diff --git a/libs/ibm/langchain_ibm/__init__.py b/libs/ibm/langchain_ibm/__init__.py
index dbda222..a5587dd 100644
--- a/libs/ibm/langchain_ibm/__init__.py
+++ b/libs/ibm/langchain_ibm/__init__.py
@@ -1,5 +1,6 @@
 from langchain_ibm.chat_models import ChatWatsonx
 from langchain_ibm.embeddings import WatsonxEmbeddings
 from langchain_ibm.llms import WatsonxLLM
+from langchain_ibm.rerank import WatsonxRerank
 
-__all__ = ["WatsonxLLM", "WatsonxEmbeddings", "ChatWatsonx"]
+__all__ = ["WatsonxLLM", "WatsonxEmbeddings", "ChatWatsonx", "WatsonxRerank"]
diff --git a/libs/ibm/langchain_ibm/chat_models.py b/libs/ibm/langchain_ibm/chat_models.py
index 71edba0..02b20f3 100644
--- a/libs/ibm/langchain_ibm/chat_models.py
+++ b/libs/ibm/langchain_ibm/chat_models.py
@@ -24,7 +24,6 @@
 from ibm_watsonx_ai import APIClient, Credentials  # type: ignore
 from ibm_watsonx_ai.foundation_models import ModelInference  # type: ignore
 from ibm_watsonx_ai.foundation_models.schema import (  # type: ignore
-    BaseSchema,
     TextChatParameters,
 )
 from langchain_core.callbacks import CallbackManagerForLLMRun
@@ -74,7 +73,7 @@
 from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
 from typing_extensions import Self
 
-from langchain_ibm.utils import check_for_attribute
+from langchain_ibm.utils import check_for_attribute, extract_params
 
 logger = logging.getLogger(__name__)
 
@@ -668,24 +667,8 @@ def _stream(
     def _create_message_dicts(
         self, messages: List[BaseMessage], stop: Optional[List[str]], **kwargs: Any
     ) -> Tuple[List[Dict[str, Any]], Dict[str, Any]]:
-        params = (
-            {
-                **(
-                    self.params.to_dict()
-                    if isinstance(self.params, BaseSchema)
-                    else self.params
-                )
-            }
-            if self.params
-            else {}
-        )
-        params = params | {
-            **(
-                kwargs.get("params", {}).to_dict()
-                if isinstance(kwargs.get("params", {}), BaseSchema)
-                else kwargs.get("params", {})
-            )
-        }
+        params = extract_params(kwargs, self.params)
+
         if stop is not None:
             if params and "stop_sequences" in params:
                 raise ValueError(
@@ -693,7 +676,7 @@ def _create_message_dicts(
                 )
             params = (params or {}) | {"stop_sequences": stop}
         message_dicts = [_convert_message_to_dict(m, self.model_id) for m in messages]
-        return message_dicts, params
+        return message_dicts, params or {}
 
     def _create_chat_result(
         self, response: dict, generation_info: Optional[Dict] = None
diff --git a/libs/ibm/langchain_ibm/embeddings.py b/libs/ibm/langchain_ibm/embeddings.py
index 27afa8b..af1767a 100644
--- a/libs/ibm/langchain_ibm/embeddings.py
+++ b/libs/ibm/langchain_ibm/embeddings.py
@@ -1,7 +1,5 @@
-from __future__ import annotations
-
 import logging
-from typing import List, Optional, Union
+from typing import Any, Dict, List, Optional, Union
 
 from ibm_watsonx_ai import APIClient, Credentials  # type: ignore
 from ibm_watsonx_ai.foundation_models.embeddings import Embeddings  # type: ignore
@@ -10,7 +8,7 @@
 from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
 from typing_extensions import Self
 
-from langchain_ibm.utils import check_for_attribute
+from langchain_ibm.utils import check_for_attribute, extract_params
 
 logger = logging.getLogger(__name__)
 
@@ -63,7 +61,7 @@ class WatsonxEmbeddings(BaseModel, LangChainEmbeddings):
     version: Optional[SecretStr] = None
     """Version of the CPD instance."""
 
-    params: Optional[dict] = None
+    params: Optional[Dict] = None
     """Model parameters to use during request generation."""
 
     verify: Union[str, bool, None] = None
@@ -151,10 +149,13 @@ def validate_environment(self) -> Self:
 
         return self
 
-    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+    def embed_documents(self, texts: List[str], **kwargs: Any) -> List[List[float]]:
         """Embed search docs."""
-        return self.watsonx_embed.embed_documents(texts=texts)
+        params = extract_params(kwargs, self.params)
+        return self.watsonx_embed.embed_documents(
+            texts=texts, **(kwargs | {"params": params})
+        )
 
-    def embed_query(self, text: str) -> List[float]:
+    def embed_query(self, text: str, **kwargs: Any) -> List[float]:
         """Embed query text."""
-        return self.embed_documents([text])[0]
+        return self.embed_documents([text], **kwargs)[0]
diff --git a/libs/ibm/langchain_ibm/llms.py b/libs/ibm/langchain_ibm/llms.py
index 0cc5f5e..fbc0aa8 100644
--- a/libs/ibm/langchain_ibm/llms.py
+++ b/libs/ibm/langchain_ibm/llms.py
@@ -16,7 +16,7 @@
 from pydantic import ConfigDict, Field, SecretStr, model_validator
 from typing_extensions import Self
 
-from langchain_ibm.utils import check_for_attribute
+from langchain_ibm.utils import check_for_attribute, extract_params
 
