diff --git a/memgpt/cli/cli_load.py b/memgpt/cli/cli_load.py
index a8e09ffe1f..d74d7c8d20 100644
--- a/memgpt/cli/cli_load.py
+++ b/memgpt/cli/cli_load.py
@@ -111,7 +111,6 @@ def load_directory(
             embedding_config=config.default_embedding_config,
             document_store=None,
             passage_store=passage_storage,
-            chunk_size=1000,
         )
         print(f"Loaded {num_passages} passages and {num_documents} documents from {name}")
 
diff --git a/memgpt/data_sources/connectors.py b/memgpt/data_sources/connectors.py
index a832db403d..a018788892 100644
--- a/memgpt/data_sources/connectors.py
+++ b/memgpt/data_sources/connectors.py
@@ -23,7 +23,6 @@ def load_data(
     embedding_config: EmbeddingConfig,
     passage_store: StorageConnector,
     document_store: Optional[StorageConnector] = None,
-    chunk_size: int = 1000,
 ):
     """Load data from a connector (generates documents and passages) into a specified source_id, associatedw with a user_id."""
 
@@ -49,7 +48,6 @@ def load_data(
 
         # generate passages
         for passage_text, passage_metadata in connector.generate_passages([document]):
-            print("passage", passage_text, passage_metadata)
             embedding = embed_model.get_text_embedding(passage_text)
             passage = Passage(
                 id=create_uuid_from_string(f"{str(source.id)}_{passage_text}"),
@@ -64,7 +62,7 @@ def load_data(
             )
 
             passages.append(passage)
-            if len(passages) >= chunk_size:
+            if len(passages) >= embedding_config.embedding_chunk_size:
                 # insert passages into passage store
                 passage_store.insert_many(passages)
 
diff --git a/memgpt/server/server.py b/memgpt/server/server.py
index 98e1038279..519395b72e 100644
--- a/memgpt/server/server.py
+++ b/memgpt/server/server.py
@@ -17,14 +17,15 @@
 
 # from memgpt.llm_api_tools import openai_get_model_list, azure_openai_get_model_list, smart_urljoin
 from memgpt.cli.cli_config import get_model_options
-
-# from memgpt.agent_store.storage import StorageConnector
+from memgpt.data_sources.connectors import DataConnector, load_data
+from memgpt.agent_store.storage import StorageConnector, TableType
 from memgpt.metadata import MetadataStore
 import memgpt.presets.presets as presets
 import memgpt.utils as utils
 import memgpt.server.utils as server_utils
 from memgpt.data_types import (
     User,
+    Source,
     Passage,
     AgentState,
     LLMConfig,
@@ -969,6 +970,10 @@ def rename_agent(self, user_id: uuid.UUID, agent_id: uuid.UUID, new_agent_name:
 
         return memgpt_agent.agent_state
 
+    def delete_user(self, user_id: uuid.UUID):
+        # TODO: delete user
+        pass
+
     def delete_agent(self, user_id: uuid.UUID, agent_id: uuid.UUID):
         """Delete an agent in the database"""
         if self.ms.get_user(user_id=user_id) is None:
@@ -1015,15 +1020,45 @@ def create_api_key_for_user(self, user_id: uuid.UUID) -> Token:
         token = self.ms.create_api_key(user_id=user_id)
         return token
 
-    def create_source(self, name: str):  # TODO: add other fields
-        # craete a data source
-        pass
+    def create_source(self, name: str, user_id: uuid.UUID) -> Source:  # TODO: add other fields
+        """Create a new data source"""
+        source = Source(name=name, user_id=user_id)
+        self.ms.create_source(source)
+        return source
 
-    def load_passages(self, source_id: uuid.UUID, passages: List[Passage]):
-        # load a list of passages into a data source
-        pass
+    def load_data(
+        self,
+        user_id: uuid.UUID,
+        connector: DataConnector,
+        source_name: Source,
+    ):
+        """Load data from a DataConnector into a source for a specified user_id"""
+        # TODO: this should be implemented as a batch job or at least async, since it may take a long time
 
-    def attach_source_to_agent(self, agent_id: uuid.UUID, source_id: uuid.UUID):
+        # load data from a data source into the document store
+        source = self.ms.get_source(source_name=source_name, user_id=user_id)
+        if source is None:
+            raise ValueError(f"Data source {source_name} does not exist for user {user_id}")
+
+        # get the data connectors
+        passage_store = StorageConnector.get_storage_connector(TableType.PASSAGES, self.config, user_id=user_id)
+        # TODO: add document store support
+        document_store = None  # StorageConnector.get_storage_connector(TableType.DOCUMENTS, self.config, user_id=user_id)
+
+        # load data into the document store
+        load_data(connector, source, self.config.default_embedding_config, passage_store, document_store)
+
+    def attach_source_to_agent(self, user_id: uuid.UUID, agent_id: uuid.UUID, source_name: str):
         # attach a data source to an agent
-        # TODO: insert passages into agent archival memory
-        pass
+        data_source = self.ms.get_source(source_name=source_name, user_id=user_id)
+        if data_source is None:
+            raise ValueError(f"Data source {source_name} does not exist")
+
+        # get connection to data source storage
+        source_connector = StorageConnector.get_storage_connector(TableType.PASSAGES, self.config, user_id=user_id)
+
+        # load agent
+        agent = self._get_or_load_agent(user_id, agent_id)
+
+        # attach source to agent
+        agent.attach_source(data_source.name, source_connector, self.ms)
diff --git a/poetry.lock b/poetry.lock
index 3d9127e665..3af38aa961 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -526,13 +526,13 @@ numpy = "*"
 
 [[package]]
 name = "chromadb"
-version = "0.4.22"
+version = "0.4.23"
 description = "Chroma."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "chromadb-0.4.22-py3-none-any.whl", hash = "sha256:ad210b27b4cda2f09d15adc9c83c81bfa66b69f39648a27b637306e40de0680d"},
-    {file = "chromadb-0.4.22.tar.gz", hash = "sha256:c793149e1c2bbbb52d77602c6c0594c5752f04cd9be12619250ddad2082af27a"},
+    {file = "chromadb-0.4.23-py3-none-any.whl", hash = "sha256:3d3c2ffb4ff560721e3daf8c1a3729fd149c551525b6f75543eddb81a4f29e16"},
+    {file = "chromadb-0.4.23.tar.gz", hash = "sha256:54d9a770640704c6cedc15317faab9fd45beb9833e7484c00037e7a8801a349f"},
 ]
 
