From dd7e5a7ab5f09ba9c646d848f7a0e4248bdbf8db Mon Sep 17 00:00:00 2001
From: Gabriel Luiz Freitas Almeida <gabriel@logspace.ai>
Date: Tue, 16 Apr 2024 13:22:31 -0300
Subject: [PATCH 1/4] Add from_lc_message method to Record class in schema.py

---
 src/backend/base/langflow/schema/schema.py | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/src/backend/base/langflow/schema/schema.py b/src/backend/base/langflow/schema/schema.py
index a48e72339..dffa04dae 100644
--- a/src/backend/base/langflow/schema/schema.py
+++ b/src/backend/base/langflow/schema/schema.py
@@ -2,6 +2,7 @@ import copy
 from typing import Literal, Optional
 
 from langchain_core.documents import Document
+from langchain_core.messages import BaseMessage
 from pydantic import BaseModel, model_validator
 
 
@@ -54,6 +55,21 @@ class Record(BaseModel):
         data["text"] = document.page_content
         return cls(data=data, text_key="text")
 
+    @classmethod
+    def from_lc_message(cls, message: BaseMessage) -> "Record":
+        """
+        Converts a BaseMessage to a Record.
+
+        Args:
+            message (BaseMessage): The BaseMessage to convert.
+
+        Returns:
+            Record: The converted Record.
+        """
+        data = {"text": message.content}
+        data["metadata"] = message.to_json()
+        return cls(data=data, text_key="text")
+
     def __add__(self, other: "Record") -> "Record":
         """
         Combines the data of two records by attempting to add values for overlapping keys

From 42e88b7a2375f2a84ed333419dcc663c3623e142 Mon Sep 17 00:00:00 2001
From: Gabriel Luiz Freitas Almeida <gabriel@logspace.ai>
Date: Tue, 16 Apr 2024 13:57:05 -0300
Subject: [PATCH 2/4] Add Experimental Agent Component (#1705)

* Update langflow base prompts API utils and add ToolCallingAgentComponent

* Update return type annotations in AzureOpenAIModel.py and ChatLiteLLMModel.py

* Update langchainhub package version to 0.1.15

* Update langflow base prompts API utils and add ToolCallingAgentComponent

* Add AgentComponent to langflow experimental components

* Update prompt variable name to user_prompt in ToolCallingAgentComponent.py

* Update prompt variable name to system_message in AgentComponent.py

* Update system_message variable name in XMLAgentComponent and ToolCallingAgentComponent

* Update prompt variable name to user_prompt in ToolCallingAgentComponent.py
---
 poetry.lock                                   | 345 +++++++++---------
 .../base/langflow/base/agents/agent.py        |  19 +-
 .../langflow/base/agents/default_prompts.py   |  23 ++
 .../base/langflow/base/agents/utils.py        | 143 ++++++++
 .../components/agents/ToolCallingAgent.py     |  64 ++++
 .../langflow/components/agents/XMLAgent.py    |  48 ++-
 .../components/experimental/AgentComponent.py | 185 ++++++++++
 .../components/experimental/__init__.py       |   2 +
 .../components/models/AzureOpenAIModel.py     |   2 +-
 .../components/models/ChatLiteLLMModel.py     |   2 +-
 src/backend/base/langflow/schema/schema.py    |  21 ++
 src/backend/base/poetry.lock                  |  31 +-
 src/backend/base/pyproject.toml               |   1 +
 13 files changed, 695 insertions(+), 191 deletions(-)
 create mode 100644 src/backend/base/langflow/base/agents/default_prompts.py
 create mode 100644 src/backend/base/langflow/base/agents/utils.py
 create mode 100644 src/backend/base/langflow/components/agents/ToolCallingAgent.py
 create mode 100644 src/backend/base/langflow/components/experimental/AgentComponent.py

diff --git a/poetry.lock b/poetry.lock
index 3b52cf6ea..59e2f80b8 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1149,13 +1149,13 @@ types = ["chardet (>=5.1.0)", "mypy", "pytest", "pytest-cov", "pytest-dependency
 
 [[package]]
 name = "cohere"
-version = "5.2.5"
+version = "5.2.6"
 description = ""
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "cohere-5.2.5-py3-none-any.whl", hash = "sha256:c29691eadd29c1253a5d9168c5a15a23583b982b0ffcfb9eace5dc17fddacb1a"},
-    {file = "cohere-5.2.5.tar.gz", hash = "sha256:5909083a9b00630108c009193fa02405dea176acc4262c590002a49ca8f7bdde"},
+    {file = "cohere-5.2.6-py3-none-any.whl", hash = "sha256:256b4ed00f47eb315401d7f28834655714f098382908e7d0ad5c98225aa6a57d"},
+    {file = "cohere-5.2.6.tar.gz", hash = "sha256:15d13682706fbafc8cf700e195f628389a643eb7ebd6d7c5e9d6e1ebd3f942fb"},
 ]
 
 [package.dependencies]
@@ -3850,6 +3850,21 @@ langchain-core = ">=0.1.28,<0.2.0"
 [package.extras]
 extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
 
+[[package]]
+name = "langchainhub"
+version = "0.1.15"
+description = "The LangChain Hub API client"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
+    {file = "langchainhub-0.1.15-py3-none-any.whl", hash = "sha256:89a0951abd1db255e91c6d545d092a598fc255aa865d1ffc3ce8f93bbeae60e7"},
+    {file = "langchainhub-0.1.15.tar.gz", hash = "sha256:fa3ff81a31946860f84c119f1e2f6b7c7707e2bd7ed2394a7313b286d59f3bda"},
+]
+
+[package.dependencies]
+requests = ">=2,<3"
+types-requests = ">=2.31.0.2,<3.0.0.0"
+
 [[package]]
 name = "langdetect"
 version = "1.0.9"
@@ -3888,6 +3903,7 @@ httpx = "*"
 jq = {version = "^1.7.0", markers = "sys_platform != \"win32\""}
 langchain = "~0.1.16"
 langchain-experimental = "*"
+langchainhub = "~0.1.15"
 loguru = "^0.7.1"
 multiprocess = "^0.70.14"
 nest-asyncio = "^1.6.0"
@@ -3920,13 +3936,13 @@ url = "src/backend/base"
 
 [[package]]
 name = "langfuse"
-version = "2.26.0"
+version = "2.26.1"
 description = "A client library for accessing langfuse"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langfuse-2.26.0-py3-none-any.whl", hash = "sha256:083e7d120d18bbe70b9d4d06f33483b96795110d2ebb2aed2e78d65c079a3ced"},
-    {file = "langfuse-2.26.0.tar.gz", hash = "sha256:c872a2cd5874bfad9780a6fcc7baa16c40de40cd50ce78d8fce59b01233d0464"},
+    {file = "langfuse-2.26.1-py3-none-any.whl", hash = "sha256:cbfb03028df42d5e1894860d889a5cdf7cbfbf56ef9deb974c6691a08c689692"},
+    {file = "langfuse-2.26.1.tar.gz", hash = "sha256:a95aab75d483614eb7ad8fd9f6e54078479c805e39098980caa676d9d42db54f"},
 ]
 
 [package.dependencies]
@@ -3976,13 +3992,13 @@ regex = ["regex"]
 
