diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
deleted file mode 100644
index b56e9db1..00000000
--- a/.github/workflows/tests.yml
+++ /dev/null
@@ -1,86 +0,0 @@
-name: Unit Tests
-
-env:
-  OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-  COMPOSIO_API_KEY: ${{ secrets.COMPOSIO_API_KEY }}
-  ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-  GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
-  GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
-  E2B_API_KEY: ${{ secrets.E2B_API_KEY }}
-  E2B_SANDBOX_TEMPLATE_ID: ${{ secrets.E2B_SANDBOX_TEMPLATE_ID }}
-
-on:
-  push:
-    branches: [ main ]
-  pull_request:
-
-jobs:
-  unit-run:
-    runs-on: ubuntu-latest
-    timeout-minutes: 15
-    strategy:
-      fail-fast: false
-      matrix:
-        test_suite:
-          - "test_vector_embeddings.py"
-          - "test_client.py"
-          - "test_client_legacy.py"
-          - "test_server.py"
-          - "test_v1_routes.py"
-          - "test_local_client.py"
-          - "test_managers.py"
-          - "test_base_functions.py"
-          - "test_tool_schema_parsing.py"
-          - "test_tool_rule_solver.py"
-          - "test_memory.py"
-          - "test_utils.py"
-          - "test_stream_buffer_readers.py"
-    services:
-      qdrant:
-        image: qdrant/qdrant
-        ports:
-          - 6333:6333
-      postgres:
-        image: pgvector/pgvector:pg17
-        ports:
-          - 5432:5432
-        env:
-          POSTGRES_HOST_AUTH_METHOD: trust
-          POSTGRES_DB: postgres
-          POSTGRES_USER: postgres
-        options: >-
-          --health-cmd pg_isready
-          --health-interval 10s
-          --health-timeout 5s
-          --health-retries 5
-
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v4
-
-      - name: Setup Python, Poetry, and Dependencies
-        uses: packetcoders/action-setup-cache-python-poetry@main
-        with:
-          python-version: "3.12"
-          poetry-version: "1.8.2"
-          install-args: "-E dev -E postgres -E external-tools -E tests -E cloud-tool-sandbox"
-      - name: Migrate database
-        env:
-          LETTA_PG_PORT: 5432
-          LETTA_PG_USER: postgres
-          LETTA_PG_PASSWORD: postgres
-          LETTA_PG_DB: postgres
-          LETTA_PG_HOST: localhost
-        run: |
-          psql -h localhost -U postgres -d postgres -c 'CREATE EXTENSION vector'
-          poetry run alembic upgrade head
-      - name: Run core unit tests
-        env:
-          LETTA_PG_PORT: 5432
-          LETTA_PG_USER: postgres
-          LETTA_PG_PASSWORD: postgres
-          LETTA_PG_DB: postgres
-          LETTA_PG_HOST: localhost
-          LETTA_SERVER_PASS: test_server_token
-        run: |
-          poetry run pytest -s -vv tests/${{ matrix.test_suite }}
diff --git a/letta/__init__.py b/letta/__init__.py
index 8fce88dc..98bc9f06 100644
--- a/letta/__init__.py
+++ b/letta/__init__.py
@@ -1,5 +1,4 @@
-__version__ = "0.6.13"
-
+__version__ = "0.6.23"
 
 # import clients
 from letta.client.client import LocalClient, RESTClient, create_client
diff --git a/letta/agent.py b/letta/agent.py
index 9b93708d..9a8ce758 100644
--- a/letta/agent.py
+++ b/letta/agent.py
@@ -260,6 +260,7 @@ class Agent(BaseAgent):
         error_msg: str,
         tool_call_id: str,
         function_name: str,
+        function_args: dict,
         function_response: str,
         messages: List[Message],
         include_function_failed_message: bool = False,
@@ -394,6 +395,7 @@ class Agent(BaseAgent):
 
         messages = []  # append these to the history when done
         function_name = None
+        function_args = {}
 
         # Step 2: check if LLM wanted to call a function
         if response_message.function_call or (response_message.tool_calls is not None and len(response_message.tool_calls) > 0):
@@ -431,6 +433,7 @@ class Agent(BaseAgent):
                     openai_message_dict=response_message.model_dump(),
                 )
             )  # extend conversation with assistant's reply
+            self.logger.info(f"Function call message: {messages[-1]}")
 
             nonnull_content = False
             if response_message.content:
@@ -445,6 +448,7 @@ class Agent(BaseAgent):
                 response_message.function_call if response_message.function_call is not None else response_message.tool_calls[0].function
             )
             function_name = function_call.name
+            self.logger.info(f"Request to call function {function_name} with tool_call_id: {tool_call_id}")
 
             # Failure case 1: function name is wrong (not in agent_state.tools)
             target_letta_tool = None
@@ -455,7 +459,9 @@ class Agent(BaseAgent):
             if not target_letta_tool:
                 error_msg = f"No function named {function_name}"
                 function_response = "None"  # more like "never ran?"
-                messages = self._handle_function_error_response(error_msg, tool_call_id, function_name, function_response, messages)
+                messages = self._handle_function_error_response(
+                    error_msg, tool_call_id, function_name, function_args, function_response, messages
+                )
                 return messages, False, True  # force a heartbeat to allow agent to handle error
 
             # Failure case 2: function name is OK, but function args are bad JSON
@@ -465,7 +471,9 @@ class Agent(BaseAgent):
             except Exception:
                 error_msg = f"Error parsing JSON for function '{function_name}' arguments: {function_call.arguments}"
                 function_response = "None"  # more like "never ran?"
-                messages = self._handle_function_error_response(error_msg, tool_call_id, function_name, function_response, messages)
+                messages = self._handle_function_error_response(
+                    error_msg, tool_call_id, function_name, function_args, function_response, messages
+                )
                 return messages, False, True  # force a heartbeat to allow agent to handle error
 
             # Check if inner thoughts is in the function call arguments (possible apparently if you are using Azure)
@@ -502,7 +510,7 @@ class Agent(BaseAgent):
 
                 if sandbox_run_result and sandbox_run_result.status == "error":
                     messages = self._handle_function_error_response(
-                        function_response, tool_call_id, function_name, function_response, messages
+                        function_response, tool_call_id, function_name, function_args, function_response, messages
                     )
                     return messages, False, True  # force a heartbeat to allow agent to handle error
 
@@ -531,7 +539,7 @@ class Agent(BaseAgent):
                 error_msg_user = f"{error_msg}\n{traceback.format_exc()}"
                 self.logger.error(error_msg_user)
                 messages = self._handle_function_error_response(
-                    error_msg, tool_call_id, function_name, function_response, messages, include_function_failed_message=True
+                    error_msg, tool_call_id, function_name, function_args, function_response, messages, include_function_failed_message=True
                 )
                 return messages, False, True  # force a heartbeat to allow agent to handle error
 