 [package.dependencies]
@@ -550,6 +550,7 @@ opentelemetry-api = ">=1.2.0"
 opentelemetry-exporter-otlp-proto-grpc = ">=1.2.0"
 opentelemetry-instrumentation-fastapi = ">=0.41b0"
 opentelemetry-sdk = ">=1.2.0"
+orjson = ">=3.9.12"
 overrides = ">=7.3.1"
 posthog = ">=2.4.0"
 pulsar-client = ">=3.1.0"
@@ -1020,13 +1021,13 @@ tqdm = ["tqdm"]
 
 [[package]]
 name = "google-auth"
-version = "2.28.0"
+version = "2.28.1"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.28.0.tar.gz", hash = "sha256:3cfc1b6e4e64797584fb53fc9bd0b7afa9b7c0dba2004fa7dcc9349e58cc3195"},
-    {file = "google_auth-2.28.0-py2.py3-none-any.whl", hash = "sha256:7634d29dcd1e101f5226a23cbc4a0c6cda6394253bf80e281d9c5c6797869c53"},
+    {file = "google-auth-2.28.1.tar.gz", hash = "sha256:34fc3046c257cedcf1622fc4b31fc2be7923d9b4d44973d481125ecc50d83885"},
+    {file = "google_auth-2.28.1-py2.py3-none-any.whl", hash = "sha256:25141e2d7a14bfcba945f5e9827f98092716e99482562f15306e5b026e21aa72"},
 ]
 
 [package.dependencies]
@@ -1131,69 +1132,69 @@ test = ["objgraph", "psutil"]
 
 [[package]]
 name = "grpcio"
-version = "1.60.1"
+version = "1.62.0"
 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.extras]
-protobuf = ["grpcio-tools (>=1.60.1)"]
+protobuf = ["grpcio-tools (>=1.62.0)"]
 
 [[package]]
 name = "h11"
@@ -1219,13 +1220,13 @@ files = [
 
 [[package]]
 name = "httpcore"
-version = "1.0.3"
+version = "1.0.4"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -1236,7 +1237,7 @@ h11 = ">=0.13,<0.15"
 asyncio = ["anyio (>=4.0,<5.0)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
-trio = ["trio (>=0.22.0,<0.24.0)"]
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 [[package]]
 name = "httptools"
@@ -1517,50 +1518,52 @@ tests = ["pandas (>=1.4)", "pytest", "pytest-asyncio", "pytest-mock", "requests"
 
 [[package]]
 name = "llama-index"
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 python-versions = ">=3.8.1,<4.0"
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 llama-index-readers-file = ">=0.1.0,<0.2.0"
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 [[package]]
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 [[package]]
 name = "llama-index-core"
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 description = "Interface between LLMs and your data"
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
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 [package.dependencies]
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 dirtyjson = ">=1.0.8,<2.0.0"
 fsspec = ">=2023.5.0"
 httpx = "*"
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 nest-asyncio = ">=1.5.8,<2.0.0"
 networkx = ">=3.0"
 nltk = ">=3.8.1,<4.0.0"
@@ -1597,18 +1600,33 @@ query-tools = ["guidance (>=0.0.64,<0.0.65)", "jsonpath-ng (>=1.6.0,<2.0.0)", "l
 
 [[package]]
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 description = "llama-index embeddings openai integration"
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 [package.dependencies]
 llama-index-core = ">=0.10.1,<0.11.0"
 
+[[package]]
+name = "llama-index-indices-managed-llama-cloud"
+version = "0.1.3"
+description = "llama-index indices llama-cloud integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
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+[package.dependencies]
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+llamaindex-py-client = ">=0.1.13,<0.2.0"
+
 [[package]]
 name = "llama-index-legacy"
 version = "0.9.48"
@@ -1650,13 +1668,13 @@ query-tools = ["guidance (>=0.0.64,<0.0.65)", "jsonpath-ng (>=1.6.0,<2.0.0)", "l
 
 [[package]]
 name = "llama-index-llms-openai"
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+version = "0.1.6"
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 optional = false
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 files = [
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 ]
 
 [package.dependencies]
@@ -1664,13 +1682,13 @@ llama-index-core = ">=0.10.1,<0.11.0"
 
 [[package]]
 name = "llama-index-multi-modal-llms-openai"
-version = "0.1.1"
+version = "0.1.4"
 description = "llama-index multi-modal-llms openai integration"
 optional = false
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+python-versions = ">=3.8.1,<4.0"
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+    {file = "llama_index_multi_modal_llms_openai-0.1.4-py3-none-any.whl", hash = "sha256:03b887d110551d5d5b99b9fd110824e6311f2e31f4d5e67dafd2ee66da32818d"},
+    {file = "llama_index_multi_modal_llms_openai-0.1.4.tar.gz", hash = "sha256:6a5d6584c33a9d1b06cf5c874c63af2603fc93b660bde481a8c547e876c6e2c3"},
 ]
 
 [package.dependencies]
@@ -1679,13 +1697,13 @@ llama-index-llms-openai = ">=0.1.1,<0.2.0"
 
 [[package]]
 name = "llama-index-program-openai"
-version = "0.1.2"
+version = "0.1.4"
 description = "llama-index program openai integration"
 optional = false
-python-versions = ">=3.8.1,<3.12"
+python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "llama_index_program_openai-0.1.2-py3-none-any.whl", hash = "sha256:0951e11b263beb804ea1c82e5354111186e2d1be4fd95655e522c5b44b181ca3"},
-    {file = "llama_index_program_openai-0.1.2.tar.gz", hash = "sha256:1a03178a21e006fcb62f6ce986d94465b2e39bb33d2d0b58577e538bacbb37ec"},
+    {file = "llama_index_program_openai-0.1.4-py3-none-any.whl", hash = "sha256:cfa8f00f3743d2fc70043e80f7c3925d23b1413a0cc7a72863ad60497a18307d"},
+    {file = "llama_index_program_openai-0.1.4.tar.gz", hash = "sha256:573e99a2dd16ad3caf382c8ab28d1ac10eb2571bc9481d84a6d89806ad6aa5d4"},
 ]
 
 [package.dependencies]
@@ -1695,13 +1713,13 @@ llama-index-llms-openai = ">=0.1.1,<0.2.0"
 