 logger = logging.getLogger(__name__)
 textgen_valid_params = [
@@ -305,12 +305,9 @@ def _override_chat_params(
     def _get_chat_params(
         self, stop: Optional[List[str]] = None, **kwargs: Any
     ) -> Tuple[Dict[str, Any], Dict[str, Any]]:
-        params = (
-            {**self.params, **kwargs.pop("params", {})}
-            if self.params
-            else kwargs.pop("params", {})
-        )
-        params, kwargs = self._override_chat_params(params, **kwargs)
+        params = extract_params(kwargs, self.params)
+
+        params, kwargs = self._override_chat_params(params or {}, **kwargs)
         if stop is not None:
             if params and "stop_sequences" in params:
                 raise ValueError(
diff --git a/libs/ibm/langchain_ibm/rerank.py b/libs/ibm/langchain_ibm/rerank.py
new file mode 100644
index 0000000..754ad5d
--- /dev/null
+++ b/libs/ibm/langchain_ibm/rerank.py
@@ -0,0 +1,232 @@
+from __future__ import annotations
+
+from copy import deepcopy
+from typing import Any, Dict, List, Optional, Sequence, Union
+
+from ibm_watsonx_ai import APIClient, Credentials  # type: ignore
+from ibm_watsonx_ai.foundation_models import Rerank  # type: ignore
+from ibm_watsonx_ai.foundation_models.schema import (  # type: ignore
+    RerankParameters,
+)
+from langchain_core.callbacks import Callbacks
+from langchain_core.documents import BaseDocumentCompressor, Document
+from langchain_core.utils.utils import secret_from_env
+from pydantic import ConfigDict, Field, SecretStr, model_validator
+from typing_extensions import Self
+
+from langchain_ibm.utils import check_for_attribute, extract_params
+
+
+class WatsonxRerank(BaseDocumentCompressor):
+    """Document compressor that uses `watsonx Rerank API`."""
+
+    model_id: str
+    """Type of model to use."""
+
+    project_id: Optional[str] = None
+    """ID of the Watson Studio project."""
+
+    space_id: Optional[str] = None
+    """ID of the Watson Studio space."""
+
+    url: SecretStr = Field(
+        alias="url", default_factory=secret_from_env("WATSONX_URL", default=None)
+    )
+    """URL to the Watson Machine Learning or CPD instance."""
+
+    apikey: Optional[SecretStr] = Field(
+        alias="apikey", default_factory=secret_from_env("WATSONX_APIKEY", default=None)
+    )
+    """API key to the Watson Machine Learning or CPD instance."""
+
+    token: Optional[SecretStr] = Field(
+        alias="token", default_factory=secret_from_env("WATSONX_TOKEN", default=None)
+    )
+    """Token to the CPD instance."""
+
+    password: Optional[SecretStr] = Field(
+        alias="password",
+        default_factory=secret_from_env("WATSONX_PASSWORD", default=None),
+    )
+    """Password to the CPD instance."""
+
+    username: Optional[SecretStr] = Field(
+        alias="username",
+        default_factory=secret_from_env("WATSONX_USERNAME", default=None),
+    )
+    """Username to the CPD instance."""
+
+    instance_id: Optional[SecretStr] = Field(
+        alias="instance_id",
+        default_factory=secret_from_env("WATSONX_INSTANCE_ID", default=None),
+    )
+    """Instance_id of the CPD instance."""
+
+    version: Optional[SecretStr] = None
+    """Version of the CPD instance."""
+
+    params: Optional[Union[dict, RerankParameters]] = None
+    """Model parameters to use during request generation."""
+
+    verify: Union[str, bool, None] = None
+    """You can pass one of following as verify:
+        * the path to a CA_BUNDLE file
+        * the path of directory with certificates of trusted CAs
+        * True - default path to truststore will be taken
+        * False - no verification will be made"""
+
+    validate_model: bool = True
+    """Model ID validation."""
+
+    streaming: bool = False
+    """ Whether to stream the results or not. """
+
+    watsonx_rerank: Rerank = Field(default=None, exclude=True)  #: :meta private:
+
+    watsonx_client: Optional[APIClient] = Field(default=None, exclude=True)
+
+    model_config = ConfigDict(
+        arbitrary_types_allowed=True,
+        extra="forbid",
+        protected_namespaces=(),
+    )
+
+    @property
+    def lc_secrets(self) -> Dict[str, str]:
+        """A map of constructor argument names to secret ids.
+
+        For example:
+            {
+                "url": "WATSONX_URL",
+                "apikey": "WATSONX_APIKEY",
+                "token": "WATSONX_TOKEN",
+                "password": "WATSONX_PASSWORD",
+                "username": "WATSONX_USERNAME",
+                "instance_id": "WATSONX_INSTANCE_ID",
+            }
+        """
+        return {
+            "url": "WATSONX_URL",
+            "apikey": "WATSONX_APIKEY",
+            "token": "WATSONX_TOKEN",
+            "password": "WATSONX_PASSWORD",
+            "username": "WATSONX_USERNAME",
+            "instance_id": "WATSONX_INSTANCE_ID",
+        }
+
+    @model_validator(mode="after")
+    def validate_environment(self) -> Self:
+        """Validate that credentials and python package exists in environment."""
+        if isinstance(self.watsonx_client, APIClient):
+            watsonx_rerank = Rerank(
+                model_id=self.model_id,
+                params=self.params,
+                api_client=self.watsonx_client,
+                project_id=self.project_id,
+                space_id=self.space_id,
+                verify=self.verify,
+            )
+            self.watsonx_rerank = watsonx_rerank
+
+        else:
+            check_for_attribute(self.url, "url", "WATSONX_URL")
+
+            if "cloud.ibm.com" in self.url.get_secret_value():
+                check_for_attribute(self.apikey, "apikey", "WATSONX_APIKEY")
+            else:
+                if not self.token and not self.password and not self.apikey:
+                    raise ValueError(
+                        "Did not find 'token', 'password' or 'apikey',"
+                        " please add an environment variable"
+                        " `WATSONX_TOKEN`, 'WATSONX_PASSWORD' or 'WATSONX_APIKEY' "
+                        "which contains it,"
+                        " or pass 'token', 'password' or 'apikey'"
+                        " as a named parameter."
+                    )
+                elif self.token:
+                    check_for_attribute(self.token, "token", "WATSONX_TOKEN")
+                elif self.password:
+                    check_for_attribute(self.password, "password", "WATSONX_PASSWORD")
+                    check_for_attribute(self.username, "username", "WATSONX_USERNAME")
+                elif self.apikey:
+                    check_for_attribute(self.apikey, "apikey", "WATSONX_APIKEY")
+                    check_for_attribute(self.username, "username", "WATSONX_USERNAME")
+
+                if not self.instance_id:
+                    check_for_attribute(
+                        self.instance_id, "instance_id", "WATSONX_INSTANCE_ID"
+                    )
+
+            credentials = Credentials(
+                url=self.url.get_secret_value() if self.url else None,
+                api_key=self.apikey.get_secret_value() if self.apikey else None,
+                token=self.token.get_secret_value() if self.token else None,
+                password=self.password.get_secret_value() if self.password else None,
+                username=self.username.get_secret_value() if self.username else None,
+                instance_id=self.instance_id.get_secret_value()
+                if self.instance_id
+                else None,
+                version=self.version.get_secret_value() if self.version else None,
+                verify=self.verify,
+            )
+
+            watsonx_rerank = Rerank(
+                model_id=self.model_id,
+                credentials=credentials,
+                params=self.params,
+                project_id=self.project_id,
+                space_id=self.space_id,
+                verify=self.verify,
+            )
+            self.watsonx_rerank = watsonx_rerank
+
+        return self
+
+    def rerank(
+        self,
+        documents: Sequence[Union[str, Document, dict]],
+        query: str,
+        **kwargs: Any,
+    ) -> List[Dict[str, Any]]:
+        if len(documents) == 0:  # to avoid empty api call
+            return []
+        docs = [
+            doc.page_content if isinstance(doc, Document) else doc for doc in documents
+        ]
+        params = extract_params(kwargs, self.params)
+
+        results = self.watsonx_rerank.generate(
+            query=query, inputs=docs, **(kwargs | {"params": params})
+        )
+        result_dicts = []
+        for res in results["results"]:
+            result_dicts.append(
+                {"index": res.get("index"), "relevance_score": res.get("score")}
+            )
+        return result_dicts
+
+    def compress_documents(
+        self,
+        documents: Sequence[Document],
+        query: str,
+        callbacks: Optional[Callbacks] = None,
+        **kwargs: Any,
+    ) -> Sequence[Document]:
+        """
+        Compress documents using watsonx's rerank API.
+
+        Args:
+            documents: A sequence of documents to compress.
+            query: The query to use for compressing the documents.
+            callbacks: Callbacks to run during the compression process.
+
+        Returns:
+            A sequence of compressed documents.
+        """
+        compressed = []
+        for res in self.rerank(documents, query, **kwargs):
+            doc = documents[res["index"]]
+            doc_copy = Document(doc.page_content, metadata=deepcopy(doc.metadata))
+            doc_copy.metadata["relevance_score"] = res["relevance_score"]
+            compressed.append(doc_copy)
+        return compressed
diff --git a/libs/ibm/langchain_ibm/utils.py b/libs/ibm/langchain_ibm/utils.py
index 6e340d9..49a764a 100644
--- a/libs/ibm/langchain_ibm/utils.py
+++ b/libs/ibm/langchain_ibm/utils.py
@@ -1,3 +1,6 @@
+from typing import Any, Dict, Optional, Union
+
+from ibm_watsonx_ai.foundation_models.schema import BaseSchema  # type: ignore
 from pydantic import SecretStr
 
 
@@ -8,3 +11,20 @@ def check_for_attribute(value: SecretStr | None, key: str, env_key: str) -> None
             f" `{env_key}` which contains it, or pass"
             f" `{key}` as a named parameter."
         )
+
+
+def extract_params(
+    kwargs: Dict[str, Any],
+    default_params: Optional[Union[BaseSchema, Dict[str, Any]]] = None,
+) -> Dict[str, Any]:
+    if kwargs.get("params") is not None:
+        params = kwargs.pop("params")
+    elif default_params is not None:
+        params = default_params
+    else:
+        params = None
+
+    if isinstance(params, BaseSchema):
+        params = params.to_dict()
+
+    return params or {}
diff --git a/libs/ibm/poetry.lock b/libs/ibm/poetry.lock
index 46a6e02..4162223 100644
--- a/libs/ibm/poetry.lock
+++ b/libs/ibm/poetry.lock
@@ -13,13 +13,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.6.2"
+version = "4.6.2.post1"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.6.2-py3-none-any.whl", hash = "sha256:6caec6b1391f6f6d7b2ef2258d2902d36753149f67478f7df4be8e54d03a8f54"},
-    {file = "anyio-4.6.2.tar.gz", hash = "sha256:f72a7bb3dd0752b3bd8b17a844a019d7fbf6ae218c588f4f9ba1b2f600b12347"},
+    {file = "anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d"},
+    {file = "anyio-4.6.2.post1.tar.gz", hash = "sha256:4c8bc31ccdb51c7f7bd251f51c609e038d63e34219b44aa86e47576389880b4c"},
 ]
 
 [package.dependencies]
@@ -188,73 +188,73 @@ files = [
 
 [[package]]
 name = "coverage"
-version = "7.6.3"
+version = "7.6.4"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.9"
 files = [
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-    {file = "coverage-7.6.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c222958f59b0ae091f4535851cbb24eb57fc0baea07ba675af718fb5302dddb2"},
-    {file = "coverage-7.6.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ab84a8b698ad5a6c365b08061920138e7a7dd9a04b6feb09ba1bfae68346ce6d"},
-    {file = "coverage-7.6.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:70a6756ce66cd6fe8486c775b30889f0dc4cb20c157aa8c35b45fd7868255c5c"},
-    {file = "coverage-7.6.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3c2e6fa98032fec8282f6b27e3f3986c6e05702828380618776ad794e938f53a"},
-    {file = "coverage-7.6.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:921fbe13492caf6a69528f09d5d7c7d518c8d0e7b9f6701b7719715f29a71e6e"},
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-    {file = "coverage-7.6.3-cp310-cp310-win32.whl", hash = "sha256:a3328c3e64ea4ab12b85999eb0779e6139295bbf5485f69d42cf794309e3d007"},
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 ]
 
 [package.dependencies]
@@ -350,57 +350,57 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "ibm-cos-sdk"
-version = "2.13.5"
+version = "2.13.6"
 description = "IBM SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "ibm-cos-sdk-2.13.5.tar.gz", hash = "sha256:1aff7f9863ac9072a3db2f0053bec99478b26f3fb5fa797ce96a15bbb13cd40e"},
+    {file = "ibm-cos-sdk-2.13.6.tar.gz", hash = "sha256:171cf2ae4ab662a4b8ab58dcf4ac994b0577d6c92d78490295fd7704a83978f6"},
 ]
 
 [package.dependencies]
-ibm-cos-sdk-core = "2.13.5"
-ibm-cos-sdk-s3transfer = "2.13.5"
+ibm-cos-sdk-core = "2.13.6"
+ibm-cos-sdk-s3transfer = "2.13.6"
 jmespath = ">=0.10.0,<=1.0.1"
 
 [[package]]
 name = "ibm-cos-sdk-core"
-version = "2.13.5"
+version = "2.13.6"
 description = "Low-level, data-driven core of IBM SDK for Python"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "ibm-cos-sdk-core-2.13.5.tar.gz", hash = "sha256:d3a99d8b06b3f8c00b1a9501f85538d592463e63ddf8cec32672ab5a0b107b83"},
+    {file = "ibm-cos-sdk-core-2.13.6.tar.gz", hash = "sha256:dd41fb789eeb65546501afabcd50e78846ab4513b6ad4042e410b6a14ff88413"},
 ]
 
 [package.dependencies]
 jmespath = ">=0.10.0,<=1.0.1"
 python-dateutil = ">=2.9.0,<3.0.0"
-requests = ">=2.32.3,<3.0"
-urllib3 = {version = ">=1.26.18,<2.2", markers = "python_version >= \"3.10\""}
+requests = ">=2.32.0,<2.32.3"
+urllib3 = ">=1.26.18,<3"
 
 [[package]]
 name = "ibm-cos-sdk-s3transfer"
-version = "2.13.5"
+version = "2.13.6"
 description = "IBM S3 Transfer Manager"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-ibm-cos-sdk-core = "2.13.5"
+ibm-cos-sdk-core = "2.13.6"
 
 [[package]]
 name = "ibm-watsonx-ai"
-version = "1.1.14"
+version = "1.1.16"
 description = "IBM watsonx.ai API Client"
 optional = false
 python-versions = ">=3.10"
 files = [
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 ]
 
 [package.dependencies]
@@ -420,7 +420,7 @@ fl-crypto = ["pyhelayers (==1.5.0.3)"]
 fl-crypto-rt24-1 = ["pyhelayers (==1.5.3.1)"]
 fl-rt23-1-py3-10 = ["GPUtil", "cryptography (==42.0.5)", "ddsketch (==2.0.4)", "diffprivlib (==0.5.1)", "environs (==9.5.0)", "gym", "image (==1.5.33)", "joblib (==1.1.1)", "lz4", "msgpack (==1.0.7)", "msgpack-numpy (==0.4.8)", "numcompress (==0.1.2)", "numpy (==1.23.5)", "pandas (==1.5.3)", "parse (==1.19.0)", "pathlib2 (==2.3.6)", "protobuf (==4.22.1)", "psutil", "pyYAML (==6.0.1)", "pytest (==6.2.5)", "requests (==2.32.3)", "scikit-learn (==1.1.1)", "scipy (==1.10.1)", "setproctitle", "skops (==0.9.0)", "skorch (==0.12.0)", "tabulate (==0.8.9)", "tensorflow (==2.12.0)", "torch (==2.0.1)", "websockets (==10.1)"]
 fl-rt24-1-py3-11 = ["GPUtil", "cryptography (==42.0.5)", "ddsketch (==2.0.4)", "diffprivlib (==0.5.1)", "environs (==9.5.0)", "gym", "image (==1.5.33)", "joblib (==1.3.2)", "lz4", "msgpack (==1.0.7)", "msgpack-numpy (==0.4.8)", "numcompress (==0.1.2)", "numpy (==1.26.4)", "pandas (==2.1.4)", "parse (==1.19.0)", "pathlib2 (==2.3.6)", "protobuf (==4.22.1)", "psutil", "pyYAML (==6.0.1)", "pytest (==6.2.5)", "requests (==2.32.3)", "scikit-learn (==1.3.0)", "scipy (==1.11.4)", "setproctitle", "skops (==0.9.0)", "skorch (==0.12.0)", "tabulate (==0.8.9)", "tensorflow (==2.14.1)", "torch (==2.1.2)", "websockets (==10.1)"]
-rag = ["beautifulsoup4 (==4.12.3)", "grpcio (>=1.60.0)", "langchain (>=0.2.15,<0.3)", "langchain-chroma (==0.1.1)", "langchain-community (>=0.2.4,<0.3)", "langchain-core (>=0.2.37,<0.3)", "langchain-elasticsearch (==0.2.2)", "langchain-ibm", "langchain-milvus (==0.1.1)", "pypdf (==4.2.0)", "python-docx (==1.1.2)"]
+rag = ["beautifulsoup4 (==4.12.3)", "grpcio (>=1.60.0)", "langchain (>=0.2.15,<0.3)", "langchain-chroma (==0.1.1)", "langchain-community (>=0.2.4,<0.3)", "langchain-core (>=0.2.37,<0.3)", "langchain-elasticsearch (==0.2.2)", "langchain-ibm", "langchain-milvus (==0.1.1)", "markdown (==3.4.1)", "pypdf (==4.2.0)", "python-docx (==1.1.2)"]
 
 [[package]]
 name = "idna"
@@ -508,7 +508,7 @@ files = [
 
 [[package]]
 name = "langchain-core"
-version = "0.3.10"
+version = "0.3.13"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = ">=3.9,<4.0"
@@ -531,7 +531,7 @@ typing-extensions = ">=4.7"
 type = "git"
 url = "https://github.com/langchain-ai/langchain.git"
 reference = "HEAD"
-resolved_reference = "2197958366b527df23adbf12bf6578e4cd5e002c"
+resolved_reference = "94e5765416037b9b90a27603cfda36cbe86bce71"
 subdirectory = "libs/core"
 
 [[package]]
@@ -553,18 +553,18 @@ syrupy = "^4"
 type = "git"
 url = "https://github.com/langchain-ai/langchain.git"
 reference = "HEAD"
-resolved_reference = "2197958366b527df23adbf12bf6578e4cd5e002c"
+resolved_reference = "94e5765416037b9b90a27603cfda36cbe86bce71"
 subdirectory = "libs/standard-tests"
 
 [[package]]
 name = "langsmith"
-version = "0.1.134"
+version = "0.1.137"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -593,43 +593,43 @@ six = ">=1.10.0"
 
 [[package]]
 name = "mypy"
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+version = "1.13.0"
 description = "Optional static typing for Python"
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 [package.dependencies]
@@ -639,6 +639,7 @@ typing-extensions = ">=4.6.0"
 
 [package.extras]
 dmypy = ["psutil (>=4.0)"]
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 install-types = ["pip"]
 mypyc = ["setuptools (>=50)"]
 reports = ["lxml"]
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+    {file = "orjson-3.10.10.tar.gz", hash = "sha256:37949383c4df7b4337ce82ee35b6d7471e55195efa7dcb45ab8226ceadb0fe3b"},
 ]
 
 [[package]]
@@ -1162,13 +1164,13 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.32.3"
+version = "2.32.2"
 description = "Python HTTP for Humans."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
-    {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
+    {file = "requests-2.32.2-py3-none-any.whl", hash = "sha256:fc06670dd0ed212426dfeb94fc1b983d917c4f9847c863f313c9dfaaffb7c23c"},
+    {file = "requests-2.32.2.tar.gz", hash = "sha256:dd951ff5ecf3e3b3aa26b40703ba77495dab41da839ae72ef3c8e5d8e2433289"},
 ]
 
 [package.dependencies]
@@ -1300,13 +1302,13 @@ files = [
 
 [[package]]
 name = "types-requests"
-version = "2.32.0.20240914"
+version = "2.32.0.20241016"
 description = "Typing stubs for requests"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-requests-2.32.0.20240914.tar.gz", hash = "sha256:2850e178db3919d9bf809e434eef65ba49d0e7e33ac92d588f4a5e295fffd405"},
-    {file = "types_requests-2.32.0.20240914-py3-none-any.whl", hash = "sha256:59c2f673eb55f32a99b2894faf6020e1a9f4a402ad0f192bfee0b64469054310"},
+    {file = "types-requests-2.32.0.20241016.tar.gz", hash = "sha256:0d9cad2f27515d0e3e3da7134a1b6f28fb97129d86b867f24d9c726452634d95"},
+    {file = "types_requests-2.32.0.20241016-py3-none-any.whl", hash = "sha256:4195d62d6d3e043a4eaaf08ff8a62184584d2e8684e9d2aa178c7915a7da3747"},
 ]
 