 [[package]]
 name = "litellm"
-version = "1.35.4"
+version = "1.35.5"
 description = "Library to easily interface with LLM API providers"
 optional = false
 python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
 files = [
-    {file = "litellm-1.35.4-py3-none-any.whl", hash = "sha256:d07f6ca96c275cb286ba5d0e8b2df9d02ea3919dcb45fcd6c3e4257d51911776"},
-    {file = "litellm-1.35.4.tar.gz", hash = "sha256:760175fe4fb8a8e71b2d4b739a93fbb9f2ef8813b1ead98862cdf30dc6bb77be"},
+    {file = "litellm-1.35.5-py3-none-any.whl", hash = "sha256:ffc7ad5550534f737097e8e33cef575dc806e5ff4c624aaec2b400e28c2b4ea3"},
+    {file = "litellm-1.35.5.tar.gz", hash = "sha256:4545d4af8cd177c1539968335920253ad44c38e09420854f142ffff9cdb3fff7"},
 ]
 
 [package.dependencies]
@@ -4024,19 +4040,19 @@ test = ["httpx (>=0.24.1)", "pytest (>=7.4.0)", "scipy (>=1.10)"]
 
 [[package]]
 name = "llama-index"
-version = "0.10.28"
+version = "0.10.29"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index-0.10.28-py3-none-any.whl", hash = "sha256:2fe2857af6c2d9cefdd978931ebd09f78265a57df2d9d094d0c78869dd0715b8"},
-    {file = "llama_index-0.10.28.tar.gz", hash = "sha256:2ecf9d6da489cc3f99b1adaea50b1549efa55e04cd050f332da784a87c2db846"},
+    {file = "llama_index-0.10.29-py3-none-any.whl", hash = "sha256:df61c04c05ddf0488aa87085c464e52ff215338933de771de46e2e4965719eaa"},
+    {file = "llama_index-0.10.29.tar.gz", hash = "sha256:f83b826007a8b4570a165f5db8ce770cf186adf7686ec0ddbeccf1887fcd5394"},
 ]
 
 [package.dependencies]
 llama-index-agent-openai = ">=0.1.4,<0.3.0"
 llama-index-cli = ">=0.1.2,<0.2.0"
-llama-index-core = ">=0.10.28,<0.11.0"
+llama-index-core = ">=0.10.29,<0.11.0"
 llama-index-embeddings-openai = ">=0.1.5,<0.2.0"
 llama-index-indices-managed-llama-cloud = ">=0.1.2,<0.2.0"
 llama-index-legacy = ">=0.9.48,<0.10.0"
@@ -4081,13 +4097,13 @@ llama-index-llms-openai = ">=0.1.1,<0.2.0"
 
 [[package]]
 name = "llama-index-core"
-version = "0.10.28"
+version = "0.10.29"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index_core-0.10.28-py3-none-any.whl", hash = "sha256:73e2ec86ea42a0efdc73dcfe46e03ba39ab7725699dcd791464c160d24a02cb1"},
-    {file = "llama_index_core-0.10.28.tar.gz", hash = "sha256:b454640396daa2678b638299e2a5e2539fa3548afd280d45d224fd3b303c20f4"},
+    {file = "llama_index_core-0.10.29-py3-none-any.whl", hash = "sha256:105eace45d877f31ff330e9afe7e86bd212b776b96d594862f24c60e03ab99b9"},
+    {file = "llama_index_core-0.10.29.tar.gz", hash = "sha256:65188c9917ec0847005ebd4343d7eaf9ddc80cea50d876a02eccbb16f1684371"},
 ]
 
 [package.dependencies]
@@ -4097,7 +4113,7 @@ deprecated = ">=1.2.9.3"
 dirtyjson = ">=1.0.8,<2.0.0"
 fsspec = ">=2023.5.0"
 httpx = "*"
-llamaindex-py-client = ">=0.1.16,<0.2.0"
+llamaindex-py-client = ">=0.1.18,<0.2.0"
 nest-asyncio = ">=1.5.8,<2.0.0"
 networkx = ">=3.0"
 nltk = ">=3.8.1,<4.0.0"
@@ -4254,13 +4270,13 @@ llama-index-program-openai = ">=0.1.1,<0.2.0"
 
 [[package]]
 name = "llama-index-readers-file"
-version = "0.1.17"
+version = "0.1.18"
 description = "llama-index readers file integration"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index_readers_file-0.1.17-py3-none-any.whl", hash = "sha256:4c14d489716704246bd65c08e0f8ea6005cf63cca5b94df38667598b1d3d1937"},
-    {file = "llama_index_readers_file-0.1.17.tar.gz", hash = "sha256:240660ca93c04383fc4aebfa9c9bdaeb43790a533e6886b4631a5fc7f00190ca"},
+    {file = "llama_index_readers_file-0.1.18-py3-none-any.whl", hash = "sha256:725fbce501eb7bdbb630b625e88985c51d55b99006b8b3342af4cefcb49bf51e"},
+    {file = "llama_index_readers_file-0.1.18.tar.gz", hash = "sha256:91c9871e80d7c911a4e2bb265ee46c3db6a93d681ba6ddf731752cd7764b368b"},
 ]
 
 [package.dependencies]
@@ -4289,17 +4305,17 @@ llama-parse = ">=0.4.0,<0.5.0"
 
 [[package]]
 name = "llama-parse"
-version = "0.4.0"
+version = "0.4.1"
 description = "Parse files into RAG-Optimized formats."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_parse-0.4.0-py3-none-any.whl", hash = "sha256:52b450c9bb94746c5f86867f54fd2e74670d89b385dcb879eb93490a42fda628"},
-    {file = "llama_parse-0.4.0.tar.gz", hash = "sha256:ee521e9422db48dbdf00303cb6e90f1066131960b5ca4e14f5b5a6db6b7917e2"},
+    {file = "llama_parse-0.4.1-py3-none-any.whl", hash = "sha256:2c08962b66791c61fc360ae2042f953729c7b8decc3590d01fea5a98ca1f6676"},
+    {file = "llama_parse-0.4.1.tar.gz", hash = "sha256:d723af84d6a1fc99eb431915d21865d20b76d8a246dbaa124d1f96c956a644f7"},
 ]
 
 [package.dependencies]
-llama-index-core = ">=0.10.7"
+llama-index-core = ">=0.10.29"
 
 [[package]]
 name = "llamaindex-py-client"
@@ -4318,13 +4334,13 @@ pydantic = ">=1.10"
 
 [[package]]
 name = "locust"
-version = "2.24.1"
+version = "2.25.0"
 description = "Developer friendly load testing framework"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "locust-2.24.1-py3-none-any.whl", hash = "sha256:7f6ed4dc289aad66c304582e6d25e4de5d7c3b175b580332442ab2be35b9d916"},
-    {file = "locust-2.24.1.tar.gz", hash = "sha256:094161d44d94839bf1120fd7898b7abb9c143833743ba7c096beb470a236b9a7"},
+    {file = "locust-2.25.0-py3-none-any.whl", hash = "sha256:35ee14d0a2b91d0d644150d0b628ce4569b0e1fec1c33c55040fa26cc693d085"},
+    {file = "locust-2.25.0.tar.gz", hash = "sha256:45bc88b3097f0346a46514f99ebf8d8a86f07325366da0b9dc2c3f207499dbc6"},
 ]
 
 [package.dependencies]
@@ -4679,13 +4695,13 @@ tests = ["pytest", "pytz", "simplejson"]
 