@@ -539,7 +547,7 @@ class Agent(BaseAgent):
             if function_response_string.startswith(ERROR_MESSAGE_PREFIX):
                 error_msg = function_response_string
                 messages = self._handle_function_error_response(
-                    error_msg, tool_call_id, function_name, function_response, messages, include_function_failed_message=True
+                    error_msg, tool_call_id, function_name, function_args, function_response, messages, include_function_failed_message=True
                 )
                 return messages, False, True  # force a heartbeat to allow agent to handle error
 
diff --git a/letta/cli/cli.py b/letta/cli/cli.py
index 4441190b..6dd4e609 100644
--- a/letta/cli/cli.py
+++ b/letta/cli/cli.py
@@ -15,7 +15,6 @@ from letta.local_llm.constants import ASSISTANT_MESSAGE_CLI_SYMBOL
 from letta.log import get_logger
 from letta.schemas.enums import OptionState
 from letta.schemas.memory import ChatMemory, Memory
-from letta.server.server import logger as server_logger
 
 # from letta.interface import CLIInterface as interface  # for printing to terminal
 from letta.streaming_interface import StreamingRefreshCLIInterface as interface  # for printing to terminal
@@ -119,6 +118,8 @@ def run(
     utils.DEBUG = debug
     # TODO: add logging command line options for runtime log level
 
+    from letta.server.server import logger as server_logger
+
     if debug:
         logger.setLevel(logging.DEBUG)
         server_logger.setLevel(logging.DEBUG)
@@ -360,4 +361,4 @@ def delete_agent(
 def version() -> str:
     import letta
 
-    return letta.__version__
+    print(letta.__version__)
diff --git a/letta/embeddings.py b/letta/embeddings.py
index e588f17a..6541cea3 100644
--- a/letta/embeddings.py
+++ b/letta/embeddings.py
@@ -167,6 +167,27 @@ class OllamaEmbeddings:
         return response_json["embedding"]
 
 
+class GoogleEmbeddings:
+    def __init__(self, api_key: str, model: str, base_url: str):
+        self.api_key = api_key
+        self.model = model
+        self.base_url = base_url  # Expected to be "https://generativelanguage.googleapis.com"
+
+    def get_text_embedding(self, text: str):
+        import httpx
+
+        headers = {"Content-Type": "application/json"}
+        # Build the URL based on the provided base_url, model, and API key.
+        url = f"{self.base_url}/v1beta/models/{self.model}:embedContent?key={self.api_key}"
+        payload = {"model": self.model, "content": {"parts": [{"text": text}]}}
+        with httpx.Client() as client:
+            response = client.post(url, headers=headers, json=payload)
+        # Raise an error for non-success HTTP status codes.
+        response.raise_for_status()
+        response_json = response.json()
+        return response_json["embedding"]["values"]
+
+
 def query_embedding(embedding_model, query_text: str):
     """Generate padded embedding for querying database"""
     query_vec = embedding_model.get_text_embedding(query_text)
@@ -237,5 +258,14 @@ def embedding_model(config: EmbeddingConfig, user_id: Optional[uuid.UUID] = None
         )
         return model
 
+    elif endpoint_type == "google_ai":
+        assert all([model_settings.gemini_api_key is not None, model_settings.gemini_base_url is not None])
+        model = GoogleEmbeddings(
+            model=config.embedding_model,
+            api_key=model_settings.gemini_api_key,
+            base_url=model_settings.gemini_base_url,
+        )
+        return model
+
     else:
         raise ValueError(f"Unknown endpoint type {endpoint_type}")
diff --git a/letta/server/rest_api/routers/v1/health.py b/letta/server/rest_api/routers/v1/health.py
index 99fce66d..3b433569 100644
--- a/letta/server/rest_api/routers/v1/health.py
+++ b/letta/server/rest_api/routers/v1/health.py
@@ -2,7 +2,7 @@ from typing import TYPE_CHECKING
 
 from fastapi import APIRouter
 
-from letta.cli.cli import version
+from letta import __version__
 from letta.schemas.health import Health
 
 if TYPE_CHECKING:
@@ -15,6 +15,6 @@ router = APIRouter(prefix="/health", tags=["health"])
 @router.get("/", response_model=Health, operation_id="health_check")
 def health_check():
     return Health(
-        version=version(),
+        version=__version__,
         status="ok",
     )
diff --git a/letta/settings.py b/letta/settings.py
index b8fde2ca..667f7242 100644
--- a/letta/settings.py
+++ b/letta/settings.py
@@ -85,7 +85,7 @@ class ModelSettings(BaseSettings):
 
     # google ai
     gemini_api_key: Optional[str] = None
-
+    gemini_base_url: str = "https://generativelanguage.googleapis.com/"
     # together
     together_api_key: Optional[str] = None
 
diff --git a/poetry.lock b/poetry.lock
index 3aeab197..a03ffeb1 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,98 +2,103 @@
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.4"
+version = "2.4.6"
 description = "Happy Eyeballs for asyncio"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8"},
-    {file = "aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745"},
+    {file = "aiohappyeyeballs-2.4.6-py3-none-any.whl", hash = "sha256:147ec992cf873d74f5062644332c539fcd42956dc69453fe5204195e560517e1"},
+    {file = "aiohappyeyeballs-2.4.6.tar.gz", hash = "sha256:9b05052f9042985d32ecbe4b59a77ae19c006a78f1344d7fdad69d28ded3d0b0"},
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.11.11"
+version = "3.11.12"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.9"
 files = [
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@@ -486,6 +530,10 @@ files = [
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@@ -493,13 +541,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2024.12.14"
+version = "2025.1.31"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 [[package]]
@@ -780,6 +828,7 @@ optional = false
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 files = [
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 [package.dependencies]
@@ -806,40 +855,42 @@ yaml = ["PyYAML"]
 
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-version = "44.0.0"
+version = "44.0.1"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
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 ]
 
 [package.dependencies]
@@ -852,7 +903,7 @@ nox = ["nox (>=2024.4.15)", "nox[uv] (>=2024.3.2)"]
 pep8test = ["check-sdist", "click (>=8.0.1)", "mypy (>=1.4)", "ruff (>=0.3.6)"]
 sdist = ["build (>=1.0.0)"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi (>=2024)", "cryptography-vectors (==44.0.0)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
+test = ["certifi (>=2024)", "cryptography-vectors (==44.0.1)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -1080,13 +1131,13 @@ files = [
 
 [[package]]
 name = "e2b"
-version = "1.0.6"
+version = "1.1.0"
 description = "E2B SDK that give agents cloud environments"
 optional = true
-python-versions = "<4.0,>=3.8"
+python-versions = "<4.0,>=3.9"
 files = [
-    {file = "e2b-1.0.6-py3-none-any.whl", hash = "sha256:4ae6e00d46e6b0b9ab05388c408f9155488ee9f022c5a6fd47939f492ccf3b58"},
-    {file = "e2b-1.0.6.tar.gz", hash = "sha256:e35d47f5581565060a5c18e4cb839cf61de310d275fa0a6589d8fc8bf65957a7"},
+    {file = "e2b-1.1.0-py3-none-any.whl", hash = "sha256:5d99c675e155cf124f457d77f91c4cb32b286d241ca6cd37ac8d6c0711fc272e"},
+    {file = "e2b-1.1.0.tar.gz", hash = "sha256:bd054fbaa9baed48919500ba853bdb72c750b04e0bac8365bde75cdfbdf80d18"},
 ]
 
 [package.dependencies]
@@ -1100,13 +1151,13 @@ typing-extensions = ">=4.1.0"
 
