utils/format_message.py
index 874eb6ec9..fd3fe20dc 100644
--- a/src/art/utils/format_message.py
+++ b/src/art/utils/format_message.py
@@ -14,7 +14,7 @@ def format_message(message: Message) -> str:
     # Format any tool calls
     tool_calls_text = "\n" if content else ""
     tool_calls_text += "\n".join(
-        f"{tool_call['function']['name']}({tool_call['function']['arguments']})"
+        f"{tool_call['function']['name']}({tool_call['function']['arguments']})"  # ty:ignore[invalid-key]
         for tool_call in message.get("tool_calls") or []
         if "function" in tool_call
     )
diff --git a/src/art/utils/litellm.py b/src/art/utils/litellm.py
index 481be5fbb..d65178d24 100644
--- a/src/art/utils/litellm.py
+++ b/src/art/utils/litellm.py
@@ -40,7 +40,7 @@ def convert_litellm_choice_to_openai(
             openai_tool_calls.append(
                 ChatCompletionMessageToolCall(
                     id=tool_call.id,
-                    type=tool_call.type,
+                    type=tool_call.type,  # ty:ignore[invalid-argument-type]
                     function=Function(
                         name=tool_call.function.name,
                         arguments=tool_call.function.arguments,
diff --git a/src/art/utils/old_benchmarking/generate_line_graphs.py b/src/art/utils/old_benchmarking/generate_line_graphs.py
index a0612c19d..182c354b1 100644
--- a/src/art/utils/old_benchmarking/generate_line_graphs.py
+++ b/src/art/utils/old_benchmarking/generate_line_graphs.py
@@ -56,7 +56,7 @@ def has_all_recorded(model):
         last_x_global: float | None = None
         for model in line_graph_models:
             if x_axis_metric == "time":
-                from matplotlib import dates as mdates  # type: ignore
+                from matplotlib import dates as mdates
 
                 x_values_float = [
                     float(mdates.date2num(step.recorded_at or datetime.min))
diff --git a/src/art/utils/retry.py b/src/art/utils/retry.py
index 51c22c548..975e53e07 100644
--- a/src/art/utils/retry.py
+++ b/src/art/utils/retry.py
@@ -61,7 +61,7 @@ async def async_wrapper(*args: P.args, **kwargs: P.kwargs) -> Any:
                             on_retry(e, attempt)
                         else:
                             logging.warning(
-                                f"Retry {attempt}/{max_attempts} for {func.__name__} "
+                                f"Retry {attempt}/{max_attempts} for {func.__name__} "  # ty:ignore[unresolved-attribute]
                                 f"after error: {str(e)}"
                             )
 
@@ -92,7 +92,7 @@ def sync_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
                             on_retry(e, attempt)
                         else:
                             logging.warning(
-                                f"Retry {attempt}/{max_attempts} for {func.__name__} "
+                                f"Retry {attempt}/{max_attempts} for {func.__name__} "  # ty:ignore[unresolved-attribute]
                                 f"after error: {str(e)}"
                             )
 
diff --git a/src/art/utils/trajectory_migration.py b/src/art/utils/trajectory_migration.py
index 3b4a14a8a..2cdf200cf 100644
--- a/src/art/utils/trajectory_migration.py
+++ b/src/art/utils/trajectory_migration.py
@@ -81,17 +81,17 @@ def message_or_choice_to_dict(message_or_choice: MessageOrChoice) -> dict[str, A
     item_dict = (
         message_or_choice
         if isinstance(message_or_choice, dict)
-        else message_or_choice.to_dict()
+        else message_or_choice.to_dict()  # ty:ignore[possibly-missing-attribute]
     )
 
     if "logprobs" in item_dict:
         # item is a choice with logprobs, remove the logprobs
-        item_dict.pop("logprobs")
+        item_dict.pop("logprobs")  # ty:ignore[invalid-argument-type]
 
     if "content" in item_dict and isinstance(item_dict["content"], Iterator):
         item_dict["content"] = list(item_dict["content"])  # type: ignore
 
-    return dict(item_dict)
+    return dict(item_dict)  # ty:ignore[no-matching-overload]
 
 
 def deserialize_trajectory_groups(serialized: str) -> list[TrajectoryGroup]:
diff --git a/src/art/vllm/engine.py b/src/art/vllm/engine.py
index 46843d003..c8da5c55b 100644
--- a/src/art/vllm/engine.py
+++ b/src/art/vllm/engine.py
@@ -14,7 +14,7 @@
 from vllm.v1.worker.gpu_worker import Worker
 