 [[package]]
 name = "matplotlib-inline"
-version = "0.1.6"
+version = "0.1.7"
 description = "Inline Matplotlib backend for Jupyter"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.8"
 files = [
-    {file = "matplotlib-inline-0.1.6.tar.gz", hash = "sha256:f887e5f10ba98e8d2b150ddcf4702c1e5f8b3a20005eb0f74bfdbd360ee6f304"},
-    {file = "matplotlib_inline-0.1.6-py3-none-any.whl", hash = "sha256:f1f41aab5328aa5aaea9b16d083b128102f8712542f819fe7e6a420ff581b311"},
+    {file = "matplotlib_inline-0.1.7-py3-none-any.whl", hash = "sha256:df192d39a4ff8f21b1895d72e6a13f5fcc5099f00fa84384e0ea28c2cc0653ca"},
+    {file = "matplotlib_inline-0.1.7.tar.gz", hash = "sha256:8423b23ec666be3d16e16b60bdd8ac4e86e840ebd1dd11a30b9f117f2fa0ab90"},
 ]
 
 [package.dependencies]
@@ -6438,41 +6454,41 @@ files = [
 
 [[package]]
 name = "pulsar-client"
-version = "3.4.0"
+version = "3.5.0"
 description = "Apache Pulsar Python client library"
 optional = false
 python-versions = "*"
 files = [
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+    {file = "pyzmq-26.0.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:08db8071020181173c70cf2dad239e5e21e5b2e95f95b0ece0da39a70f5a483c"},
+    {file = "pyzmq-26.0.0.tar.gz", hash = "sha256:10ff405db5cee3bbd7aa143d78b25d90356097aed7864e50f0ae644e08759fe9"},
 ]
 
 [package.dependencies]
@@ -8232,13 +8243,13 @@ transformers = ">=4.32.0,<5.0.0"
 
 [[package]]
 name = "setuptools"
-version = "69.5.0"
+version = "69.5.1"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "setuptools-69.5.0-py3-none-any.whl", hash = "sha256:3b2dbd8f63dcc6b7c327d0243c2d7dc8c96cc507c016f09221f3787e6e528719"},
-    {file = "setuptools-69.5.0.tar.gz", hash = "sha256:8d881f842bfc0e29e93bc98a2e650e8845609adff4d2989ba6c748e67b09d5be"},
+    {file = "setuptools-69.5.1-py3-none-any.whl", hash = "sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32"},
+    {file = "setuptools-69.5.1.tar.gz", hash = "sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987"},
 ]
 
 [package.extras]
@@ -8490,19 +8501,19 @@ files = [
 
 [[package]]
 name = "supabase"
-version = "2.4.1"
+version = "2.4.2"
 description = "Supabase client for Python."
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "supabase-2.4.1-py3-none-any.whl", hash = "sha256:8b95744ce4ad24245ec23c090f273dfc9c2d9a53e3a80186959903947dbe1ed6"},
-    {file = "supabase-2.4.1.tar.gz", hash = "sha256:a7dec0586f8931f378a45b2ffb28d8e37b3719f979c17f541b0156019144e645"},
+    {file = "supabase-2.4.2-py3-none-any.whl", hash = "sha256:ce5de33e56eeccd92caa529dc29f484f0d5de073fd543b7dfd969e8cc57f5f62"},
+    {file = "supabase-2.4.2.tar.gz", hash = "sha256:04e7095c3458e94a83f2b77493f788e730d148b2bc0c5d899de6f0bfb43d1ea6"},
 ]
 
 [package.dependencies]
 gotrue = ">=1.3,<3.0"
 httpx = ">=0.24,<0.28"
-postgrest = ">=0.10.8,<0.17.0"
+postgrest = ">=0.14,<0.17.0"
 realtime = ">=1.0.0,<2.0.0"
 storage3 = ">=0.5.3,<0.8.0"
 supafunc = ">=0.3.1,<0.5.0"
@@ -9045,13 +9056,13 @@ files = [
 
 [[package]]
 name = "types-pillow"
-version = "10.2.0.20240406"
+version = "10.2.0.20240415"
 description = "Typing stubs for Pillow"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-Pillow-10.2.0.20240406.tar.gz", hash = "sha256:62e0cc1f17caba40e72e7154a483f4c7f3bea0e1c34c0ebba9de3c7745bc306d"},
-    {file = "types_Pillow-10.2.0.20240406-py3-none-any.whl", hash = "sha256:5ac182e8afce53de30abca2fdf9cbec7b2500e549d0be84da035a729a84c7c47"},
+    {file = "types-Pillow-10.2.0.20240415.tar.gz", hash = "sha256:dd6058027639bcdc66ba78b228cc25fdae42524c2150c78c804da427e7e76e70"},
+    {file = "types_Pillow-10.2.0.20240415-py3-none-any.whl", hash = "sha256:f933332b7e96010bae9b9cf82a4c9979ff0c270d63f5c5bbffb2d789b85cd00b"},
 ]
 
 [[package]]
diff --git a/src/backend/base/langflow/base/agents/agent.py b/src/backend/base/langflow/base/agents/agent.py
index 5ef498b66..ce40f1f51 100644
--- a/src/backend/base/langflow/base/agents/agent.py
+++ b/src/backend/base/langflow/base/agents/agent.py
@@ -1,13 +1,19 @@
 from typing import List, Optional, Union, cast
 
 from langchain.agents import AgentExecutor, BaseMultiActionAgent, BaseSingleActionAgent
+from langchain_core.messages import BaseMessage
 from langchain_core.runnables import Runnable
 
+from langflow.base.agents.utils import get_agents_list, records_to_messages
 from langflow.custom import CustomComponent
-from langflow.field_typing import BaseMemory, Text, Tool
+from langflow.field_typing import Text, Tool
+from langflow.schema.schema import Record
 