 [[package]]
 name = "llama-index-question-gen-openai"
-version = "0.1.1"
+version = "0.1.3"
 description = "llama-index question_gen openai integration"
 optional = false
-python-versions = ">=3.8.1,<3.12"
+python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "llama_index_question_gen_openai-0.1.1-py3-none-any.whl", hash = "sha256:b02ee22876c9c4afa6ca617b56e14f5587acdcc051204f5e224c2eb982fa52ea"},
-    {file = "llama_index_question_gen_openai-0.1.1.tar.gz", hash = "sha256:d73074a3495c89cb6505d4f957d5c2878ce3327c7636277f6c4a434eff0f3fc6"},
+    {file = "llama_index_question_gen_openai-0.1.3-py3-none-any.whl", hash = "sha256:1f83b49e8b2e665030d1ec8c54687d6985d9fa8426147b64e46628a9e489b302"},
+    {file = "llama_index_question_gen_openai-0.1.3.tar.gz", hash = "sha256:4486198117a45457d2e036ae60b93af58052893cc7d78fa9b6f47dd47b81e2e1"},
 ]
 
 [package.dependencies]
@@ -1726,6 +1744,35 @@ bs4 = ">=0.0.2,<0.0.3"
 llama-index-core = ">=0.10.1,<0.11.0"
 pymupdf = ">=1.23.21,<2.0.0"
 
+[[package]]
+name = "llama-index-readers-llama-parse"
+version = "0.1.3"
+description = "llama-index readers llama-parse integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
+    {file = "llama_index_readers_llama_parse-0.1.3-py3-none-any.whl", hash = "sha256:f52a06a2765a2ffe6c138cf1703ab1de6249ff069ba62d80b9147e849bbcbc27"},
+    {file = "llama_index_readers_llama_parse-0.1.3.tar.gz", hash = "sha256:e0ee0c393e10fc80eac644788338bbd2032050c8b8a474f3d0b5ebd08e9867fe"},
+]
+
+[package.dependencies]
+llama-index-core = ">=0.10.7,<0.11.0"
+llama-parse = ">=0.3.3,<0.4.0"
+
+[[package]]
+name = "llama-parse"
+version = "0.3.4"
+description = "Parse files into RAG-Optimized formats."
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
+    {file = "llama_parse-0.3.4-py3-none-any.whl", hash = "sha256:b667c78d4c32fc5d0561e6e3ca6c53648a6701b436f21d0d252cd46774927660"},
+    {file = "llama_parse-0.3.4.tar.gz", hash = "sha256:5a30569c390ab9089dad66cf2a8c967f8c21d77641deec0a922672df4e16cfa3"},
+]
+
+[package.dependencies]
+llama-index-core = ">=0.10.7"
+
 [[package]]
 name = "llamaindex-py-client"
 version = "0.1.13"
@@ -2460,13 +2507,13 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 
 [[package]]
 name = "opentelemetry-api"
-version = "1.22.0"
+version = "1.23.0"
 description = "OpenTelemetry Python API"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_api-1.22.0-py3-none-any.whl", hash = "sha256:43621514301a7e9f5d06dd8013a1b450f30c2e9372b8e30aaeb4562abf2ce034"},
-    {file = "opentelemetry_api-1.22.0.tar.gz", hash = "sha256:15ae4ca925ecf9cfdfb7a709250846fbb08072260fca08ade78056c502b86bed"},
+    {file = "opentelemetry_api-1.23.0-py3-none-any.whl", hash = "sha256:cc03ea4025353048aadb9c64919099663664672ea1c6be6ddd8fee8e4cd5e774"},
+    {file = "opentelemetry_api-1.23.0.tar.gz", hash = "sha256:14a766548c8dd2eb4dfc349739eb4c3893712a0daa996e5dbf945f9da665da9d"},
 ]
 
 [package.dependencies]
@@ -2475,52 +2522,50 @@ importlib-metadata = ">=6.0,<7.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-common"
-version = "1.22.0"
+version = "1.23.0"
 description = "OpenTelemetry Protobuf encoding"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_exporter_otlp_proto_common-1.22.0-py3-none-any.whl", hash = "sha256:3f2538bec5312587f8676c332b3747f54c89fe6364803a807e217af4603201fa"},
-    {file = "opentelemetry_exporter_otlp_proto_common-1.22.0.tar.gz", hash = "sha256:71ae2f81bc6d6fe408d06388826edc8933759b2ca3a97d24054507dc7cfce52d"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.23.0-py3-none-any.whl", hash = "sha256:2a9e7e9d5a8b026b572684b6b24dcdefcaa58613d5ce3d644130b0c373c056c1"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.23.0.tar.gz", hash = "sha256:35e4ea909e7a0b24235bd0aaf17fba49676527feb1823b46565ff246d5a1ab18"},
 ]
 
 [package.dependencies]
-backoff = {version = ">=1.10.0,<3.0.0", markers = "python_version >= \"3.7\""}
-opentelemetry-proto = "1.22.0"
+opentelemetry-proto = "1.23.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-grpc"
-version = "1.22.0"
+version = "1.23.0"
 description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_exporter_otlp_proto_grpc-1.22.0-py3-none-any.whl", hash = "sha256:b5bcadc129272004316a455e9081216d3380c1fc2231a928ea6a70aa90e173fb"},
-    {file = "opentelemetry_exporter_otlp_proto_grpc-1.22.0.tar.gz", hash = "sha256:1e0e5aa4bbabc74942f06f268deffd94851d12a8dc30b02527472ef1729fe5b1"},
+    {file = "opentelemetry_exporter_otlp_proto_grpc-1.23.0-py3-none-any.whl", hash = "sha256:40f9e3e7761eb34f2a1001f4543028783ac26e2db27e420d5374f2cca0182dad"},
+    {file = "opentelemetry_exporter_otlp_proto_grpc-1.23.0.tar.gz", hash = "sha256:aa1a012eea5342bfef51fcf3f7f22601dcb0f0984a07ffe6025b2fbb6d91a2a9"},
 ]
 
 [package.dependencies]
-backoff = {version = ">=1.10.0,<3.0.0", markers = "python_version >= \"3.7\""}
 deprecated = ">=1.2.6"
 googleapis-common-protos = ">=1.52,<2.0"
 grpcio = ">=1.0.0,<2.0.0"
 opentelemetry-api = ">=1.15,<2.0"
-opentelemetry-exporter-otlp-proto-common = "1.22.0"
-opentelemetry-proto = "1.22.0"
-opentelemetry-sdk = ">=1.22.0,<1.23.0"
+opentelemetry-exporter-otlp-proto-common = "1.23.0"
+opentelemetry-proto = "1.23.0"
+opentelemetry-sdk = ">=1.23.0,<1.24.0"
 
 [package.extras]
 test = ["pytest-grpc"]
 