 [package.dependencies]
@@ -1336,17 +1338,18 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "2.1.0"
+version = "2.2.3"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.1.0-py3-none-any.whl", hash = "sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3"},
-    {file = "urllib3-2.1.0.tar.gz", hash = "sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"},
+    {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
+    {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
 ]
 
 [package.extras]
 brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
diff --git a/libs/ibm/pyproject.toml b/libs/ibm/pyproject.toml
index 3237220..bb60464 100644
--- a/libs/ibm/pyproject.toml
+++ b/libs/ibm/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-ibm"
-version = "0.3.1"
+version = "0.3.2"
 description = "An integration package connecting IBM watsonx.ai and LangChain"
 authors = ["IBM"]
 readme = "README.md"
diff --git a/libs/ibm/tests/integration_tests/test_chat_models.py b/libs/ibm/tests/integration_tests/test_chat_models.py
index f37c4af..184d33a 100644
--- a/libs/ibm/tests/integration_tests/test_chat_models.py
+++ b/libs/ibm/tests/integration_tests/test_chat_models.py
@@ -27,6 +27,8 @@
 MODEL_ID = "ibm/granite-34b-code-instruct"
 MODEL_ID_TOOL = "mistralai/mistral-large"
 
+PARAMS_WITH_MAX_TOKENS = {"max_tokens": 20}
+
 
 def test_01_generate_chat() -> None:
     chat = ChatWatsonx(model_id=MODEL_ID, url=URL, project_id=WX_PROJECT_ID)  # type: ignore[arg-type]
@@ -122,7 +124,12 @@ def test_01b_generate_chat_with_invoke_params() -> None:
 
 
 def test_02_generate_chat_with_few_inputs() -> None:
-    chat = ChatWatsonx(model_id=MODEL_ID, url=URL, project_id=WX_PROJECT_ID)  # type: ignore[arg-type]
+    chat = ChatWatsonx(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+        params=PARAMS_WITH_MAX_TOKENS,
+    )
     message = HumanMessage(content="Hello")
     response = chat.generate([[message], [message]])
     assert response
@@ -131,7 +138,12 @@ def test_02_generate_chat_with_few_inputs() -> None:
 
 
 def test_03_generate_chat_with_few_various_inputs() -> None:
-    chat = ChatWatsonx(model_id=MODEL_ID, url=URL, project_id=WX_PROJECT_ID)  # type: ignore[arg-type]
+    chat = ChatWatsonx(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+        params=PARAMS_WITH_MAX_TOKENS,
+    )
     system_message = SystemMessage(content="You are to chat with the user.")
     human_message = HumanMessage(content="Hello")
     response = chat.invoke([system_message, human_message])
@@ -142,7 +154,12 @@ def test_03_generate_chat_with_few_various_inputs() -> None:
 
 
 def test_05_generate_chat_with_stream() -> None:
-    chat = ChatWatsonx(model_id=MODEL_ID, url=URL, project_id=WX_PROJECT_ID)  # type: ignore[arg-type]
+    chat = ChatWatsonx(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+        params=PARAMS_WITH_MAX_TOKENS,
+    )
     response = chat.stream("What's the weather in san francisco")
     for chunk in response:
         assert isinstance(chunk.content, str)
@@ -154,6 +171,7 @@ def test_05a_invoke_chat_with_streaming() -> None:
         url=URL,  # type: ignore[arg-type]
         project_id=WX_PROJECT_ID,
         streaming=True,
+        params=PARAMS_WITH_MAX_TOKENS,
     )
     response = chat.invoke("What's the weather in san francisco")
     assert isinstance(response.content, str)
@@ -185,6 +203,7 @@ def test_06_chain_invoke() -> None:
         model_id=MODEL_ID,
         url=URL,  # type: ignore[arg-type]
         project_id=WX_PROJECT_ID,
+        params=PARAMS_WITH_MAX_TOKENS,
     )
 
     system = "You are a helpful assistant."
@@ -199,48 +218,18 @@ def test_06_chain_invoke() -> None:
 
 
 def test_10_chaining() -> None:
-    chat = ChatWatsonx(model_id=MODEL_ID, url=URL, project_id=WX_PROJECT_ID)  # type: ignore[arg-type]
-    prompt = ChatPromptTemplate.from_messages(
-        [
-            (
-                "system",
-                "You are a helpful assistant that "
-                "translates {input_language} to {output_language}.",
-            ),
-            ("human", "{input}"),
-        ]
-    )
-    chain = prompt | chat
-
-    response = chain.invoke(
-        {
-            "input_language": "English",
-            "output_language": "German",
-            "input": "I love programming.",
-        }
-    )
-    assert response
-    assert response.content
-
-
-def test_11_chaining_with_params() -> None:
-    parameters = {
-        GenTextParamsMetaNames.DECODING_METHOD: "sample",
-        GenTextParamsMetaNames.MIN_NEW_TOKENS: 5,
-        GenTextParamsMetaNames.MAX_NEW_TOKENS: 10,
-    }
     chat = ChatWatsonx(
         model_id=MODEL_ID,
         url=URL,  # type: ignore[arg-type]
         project_id=WX_PROJECT_ID,
-        params=parameters,
+        params=PARAMS_WITH_MAX_TOKENS,
     )
     prompt = ChatPromptTemplate.from_messages(
         [
             (
                 "system",
-                "You are a helpful assistant that translates "
-                "{input_language} to {output_language}.",
+                "You are a helpful assistant that "
+                "translates {input_language} to {output_language}.",
             ),
             ("human", "{input}"),
         ]
diff --git a/libs/ibm/tests/integration_tests/test_chat_models_standard.py b/libs/ibm/tests/integration_tests/test_chat_models_standard.py
index a845aec..99b57f8 100644
--- a/libs/ibm/tests/integration_tests/test_chat_models_standard.py
+++ b/libs/ibm/tests/integration_tests/test_chat_models_standard.py
@@ -13,13 +13,26 @@
 URL = "https://us-south.ml.cloud.ibm.com"
 
 MODEL_ID = "mistralai/mistral-large"
+MODEL_ID_IMAGE = "meta-llama/llama-3-2-11b-vision-instruct"
 
 
-class TestWatsonxStandard(ChatModelIntegrationTests):
+class TestChatWatsonxStandard(ChatModelIntegrationTests):
     @property
     def chat_model_class(self) -> Type[BaseChatModel]:
         return ChatWatsonx
 
+    @property
+    def has_tool_calling(self) -> bool:
+        return True
+
+    @property
+    def returns_usage_metadata(self) -> bool:
+        return True
+
+    @property
+    def supports_image_inputs(self) -> bool:
+        return True
+
     @property
     def supported_usage_metadata_details(
         self,
@@ -49,6 +62,12 @@ def chat_model_params(self) -> dict:
             "project_id": WX_PROJECT_ID,
         }
 
+    @pytest.mark.xfail(reason="Supported for vision model.")
+    def test_image_inputs(self, model: BaseChatModel) -> None:
+        model.watsonx_model._inference.model_id = MODEL_ID_IMAGE  # type: ignore[attr-defined]
+        super().test_image_inputs(model)
+        model.watsonx_model._inference.model_id = MODEL_ID  # type: ignore[attr-defined]
+
     @pytest.mark.xfail(reason="Not implemented tool_choice as `any`.")
     def test_structured_few_shot_examples(self, model: BaseChatModel) -> None:
         super().test_structured_few_shot_examples(model)
diff --git a/libs/ibm/tests/integration_tests/test_embeddings.py b/libs/ibm/tests/integration_tests/test_embeddings.py
index 23ba79b..2af2b24 100644
--- a/libs/ibm/tests/integration_tests/test_embeddings.py
+++ b/libs/ibm/tests/integration_tests/test_embeddings.py
@@ -30,7 +30,55 @@ def test_01_generate_embed_documents() -> None:
     assert all(isinstance(el, float) for el in generate_embedding[0])
 
 
-def test_02_generate_embed_query() -> None:
+def test_02_generate_embed_documents_with_param() -> None:
+    embed_params = {
+        EmbedTextParamsMetaNames.TRUNCATE_INPUT_TOKENS: 3,
+    }
+    watsonx_embedding = WatsonxEmbeddings(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+        params=embed_params,
+    )
+    generate_embedding = watsonx_embedding.embed_documents(texts=DOCUMENTS)
+    assert len(generate_embedding) == len(DOCUMENTS)
+    assert all(isinstance(el, float) for el in generate_embedding[0])
+
+
+def test_03_generate_embed_documents_with_param_in_method() -> None:
+    embed_params = {
+        EmbedTextParamsMetaNames.TRUNCATE_INPUT_TOKENS: 3,
+    }
+    watsonx_embedding = WatsonxEmbeddings(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+    )
+    generate_embedding = watsonx_embedding.embed_documents(
+        texts=DOCUMENTS, params=embed_params
+    )
+    assert len(generate_embedding) == len(DOCUMENTS)
+    assert all(isinstance(el, float) for el in generate_embedding[0])
+
+
+def test_04_generate_embed_documents_with_param_and_concurrency_limit() -> None:
+    embed_params = {
+        EmbedTextParamsMetaNames.TRUNCATE_INPUT_TOKENS: 3,
+    }
+    watsonx_embedding = WatsonxEmbeddings(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+        params=embed_params,
+    )
+    generate_embedding = watsonx_embedding.embed_documents(
+        texts=DOCUMENTS, concurrency_limit=9
+    )
+    assert len(generate_embedding) == len(DOCUMENTS)
+    assert all(isinstance(el, float) for el in generate_embedding[0])
+
+
+def test_10_generate_embed_query() -> None:
     watsonx_embedding = WatsonxEmbeddings(
         model_id=MODEL_ID,
         url=URL,  # type: ignore[arg-type]
@@ -42,7 +90,24 @@ def test_02_generate_embed_query() -> None:
     )
 
 
-def test_03_generate_embed_documents_with_param() -> None:
+def test_11_generate_embed_query_with_params() -> None:
+    embed_params = {
+        EmbedTextParamsMetaNames.TRUNCATE_INPUT_TOKENS: 3,
+    }
+    watsonx_embedding = WatsonxEmbeddings(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+    )
+    generate_embedding = watsonx_embedding.embed_query(
+        text=DOCUMENTS[0], params=embed_params
+    )
+    assert isinstance(generate_embedding, list) and isinstance(
+        generate_embedding[0], float
+    )
+
+
+def test_12_generate_embed_query_with_params_and_concurrency_limit() -> None:
     embed_params = {
         EmbedTextParamsMetaNames.TRUNCATE_INPUT_TOKENS: 3,
     }
@@ -52,12 +117,15 @@ def test_03_generate_embed_documents_with_param() -> None:
         project_id=WX_PROJECT_ID,
         params=embed_params,
     )
-    generate_embedding = watsonx_embedding.embed_documents(texts=DOCUMENTS)
-    assert len(generate_embedding) == len(DOCUMENTS)
-    assert all(isinstance(el, float) for el in generate_embedding[0])
+    generate_embedding = watsonx_embedding.embed_query(
+        text=DOCUMENTS[0], concurrency_limit=9
+    )
+    assert isinstance(generate_embedding, list) and isinstance(
+        generate_embedding[0], float
+    )
 
 
-def test_10_generate_embed_query_with_client_initialization() -> None:
+def test_20_generate_embed_query_with_client_initialization() -> None:
     watsonx_client = APIClient(
         credentials={
             "url": URL,
diff --git a/libs/ibm/tests/integration_tests/test_embeddings_standard.py b/libs/ibm/tests/integration_tests/test_embeddings_standard.py
new file mode 100644
index 0000000..ace9ff5
--- /dev/null
+++ b/libs/ibm/tests/integration_tests/test_embeddings_standard.py
@@ -0,0 +1,28 @@
+import os
+from typing import Type
+
+from langchain_standard_tests.integration_tests import EmbeddingsIntegrationTests
+
+from langchain_ibm import WatsonxEmbeddings
+
+WX_APIKEY = os.environ.get("WATSONX_APIKEY", "")
+WX_PROJECT_ID = os.environ.get("WATSONX_PROJECT_ID", "")
+
+URL = "https://us-south.ml.cloud.ibm.com"
+
+MODEL_ID = "ibm/slate-125m-english-rtrvr"
+
+
+class TestWatsonxEmbeddingsStandard(EmbeddingsIntegrationTests):
+    @property
+    def embeddings_class(self) -> Type[WatsonxEmbeddings]:
+        return WatsonxEmbeddings
+
+    @property
+    def embedding_model_params(self) -> dict:
+        return {
+            "model_id": MODEL_ID,
+            "url": URL,
+            "apikey": WX_APIKEY,
+            "project_id": WX_PROJECT_ID,
+        }
diff --git a/libs/ibm/tests/integration_tests/test_llms.py b/libs/ibm/tests/integration_tests/test_llms.py
index 5a8cfb7..bfc6d2b 100644
--- a/libs/ibm/tests/integration_tests/test_llms.py
+++ b/libs/ibm/tests/integration_tests/test_llms.py
@@ -34,11 +34,7 @@ def test_watsonxllm_invoke() -> None:
 
 
 def test_watsonxllm_invoke_with_params() -> None:
-    parameters = {
-        GenTextParamsMetaNames.DECODING_METHOD: "sample",
-        GenTextParamsMetaNames.MAX_NEW_TOKENS: 10,
-        GenTextParamsMetaNames.MIN_NEW_TOKENS: 5,
-    }
+    parameters = {GenTextParamsMetaNames.MAX_NEW_TOKENS: 4}
 
     watsonxllm = WatsonxLLM(
         model_id=MODEL_ID,
@@ -46,10 +42,10 @@ def test_watsonxllm_invoke_with_params() -> None:
         project_id=WX_PROJECT_ID,
         params=parameters,
     )
-    response = watsonxllm.invoke("What color sunflower is?")
+    response = watsonxllm.invoke("Write: 'ttttttttttttt'?")
     print(f"\nResponse: {response}")
     assert isinstance(response, str)
-    assert len(response) > 0
+    assert 0 < len(response) < 5
 
 
 def test_watsonxllm_invoke_with_params_2() -> None:
@@ -112,6 +108,32 @@ def test_watsonxllm_invoke_with_params_4() -> None:
     assert len(response) > 0
 
 
+def test_watsonxllm_invoke_with_params_5_diff() -> None:
+    parameters_1 = {
+        GenTextParamsMetaNames.MAX_NEW_TOKENS: 5,
+    }
+    parameters_2 = {
+        GenTextParamsMetaNames.MAX_NEW_TOKENS: 10,
+    }
+
+    watsonxllm = WatsonxLLM(
+        model_id=MODEL_ID,
+        url="https://us-south.ml.cloud.ibm.com",  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+        params=parameters_1,
+    )
+    response_1 = watsonxllm.invoke("Please write 'ttttttttttttttttttttttt'?")
+    print(f"\nResponse 1: {response_1}")
+    assert isinstance(response_1, str)
+    assert 3 < len(response_1) < 5
+    response_2 = watsonxllm.invoke(
+        "Please write 'ttttttttttttttttttttttt'?", params=parameters_2
+    )
+    print(f"\nResponse 2: {response_2}")
+    assert isinstance(response_2, str)
+    assert 8 < len(response_2) < 10
+
+
 def test_watsonxllm_generate() -> None:
     watsonxllm = WatsonxLLM(
         model_id=MODEL_ID,
diff --git a/libs/ibm/tests/integration_tests/test_rerank.py b/libs/ibm/tests/integration_tests/test_rerank.py
new file mode 100644
index 0000000..5e4a7d2
--- /dev/null
+++ b/libs/ibm/tests/integration_tests/test_rerank.py
@@ -0,0 +1,147 @@
+import os
+
+from ibm_watsonx_ai import APIClient  # type: ignore
+from ibm_watsonx_ai.foundation_models.schema import (  # type: ignore
+    RerankParameters,
+    RerankReturnOptions,
+)
+from langchain_core.documents import Document
+
+from langchain_ibm import WatsonxRerank
+
+WX_APIKEY = os.environ.get("WATSONX_APIKEY", "")
+WX_PROJECT_ID = os.environ.get("WATSONX_PROJECT_ID", "")
+
+URL = "https://us-south.ml.cloud.ibm.com"
+
+MODEL_ID = "ibm/slate-125m-english-rtrvr"
+
+
+def test_01_rerank_init() -> None:
+    wx_rerank = WatsonxRerank(model_id=MODEL_ID, url=URL, project_id=WX_PROJECT_ID)  # type: ignore[arg-type]
+    assert isinstance(wx_rerank, WatsonxRerank)
+
+
+def test_01_rerank_init_with_client() -> None:
+    wx_client = APIClient(
+        credentials={
+            "url": URL,
+            "apikey": WX_APIKEY,
+        }
+    )
+    wx_rerank = WatsonxRerank(
+        model_id=MODEL_ID, project_id=WX_PROJECT_ID, watsonx_client=wx_client
+    )
+    assert isinstance(wx_rerank, WatsonxRerank)
+
+
+def test_02_rerank_documents() -> None:
+    wx_rerank = WatsonxRerank(model_id=MODEL_ID, url=URL, project_id=WX_PROJECT_ID)  # type: ignore[arg-type]
+    test_documents = [
+        Document(page_content="This is a test document."),
+        Document(page_content="Another test document."),
+    ]
+    test_query = "Test query"
+    results = wx_rerank.rerank(test_documents, test_query)
+    assert len(results) == 2
+
+
+def test_02_rerank_documents_with_params() -> None:
+    params = RerankParameters(truncate_input_tokens=1)
+    test_documents = [
+        Document(page_content="This is a test document."),
+    ]
+    test_query = "Test query"
+
+    wx_rerank = WatsonxRerank(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+    )
+
+    results_1 = wx_rerank.rerank(test_documents, test_query)
+    assert len(results_1) == 1
+
+    results_2 = wx_rerank.rerank(test_documents, test_query, params=params)
+    assert len(results_2) == 1
+
+    assert results_1[0]["relevance_score"] != results_2[0]["relevance_score"]
+
+
+def test_03_compress_documents() -> None:
+    wx_rerank = WatsonxRerank(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+    )
+    doc_list = [
+        "The Mediterranean diet emphasizes fish, olive oil, and vegetables"
+        ", believed to reduce chronic diseases.",
+        "Photosynthesis in plants converts light energy into glucose and "
+        "produces essential oxygen.",
+        "20th-century innovations, from radios to smartphones, centered "
+        "on electronic advancements.",
+        "Rivers provide water, irrigation, and habitat for aquatic species, "
+        "vital for ecosystems.",
+        "Apple’s conference call to discuss fourth fiscal quarter results and "
+        "business updates is scheduled for Thursday, November 2, 2023 at 2:00 "
+        "p.m. PT / 5:00 p.m. ET.",
+        "Shakespeare's works, like 'Hamlet' and 'A Midsummer Night's Dream,' "
+        "endure in literature.",
+    ]
+    documents = [Document(page_content=x) for x in doc_list]
+
+    result = wx_rerank.compress_documents(
+        query="When is the Apple's conference call scheduled?", documents=documents
+    )
+    assert len(doc_list) == len(result)
+
+
+def test_04_compress_documents_with_param() -> None:
+    params_1 = RerankParameters(
+        truncate_input_tokens=1, return_options=RerankReturnOptions(inputs=True)
+    )
+    params_2 = RerankParameters(truncate_input_tokens=2)
+    wx_rerank = WatsonxRerank(
+        model_id=MODEL_ID,
+        url=URL,  # type: ignore[arg-type]
+        project_id=WX_PROJECT_ID,
+        params=params_1,
+    )
+    doc_list = [
+        "The Mediterranean diet emphasizes fish, olive oil, and vegetables"
+        ", believed to reduce chronic diseases.",
+        "Photosynthesis in plants converts light energy into glucose and "
+        "produces essential oxygen.",
+        "20th-century innovations, from radios to smartphones, centered "
+        "on electronic advancements.",
+        "Rivers provide water, irrigation, and habitat for aquatic species, "
+        "vital for ecosystems.",
+        "Apple’s conference call to discuss fourth fiscal quarter results and "
+        "business updates is scheduled for Thursday, November 2, 2023 at 2:00 "
+        "p.m. PT / 5:00 p.m. ET.",
+        "Shakespeare's works, like 'Hamlet' and 'A Midsummer Night's Dream,' "
+        "endure in literature.",
+    ]
+    documents = [Document(page_content=x) for x in doc_list]
+
+    result_1 = wx_rerank.compress_documents(
+        query="When is the Apple's conference call scheduled?", documents=documents
+    )
+    assert len(doc_list) == len(result_1)
+    result_2 = wx_rerank.compress_documents(
+        query="When is the Apple's conference call scheduled?",
+        documents=documents,
+        params=params_2,
+    )
+    assert len(doc_list) == len(result_2)
+
+    assert [
+        el.metadata["relevance_score"]
+        for el in result_1
+        if el.page_content.startswith("20th")
+    ][0] != [
+        el.metadata["relevance_score"]
+        for el in result_2
+        if el.page_content.startswith("20th")
+    ][0]
diff --git a/libs/ibm/tests/unit_tests/test_embeddings_standard.py b/libs/ibm/tests/unit_tests/test_embeddings_standard.py
new file mode 100644
index 0000000..7181d90
--- /dev/null
+++ b/libs/ibm/tests/unit_tests/test_embeddings_standard.py
@@ -0,0 +1,28 @@
+from typing import Type
+
+from ibm_watsonx_ai import APIClient, Credentials  # type: ignore
+from ibm_watsonx_ai.service_instance import ServiceInstance  # type: ignore
+from langchain_standard_tests.unit_tests.embeddings import EmbeddingsUnitTests
+
+from langchain_ibm import WatsonxEmbeddings
+
+client = APIClient.__new__(APIClient)
+client.CLOUD_PLATFORM_SPACES = True
+client.ICP_PLATFORM_SPACES = True
+credentials = Credentials(api_key="api_key")
+client.credentials = credentials
+client.service_instance = ServiceInstance.__new__(ServiceInstance)
+client.service_instance._credentials = credentials
+
+
+class TestWatsonxEmbeddingsStandard(EmbeddingsUnitTests):
+    @property
+    def embeddings_class(self) -> Type[WatsonxEmbeddings]:
+        return WatsonxEmbeddings
+
+    @property
+    def embedding_model_params(self) -> dict:
+        return {
+            "model_id": "ibm/granite-13b-instruct-v2",
+            "watsonx_client": client,
+        }
diff --git a/libs/ibm/tests/unit_tests/test_imports.py b/libs/ibm/tests/unit_tests/test_imports.py
index 7bdeb32..bd4594d 100644
--- a/libs/ibm/tests/unit_tests/test_imports.py
+++ b/libs/ibm/tests/unit_tests/test_imports.py
@@ -1,6 +1,6 @@
 from langchain_ibm import __all__
 
-EXPECTED_ALL = ["WatsonxLLM", "WatsonxEmbeddings", "ChatWatsonx"]
+EXPECTED_ALL = ["WatsonxLLM", "WatsonxEmbeddings", "ChatWatsonx", "WatsonxRerank"]
 
 
 def test_all_imports() -> None:
diff --git a/libs/ibm/tests/unit_tests/test_rerank.py b/libs/ibm/tests/unit_tests/test_rerank.py
new file mode 100644
index 0000000..38b58ca
--- /dev/null
+++ b/libs/ibm/tests/unit_tests/test_rerank.py
@@ -0,0 +1,84 @@
+"""Test WatsonxLLM API wrapper."""
+
+import os
+
+from langchain_ibm import WatsonxRerank
+
+os.environ.pop("WATSONX_APIKEY", None)
+os.environ.pop("WATSONX_PROJECT_ID", None)
+
+MODEL_ID = "sample_rerank_model"
+
+
+def test_initialize_watsonxllm_bad_path_without_url() -> None:
+    try:
+        WatsonxRerank(
+            model_id=MODEL_ID,
+        )
+    except ValueError as e:
+        assert "url" in e.__str__()
+        assert "WATSONX_URL" in e.__str__()
+
+
+def test_initialize_watsonxllm_cloud_bad_path() -> None:
+    try:
+        WatsonxRerank(model_id=MODEL_ID, url="https://us-south.ml.cloud.ibm.com")  # type: ignore[arg-type]
+    except ValueError as e:
+        assert "apikey" in e.__str__()
+        assert "WATSONX_APIKEY" in e.__str__()
+
+
+def test_initialize_watsonxllm_cpd_bad_path_without_all() -> None:
+    try:
+        WatsonxRerank(
+            model_id=MODEL_ID,
+            url="https://cpd-zen.apps.cpd48.cp.fyre.ibm.com",  # type: ignore[arg-type]
+        )
+    except ValueError as e:
+        assert (
+            "apikey" in e.__str__()
+            and "password" in e.__str__()
+            and "token" in e.__str__()
+        )
+        assert (
+            "WATSONX_APIKEY" in e.__str__()
+            and "WATSONX_PASSWORD" in e.__str__()
+            and "WATSONX_TOKEN" in e.__str__()
+        )
+
+
+def test_initialize_watsonxllm_cpd_bad_path_password_without_username() -> None:
+    try:
+        WatsonxRerank(
+            model_id=MODEL_ID,
+            url="https://cpd-zen.apps.cpd48.cp.fyre.ibm.com",  # type: ignore[arg-type]
+            password="test_password",  # type: ignore[arg-type]
+        )
+    except ValueError as e:
+        assert "username" in e.__str__()
+        assert "WATSONX_USERNAME" in e.__str__()
+
+
+def test_initialize_watsonxllm_cpd_bad_path_apikey_without_username() -> None:
+    try:
+        WatsonxRerank(
+            model_id=MODEL_ID,
+            url="https://cpd-zen.apps.cpd48.cp.fyre.ibm.com",  # type: ignore[arg-type]
+            apikey="test_apikey",  # type: ignore[arg-type]
+        )
+    except ValueError as e:
+        assert "username" in e.__str__()
+        assert "WATSONX_USERNAME" in e.__str__()
+
+
+def test_initialize_watsonxllm_cpd_bad_path_without_instance_id() -> None:
+    try:
+        WatsonxRerank(
+            model_id=MODEL_ID,
+            url="https://cpd-zen.apps.cpd48.cp.fyre.ibm.com",  # type: ignore[arg-type]
+            apikey="test_apikey",  # type: ignore[arg-type]
+            username="test_user",  # type: ignore[arg-type]
+        )
+    except ValueError as e:
+        assert "instance_id" in e.__str__()
+        assert "WATSONX_INSTANCE_ID" in e.__str__()