 
 class LCAgentComponent(CustomComponent):
+    def get_agents_list(self):
+        return get_agents_list()
+
     def build_config(self):
         return {
             "lc": {
@@ -42,9 +48,8 @@ class LCAgentComponent(CustomComponent):
         self,
         agent: Union[Runnable, BaseSingleActionAgent, BaseMultiActionAgent, AgentExecutor],
         inputs: str,
-        input_variables: list[str],
         tools: List[Tool],
-        memory: Optional[BaseMemory] = None,
+        message_history: Optional[List[Record]] = None,
         handle_parsing_errors: bool = True,
         output_key: str = "output",
     ) -> Text:
@@ -55,13 +60,11 @@ class LCAgentComponent(CustomComponent):
                 agent=agent,  # type: ignore
                 tools=tools,
                 verbose=True,
-                memory=memory,
                 handle_parsing_errors=handle_parsing_errors,
             )
-        input_dict = {"input": inputs}
-        for var in input_variables:
-            if var not in ["agent_scratchpad", "input"]:
-                input_dict[var] = ""
+        input_dict: dict[str, str | list[BaseMessage]] = {"input": inputs}
+        if message_history:
+            input_dict["chat_history"] = records_to_messages(message_history)
         result = await runnable.ainvoke(input_dict)
         self.status = result
         if output_key in result:
diff --git a/src/backend/base/langflow/base/agents/default_prompts.py b/src/backend/base/langflow/base/agents/default_prompts.py
new file mode 100644
index 000000000..04e394813
--- /dev/null
+++ b/src/backend/base/langflow/base/agents/default_prompts.py
@@ -0,0 +1,23 @@
+XML_AGENT_PROMPT = """You are a helpful assistant. Help the user answer any questions.
+
+            You have access to the following tools:
+
+            {tools}
+
+            In order to use a tool, you can use <tool></tool> and <tool_input></tool_input> tags. You will then get back a response in the form <observation></observation>
+            For example, if you have a tool called 'search' that could run a google search, in order to search for the weather in SF you would respond:
+
+            <tool>search</tool><tool_input>weather in SF</tool_input>
+            <observation>64 degrees</observation>
+
+            When you are done, respond with a final answer between <final_answer></final_answer>. For example:
+
+            <final_answer>The weather in SF is 64 degrees</final_answer>
+
+            Begin!
+
+            Previous Conversation:
+            {chat_history}
+
+            Question: {input}
+            {agent_scratchpad}"""
diff --git a/src/backend/base/langflow/base/agents/utils.py b/src/backend/base/langflow/base/agents/utils.py
new file mode 100644
index 000000000..cb34d1cea
--- /dev/null
+++ b/src/backend/base/langflow/base/agents/utils.py
@@ -0,0 +1,143 @@
+from typing import Any, Callable, Dict, List, Optional, Sequence, Union
+
+from langchain.agents import (
+    create_json_chat_agent,
+    create_openai_tools_agent,
+    create_tool_calling_agent,
+    create_xml_agent,
+)
+from langchain.agents.xml.base import render_text_description
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import BaseMessage
+from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate
+from langchain_core.tools import BaseTool
+from pydantic import BaseModel
+
+from langflow.schema.schema import Record
+
+from .default_prompts import XML_AGENT_PROMPT
+
+
+class AgentSpec(BaseModel):
+    func: Callable[
+        [
+            BaseLanguageModel,
+            Sequence[BaseTool],
+            BasePromptTemplate | ChatPromptTemplate,
+            Optional[Callable[[List[BaseTool]], str]],
+            Optional[Union[bool, List[str]]],
+        ],
+        Any,
+    ]
+    prompt: Optional[Any] = None
+    fields: List[str]
+    hub_repo: Optional[str] = None
+
+
+def records_to_messages(records: List[Record]) -> List[BaseMessage]:
+    """
+    Convert a list of records to a list of messages.
+
+    Args:
+        records (List[Record]): The records to convert.
+
+    Returns:
+        List[Message]: The records as messages.
+    """
+    return [record.to_lc_message() for record in records]
+
+
+def validate_and_create_xml_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: BasePromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_xml_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+        tools_renderer=tools_renderer,
+        stop_sequence=stop_sequence,
+    )
+
+
+def validate_and_create_openai_tools_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: ChatPromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_openai_tools_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+    )
+
+
+def validate_and_create_tool_calling_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: ChatPromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_tool_calling_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+    )
+
+
+def validate_and_create_json_chat_agent(
+    llm: BaseLanguageModel,
+    tools: Sequence[BaseTool],
+    prompt: ChatPromptTemplate,
+    tools_renderer: Callable[[List[BaseTool]], str] = render_text_description,
+    *,
+    stop_sequence: Union[bool, List[str]] = True,
+):
+    return create_json_chat_agent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+        tools_renderer=tools_renderer,
+        stop_sequence=stop_sequence,
+    )
+
+
+AGENTS: Dict[str, AgentSpec] = {
+    "Tool Calling Agent": AgentSpec(
+        func=validate_and_create_tool_calling_agent,
+        prompt=None,
+        fields=["llm", "tools", "prompt"],
+        hub_repo=None,
+    ),
+    "XML Agent": AgentSpec(
+        func=validate_and_create_xml_agent,
+        prompt=XML_AGENT_PROMPT,  # Ensure XML_AGENT_PROMPT is properly defined and typed.
+        fields=["llm", "tools", "prompt", "tools_renderer", "stop_sequence"],
+        hub_repo="hwchase17/xml-agent-convo",
+    ),
+    "OpenAI Tools Agent": AgentSpec(
+        func=validate_and_create_openai_tools_agent,
+        prompt=None,
+        fields=["llm", "tools", "prompt"],
+        hub_repo=None,
+    ),
+    "JSON Chat Agent": AgentSpec(
+        func=validate_and_create_json_chat_agent,
+        prompt=None,
+        fields=["llm", "tools", "prompt", "tools_renderer", "stop_sequence"],
+        hub_repo="hwchase17/react-chat-json",
+    ),
+}
+
+
+def get_agents_list():
+    return list(AGENTS.keys())
diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py
new file mode 100644
index 000000000..b4a319e2f
--- /dev/null
+++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py
@@ -0,0 +1,64 @@
+from typing import List, Optional
+
+from langchain.agents.tool_calling_agent.base import create_tool_calling_agent
+from langchain_core.prompts import ChatPromptTemplate
+
+from langflow.base.agents.agent import LCAgentComponent
+from langflow.field_typing import BaseLanguageModel, Text, Tool
+from langflow.schema.schema import Record
+
+
+class ToolCallingAgentComponent(LCAgentComponent):
+    display_name: str = "Tool Calling Agent"
+    description: str = "Agent that uses tools. Only models that are compatible with function calling are supported."
+
+    def build_config(self):
+        return {
+            "llm": {"display_name": "LLM"},
+            "tools": {"display_name": "Tools"},
+            "user_prompt": {
+                "display_name": "Prompt",
+                "multiline": True,
+                "info": "This prompt must contain 'input' key.",
+            },
+            "handle_parsing_errors": {
+                "display_name": "Handle Parsing Errors",
+                "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.",
+                "advanced": True,
+            },
+            "memory": {
+                "display_name": "Memory",
+                "info": "Memory to use for the agent.",
+            },
+            "input_value": {
+                "display_name": "Inputs",
+                "info": "Input text to pass to the agent.",
+            },
+        }
+
+    async def build(
+        self,
+        input_value: str,
+        llm: BaseLanguageModel,
+        tools: List[Tool],
+        user_prompt: str = "{input}",
+        message_history: Optional[List[Record]] = None,
+        system_message: str = "You are a helpful assistant",
+        handle_parsing_errors: bool = True,
+    ) -> Text:
+        if "input" not in user_prompt:
+            raise ValueError("Prompt must contain 'input' key.")
+        messages = [
+            ("system", system_message),
+            (
+                "placeholder",
+                "{chat_history}",
+            ),
+            ("human", user_prompt),
+            ("placeholder", "{agent_scratchpad}"),
+        ]
+        prompt = ChatPromptTemplate.from_messages(messages)
+        agent = create_tool_calling_agent(llm, tools, prompt)
+        result = await self.run_agent(agent, input_value, tools, message_history, handle_parsing_errors)
+        self.status = result
+        return result
diff --git a/src/backend/base/langflow/components/agents/XMLAgent.py b/src/backend/base/langflow/components/agents/XMLAgent.py
index 117399af9..76f96da53 100644
--- a/src/backend/base/langflow/components/agents/XMLAgent.py
+++ b/src/backend/base/langflow/components/agents/XMLAgent.py
@@ -1,10 +1,12 @@
 from typing import List, Optional
 
 from langchain.agents import create_xml_agent
-from langchain_core.prompts import PromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
+
 
 from langflow.base.agents.agent import LCAgentComponent
-from langflow.field_typing import BaseLanguageModel, BaseMemory, Text, Tool
+from langflow.field_typing import BaseLanguageModel, Text, Tool
+from langflow.schema.schema import Record
 
