diff --git a/.env.example b/.env.example
index 66f0daf..fbbe996 100644
--- a/.env.example
+++ b/.env.example
@@ -1,3 +1,4 @@
 # For functional testing
 OPENAI_API_KEY=""
-ANTHROPIC_API_KEY=""
\ No newline at end of file
+ANTHROPIC_API_KEY=""
+GROQ_API_KEY=""
\ No newline at end of file
diff --git a/README.md b/README.md
index 8e3172a..24de874 100644
--- a/README.md
+++ b/README.md
@@ -6,7 +6,9 @@ A `FastAPI` + `Langchain` / `langgraph` extension to expose agent result as an O
 
 Use any OpenAI-compatible UI or UI framework with your custom `Langchain Agent`.
 
-Support:
+### Support:
+
+#### OpenAI API features:
 
 - ✅ [Chat Completions API](https://platform.openai.com/docs/api-reference/chat)
   - ✅ Invoke
@@ -19,6 +21,12 @@ Support:
   - ✅ Tools step stream
   - 🚧 Human In The Loop
 
+#### Vendors features:
+
+- ✅ OpenAI
+- ✅ Anthropic
+- ✅ Groq (excluding multimodal)
+
 If you find this project useful, please give it a star ⭐!
 
 ## Table of Content
diff --git a/langchain_openai_api_bridge/chat_model_adapter/default_openai_compatible_chat_model_adapter.py b/langchain_openai_api_bridge/chat_model_adapter/default_openai_compatible_chat_model_adapter.py
new file mode 100644
index 0000000..c7899ba
--- /dev/null
+++ b/langchain_openai_api_bridge/chat_model_adapter/default_openai_compatible_chat_model_adapter.py
@@ -0,0 +1,19 @@
+from abc import abstractmethod
+from typing import List, Union
+from langchain_core.messages import BaseMessage
+
+from langchain_openai_api_bridge.chat_model_adapter.base_openai_compatible_chat_model_adapter import (
+    BaseOpenAICompatibleChatModelAdapter,
+)
+
+
+class DefaultOpenAICompatibleChatModelAdapter(BaseOpenAICompatibleChatModelAdapter):
+
+    @abstractmethod
+    def is_compatible(self, llm_type: str):
+        return True
+
+    def to_openai_format_messages(
+        self, messages: Union[List[BaseMessage], List[List[BaseMessage]]]
+    ):
+        return messages
diff --git a/langchain_openai_api_bridge/chat_model_adapter/openai_compatible_chat_model.py b/langchain_openai_api_bridge/chat_model_adapter/openai_compatible_chat_model.py
index 60c6f83..8ba8d7c 100644
--- a/langchain_openai_api_bridge/chat_model_adapter/openai_compatible_chat_model.py
+++ b/langchain_openai_api_bridge/chat_model_adapter/openai_compatible_chat_model.py
@@ -3,6 +3,11 @@
 from langchain_core.language_models import BaseChatModel
 from langchain_core.pydantic_v1 import root_validator
 
+from langchain_openai_api_bridge.chat_model_adapter.default_openai_compatible_chat_model_adapter import (
+    DefaultOpenAICompatibleChatModelAdapter,
+)
+
+
 from .anthropic_openai_compatible_chat_model_adapter import (
     AnthropicOpenAICompatibleChatModelAdapter,
 )
@@ -10,7 +15,9 @@
     BaseOpenAICompatibleChatModelAdapter,
 )
 
-default_adapters = [AnthropicOpenAICompatibleChatModelAdapter()]
+default_adapters = [
+    AnthropicOpenAICompatibleChatModelAdapter(),
+]
 
 
 class OpenAICompatibleChatModel(BaseChatModel):
@@ -20,12 +27,16 @@ class OpenAICompatibleChatModel(BaseChatModel):
 