 [[package]]
 name = "opentelemetry-instrumentation"
-version = "0.43b0"
+version = "0.44b0"
 description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation-0.43b0-py3-none-any.whl", hash = "sha256:0ff1334d7e359e27640e9d420024efeb73eacae464309c2e14ede7ba6c93967e"},
-    {file = "opentelemetry_instrumentation-0.43b0.tar.gz", hash = "sha256:c3755da6c4be8033be0216d0501e11f4832690f4e2eca5a3576fbf113498f0f6"},
+    {file = "opentelemetry_instrumentation-0.44b0-py3-none-any.whl", hash = "sha256:79560f386425176bcc60c59190064597096114c4a8e5154f1cb281bb4e47d2fc"},
+    {file = "opentelemetry_instrumentation-0.44b0.tar.gz", hash = "sha256:8213d02d8c0987b9b26386ae3e091e0477d6331673123df736479322e1a50b48"},
 ]
 
 [package.dependencies]
@@ -2530,57 +2575,57 @@ wrapt = ">=1.0.0,<2.0.0"
 
 [[package]]
 name = "opentelemetry-instrumentation-asgi"
-version = "0.43b0"
+version = "0.44b0"
 description = "ASGI instrumentation for OpenTelemetry"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation_asgi-0.43b0-py3-none-any.whl", hash = "sha256:1f593829fa039e9367820736fb063e92acd15c25b53d7bcb5d319971b8e93fd7"},
-    {file = "opentelemetry_instrumentation_asgi-0.43b0.tar.gz", hash = "sha256:3f6f19333dca31ef696672e4e36cb1c2613c71dc7e847c11ff36a37e1130dadc"},
+    {file = "opentelemetry_instrumentation_asgi-0.44b0-py3-none-any.whl", hash = "sha256:0d95c84a8991008c8a8ac35e15d43cc7768a5bb46f95f129e802ad2990d7c366"},
+    {file = "opentelemetry_instrumentation_asgi-0.44b0.tar.gz", hash = "sha256:72d4d28ec7ccd551eac11edc5ae8cac3586c0a228467d6a95fad7b6d4edd597a"},
 ]
 
 [package.dependencies]
 asgiref = ">=3.0,<4.0"
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.43b0"
-opentelemetry-semantic-conventions = "0.43b0"
-opentelemetry-util-http = "0.43b0"
+opentelemetry-instrumentation = "0.44b0"
+opentelemetry-semantic-conventions = "0.44b0"
+opentelemetry-util-http = "0.44b0"
 
 [package.extras]
 instruments = ["asgiref (>=3.0,<4.0)"]
-test = ["opentelemetry-instrumentation-asgi[instruments]", "opentelemetry-test-utils (==0.43b0)"]
+test = ["opentelemetry-instrumentation-asgi[instruments]", "opentelemetry-test-utils (==0.44b0)"]
 
 [[package]]
 name = "opentelemetry-instrumentation-fastapi"
-version = "0.43b0"
+version = "0.44b0"
 description = "OpenTelemetry FastAPI Instrumentation"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation_fastapi-0.43b0-py3-none-any.whl", hash = "sha256:b79c044df68a52e07b35fa12a424e7cc0dd27ff0a171c5fdcc41dea9de8fc938"},
-    {file = "opentelemetry_instrumentation_fastapi-0.43b0.tar.gz", hash = "sha256:2afaaf470622e1a2732182c68f6d2431ffe5e026a7edacd0f83605632b66347f"},
+    {file = "opentelemetry_instrumentation_fastapi-0.44b0-py3-none-any.whl", hash = "sha256:4441482944bea6676816668d56deb94af990e8c6e9582c581047e5d84c91d3c9"},
+    {file = "opentelemetry_instrumentation_fastapi-0.44b0.tar.gz", hash = "sha256:67ed10b93ad9d35238ae0be73cf8acbbb65a4a61fb7444d0aee5b0c492e294db"},
 ]
 
 [package.dependencies]
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.43b0"
-opentelemetry-instrumentation-asgi = "0.43b0"
-opentelemetry-semantic-conventions = "0.43b0"
-opentelemetry-util-http = "0.43b0"
+opentelemetry-instrumentation = "0.44b0"
+opentelemetry-instrumentation-asgi = "0.44b0"
+opentelemetry-semantic-conventions = "0.44b0"
+opentelemetry-util-http = "0.44b0"
 
 [package.extras]
 instruments = ["fastapi (>=0.58,<1.0)"]
-test = ["httpx (>=0.22,<1.0)", "opentelemetry-instrumentation-fastapi[instruments]", "opentelemetry-test-utils (==0.43b0)", "requests (>=2.23,<3.0)"]
+test = ["httpx (>=0.22,<1.0)", "opentelemetry-instrumentation-fastapi[instruments]", "opentelemetry-test-utils (==0.44b0)", "requests (>=2.23,<3.0)"]
 
 [[package]]
 name = "opentelemetry-proto"
-version = "1.22.0"
+version = "1.23.0"
 description = "OpenTelemetry Python Proto"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_proto-1.22.0-py3-none-any.whl", hash = "sha256:ce7188d22c75b6d0fe53e7fb58501613d0feade5139538e79dedd9420610fa0c"},
-    {file = "opentelemetry_proto-1.22.0.tar.gz", hash = "sha256:9ec29169286029f17ca34ec1f3455802ffb90131642d2f545ece9a63e8f69003"},
+    {file = "opentelemetry_proto-1.23.0-py3-none-any.whl", hash = "sha256:4c017deca052cb287a6003b7c989ed8b47af65baeb5d57ebf93dde0793f78509"},
+    {file = "opentelemetry_proto-1.23.0.tar.gz", hash = "sha256:e6aaf8b7ace8d021942d546161401b83eed90f9f2cc6f13275008cea730e4651"},
 ]
 
 [package.dependencies]
@@ -2588,40 +2633,99 @@ protobuf = ">=3.19,<5.0"
 
 [[package]]
 name = "opentelemetry-sdk"
-version = "1.22.0"
+version = "1.23.0"
 description = "OpenTelemetry Python SDK"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_sdk-1.22.0-py3-none-any.whl", hash = "sha256:a730555713d7c8931657612a88a141e3a4fe6eb5523d9e2d5a8b1e673d76efa6"},
-    {file = "opentelemetry_sdk-1.22.0.tar.gz", hash = "sha256:45267ac1f38a431fc2eb5d6e0c0d83afc0b78de57ac345488aa58c28c17991d0"},
+    {file = "opentelemetry_sdk-1.23.0-py3-none-any.whl", hash = "sha256:a93c96990ac0f07c6d679e2f1015864ff7a4f5587122dd5af968034436efb1fd"},
+    {file = "opentelemetry_sdk-1.23.0.tar.gz", hash = "sha256:9ddf60195837b59e72fd2033d6a47e2b59a0f74f0ec37d89387d89e3da8cab7f"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.22.0"
-opentelemetry-semantic-conventions = "0.43b0"
+opentelemetry-api = "1.23.0"
+opentelemetry-semantic-conventions = "0.44b0"
 typing-extensions = ">=3.7.4"
 