 
 class XMLAgentComponent(LCAgentComponent):
@@ -15,7 +17,7 @@ class XMLAgentComponent(LCAgentComponent):
         return {
             "llm": {"display_name": "LLM"},
             "tools": {"display_name": "Tools"},
-            "prompt": {
+            "user_prompt": {
                 "display_name": "Prompt",
                 "multiline": True,
                 "info": "This prompt must contain 'tools' and 'agent_scratchpad' keys.",
@@ -43,6 +45,11 @@ class XMLAgentComponent(LCAgentComponent):
             Question: {input}
             {agent_scratchpad}""",
             },
+            "system_message": {
+                "display_name": "System Message",
+                "info": "System message to be passed to the LLM.",
+                "advanced": True,
+            },
             "tool_template": {
                 "display_name": "Tool Template",
                 "info": "Template for rendering tools in the prompt. Tools have 'name' and 'description' keys.",
@@ -53,9 +60,9 @@ class XMLAgentComponent(LCAgentComponent):
                 "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.",
                 "advanced": True,
             },
-            "memory": {
-                "display_name": "Memory",
-                "info": "Memory to use for the agent.",
+            "message_history": {
+                "display_name": "Message History",
+                "info": "Message history to pass to the agent.",
             },
             "input_value": {
                 "display_name": "Inputs",
@@ -68,12 +75,13 @@ class XMLAgentComponent(LCAgentComponent):
         input_value: str,
         llm: BaseLanguageModel,
         tools: List[Tool],
-        prompt: str,
-        memory: Optional[BaseMemory] = None,
+        user_prompt: str = "{input}",
+        system_message: str = "You are a helpful assistant",
+        message_history: Optional[List[Record]] = None,
         tool_template: str = "{name}: {description}",
         handle_parsing_errors: bool = True,
     ) -> Text:
-        if "input" not in prompt:
+        if "input" not in user_prompt:
             raise ValueError("Prompt must contain 'input' key.")
 
         def render_tool_description(tools):
@@ -81,9 +89,23 @@ class XMLAgentComponent(LCAgentComponent):
                 [tool_template.format(name=tool.name, description=tool.description, args=tool.args) for tool in tools]
             )
 
-        prompt_template = PromptTemplate.from_template(prompt)
-        input_variables = prompt_template.input_variables
-        agent = create_xml_agent(llm, tools, prompt_template, tools_renderer=render_tool_description)
-        result = await self.run_agent(agent, input_value, input_variables, tools, memory, handle_parsing_errors)
+        messages = [
+            ("system", system_message),
+            (
+                "placeholder",
+                "{chat_history}",
+            ),
+            ("human", user_prompt),
+            ("placeholder", "{agent_scratchpad}"),
+        ]
+        prompt = ChatPromptTemplate.from_messages(messages)
+        agent = create_xml_agent(llm, tools, prompt, tools_renderer=render_tool_description)
+        result = await self.run_agent(
+            agent=agent,
+            inputs=input_value,
+            tools=tools,
+            message_history=message_history,
+            handle_parsing_errors=handle_parsing_errors,
+        )
         self.status = result
         return result
diff --git a/src/backend/base/langflow/components/experimental/AgentComponent.py b/src/backend/base/langflow/components/experimental/AgentComponent.py
new file mode 100644
index 000000000..9a6840a41
--- /dev/null
+++ b/src/backend/base/langflow/components/experimental/AgentComponent.py
@@ -0,0 +1,185 @@
+from typing import Any, List, Optional, cast
+
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.prompts.chat import HumanMessagePromptTemplate, SystemMessagePromptTemplate
+
+from langflow.base.agents.agent import LCAgentComponent
+from langflow.base.agents.utils import AGENTS, AgentSpec, get_agents_list
+from langflow.field_typing import BaseLanguageModel, Text, Tool
+from langflow.schema.dotdict import dotdict
+from langflow.schema.schema import Record
+
+
+class AgentComponent(LCAgentComponent):
+    display_name = "Agent"
+    description = "Run any LangChain agent using a simplified interface."
+    field_order = [
+        "agent_name",
+        "llm",
+        "tools",
+        "prompt",
+        "tool_template",
+        "handle_parsing_errors",
+        "memory",
+        "input_value",
+    ]
+
+    def build_config(self):
+        return {
+            "agent_name": {
+                "display_name": "Agent",
+                "info": "The agent to use.",
+                "refresh_button": True,
+                "real_time_refresh": True,
+                "options": get_agents_list(),
+            },
+            "llm": {"display_name": "LLM"},
+            "tools": {"display_name": "Tools"},
+            "user_prompt": {
+                "display_name": "Prompt",
+                "multiline": True,
+                "info": "This prompt must contain 'tools' and 'agent_scratchpad' keys.",
+            },
+            "system_message": {
+                "display_name": "System Message",
+                "info": "System message to be passed to the LLM.",
+                "advanced": True,
+            },
+            "tool_template": {
+                "display_name": "Tool Template",
+                "info": "Template for rendering tools in the prompt. Tools have 'name' and 'description' keys.",
+                "advanced": True,
+            },
+            "handle_parsing_errors": {
+                "display_name": "Handle Parsing Errors",
+                "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.",
+                "advanced": True,
+            },
+            "message_history": {
+                "display_name": "Message History",
+                "info": "Message history to pass to the agent.",
+            },
+            "input_value": {
+                "display_name": "Input",
+                "info": "Input text to pass to the agent.",
+            },
+            "langchain_hub_api_key": {
+                "display_name": "LangChain Hub API Key",
+                "info": "API key to use for LangChain Hub. If provided, prompts will be fetched from LangChain Hub.",
+                "advanced": True,
+            },
+        }
+
+    def get_system_and_user_message_from_prompt(self, prompt: Any):
+        """
+        Extracts the system message and user prompt from a given prompt object.
+
+        Args:
+            prompt (Any): The prompt object from which to extract the system message and user prompt.
+
+        Returns:
+            Tuple[Optional[str], Optional[str]]: A tuple containing the system message and user prompt.
+                If the prompt object does not have any messages, both values will be None.
+        """
+        if hasattr(prompt, "messages"):
+            system_message = None
+            user_prompt = None
+            for message in prompt.messages:
+                if isinstance(message, SystemMessagePromptTemplate):
+                    s_prompt = message.prompt
+                    if isinstance(s_prompt, list):
+                        s_template = " ".join([cast(str, s.template) for s in s_prompt if hasattr(s, "template")])
+                    elif hasattr(s_prompt, "template"):
+                        s_template = s_prompt.template
+                    system_message = s_template
+                elif isinstance(message, HumanMessagePromptTemplate):
+                    h_prompt = message.prompt
+                    if isinstance(h_prompt, list):
+                        h_template = " ".join([cast(str, h.template) for h in h_prompt if hasattr(h, "template")])
+                    elif hasattr(h_prompt, "template"):
+                        h_template = h_prompt.template
+                    user_prompt = h_template
+            return system_message, user_prompt
+        return None, None
+
+    def update_build_config(self, build_config: dotdict, field_value: Any, field_name: Text | None = None):
+        """
+        Updates the build configuration based on the provided field value and field name.
+
+        Args:
+            build_config (dotdict): The build configuration to be updated.
+            field_value (Any): The value of the field being updated.
+            field_name (Text | None, optional): The name of the field being updated. Defaults to None.
+
+        Returns:
+            dotdict: The updated build configuration.
+        """
+        if field_name == "agent":
+            build_config["agent"]["options"] = get_agents_list()
+            if field_value in AGENTS:
+                # if langchain_hub_api_key is provided, fetch the prompt from LangChain Hub
+                if build_config["langchain_hub_api_key"]["value"] and AGENTS[field_value].hub_repo:
+                    from langchain import hub
+
+                    hub_repo: str | None = AGENTS[field_value].hub_repo
+                    if hub_repo:
+                        hub_api_key: str = build_config["langchain_hub_api_key"]["value"]
+                        prompt = hub.pull(hub_repo, api_key=hub_api_key)
+                        system_message, user_prompt = self.get_system_and_user_message_from_prompt(prompt)
+                        if system_message:
+                            build_config["system_message"]["value"] = system_message
+                        if user_prompt:
+                            build_config["user_prompt"]["value"] = user_prompt
+
+                if AGENTS[field_value].prompt:
+                    build_config["user_prompt"]["value"] = AGENTS[field_value].prompt
+                else:
+                    build_config["user_prompt"]["value"] = "{input}"
+            fields = AGENTS[field_value].fields
+            for field in ["llm", "tools", "prompt", "tools_renderer"]:
+                if field not in fields:
+                    build_config[field]["show"] = False
+        return build_config
+
+    async def build(
+        self,
+        agent_name: str,
+        input_value: str,
+        llm: BaseLanguageModel,
+        tools: List[Tool],
+        system_message: str = "You are a helpful assistant. Help the user answer any questions.",
+        user_prompt: str = "{input}",
+        message_history: Optional[List[Record]] = None,
+        tool_template: str = "{name}: {description}",
+        handle_parsing_errors: bool = True,
+    ) -> Text:
+        agent_spec: Optional[AgentSpec] = AGENTS.get(agent_name)
+        if agent_spec is None:
+            raise ValueError(f"{agent_name} not found.")
+
+        def render_tool_description(tools):
+            return "\n".join(
+                [tool_template.format(name=tool.name, description=tool.description, args=tool.args) for tool in tools]
+            )
+
+        messages = [
+            ("system", system_message),
+            (
+                "placeholder",
+                "{chat_history}",
+            ),
+            ("human", user_prompt),
+            ("placeholder", "{agent_scratchpad}"),
+        ]
+        prompt = ChatPromptTemplate.from_messages(messages)
+        agent_func = agent_spec.func
+        agent = agent_func(llm, tools, prompt, render_tool_description, True)
+        result = await self.run_agent(
+            agent=agent,
+            inputs=input_value,
+            tools=tools,
+            message_history=message_history,
+            handle_parsing_errors=handle_parsing_errors,
+        )
+        self.status = result
+        return result
diff --git a/src/backend/base/langflow/components/experimental/__init__.py b/src/backend/base/langflow/components/experimental/__init__.py
index 54ca60a3b..a8e83125c 100644
--- a/src/backend/base/langflow/components/experimental/__init__.py
+++ b/src/backend/base/langflow/components/experimental/__init__.py
@@ -10,8 +10,10 @@ from .RunFlow import RunFlowComponent
 from .RunnableExecutor import RunnableExecComponent
 from .SQLExecutor import SQLExecutorComponent
 from .SubFlow import SubFlowComponent
+from .AgentComponent import AgentComponent
 