 
-async def get_llm(args: vllm.AsyncEngineArgs) -> AsyncLLM:
+async def get_llm(args: vllm.AsyncEngineArgs) -> AsyncLLM:  # ty:ignore[unresolved-attribute]
     """
     Create an AsyncLLM engine with model download and patches applied.
 
diff --git a/src/art/vllm/patches.py b/src/art/vllm/patches.py
index 54d2eba89..6bd28bf9f 100644
--- a/src/art/vllm/patches.py
+++ b/src/art/vllm/patches.py
@@ -11,12 +11,12 @@ def subclass_chat_completion_request() -> None:
 
     class ChatCompletionRequest(vllm.entrypoints.openai.protocol.ChatCompletionRequest):
         def __init__(self, *args: object, **kwargs: object) -> None:
-            super().__init__(*args, **kwargs)
+            super().__init__(*args, **kwargs)  # ty:ignore[invalid-argument-type]
             self.logprobs = True
             if self.top_logprobs is None:
                 self.top_logprobs = 0
 
-    vllm.entrypoints.openai.protocol.ChatCompletionRequest = ChatCompletionRequest
+    vllm.entrypoints.openai.protocol.ChatCompletionRequest = ChatCompletionRequest  # ty:ignore[invalid-assignment]
 
 
 def patch_listen_for_disconnect() -> None:
@@ -32,7 +32,7 @@ async def patched_listen_for_disconnect(request):
     # Replace the original function
     import vllm.entrypoints.utils
 
-    vllm.entrypoints.utils.listen_for_disconnect = patched_listen_for_disconnect
+    vllm.entrypoints.utils.listen_for_disconnect = patched_listen_for_disconnect  # ty:ignore[invalid-assignment]
 
 
 def patch_tool_parser_manager() -> None:
@@ -54,7 +54,7 @@ def patch(
         ) -> Any:
             return original(*args, **kwargs) or DeltaMessage()
 
-        tool_parser_class.extract_tool_calls_streaming = patch
+        tool_parser_class.extract_tool_calls_streaming = patch  # ty:ignore[invalid-assignment]
         return tool_parser_class
 
-    ToolParserManager.get_tool_parser = patched_get_tool_parser
+    ToolParserManager.get_tool_parser = patched_get_tool_parser  # ty:ignore[invalid-assignment]
diff --git a/src/art/vllm/server.py b/src/art/vllm/server.py
index 20f62db4d..0131eaae3 100644
--- a/src/art/vllm/server.py
+++ b/src/art/vllm/server.py
@@ -58,7 +58,7 @@ def _init(self, *args: Any, **kwargs: Any) -> None:
             global _openai_serving_models
             _openai_serving_models = self
 
-        serving_models.OpenAIServingModels.__init__ = _init
+        serving_models.OpenAIServingModels.__init__ = _init  # ty:ignore[invalid-assignment]
 
     patch_listen_for_disconnect()
     patch_tool_parser_manager()
@@ -86,7 +86,7 @@ async def _add_lora(lora_request) -> bool:
             _openai_serving_models.lora_requests[lora_request.lora_name] = lora_request
         return added
 
-    engine.add_lora = _add_lora
+    engine.add_lora = _add_lora  # ty:ignore[invalid-assignment]
 
     @asynccontextmanager
     async def build_async_engine_client(
diff --git a/tests/integration.py b/tests/integration.py
index 43a60c09a..3ed8070c5 100644
--- a/tests/integration.py
+++ b/tests/integration.py
@@ -331,7 +331,7 @@ def main() -> int:
             processed_config = config.copy()
 