 [[package]]
 name = "opentelemetry-semantic-conventions"
-version = "0.43b0"
+version = "0.44b0"
 description = "OpenTelemetry Semantic Conventions"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_semantic_conventions-0.43b0-py3-none-any.whl", hash = "sha256:291284d7c1bf15fdaddf309b3bd6d3b7ce12a253cec6d27144439819a15d8445"},
-    {file = "opentelemetry_semantic_conventions-0.43b0.tar.gz", hash = "sha256:b9576fb890df479626fa624e88dde42d3d60b8b6c8ae1152ad157a8b97358635"},
+    {file = "opentelemetry_semantic_conventions-0.44b0-py3-none-any.whl", hash = "sha256:7c434546c9cbd797ab980cc88bf9ff3f4a5a28f941117cad21694e43d5d92019"},
+    {file = "opentelemetry_semantic_conventions-0.44b0.tar.gz", hash = "sha256:2e997cb28cd4ca81a25a9a43365f593d0c2b76be0685015349a89abdf1aa4ffa"},
 ]
 
 [[package]]
 name = "opentelemetry-util-http"
-version = "0.43b0"
+version = "0.44b0"
 description = "Web util for OpenTelemetry"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_util_http-0.43b0-py3-none-any.whl", hash = "sha256:f25a820784b030f6cb86b3d76e5676c769b75ed3f55a210bcdae0a5e175ebadb"},
-    {file = "opentelemetry_util_http-0.43b0.tar.gz", hash = "sha256:3ff6ab361dbe99fc81200d625603c0fb890c055c6e416a3e6d661ddf47a6c7f7"},
+    {file = "opentelemetry_util_http-0.44b0-py3-none-any.whl", hash = "sha256:ff018ab6a2fa349537ff21adcef99a294248b599be53843c44f367aef6bccea5"},
+    {file = "opentelemetry_util_http-0.44b0.tar.gz", hash = "sha256:75896dffcbbeb5df5429ad4526e22307fc041a27114e0c5bfd90bb219381e68f"},
+]
+
+[[package]]
+name = "orjson"
+version = "3.9.15"
+description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "orjson-3.9.15-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:d61f7ce4727a9fa7680cd6f3986b0e2c732639f46a5e0156e550e35258aa313a"},
+    {file = "orjson-3.9.15-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4feeb41882e8aa17634b589533baafdceb387e01e117b1ec65534ec724023d04"},
+    {file = "orjson-3.9.15-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:fbbeb3c9b2edb5fd044b2a070f127a0ac456ffd079cb82746fc84af01ef021a4"},
+    {file = "orjson-3.9.15-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b66bcc5670e8a6b78f0313bcb74774c8291f6f8aeef10fe70e910b8040f3ab75"},
+    {file = "orjson-3.9.15-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2973474811db7b35c30248d1129c64fd2bdf40d57d84beed2a9a379a6f57d0ab"},
+    {file = "orjson-3.9.15-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9fe41b6f72f52d3da4db524c8653e46243c8c92df826ab5ffaece2dba9cccd58"},
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@@ -2712,6 +2816,7 @@ parquet = ["pyarrow (>=10.0.1)"]
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 plot = ["matplotlib (>=3.6.3)"]
 postgresql = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "psycopg2 (>=2.9.6)"]
+pyarrow = ["pyarrow (>=10.0.1)"]
 spss = ["pyreadstat (>=1.2.0)"]
 sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)"]
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@@ -2744,13 +2849,13 @@ ptyprocess = ">=0.5"
 
 [[package]]
 name = "pg8000"
-version = "1.30.4"
+version = "1.30.5"
 description = "PostgreSQL interface library"
 optional = true
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -2887,13 +2992,13 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
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-version = "3.4.1"
+version = "3.4.2"
 description = "Integrate PostHog into any python application."
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 [package.dependencies]
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 [[package]]
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+version = "3.10.0"
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 python-versions = ">=3.8"
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 [package.dependencies]
 wcwidth = "*"
 
 [package.extras]
-tests = ["pytest", "pytest-cov", "pytest-lazy-fixture"]
+tests = ["pytest", "pytest-cov", "pytest-lazy-fixtures"]
 
 [[package]]
 name = "prompt-toolkit"
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 [[package]]
 name = "pydantic"
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 typing-extensions = ">=4.6.1"
 
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 [package.dependencies]
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 ]
 
 [package.dependencies]
@@ -3414,13 +3524,13 @@ files = [
 
 [[package]]
 name = "pyright"
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+version = "1.1.351"
 description = "Command line wrapper for pyright"
 optional = true
 python-versions = ">=3.7"
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 [package.dependencies]
@@ -3470,6 +3580,20 @@ pytest = ">=7.0.0,<9"
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
 testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
+[[package]]
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+version = "1.2.0"
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+optional = true
+python-versions = ">=3.6"
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+
 [[package]]
 name = "python-box"
 version = "7.1.1"
@@ -4376,36 +4500,36 @@ files = [
 