 __all__ = [
+    "AgentComponent",
     "ClearMessageHistoryComponent",
     "ExtractKeyFromRecordComponent",
     "FlowToolComponent",
diff --git a/src/backend/base/langflow/components/models/AzureOpenAIModel.py b/src/backend/base/langflow/components/models/AzureOpenAIModel.py
index 1440df4d0..b6d3607f3 100644
--- a/src/backend/base/langflow/components/models/AzureOpenAIModel.py
+++ b/src/backend/base/langflow/components/models/AzureOpenAIModel.py
@@ -105,7 +105,7 @@ class AzureChatOpenAIComponent(LCModelComponent):
         system_message: Optional[str] = None,
         max_tokens: Optional[int] = 1000,
         stream: bool = False,
-    ) -> BaseLanguageModel:
+    ) -> Text:
         if api_key:
             secret_api_key = SecretStr(api_key)
         else:
diff --git a/src/backend/base/langflow/components/models/ChatLiteLLMModel.py b/src/backend/base/langflow/components/models/ChatLiteLLMModel.py
index 5266c6935..23ac483cb 100644
--- a/src/backend/base/langflow/components/models/ChatLiteLLMModel.py
+++ b/src/backend/base/langflow/components/models/ChatLiteLLMModel.py
@@ -142,7 +142,7 @@ class ChatLiteLLMModelComponent(LCModelComponent):
         max_retries: int = 6,
         verbose: bool = False,
         system_message: Optional[str] = None,
-    ) -> BaseLanguageModel:
+    ) -> Text:
         try:
             import litellm  # type: ignore
 
diff --git a/src/backend/base/langflow/schema/schema.py b/src/backend/base/langflow/schema/schema.py
index dffa04dae..979c78920 100644
--- a/src/backend/base/langflow/schema/schema.py
+++ b/src/backend/base/langflow/schema/schema.py
@@ -4,6 +4,7 @@ from typing import Literal, Optional
 from langchain_core.documents import Document
 from langchain_core.messages import BaseMessage
 from pydantic import BaseModel, model_validator
+from langchain_core.messages import HumanMessage, AIMessage, BaseMessage
 
 
 class Record(BaseModel):
@@ -101,6 +102,26 @@ class Record(BaseModel):
         text = self.data.pop(self.text_key, self.default_value)
         return Document(page_content=text, metadata=self.data)
 
+    def to_lc_message(self) -> BaseMessage:
+        """
+        Converts the Record to a BaseMessage.
+
+        Returns:
+            BaseMessage: The converted BaseMessage.
+        """
+        # The idea of this function is to be a helper to convert a Record to a BaseMessage
+        # It will use the "sender" key to determine if the message is Human or AI
+        # If the key is not present, it will default to AI
+        # But first we check if all required keys are present in the data dictionary
+        # they are: "text", "sender"
+        if not all(key in self.data for key in ["text", "sender"]):
+            raise ValueError(f"Missing required keys ('text', 'sender') in Record: {self.data}")
+        sender = self.data.get("sender", "Machine")
+        text = self.data.get("text", "")
+        if sender == "User":
+            return HumanMessage(content=text)
+        return AIMessage(content=text)
+
     def __getattr__(self, key):
         """
         Allows attribute-like access to the data dictionary.
diff --git a/src/backend/base/poetry.lock b/src/backend/base/poetry.lock
index 0401ba407..9174a0f4c 100644
--- a/src/backend/base/poetry.lock
+++ b/src/backend/base/poetry.lock
@@ -1144,6 +1144,21 @@ langchain-core = ">=0.1.28,<0.2.0"
 [package.extras]
 extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
 
+[[package]]
+name = "langchainhub"
+version = "0.1.15"
+description = "The LangChain Hub API client"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
+    {file = "langchainhub-0.1.15-py3-none-any.whl", hash = "sha256:89a0951abd1db255e91c6d545d092a598fc255aa865d1ffc3ce8f93bbeae60e7"},
+    {file = "langchainhub-0.1.15.tar.gz", hash = "sha256:fa3ff81a31946860f84c119f1e2f6b7c7707e2bd7ed2394a7313b286d59f3bda"},
+]
+
+[package.dependencies]
+requests = ">=2,<3"
+types-requests = ">=2.31.0.2,<3.0.0.0"
+
 [[package]]
 name = "langsmith"
 version = "0.1.47"
@@ -2568,6 +2583,20 @@ rich = ">=10.11.0"
 shellingham = ">=1.3.0"
 typing-extensions = ">=3.7.4.3"
 
