diff --git a/.github/workflows/test-action.yml b/.github/workflows/test-action.yml
new file mode 100644
index 000000000000..16e6a672e38f
--- /dev/null
+++ b/.github/workflows/test-action.yml
@@ -0,0 +1,19 @@
+name: Test main.py
+on:
+  push:
+  pull_request:
+    branches: [ main ]
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    services:
+      docker:
+        image: docker:19.03.12
+        options: --privileged
+    steps:
+    - uses: actions/checkout@v4
+    - name: Run main.py with fake model
+      run: |
+        export SANDBOX_CONTAINER_IMAGE="ubuntu:24.04"
+        python -m pip install -r requirements.txt
+        PYTHONPATH=`pwd` python ./opendevin/main.py -d ./ -t "write a hello world script" --model-name=fake
diff --git a/agenthub/codeact_agent/__init__.py b/agenthub/codeact_agent/__init__.py
index 8b925723b623..a8ac1753382b 100644
--- a/agenthub/codeact_agent/__init__.py
+++ b/agenthub/codeact_agent/__init__.py
@@ -9,10 +9,6 @@
 from opendevin.lib.command_manager import CommandManager
 from opendevin.sandbox.sandbox import DockerInteractive
 
-assert (
-    "OPENAI_API_KEY" in os.environ
-), "Please set the OPENAI_API_KEY environment variable."
-
 
 
 SYSTEM_MESSAGE = """You are a helpful assistant. You will be provided access (as root) to a bash shell to complete user-provided tasks.
@@ -64,7 +60,12 @@ def __init__(
         - instruction (str): The instruction for the agent to execute.
         - max_steps (int): The maximum number of steps to run the agent.
         """
+        assert (
+            "OPENAI_API_KEY" in os.environ
+        ), "Please set the OPENAI_API_KEY environment variable."
+
         super().__init__(instruction, workspace_dir, max_steps)
+
         self._history = [Message(Role.SYSTEM, SYSTEM_MESSAGE)]
         self._history.append(Message(Role.USER, instruction))
         self.env = DockerInteractive(workspace_dir=workspace_dir)
diff --git a/agenthub/langchains_agent/utils/agent.py b/agenthub/langchains_agent/utils/agent.py
index 2c310a61fa49..b454d7008bb9 100644
--- a/agenthub/langchains_agent/utils/agent.py
+++ b/agenthub/langchains_agent/utils/agent.py
@@ -11,7 +11,7 @@ def __init__(self, task, model_name):
         self.task = task
         self.model_name = model_name
         self.monologue = Monologue(model_name)
-        self.memory = LongTermMemory()
+        self.memory = LongTermMemory(local_embeddings=(model_name == 'fake'))
 
     def add_event(self, event):
         if 'output' in event.args:
@@ -22,6 +22,8 @@ def add_event(self, event):
             self.monologue.condense()
 
     def get_next_action(self, cmd_mgr):
+        if self.model_name == 'fake':
+            return Event('finish', {})
         action_dict = llm.request_action(
             self.task,
             self.monologue.get_thoughts(),
diff --git a/agenthub/langchains_agent/utils/llm.py b/agenthub/langchains_agent/utils/llm.py
index 98475e3cedaf..29318811a73a 100644
--- a/agenthub/langchains_agent/utils/llm.py
+++ b/agenthub/langchains_agent/utils/llm.py
@@ -96,7 +96,8 @@ class NewMonologue(BaseModel):
     new_monologue: List[Action]
 
 def get_chain(template, model_name):
-    assert "OPENAI_API_KEY" in os.environ, "Please set the OPENAI_API_KEY environment variable to use langchains_agent."
+    if model_name != "fake":
+        assert "OPENAI_API_KEY" in os.environ, "Please set the OPENAI_API_KEY environment variable to use langchains_agent."
     llm = ChatOpenAI(openai_api_key=os.getenv("OPENAI_API_KEY"), model_name=model_name)
     prompt = PromptTemplate.from_template(template)
     llm_chain = LLMChain(prompt=prompt, llm=llm)
diff --git a/agenthub/langchains_agent/utils/memory.py b/agenthub/langchains_agent/utils/memory.py
index c73bc613e95d..88e0e23dfa6e 100644
--- a/agenthub/langchains_agent/utils/memory.py
+++ b/agenthub/langchains_agent/utils/memory.py
@@ -8,11 +8,15 @@
 from llama_index.vector_stores.chroma import ChromaVectorStore
 
 class LongTermMemory:
-    def __init__(self):
+    def __init__(self, local_embeddings=False):
         db = chromadb.Client()
         self.collection = db.get_or_create_collection(name="memories")
         vector_store = ChromaVectorStore(chroma_collection=self.collection)
-        self.index = VectorStoreIndex.from_vector_store(vector_store)
+        storage_context = StorageContext.from_defaults(vector_store=vector_store)
+        if local_embeddings:
+            self.index = VectorStoreIndex.from_vector_store(vector_store, embed_model='local')
+        else:
+            self.index = VectorStoreIndex.from_vector_store(vector_store)
         self.thought_idx = 0
 
     def add_event(self, event):
diff --git a/requirements.txt b/requirements.txt
index a012a665b901..cfec06116943 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -14,4 +14,5 @@ langchain-openai
 langchain-community
 llama-index
 llama-index-vector-stores-chroma
-chromadb
\ No newline at end of file
+llama-index-embeddings-huggingface
+chromadb