     @root_validator()
     def set_adapter(cls, values):
-        adapter = values.get(
-            "adapter",
-            OpenAICompatibleChatModel._find_adatper(
-                values.get("chat_model"), values.get("adapters", default_adapters)
-            ),
-        )
+        adapter = values.get("adapter")
+
+        if adapter is None:
+            chat_model = values.get("chat_model")
+            adapters = values.get("adapters", default_adapters)
+            adapter = OpenAICompatibleChatModel._find_adatper(chat_model, adapters)
+
+        if adapter is None:
+            raise ValueError("Could not find an adapter for the given chat model")
+
         values["adapter"] = adapter
 
         return values
@@ -43,7 +54,7 @@ def _stream(self, messages, stop, run_manager, **kwargs):
             messages=messages, stop=stop, run_manager=run_manager, **kwargs
         )
 
-    def _astream(self, messages, stop, run_manager, **kwargs):
+    async def _astream(self, messages, stop, run_manager, **kwargs):
         return self.chat_model._astream(
             messages=messages, stop=stop, run_manager=run_manager, **kwargs
         )
@@ -74,4 +85,4 @@ def _find_adatper(
             if adapter.is_compatible(llm_type):
                 return adapter
 
-        raise ValueError(f"Could not find an adapter for {llm_type}")
+        return DefaultOpenAICompatibleChatModelAdapter()
diff --git a/poetry.lock b/poetry.lock
index 1628f64..e25c8dd 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -715,6 +715,25 @@ files = [
 docs = ["Sphinx", "furo"]
 test = ["objgraph", "psutil"]
 
+[[package]]
+name = "groq"
+version = "0.9.0"
+description = "The official Python library for the groq API"
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "groq-0.9.0-py3-none-any.whl", hash = "sha256:d0e46f4ad645504672bb09c8100af3ced3a7db0d5119dc13e4aca535fc455874"},
+    {file = "groq-0.9.0.tar.gz", hash = "sha256:130ed5e35d3acfaab46b9e7a078eeaebf91052f4a9d71f86f87fb319b5fec332"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+typing-extensions = ">=4.7,<5"
+
 [[package]]
 name = "h11"
 version = "0.14.0"
@@ -1066,6 +1085,21 @@ pydantic = [
 PyYAML = ">=5.3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
+[[package]]
+name = "langchain-groq"
+version = "0.1.6"
+description = "An integration package connecting Groq and LangChain"
+optional = true
+python-versions = "<4.0,>=3.8.1"
+files = [
+    {file = "langchain_groq-0.1.6-py3-none-any.whl", hash = "sha256:c7e91f8a333299b25dad5e8c3bc555cc579560431247ac8e0c3d2705dd7411f8"},
+    {file = "langchain_groq-0.1.6.tar.gz", hash = "sha256:ecd3aac54e5e454633f3920a11d093dcb425c18830f721cc86e69e5acfbe7c85"},
+]
+
+[package.dependencies]
+groq = ">=0.4.1,<1"
+langchain-core = ">=0.2.2,<0.3"
+
 [[package]]
 name = "langchain-openai"
 version = "0.1.15"
@@ -2815,11 +2849,12 @@ idna = ">=2.0"
 multidict = ">=4.0"
 
 [extras]
+anthropic = ["langchain-anthropic"]
+groq = ["langchain-groq"]
 langchain = ["langchain", "langchain-openai", "langgraph"]
-langchain-anthropic = ["langchain-anthropic"]
 langchain-serve = ["fastapi", "python-dotenv"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<4.0"
-content-hash = "367382a3138461436bac423d6a23f918c3f1d6f82edae44674c1c6d3489daa77"
+content-hash = "2563664ba320e554f0cfe306c0cb5f8797cae6cd7f26e7bdea96ca0c4ef322bb"
diff --git a/pyproject.toml b/pyproject.toml
index 0aa9b0b..3304d2d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,6 +17,7 @@ fastapi = { version = "^0.111.0", optional = true }
 python-dotenv = { version = "^1.0.1", optional = true }
 langgraph = { version = "^0.0.62", optional = true }
 langchain-anthropic = { version = "^0.1.19", optional = true }
+langchain-groq = { version = "^0.1.6", optional = true }
 