+[[package]]
+name = "types-requests"
+version = "2.31.0.20240406"
+description = "Typing stubs for requests"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "types-requests-2.31.0.20240406.tar.gz", hash = "sha256:4428df33c5503945c74b3f42e82b181e86ec7b724620419a2966e2de604ce1a1"},
+    {file = "types_requests-2.31.0.20240406-py3-none-any.whl", hash = "sha256:6216cdac377c6b9a040ac1c0404f7284bd13199c0e1bb235f4324627e8898cf5"},
+]
+
+[package.dependencies]
+urllib3 = ">=2"
+
 [[package]]
 name = "typing-extensions"
 version = "4.11.0"
@@ -2861,4 +2890,4 @@ local = []
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.12"
-content-hash = "11b7861d29ff2ca23defcb03faf670c409c639c7b4ee81455c0c1fea50ea54e9"
+content-hash = "4baea3d7c34ad33205fbb00a9da20b4c696b9487a2d62dada9babf1d21ed2dba"
diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml
index cc69ada3c..441400fd8 100644
--- a/src/backend/base/pyproject.toml
+++ b/src/backend/base/pyproject.toml
@@ -31,6 +31,7 @@ httpx = "*"
 uvicorn = "^0.29.0"
 gunicorn = "^21.2.0"
 langchain = "~0.1.16"
+langchainhub = "~0.1.15"
 sqlmodel = "^0.0.16"
 loguru = "^0.7.1"
 rich = "^13.7.0"

From 3549d38d871278100bb0dcfe662ac4e82d101503 Mon Sep 17 00:00:00 2001
From: Yuri Kovalov <yuri@yurikoval.com>
Date: Wed, 17 Apr 2024 00:58:22 +0800
Subject: [PATCH 3/4] Fix GCP deploy buttons in GCP docs (#1702)

Fix GCP deploy buttons in docs to call walkthrough from correct directory
---
 GCP_DEPLOYMENT.md                      | 4 ++--
 docs/docs/deployment/gcp-deployment.md | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/GCP_DEPLOYMENT.md b/GCP_DEPLOYMENT.md
index 12b6b0239..9f17e550b 100644
--- a/GCP_DEPLOYMENT.md
+++ b/GCP_DEPLOYMENT.md
@@ -6,7 +6,7 @@ This guide will help you set up a Langflow development VM in a Google Cloud Plat
 
 ## Standard VM
 
-[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md)
+[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md)
 
 This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment.
 
@@ -14,7 +14,7 @@ This script sets up a Debian-based VM with the Langflow package, Nginx, and the
 
 ## Spot/Preemptible Instance
 
-[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
+[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md)
 
 When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts.
 
diff --git a/docs/docs/deployment/gcp-deployment.md b/docs/docs/deployment/gcp-deployment.md
index bd2b48968..e126e785c 100644
--- a/docs/docs/deployment/gcp-deployment.md
+++ b/docs/docs/deployment/gcp-deployment.md
@@ -8,7 +8,7 @@ This guide will help you set up a Langflow development VM in a Google Cloud Plat
 
 ## Standard VM
 
-[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md)
+[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md)
 
 This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment.
 
@@ -16,7 +16,7 @@ This script sets up a Debian-based VM with the Langflow package, Nginx, and the
 
 ## Spot/Preemptible Instance
 
-[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md)
+[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md)
 
 When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts.
 

From 374508cf185480a1619724cd820dd35d047a5ec6 Mon Sep 17 00:00:00 2001
From: Gabriel Luiz Freitas Almeida <gabriel@logspace.ai>
Date: Tue, 16 Apr 2024 14:03:53 -0300
Subject: [PATCH 4/4] Update package versions in pyproject.toml and poetry.lock
 files

---
 poetry.lock                     | 279 ++++++++++++++++----------------
 pyproject.toml                  |   2 +-
 src/backend/base/poetry.lock    |  20 +--
 src/backend/base/pyproject.toml |   2 +-
 4 files changed, 147 insertions(+), 156 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 59e2f80b8..f3377fba2 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -167,13 +167,13 @@ files = [
 
 [[package]]
 name = "anthropic"
-version = "0.25.1"
+version = "0.25.2"
 description = "The official Python library for the anthropic API"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "anthropic-0.25.1-py3-none-any.whl", hash = "sha256:95d0cedc2a4b5beae3a78f9030aea4001caea5f46c6d263cce377c891c594e71"},
-    {file = "anthropic-0.25.1.tar.gz", hash = "sha256:0c01b30b77d041a8d07c532737bae69da58086031217150008e4541f52a64bd9"},
+    {file = "anthropic-0.25.2-py3-none-any.whl", hash = "sha256:f854030b11052f7cbb5257be6134c8a8f25aa538f73013260e12238ff94234a3"},
+    {file = "anthropic-0.25.2.tar.gz", hash = "sha256:cdf30ac234e3c0b305307399a6bb5dba45881adcb188d88fdf59802f90f15d6d"},
 ]
 
 [package.dependencies]
@@ -1149,13 +1149,13 @@ types = ["chardet (>=5.1.0)", "mypy", "pytest", "pytest-cov", "pytest-dependency
 
 [[package]]
 name = "cohere"
-version = "5.2.6"
+version = "5.3.0"
 description = ""
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "cohere-5.2.6-py3-none-any.whl", hash = "sha256:256b4ed00f47eb315401d7f28834655714f098382908e7d0ad5c98225aa6a57d"},
-    {file = "cohere-5.2.6.tar.gz", hash = "sha256:15d13682706fbafc8cf700e195f628389a643eb7ebd6d7c5e9d6e1ebd3f942fb"},
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+    {file = "cohere-5.3.0.tar.gz", hash = "sha256:9f28910bd7eb897a8cde3abd66bbdee6051846909a431d2398089157ccb40c3c"},
 ]
 
 [package.dependencies]
@@ -2516,13 +2516,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.125.0"
+version = "2.126.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -3735,19 +3735,19 @@ langchain-core = ">=0.1.32,<0.2.0"
 
 [[package]]
 name = "langchain-community"
-version = "0.0.32"
+version = "0.0.33"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_community-0.0.32-py3-none-any.whl", hash = "sha256:406977009999952d0705de3806de2b4867e9bb8eda8ca154a59c7a8ed58da38d"},
-    {file = "langchain_community-0.0.32.tar.gz", hash = "sha256:1510217d646c8380f54e9850351f6d2a0b0dd73c501b666c6f4b40baa8160b29"},
+    {file = "langchain_community-0.0.33-py3-none-any.whl", hash = "sha256:830f0d5f4ff9638b99ca01820c26abfa4b65fa705ef89b5ce55ac9aa3a7d83af"},
+    {file = "langchain_community-0.0.33.tar.gz", hash = "sha256:bb56dbc1ef11ca09f258468e11368781adda9219e144073e30cda69496d342b2"},
 ]
 