         # Resolve path relative to this file
-        p = (here / processed_config["path"]).resolve()
+        p = (here / processed_config["path"]).resolve()  # ty:ignore[unsupported-operator]
         if not p.exists():
             print(f"Warning: notebook not found: {p}")
         processed_config["path"] = str(p)
diff --git a/tests/integration/test_multi_checkpoint_training.py b/tests/integration/test_multi_checkpoint_training.py
index 38c3c3c9f..9252f59a4 100644
--- a/tests/integration/test_multi_checkpoint_training.py
+++ b/tests/integration/test_multi_checkpoint_training.py
@@ -83,7 +83,7 @@ async def run_training_loop(
                     ]
                 )
                 for prompt in prompts
-            ]
+            ]  # ty:ignore[invalid-argument-type]
         )
         result = await backend.train(model, train_groups, learning_rate=1e-5)
         await model.log(
diff --git a/tests/test_backend_train_api.py b/tests/test_backend_train_api.py
index bc9551175..b24200ae1 100644
--- a/tests/test_backend_train_api.py
+++ b/tests/test_backend_train_api.py
@@ -78,7 +78,7 @@ async def main():
                         ]
                     )
                     for prompt in prompts
-                ]
+                ]  # ty:ignore[invalid-argument-type]
             )
             print(f"   ✓ Gathered {len(train_groups)} trajectory groups")
 
diff --git a/tests/unit/test_auto_trajectory.py b/tests/unit/test_auto_trajectory.py
index d70243bd7..fadd6ab98 100644
--- a/tests/unit/test_auto_trajectory.py
+++ b/tests/unit/test_auto_trajectory.py
@@ -181,7 +181,7 @@
                 }
             ],
         },
-    }
+    }  # ty:ignore[invalid-argument-type]
 )
 
 
@@ -288,9 +288,9 @@ async def say_hi() -> str | None:
     trajectory = await art.capture_auto_trajectory(say_hi())
     assert trajectory.messages_and_choices == [
         message,
-        Choice(**mock_response["choices"][0]),
+        Choice(**mock_response["choices"][0]),  # ty:ignore[invalid-argument-type, not-subscriptable]
         message,
-        Choice(**mock_response["choices"][0]),
+        Choice(**mock_response["choices"][0]),  # ty:ignore[invalid-argument-type, not-subscriptable]
     ]
     assert trajectory.tools == tools
     assert trajectory.additional_histories[0].messages_and_choices == [
@@ -305,12 +305,12 @@ async def say_hi() -> str | None:
             "role": "assistant",
         },
         message,
-        Choice(**mock_response["choices"][0]),
+        Choice(**mock_response["choices"][0]),  # ty:ignore[invalid-argument-type, not-subscriptable]
     ]
     assert trajectory.additional_histories[0].tools is None
     assert trajectory.additional_histories[1].messages_and_choices == [
         message,
-        Choice(**mock_response["choices"][0]),
+        Choice(**mock_response["choices"][0]),  # ty:ignore[invalid-argument-type, not-subscriptable]
     ]
     assert trajectory.additional_histories[1].tools == tools
     assert trajectory.additional_histories[2].messages_and_choices == [
@@ -387,9 +387,9 @@ async def say_hi() -> str | None:
     trajectory = await art.capture_auto_trajectory(say_hi())
     assert trajectory.messages_and_choices == [
         message,
-        Choice(**mock_response["choices"][0]),
+        Choice(**mock_response["choices"][0]),  # ty:ignore[invalid-argument-type, not-subscriptable]
         message,
-        Choice(**mock_response["choices"][0]),
+        Choice(**mock_response["choices"][0]),  # ty:ignore[invalid-argument-type, not-subscriptable]
     ]
     assert trajectory.additional_histories[0].messages_and_choices == [
         message,
diff --git a/tests/unit/test_tokenize_trajectory_groups.ipynb b/tests/unit/test_tokenize_trajectory_groups.ipynb
index 0628de3ee..ed488855d 100644
--- a/tests/unit/test_tokenize_trajectory_groups.ipynb
+++ b/tests/unit/test_tokenize_trajectory_groups.ipynb
@@ -126,7 +126,7 @@
     "    result.weight = round(result.weight, 2)\n",
     "    # set prompt_id to 0 to eliminate stochasticity\n",
     "    result.prompt_id = 0\n",
-    "    display(result)"
+    "    display(result)  # ty:ignore[unresolved-reference]"
    ]
   }
  ],
diff --git a/tests/unit/test_trajectory_parquet.py b/tests/unit/test_trajectory_parquet.py
index dbcef3bbb..597d93e71 100644
--- a/tests/unit/test_trajectory_parquet.py
+++ b/tests/unit/test_trajectory_parquet.py
@@ -58,7 +58,7 @@
 def _ensure_message(item: MessageOrChoice) -> ChatCompletionMessageParam:
     """Narrow a trajectory entry to a concrete message (not a Choice)."""
     assert not isinstance(item, Choice)
-    return cast(ChatCompletionMessageParam, item)
+    return cast(ChatCompletionMessageParam, item)  # ty:ignore[redundant-cast]
 