 [tool.poetry.group.dev.dependencies]
 flake8 = "^7.0.0"
@@ -33,7 +34,8 @@ fastapi-injector = { version = "^0.6.0", python = ">=3.9,<3.13" }
 
 [tool.poetry.extras]
 langchain = ["langchain", "langchain-openai", "langgraph"]
-langchain-anthropic = ["langchain-anthropic"]
+anthropic = ["langchain-anthropic"]
+groq = ["langchain-groq"]
 langchain_serve = ["fastapi", "python-dotenv"]
 
 
diff --git a/tests/test_functional/fastapi_assistant_agent_anthropic/README.md b/tests/test_functional/fastapi_assistant_agent_anthropic/README.md
index cc65074..7da8540 100644
--- a/tests/test_functional/fastapi_assistant_agent_anthropic/README.md
+++ b/tests/test_functional/fastapi_assistant_agent_anthropic/README.md
@@ -2,13 +2,26 @@
 
 The default `from langchain_anthropic import ChatAnthropic` is not compatible with multimodal prompts as the image format differs between OpenAI and Anthropic.
 
-To use multimodal prompts, use the `OpenAICompatibleAnthropicChatModel` adapter (from `langchain_openai_api_bridge.chat_model_adapter`) which transforms OpenAI format to Anthropic format. This enables you to use one or the other seamlessly.
+To use multimodal prompts, use the `OpenAICompatibleChatModel` which transforms OpenAI format to Anthropic format. This enables you to use one or the other seamlessly.
 Look at `my_anthropic_agent_factory.py` for usage example.
 
-#### Multimodal Formats
+```python
+chat_model = ChatAnthropic(
+    model="claude-3-5-sonnet-20240620",
+    max_tokens=1024,
+    streaming=True,
+)
+
+return OpenAICompatibleChatModel(chat_model=chat_model)
+
+```
+
+#### Multimodal Formats differences
 