 [[package]]
 name = "torch"
-version = "2.2.0"
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 python-versions = ">=3.8.0"
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-    {file = "torch-2.2.0-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:08f53ccc38c49d839bc703ea1b20769cc8a429e0c4b20b56921a9f64949bf325"},
-    {file = "torch-2.2.0-cp38-cp38-win_amd64.whl", hash = "sha256:93bffe3779965a71dab25fc29787538c37c5d54298fd2f2369e372b6fb137d41"},
-    {file = "torch-2.2.0-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:c17ec323da778efe8dad49d8fb534381479ca37af1bfc58efdbb8607a9d263a3"},
-    {file = "torch-2.2.0-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:c02685118008834e878f676f81eab3a952b7936fa31f474ef8a5ff4b5c78b36d"},
-    {file = "torch-2.2.0-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:d9f39d6f53cec240a0e3baa82cb697593340f9d4554cee6d3d6ca07925c2fac0"},
-    {file = "torch-2.2.0-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:51770c065206250dc1222ea7c0eff3f88ab317d3e931cca2aee461b85fbc2472"},
-    {file = "torch-2.2.0-cp39-cp39-win_amd64.whl", hash = "sha256:008e4c6ad703de55af760c73bf937ecdd61a109f9b08f2bbb9c17e7c7017f194"},
-    {file = "torch-2.2.0-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:de8680472dd14e316f42ceef2a18a301461a9058cd6e99a1f1b20f78f11412f1"},
-    {file = "torch-2.2.0-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:99e1dcecb488e3fd25bcaac56e48cdb3539842904bdc8588b0b255fde03a254c"},
+    {file = "torch-2.2.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:8d3bad336dd2c93c6bcb3268e8e9876185bda50ebde325ef211fb565c7d15273"},
+    {file = "torch-2.2.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:5297f13370fdaca05959134b26a06a7f232ae254bf2e11a50eddec62525c9006"},
+    {file = "torch-2.2.1-cp310-cp310-win_amd64.whl", hash = "sha256:5f5dee8433798888ca1415055f5e3faf28a3bad660e4c29e1014acd3275ab11a"},
+    {file = "torch-2.2.1-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:b6d78338acabf1fb2e88bf4559d837d30230cf9c3e4337261f4d83200df1fcbe"},
+    {file = "torch-2.2.1-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:6ab3ea2e29d1aac962e905142bbe50943758f55292f1b4fdfb6f4792aae3323e"},
+    {file = "torch-2.2.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:d86664ec85902967d902e78272e97d1aff1d331f7619d398d3ffab1c9b8e9157"},
+    {file = "torch-2.2.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:d6227060f268894f92c61af0a44c0d8212e19cb98d05c20141c73312d923bc0a"},
+    {file = "torch-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:77e990af75fb1675490deb374d36e726f84732cd5677d16f19124934b2409ce9"},
+    {file = "torch-2.2.1-cp311-none-macosx_10_9_x86_64.whl", hash = "sha256:46085e328d9b738c261f470231e987930f4cc9472d9ffb7087c7a1343826ac51"},
+    {file = "torch-2.2.1-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:2d9e7e5ecbb002257cf98fae13003abbd620196c35f85c9e34c2adfb961321ec"},
+    {file = "torch-2.2.1-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:ada53aebede1c89570e56861b08d12ba4518a1f8b82d467c32665ec4d1f4b3c8"},
+    {file = "torch-2.2.1-cp312-cp312-manylinux2014_aarch64.whl", hash = "sha256:be21d4c41ecebed9e99430dac87de1439a8c7882faf23bba7fea3fea7b906ac1"},
+    {file = "torch-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:79848f46196750367dcdf1d2132b722180b9d889571e14d579ae82d2f50596c5"},
+    {file = "torch-2.2.1-cp312-none-macosx_10_9_x86_64.whl", hash = "sha256:7ee804847be6be0032fbd2d1e6742fea2814c92bebccb177f0d3b8e92b2d2b18"},
+    {file = "torch-2.2.1-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:84b2fb322ab091039fdfe74e17442ff046b258eb5e513a28093152c5b07325a7"},
+    {file = "torch-2.2.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:5c0c83aa7d94569997f1f474595e808072d80b04d34912ce6f1a0e1c24b0c12a"},
+    {file = "torch-2.2.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:91a1b598055ba06b2c386415d2e7f6ac818545e94c5def597a74754940188513"},
+    {file = "torch-2.2.1-cp38-cp38-win_amd64.whl", hash = "sha256:8f93ddf3001ecec16568390b507652644a3a103baa72de3ad3b9c530e3277098"},
+    {file = "torch-2.2.1-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:0e8bdd4c77ac2584f33ee14c6cd3b12767b4da508ec4eed109520be7212d1069"},
+    {file = "torch-2.2.1-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:6a21bcd7076677c97ca7db7506d683e4e9db137e8420eb4a68fb67c3668232a7"},
+    {file = "torch-2.2.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:f1b90ac61f862634039265cd0f746cc9879feee03ff962c803486301b778714b"},
+    {file = "torch-2.2.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:ed9e29eb94cd493b36bca9cb0b1fd7f06a0688215ad1e4b3ab4931726e0ec092"},
+    {file = "torch-2.2.1-cp39-cp39-win_amd64.whl", hash = "sha256:c47bc25744c743f3835831a20efdcfd60aeb7c3f9804a213f61e45803d16c2a5"},
+    {file = "torch-2.2.1-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:0952549bcb43448c8d860d5e3e947dd18cbab491b14638e21750cb3090d5ad3e"},
+    {file = "torch-2.2.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:26bd2272ec46fc62dcf7d24b2fb284d44fcb7be9d529ebf336b9860350d674ed"},
 ]
 
 [package.dependencies]
@@ -4425,7 +4549,7 @@ nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"
 nvidia-nccl-cu12 = {version = "2.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
-triton = {version = "2.2.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+triton = {version = "2.2.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
@@ -4694,13 +4818,13 @@ test = ["Cython (>=0.29.36,<0.30.0)", "aiohttp (==3.9.0b0)", "aiohttp (>=3.8.1)"
 
 [[package]]
 name = "virtualenv"
-version = "20.25.0"
+version = "20.25.1"
 description = "Virtual Python Environment builder"
 optional = true
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.25.0-py3-none-any.whl", hash = "sha256:4238949c5ffe6876362d9c0180fc6c3a824a7b12b80604eeb8085f2ed7460de3"},
-    {file = "virtualenv-20.25.0.tar.gz", hash = "sha256:bf51c0d9c7dd63ea8e44086fa1e4fb1093a31e963b86959257378aef020e1f1b"},
+    {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
+    {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
 ]
 
 [package.dependencies]
@@ -5223,7 +5347,7 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 
 [extras]
 autogen = ["pyautogen"]
-dev = ["black", "datasets", "pexpect", "pre-commit", "pyright", "pytest", "pytest-asyncio"]
+dev = ["black", "datasets", "pexpect", "pre-commit", "pyright", "pytest", "pytest-asyncio", "pytest-order"]
 local = ["huggingface-hub", "torch", "transformers"]
 postgres = ["pg8000", "pgvector"]
 server = ["fastapi", "uvicorn", "websockets"]
@@ -5231,4 +5355,4 @@ server = ["fastapi", "uvicorn", "websockets"]
 [metadata]
 lock-version = "2.0"
 python-versions = "<3.12,>=3.10"
-content-hash = "3d81b1d8c0327b4b0e3aab58bdc42747b3db4a58614de5fe885e0a85fb0dd8ef"
+content-hash = "54b8e1032e102309af93436084f4f252944c9426d357264797c2e70d55894dbd"
diff --git a/pyproject.toml b/pyproject.toml
index f4e65db52b..eb1338eccd 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -55,11 +55,12 @@ pyright = {version = "^1.1.347", optional = true}
 llama-index = "^0.10.6"
 llama-index-embeddings-openai = "^0.1.1"
 python-box = "^7.1.1"
+pytest-order = {version = "^1.2.0", optional = true}
 
 [tool.poetry.extras]
 local = ["torch", "huggingface-hub", "transformers"]
 postgres = ["pgvector", "pg8000"]
-dev = ["pytest", "pytest-asyncio", "pexpect", "black", "pre-commit", "datasets", "pyright"]
+dev = ["pytest", "pytest-asyncio", "pexpect", "black", "pre-commit", "datasets", "pyright", "pytest-order"]
 server = ["websockets", "fastapi", "uvicorn"]
 autogen = ["pyautogen"]
 
diff --git a/tests/test_server.py b/tests/test_server.py
index b140ddb767..0272560438 100644
--- a/tests/test_server.py
+++ b/tests/test_server.py
@@ -1,4 +1,5 @@
 import uuid
+import pytest
 import os
 import memgpt.utils as utils
 from dotenv import load_dotenv
@@ -10,10 +11,11 @@
 from memgpt.data_types import EmbeddingConfig, AgentState, LLMConfig, Message, Passage, User
 from memgpt.embeddings import embedding_model
 from memgpt.presets.presets import add_default_presets
-from .utils import wipe_config, wipe_memgpt_home
+from .utils import wipe_config, wipe_memgpt_home, DummyDataConnector
 
 
-def test_server():
+@pytest.fixture(scope="module")
+def server():
     load_dotenv()
     wipe_config()
     wipe_memgpt_home()
@@ -73,36 +75,56 @@ def test_server():
     credentials.save()
 
     server = SyncServer()
+    return server
 
+
+@pytest.fixture(scope="module")
+def user_id(server):
     # create user
     user = server.create_user()
     print(f"Created user\n{user.id}")
 
-    try:
-        fake_agent_id = uuid.uuid4()
-        server.user_message(user_id=user.id, agent_id=fake_agent_id, message="Hello?")
-        raise Exception("user_message call should have failed")
-    except (KeyError, ValueError) as e:
-        # Error is expected
-        print(e)
-    except:
-        raise
+    # initialize with default presets
+    server.initialize_default_presets(user.id)
+    yield user.id
+
+    # cleanup
+    server.delete_user(user.id)
 
-    # create presets
-    add_default_presets(user.id, server.ms)
 
+@pytest.fixture(scope="module")
+def agent_id(server, user_id):
     # create agent
     agent_state = server.create_agent(
-        user_id=user.id,
+        user_id=user_id,
         name="test_agent",
         preset="memgpt_chat",
         human="cs_phd",
         persona="sam_pov",
     )
     print(f"Created agent\n{agent_state}")
+    yield agent_state.id
+
+    # cleanup
+    server.delete_agent(user_id, agent_state.id)
+
+
+def test_error_on_nonexistent_agent(server, user_id, agent_id):
+    try:
+        fake_agent_id = uuid.uuid4()
+        server.user_message(user_id=user_id, agent_id=fake_agent_id, message="Hello?")
+        raise Exception("user_message call should have failed")
+    except (KeyError, ValueError) as e:
+        # Error is expected
+        print(e)
+    except:
+        raise
+
 
+@pytest.mark.order(1)
+def test_user_message(server, user_id, agent_id):
     try:
-        server.user_message(user_id=user.id, agent_id=agent_state.id, message="/memory")
+        server.user_message(user_id=user_id, agent_id=agent_id, message="/memory")
         raise Exception("user_message call should have failed")
     except ValueError as e:
         # Error is expected
@@ -110,62 +132,93 @@ def test_server():
     except:
         raise
 
-    print(server.run_command(user_id=user.id, agent_id=agent_state.id, command="/memory"))
+    server.run_command(user_id=user_id, agent_id=agent_id, command="/memory")
+
 
-    # add data into archival memory
-    agent = server._load_agent(user_id=user.id, agent_id=agent_state.id)
+@pytest.mark.order(3)
+def test_load_data(server, user_id, agent_id):
+    # create source
+    source = server.create_source("test_source", user_id)
+
+    # load data
     archival_memories = ["alpha", "Cinderella wore a blue dress", "Dog eat dog", "ZZZ", "Shishir loves indian food"]
-    embed_model = embedding_model(agent.agent_state.embedding_config)
-    for text in archival_memories:
-        embedding = embed_model.get_text_embedding(text)
-        agent.persistence_manager.archival_memory.storage.insert(
-            Passage(
-                user_id=user.id,
-                agent_id=agent_state.id,
-                text=text,
-                embedding=embedding,
-                embedding_dim=agent.agent_state.embedding_config.embedding_dim,
-                embedding_model=agent.agent_state.embedding_config.embedding_model,
-            )
-        )
+    connector = DummyDataConnector(archival_memories)
+    server.load_data(user_id, connector, source.name)
+
 
+@pytest.mark.order(3)
+def test_attach_source_to_agent(server, user_id, agent_id):
+    # check archival memory size
+    passages_before = server.get_agent_archival(user_id=user_id, agent_id=agent_id, start=0, count=10000)
+    assert len(passages_before) == 0
+
+    # attach source
+    server.attach_source_to_agent(user_id, agent_id, "test_source")
+
+    # check archival memory size
+    passages_after = server.get_agent_archival(user_id=user_id, agent_id=agent_id, start=0, count=10000)
+    assert len(passages_after) == 5
+
+
+def test_save_archival_memory(server, user_id, agent_id):
+    # TODO: insert into archival memory
+    pass
+
+
+@pytest.mark.order(4)
+def test_user_message(server, user_id, agent_id):
     # add data into recall memory
-    server.user_message(user_id=user.id, agent_id=agent_state.id, message="Hello?")
-    server.user_message(user_id=user.id, agent_id=agent_state.id, message="Hello?")
-    server.user_message(user_id=user.id, agent_id=agent_state.id, message="Hello?")
-    server.user_message(user_id=user.id, agent_id=agent_state.id, message="Hello?")
-    server.user_message(user_id=user.id, agent_id=agent_state.id, message="Hello?")
+    server.user_message(user_id=user_id, agent_id=agent_id, message="Hello?")
+    server.user_message(user_id=user_id, agent_id=agent_id, message="Hello?")
+    server.user_message(user_id=user_id, agent_id=agent_id, message="Hello?")
+    server.user_message(user_id=user_id, agent_id=agent_id, message="Hello?")
+    server.user_message(user_id=user_id, agent_id=agent_id, message="Hello?")
+
 
+@pytest.mark.order5
+def test_get_recall_memory(server, user_id, agent_id):
     # test recall memory cursor pagination
-    cursor1, messages_1 = server.get_agent_recall_cursor(user_id=user.id, agent_id=agent_state.id, reverse=True, limit=2)
-    cursor2, messages_2 = server.get_agent_recall_cursor(user_id=user.id, agent_id=agent_state.id, reverse=True, after=cursor1, limit=1000)
-    cursor3, messages_3 = server.get_agent_recall_cursor(user_id=user.id, agent_id=agent_state.id, reverse=True, limit=1000)
+    cursor1, messages_1 = server.get_agent_recall_cursor(user_id=user_id, agent_id=agent_id, reverse=True, limit=2)
+    cursor2, messages_2 = server.get_agent_recall_cursor(user_id=user_id, agent_id=agent_id, reverse=True, after=cursor1, limit=1000)
+    cursor3, messages_3 = server.get_agent_recall_cursor(user_id=user_id, agent_id=agent_id, reverse=True, limit=1000)
     ids3 = [m["id"] for m in messages_3]
     ids2 = [m["id"] for m in messages_2]
     timestamps = [m["created_at"] for m in messages_3]
     print("timestamps", timestamps)
     assert messages_3[-1]["created_at"] < messages_3[0]["created_at"]
     assert len(messages_3) == len(messages_1) + len(messages_2)
-    cursor4, messages_4 = server.get_agent_recall_cursor(user_id=user.id, agent_id=agent_state.id, reverse=True, before=cursor1)
+    cursor4, messages_4 = server.get_agent_recall_cursor(user_id=user_id, agent_id=agent_id, reverse=True, before=cursor1)
     assert len(messages_4) == 1
 
     # test in-context message ids
-    in_context_ids = server.get_in_context_message_ids(user_id=user.id, agent_id=agent_state.id)
+    in_context_ids = server.get_in_context_message_ids(user_id=user_id, agent_id=agent_id)
     assert len(in_context_ids) == len(messages_3)
     assert isinstance(in_context_ids[0], uuid.UUID)
     message_ids = [m["id"] for m in messages_3]
     for message_id in message_ids:
         assert message_id in in_context_ids, f"{message_id} not in {in_context_ids}"
 
+    # test recall memory
+    messages_1 = server.get_agent_messages(user_id=user_id, agent_id=agent_id, start=0, count=1)
+    assert len(messages_1) == 1
+    messages_2 = server.get_agent_messages(user_id=user_id, agent_id=agent_id, start=1, count=1000)
+    messages_3 = server.get_agent_messages(user_id=user_id, agent_id=agent_id, start=1, count=5)
+    # not sure exactly how many messages there should be
+    assert len(messages_2) > len(messages_3)
+    # test safe empty return
+    messages_none = server.get_agent_messages(user_id=user_id, agent_id=agent_id, start=1000, count=1000)
+    assert len(messages_none) == 0
+
+
+@pytest.mark.order6
+def test_get_archival_memory(server, user_id, agent_id):
     # test archival memory cursor pagination
-    cursor1, passages_1 = server.get_agent_archival_cursor(
-        user_id=user.id, agent_id=agent_state.id, reverse=False, limit=2, order_by="text"
-    )
+    cursor1, passages_1 = server.get_agent_archival_cursor(user_id=user_id, agent_id=agent_id, reverse=False, limit=2, order_by="text")
     cursor2, passages_2 = server.get_agent_archival_cursor(
-        user_id=user.id, agent_id=agent_state.id, reverse=False, after=cursor1, order_by="text"
+        user_id=user_id, agent_id=agent_id, reverse=False, after=cursor1, order_by="text"
     )
     cursor3, passages_3 = server.get_agent_archival_cursor(
-        user_id=user.id, agent_id=agent_state.id, reverse=False, before=cursor2, limit=1000, order_by="text"
+        user_id=user_id, agent_id=agent_id, reverse=False, before=cursor2, limit=1000, order_by="text"
     )
     print("p1", [p["text"] for p in passages_1])
     print("p2", [p["text"] for p in passages_2])
@@ -174,26 +227,11 @@ def test_server():
     assert len(passages_2) == 3
     assert len(passages_3) == 4
 
-    # test recall memory
-    messages_1 = server.get_agent_messages(user_id=user.id, agent_id=agent_state.id, start=0, count=1)
-    assert len(messages_1) == 1
-    messages_2 = server.get_agent_messages(user_id=user.id, agent_id=agent_state.id, start=1, count=1000)
-    messages_3 = server.get_agent_messages(user_id=user.id, agent_id=agent_state.id, start=1, count=5)
-    # not sure exactly how many messages there should be
-    assert len(messages_2) > len(messages_3)
-    # test safe empty return
-    messages_none = server.get_agent_messages(user_id=user.id, agent_id=agent_state.id, start=1000, count=1000)
-    assert len(messages_none) == 0
-
     # test archival memory
-    passage_1 = server.get_agent_archival(user_id=user.id, agent_id=agent_state.id, start=0, count=1)
+    passage_1 = server.get_agent_archival(user_id=user_id, agent_id=agent_id, start=0, count=1)
     assert len(passage_1) == 1
-    passage_2 = server.get_agent_archival(user_id=user.id, agent_id=agent_state.id, start=1, count=1000)
+    passage_2 = server.get_agent_archival(user_id=user_id, agent_id=agent_id, start=1, count=1000)
     assert len(passage_2) == 4
     # test safe empty return
-    passage_none = server.get_agent_archival(user_id=user.id, agent_id=agent_state.id, start=1000, count=1000)
+    passage_none = server.get_agent_archival(user_id=user_id, agent_id=agent_id, start=1000, count=1000)
     assert len(passage_none) == 0
-
-
-if __name__ == "__main__":
-    test_server()
diff --git a/tests/utils.py b/tests/utils.py
index 5225902f4c..973c420e08 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -1,13 +1,32 @@
 import datetime
+from typing import Dict, List, Tuple, Iterator
 import os
 
 from memgpt.config import MemGPTConfig
 from memgpt.cli.cli import quickstart, QuickstartChoice
+from memgpt.data_sources.connectors import DataConnector
 from memgpt import Admin
+from memgpt.data_types import Document
 
 from .constants import TIMEOUT
 
 
+class DummyDataConnector(DataConnector):
+
+    """Fake data connector for texting which yields document/passage texts from a provided list"""
+
+    def __init__(self, texts: List[str]):
+        self.texts = texts
+
+    def generate_documents(self) -> Iterator[Tuple[str, Dict]]:
+        for text in self.texts:
+            yield text, {"metadata": "dummy"}
+
+    def generate_passages(self, documents: List[Document], chunk_size: int = 1024) -> Iterator[Tuple[str | Dict]]:
+        for doc in documents:
+            yield doc.text, doc.metadata
+
+
 def create_config(endpoint="openai"):
     """Create config file matching quickstart option"""
     if endpoint == "openai":