 [[package]]
 name = "e2b-code-interpreter"
-version = "1.0.4"
+version = "1.0.5"
 description = "E2B Code Interpreter - Stateful code execution"
 optional = true
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "e2b_code_interpreter-1.0.4-py3-none-any.whl", hash = "sha256:e8cea4946b3457072a524250aee712f7f8d44834b91cd9c13da3bdf96eda1a6e"},
-    {file = "e2b_code_interpreter-1.0.4.tar.gz", hash = "sha256:fec5651d98ca0d03dd038c5df943a0beaeb59c6d422112356f55f2b662d8dea1"},
+    {file = "e2b_code_interpreter-1.0.5-py3-none-any.whl", hash = "sha256:4c7814e9eabba58097bf5e4019d327b3a82fab0813eafca4311b29ca6ea0639d"},
+    {file = "e2b_code_interpreter-1.0.5.tar.gz", hash = "sha256:e7f70b039e6a70f8e592f90f806d696dc1056919414daabeb89e86c9b650a987"},
 ]
 
 [package.dependencies]
@@ -1158,13 +1209,13 @@ tzdata = "*"
 
 [[package]]
 name = "fastapi"
-version = "0.115.7"
+version = "0.115.8"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fastapi-0.115.7-py3-none-any.whl", hash = "sha256:eb6a8c8bf7f26009e8147111ff15b5177a0e19bb4a45bc3486ab14804539d21e"},
-    {file = "fastapi-0.115.7.tar.gz", hash = "sha256:0f106da6c01d88a6786b3248fb4d7a940d071f6f488488898ad5d354b25ed015"},
+    {file = "fastapi-0.115.8-py3-none-any.whl", hash = "sha256:753a96dd7e036b34eeef8babdfcfe3f28ff79648f86551eb36bfc1b0bf4a8cbf"},
+    {file = "fastapi-0.115.8.tar.gz", hash = "sha256:0ce9111231720190473e222cdf0f07f7206ad7e53ea02beb1d2dc36e2f0741e9"},
 ]
 
 [package.dependencies]
@@ -1790,18 +1841,18 @@ files = [
 
 [[package]]
 name = "h2"
-version = "4.1.0"
-description = "HTTP/2 State-Machine based protocol implementation"
+version = "4.2.0"
+description = "Pure-Python HTTP/2 protocol implementation"
 optional = true
-python-versions = ">=3.6.1"
+python-versions = ">=3.9"
 files = [
-    {file = "h2-4.1.0-py3-none-any.whl", hash = "sha256:03a46bcf682256c95b5fd9e9a99c1323584c3eec6440d379b9903d709476bc6d"},
-    {file = "h2-4.1.0.tar.gz", hash = "sha256:a83aca08fbe7aacb79fec788c9c0bac936343560ed9ec18b82a13a12c28d2abb"},
+    {file = "h2-4.2.0-py3-none-any.whl", hash = "sha256:479a53ad425bb29af087f3458a61d30780bc818e4ebcf01f0b536ba916462ed0"},
+    {file = "h2-4.2.0.tar.gz", hash = "sha256:c8a52129695e88b1a0578d8d2cc6842bbd79128ac685463b887ee278126ad01f"},
 ]
 
 [package.dependencies]
-hpack = ">=4.0,<5"
-hyperframe = ">=6.0,<7"
+hpack = ">=4.1,<5"
+hyperframe = ">=6.1,<7"
 
 [[package]]
 name = "hpack"
@@ -1884,13 +1935,13 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.28.0"
+version = "0.28.1"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = true
 python-versions = ">=3.8.0"
 files = [
-    {file = "huggingface_hub-0.28.0-py3-none-any.whl", hash = "sha256:71cff4e500efe68061d94b7f6d3114e183715088be7a90bf4dd84af83b5f5cdb"},
-    {file = "huggingface_hub-0.28.0.tar.gz", hash = "sha256:c2b18c02a47d4384763caddb4d0ab2a8fc6c16e0800d6de4d55d0a896244aba3"},
+    {file = "huggingface_hub-0.28.1-py3-none-any.whl", hash = "sha256:aa6b9a3ffdae939b72c464dbb0d7f99f56e649b55c3d52406f49e0a5a620c0a7"},
+    {file = "huggingface_hub-0.28.1.tar.gz", hash = "sha256:893471090c98e3b6efbdfdacafe4052b20b84d59866fb6f54c33d9af18c303ae"},
 ]
 
 [package.dependencies]
@@ -1929,13 +1980,13 @@ files = [
 
 [[package]]
 name = "identify"
-version = "2.6.6"
+version = "2.6.7"
 description = "File identification library for Python"
 optional = true
 python-versions = ">=3.9"
 files = [
-    {file = "identify-2.6.6-py2.py3-none-any.whl", hash = "sha256:cbd1810bce79f8b671ecb20f53ee0ae8e86ae84b557de31d89709dc2a48ba881"},
-    {file = "identify-2.6.6.tar.gz", hash = "sha256:7bec12768ed44ea4761efb47806f0a41f86e7c0a5fdf5950d4648c90eca7e251"},
+    {file = "identify-2.6.7-py2.py3-none-any.whl", hash = "sha256:155931cb617a401807b09ecec6635d6c692d180090a1cedca8ef7d58ba5b6aa0"},
+    {file = "identify-2.6.7.tar.gz", hash = "sha256:3fa266b42eba321ee0b2bb0936a6a6b9e36a1351cbb69055b3082f4193035684"},
 ]
 
 [package.extras]
@@ -2051,13 +2102,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
 
 [[package]]
 name = "ipython"
-version = "8.31.0"
+version = "8.32.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.10"
 files = [
-    {file = "ipython-8.31.0-py3-none-any.whl", hash = "sha256:46ec58f8d3d076a61d128fe517a51eb730e3aaf0c184ea8c17d16e366660c6a6"},
-    {file = "ipython-8.31.0.tar.gz", hash = "sha256:b6a2274606bec6166405ff05e54932ed6e5cfecaca1fc05f2cacde7bb074d70b"},
+    {file = "ipython-8.32.0-py3-none-any.whl", hash = "sha256:cae85b0c61eff1fc48b0a8002de5958b6528fa9c8defb1894da63f42613708aa"},
+    {file = "ipython-8.32.0.tar.gz", hash = "sha256:be2c91895b0b9ea7ba49d33b23e2040c352b33eb6a519cca7ce6e0c743444251"},
 ]
 
 [package.dependencies]
@@ -2359,23 +2410,23 @@ test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"
 