 ##### Anthropic
 
+https://docs.anthropic.com/en/docs/build-with-claude/vision#about-the-prompt-examples
+
 ```python
 {
     "role": "user",
diff --git a/tests/test_functional/fastapi_assistant_agent_groq/README.md b/tests/test_functional/fastapi_assistant_agent_groq/README.md
new file mode 100644
index 0000000..26fd714
--- /dev/null
+++ b/tests/test_functional/fastapi_assistant_agent_groq/README.md
@@ -0,0 +1,21 @@
+# Expose as an OpenAI API Groq assistant (Assistant API)
+
+:warning: Groq does not support streaming with tools. Make sure to set `streaming=False,`
+
+```python
+chat_model = ChatGroq(
+    model="llama3-8b-8192",
+    streaming=False, # <<--- Must be set to False when used with LangGraph / Tools
+)
+```
+
+:warning: Note that Groq models do not currently support multi-modal capabilities. Do not use payload with image reference
+
+```python
+{
+    "type": "image_url",
+    "image_url": {
+        "url": "data:image/jpeg;base64,iVBORw0KGgo="
+    },
+},
+```
diff --git a/tests/test_functional/fastapi_assistant_agent_groq/assistant_server_groq.py b/tests/test_functional/fastapi_assistant_agent_groq/assistant_server_groq.py
new file mode 100644
index 0000000..07b383c
--- /dev/null
+++ b/tests/test_functional/fastapi_assistant_agent_groq/assistant_server_groq.py
@@ -0,0 +1,52 @@
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi import FastAPI
+from dotenv import load_dotenv, find_dotenv
+import uvicorn
+
+from langchain_openai_api_bridge.assistant import (
+    InMemoryMessageRepository,
+    InMemoryRunRepository,
+    InMemoryThreadRepository,
+)
+from langchain_openai_api_bridge.fastapi.langchain_openai_api_bridge_fastapi import (
+    LangchainOpenaiApiBridgeFastAPI,
+)
+from tests.test_functional.fastapi_assistant_agent_groq.my_groq_agent_factory import (
+    MyGroqAgentFactory,
+)
+
+_ = load_dotenv(find_dotenv())
+
+
+app = FastAPI(
+    title="Langchain Agent OpenAI API Bridge",
+    version="1.0",
+    description="OpenAI API exposing langchain agent",
+)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+    expose_headers=["*"],
+)
+
+in_memory_thread_repository = InMemoryThreadRepository()
+in_memory_message_repository = InMemoryMessageRepository()
+in_memory_run_repository = InMemoryRunRepository()
+
+bridge = LangchainOpenaiApiBridgeFastAPI(
+    app=app, agent_factory_provider=lambda: MyGroqAgentFactory()
+)
+bridge.bind_openai_assistant_api(
+    thread_repository_provider=in_memory_thread_repository,
+    message_repository_provider=in_memory_message_repository,
+    run_repository_provider=in_memory_run_repository,
+    prefix="/my-groq-assistant",
+)
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="localhost")
diff --git a/tests/test_functional/fastapi_assistant_agent_groq/my_groq_agent_factory.py b/tests/test_functional/fastapi_assistant_agent_groq/my_groq_agent_factory.py
new file mode 100644
index 0000000..048977d
--- /dev/null
+++ b/tests/test_functional/fastapi_assistant_agent_groq/my_groq_agent_factory.py
@@ -0,0 +1,35 @@
+from langchain_groq import ChatGroq
+from langchain_openai_api_bridge.chat_model_adapter import (
+    OpenAICompatibleChatModel,
+)
+from langchain_openai_api_bridge.core.agent_factory import AgentFactory
+from langgraph.graph.graph import CompiledGraph
+from langchain_core.language_models import BaseChatModel
+from langchain_core.tools import tool
+from langgraph.prebuilt import create_react_agent
+
+from langchain_openai_api_bridge.core.create_agent_dto import CreateAgentDto
+
+
+@tool
+def magic_number_tool(input: int) -> int:
+    """Applies a magic function to an input."""
+    return input + 2
+
+
+class MyGroqAgentFactory(AgentFactory):
+
+    def create_agent(self, llm: BaseChatModel, dto: CreateAgentDto) -> CompiledGraph:
+        return create_react_agent(
+            llm,
+            [magic_number_tool],
+            messages_modifier="""You are a helpful assistant.""",
+        )
+
+    def create_llm(self, dto: CreateAgentDto) -> CompiledGraph:
+        chat_model = ChatGroq(
+            model=dto.model,
+            streaming=False,
+        )
+
+        return OpenAICompatibleChatModel(chat_model=chat_model)
diff --git a/tests/test_functional/fastapi_assistant_agent_groq/test_assistant_server_groq.py b/tests/test_functional/fastapi_assistant_agent_groq/test_assistant_server_groq.py
new file mode 100644
index 0000000..58b0c39
--- /dev/null
+++ b/tests/test_functional/fastapi_assistant_agent_groq/test_assistant_server_groq.py
@@ -0,0 +1,47 @@
+import pytest
+from openai import OpenAI
+
+from fastapi.testclient import TestClient
+from assistant_server_groq import app
+from tests.test_functional.assistant_stream_utils import (
+    assistant_stream_events_to_str_response,
+)
+
+
+test_api = TestClient(app)
+
+
+@pytest.fixture(scope="session")
+def openai_client():
+    return OpenAI(
+        base_url="http://testserver/my-groq-assistant/openai/v1",
+        http_client=test_api,
+    )
+
+
+class TestGroqAssistant:
+
+    def test_run_stream_message_deltas(
+        self,
+        openai_client: OpenAI,
+    ):
+        thread = openai_client.beta.threads.create(
+            messages=[
+                {
+                    "role": "user",
+                    "content": "Hello!",
+                },
+            ]
+        )
+
+        stream = openai_client.beta.threads.runs.create(
+            thread_id=thread.id,
+            model="llama3-8b-8192",
+            assistant_id="any",
+            stream=True,
+            temperature=0,
+        )
+
+        str_response = assistant_stream_events_to_str_response(stream)
+
+        assert len(str_response) > 0