 
 def _ensure_assistant_message(
@@ -66,19 +66,19 @@ def _ensure_assistant_message(
 ) -> ChatCompletionAssistantMessageParam:
     msg = _ensure_message(item)
     assert msg["role"] == "assistant"
-    return cast(ChatCompletionAssistantMessageParam, msg)
+    return cast(ChatCompletionAssistantMessageParam, msg)  # ty:ignore[redundant-cast]
 
 
 def _ensure_tool_message(item: MessageOrChoice) -> ChatCompletionToolMessageParam:
     msg = _ensure_message(item)
     assert msg["role"] == "tool"
-    return cast(ChatCompletionToolMessageParam, msg)
+    return cast(ChatCompletionToolMessageParam, msg)  # ty:ignore[redundant-cast]
 
 
 def _ensure_user_message(item: MessageOrChoice) -> ChatCompletionUserMessageParam:
     msg = _ensure_message(item)
     assert msg["role"] == "user"
-    return cast(ChatCompletionUserMessageParam, msg)
+    return cast(ChatCompletionUserMessageParam, msg)  # ty:ignore[redundant-cast]
 
 
 class TestParquetRoundTrip:
@@ -173,7 +173,7 @@ def test_tool_calls(self, tmp_path: Path):
         assert tool_calls, "Assistant message should include tool calls"
         first_call = tool_calls[0]
         assert first_call["type"] == "function"
-        function_call = cast(ChatCompletionMessageFunctionToolCallParam, first_call)
+        function_call = cast(ChatCompletionMessageFunctionToolCallParam, first_call)  # ty:ignore[redundant-cast]
         assert function_call["function"]["name"] == "search"
 
         # Check tool result message
diff --git a/tests/unit/test_yield_trajectory.py b/tests/unit/test_yield_trajectory.py
index c7114051b..dbc6a3d94 100644
--- a/tests/unit/test_yield_trajectory.py
+++ b/tests/unit/test_yield_trajectory.py
@@ -150,5 +150,5 @@ async def say_hi() -> str | None:
     trajectory = await art.capture_yielded_trajectory(say_hi())
     assert trajectory.messages_and_choices == [
         {"role": "user", "content": "Hi!"},
-        Choice(**mock_response["choices"][0]),
+        Choice(**mock_response["choices"][0]),  # ty:ignore[invalid-argument-type, not-subscriptable]
     ]
diff --git a/uv.lock b/uv.lock
index 647914fd8..1e73e5e41 100644
--- a/uv.lock
+++ b/uv.lock
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-]
-
 [[package]]
 name = "numba"
 version = "0.61.2"
@@ -5112,11 +5087,11 @@ dev = [
     { name = "nbval" },
     { name = "prek" },
     { name = "pyarrow" },
-    { name = "pyright", extra = ["nodejs"] },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "pytest-xdist" },
     { name = "ruff" },
+    { name = "ty" },
 ]
 
 [package.metadata]
@@ -5171,11 +5146,11 @@ dev = [
     { name = "nbval", specifier = ">=0.11.0" },
     { name = "prek", specifier = ">=0.2.29" },
     { name = "pyarrow", specifier = ">=15.0.0" },
-    { name = "pyright", extras = ["nodejs"], specifier = ">=1.1.403" },
     { name = "pytest", specifier = ">=8.4.1" },
     { name = "pytest-asyncio", specifier = ">=1.1.0" },
     { name = "pytest-xdist", specifier = ">=3.8.0" },
     { name = "ruff", specifier = ">=0.12.1" },
+    { name = "ty", specifier = ">=0.0.14" },
 ]
 
 [[package]]
@@ -6658,24 +6633,6 @@ wheels = [
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 ]
 
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-version = "1.1.407"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "nodeenv" },
-    { name = "typing-extensions" },
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-
-[package.optional-dependencies]
-nodejs = [
-    { name = "nodejs-wheel-binaries" },
-]
-
 [[package]]
 name = "pytest"
 version = "9.0.2"
@@ -8648,6 +8605,30 @@ wheels = [
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 ]
 
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