 [[package]]
 name = "langchain"
-version = "0.3.16"
+version = "0.3.18"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain-0.3.16-py3-none-any.whl", hash = "sha256:9a9c1a0604b599e929a5a823ee1491065dc8758fc1802d3df344214ab765f555"},
-    {file = "langchain-0.3.16.tar.gz", hash = "sha256:17d35ee6991e0ebd980c1be86c34b2d48e961213ca89e7b585f6333c90cdbdb4"},
+    {file = "langchain-0.3.18-py3-none-any.whl", hash = "sha256:1a6e629f02a25962aa5b16932e8f073248104a66804ed5af1f78618ad7c1d38d"},
+    {file = "langchain-0.3.18.tar.gz", hash = "sha256:311ac227a995545ff7c3f74c7767930c5349edef0b39f19d3105b86d39316b69"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.3.32,<0.4.0"
-langchain-text-splitters = ">=0.3.3,<0.4.0"
+langchain-core = ">=0.3.34,<1.0.0"
+langchain-text-splitters = ">=0.3.6,<1.0.0"
 langsmith = ">=0.1.17,<0.4"
 numpy = [
-    {version = ">=1.22.4,<2", markers = "python_version < \"3.12\""},
+    {version = ">=1.26.4,<2", markers = "python_version < \"3.12\""},
     {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""},
 ]
 pydantic = ">=2.7.4,<3.0.0"
@@ -2384,26 +2435,42 @@ requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
+[package.extras]
+anthropic = ["langchain-anthropic"]
+aws = ["langchain-aws"]
+cohere = ["langchain-cohere"]
+community = ["langchain-community"]
+deepseek = ["langchain-deepseek"]
+fireworks = ["langchain-fireworks"]
+google-genai = ["langchain-google-genai"]
+google-vertexai = ["langchain-google-vertexai"]
+groq = ["langchain-groq"]
+huggingface = ["langchain-huggingface"]
+mistralai = ["langchain-mistralai"]
+ollama = ["langchain-ollama"]
+openai = ["langchain-openai"]
+together = ["langchain-together"]
+
 [[package]]
 name = "langchain-community"
-version = "0.3.16"
+version = "0.3.17"
 description = "Community contributed LangChain integrations."
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_community-0.3.16-py3-none-any.whl", hash = "sha256:a702c577b048d48882a46708bb3e08ca9aec79657c421c3241a305409040c0d6"},
-    {file = "langchain_community-0.3.16.tar.gz", hash = "sha256:825709bc328e294942b045d0b7f55053e8e88f7f943576306d778cf56417126c"},
+    {file = "langchain_community-0.3.17-py3-none-any.whl", hash = "sha256:13bbd87d681b0df67bafa294321613b13ac524f173c92f11048d40c74e585f0b"},
+    {file = "langchain_community-0.3.17.tar.gz", hash = "sha256:d8547a3d4f8307950be88ca638cd6ab1abe2440d0012e401a172ba4a39aa8044"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.7"
-httpx-sse = ">=0.4.0,<0.5.0"
-langchain = ">=0.3.16,<0.4.0"
-langchain-core = ">=0.3.32,<0.4.0"
+httpx-sse = ">=0.4.0,<1.0.0"
+langchain = ">=0.3.18,<1.0.0"
+langchain-core = ">=0.3.34,<1.0.0"
 langsmith = ">=0.1.125,<0.4"
 numpy = [
-    {version = ">=1.22.4,<2", markers = "python_version < \"3.12\""},
+    {version = ">=1.26.4,<2", markers = "python_version < \"3.12\""},
     {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""},
 ]
 pydantic-settings = ">=2.4.0,<3.0.0"
@@ -2414,13 +2481,13 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.32"
+version = "0.3.34"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_core-0.3.32-py3-none-any.whl", hash = "sha256:c050bd1e6dd556ae49073d338aca9dca08b7b55f4778ddce881a12224bc82a7e"},
-    {file = "langchain_core-0.3.32.tar.gz", hash = "sha256:4eb85d8428585e67a1766e29c6aa2f246c6329d97cb486e8d6f564ab0bd94a4f"},
+    {file = "langchain_core-0.3.34-py3-none-any.whl", hash = "sha256:a057ebeddd2158d3be14bde341b25640ddf958b6989bd6e47160396f5a8202ae"},
+    {file = "langchain_core-0.3.34.tar.gz", hash = "sha256:26504cf1e8e6c310adad907b890d4e3c147581cfa7434114f6dc1134fe4bc6d3"},
 ]
 
 [package.dependencies]
@@ -2437,33 +2504,33 @@ typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-openai"
-version = "0.3.2"
+version = "0.3.5"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_openai-0.3.2-py3-none-any.whl", hash = "sha256:8674183805e26d3ae3f78cc44f79fe0b2066f61e2de0e7e18be3b86f0d3b2759"},
-    {file = "langchain_openai-0.3.2.tar.gz", hash = "sha256:c2c80ac0208eb7cefdef96f6353b00fa217979ffe83f0a21cc8666001df828c1"},
+    {file = "langchain_openai-0.3.5-py3-none-any.whl", hash = "sha256:137a7514f11afeab26e5fc1eda3c2b96fbbb18a96d963ba256faecceb189ea71"},
+    {file = "langchain_openai-0.3.5.tar.gz", hash = "sha256:40cd5649b93b1af20a20e1cbee5a47628a77e15114a11f9b3f2ab08c7d1302bf"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.31,<0.4.0"
+langchain-core = ">=0.3.34,<1.0.0"
 openai = ">=1.58.1,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.3.5"
+version = "0.3.6"
 description = "LangChain text splitting utilities"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langchain_text_splitters-0.3.5-py3-none-any.whl", hash = "sha256:8c9b059827438c5fa8f327b4df857e307828a5ec815163c9b5c9569a3e82c8ee"},
-    {file = "langchain_text_splitters-0.3.5.tar.gz", hash = "sha256:11cb7ca3694e5bdd342bc16d3875b7f7381651d4a53cbb91d34f22412ae16443"},
+    {file = "langchain_text_splitters-0.3.6-py3-none-any.whl", hash = "sha256:e5d7b850f6c14259ea930be4a964a65fa95d9df7e1dbdd8bad8416db72292f4e"},
+    {file = "langchain_text_splitters-0.3.6.tar.gz", hash = "sha256:c537972f4b7c07451df431353a538019ad9dadff7a1073ea363946cea97e1bee"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.29,<0.4.0"
+langchain-core = ">=0.3.34,<1.0.0"
 
 [[package]]
 name = "langchainhub"
@@ -2483,13 +2550,13 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
 
 [[package]]
 name = "langsmith"
-version = "0.3.2"
+version = "0.3.8"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "langsmith-0.3.2-py3-none-any.whl", hash = "sha256:48ff6bc5eda62f4729596bb68d4f96166d2654728ac32970b69b1be874c61925"},
-    {file = "langsmith-0.3.2.tar.gz", hash = "sha256:7724668e9705734ab25a7977fc34a9ee15a40ba4108987926c69293a05d40229"},
+    {file = "langsmith-0.3.8-py3-none-any.whl", hash = "sha256:fbb9dd97b0f090219447fca9362698d07abaeda1da85aa7cc6ec6517b36581b1"},
+    {file = "langsmith-0.3.8.tar.gz", hash = "sha256:97f9bebe0b7cb0a4f278e6ff30ae7d5ededff3883b014442ec6d7d575b02a0f1"},
 ]
 
 [package.dependencies]
@@ -2509,13 +2576,13 @@ pytest = ["pytest (>=7.0.0)", "rich (>=13.9.4,<14.0.0)"]
 
 [[package]]
 name = "letta-client"
-version = "0.1.23"
+version = "0.1.27"
 description = ""
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "letta_client-0.1.23-py3-none-any.whl", hash = "sha256:755c78e99d9e69589c333c9e362e08a75d6edac379fc0eb8265adb7546fffda7"},
-    {file = "letta_client-0.1.23.tar.gz", hash = "sha256:d3b0d5bde93827a700f23325f4f9fbd9dc0d0789aaced9f0511e9e6fb6d23446"},
+    {file = "letta_client-0.1.27-py3-none-any.whl", hash = "sha256:dbd8ac70993f8b2776bf2203e46e6d637a216a7b85974217534b3cf29479fabf"},
+    {file = "letta_client-0.1.27.tar.gz", hash = "sha256:191b29810c02e4b4818542affca41da4a2f2de97d05aac04fdab32b5b52a5da5"},
 ]
 
 [package.dependencies]
@@ -2527,35 +2594,53 @@ typing_extensions = ">=4.0.0"
 
 [[package]]
 name = "llama-cloud"
-version = "0.1.11"
+version = "0.1.12"
 description = ""
 optional = false
 python-versions = "<4,>=3.8"
 files = [
-    {file = "llama_cloud-0.1.11-py3-none-any.whl", hash = "sha256:b703765d03783a5a0fc57a52adc9892f8b91b0c19bbecb85a54ad4e813342951"},
-    {file = "llama_cloud-0.1.11.tar.gz", hash = "sha256:d4be5b48659fd9fe1698727be257269a22d7f2733a2ed11bce7065768eb94cbe"},
+    {file = "llama_cloud-0.1.12-py3-none-any.whl", hash = "sha256:de1b4f89afc3cf3adf86ca9a6eb2b8de3f131b20fd25a5647b5a162e6bf2ed1b"},
+    {file = "llama_cloud-0.1.12.tar.gz", hash = "sha256:d51d26cc4c542398a3490813bc791f7504a40298225e62ed918951bf57266e2a"},
 ]
 
 [package.dependencies]
-certifi = ">=2024.7.4,<2025.0.0"
+certifi = ">=2024.7.4"
 httpx = ">=0.20.0"
 pydantic = ">=1.10"
 
+[[package]]
+name = "llama-cloud-services"
+version = "0.6.0"
+description = "Tailored SDK clients for LlamaCloud services."
+optional = false
+python-versions = "<4.0,>=3.9"
+files = [
+    {file = "llama_cloud_services-0.6.0-py3-none-any.whl", hash = "sha256:b9647e236ba4e13d0b04bf336ed4023e422a2a48d363258924056ef9eb8f688d"},
+    {file = "llama_cloud_services-0.6.0.tar.gz", hash = "sha256:9c1ed2849f8ba7374df16bdfda69bed145eb4a425b546048f5e751c48efe293a"},
+]
+
+[package.dependencies]
+click = ">=8.1.7,<9.0.0"
+llama-cloud = ">=0.1.11,<0.2.0"
+llama-index-core = ">=0.11.0"
+pydantic = "!=2.10"
+python-dotenv = ">=1.0.1,<2.0.0"
+
 [[package]]
 name = "llama-index"
-version = "0.12.14"
+version = "0.12.16"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index-0.12.14-py3-none-any.whl", hash = "sha256:cafbac9f08f1f7293169bfd3c75545db3b761742ea829ba6940c3f2c3b1c2d26"},
-    {file = "llama_index-0.12.14.tar.gz", hash = "sha256:aa74315b32e93a77e285519459d77b98be7db9ae4c5aa64aac2c54cc919c838f"},
+    {file = "llama_index-0.12.16-py3-none-any.whl", hash = "sha256:c94d0cf6735219d97d91e2eca5bcfac89ec1583990917f934b075d5a45686cf6"},
+    {file = "llama_index-0.12.16.tar.gz", hash = "sha256:4fd5f5b94eb3f8dd470bb8cc0e1b985d931e8f31473266ef69855488fd8ae3f2"},
 ]
 
 [package.dependencies]
 llama-index-agent-openai = ">=0.4.0,<0.5.0"
 llama-index-cli = ">=0.4.0,<0.5.0"
-llama-index-core = ">=0.12.14,<0.13.0"
+llama-index-core = ">=0.12.16,<0.13.0"
 llama-index-embeddings-openai = ">=0.3.0,<0.4.0"
 llama-index-indices-managed-llama-cloud = ">=0.4.0"
 llama-index-llms-openai = ">=0.3.0,<0.4.0"
@@ -2568,13 +2653,13 @@ nltk = ">3.8.1"
 
 [[package]]
 name = "llama-index-agent-openai"
-version = "0.4.3"
+version = "0.4.5"
 description = "llama-index agent openai integration"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index_agent_openai-0.4.3-py3-none-any.whl", hash = "sha256:5d1fbb6831113e609296e457b0a4d1c08c9267acca219eb78cb702bd76a0744d"},
-    {file = "llama_index_agent_openai-0.4.3.tar.gz", hash = "sha256:ff1f4a13ba417cb4b9cfbc2ffa9f162bdbdda9b87d6645d512cbde2061f55412"},
+    {file = "llama_index_agent_openai-0.4.5-py3-none-any.whl", hash = "sha256:3fcadce03420a1974e6cf5ecd8e58337652df2f81d5f30033b3b32a576dc790a"},
+    {file = "llama_index_agent_openai-0.4.5.tar.gz", hash = "sha256:c09be43e01b3d5b2d8859814fcdabd000769ab1b54958a7025b3ce391147b005"},
 ]
 
 [package.dependencies]
@@ -2600,13 +2685,13 @@ llama-index-llms-openai = ">=0.3.0,<0.4.0"
 
 [[package]]
 name = "llama-index-core"
-version = "0.12.14"
+version = "0.12.17"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index_core-0.12.14-py3-none-any.whl", hash = "sha256:6fdb30e3fadf98e7df75f9db5d06f6a7f8503ca545a71e048d786ff88012bd50"},
-    {file = "llama_index_core-0.12.14.tar.gz", hash = "sha256:378bbf5bf4d1a8c692d3a980c1a6ed3be7a9afb676a4960429dea15f62d06cd3"},
+    {file = "llama_index_core-0.12.17-py3-none-any.whl", hash = "sha256:867ec650a1f9eba9f6d65005045a68bc13bae8d65763e32029d9610360c03979"},
+    {file = "llama_index_core-0.12.17.tar.gz", hash = "sha256:2e8fb457983978af19db1ceba71d440f6891279525c5e7eb2ec73a6b727be113"},
 ]
 
 [package.dependencies]
@@ -2665,13 +2750,13 @@ llama-index-core = ">=0.12.0,<0.13.0"
 
 [[package]]
 name = "llama-index-llms-openai"
-version = "0.3.14"
+version = "0.3.18"
 description = "llama-index llms openai integration"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index_llms_openai-0.3.14-py3-none-any.whl", hash = "sha256:9071cc28941ecf89f1b270668d80a2d8677cf0f573a983405e3f4b8198209216"},
-    {file = "llama_index_llms_openai-0.3.14.tar.gz", hash = "sha256:a87a5db42046fb5ff92fa8fda6d51c55a07f9d5fa42da187accf66e5293fd3d0"},
+    {file = "llama_index_llms_openai-0.3.18-py3-none-any.whl", hash = "sha256:e2e78ab94fafda8ac99fbfea1b19c5ba4e49d292557d2bdd9c7cc4b445f8745f"},
+    {file = "llama_index_llms_openai-0.3.18.tar.gz", hash = "sha256:81807ba318bac28aca67873228c55242c5fe55f8beba35d23828af6e03b1b234"},
 ]
 
 [package.dependencies]
@@ -2680,13 +2765,13 @@ openai = ">=1.58.1,<2.0.0"
 
 [[package]]
 name = "llama-index-multi-modal-llms-openai"
-version = "0.4.2"
+version = "0.4.3"
 description = "llama-index multi-modal-llms openai integration"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index_multi_modal_llms_openai-0.4.2-py3-none-any.whl", hash = "sha256:093f60f59fc423abab110810f8f129b96b0212b9737d74480f0e3e1b715e975b"},
-    {file = "llama_index_multi_modal_llms_openai-0.4.2.tar.gz", hash = "sha256:3437a08cec85cebbc212aa73da5c9b8b054b4dc628338568435a7df88489476f"},
+    {file = "llama_index_multi_modal_llms_openai-0.4.3-py3-none-any.whl", hash = "sha256:1ceb42716472ac8bd5130afa29b793869d367946aedd02e48a3b03184e443ad1"},
+    {file = "llama_index_multi_modal_llms_openai-0.4.3.tar.gz", hash = "sha256:5e6ca54069d3d18c2f5f7ca34f3720fba1d1b9126482ad38feb0c858f4feb63b"},
 ]
 
 [package.dependencies]
@@ -2727,13 +2812,13 @@ llama-index-program-openai = ">=0.3.0,<0.4.0"
 
 [[package]]
 name = "llama-index-readers-file"
-version = "0.4.4"
+version = "0.4.5"
 description = "llama-index readers file integration"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_index_readers_file-0.4.4-py3-none-any.whl", hash = "sha256:01589a4895e2d4abad30294c9b0d2813520ee1f5164922ad92f11e64a1d65d6c"},
-    {file = "llama_index_readers_file-0.4.4.tar.gz", hash = "sha256:e076b3fa1e68eea1594d47cec1f64b384fb6067f2697ca8aae22b4a21ad27ca7"},
+    {file = "llama_index_readers_file-0.4.5-py3-none-any.whl", hash = "sha256:704ac6b549f0ec59c0bd796007fceced2fff89a44b03d7ee36bce2d26b39e526"},
+    {file = "llama_index_readers_file-0.4.5.tar.gz", hash = "sha256:3ce5c8ad7f285bb7ff828c5b2e20088856ac65cf96640287eca770b69a21df88"},
 ]
 
 [package.dependencies]
@@ -2763,29 +2848,27 @@ llama-parse = ">=0.5.0"
 
 [[package]]
 name = "llama-parse"
-version = "0.5.20"
+version = "0.6.0"
 description = "Parse files into RAG-Optimized formats."
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "llama_parse-0.5.20-py3-none-any.whl", hash = "sha256:9617edb3428d3218ea01f1708f0b6105f3ffef142fedbeb8c98d50082c37e226"},
-    {file = "llama_parse-0.5.20.tar.gz", hash = "sha256:649e256431d3753025b9a320bb03b76849ce4b5a1121394c803df543e6c1006f"},
+    {file = "llama_parse-0.6.0-py3-none-any.whl", hash = "sha256:786f3b5cb0afdb784cd3d4b8b03489573b56d7d574212cc88a2eda508965121d"},
+    {file = "llama_parse-0.6.0.tar.gz", hash = "sha256:ac54ce4a43929b401a3ae4643e02ba4214e14814efb06062586263e13996ec54"},
 ]
 
 [package.dependencies]
-click = ">=8.1.7,<9.0.0"
-llama-index-core = ">=0.11.0"
-pydantic = "!=2.10"
+llama-cloud-services = "*"
 
 [[package]]
 name = "locust"
-version = "2.32.6"
+version = "2.32.9"
 description = "Developer-friendly load testing framework"
 optional = true
 python-versions = ">=3.9"
 files = [
-    {file = "locust-2.32.6-py3-none-any.whl", hash = "sha256:d5c0e4f73134415d250087034431cf3ea42ca695d3dee7f10812287cacb6c4ef"},
-    {file = "locust-2.32.6.tar.gz", hash = "sha256:6600cc308398e724764aacc56ccddf6cfcd0127c4c92dedd5c4979dd37ef5b15"},
+    {file = "locust-2.32.9-py3-none-any.whl", hash = "sha256:d9447c26d2bbaec5a0ace7cadefa1a31820ed392234257b309965a43d5e8d26f"},
+    {file = "locust-2.32.9.tar.gz", hash = "sha256:4c297afa5cdc3de15dfa79279576e5f33c1d69dd70006b51d079dcbd212201cc"},
 ]
 
 [package.dependencies]
@@ -2813,13 +2896,13 @@ Werkzeug = ">=2.0.0"
 
 [[package]]
 name = "mako"
-version = "1.3.8"
+version = "1.3.9"
 description = "A super-fast templating language that borrows the best ideas from the existing templating languages."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "Mako-1.3.8-py3-none-any.whl", hash = "sha256:42f48953c7eb91332040ff567eb7eea69b22e7a4affbc5ba8e845e8f730f6627"},
-    {file = "mako-1.3.8.tar.gz", hash = "sha256:577b97e414580d3e088d47c2dbbe9594aa7a5146ed2875d4dfa9075af2dd3cc8"},
+    {file = "Mako-1.3.9-py3-none-any.whl", hash = "sha256:95920acccb578427a9aa38e37a186b1e43156c87260d7ba18ca63aa4c7cbd3a1"},
+    {file = "mako-1.3.9.tar.gz", hash = "sha256:b5d65ff3462870feec922dbccf38f6efb44e5714d7b593a656be86663d8600ac"},
 ]
 
 [package.dependencies]
@@ -2926,13 +3009,13 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.26.0"
+version = "3.26.1"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "marshmallow-3.26.0-py3-none-any.whl", hash = "sha256:1287bca04e6a5f4094822ac153c03da5e214a0a60bcd557b140f3e66991b8ca1"},
-    {file = "marshmallow-3.26.0.tar.gz", hash = "sha256:eb36762a1cc76d7abf831e18a3a1b26d3d481bbc74581b8e532a3d3a8115e1cb"},
+    {file = "marshmallow-3.26.1-py3-none-any.whl", hash = "sha256:3350409f20a70a7e4e11a27661187b77cdcaeb20abca41c1454fe33636bea09c"},
+    {file = "marshmallow-3.26.1.tar.gz", hash = "sha256:e6d8affb6cb61d39d26402096dc0aee12d5a26d490a121f118d2e81dc0719dc6"},
 ]
 
 [package.dependencies]
@@ -3293,13 +3376,13 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.60.2"
+version = "1.61.1"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "openai-1.60.2-py3-none-any.whl", hash = "sha256:993bd11b96900b9098179c728026f016b4982ded7ee30dfcf4555eab1171fff9"},
-    {file = "openai-1.60.2.tar.gz", hash = "sha256:a8f843e10f2855713007f491d96afb2694b11b5e02cb97c7d01a0be60bc5bb51"},
+    {file = "openai-1.61.1-py3-none-any.whl", hash = "sha256:72b0826240ce26026ac2cd17951691f046e5be82ad122d20a8e1b30ca18bd11e"},
+    {file = "openai-1.61.1.tar.gz", hash = "sha256:ce1851507218209961f89f3520e06726c0aa7d0512386f0f977e3ac3e4f2472e"},
 ]
 
 [package.dependencies]
@@ -3503,13 +3586,13 @@ xml = ["lxml (>=4.9.2)"]
 
 [[package]]
 name = "paramiko"
-version = "3.5.0"
+version = "3.5.1"
 description = "SSH2 protocol library"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "paramiko-3.5.0-py3-none-any.whl", hash = "sha256:1fedf06b085359051cd7d0d270cebe19e755a8a921cc2ddbfa647fb0cd7d68f9"},
-    {file = "paramiko-3.5.0.tar.gz", hash = "sha256:ad11e540da4f55cedda52931f1a3f812a8238a7af7f62a60de538cd80bb28124"},
+    {file = "paramiko-3.5.1-py3-none-any.whl", hash = "sha256:43b9a0501fc2b5e70680388d9346cf252cfb7d00b0667c39e80eb43a408b8f61"},
+    {file = "paramiko-3.5.1.tar.gz", hash = "sha256:b2c665bc45b2b215bd7d7f039901b14b067da00f3a11e6640995fd58f2664822"},
 ]
 
 [package.dependencies]
@@ -3764,13 +3847,13 @@ virtualenv = ">=20.10.0"
 
 [[package]]
 name = "prettytable"
-version = "3.13.0"
+version = "3.14.0"
 description = "A simple Python library for easily displaying tabular data in a visually appealing ASCII table format"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "prettytable-3.13.0-py3-none-any.whl", hash = "sha256:d4f5817a248b77ddaa25b27007566c0a6a064308d991516b61b436ffdbb4f8e9"},
-    {file = "prettytable-3.13.0.tar.gz", hash = "sha256:30e1a097a7acb075b5c488ffe01195349b37009c2d43ca7fa8b5f6a61daace5b"},
+    {file = "prettytable-3.14.0-py3-none-any.whl", hash = "sha256:61d5c68f04a94acc73c7aac64f0f380f5bed4d2959d59edc6e4cbb7a0e7b55c4"},
+    {file = "prettytable-3.14.0.tar.gz", hash = "sha256:b804b8d51db23959b96b329094debdbbdf10c8c3aa75958c5988cfd7f78501dd"},
 ]
 
 [package.dependencies]
@@ -3947,6 +4030,7 @@ files = [
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     {file = "psycopg2-2.9.10-cp312-cp312-win32.whl", hash = "sha256:65a63d7ab0e067e2cdb3cf266de39663203d38d6a8ed97f5ca0cb315c73fe067"},
     {file = "psycopg2-2.9.10-cp312-cp312-win_amd64.whl", hash = "sha256:4a579d6243da40a7b3182e0430493dbd55950c493d8c68f4eec0b302f6bbf20e"},
+    {file = "psycopg2-2.9.10-cp313-cp313-win_amd64.whl", hash = "sha256:91fd603a2155da8d0cfcdbf8ab24a2d54bca72795b90d2a3ed2b6da8d979dee2"},
     {file = "psycopg2-2.9.10-cp39-cp39-win32.whl", hash = "sha256:9d5b3b94b79a844a986d029eee38998232451119ad653aea42bb9220a8c5066b"},
     {file = "psycopg2-2.9.10-cp39-cp39-win_amd64.whl", hash = "sha256:88138c8dedcbfa96408023ea2b0c369eda40fe5d75002c0964c78f46f11fa442"},
     {file = "psycopg2-2.9.10.tar.gz", hash = "sha256:12ec0b40b0273f95296233e8750441339298e6a572f7039da5b260e3c8b60e11"},
@@ -4006,6 +4090,7 @@ files = [
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     {file = "psycopg2_binary-2.9.10-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:f0c2d907a1e102526dd2986df638343388b94c33860ff3bbe1384130828714b1"},
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+    {file = "psycopg2_binary-2.9.10-cp313-cp313-win_amd64.whl", hash = "sha256:27422aa5f11fbcd9b18da48373eb67081243662f9b46e6fd07c3eb46e4535142"},
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     {file = "psycopg2_binary-2.9.10-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b73d6d7f0ccdad7bc43e6d34273f70d587ef62f824d7261c4ae9b8b1b6af90e8"},
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@@ -4326,13 +4411,13 @@ tests = ["hypothesis (>=3.27.0)", "pytest (>=3.2.1,!=3.3.0)"]
 
 [[package]]
 name = "pypdf"
-version = "5.2.0"
+version = "5.3.0"
 description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pypdf-5.2.0-py3-none-any.whl", hash = "sha256:d107962ec45e65e3bd10c1d9242bdbbedaa38193c9e3a6617bd6d996e5747b19"},
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+    {file = "pypdf-5.3.0.tar.gz", hash = "sha256:08393660dfea25b27ec6fe863fb2f2248e6270da5103fae49e9dea8178741951"},
 ]
 
 [package.dependencies]
@@ -4358,13 +4443,13 @@ files = [
 
 [[package]]
 name = "pyright"
-version = "1.1.392.post0"
+version = "1.1.393"
 description = "Command line wrapper for pyright"
 optional = true
 python-versions = ">=3.7"
 files = [
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-    {file = "pyright-1.1.392.post0.tar.gz", hash = "sha256:3b7f88de74a28dcfa90c7d90c782b6569a48c2be5f9d4add38472bdaac247ebd"},
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+    {file = "pyright-1.1.393.tar.gz", hash = "sha256:aeeb7ff4e0364775ef416a80111613f91a05c8e01e58ecfefc370ca0db7aed9c"},
 ]
 
 [package.dependencies]
@@ -4637,120 +4722,120 @@ files = [
 
 [[package]]
 name = "pyzmq"
-version = "26.2.0"
+version = "26.2.1"
 description = "Python bindings for 0MQ"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "SQLAlchemy-2.0.38-py3-none-any.whl", hash = "sha256:63178c675d4c80def39f1febd625a6333f44c0ba269edd8a468b156394b27753"},
+    {file = "sqlalchemy-2.0.38.tar.gz", hash = "sha256:e5a4d82bdb4bf1ac1285a68eab02d253ab73355d9f0fe725a97e1e0fa689decb"},
 ]
 
 [package.dependencies]
@@ -5730,13 +5815,13 @@ standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)",
 
 [[package]]
 name = "virtualenv"
-version = "20.29.1"
+version = "20.29.2"
 description = "Virtual Python Environment builder"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "virtualenv-20.29.1-py3-none-any.whl", hash = "sha256:4e4cb403c0b0da39e13b46b1b2476e505cb0046b25f242bee80f62bf990b2779"},
-    {file = "virtualenv-20.29.1.tar.gz", hash = "sha256:b8b8970138d32fb606192cb97f6cd4bb644fa486be9308fb9b63f81091b5dc35"},
+    {file = "virtualenv-20.29.2-py3-none-any.whl", hash = "sha256:febddfc3d1ea571bdb1dc0f98d7b45d24def7428214d4fb73cc486c9568cce6a"},
+    {file = "virtualenv-20.29.2.tar.gz", hash = "sha256:fdaabebf6d03b5ba83ae0a02cfe96f48a716f4fae556461d180825866f75b728"},
 ]
 
 [package.dependencies]
@@ -6420,4 +6505,4 @@ tests = ["wikipedia"]
 [metadata]
 lock-version = "2.0"
 python-versions = "<3.14,>=3.10"
-content-hash = "e2101628603fc9585b5f082e974d9d503de7a50117ce89a518f28c783c5fe650"
+content-hash = "1cb8ed2407a871e0753b46cd32454b0c78fb166fe60624b12265f800430e6d28"
diff --git a/pyproject.toml b/pyproject.toml
index eafe7109..7921d6ed 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,8 +1,6 @@
 [tool.poetry]
 name = "letta"
-
-
-version = "0.6.13"
+version = "0.6.23"
 packages = [
     {include = "letta"},
 ]
@@ -82,6 +80,7 @@ anthropic = "^0.43.0"
 letta_client = "^0.1.23"
 openai = "^1.60.0"
 faker = "^36.1.0"
+colorama = "^0.4.6"
 
 
 [tool.poetry.extras]
diff --git a/tests/test_cli.py b/tests/test_cli.py
index c6497f50..c0b8525b 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -1,4 +1,5 @@
 import os
+import re
 import shutil
 import sys
 
@@ -74,3 +75,16 @@ def test_letta_run_create_new_agent(swap_letta_config):
     # Count occurrences of assistant messages
     robot = full_output.count(ASSISTANT_MESSAGE_CLI_SYMBOL)
     assert robot == 1, f"It appears that there are multiple instances of assistant messages outputted."
+
+
+def test_letta_version_prints_only_version(swap_letta_config):
+    # Start the letta version command
+    output = pexpect.run("poetry run letta version", encoding="utf-8")
+
+    # Remove ANSI escape sequences and whitespace
+    output = re.sub(r"\x1b\[[0-9;]*[mK]", "", output).strip()
+
+    from letta import __version__
+
+    # Get the full output and verify it contains only the version
+    assert output == __version__, f"Expected only '{__version__}', but got '{repr(output)}'"
diff --git a/tests/test_google_embeddings.py b/tests/test_google_embeddings.py
new file mode 100644
index 00000000..71570ff0
--- /dev/null
+++ b/tests/test_google_embeddings.py
@@ -0,0 +1,153 @@
+import httpx
+import pytest
+from dotenv import load_dotenv
+
+from letta.embeddings import GoogleEmbeddings  # Adjust the import based on your module structure
+
+load_dotenv()
+import os
+import threading
+import time
+import uuid
+
+import pytest
+from letta_client import CreateBlock
+from letta_client import Letta as LettaSDKClient
+from letta_client import MessageCreate
+
+SERVER_PORT = 8283
+
+
+def run_server():
+    load_dotenv()
+
+    from letta.server.rest_api.app import start_server
+
+    print("Starting server...")
+    start_server(debug=True)
+
+
+@pytest.fixture(scope="module")
+def client() -> LettaSDKClient:
+    # Get URL from environment or start server
+    server_url = os.getenv("LETTA_SERVER_URL", f"http://localhost:{SERVER_PORT}")
+    if not os.getenv("LETTA_SERVER_URL"):
+        print("Starting server thread")
+        thread = threading.Thread(target=run_server, daemon=True)
+        thread.start()
+        time.sleep(5)
+    print("Running client tests with server:", server_url)
+    client = LettaSDKClient(base_url=server_url, token=None)
+    yield client
+
+
+def test_google_embeddings_response():
+    api_key = os.environ.get("GEMINI_API_KEY")
+    model = "text-embedding-004"
+    base_url = "https://generativelanguage.googleapis.com"
+    text = "Hello, world!"
+
+    embedding_model = GoogleEmbeddings(api_key, model, base_url)
+    response = None
+
+    try:
+        response = embedding_model.get_text_embedding(text)
+    except httpx.HTTPStatusError as e:
+        pytest.fail(f"Request failed with status code {e.response.status_code}")
+
+    assert response is not None, "No response received from API"
+    assert isinstance(response, list), "Response is not a list of embeddings"
+
+
+def test_archival_insert_text_embedding_004(client: LettaSDKClient):
+    """
+    Test that an agent with model 'gemini-2.0-flash-exp' and embedding 'text_embedding_004'
+    correctly inserts a message into its archival memory.
+
+    The test works by:
+      1. Creating an agent with the desired model and embedding.
+      2. Sending a message prefixed with 'archive :' to instruct the agent to store the message in archival.
+      3. Retrieving the archival memory via the agent messaging API.
+      4. Verifying that the archival message is stored.
+    """
+    # Create an agent with the specified model and embedding.
+    agent = client.agents.create(
+        name=f"archival_insert_text_embedding_004",
+        memory_blocks=[
+            CreateBlock(label="human", value="name: archival_test"),
+            CreateBlock(label="persona", value="You are a helpful assistant that loves helping out the user"),
+        ],
+        model="google_ai/gemini-2.0-flash-exp",
+        embedding="google_ai/text-embedding-004",
+    )
+
+    # Define the archival message.
+    archival_message = "Archival insertion test message"
+
+    # Send a message instructing the agent to archive it.
+    res = client.agents.messages.create(
+        agent_id=agent.id,
+        messages=[MessageCreate(role="user", content=f"Store this in your archive memory: {archival_message}")],
+    )
+    print(res.messages)
+
+    # Retrieve the archival messages through the agent messaging API.
+    archived_messages = client.agents.messages.create(
+        agent_id=agent.id,
+        messages=[MessageCreate(role="user", content=f"retrieve from archival memory : {archival_message}")],
+    )
+
+    print(archived_messages.messages)
+    # Assert that the archival message is present.
+    assert any(
+        message.status == "success" for message in archived_messages.messages if message.message_type == "tool_return_message"
+    ), f"Archival message '{archival_message}' not found. Archived messages: {archived_messages}"
+
+    # Cleanup: Delete the agent.
+    client.agents.delete(agent.id)
+
+
+def test_archival_insert_embedding_001(client: LettaSDKClient):
+    """
+    Test that an agent with model 'gemini-2.0-flash-exp' and embedding 'embedding_001'
+    correctly inserts a message into its archival memory.
+
+    The test works by:
+      1. Creating an agent with the desired model and embedding.
+      2. Sending a message prefixed with 'archive :' to instruct the agent to store the message in archival.
+      3. Retrieving the archival memory via the agent messaging API.
+      4. Verifying that the archival message is stored.
+    """
+    # Create an agent with the specified model and embedding.
+    agent = client.agents.create(
+        name=f"archival_insert_embedding_001",
+        memory_blocks=[
+            CreateBlock(label="human", value="name: archival_test"),
+            CreateBlock(label="persona", value="You are a helpful assistant that loves helping out the user"),
+        ],
+        model="google_ai/gemini-2.0-flash-exp",
+        embedding="google_ai/embedding-001",
+    )
+
+    # Define the archival message.
+    archival_message = "Archival insertion test message"
+
+    # Send a message instructing the agent to archive it.
+    client.agents.messages.create(
+        agent_id=agent.id,
+        messages=[MessageCreate(role="user", content=f"archive : {archival_message}")],
+    )
+
+    # Retrieve the archival messages through the agent messaging API.
+    archived_messages = client.agents.messages.create(
+        agent_id=agent.id,
+        messages=[MessageCreate(role="user", content=f"retrieve from archival memory : {archival_message}")],
+    )
+
+    # Assert that the archival message is present.
+    assert any(
+        message.status == "success" for message in archived_messages.messages if message.message_type == "tool_return_message"
+    ), f"Archival message '{archival_message}' not found. Archived messages: {archived_messages}"
+
+    # Cleanup: Delete the agent.
+    client.agents.delete(agent.id)