 [package.dependencies]
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 dataclasses-json = ">=0.5.7,<0.7"
-langchain-core = ">=0.1.41,<0.2.0"
+langchain-core = ">=0.1.43,<0.2.0"
 langsmith = ">=0.1.0,<0.2.0"
 numpy = ">=1,<2"
 PyYAML = ">=5.3"
@@ -3761,13 +3761,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
 
 [[package]]
 name = "langchain-core"
-version = "0.1.42"
+version = "0.1.43"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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+    {file = "langchain_core-0.1.43.tar.gz", hash = "sha256:499133fadc28efcf7d24306236521518080bb10fd8bf6f7426de4a2bbf2aebb5"},
 ]
 
 [package.dependencies]
@@ -3881,7 +3881,7 @@ six = "*"
 
 [[package]]
 name = "langflow-base"
-version = "0.0.34"
+version = "0.0.35"
 description = "A Python package with a built-in web application"
 optional = false
 python-versions = ">=3.10,<3.12"
@@ -3959,13 +3959,13 @@ openai = ["openai (>=0.27.8)"]
 
 [[package]]
 name = "langsmith"
-version = "0.1.47"
+version = "0.1.48"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -3992,13 +3992,13 @@ regex = ["regex"]
 
 [[package]]
 name = "litellm"
-version = "1.35.5"
+version = "1.35.8"
 description = "Library to easily interface with LLM API providers"
 optional = false
 python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4270,13 +4270,13 @@ llama-index-program-openai = ">=0.1.1,<0.2.0"
 
 [[package]]
 name = "llama-index-readers-file"
-version = "0.1.18"
+version = "0.1.19"
 description = "llama-index readers file integration"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -5509,13 +5509,13 @@ sympy = "*"
 
 [[package]]
 name = "openai"
-version = "1.17.1"
+version = "1.19.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -6610,13 +6610,13 @@ pyasn1 = ">=0.4.6,<0.7.0"
 
 [[package]]
 name = "pyautogen"
-version = "0.2.23"
+version = "0.2.24"
 description = "Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework"
 optional = false
 python-versions = "<3.13,>=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -6633,6 +6633,7 @@ tiktoken = "*"
 [package.extras]
 autobuild = ["chromadb", "huggingface-hub", "sentence-transformers"]
 blendsearch = ["flaml[blendsearch]"]
+cosmosdb = ["azure-cosmos (>=4.2.0)"]
 graph = ["matplotlib", "networkx"]
 jupyter-executor = ["ipykernel (>=6.29.0)", "jupyter-client (>=8.6.0)", "jupyter-kernel-gateway", "requests", "websocket-client"]
 lmm = ["pillow", "replicate"]
@@ -8006,121 +8007,111 @@ crt = ["botocore[crt] (>=1.33.2,<2.0a.0)"]
 
 [[package]]
 name = "safetensors"
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 python-versions = ">=3.7"
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 ]
 
 [package.extras]
@@ -8133,7 +8124,7 @@ paddlepaddle = ["paddlepaddle (>=2.4.1)", "safetensors[numpy]"]
 pinned-tf = ["safetensors[numpy]", "tensorflow (==2.11.0)"]
 quality = ["black (==22.3)", "click (==8.0.4)", "flake8 (>=3.8.3)", "isort (>=5.5.4)"]
 tensorflow = ["safetensors[numpy]", "tensorflow (>=2.11.0)"]
-testing = ["h5py (>=3.7.0)", "huggingface_hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools_rust (>=1.5.2)"]
+testing = ["h5py (>=3.7.0)", "huggingface-hub (>=0.12.1)", "hypothesis (>=6.70.2)", "pytest (>=7.2.0)", "pytest-benchmark (>=4.0.0)", "safetensors[numpy]", "setuptools-rust (>=1.5.2)"]
 torch = ["safetensors[numpy]", "torch (>=1.10)"]
 
 [[package]]
diff --git a/pyproject.toml b/pyproject.toml
index 1203a84cc..04e9f22a4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "1.0.0a22"
+version = "1.0.0a23"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [
diff --git a/src/backend/base/poetry.lock b/src/backend/base/poetry.lock
index 9174a0f4c..ba32a6ecb 100644
--- a/src/backend/base/poetry.lock
+++ b/src/backend/base/poetry.lock
@@ -1063,19 +1063,19 @@ text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
 
 [[package]]
 name = "langchain-community"
-version = "0.0.32"
+version = "0.0.33"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_community-0.0.32-py3-none-any.whl", hash = "sha256:406977009999952d0705de3806de2b4867e9bb8eda8ca154a59c7a8ed58da38d"},
-    {file = "langchain_community-0.0.32.tar.gz", hash = "sha256:1510217d646c8380f54e9850351f6d2a0b0dd73c501b666c6f4b40baa8160b29"},
+    {file = "langchain_community-0.0.33-py3-none-any.whl", hash = "sha256:830f0d5f4ff9638b99ca01820c26abfa4b65fa705ef89b5ce55ac9aa3a7d83af"},
+    {file = "langchain_community-0.0.33.tar.gz", hash = "sha256:bb56dbc1ef11ca09f258468e11368781adda9219e144073e30cda69496d342b2"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.7"
-langchain-core = ">=0.1.41,<0.2.0"
+langchain-core = ">=0.1.43,<0.2.0"
 langsmith = ">=0.1.0,<0.2.0"
 numpy = ">=1,<2"
 PyYAML = ">=5.3"
@@ -1089,13 +1089,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
 
 [[package]]
 name = "langchain-core"
-version = "0.1.42"
+version = "0.1.43"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.1.42-py3-none-any.whl", hash = "sha256:c5653ffa08a44f740295c157a24c0def4a753333f6a2c41f76bf431cd00be8b5"},
-    {file = "langchain_core-0.1.42.tar.gz", hash = "sha256:40751bf60ea5d8e2b2efe65290db434717ee3834870c002e40e2811f09d814e6"},
+    {file = "langchain_core-0.1.43-py3-none-any.whl", hash = "sha256:9b601916602c17cb7588e8089302e30872cbd049b583a27debf5566018af6405"},
+    {file = "langchain_core-0.1.43.tar.gz", hash = "sha256:499133fadc28efcf7d24306236521518080bb10fd8bf6f7426de4a2bbf2aebb5"},
 ]
 
 [package.dependencies]
@@ -1161,13 +1161,13 @@ types-requests = ">=2.31.0.2,<3.0.0.0"
 
 [[package]]
 name = "langsmith"
-version = "0.1.47"
+version = "0.1.48"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.47-py3-none-any.whl", hash = "sha256:17b0a908b8d39b6da3ecff658c8c00304b0b62f59945a5e16c2da5a254ea21a6"},
-    {file = "langsmith-0.1.47.tar.gz", hash = "sha256:f5ddd17628baa03a775525c5547a543a559313e425cdb2bf23579ffcf6056a76"},
+    {file = "langsmith-0.1.48-py3-none-any.whl", hash = "sha256:2f8967e2aaaed8881efe6f346590681243b315af8ba8a037d969c299d42071d3"},
+    {file = "langsmith-0.1.48.tar.gz", hash = "sha256:9cd21cd0928123b2bd2363f03515cb1f6a833d9a9f00420240d5132861d15fcc"},
 ]
 
 [package.dependencies]
diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml
index 441400fd8..c74d50b55 100644
--- a/src/backend/base/pyproject.toml
+++ b/src/backend/base/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow-base"
-version = "0.0.34"
+version = "0.0.35"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [