diff --git a/dev.Dockerfile b/dev.Dockerfile
index 0f559a0cf..7e439c69a 100644
--- a/dev.Dockerfile
+++ b/dev.Dockerfile
@@ -15,4 +15,4 @@ COPY ./ ./
 # Install dependencies
 RUN poetry config virtualenvs.create false && poetry install --no-interaction --no-ansi
 
-CMD ["uvicorn", "langflow.main:app", "--host", "0.0.0.0", "--port", "5003", "--reload"]
\ No newline at end of file
+CMD ["uvicorn", "langflow.main:app", "--host", "0.0.0.0", "--port", "5003", "--reload", "log-level", "debug"]
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
index 73235eb67..4aa7d59ca 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -239,37 +239,37 @@ lxml = ["lxml"]
 
 [[package]]
 name = "black"
-version = "23.1.0"
+version = "23.3.0"
 description = "The uncompromising code formatter."
 category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "black-23.1.0-cp310-cp310-macosx_10_16_universal2.whl", hash = "sha256:57c18c5165c1dbe291d5306e53fb3988122890e57bd9b3dcb75f967f13411a26"},
-    {file = "black-23.1.0-cp310-cp310-macosx_10_16_x86_64.whl", hash = "sha256:9880d7d419bb7e709b37e28deb5e68a49227713b623c72b2b931028ea65f619b"},
-    {file = "black-23.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e6663f91b6feca5d06f2ccd49a10f254f9298cc1f7f49c46e498a0771b507104"},
-    {file = "black-23.1.0-cp310-cp310-win_amd64.whl", hash = "sha256:9afd3f493666a0cd8f8df9a0200c6359ac53940cbde049dcb1a7eb6ee2dd7074"},
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+    {file = "black-23.3.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:50cb33cac881766a5cd9913e10ff75b1e8eb71babf4c7104f2e9c52da1fb7de2"},
+    {file = "black-23.3.0-cp37-cp37m-win_amd64.whl", hash = "sha256:e114420bf26b90d4b9daa597351337762b63039752bdf72bf361364c1aa05925"},
+    {file = "black-23.3.0-cp38-cp38-macosx_10_16_arm64.whl", hash = "sha256:48f9d345675bb7fbc3dd85821b12487e1b9a75242028adad0333ce36ed2a6d27"},
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+    {file = "black-23.3.0-cp38-cp38-macosx_10_16_x86_64.whl", hash = "sha256:064101748afa12ad2291c2b91c960be28b817c0c7eaa35bec09cc63aa56493c5"},
+    {file = "black-23.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:562bd3a70495facf56814293149e51aa1be9931567474993c7942ff7d3533961"},
+    {file = "black-23.3.0-cp38-cp38-win_amd64.whl", hash = "sha256:e198cf27888ad6f4ff331ca1c48ffc038848ea9f031a3b40ba36aced7e22f2c8"},
+    {file = "black-23.3.0-cp39-cp39-macosx_10_16_arm64.whl", hash = "sha256:3238f2aacf827d18d26db07524e44741233ae09a584273aa059066d644ca7b30"},
+    {file = "black-23.3.0-cp39-cp39-macosx_10_16_universal2.whl", hash = "sha256:f0bd2f4a58d6666500542b26354978218a9babcdc972722f4bf90779524515f3"},
+    {file = "black-23.3.0-cp39-cp39-macosx_10_16_x86_64.whl", hash = "sha256:92c543f6854c28a3c7f39f4d9b7694f9a6eb9d3c5e2ece488c327b6e7ea9b266"},
+    {file = "black-23.3.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3a150542a204124ed00683f0db1f5cf1c2aaaa9cc3495b7a3b5976fb136090ab"},
+    {file = "black-23.3.0-cp39-cp39-win_amd64.whl", hash = "sha256:6b39abdfb402002b8a7d030ccc85cf5afff64ee90fa4c5aebc531e3ad0175ddb"},
+    {file = "black-23.3.0-py3-none-any.whl", hash = "sha256:ec751418022185b0c1bb7d7736e6933d40bbb14c14a0abcf9123d1b159f98dd4"},
+    {file = "black-23.3.0.tar.gz", hash = "sha256:1c7b8d606e728a41ea1ccbd7264677e494e87cf630e399262ced92d4a8dac940"},
 ]
 
 [package.dependencies]
@@ -579,6 +579,21 @@ files = [
     {file = "decorator-5.1.1.tar.gz", hash = "sha256:637996211036b6385ef91435e4fae22989472f9d571faba8927ba8253acbc330"},
 ]
 
+[[package]]
+name = "dill"
+version = "0.3.6"
+description = "serialize all of python"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "dill-0.3.6-py3-none-any.whl", hash = "sha256:a07ffd2351b8c678dfc4a856a3005f8067aea51d6ba6c700796a4d9e280f39f0"},
+    {file = "dill-0.3.6.tar.gz", hash = "sha256:e5db55f3687856d8fbdab002ed78544e1c4559a130302693d839dfe8f93f2373"},
+]
+
+[package.extras]
+graph = ["objgraph (>=1.7.2)"]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.1.1"
@@ -759,14 +774,14 @@ uritemplate = ">=3.0.1,<5"
 
 [[package]]
 name = "google-auth"
-version = "2.17.0"
+version = "2.17.1"
 description = "Google Authentication Library"
 category = "main"
 optional = false
 python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
 files = [
-    {file = "google-auth-2.17.0.tar.gz", hash = "sha256:f51d26ebb3e5d723b9a7dbd310b6c88654ef1ad1fc35750d1fdba48ca4d82f52"},
-    {file = "google_auth-2.17.0-py2.py3-none-any.whl", hash = "sha256:45ba9b4b3e49406de3c5451697820694b2f6ce8a6b75bb187852fdae231dab94"},
+    {file = "google-auth-2.17.1.tar.gz", hash = "sha256:8f379b46bad381ad2a0b989dfb0c13ad28d3c2a79f27348213f8946a1d15d55a"},
+    {file = "google_auth-2.17.1-py2.py3-none-any.whl", hash = "sha256:357ff22a75b4c0f6093470f21816a825d2adee398177569824e37b6c10069e19"},
 ]
 
 [package.dependencies]
@@ -1079,14 +1094,14 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio"
 
 [[package]]
 name = "ipython"
-version = "8.11.0"
+version = "8.12.0"
 description = "IPython: Productive Interactive Computing"
 category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "ipython-8.11.0-py3-none-any.whl", hash = "sha256:5b54478e459155a326bf5f42ee4f29df76258c0279c36f21d71ddb560f88b156"},
-    {file = "ipython-8.11.0.tar.gz", hash = "sha256:735cede4099dbc903ee540307b9171fbfef4aa75cfcacc5a273b2cda2f02be04"},
+    {file = "ipython-8.12.0-py3-none-any.whl", hash = "sha256:1c183bf61b148b00bcebfa5d9b39312733ae97f6dad90d7e9b4d86c8647f498c"},
+    {file = "ipython-8.12.0.tar.gz", hash = "sha256:a950236df04ad75b5bc7f816f9af3d74dc118fd42f2ff7e80e8e60ca1f182e2d"},
 ]
 
 [package.dependencies]
@@ -1102,6 +1117,7 @@ prompt-toolkit = ">=3.0.30,<3.0.37 || >3.0.37,<3.1.0"
 pygments = ">=2.4.0"
 stack-data = "*"
 traitlets = ">=5"
+typing-extensions = {version = "*", markers = "python_version < \"3.10\""}
 
 [package.extras]
 all = ["black", "curio", "docrepr", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.21)", "pandas", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
@@ -1183,14 +1199,14 @@ test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "langchain"
-version = "0.0.113"
+version = "0.0.127"
 description = "Building applications with LLMs through composability"
 category = "main"
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "langchain-0.0.113-py3-none-any.whl", hash = "sha256:9e146d116fd3b9b2210c8c447cabfa20ef27c26ea3f2bc986eab97d1dad0aab6"},
-    {file = "langchain-0.0.113.tar.gz", hash = "sha256:a494fe02bc63da4bcda7da8d7f4a346522fbc87f0a4955b72519ec2ed86bf906"},
+    {file = "langchain-0.0.127-py3-none-any.whl", hash = "sha256:04ba053881e6098e80e0f4afc8922f3fe78923b160fd12d856aebce49c261918"},
+    {file = "langchain-0.0.127.tar.gz", hash = "sha256:e8a3b67fd86a6f79c4334f0a7588c9476fcb57b27a8fb0e617f47c01eaab8be8"},
 ]
 
 [package.dependencies]
@@ -1198,14 +1214,14 @@ aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.6.0"
 numpy = ">=1,<2"
 pydantic = ">=1,<2"
-PyYAML = ">=6,<7"
+PyYAML = ">=5.4.1"
 requests = ">=2,<3"
 SQLAlchemy = ">=1,<2"
 tenacity = ">=8.1.0,<9.0.0"
 
 [package.extras]
-all = ["aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.2.2,<0.3.0)", "beautifulsoup4 (>=4,<5)", "cohere (>=3,<4)", "deeplake (>=3.2.9,<4.0.0)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "huggingface_hub (>=0,<1)", "jinja2 (>=3,<4)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "openai (>=0,<1)", "opensearch-py (>=2.0.0,<3.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pypdf (>=3.4.0,<4.0.0)", "qdrant-client (>=1.0.4,<2.0.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"]
-llms = ["anthropic (>=0.2.2,<0.3.0)", "cohere (>=3,<4)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)"]
+all = ["aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.2.4,<0.3.0)", "beautifulsoup4 (>=4,<5)", "boto3 (>=1.26.96,<2.0.0)", "cohere (>=3,<4)", "deeplake (>=3.2.9,<4.0.0)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "huggingface_hub (>=0,<1)", "jina (>=3.14,<4.0)", "jinja2 (>=3,<4)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "openai (>=0,<1)", "opensearch-py (>=2.0.0,<3.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pyowm (>=3.3.0,<4.0.0)", "pypdf (>=3.4.0,<4.0.0)", "qdrant-client (>=1.0.4,<2.0.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0.3.2,<0.4.0)", "torch (>=1,<2)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"]
+llms = ["anthropic (>=0.2.4,<0.3.0)", "cohere (>=3,<4)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)"]
 
 [[package]]
 name = "markdown-it-py"
@@ -1523,6 +1539,55 @@ files = [
     {file = "packaging-23.0.tar.gz", hash = "sha256:b6ad297f8907de0fa2fe1ccbd26fdaf387f5f47c7275fedf8cce89f99446cf97"},
 ]
 
+[[package]]
+name = "pandas"
+version = "1.5.3"
+description = "Powerful data structures for data analysis, time series, and statistics"
+category = "main"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pandas-1.5.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:3749077d86e3a2f0ed51367f30bf5b82e131cc0f14260c4d3e499186fccc4406"},
+    {file = "pandas-1.5.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:972d8a45395f2a2d26733eb8d0f629b2f90bebe8e8eddbb8829b180c09639572"},
+    {file = "pandas-1.5.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:50869a35cbb0f2e0cd5ec04b191e7b12ed688874bd05dd777c19b28cbea90996"},
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+    {file = "pandas-1.5.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f69c4029613de47816b1bb30ff5ac778686688751a5e9c99ad8c7031f6508e5"},
+    {file = "pandas-1.5.3-cp39-cp39-win32.whl", hash = "sha256:7cec0bee9f294e5de5bbfc14d0573f65526071029d036b753ee6507d2a21480a"},
+    {file = "pandas-1.5.3-cp39-cp39-win_amd64.whl", hash = "sha256:dfd681c5dc216037e0b0a2c821f5ed99ba9f03ebcf119c7dac0e9a7b960b9ec9"},
+    {file = "pandas-1.5.3.tar.gz", hash = "sha256:74a3fd7e5a7ec052f183273dc7b0acd3a863edf7520f5d3a1765c04ffdb3b0b1"},
+]
+
+[package.dependencies]
+numpy = [
+    {version = ">=1.20.3", markers = "python_version < \"3.10\""},
+    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
+    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
+]
+python-dateutil = ">=2.8.1"
+pytz = ">=2020.1"
+
+[package.extras]
+test = ["hypothesis (>=5.5.3)", "pytest (>=6.0)", "pytest-xdist (>=1.31)"]
+
 [[package]]
 name = "parso"
 version = "0.8.3"
@@ -1852,7 +1917,7 @@ testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.
 name = "python-dateutil"
 version = "2.8.2"
 description = "Extensions to the standard Python datetime module"
-category = "dev"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
@@ -1863,6 +1928,18 @@ files = [
 [package.dependencies]
 six = ">=1.5"
 
+[[package]]
+name = "pytz"
+version = "2023.3"
+description = "World timezone definitions, modern and historical"
+category = "main"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pytz-2023.3-py2.py3-none-any.whl", hash = "sha256:a151b3abb88eda1d4e34a9814df37de2a80e301e68ba0fd856fb9b46bfbbbffb"},
+    {file = "pytz-2023.3.tar.gz", hash = "sha256:1d8ce29db189191fb55338ee6d0387d82ab59f3d00eac103412d64e0ebd0c588"},
+]
+
 [[package]]
 name = "pywin32"
 version = "306"
@@ -2635,4 +2712,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "18b858c93c242f3b53e9f77284904aa0eabb4c955f905cfe5fb227a6785bfabc"
+content-hash = "2b523f3d737ef8f7082e8156f096bce6f4f84a8bee9d07bd4ed23a29d3dcfab1"
diff --git a/pyproject.toml b/pyproject.toml
index c7d2d8767..ec715385f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.0.50"
+version = "0.0.52"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [
@@ -29,9 +29,11 @@ google-search-results = "^2.4.1"
 google-api-python-client = "^2.79.0"
 typer = "^0.7.0"
 gunicorn = "^20.1.0"
-langchain = "^0.0.113"
+langchain = "^0.0.127"
 openai = "^0.27.2"
 types-pyyaml = "^6.0.12.8"
+dill = "^0.3.6"
+pandas = "^1.5.3"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.1.0"
diff --git a/src/backend/langflow/__main__.py b/src/backend/langflow/__main__.py
index ea9386d7f..030a41ed0 100644
--- a/src/backend/langflow/__main__.py
+++ b/src/backend/langflow/__main__.py
@@ -7,6 +7,7 @@ import typer
 from fastapi.staticfiles import StaticFiles
 
 from langflow.main import create_app
+from langflow.settings import settings
 
 logger = logging.getLogger(__name__)
 
@@ -17,9 +18,21 @@ def get_number_of_workers(workers=None):
     return workers
 
 
+def update_settings(config: str):
+    """Update the settings from a config file."""
+    if config:
+        settings.update_from_yaml(config)
+
+
 def serve(
-    host: str = "127.0.0.1", workers: int = 1, timeout: int = 60, port: int = 7860
+    host: str = "127.0.0.1",
+    workers: int = 1,
+    timeout: int = 60,
+    port: int = 7860,
+    config: str = "config.yaml",
+    log_level: str = "info",
 ):
+    update_settings(config)
     app = create_app()
     # get the directory of the current file
     path = Path(__file__).parent
@@ -42,7 +55,7 @@ def serve(
         # MacOS requires a env variable to be set to use gunicorn
         import uvicorn
 
-        uvicorn.run(app, host=host, port=port, log_level="info")
+        uvicorn.run(app, host=host, port=port, log_level=log_level)
     else:
         from langflow.server import LangflowApplication
 
diff --git a/src/backend/langflow/api/endpoints.py b/src/backend/langflow/api/endpoints.py
index e0f1ac0f1..c82616d3e 100644
--- a/src/backend/langflow/api/endpoints.py
+++ b/src/backend/langflow/api/endpoints.py
@@ -1,15 +1,16 @@
+import logging
 from typing import Any, Dict
 
 from fastapi import APIRouter, HTTPException
-from langflow.api.base import Code, ValidationResponse
 
+from langflow.api.base import Code, ValidationResponse
 from langflow.interface.run import process_graph
 from langflow.interface.types import build_langchain_types_dict
 from langflow.utils.validate import validate_code
 
-
 # build router
 router = APIRouter()
+logger = logging.getLogger(__name__)
 
 
 @router.get("/all")
@@ -22,7 +23,9 @@ def get_load(data: Dict[str, Any]):
     try:
         return process_graph(data)
     except Exception as e:
-        return HTTPException(status_code=500, detail=str(e))
+        # Log stack trace
+        logger.exception(e)
+        raise HTTPException(status_code=500, detail=str(e)) from e
 
 
 @router.post("/validate", status_code=200, response_model=ValidationResponse)
diff --git a/src/backend/langflow/api/list_endpoints.py b/src/backend/langflow/api/list_endpoints.py
deleted file mode 100644
index 15946a2db..000000000
--- a/src/backend/langflow/api/list_endpoints.py
+++ /dev/null
@@ -1,58 +0,0 @@
-from fastapi import APIRouter
-
-from langflow.interface.listing import list_type
-
-# build router
-router = APIRouter(
-    prefix="/list",
-    tags=["list"],
-)
-
-
-@router.get("/")
-def read_items():
-    """List all components"""
-    return [
-        "chains",
-        "agents",
-        "prompts",
-        "llms",
-        "tools",
-    ]
-
-
-@router.get("/chains")
-def list_chains():
-    """List all chain types"""
-    return list_type("chains")
-
-
-@router.get("/agents")
-def list_agents():
-    """List all agent types"""
-    # return list(agents.loading.AGENT_TO_CLASS.keys())
-    return list_type("agents")
-
-
-@router.get("/prompts")
-def list_prompts():
-    """List all prompt types"""
-    return list_type("prompts")
-
-
-@router.get("/llms")
-def list_llms():
-    """List all llm types"""
-    return list_type("llms")
-
-
-@router.get("/memories")
-def list_memories():
-    """List all memory types"""
-    return list_type("memories")
-
-
-@router.get("/tools")
-def list_tools():
-    """List all load tools"""
-    return list_type("tools")
diff --git a/src/backend/langflow/api/signature.py b/src/backend/langflow/api/signature.py
deleted file mode 100644
index 96b654dbe..000000000
--- a/src/backend/langflow/api/signature.py
+++ /dev/null
@@ -1,63 +0,0 @@
-from fastapi import APIRouter, HTTPException
-
-from langflow.interface.signature import get_signature
-
-# build router
-router = APIRouter(
-    prefix="/signatures",
-    tags=["signatures"],
-)
-
-
-@router.get("/chain")
-def get_chain(name: str):
-    """Get the signature of a chain."""
-    try:
-        return get_signature(name, "chains")
-    except ValueError as exc:
-        raise HTTPException(status_code=404, detail="Chain not found") from exc
-
-
-@router.get("/agent")
-def get_agent(name: str):
-    """Get the signature of an agent."""
-    try:
-        return get_signature(name, "agents")
-    except ValueError as exc:
-        raise HTTPException(status_code=404, detail="Agent not found") from exc
-
-
-@router.get("/prompt")
-def get_prompt(name: str):
-    """Get the signature of a prompt."""
-    try:
-        return get_signature(name, "prompts")
-    except ValueError as exc:
-        raise HTTPException(status_code=404, detail="Prompt not found") from exc
-
-
-@router.get("/llm")
-def get_llm(name: str):
-    """Get the signature of an llm."""
-    try:
-        return get_signature(name, "llms")
-    except ValueError as exc:
-        raise HTTPException(status_code=404, detail="LLM not found") from exc
-
-
-@router.get("/memory")
-def get_memory(name: str):
-    """Get the signature of a memory."""
-    try:
-        return get_signature(name, "memories")
-    except ValueError as exc:
-        raise HTTPException(status_code=404, detail="Memory not found") from exc
-
-
-@router.get("/tool")
-def get_tool(name: str):
-    """Get the signature of a tool."""
-    try:
-        return get_signature(name, "tools")
-    except ValueError as exc:
-        raise HTTPException(status_code=404, detail="Tool not found") from exc
diff --git a/src/backend/langflow/cache/__init__.py b/src/backend/langflow/cache/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/backend/langflow/cache/utils.py b/src/backend/langflow/cache/utils.py
new file mode 100644
index 000000000..514d991e5
--- /dev/null
+++ b/src/backend/langflow/cache/utils.py
@@ -0,0 +1,50 @@
+import contextlib
+import hashlib
+import json
+import os
+import tempfile
+from pathlib import Path
+
+import dill  # type: ignore
+
+PREFIX = "langflow_cache"
+
+
+def clear_old_cache_files(max_cache_size: int = 10):
+    cache_dir = Path(tempfile.gettempdir())
+    cache_files = list(cache_dir.glob(f"{PREFIX}_*.dill"))
+
+    if len(cache_files) > max_cache_size:
+        cache_files_sorted_by_mtime = sorted(
+            cache_files, key=lambda x: x.stat().st_mtime, reverse=True
+        )
+
+        for cache_file in cache_files_sorted_by_mtime[max_cache_size:]:
+            with contextlib.suppress(OSError):
+                os.remove(cache_file)
+
+
+def remove_position_info(node):
+    node.pop("position", None)
+
+
+def compute_hash(graph_data):
+    for node in graph_data["nodes"]:
+        remove_position_info(node)
+
+    cleaned_graph_json = json.dumps(graph_data, sort_keys=True)
+    return hashlib.sha256(cleaned_graph_json.encode("utf-8")).hexdigest()
+
+
+def save_cache(hash_val, chat_data):
+    cache_path = Path(tempfile.gettempdir()) / f"{PREFIX}_{hash_val}.dill"
+    with cache_path.open("wb") as cache_file:
+        dill.dump(chat_data, cache_file)
+
+
+def load_cache(hash_val):
+    cache_path = Path(tempfile.gettempdir()) / f"{PREFIX}_{hash_val}.dill"
+    if cache_path.exists():
+        with cache_path.open("rb") as cache_file:
+            return dill.load(cache_file)
+    return None
diff --git a/src/backend/langflow/config.yaml b/src/backend/langflow/config.yaml
index 602c89925..5f2d37d74 100644
--- a/src/backend/langflow/config.yaml
+++ b/src/backend/langflow/config.yaml
@@ -6,6 +6,8 @@ chains:
 
 agents:
   - ZeroShotAgent
+  - JsonAgent
+  - CSVAgent
 
 prompts:
   - PromptTemplate
@@ -22,9 +24,14 @@ tools:
   - Serper Search
   - Tool
   - PythonFunction
+  - JsonSpec
 
-memories:
-  # - ConversationBufferMemory
+wrappers:
+  - RequestsWrapper
+
+toolkits:
+ - OpenAPIToolkit
+ - JsonToolkit
 
 embeddings:
   #
diff --git a/src/backend/langflow/custom/customs.py b/src/backend/langflow/custom/customs.py
index 877a06387..6a70732a0 100644
--- a/src/backend/langflow/custom/customs.py
+++ b/src/backend/langflow/custom/customs.py
@@ -1,9 +1,9 @@
 from langflow.template import nodes
 
-
 CUSTOM_NODES = {
     "prompts": {**nodes.ZeroShotPromptNode().to_dict()},
     "tools": {**nodes.PythonFunctionNode().to_dict(), **nodes.ToolNode().to_dict()},
+    "agents": {**nodes.JsonAgentNode().to_dict(), **nodes.CSVAgentNode().to_dict()},
 }
 
 
diff --git a/src/backend/langflow/graph/__init__.py b/src/backend/langflow/graph/__init__.py
index e69de29bb..097b7a695 100644
--- a/src/backend/langflow/graph/__init__.py
+++ b/src/backend/langflow/graph/__init__.py
@@ -0,0 +1,4 @@
+from langflow.graph.base import Edge, Node
+from langflow.graph.graph import Graph
+
+__all__ = ["Graph", "Node", "Edge"]
diff --git a/src/backend/langflow/graph/base.py b/src/backend/langflow/graph/base.py
new file mode 100644
index 000000000..08ad786ac
--- /dev/null
+++ b/src/backend/langflow/graph/base.py
@@ -0,0 +1,251 @@
+# Description: Graph class for building a graph of nodes and edges
+# Insights:
+#   - Defer prompts building to the last moment or when they have all the tools
+#   - Build each inner agent first, then build the outer agent
+
+import logging
+import types
+from copy import deepcopy
+from typing import Any, Dict, List
+
+from langflow.graph.constants import DIRECT_TYPES
+from langflow.graph.utils import load_file
+from langflow.interface import loading
+from langflow.interface.listing import ALL_TYPES_DICT
+
+logger = logging.getLogger(__name__)
+
+
+class Node:
+    def __init__(self, data: Dict, base_type: str | None = None) -> None:
+        self.id: str = data["id"]
+        self._data = data
+        self.edges: List[Edge] = []
+        self.base_type: str | None = base_type
+        self._parse_data()
+        self._built_object = None
+        self._built = False
+
+    def _parse_data(self) -> None:
+        self.data = self._data["data"]
+        self.output = self.data["node"]["base_classes"]
+        template_dicts = {
+            key: value
+            for key, value in self.data["node"]["template"].items()
+            if isinstance(value, dict)
+        }
+
+        self.required_inputs = [
+            template_dicts[key]["type"]
+            for key, value in template_dicts.items()
+            if value["required"]
+        ]
+        self.optional_inputs = [
+            template_dicts[key]["type"]
+            for key, value in template_dicts.items()
+            if not value["required"]
+        ]
+
+        template_dict = self.data["node"]["template"]
+        self.node_type = (
+            self.data["type"] if "Tool" not in self.output else template_dict["_type"]
+        )
+        if self.base_type is None:
+            for base_type, value in ALL_TYPES_DICT.items():
+                if self.node_type in value:
+                    self.base_type = base_type
+                    break
+
+    def _build_params(self):
+        # Some params are required, some are optional
+        # but most importantly, some params are python base classes
+        # like str and others are LangChain objects like LLMChain, BasePromptTemplate
+        # so we need to be able to distinguish between the two
+
+        # The dicts with "type" == "str" are the ones that are python base classes
+        # and most likely have a "value" key
+
+        # So for each key besides "_type" in the template dict, we have a dict
+        # with a "type" key. If the type is not "str", then we need to get the
+        # edge that connects to that node and get the Node with the required data
+        # and use that as the value for the param
+        # If the type is "str", then we need to get the value of the "value" key
+        # and use that as the value for the param
+        template_dict = {
+            key: value
+            for key, value in self.data["node"]["template"].items()
+            if isinstance(value, dict)
+        }
+        params = {}
+        for key, value in template_dict.items():
+            if key == "_type":
+                continue
+            # If the type is not transformable to a python base class
+            # then we need to get the edge that connects to this node
+            if value["type"] == "file":
+                # Load the type in value.get('suffixes') using
+                # what is inside value.get('content')
+                # value.get('value') is the file name
+                type_to_load = value.get("suffixes")
+                file_name = value.get("value")
+                content = value.get("content")
+                loaded_dict = load_file(file_name, content, type_to_load)
+                params[key] = loaded_dict
+
+            # We should check if the type is in something not
+            # the opposite
+            elif value["type"] not in DIRECT_TYPES:
+                # Get the edge that connects to this node
+                try:
+                    edge = next(
+                        (
+                            edge
+                            for edge in self.edges
+                            if edge.target == self
+                            and edge.matched_type in value["type"]
+                        ),
+                        None,
+                    )
+
+                except Exception as e:
+                    raise e
+                # Get the output of the node that the edge connects to
+                # if the value['list'] is True, then there will be more
+                # than one time setting to params[key]
+                # so we need to append to a list if it exists
+                # or create a new list if it doesn't
+
+                if edge is None and value["required"]:
+                    # break line
+                    raise ValueError(
+                        f"Required input {key} for module {self.node_type} not found"
+                    )
+                elif value["list"]:
+                    if key in params:
+                        params[key].append(edge.source)
+                    else:
+                        params[key] = [edge.source]
+                elif value["required"] or edge is not None:
+                    params[key] = edge.source
+            elif value["required"] or value.get("value"):
+                params[key] = value["value"]
+
+        # Add _type to params
+        self.params = params
+
+    def _build(self):
+        # The params dict is used to build the module
+        # it contains values and keys that point to nodes which
+        # have their own params dict
+        # When build is called, we iterate through the params dict
+        # and if the value is a node, we call build on that node
+        # and use the output of that build as the value for the param
+        # if the value is not a node, then we use the value as the param
+        # and continue
+        # Another aspect is that the node_type is the class that we need to import
+        # and instantiate with these built params
+        logger.debug(f"Building {self.node_type}")
+        # Build each node in the params dict
+        for key, value in self.params.copy().items():
+            # Check if Node or list of Nodes and not self
+            # to avoid recursion
+            if isinstance(value, Node):
+                if value == self:
+                    del self.params[key]
+                    continue
+                result = value.build()
+                # If the key is "func", then we need to use the run method
+                if key == "func" and not isinstance(result, types.FunctionType):
+                    # func can be PythonFunction(code='\ndef upper_case(text: str) -> str:\n    return text.upper()\n')
+                    # so we need to check if there is an attribute called run
+                    if hasattr(result, "run"):
+                        result = result.run  # type: ignore
+                    elif hasattr(result, "get_function"):
+                        result = result.get_function()  # type: ignore
+                self.params[key] = result
+            elif isinstance(value, list) and all(
+                isinstance(node, Node) for node in value
+            ):
+                self.params[key] = [node.build() for node in value]  # type: ignore
+
+        # Get the class from LANGCHAIN_TYPES_DICT
+        # and instantiate it with the params
+        # and return the instance
+
+        try:
+            self._built_object = loading.instantiate_class(
+                node_type=self.node_type,
+                base_type=self.base_type,
+                params=self.params,
+            )
+        except Exception as exc:
+            raise ValueError(f"Error building node {self.node_type}") from exc
+
+        if self._built_object is None:
+            raise ValueError(f"Node type {self.node_type} not found")
+
+        self._built = True
+
+    def build(self, force: bool = False) -> Any:
+        if not self._built or force:
+            self._build()
+        return deepcopy(self._built_object)
+
+    def add_edge(self, edge: "Edge") -> None:
+        self.edges.append(edge)
+
+    def __repr__(self) -> str:
+        return f"Node(id={self.id}, data={self.data})"
+
+    def __eq__(self, __o: object) -> bool:
+        return self.id == __o.id if isinstance(__o, Node) else False
+
+    def __hash__(self) -> int:
+        return id(self)
+
+
+class Edge:
+    def __init__(self, source: "Node", target: "Node"):
+        self.source: "Node" = source
+        self.target: "Node" = target
+        self.validate_edge()
+
+    def validate_edge(self) -> None:
+        # Validate that the outputs of the source node are valid inputs
+        # for the target node
+        self.source_types = self.source.output
+        self.target_reqs = self.target.required_inputs + self.target.optional_inputs
+        # Both lists contain strings and sometimes a string contains the value we are
+        # looking for e.g. comgin_out=["Chain"] and target_reqs=["LLMChain"]
+        # so we need to check if any of the strings in source_types is in target_reqs
+        self.valid = any(
+            output in target_req
+            for output in self.source_types
+            for target_req in self.target_reqs
+        )
+        # Get what type of input the target node is expecting
+
+        self.matched_type = next(
+            (
+                output
+                for output in self.source_types
+                for target_req in self.target_reqs
+                if output in target_req
+            ),
+            None,
+        )
+        no_matched_type = self.matched_type is None
+        if no_matched_type:
+            logger.debug(self.source_types)
+            logger.debug(self.target_reqs)
+        if no_matched_type:
+            raise ValueError(
+                f"Edge between {self.source.node_type} and {self.target.node_type} "
+                f"has no matched type"
+            )
+
+    def __repr__(self) -> str:
+        return (
+            f"Edge(source={self.source.id}, target={self.target.id}, valid={self.valid}"
+            f", matched_type={self.matched_type})"
+        )
diff --git a/src/backend/langflow/graph/constants.py b/src/backend/langflow/graph/constants.py
new file mode 100644
index 000000000..095843816
--- /dev/null
+++ b/src/backend/langflow/graph/constants.py
@@ -0,0 +1 @@
+DIRECT_TYPES = ["str", "bool", "code", "int", "float", "Any"]
diff --git a/src/backend/langflow/graph/graph.py b/src/backend/langflow/graph/graph.py
index 8e3c06ef5..ad6cb8d28 100644
--- a/src/backend/langflow/graph/graph.py
+++ b/src/backend/langflow/graph/graph.py
@@ -1,296 +1,25 @@
-# Description: Graph class for building a graph of nodes and edges
-# Insights:
-#   - Defer prompts building to the last moment or when they have all the tools
-#   - Build each inner agent first, then build the outer agent
+from typing import Dict, List, Union
 
-from copy import deepcopy
-import types
-from typing import Any, Dict, List, Optional, Union
+from langflow.graph.base import Edge, Node
+from langflow.graph.nodes import (
+    AgentNode,
+    ChainNode,
+    FileToolNode,
+    LLMNode,
+    PromptNode,
+    ToolkitNode,
+    ToolNode,
+    WrapperNode,
+)
+from langflow.interface.agents.base import agent_creator
+from langflow.interface.chains.base import chain_creator
+from langflow.interface.llms.base import llm_creator
+from langflow.interface.prompts.base import prompt_creator
+from langflow.interface.toolkits.base import toolkits_creator
+from langflow.interface.tools.base import tool_creator
+from langflow.interface.tools.constants import ALL_TOOLS_NAMES, FILE_TOOLS
+from langflow.interface.wrappers.base import wrapper_creator
 from langflow.utils import payload
-from langflow.interface.listing import ALL_TYPES_DICT, ALL_TOOLS_NAMES, TOOLS_DICT
-from langflow.interface import loading
-
-
-class Node:
-    def __init__(self, data: Dict):
-        self.id: str = data["id"]
-        self._data = data
-        self.edges: List[Edge] = []
-        self._parse_data()
-        self._built_object = None
-        self._built = False
-
-    def _parse_data(self) -> None:
-        self.data = self._data["data"]
-        self.output = self.data["node"]["base_classes"]
-        template_dicts = {
-            key: value
-            for key, value in self.data["node"]["template"].items()
-            if isinstance(value, dict)
-        }
-
-        self.required_inputs = [
-            template_dicts[key]["type"]
-            for key, value in template_dicts.items()
-            if value["required"]
-        ]
-        self.optional_inputs = [
-            template_dicts[key]["type"]
-            for key, value in template_dicts.items()
-            if not value["required"]
-        ]
-
-        template_dict = self.data["node"]["template"]
-        self.node_type = (
-            self.data["type"] if "Tool" not in self.output else template_dict["_type"]
-        )
-
-    def _build_params(self):
-        # Some params are required, some are optional
-        # but most importantly, some params are python base classes
-        # like str and others are LangChain objects like LLMChain, BasePromptTemplate
-        # so we need to be able to distinguish between the two
-
-        # The dicts with "type" == "str" are the ones that are python base classes
-        # and most likely have a "value" key
-
-        # So for each key besides "_type" in the template dict, we have a dict
-        # with a "type" key. If the type is not "str", then we need to get the
-        # edge that connects to that node and get the Node with the required data
-        # and use that as the value for the param
-        # If the type is "str", then we need to get the value of the "value" key
-        # and use that as the value for the param
-        template_dict = {
-            key: value
-            for key, value in self.data["node"]["template"].items()
-            if isinstance(value, dict)
-        }
-        params = {}
-        for key, value in template_dict.items():
-            if key == "_type":
-                continue
-            # If the type is not transformable to a python base class
-            # then we need to get the edge that connects to this node
-            if value["type"] not in ["str", "bool", "code"]:
-                # Get the edge that connects to this node
-                edge = next(
-                    (
-                        edge
-                        for edge in self.edges
-                        if edge.target == self and edge.matched_type in value["type"]
-                    ),
-                    None,
-                )
-                # Get the output of the node that the edge connects to
-                # if the value['list'] is True, then there will be more
-                # than one time setting to params[key]
-                # so we need to append to a list if it exists
-                # or create a new list if it doesn't
-                if edge is None and value["required"]:
-                    # break line
-                    raise ValueError(
-                        f"Required input {key} for module {self.node_type} not found"
-                    )
-                if value["list"]:
-                    if key in params:
-                        params[key].append(edge.source)
-                    else:
-                        params[key] = [edge.source]
-                elif value["required"] or edge is not None:
-                    params[key] = edge.source
-            elif value["required"] or value.get("value"):
-                params[key] = value["value"]
-
-        # Add _type to params
-        self.params = params
-
-    def _build(self):
-        # The params dict is used to build the module
-        # it contains values and keys that point to nodes which
-        # have their own params dict
-        # When build is called, we iterate through the params dict
-        # and if the value is a node, we call build on that node
-        # and use the output of that build as the value for the param
-        # if the value is not a node, then we use the value as the param
-        # and continue
-        # Another aspect is that the node_type is the class that we need to import
-        # and instantiate with these built params
-
-        # Build each node in the params dict
-        for key, value in self.params.items():
-            # Check if Node or list of Nodes
-            if isinstance(value, Node):
-                result = value.build()
-                # If the key is "func", then we need to use the run method
-                if key == "func" and not isinstance(result, types.FunctionType):
-                    # func can be PythonFunction(code='\ndef upper_case(text: str) -> str:\n    return text.upper()\n')
-                    # so we need to check if there is an attribute called run
-                    if hasattr(result, "run"):
-                        result = result.run  # type: ignore
-                    elif hasattr(result, "get_function"):
-                        result = result.get_function()  # type: ignore
-                self.params[key] = result
-            elif isinstance(value, list) and all(
-                isinstance(node, Node) for node in value
-            ):
-                self.params[key] = [node.build() for node in value]  # type: ignore
-
-        # Get the class from LANGCHAIN_TYPES_DICT
-        # and instantiate it with the params
-        # and return the instance
-        for base_type, value in ALL_TYPES_DICT.items():
-            if base_type == "tools":
-                value = TOOLS_DICT
-
-            if self.node_type in value:
-                self._built_object = loading.instantiate_class(
-                    node_type=self.node_type,
-                    base_type=base_type,
-                    params=self.params,
-                )
-                break
-
-        if self._built_object is None:
-            raise ValueError(f"Node type {self.node_type} not found")
-
-        self._built = True
-
-    def build(self, force: bool = False) -> Any:
-        if not self._built or force:
-            self._build()
-        return deepcopy(self._built_object)
-
-    def add_edge(self, edge: "Edge") -> None:
-        self.edges.append(edge)
-
-    def __repr__(self) -> str:
-        return f"Node(id={self.id}, data={self.data})"
-
-    def __eq__(self, __o: object) -> bool:
-        return self.id == __o.id if isinstance(__o, Node) else False
-
-    def __hash__(self) -> int:
-        return id(self)
-
-
-class AgentNode(Node):
-    def __init__(self, data: Dict):
-        super().__init__(data)
-        self.tools: List[ToolNode] = []
-        self.chains: List[ChainNode] = []
-
-    def _set_tools_and_chains(self) -> None:
-        for edge in self.edges:
-            source_node = edge.source
-            if isinstance(source_node, ToolNode):
-                self.tools.append(source_node)
-            elif isinstance(source_node, ChainNode):
-                self.chains.append(source_node)
-
-    def build(self, force: bool = False) -> Any:
-        if not self._built or force:
-            self._set_tools_and_chains()
-            # First, build the tools
-            for tool_node in self.tools:
-                tool_node.build()
-
-            # Next, build the chains and the rest
-            for chain_node in self.chains:
-                chain_node.build(tools=self.tools)
-
-            self._build()
-        return deepcopy(self._built_object)
-
-
-class Edge:
-    def __init__(self, source: "Node", target: "Node"):
-        self.source: "Node" = source
-        self.target: "Node" = target
-        self.validate_edge()
-
-    def validate_edge(self) -> None:
-        # Validate that the outputs of the source node are valid inputs
-        # for the target node
-        self.source_types = self.source.output
-        self.target_reqs = self.target.required_inputs + self.target.optional_inputs
-        # Both lists contain strings and sometimes a string contains the value we are
-        # looking for e.g. comgin_out=["Chain"] and target_reqs=["LLMChain"]
-        # so we need to check if any of the strings in source_types is in target_reqs
-        self.valid = any(
-            output in target_req
-            for output in self.source_types
-            for target_req in self.target_reqs
-        )
-        # Get what type of input the target node is expecting
-
-        self.matched_type = next(
-            (
-                output
-                for output in self.source_types
-                for target_req in self.target_reqs
-                if output in target_req
-            ),
-            None,
-        )
-
-    def __repr__(self) -> str:
-        return (
-            f"Edge(source={self.source.id}, target={self.target.id}, valid={self.valid}"
-            f", matched_type={self.matched_type})"
-        )
-
-
-class ToolNode(Node):
-    def __init__(self, data: Dict):
-        super().__init__(data)
-
-    def build(self, force: bool = False) -> Any:
-        if not self._built or force:
-            self._build()
-        return deepcopy(self._built_object)
-
-
-class PromptNode(Node):
-    def __init__(self, data: Dict):
-        super().__init__(data)
-
-    def build(
-        self,
-        force: bool = False,
-        tools: Optional[Union[List[Node], List[ToolNode]]] = None,
-    ) -> Any:
-        if not self._built or force:
-            # Check if it is a ZeroShotPrompt and needs a tool
-            if self.node_type == "ZeroShotPrompt":
-                tools = (
-                    [tool_node.build() for tool_node in tools]
-                    if tools is not None
-                    else []
-                )
-                self.params["tools"] = tools
-
-            self._build()
-        return deepcopy(self._built_object)
-
-
-class ChainNode(Node):
-    def __init__(self, data: Dict):
-        super().__init__(data)
-
-    def build(
-        self,
-        force: bool = False,
-        tools: Optional[Union[List[Node], List[ToolNode]]] = None,
-    ) -> Any:
-        if not self._built or force:
-            # Check if the chain requires a PromptNode
-            for key, value in self.params.items():
-                if isinstance(value, PromptNode):
-                    # Build the PromptNode, passing the tools if available
-                    self.params[key] = value.build(tools=tools, force=force)
-
-            self._build()
-        return deepcopy(self._built_object)
 
 
 class Graph:
@@ -310,9 +39,19 @@ class Graph:
             edge.source.add_edge(edge)
             edge.target.add_edge(edge)
 
+        # This is a hack to make sure that the LLM node is sent to
+        # the toolkit node
+        llm_node = None
         for node in self.nodes:
             node._build_params()
 
+            if isinstance(node, LLMNode):
+                llm_node = node
+
+        for node in self.nodes:
+            if isinstance(node, ToolkitNode):
+                node.params["llm"] = llm_node
+
     def get_node(self, node_id: str) -> Union[None, Node]:
         return next((node for node in self.nodes if node.id == node_id), None)
 
@@ -365,14 +104,22 @@ class Graph:
             node_type: str = node_data["type"]  # type: ignore
             node_lc_type: str = node_data["node"]["template"]["_type"]  # type: ignore
 
-            if node_type in {"ZeroShotPrompt", "PromptTemplate"}:
+            if node_type in prompt_creator.to_list():
                 nodes.append(PromptNode(node))
-            elif "agent" in node_type.lower():
+            elif node_type in agent_creator.to_list():
                 nodes.append(AgentNode(node))
-            elif "chain" in node_type.lower():
+            elif node_type in chain_creator.to_list():
                 nodes.append(ChainNode(node))
-            elif "tool" in node_type.lower() or node_lc_type in ALL_TOOLS_NAMES:
+            elif node_type in tool_creator.to_list() or node_lc_type in ALL_TOOLS_NAMES:
+                if node_type in FILE_TOOLS:
+                    nodes.append(FileToolNode(node))
                 nodes.append(ToolNode(node))
+            elif node_type in toolkits_creator.to_list():
+                nodes.append(ToolkitNode(node))
+            elif node_type in wrapper_creator.to_list():
+                nodes.append(WrapperNode(node))
+            elif node_type in llm_creator.to_list():
+                nodes.append(LLMNode(node))
             else:
                 nodes.append(Node(node))
         return nodes
diff --git a/src/backend/langflow/graph/nodes.py b/src/backend/langflow/graph/nodes.py
new file mode 100644
index 000000000..b465e3817
--- /dev/null
+++ b/src/backend/langflow/graph/nodes.py
@@ -0,0 +1,144 @@
+from copy import deepcopy
+from typing import Any, Dict, List, Optional, Union
+
+from langflow.graph.base import Node
+from langflow.graph.utils import extract_input_variables_from_prompt
+
+
+class AgentNode(Node):
+    def __init__(self, data: Dict):
+        super().__init__(data, base_type="agents")
+
+        self.tools: List[ToolNode] = []
+        self.chains: List[ChainNode] = []
+
+    def _set_tools_and_chains(self) -> None:
+        for edge in self.edges:
+            source_node = edge.source
+            if isinstance(source_node, ToolNode):
+                self.tools.append(source_node)
+            elif isinstance(source_node, ChainNode):
+                self.chains.append(source_node)
+
+    def build(self, force: bool = False) -> Any:
+        if not self._built or force:
+            self._set_tools_and_chains()
+            # First, build the tools
+            for tool_node in self.tools:
+                tool_node.build()
+
+            # Next, build the chains and the rest
+            for chain_node in self.chains:
+                chain_node.build(tools=self.tools)
+
+            self._build()
+        return deepcopy(self._built_object)
+
+
+class ToolNode(Node):
+    def __init__(self, data: Dict):
+        super().__init__(data, base_type="tools")
+
+    def build(self, force: bool = False) -> Any:
+        if not self._built or force:
+            self._build()
+        return deepcopy(self._built_object)
+
+
+class PromptNode(Node):
+    def __init__(self, data: Dict):
+        super().__init__(data, base_type="prompts")
+
+    def build(
+        self,
+        force: bool = False,
+        tools: Optional[Union[List[Node], List[ToolNode]]] = None,
+    ) -> Any:
+        if not self._built or force:
+            if "input_variables" not in self.params:
+                self.params["input_variables"] = []
+            # Check if it is a ZeroShotPrompt and needs a tool
+            if "ShotPrompt" in self.node_type:
+                tools = (
+                    [tool_node.build() for tool_node in tools]
+                    if tools is not None
+                    else []
+                )
+                self.params["tools"] = tools
+                prompt_params = [
+                    key
+                    for key, value in self.params.items()
+                    if isinstance(value, str) and key != "format_instructions"
+                ]
+            else:
+                prompt_params = ["template"]
+            for param in prompt_params:
+                prompt_text = self.params[param]
+                variables = extract_input_variables_from_prompt(prompt_text)
+                self.params["input_variables"].extend(variables)
+
+            self._build()
+        return deepcopy(self._built_object)
+
+
+class ChainNode(Node):
+    def __init__(self, data: Dict):
+        super().__init__(data, base_type="chains")
+
+    def build(
+        self,
+        force: bool = False,
+        tools: Optional[Union[List[Node], List[ToolNode]]] = None,
+    ) -> Any:
+        if not self._built or force:
+            # Check if the chain requires a PromptNode
+            for key, value in self.params.items():
+                if isinstance(value, PromptNode):
+                    # Build the PromptNode, passing the tools if available
+                    self.params[key] = value.build(tools=tools, force=force)
+
+            self._build()
+        return deepcopy(self._built_object)
+
+
+class LLMNode(Node):
+    def __init__(self, data: Dict):
+        super().__init__(data, base_type="llms")
+
+    def build(self, force: bool = False) -> Any:
+        if not self._built or force:
+            self._build()
+        return deepcopy(self._built_object)
+
+
+class ToolkitNode(Node):
+    def __init__(self, data: Dict):
+        super().__init__(data, base_type="toolkits")
+
+    def build(self, force: bool = False) -> Any:
+        if not self._built or force:
+            self._build()
+
+        return deepcopy(self._built_object)
+
+
+class FileToolNode(ToolNode):
+    def __init__(self, data: Dict):
+        super().__init__(data)
+
+    def build(self, force: bool = False) -> Any:
+        if not self._built or force:
+            self._build()
+        return deepcopy(self._built_object)
+
+
+class WrapperNode(Node):
+    def __init__(self, data: Dict):
+        super().__init__(data, base_type="wrappers")
+
+    def build(self, force: bool = False) -> Any:
+        if not self._built or force:
+            if "headers" in self.params:
+                self.params["headers"] = eval(self.params["headers"])
+            self._build()
+        return deepcopy(self._built_object)
diff --git a/src/backend/langflow/graph/utils.py b/src/backend/langflow/graph/utils.py
index e69de29bb..e7dc9e593 100644
--- a/src/backend/langflow/graph/utils.py
+++ b/src/backend/langflow/graph/utils.py
@@ -0,0 +1,53 @@
+import base64
+import csv
+import io
+import json
+import re
+from typing import Any
+
+import yaml
+
+
+def load_file(file_name, file_content, accepted_types) -> Any:
+    """Load a file from a string."""
+    # Check if the file is accepted
+    if not any(file_name.endswith(suffix) for suffix in accepted_types):
+        raise ValueError(f"File {file_name} is not accepted")
+    # Get the suffix
+    suffix = file_name.split(".")[-1]
+    # file_content == 'data:application/x-yaml;base64,b3BlbmFwaTogIjMuMC4wIg...'
+    data = file_content.split(",")[1]
+    decoded_bytes = base64.b64decode(data)
+
+    # Convert the bytes object to a string
+    decoded_string = decoded_bytes.decode("utf-8")
+    if suffix == "json":
+        # Return the json content
+        return json.loads(decoded_string)
+    elif suffix in ["yaml", "yml"]:
+        # Return the yaml content
+        return yaml.safe_load(decoded_string)
+    elif suffix == "csv":
+        # Load the csv content
+        csv_reader = csv.DictReader(io.StringIO(decoded_string))
+        return list(csv_reader)
+    else:
+        raise ValueError(f"File {file_name} is not accepted")
+
+
+def validate_prompt(prompt: str):
+    """Validate prompt."""
+    if extract_input_variables_from_prompt(prompt):
+        return prompt
+
+    return fix_prompt(prompt)
+
+
+def fix_prompt(prompt: str):
+    """Fix prompt."""
+    return prompt + " {input}"
+
+
+def extract_input_variables_from_prompt(prompt: str) -> list[str]:
+    """Extract input variables from prompt."""
+    return re.findall(r"{(.*?)}", prompt)
diff --git a/src/backend/langflow/interface/agents/__init__.py b/src/backend/langflow/interface/agents/__init__.py
new file mode 100644
index 000000000..df15bc39b
--- /dev/null
+++ b/src/backend/langflow/interface/agents/__init__.py
@@ -0,0 +1,3 @@
+from langflow.interface.agents.base import AgentCreator
+
+__all__ = ["AgentCreator"]
diff --git a/src/backend/langflow/interface/agents.py b/src/backend/langflow/interface/agents/base.py
similarity index 61%
rename from src/backend/langflow/interface/agents.py
rename to src/backend/langflow/interface/agents/base.py
index b271e46b1..35df3bee6 100644
--- a/src/backend/langflow/interface/agents.py
+++ b/src/backend/langflow/interface/agents/base.py
@@ -1,19 +1,30 @@
-from langchain.agents import loading
-from langflow.interface.base import LangChainTypeCreator
-from langflow.utils.util import build_template_from_class
-from langflow.settings import settings
 from typing import Dict, List
 
+from langchain.agents import loading
+
+from langflow.custom.customs import get_custom_nodes
+from langflow.interface.agents.custom import CUSTOM_AGENTS
+from langflow.interface.base import LangChainTypeCreator
+from langflow.settings import settings
+from langflow.utils.util import build_template_from_class
+
 
 class AgentCreator(LangChainTypeCreator):
     type_name: str = "agents"
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return loading.AGENT_TO_CLASS
+        if self.type_dict is None:
+            self.type_dict = loading.AGENT_TO_CLASS
+            # Add JsonAgent to the list of agents
+            for name, agent in CUSTOM_AGENTS.items():
+                self.type_dict[name] = agent
+        return self.type_dict
 
     def get_signature(self, name: str) -> Dict | None:
         try:
+            if name in get_custom_nodes(self.type_name).keys():
+                return get_custom_nodes(self.type_name)[name]
             return build_template_from_class(
                 name, self.type_to_loader_dict, add_function=True
             )
@@ -26,3 +37,6 @@ class AgentCreator(LangChainTypeCreator):
             for agent in self.type_to_loader_dict.values()
             if agent.__name__ in settings.agents or settings.dev
         ]
+
+
+agent_creator = AgentCreator()
diff --git a/src/backend/langflow/interface/agents/custom.py b/src/backend/langflow/interface/agents/custom.py
new file mode 100644
index 000000000..653e3b0be
--- /dev/null
+++ b/src/backend/langflow/interface/agents/custom.py
@@ -0,0 +1,93 @@
+from typing import Any, Optional
+
+from langchain import LLMChain
+from langchain.agents import AgentExecutor, ZeroShotAgent
+from langchain.agents.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX
+from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
+from langchain.agents.agent_toolkits.pandas.prompt import PREFIX as PANDAS_PREFIX
+from langchain.agents.agent_toolkits.pandas.prompt import SUFFIX as PANDAS_SUFFIX
+from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
+from langchain.schema import BaseLanguageModel
+from langchain.tools.python.tool import PythonAstREPLTool
+
+
+class JsonAgent(AgentExecutor):
+    """Json agent"""
+
+    @classmethod
+    def initialize(cls, *args, **kwargs):
+        return cls.from_toolkit_and_llm(*args, **kwargs)
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+    @classmethod
+    def from_toolkit_and_llm(cls, toolkit: JsonToolkit, llm: BaseLanguageModel):
+        tools = toolkit.get_tools()
+        tool_names = [tool.name for tool in tools]
+        prompt = ZeroShotAgent.create_prompt(
+            tools,
+            prefix=JSON_PREFIX,
+            suffix=JSON_SUFFIX,
+            format_instructions=FORMAT_INSTRUCTIONS,
+            input_variables=None,
+        )
+        llm_chain = LLMChain(
+            llm=llm,
+            prompt=prompt,
+        )
+        agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names)
+        return cls.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
+
+    def run(self, *args, **kwargs):
+        return super().run(*args, **kwargs)
+
+
+class CSVAgent(AgentExecutor):
+    """CSV agent"""
+
+    @classmethod
+    def initialize(cls, *args, **kwargs):
+        return cls.from_toolkit_and_llm(*args, **kwargs)
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+    @classmethod
+    def from_toolkit_and_llm(
+        cls,
+        path: dict,
+        llm: BaseLanguageModel,
+        pandas_kwargs: Optional[dict] = None,
+        **kwargs: Any
+    ):
+        import pandas as pd  # type: ignore
+
+        _kwargs = pandas_kwargs or {}
+        df = pd.DataFrame.from_dict(path, **_kwargs)
+
+        tools = [PythonAstREPLTool(locals={"df": df})]  # type: ignore
+        prompt = ZeroShotAgent.create_prompt(
+            tools,
+            prefix=PANDAS_PREFIX,
+            suffix=PANDAS_SUFFIX,
+            input_variables=["df", "input", "agent_scratchpad"],
+        )
+        partial_prompt = prompt.partial(df=str(df.head()))
+        llm_chain = LLMChain(
+            llm=llm,
+            prompt=partial_prompt,
+        )
+        tool_names = [tool.name for tool in tools]
+        agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
+
+        return cls.from_agent_and_tools(agent=agent, tools=tools, verbose=True)
+
+    def run(self, *args, **kwargs):
+        return super().run(*args, **kwargs)
+
+
+CUSTOM_AGENTS = {
+    "JsonAgent": JsonAgent,
+    "CSVAgent": CSVAgent,
+}
diff --git a/src/backend/langflow/interface/base.py b/src/backend/langflow/interface/base.py
index 3ae5e7c08..eb3432d12 100644
--- a/src/backend/langflow/interface/base.py
+++ b/src/backend/langflow/interface/base.py
@@ -1,40 +1,49 @@
-from typing import Dict, List
-from pydantic import BaseModel
 from abc import ABC, abstractmethod
-from langflow.template.template import Template, Field, FrontendNode
+from typing import Any, Dict, List, Optional
 
+from pydantic import BaseModel
+
+from langflow.template.base import FrontendNode, Template, TemplateField
 
 # Assuming necessary imports for Field, Template, and FrontendNode classes
 
 
 class LangChainTypeCreator(BaseModel, ABC):
     type_name: str
+    type_dict: Optional[Dict] = None
 
     @property
     @abstractmethod
     def type_to_loader_dict(self) -> Dict:
-        pass
+        if self.type_dict is None:
+            raise NotImplementedError
+        return self.type_dict
 
     @abstractmethod
-    def get_signature(self, name: str) -> Dict:
+    def get_signature(self, name: str) -> Optional[Dict[Any, Any]]:
         pass
 
     @abstractmethod
     def to_list(self) -> List[str]:
         pass
 
-    def to_dict(self):
-        result = {self.type_name: {}}  # type: Dict
+    def to_dict(self) -> Dict:
+        result: Dict = {self.type_name: {}}
 
         for name in self.to_list():
-            result[self.type_name][name] = self.get_signature(name)
+            # frontend_node.to_dict() returns a dict with the following structure:
+            # {name: {template: {fields}, description: str}}
+            # so we should update the result dict
+            result[self.type_name].update(self.frontend_node(name).to_dict())
 
         return result
 
     def frontend_node(self, name) -> FrontendNode:
         signature = self.get_signature(name)
+        if signature is None:
+            raise ValueError(f"{name} not found")
         fields = [
-            Field(
+            TemplateField(
                 name=key,
                 field_type=value["type"],
                 required=value.get("required", False),
@@ -43,6 +52,9 @@ class LangChainTypeCreator(BaseModel, ABC):
                 show=value.get("show", True),
                 multiline=value.get("multiline", False),
                 value=value.get("value", None),
+                suffixes=value.get("suffixes", []),
+                file_types=value.get("fileTypes", []),
+                content=value.get("content", None),
             )
             for key, value in signature["template"].items()
             if key != "_type"
@@ -50,7 +62,7 @@ class LangChainTypeCreator(BaseModel, ABC):
         template = Template(type_name=name, fields=fields)
         return FrontendNode(
             template=template,
-            description=signature["description"],
+            description=signature.get("description", ""),
             base_classes=signature["base_classes"],
             name=name,
         )
diff --git a/src/backend/langflow/interface/chains/__init__.py b/src/backend/langflow/interface/chains/__init__.py
new file mode 100644
index 000000000..2e5570b3c
--- /dev/null
+++ b/src/backend/langflow/interface/chains/__init__.py
@@ -0,0 +1,3 @@
+from langflow.interface.chains.base import ChainCreator
+
+__all__ = ["ChainCreator"]
diff --git a/src/backend/langflow/interface/chains.py b/src/backend/langflow/interface/chains/base.py
similarity index 85%
rename from src/backend/langflow/interface/chains.py
rename to src/backend/langflow/interface/chains/base.py
index 4fb323330..e24cba99b 100644
--- a/src/backend/langflow/interface/chains.py
+++ b/src/backend/langflow/interface/chains/base.py
@@ -1,11 +1,11 @@
 from typing import Dict, List
-from langflow.interface.base import LangChainTypeCreator
-from langflow.interface.signature import get_chain_signature
-from langflow.template.template import Field, FrontendNode, Template
-from langflow.utils.util import build_template_from_function
-from langflow.settings import settings
+
 from langchain.chains import loading as chains_loading
 
+from langflow.interface.base import LangChainTypeCreator
+from langflow.settings import settings
+from langflow.utils.util import build_template_from_function
+
 # Assuming necessary imports for Field, Template, and FrontendNode classes
 
 
@@ -14,7 +14,9 @@ class ChainCreator(LangChainTypeCreator):
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return chains_loading.type_to_loader_dict
+        if self.type_dict is None:
+            self.type_dict = chains_loading.type_to_loader_dict
+        return self.type_dict
 
     def get_signature(self, name: str) -> Dict | None:
         try:
@@ -33,3 +35,6 @@ class ChainCreator(LangChainTypeCreator):
                 or settings.dev
             )
         ]
+
+
+chain_creator = ChainCreator()
diff --git a/src/backend/langflow/interface/custom/__init__.py b/src/backend/langflow/interface/custom/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/backend/langflow/interface/custom_types.py b/src/backend/langflow/interface/custom/types.py
similarity index 99%
rename from src/backend/langflow/interface/custom_types.py
rename to src/backend/langflow/interface/custom/types.py
index 05d77fd1d..4c641f388 100644
--- a/src/backend/langflow/interface/custom_types.py
+++ b/src/backend/langflow/interface/custom/types.py
@@ -1,7 +1,9 @@
 from typing import Callable, Optional
-from langflow.utils import validate
+
 from pydantic import BaseModel, validator
 
+from langflow.utils import validate
+
 
 class Function(BaseModel):
     code: str
diff --git a/src/backend/langflow/interface/custom_lists.py b/src/backend/langflow/interface/custom_lists.py
index 7e79c8543..59f163338 100644
--- a/src/backend/langflow/interface/custom_lists.py
+++ b/src/backend/langflow/interface/custom_lists.py
@@ -1,15 +1,11 @@
-## LLM
 from typing import Any
 
-from langchain import llms
-from langchain.llms.openai import OpenAIChat
-
-llm_type_to_cls_dict = llms.type_to_cls_dict
-llm_type_to_cls_dict["openai-chat"] = OpenAIChat
-
+## LLM
+from langchain import llms, requests
+from langchain.agents import agent_toolkits
+from langchain.chat_models import ChatOpenAI
 
 ## Memory
-
 # from langchain.memory.buffer_window import ConversationBufferWindowMemory
 # from langchain.memory.chat_memory import ChatMessageHistory
 # from langchain.memory.combined import CombinedMemory
@@ -19,6 +15,96 @@ llm_type_to_cls_dict["openai-chat"] = OpenAIChat
 # from langchain.memory.simple import SimpleMemory
 # from langchain.memory.summary import ConversationSummaryMemory
 # from langchain.memory.summary_buffer import ConversationSummaryBufferMemory
+## Document Loaders
+from langchain.document_loaders import (
+    AirbyteJSONLoader,
+    AZLyricsLoader,
+    CollegeConfidentialLoader,
+    CoNLLULoader,
+    CSVLoader,
+    DirectoryLoader,
+    EverNoteLoader,
+    FacebookChatLoader,
+    GCSDirectoryLoader,
+    GCSFileLoader,
+    GitbookLoader,
+    GoogleApiClient,
+    GoogleApiYoutubeLoader,
+    GoogleDriveLoader,
+    GutenbergLoader,
+    HNLoader,
+    IFixitLoader,
+    IMSDbLoader,
+    NotebookLoader,
+    NotionDirectoryLoader,
+    ObsidianLoader,
+    OnlinePDFLoader,
+    PagedPDFSplitter,
+    PDFMinerLoader,
+    PyMuPDFLoader,
+    PyPDFLoader,
+    ReadTheDocsLoader,
+    RoamLoader,
+    S3DirectoryLoader,
+    S3FileLoader,
+    SRTLoader,
+    TelegramChatLoader,
+    TextLoader,
+    UnstructuredEmailLoader,
+    UnstructuredFileIOLoader,
+    UnstructuredFileLoader,
+    UnstructuredHTMLLoader,
+    UnstructuredImageLoader,
+    UnstructuredMarkdownLoader,
+    UnstructuredPDFLoader,
+    # BSHTMLLoader,
+    UnstructuredPowerPointLoader,
+    UnstructuredURLLoader,
+    UnstructuredWordDocumentLoader,
+    WebBaseLoader,
+    YoutubeLoader,
+)
+
+## Embeddings
+from langchain.embeddings import (
+    CohereEmbeddings,
+    FakeEmbeddings,
+    HuggingFaceEmbeddings,
+    HuggingFaceHubEmbeddings,
+    HuggingFaceInstructEmbeddings,
+    OpenAIEmbeddings,
+    SelfHostedEmbeddings,
+    SelfHostedHuggingFaceEmbeddings,
+    SelfHostedHuggingFaceInstructEmbeddings,
+    # SagemakerEndpointEmbeddings,
+    TensorflowHubEmbeddings,
+)
+
+## Vector Stores
+from langchain.vectorstores import (
+    FAISS,
+    AtlasDB,
+    Chroma,
+    DeepLake,
+    ElasticVectorSearch,
+    Milvus,
+    OpenSearchVectorSearch,
+    Pinecone,
+    Qdrant,
+    VectorStore,
+    Weaviate,
+)
+
+## Toolkits
+from langflow.interface.importing.utils import import_class
+
+## LLM
+
+llm_type_to_cls_dict = llms.type_to_cls_dict
+llm_type_to_cls_dict["openai-chat"] = ChatOpenAI  # type: ignore
+
+
+## Memory
 
 memory_type_to_cls_dict: dict[str, Any] = {
     # "CombinedMemory": CombinedMemory,
@@ -42,21 +128,26 @@ memory_type_to_cls_dict: dict[str, Any] = {
 # chain_type_to_cls_dict = type_to_loader_dict
 # chain_type_to_cls_dict["conversation_chain"] = ConversationChain
 
+toolkit_type_to_loader_dict: dict[str, Any] = {
+    toolkit_name: import_class(f"langchain.agents.agent_toolkits.{toolkit_name}")
+    # if toolkit_name is lower case it is a loader
+    for toolkit_name in agent_toolkits.__all__
+    if toolkit_name.islower()
+}
+
+toolkit_type_to_cls_dict: dict[str, Any] = {
+    toolkit_name: import_class(f"langchain.agents.agent_toolkits.{toolkit_name}")
+    # if toolkit_name is not lower case it is a class
+    for toolkit_name in agent_toolkits.__all__
+    if not toolkit_name.islower()
+}
+
+
+wrapper_type_to_cls_dict: dict[str, Any] = {
+    wrapper.__name__: wrapper for wrapper in [requests.RequestsWrapper]
+}
 
 ## Embeddings
-from langchain.embeddings import (
-    CohereEmbeddings,
-    FakeEmbeddings,
-    HuggingFaceEmbeddings,
-    HuggingFaceInstructEmbeddings,
-    HuggingFaceHubEmbeddings,
-    OpenAIEmbeddings,
-    # SagemakerEndpointEmbeddings,
-    TensorflowHubEmbeddings,
-    SelfHostedHuggingFaceEmbeddings,
-    SelfHostedHuggingFaceInstructEmbeddings,
-    SelfHostedEmbeddings,
-)
 
 embedding_type_to_cls_dict = {
     "OpenAIEmbeddings": OpenAIEmbeddings,
@@ -73,19 +164,6 @@ embedding_type_to_cls_dict = {
 }
 
 ## Vector Stores
-from langchain.vectorstores import (
-    ElasticVectorSearch,
-    FAISS,
-    VectorStore,
-    Pinecone,
-    Weaviate,
-    Qdrant,
-    Milvus,
-    Chroma,
-    OpenSearchVectorSearch,
-    AtlasDB,
-    DeepLake,
-)
 
 vectorstores_type_to_cls_dict = {
     "ElasticVectorSearch": ElasticVectorSearch,
@@ -103,57 +181,6 @@ vectorstores_type_to_cls_dict = {
 
 ## Document Loaders
 
-from langchain.document_loaders import (
-    UnstructuredFileLoader,
-    UnstructuredFileIOLoader,
-    UnstructuredURLLoader,
-    DirectoryLoader,
-    NotionDirectoryLoader,
-    ReadTheDocsLoader,
-    GoogleDriveLoader,
-    UnstructuredHTMLLoader,
-    # BSHTMLLoader,
-    UnstructuredPowerPointLoader,
-    UnstructuredWordDocumentLoader,
-    UnstructuredPDFLoader,
-    UnstructuredImageLoader,
-    ObsidianLoader,
-    UnstructuredEmailLoader,
-    UnstructuredMarkdownLoader,
-    RoamLoader,
-    YoutubeLoader,
-    S3FileLoader,
-    TextLoader,
-    HNLoader,
-    GitbookLoader,
-    S3DirectoryLoader,
-    GCSFileLoader,
-    GCSDirectoryLoader,
-    WebBaseLoader,
-    IMSDbLoader,
-    AZLyricsLoader,
-    CollegeConfidentialLoader,
-    IFixitLoader,
-    GutenbergLoader,
-    PagedPDFSplitter,
-    PyPDFLoader,
-    EverNoteLoader,
-    AirbyteJSONLoader,
-    OnlinePDFLoader,
-    PDFMinerLoader,
-    PyMuPDFLoader,
-    TelegramChatLoader,
-    SRTLoader,
-    FacebookChatLoader,
-    NotebookLoader,
-    CoNLLULoader,
-    GoogleApiYoutubeLoader,
-    GoogleApiClient,
-    CSVLoader,
-    # BlackboardLoader
-)
-
-
 documentloaders_type_to_cls_dict = {
     "UnstructuredFileLoader": UnstructuredFileLoader,
     "UnstructuredFileIOLoader": UnstructuredFileIOLoader,
diff --git a/src/backend/langflow/interface/documentloaders.py b/src/backend/langflow/interface/documentLoaders/base.py
similarity index 95%
rename from src/backend/langflow/interface/documentloaders.py
rename to src/backend/langflow/interface/documentLoaders/base.py
index ce4dc79ae..494fabfd3 100644
--- a/src/backend/langflow/interface/documentloaders.py
+++ b/src/backend/langflow/interface/documentLoaders/base.py
@@ -1,8 +1,9 @@
+from typing import Dict, List
+
+from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import documentloaders_type_to_cls_dict
 from langflow.settings import settings
-from langflow.interface.base import LangChainTypeCreator
 from langflow.utils.util import build_template_from_class
-from typing import Dict, List
 
 
 class DocumentLoaderCreator(LangChainTypeCreator):
@@ -25,3 +26,6 @@ class DocumentLoaderCreator(LangChainTypeCreator):
             for documentloader in self.type_to_loader_dict.values()
             if documentloader.__name__ in settings.documentloaders or settings.dev
         ]
+
+
+documentloader_creator = DocumentLoaderCreator()
diff --git a/src/backend/langflow/interface/embeddings.py b/src/backend/langflow/interface/embeddings/base.py
similarity index 95%
rename from src/backend/langflow/interface/embeddings.py
rename to src/backend/langflow/interface/embeddings/base.py
index 61130305d..de1921b5e 100644
--- a/src/backend/langflow/interface/embeddings.py
+++ b/src/backend/langflow/interface/embeddings/base.py
@@ -1,8 +1,9 @@
+from typing import Dict, List
+
+from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import embedding_type_to_cls_dict
 from langflow.settings import settings
-from langflow.interface.base import LangChainTypeCreator
 from langflow.utils.util import build_template_from_class
-from typing import Dict, List
 
 
 class EmbeddingCreator(LangChainTypeCreator):
@@ -25,3 +26,6 @@ class EmbeddingCreator(LangChainTypeCreator):
             for embedding in self.type_to_loader_dict.values()
             if embedding.__name__ in settings.embeddings or settings.dev
         ]
+
+
+embedding_creator = EmbeddingCreator()
diff --git a/src/backend/langflow/interface/importing/utils.py b/src/backend/langflow/interface/importing/utils.py
index 5524e2d32..f054ddc26 100644
--- a/src/backend/langflow/interface/importing/utils.py
+++ b/src/backend/langflow/interface/importing/utils.py
@@ -8,12 +8,22 @@ from langchain.agents import Agent
 from langchain.chains.base import Chain
 from langchain.llms.base import BaseLLM
 from langchain.tools import BaseTool
-from langflow.utils.util import get_tool_by_name
+
+from langflow.interface.tools.util import get_tool_by_name
 
 
 def import_module(module_path: str) -> Any:
     """Import module from module path"""
-    return importlib.import_module(module_path)
+    if "from" not in module_path:
+        # Import the module using the module path
+        return importlib.import_module(module_path)
+    # Split the module path into its components
+    _, module_path, _, object_name = module_path.split()
+
+    # Import the module using the module path
+    module = importlib.import_module(module_path)
+
+    return getattr(module, object_name)
 
 
 def import_by_type(_type: str, name: str) -> Any:
@@ -24,6 +34,8 @@ def import_by_type(_type: str, name: str) -> Any:
         "llms": import_llm,
         "tools": import_tool,
         "chains": import_chain,
+        "toolkits": import_toolkit,
+        "wrappers": import_wrapper,
     }
     return func_dict[_type](name)
 
@@ -42,8 +54,20 @@ def import_prompt(prompt: str) -> PromptTemplate:
     return import_class(f"langchain.prompts.{prompt}")
 
 
+def import_wrapper(wrapper: str) -> Any:
+    """Import wrapper from wrapper name"""
+    return import_module(f"from langchain.requests import {wrapper}")
+
+
+def import_toolkit(toolkit: str) -> Any:
+    """Import toolkit from toolkit name"""
+    return import_module(f"from langchain.agents.agent_toolkits import {toolkit}")
+
+
 def import_agent(agent: str) -> Agent:
     """Import agent from agent name"""
+    # check for custom agent
+
     return import_class(f"langchain.agents.{agent}")
 
 
diff --git a/src/backend/langflow/interface/listing.py b/src/backend/langflow/interface/listing.py
index 53d34e2a5..b11b3cef9 100644
--- a/src/backend/langflow/interface/listing.py
+++ b/src/backend/langflow/interface/listing.py
@@ -1,106 +1,27 @@
-from langchain import agents, chains, prompts
-
-from langflow.custom import customs
-from langflow.interface.custom_lists import (
-    llm_type_to_cls_dict,
-    memory_type_to_cls_dict,
-)
-from langflow.settings import settings
-from langflow.utils import util
-from langchain.agents.load_tools import get_all_tool_names
-from langchain.agents import Tool
-from langflow.interface.custom_types import PythonFunction
-
-
-CUSTOM_TOOLS = {"Tool": Tool, "PythonFunction": PythonFunction}
-TOOLS_DICT = util.get_tools_dict()
-ALL_TOOLS_NAMES = set(get_all_tool_names() + list(CUSTOM_TOOLS.keys()))
+from langflow.interface.agents.base import agent_creator
+from langflow.interface.chains.base import chain_creator
+from langflow.interface.llms.base import llm_creator
+from langflow.interface.memories.base import memory_creator
+from langflow.interface.prompts.base import prompt_creator
+from langflow.interface.toolkits.base import toolkits_creator
+from langflow.interface.tools.base import tool_creator
+from langflow.interface.wrappers.base import wrapper_creator
 
 
 def get_type_dict():
     return {
-        "chains": list_chain_types,
-        "agents": list_agents,
-        "prompts": list_prompts,
-        "llms": list_llms,
-        "tools": list_tools,
-        "memories": list_memories,
+        "agents": agent_creator.to_list(),
+        "prompts": prompt_creator.to_list(),
+        "llms": llm_creator.to_list(),
+        "tools": tool_creator.to_list(),
+        "chains": chain_creator.to_list(),
+        "memory": memory_creator.to_list(),
+        "toolkits": toolkits_creator.to_list(),
+        "wrappers": wrapper_creator.to_list(),
     }
 
 
-def list_type(object_type: str):
-    """List all components"""
-    return get_type_dict().get(object_type, lambda: None)()
-
-
-def list_agents():
-    """List all agent types"""
-    return [
-        agent.__name__
-        for agent in agents.loading.AGENT_TO_CLASS.values()
-        if agent.__name__ in settings.agents or settings.dev
-    ]
-
-
-def list_prompts():
-    """List all prompt types"""
-    custom_prompts = customs.get_custom_nodes("prompts")
-    library_prompts = [
-        prompt.__annotations__["return"].__name__
-        for prompt in prompts.loading.type_to_loader_dict.values()
-        if prompt.__annotations__["return"].__name__ in settings.prompts or settings.dev
-    ]
-    return library_prompts + list(custom_prompts.keys())
-
-
-def list_tools():
-    """List all load tools"""
-
-    tools = []
-
-    for tool in ALL_TOOLS_NAMES:
-        tool_params = util.get_tool_params(util.get_tool_by_name(tool))
-        if tool_params and (
-            tool_params.get("name") in settings.tools
-            or (tool_params.get("name") and settings.dev)
-        ):
-            tools.append(tool_params["name"])
-
-    # Add Tool
-    custom_tools = customs.get_custom_nodes("tools")
-    return tools + list(custom_tools.keys())
-
-
-def list_llms():
-    """List all llm types"""
-    return [
-        llm.__name__
-        for llm in llm_type_to_cls_dict.values()
-        if llm.__name__ in settings.llms or settings.dev
-    ]
-
-
-def list_chain_types():
-    """List all chain types"""
-    return [
-        chain.__annotations__["return"].__name__
-        for chain in chains.loading.type_to_loader_dict.values()
-        if chain.__annotations__["return"].__name__ in settings.chains or settings.dev
-    ]
-
-
-def list_memories():
-    """List all memory types"""
-    return [
-        memory.__name__
-        for memory in memory_type_to_cls_dict.values()
-        if memory.__name__ in settings.memories or settings.dev
-    ]
-
-
-LANGCHAIN_TYPES_DICT = {
-    k: list_function() for k, list_function in get_type_dict().items()
-}
+LANGCHAIN_TYPES_DICT = get_type_dict()
 
 # Now we'll build a dict with Langchain types and ours
 
diff --git a/src/backend/langflow/interface/llms/__init__.py b/src/backend/langflow/interface/llms/__init__.py
new file mode 100644
index 000000000..c5d7186fb
--- /dev/null
+++ b/src/backend/langflow/interface/llms/__init__.py
@@ -0,0 +1,3 @@
+from langflow.interface.llms.base import LLMCreator
+
+__all__ = ["LLMCreator"]
diff --git a/src/backend/langflow/interface/llms.py b/src/backend/langflow/interface/llms/base.py
similarity index 85%
rename from src/backend/langflow/interface/llms.py
rename to src/backend/langflow/interface/llms/base.py
index 60dbdb313..688845301 100644
--- a/src/backend/langflow/interface/llms.py
+++ b/src/backend/langflow/interface/llms/base.py
@@ -1,8 +1,9 @@
+from typing import Dict, List
+
+from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import llm_type_to_cls_dict
 from langflow.settings import settings
-from langflow.interface.base import LangChainTypeCreator
 from langflow.utils.util import build_template_from_class
-from typing import Dict, List
 
 
 class LLMCreator(LangChainTypeCreator):
@@ -10,7 +11,9 @@ class LLMCreator(LangChainTypeCreator):
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return llm_type_to_cls_dict
+        if self.type_dict is None:
+            self.type_dict = llm_type_to_cls_dict
+        return self.type_dict
 
     def get_signature(self, name: str) -> Dict | None:
         """Get the signature of an llm."""
@@ -25,3 +28,6 @@ class LLMCreator(LangChainTypeCreator):
             for llm in self.type_to_loader_dict.values()
             if llm.__name__ in settings.llms or settings.dev
         ]
+
+
+llm_creator = LLMCreator()
diff --git a/src/backend/langflow/interface/loading.py b/src/backend/langflow/interface/loading.py
index 1c73368e9..98506f73d 100644
--- a/src/backend/langflow/interface/loading.py
+++ b/src/backend/langflow/interface/loading.py
@@ -1,19 +1,16 @@
 import json
-from typing import Any, Dict, Optional
+from typing import Any, Callable, Dict, Optional
 
+from langchain.agents import ZeroShotAgent
+from langchain.agents import agent as agent_module
 from langchain.agents.agent import AgentExecutor
+from langchain.agents.agent_toolkits.base import BaseToolkit
 from langchain.agents.load_tools import (
     _BASE_TOOLS,
     _EXTRA_LLM_TOOLS,
     _EXTRA_OPTIONAL_TOOLS,
     _LLM_TOOLS,
 )
-from langchain.agents import agent as agent_module
-
-
-from langflow.interface.importing.utils import import_by_type
-
-from langchain.agents import ZeroShotAgent
 from langchain.agents.loading import load_agent_from_config
 from langchain.agents.tools import Tool
 from langchain.callbacks.base import BaseCallbackManager
@@ -21,20 +18,29 @@ from langchain.chains.loading import load_chain_from_config
 from langchain.llms.base import BaseLLM
 from langchain.llms.loading import load_llm_from_config
 
+from langflow.interface.agents.custom import CUSTOM_AGENTS
+from langflow.interface.importing.utils import import_by_type
+from langflow.interface.toolkits.base import toolkits_creator
 from langflow.interface.types import get_type_list
 from langflow.utils import payload, util, validate
 
 
 def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
     """Instantiate class from module type and key, and params"""
+    if node_type in CUSTOM_AGENTS:
+        if custom_agent := CUSTOM_AGENTS.get(node_type):
+            return custom_agent.initialize(**params)  # type: ignore
+
     class_object = import_by_type(_type=base_type, name=node_type)
+
     if base_type == "agents":
         # We need to initialize it differently
-        allowed_tools = params["allowed_tools"]
-        llm_chain = params["llm_chain"]
-        return load_agent_executor(class_object, allowed_tools, llm_chain)
-    elif base_type == "tools" or node_type != "ZeroShotPrompt":
-        return class_object(**params)
+        return load_agent_executor(class_object, params)
+    elif node_type == "ZeroShotPrompt":
+        if "tools" not in params:
+            params["tools"] = []
+        return ZeroShotAgent.create_prompt(**params)
+
     elif node_type == "PythonFunction":
         # If the node_type is "PythonFunction"
         # we need to get the function from the params
@@ -45,15 +51,19 @@ def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
         if isinstance(function_string, str):
             return validate.eval_function(function_string)
         raise ValueError("Function should be a string")
+    elif base_type == "toolkits":
+        loaded_toolkit = class_object(**params)
+        # Check if node_type has a loader
+        if toolkits_creator.has_create_function(node_type):
+            return load_toolkits_executor(node_type, loaded_toolkit, params)
+        return loaded_toolkit
     else:
-        if "tools" not in params:
-            params["tools"] = []
-        return ZeroShotAgent.create_prompt(**params)
+        return class_object(**params)
 
 
 def load_flow_from_json(path: str):
     # This is done to avoid circular imports
-    from langflow.graph.graph import Graph
+    from langflow.graph import Graph
 
     """Load flow from json file"""
     with open(path, "r") as f:
@@ -122,10 +132,10 @@ def load_agent_executor_from_config(
     )
 
 
-def load_agent_executor(
-    agent_class: type[agent_module.Agent], allowed_tools, llm_chain, **kwargs
-):
+def load_agent_executor(agent_class: type[agent_module.Agent], params, **kwargs):
     """Load agent executor from agent class, tools and chain"""
+    allowed_tools = params["allowed_tools"]
+    llm_chain = params["llm_chain"]
     tool_names = [tool.name for tool in allowed_tools]
     agent = agent_class(allowed_tools=tool_names, llm_chain=llm_chain)
     return AgentExecutor.from_agent_and_tools(
@@ -135,6 +145,12 @@ def load_agent_executor(
     )
 
 
+def load_toolkits_executor(node_type: str, toolkit: BaseToolkit, params: dict):
+    create_function: Callable = toolkits_creator.get_create_function(node_type)
+    if llm := params.get("llm"):
+        return create_function(llm=llm, toolkit=toolkit)
+
+
 def load_tools_from_config(tool_list: list[dict]) -> list:
     """Load tools based on a config list.
 
diff --git a/src/backend/langflow/interface/memories/__init__.py b/src/backend/langflow/interface/memories/__init__.py
new file mode 100644
index 000000000..845eb29fe
--- /dev/null
+++ b/src/backend/langflow/interface/memories/__init__.py
@@ -0,0 +1,3 @@
+from langflow.interface.memories.base import MemoryCreator
+
+__all__ = ["MemoryCreator"]
diff --git a/src/backend/langflow/interface/memories.py b/src/backend/langflow/interface/memories/base.py
similarity index 85%
rename from src/backend/langflow/interface/memories.py
rename to src/backend/langflow/interface/memories/base.py
index f14da7e70..99af98a1b 100644
--- a/src/backend/langflow/interface/memories.py
+++ b/src/backend/langflow/interface/memories/base.py
@@ -1,8 +1,9 @@
+from typing import Dict, List
+
+from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import memory_type_to_cls_dict
 from langflow.settings import settings
-from langflow.interface.base import LangChainTypeCreator
 from langflow.utils.util import build_template_from_class
-from typing import Dict, List
 
 
 class MemoryCreator(LangChainTypeCreator):
@@ -10,7 +11,9 @@ class MemoryCreator(LangChainTypeCreator):
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return memory_type_to_cls_dict
+        if self.type_dict is None:
+            self.type_dict = memory_type_to_cls_dict
+        return self.type_dict
 
     def get_signature(self, name: str) -> Dict | None:
         """Get the signature of a memory."""
@@ -25,3 +28,6 @@ class MemoryCreator(LangChainTypeCreator):
             for memory in self.type_to_loader_dict.values()
             if memory.__name__ in settings.memories or settings.dev
         ]
+
+
+memory_creator = MemoryCreator()
diff --git a/src/backend/langflow/interface/prompts/__init__.py b/src/backend/langflow/interface/prompts/__init__.py
new file mode 100644
index 000000000..2a81e8bf0
--- /dev/null
+++ b/src/backend/langflow/interface/prompts/__init__.py
@@ -0,0 +1,3 @@
+from langflow.interface.prompts.base import PromptCreator
+
+__all__ = ["PromptCreator"]
diff --git a/src/backend/langflow/interface/prompts.py b/src/backend/langflow/interface/prompts/base.py
similarity index 78%
rename from src/backend/langflow/interface/prompts.py
rename to src/backend/langflow/interface/prompts/base.py
index 0b32b6313..f730481a9 100644
--- a/src/backend/langflow/interface/prompts.py
+++ b/src/backend/langflow/interface/prompts/base.py
@@ -1,22 +1,26 @@
-from langchain.prompts import loading
-from langflow.interface.base import LangChainTypeCreator
-from langflow.utils.util import build_template_from_function
-from langflow.settings import settings
-from langflow.custom.customs import get_custom_nodes
 from typing import Dict, List
 
+from langchain.prompts import loading
+
+from langflow.custom.customs import get_custom_nodes
+from langflow.interface.base import LangChainTypeCreator
+from langflow.settings import settings
+from langflow.utils.util import build_template_from_function
+
 
 class PromptCreator(LangChainTypeCreator):
     type_name: str = "prompts"
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return loading.type_to_loader_dict
+        if self.type_dict is None:
+            self.type_dict = loading.type_to_loader_dict
+        return self.type_dict
 
     def get_signature(self, name: str) -> Dict | None:
         try:
-            if name in get_custom_nodes("prompts").keys():
-                return get_custom_nodes("prompts")[name]
+            if name in get_custom_nodes(self.type_name).keys():
+                return get_custom_nodes(self.type_name)[name]
             return build_template_from_function(name, self.type_to_loader_dict)
         except ValueError as exc:
             raise ValueError("Prompt not found") from exc
@@ -30,3 +34,6 @@ class PromptCreator(LangChainTypeCreator):
             or settings.dev
         ]
         return library_prompts + list(custom_prompts.keys())
+
+
+prompt_creator = PromptCreator()
diff --git a/src/backend/langflow/interface/run.py b/src/backend/langflow/interface/run.py
index f4363562c..cb86789ae 100644
--- a/src/backend/langflow/interface/run.py
+++ b/src/backend/langflow/interface/run.py
@@ -3,9 +3,28 @@ import io
 import re
 from typing import Any, Dict
 
+from langflow.cache.utils import compute_hash, load_cache, save_cache
+from langflow.graph.graph import Graph
 from langflow.interface import loading
 from langflow.utils import payload
-from langflow.graph.graph import Graph
+
+
+def load_langchain_object(data_graph):
+    computed_hash = compute_hash(data_graph)
+
+    # Load langchain_object from cache if it exists
+    langchain_object = load_cache(computed_hash)
+    if langchain_object is None:
+        nodes = data_graph["nodes"]
+        # Add input variables
+        nodes = payload.extract_input_variables(nodes)
+        # Nodes, edges and root node
+        edges = data_graph["edges"]
+        graph = Graph(nodes, edges)
+
+        langchain_object = graph.build()
+
+    return computed_hash, langchain_object
 
 
 def process_graph(data_graph: Dict[str, Any]):
@@ -13,19 +32,18 @@ def process_graph(data_graph: Dict[str, Any]):
     Process graph by extracting input variables and replacing ZeroShotPrompt
     with PromptTemplate,then run the graph and return the result and thought.
     """
-    nodes = data_graph["nodes"]
-    # Add input variables
-    # ? Is this necessary?
-    nodes = payload.extract_input_variables(nodes)
-    # Nodes, edges and root node
-    edges = data_graph["edges"]
-    graph = Graph(nodes, edges)
-
-    langchain_object = graph.build()
+    # Load langchain object
+    computed_hash, langchain_object = load_langchain_object(data_graph)
     message = data_graph["message"]
-    # Process json
+
+    # Generate result and thought
     result, thought = get_result_and_thought_using_graph(langchain_object, message)
 
+    # Save langchain_object to cache
+    # We have to save it here because if the
+    # memory is updated we need to keep the new values
+    save_cache(computed_hash, langchain_object)
+
     return {
         "result": result,
         "thought": re.sub(
@@ -48,9 +66,8 @@ def get_result_and_thought_using_graph(loaded_langchain, message: str):
             )
             thought = output_buffer.getvalue()
 
-    except Exception as e:
-        result = f"Error: {str(e)}"
-        thought = ""
+    except Exception as exc:
+        raise ValueError(f"Error: {str(exc)}") from exc
     return result, thought
 
 
diff --git a/src/backend/langflow/interface/signature.py b/src/backend/langflow/interface/signature.py
deleted file mode 100644
index 390f64671..000000000
--- a/src/backend/langflow/interface/signature.py
+++ /dev/null
@@ -1,170 +0,0 @@
-from typing import Any, Dict  # noqa: F401
-
-from langchain import agents, chains, prompts
-from langchain.agents.load_tools import (
-    _BASE_TOOLS,
-    _EXTRA_LLM_TOOLS,
-    _EXTRA_OPTIONAL_TOOLS,
-    _LLM_TOOLS,
-)
-
-from langflow.custom import customs
-from langflow.interface.custom_lists import (
-    llm_type_to_cls_dict,
-    memory_type_to_cls_dict,
-)
-from langflow.interface.listing import CUSTOM_TOOLS, ALL_TOOLS_NAMES
-from langflow.template.template import Field, Template
-from langflow.utils import util
-
-
-def get_signature(name: str, object_type: str):
-    """Get the signature of an object."""
-    return {
-        "chains": get_chain_signature,
-        "agents": get_agent_signature,
-        "prompts": get_prompt_signature,
-        "llms": get_llm_signature,
-        # "memories": get_memory_signature,
-        "tools": get_tool_signature,
-    }.get(object_type, lambda name: f"Invalid type: {name}")(name)
-
-
-def get_chain_signature(name: str):
-    """Get the chain type by signature."""
-    try:
-        return util.build_template_from_function(
-            name, chains.loading.type_to_loader_dict, add_function=True
-        )
-
-    except ValueError as exc:
-        raise ValueError("Chain not found") from exc
-
-
-def get_agent_signature(name: str):
-    """Get the signature of an agent."""
-    try:
-        return util.build_template_from_class(
-            name, agents.loading.AGENT_TO_CLASS, add_function=True
-        )
-    except ValueError as exc:
-        raise ValueError("Agent not found") from exc
-
-
-def get_prompt_signature(name: str):
-    """Get the signature of a prompt."""
-    try:
-        if name in customs.get_custom_nodes("prompts").keys():
-            return customs.get_custom_nodes("prompts")[name]
-        return util.build_template_from_function(
-            name, prompts.loading.type_to_loader_dict
-        )
-    except ValueError as exc:
-        raise ValueError("Prompt not found") from exc
-
-
-def get_llm_signature(name: str):
-    """Get the signature of an llm."""
-    try:
-        return util.build_template_from_class(name, llm_type_to_cls_dict)
-    except ValueError as exc:
-        raise ValueError("LLM not found") from exc
-
-
-def get_memory_signature(name: str):
-    """Get the signature of a memory."""
-    try:
-        return util.build_template_from_class(name, memory_type_to_cls_dict)
-    except ValueError as exc:
-        raise ValueError("Memory not found") from exc
-
-
-def get_tool_signature(name: str):
-    """Get the signature of a tool."""
-
-    NODE_INPUTS = ["llm", "func"]
-    base_classes = ["Tool"]
-    all_tools = {}
-    for tool in ALL_TOOLS_NAMES:
-        if tool_params := util.get_tool_params(util.get_tool_by_name(tool)):
-            tool_name = tool_params.get("name") or str(tool)
-            all_tools[tool_name] = {"type": tool, "params": tool_params}
-
-    # Raise error if name is not in tools
-    if name not in all_tools.keys():
-        raise ValueError("Tool not found")
-
-    type_dict = {
-        "str": Field(
-            field_type="str",
-            required=True,
-            is_list=False,
-            show=True,
-            placeholder="",
-            value="",
-        ),
-        "llm": Field(field_type="BaseLLM", required=True, is_list=False, show=True),
-        "func": Field(
-            field_type="function",
-            required=True,
-            is_list=False,
-            show=True,
-            multiline=True,
-        ),
-        "code": Field(
-            field_type="str",
-            required=True,
-            is_list=False,
-            show=True,
-            value="",
-            multiline=True,
-        ),
-    }
-
-    tool_type: str = all_tools[name]["type"]  # type: ignore
-
-    if tool_type in _BASE_TOOLS:
-        params = []
-    elif tool_type in _LLM_TOOLS:
-        params = ["llm"]
-    elif tool_type in _EXTRA_LLM_TOOLS:
-        _, extra_keys = _EXTRA_LLM_TOOLS[tool_type]
-        params = ["llm"] + extra_keys
-    elif tool_type in _EXTRA_OPTIONAL_TOOLS:
-        _, extra_keys = _EXTRA_OPTIONAL_TOOLS[tool_type]
-        params = extra_keys
-    elif tool_type == "Tool":
-        params = ["name", "description", "func"]
-    elif tool_type in CUSTOM_TOOLS:
-        # Get custom tool params
-        params = all_tools[name]["params"]  # type: ignore
-        base_classes = ["function"]
-        if node := customs.get_custom_nodes("tools").get(tool_type):
-            return node
-
-    else:
-        params = []
-
-    # Copy the field and add the name
-    fields = []
-    for param in params:
-        if param in NODE_INPUTS:
-            field = type_dict[param].copy()
-        else:
-            field = type_dict["str"].copy()
-        field.name = param
-        if param == "aiosession":
-            field.show = False
-            field.required = False
-        fields.append(field)
-
-    template = Template(fields=fields, type_name=tool_type)
-
-    tool_params = util.get_tool_params(util.get_tool_by_name(tool_type))
-    if tool_params is None:
-        tool_params = {}
-    return {
-        "template": util.format_dict(template.to_dict()),
-        **tool_params,
-        "base_classes": base_classes,
-    }
diff --git a/src/backend/langflow/interface/toolkits/__init__.py b/src/backend/langflow/interface/toolkits/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/backend/langflow/interface/toolkits/base.py b/src/backend/langflow/interface/toolkits/base.py
new file mode 100644
index 000000000..c78a9c051
--- /dev/null
+++ b/src/backend/langflow/interface/toolkits/base.py
@@ -0,0 +1,65 @@
+from typing import Callable, Dict, List
+
+from langchain.agents import agent_toolkits
+
+from langflow.interface.base import LangChainTypeCreator
+from langflow.interface.importing.utils import import_class, import_module
+from langflow.settings import settings
+from langflow.utils.util import build_template_from_class
+
+
+class ToolkitCreator(LangChainTypeCreator):
+    type_name: str = "toolkits"
+    all_types: List[str] = agent_toolkits.__all__
+    create_functions: Dict = {
+        "JsonToolkit": [],
+        "SQLDatabaseToolkit": [],
+        "OpenAPIToolkit": ["create_openapi_agent"],
+        "VectorStoreToolkit": [
+            "create_vectorstore_agent",
+            "create_vectorstore_router_agent",
+            "VectorStoreInfo",
+        ],
+        "ZapierToolkit": [],
+        "PandasToolkit": ["create_pandas_dataframe_agent"],
+        "CSVToolkit": ["create_csv_agent"],
+    }
+
+    @property
+    def type_to_loader_dict(self) -> Dict:
+        if self.type_dict is None:
+            self.type_dict = {
+                toolkit_name: import_class(
+                    f"langchain.agents.agent_toolkits.{toolkit_name}"
+                )
+                # if toolkit_name is not lower case it is a class
+                for toolkit_name in agent_toolkits.__all__
+                if not toolkit_name.islower() and toolkit_name in settings.toolkits
+            }
+
+        return self.type_dict
+
+    def get_signature(self, name: str) -> Dict | None:
+        try:
+            return build_template_from_class(name, self.type_to_loader_dict)
+        except ValueError as exc:
+            raise ValueError("Prompt not found") from exc
+
+    def to_list(self) -> List[str]:
+        return list(self.type_to_loader_dict.keys())
+
+    def get_create_function(self, name: str) -> Callable:
+        if loader_name := self.create_functions.get(name, None):
+            # import loader
+            return import_module(
+                f"from langchain.agents.agent_toolkits import {loader_name[0]}"
+            )
+        else:
+            raise ValueError("Loader not found")
+
+    def has_create_function(self, name: str) -> bool:
+        # check if the function list is not empty
+        return bool(self.create_functions.get(name, None))
+
+
+toolkits_creator = ToolkitCreator()
diff --git a/src/backend/langflow/interface/tools/__init__.py b/src/backend/langflow/interface/tools/__init__.py
new file mode 100644
index 000000000..148892e90
--- /dev/null
+++ b/src/backend/langflow/interface/tools/__init__.py
@@ -0,0 +1,3 @@
+from langflow.interface.tools.base import ToolCreator
+
+__all__ = ["ToolCreator"]
diff --git a/src/backend/langflow/interface/tools.py b/src/backend/langflow/interface/tools/base.py
similarity index 61%
rename from src/backend/langflow/interface/tools.py
rename to src/backend/langflow/interface/tools/base.py
index c0a68c691..979e7b8fb 100644
--- a/src/backend/langflow/interface/tools.py
+++ b/src/backend/langflow/interface/tools/base.py
@@ -1,10 +1,5 @@
-from langflow.custom import customs
-from langflow.interface.listing import ALL_TOOLS_NAMES, CUSTOM_TOOLS
-from langflow.template.template import Field, Template
-from langflow.utils import util
-from langflow.settings import settings
-from langflow.interface.base import LangChainTypeCreator
 from typing import Dict, List
+
 from langchain.agents.load_tools import (
     _BASE_TOOLS,
     _EXTRA_LLM_TOOLS,
@@ -12,22 +7,74 @@ from langchain.agents.load_tools import (
     _LLM_TOOLS,
 )
 
+from langflow.custom import customs
+from langflow.interface.base import LangChainTypeCreator
+from langflow.interface.tools.constants import (
+    ALL_TOOLS_NAMES,
+    CUSTOM_TOOLS,
+    FILE_TOOLS,
+)
+from langflow.interface.tools.util import (
+    get_tool_by_name,
+    get_tool_params,
+    get_tools_dict,
+)
+from langflow.settings import settings
+from langflow.template.base import Template, TemplateField
+from langflow.utils import util
+
+TOOL_INPUTS = {
+    "str": TemplateField(
+        field_type="str",
+        required=True,
+        is_list=False,
+        show=True,
+        placeholder="",
+        value="",
+    ),
+    "llm": TemplateField(field_type="BaseLLM", required=True, is_list=False, show=True),
+    "func": TemplateField(
+        field_type="function",
+        required=True,
+        is_list=False,
+        show=True,
+        multiline=True,
+    ),
+    "code": TemplateField(
+        field_type="str",
+        required=True,
+        is_list=False,
+        show=True,
+        value="",
+        multiline=True,
+    ),
+    "dict_": TemplateField(
+        field_type="file",
+        required=True,
+        is_list=False,
+        show=True,
+        value="",
+    ),
+}
+
 
 class ToolCreator(LangChainTypeCreator):
     type_name: str = "tools"
+    tools_dict: Dict | None = None
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return ALL_TOOLS_NAMES
+        if self.tools_dict is None:
+            self.tools_dict = get_tools_dict()
+        return self.tools_dict
 
     def get_signature(self, name: str) -> Dict | None:
         """Get the signature of a tool."""
 
-        NODE_INPUTS = ["llm", "func"]
         base_classes = ["Tool"]
         all_tools = {}
-        for tool in ALL_TOOLS_NAMES:
-            if tool_params := util.get_tool_params(util.get_tool_by_name(tool)):
+        for tool in self.type_to_loader_dict.keys():
+            if tool_params := get_tool_params(get_tool_by_name(tool)):
                 tool_name = tool_params.get("name") or str(tool)
                 all_tools[tool_name] = {"type": tool, "params": tool_params}
 
@@ -35,33 +82,6 @@ class ToolCreator(LangChainTypeCreator):
         if name not in all_tools.keys():
             raise ValueError("Tool not found")
 
-        type_dict = {
-            "str": Field(
-                field_type="str",
-                required=True,
-                is_list=False,
-                show=True,
-                placeholder="",
-                value="",
-            ),
-            "llm": Field(field_type="BaseLLM", required=True, is_list=False, show=True),
-            "func": Field(
-                field_type="function",
-                required=True,
-                is_list=False,
-                show=True,
-                multiline=True,
-            ),
-            "code": Field(
-                field_type="str",
-                required=True,
-                is_list=False,
-                show=True,
-                value="",
-                multiline=True,
-            ),
-        }
-
         tool_type: str = all_tools[name]["type"]  # type: ignore
 
         if tool_type in _BASE_TOOLS:
@@ -82,6 +102,9 @@ class ToolCreator(LangChainTypeCreator):
             base_classes = ["function"]
             if node := customs.get_custom_nodes("tools").get(tool_type):
                 return node
+        elif tool_type in FILE_TOOLS:
+            params = all_tools[name]["params"]  # type: ignore
+            base_classes += [name]
 
         else:
             params = []
@@ -89,10 +112,7 @@ class ToolCreator(LangChainTypeCreator):
         # Copy the field and add the name
         fields = []
         for param in params:
-            if param in NODE_INPUTS:
-                field = type_dict[param].copy()
-            else:
-                field = type_dict["str"].copy()
+            field = TOOL_INPUTS.get(param, TOOL_INPUTS["str"]).copy()
             field.name = param
             if param == "aiosession":
                 field.show = False
@@ -101,9 +121,7 @@ class ToolCreator(LangChainTypeCreator):
 
         template = Template(fields=fields, type_name=tool_type)
 
-        tool_params = util.get_tool_params(util.get_tool_by_name(tool_type))
-        if tool_params is None:
-            tool_params = {}
+        tool_params = all_tools[name]["params"]
         return {
             "template": util.format_dict(template.to_dict()),
             **tool_params,
@@ -116,7 +134,11 @@ class ToolCreator(LangChainTypeCreator):
         tools = []
 
         for tool in ALL_TOOLS_NAMES:
-            tool_params = util.get_tool_params(util.get_tool_by_name(tool))
+            tool_params = get_tool_params(get_tool_by_name(tool))
+
+            if tool_params and not tool_params.get("name"):
+                tool_params["name"] = tool
+
             if tool_params and (
                 tool_params.get("name") in settings.tools
                 or (tool_params.get("name") and settings.dev)
@@ -126,3 +148,6 @@ class ToolCreator(LangChainTypeCreator):
         # Add Tool
         custom_tools = customs.get_custom_nodes("tools")
         return tools + list(custom_tools.keys())
+
+
+tool_creator = ToolCreator()
diff --git a/src/backend/langflow/interface/tools/constants.py b/src/backend/langflow/interface/tools/constants.py
new file mode 100644
index 000000000..caab662a9
--- /dev/null
+++ b/src/backend/langflow/interface/tools/constants.py
@@ -0,0 +1,11 @@
+from langchain.agents import Tool
+from langchain.agents.load_tools import get_all_tool_names
+from langchain.tools.json.tool import JsonSpec
+
+from langflow.interface.custom.types import PythonFunction
+
+FILE_TOOLS = {"JsonSpec": JsonSpec}
+CUSTOM_TOOLS = {"Tool": Tool, "PythonFunction": PythonFunction}
+ALL_TOOLS_NAMES = set(
+    get_all_tool_names() + list(CUSTOM_TOOLS.keys()) + list(FILE_TOOLS.keys())
+)
diff --git a/src/backend/langflow/interface/tools/util.py b/src/backend/langflow/interface/tools/util.py
new file mode 100644
index 000000000..42bc64797
--- /dev/null
+++ b/src/backend/langflow/interface/tools/util.py
@@ -0,0 +1,124 @@
+import ast
+import inspect
+from typing import Dict, Union
+
+from langchain.agents.load_tools import (
+    _BASE_TOOLS,
+    _EXTRA_LLM_TOOLS,
+    _EXTRA_OPTIONAL_TOOLS,
+    _LLM_TOOLS,
+)
+from langchain.agents.tools import Tool
+
+from langflow.interface.tools.constants import CUSTOM_TOOLS, FILE_TOOLS
+
+
+def get_tools_dict():
+    """Get the tools dictionary."""
+
+    return {
+        **_BASE_TOOLS,
+        **_LLM_TOOLS,
+        **{k: v[0] for k, v in _EXTRA_LLM_TOOLS.items()},
+        **{k: v[0] for k, v in _EXTRA_OPTIONAL_TOOLS.items()},
+        **CUSTOM_TOOLS,
+        **FILE_TOOLS,
+    }
+
+
+def get_tool_by_name(name: str):
+    """Get a tool from the tools dictionary."""
+    tools = get_tools_dict()
+    if name not in tools:
+        raise ValueError(f"{name} not found.")
+    return tools[name]
+
+
+def get_func_tool_params(func, **kwargs) -> Union[Dict, None]:
+    tree = ast.parse(inspect.getsource(func))
+
+    # Iterate over the statements in the abstract syntax tree
+    for node in ast.walk(tree):
+        # Find the first return statement
+        if isinstance(node, ast.Return):
+            tool = node.value
+            if isinstance(tool, ast.Call):
+                if isinstance(tool.func, ast.Name) and tool.func.id == "Tool":
+                    if tool.keywords:
+                        tool_params = {}
+                        for keyword in tool.keywords:
+                            if keyword.arg == "name":
+                                tool_params["name"] = ast.literal_eval(keyword.value)
+                            elif keyword.arg == "description":
+                                tool_params["description"] = ast.literal_eval(
+                                    keyword.value
+                                )
+
+                        return tool_params
+                    return {
+                        "name": ast.literal_eval(tool.args[0]),
+                        "description": ast.literal_eval(tool.args[2]),
+                    }
+                #
+                else:
+                    # get the class object from the return statement
+                    try:
+                        class_obj = eval(
+                            compile(ast.Expression(tool), "<string>", "eval")
+                        )
+                    except Exception:
+                        return None
+
+                    return {
+                        "name": getattr(class_obj, "name"),
+                        "description": getattr(class_obj, "description"),
+                    }
+        # Return None if no return statement was found
+    return None
+
+
+def get_class_tool_params(cls, **kwargs) -> Union[Dict, None]:
+    tree = ast.parse(inspect.getsource(cls))
+
+    tool_params = {}
+
+    # Iterate over the statements in the abstract syntax tree
+    for node in ast.walk(tree):
+        if isinstance(node, ast.ClassDef):
+            # Find the class definition and look for methods
+            for stmt in node.body:
+                if isinstance(stmt, ast.FunctionDef) and stmt.name == "__init__":
+                    # There is no assignment statements in the __init__ method
+                    # So we need to get the params from the function definition
+                    for arg in stmt.args.args:
+                        if arg.arg == "name":
+                            # It should be the name of the class
+                            tool_params[arg.arg] = cls.__name__
+                        elif arg.arg == "self":
+                            continue
+                        # If there is not default value, set it to an empty string
+                        else:
+                            try:
+                                annotation = ast.literal_eval(arg.annotation)  # type: ignore
+                                tool_params[arg.arg] = annotation
+                            except ValueError:
+                                tool_params[arg.arg] = ""
+                # Get the attribute name and the annotation
+                elif cls != Tool and isinstance(stmt, ast.AnnAssign):
+                    # Get the attribute name and the annotation
+                    tool_params[stmt.target.id] = ""  # type: ignore
+
+    return tool_params
+
+
+def get_tool_params(tool, **kwargs) -> Dict:
+    # Parse the function code into an abstract syntax tree
+    # Define if it is a function or a class
+    if inspect.isfunction(tool):
+        return get_func_tool_params(tool, **kwargs) or {}
+    elif inspect.isclass(tool):
+        # Get the parameters necessary to
+        # instantiate the class
+        return get_class_tool_params(tool, **kwargs) or {}
+    else:
+        raise ValueError("Tool must be a function or class.")
diff --git a/src/backend/langflow/interface/types.py b/src/backend/langflow/interface/types.py
index 8f1f6da76..aaa616de3 100644
--- a/src/backend/langflow/interface/types.py
+++ b/src/backend/langflow/interface/types.py
@@ -1,15 +1,14 @@
-from langflow.interface.agents import AgentCreator
-from langflow.interface.listing import list_type
-from langflow.interface.llms import LLMCreator
-from langflow.interface.memories import MemoryCreator
-from langflow.interface.prompts import PromptCreator
-from langflow.interface.signature import get_signature
-from langflow.interface.embeddings import EmbeddingCreator
-from langflow.interface.vectorstore import VectorstoreCreator
-from langflow.interface.documentloaders import DocumentLoaderCreator
-from langchain import chains
-from langflow.interface.chains import ChainCreator
-from langflow.interface.tools import ToolCreator
+from langflow.interface.agents.base import agent_creator
+from langflow.interface.chains.base import chain_creator
+from langflow.interface.documentLoaders.base import documentloader_creator
+from langflow.interface.embeddings.base import embedding_creator
+from langflow.interface.llms.base import llm_creator
+from langflow.interface.memories.base import memory_creator
+from langflow.interface.prompts.base import prompt_creator
+from langflow.interface.toolkits.base import toolkits_creator
+from langflow.interface.tools.base import tool_creator
+from langflow.interface.vectorStore.base import vectorstore_creator
+from langflow.interface.wrappers.base import wrapper_creator
 
 
 def get_type_list():
@@ -26,15 +25,6 @@ def get_type_list():
 
 def build_langchain_types_dict():
     """Build a dictionary of all langchain types"""
-    chain_creator = ChainCreator()
-    agent_creator = AgentCreator()
-    prompt_creator = PromptCreator()
-    tool_creator = ToolCreator()
-    llm_creator = LLMCreator()
-    memory_creator = MemoryCreator()
-    embedding_creator = EmbeddingCreator()
-    vectorstore_creator = VectorstoreCreator()
-    documentloader_creator = DocumentLoaderCreator()
 
     all_types = {}
 
@@ -45,6 +35,8 @@ def build_langchain_types_dict():
         llm_creator,
         memory_creator,
         tool_creator,
+        toolkits_creator,
+        wrapper_creator,
         embedding_creator,
         vectorstore_creator,
         documentloader_creator,
diff --git a/src/backend/langflow/interface/vectorstore.py b/src/backend/langflow/interface/vectorStore/base.py
similarity index 95%
rename from src/backend/langflow/interface/vectorstore.py
rename to src/backend/langflow/interface/vectorStore/base.py
index f97674ca4..01c222e07 100644
--- a/src/backend/langflow/interface/vectorstore.py
+++ b/src/backend/langflow/interface/vectorStore/base.py
@@ -1,8 +1,9 @@
+from typing import Dict, List
+
+from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import vectorstores_type_to_cls_dict
 from langflow.settings import settings
-from langflow.interface.base import LangChainTypeCreator
 from langflow.utils.util import build_template_from_class
-from typing import Dict, List
 
 
 class VectorstoreCreator(LangChainTypeCreator):
@@ -25,3 +26,6 @@ class VectorstoreCreator(LangChainTypeCreator):
             for vectorstore in self.type_to_loader_dict.keys()
             if vectorstore in settings.vectorstores or settings.dev
         ]
+
+
+vectorstore_creator = VectorstoreCreator()
diff --git a/src/backend/langflow/interface/wrappers/__init__.py b/src/backend/langflow/interface/wrappers/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/backend/langflow/interface/wrappers/base.py b/src/backend/langflow/interface/wrappers/base.py
new file mode 100644
index 000000000..abfa559a1
--- /dev/null
+++ b/src/backend/langflow/interface/wrappers/base.py
@@ -0,0 +1,30 @@
+from typing import Dict, List
+
+from langchain import requests
+
+from langflow.interface.base import LangChainTypeCreator
+from langflow.utils.util import build_template_from_class
+
+
+class WrapperCreator(LangChainTypeCreator):
+    type_name: str = "wrappers"
+
+    @property
+    def type_to_loader_dict(self) -> Dict:
+        if self.type_dict is None:
+            self.type_dict = {
+                wrapper.__name__: wrapper for wrapper in [requests.RequestsWrapper]
+            }
+        return self.type_dict
+
+    def get_signature(self, name: str) -> Dict | None:
+        try:
+            return build_template_from_class(name, self.type_to_loader_dict)
+        except ValueError as exc:
+            raise ValueError("Wrapper not found") from exc
+
+    def to_list(self) -> List[str]:
+        return list(self.type_to_loader_dict.keys())
+
+
+wrapper_creator = WrapperCreator()
diff --git a/src/backend/langflow/main.py b/src/backend/langflow/main.py
index a2a02465e..21d17690a 100644
--- a/src/backend/langflow/main.py
+++ b/src/backend/langflow/main.py
@@ -2,8 +2,6 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 
 from langflow.api.endpoints import router as endpoints_router
-from langflow.api.list_endpoints import router as list_router
-from langflow.api.signature import router as signatures_router
 
 
 def create_app():
@@ -23,8 +21,6 @@ def create_app():
     )
 
     app.include_router(endpoints_router)
-    app.include_router(list_router)
-    app.include_router(signatures_router)
     return app
 
 
diff --git a/src/backend/langflow/settings.py b/src/backend/langflow/settings.py
index 6c5c170eb..c0fd66c58 100644
--- a/src/backend/langflow/settings.py
+++ b/src/backend/langflow/settings.py
@@ -1,32 +1,47 @@
 import os
-from typing import List, Optional
+from typing import List
 
 import yaml
-from pydantic import BaseSettings, Field, root_validator
+from pydantic import BaseSettings, root_validator
 
 
 class Settings(BaseSettings):
-    chains: Optional[List[str]] = Field(...)
-    agents: Optional[List[str]] = Field(...)
-    prompts: Optional[List[str]] = Field(...)
-    llms: Optional[List[str]] = Field(...)
-    tools: Optional[List[str]] = Field(...)
-    memories: Optional[List[str]] = Field(...)
-    embeddings: Optional[List[str]] = Field(...)
-    vectorstores: Optional[List[str]] = Field(...)
-    documentloaders: Optional[List[str]] = Field(...)
-    dev: bool = Field(...)
+    chains: List[str] = []
+    agents: List[str] = []
+    prompts: List[str] = []
+    llms: List[str] = []
+    tools: List[str] = []
+    memories: List[str] = []
+    embeddings: List[str] = []
+    vectorstores: List[str] = []
+    documentloaders: List[str] = []
+    wrappers: List[str] = []
+    toolkits: List[str] = []
+    dev: bool = False
 
     class Config:
         validate_assignment = True
+        extra = "ignore"
 
-    @root_validator
+    @root_validator(allow_reuse=True)
     def validate_lists(cls, values):
         for key, value in values.items():
             if key != "dev" and not value:
                 values[key] = []
         return values
 
+    def update_from_yaml(self, file_path: str):
+        new_settings = load_settings_from_yaml(file_path)
+        self.chains = new_settings.chains or []
+        self.agents = new_settings.agents or []
+        self.prompts = new_settings.prompts or []
+        self.llms = new_settings.llms or []
+        self.tools = new_settings.tools or []
+        self.memories = new_settings.memories or []
+        self.wrappers = new_settings.wrappers or []
+        self.toolkits = new_settings.toolkits or []
+        self.dev = new_settings.dev or False
+
 
 def save_settings_to_yaml(settings: Settings, file_path: str):
     with open(file_path, "w") as f:
@@ -44,9 +59,8 @@ def load_settings_from_yaml(file_path: str) -> Settings:
 
     with open(file_path, "r") as f:
         settings_dict = yaml.safe_load(f)
-        a = Settings.parse_obj(settings_dict)
 
-    return a
+    return Settings(**settings_dict)
 
 
 settings = load_settings_from_yaml("config.yaml")
diff --git a/src/backend/langflow/template/base.py b/src/backend/langflow/template/base.py
new file mode 100644
index 000000000..eb7b8898b
--- /dev/null
+++ b/src/backend/langflow/template/base.py
@@ -0,0 +1,159 @@
+from abc import ABC
+from typing import Any, Dict, Optional, Union
+
+from pydantic import BaseModel
+
+from langflow.utils import constants
+
+
+class TemplateFieldCreator(BaseModel, ABC):
+    field_type: str = "str"
+    required: bool = False
+    placeholder: str = ""
+    is_list: bool = False
+    show: bool = True
+    multiline: bool = False
+    value: Any = None
+    suffixes: list[str] = []
+    fileTypes: list[str] = []
+    file_types: list[str] = []
+    content: Union[str, None] = None
+    password: bool = False
+    options: list[str] = []
+    # _name will be used to store the name of the field
+    # in the template
+    name: str = ""
+
+    def to_dict(self):
+        result = self.dict()
+        # Remove key if it is None
+        for key in list(result.keys()):
+            if result[key] is None or result[key] == []:
+                del result[key]
+        result["type"] = result.pop("field_type")
+        result["list"] = result.pop("is_list")
+
+        if result.get("file_types"):
+            result["fileTypes"] = result.pop("file_types")
+
+        if self.field_type == "file":
+            result["content"] = self.content
+        return result
+
+    def process_field(
+        self, key: str, value: Dict[str, Any], name: Optional[str] = None
+    ) -> None:
+        _type = value["type"]
+
+        # Remove 'Optional' wrapper
+        if "Optional" in _type:
+            _type = _type.replace("Optional[", "")[:-1]
+
+        # Check for list type
+        if "List" in _type:
+            _type = _type.replace("List[", "")[:-1]
+            self.is_list = True
+        else:
+            self.is_list = False
+
+        # Replace 'Mapping' with 'dict'
+        if "Mapping" in _type:
+            _type = _type.replace("Mapping", "dict")
+
+        # Change type from str to Tool
+        self.field_type = "Tool" if key in ["allowed_tools"] else _type
+
+        self.field_type = "int" if key in ["max_value_length"] else self.field_type
+
+        # Show or not field
+        self.show = bool(
+            (self.required and key not in ["input_variables"])
+            or key
+            in [
+                "allowed_tools",
+                "memory",
+                "prefix",
+                "examples",
+                "temperature",
+                "model_name",
+                "headers",
+                "max_value_length",
+            ]
+            or "api_key" in key
+        )
+
+        # Add password field
+        self.password = any(
+            text in key.lower() for text in ["password", "token", "api", "key"]
+        )
+
+        # Add multline
+        self.multiline = key in [
+            "suffix",
+            "prefix",
+            "template",
+            "examples",
+            "code",
+            "headers",
+        ]
+
+        # Replace dict type with str
+        if "dict" in self.field_type.lower():
+            self.field_type = "code"
+
+        if key == "dict_":
+            self.field_type = "file"
+            self.suffixes = [".json", ".yaml", ".yml"]
+            self.file_types = ["json", "yaml", "yml"]
+
+        # Replace default value with actual value
+        if "default" in value:
+            self.value = value["default"]
+
+        if key == "headers":
+            self.value = """{'Authorization':
+            'Bearer <token>'}"""
+
+        # Add options to openai
+        if name == "OpenAI" and key == "model_name":
+            self.options = constants.OPENAI_MODELS
+            self.is_list = True
+        elif name == "OpenAIChat" and key == "model_name":
+            self.options = constants.CHAT_OPENAI_MODELS
+            self.is_list = True
+
+
+class TemplateField(TemplateFieldCreator):
+    pass
+
+
+class Template(BaseModel):
+    type_name: str
+    fields: list[TemplateField]
+
+    def process_fields(self, name: Optional[str] = None) -> None:
+        for field in self.fields:
+            signature = field.to_dict()
+            field.process_field(field.name, signature, name)
+
+    def to_dict(self):
+        self.process_fields(self.type_name)
+        result = {field.name: field.to_dict() for field in self.fields}
+        result["_type"] = self.type_name  # type: ignore
+        return result
+
+
+class FrontendNode(BaseModel):
+    template: Template
+    description: str
+    base_classes: list
+    name: str = ""
+
+    def to_dict(self):
+        return {
+            self.name: {
+                "template": self.template.to_dict(),
+                "description": self.description,
+                "base_classes": self.base_classes,
+            }
+        }
diff --git a/src/backend/langflow/template/fields.py b/src/backend/langflow/template/fields.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/backend/langflow/template/nodes.py b/src/backend/langflow/template/nodes.py
index 642d0c237..718d66387 100644
--- a/src/backend/langflow/template/nodes.py
+++ b/src/backend/langflow/template/nodes.py
@@ -1,5 +1,6 @@
-from langflow.template.template import Field, FrontendNode, Template
 from langchain.agents.mrkl import prompt
+
+from langflow.template.base import FrontendNode, Template, TemplateField
 from langflow.utils.constants import DEFAULT_PYTHON_FUNCTION
 
 
@@ -8,7 +9,7 @@ class ZeroShotPromptNode(FrontendNode):
     template: Template = Template(
         type_name="zero_shot",
         fields=[
-            Field(
+            TemplateField(
                 field_type="str",
                 required=False,
                 placeholder="",
@@ -18,7 +19,7 @@ class ZeroShotPromptNode(FrontendNode):
                 value=prompt.PREFIX,
                 name="prefix",
             ),
-            Field(
+            TemplateField(
                 field_type="str",
                 required=True,
                 placeholder="",
@@ -28,7 +29,7 @@ class ZeroShotPromptNode(FrontendNode):
                 value=prompt.SUFFIX,
                 name="suffix",
             ),
-            Field(
+            TemplateField(
                 field_type="str",
                 required=False,
                 placeholder="",
@@ -52,7 +53,7 @@ class PythonFunctionNode(FrontendNode):
     template: Template = Template(
         type_name="python_function",
         fields=[
-            Field(
+            TemplateField(
                 field_type="code",
                 required=True,
                 placeholder="",
@@ -75,7 +76,7 @@ class ToolNode(FrontendNode):
     template: Template = Template(
         type_name="tool",
         fields=[
-            Field(
+            TemplateField(
                 field_type="str",
                 required=True,
                 placeholder="",
@@ -85,7 +86,7 @@ class ToolNode(FrontendNode):
                 value="",
                 name="name",
             ),
-            Field(
+            TemplateField(
                 field_type="str",
                 required=True,
                 placeholder="",
@@ -95,7 +96,7 @@ class ToolNode(FrontendNode):
                 value="",
                 name="description",
             ),
-            Field(
+            TemplateField(
                 field_type="str",
                 required=True,
                 placeholder="",
@@ -112,3 +113,58 @@ class ToolNode(FrontendNode):
 
     def to_dict(self):
         return super().to_dict()
+
+
+class JsonAgentNode(FrontendNode):
+    name: str = "JsonAgent"
+    template: Template = Template(
+        type_name="json_agent",
+        fields=[
+            TemplateField(
+                field_type="BaseToolkit",
+                required=True,
+                show=True,
+                name="toolkit",
+            ),
+            TemplateField(
+                field_type="BaseLanguageModel",
+                required=True,
+                show=True,
+                name="llm",
+            ),
+        ],
+    )
+    description: str = """Construct a json agent from an LLM and tools."""
+    base_classes: list[str] = ["AgentExecutor"]
+
+    def to_dict(self):
+        return super().to_dict()
+
+
+class CSVAgentNode(FrontendNode):
+    name: str = "CSVAgent"
+    template: Template = Template(
+        type_name="csv_agent",
+        fields=[
+            TemplateField(
+                field_type="file",
+                required=True,
+                show=True,
+                name="path",
+                value="",
+                suffixes=[".csv"],
+                fileTypes=["csv"],
+            ),
+            TemplateField(
+                field_type="BaseLanguageModel",
+                required=True,
+                show=True,
+                name="llm",
+            ),
+        ],
+    )
+    description: str = """Construct a json agent from a CSV and tools."""
+    base_classes: list[str] = ["AgentExecutor"]
+
+    def to_dict(self):
+        return super().to_dict()
diff --git a/src/backend/langflow/template/template.py b/src/backend/langflow/template/template.py
deleted file mode 100644
index 21b23486a..000000000
--- a/src/backend/langflow/template/template.py
+++ /dev/null
@@ -1,51 +0,0 @@
-from typing import Any
-from pydantic import BaseModel
-
-
-class Field(BaseModel):
-    field_type: str = "str"
-    required: bool = False
-    placeholder: str = ""
-    is_list: bool = False
-    show: bool = True
-    multiline: bool = False
-    value: Any = None
-    # _name will be used to store the name of the field
-    # in the template
-    name: str = ""
-
-    def to_dict(self):
-        result = self.dict()
-        # Remove key if it is None
-        for key in list(result.keys()):
-            if result[key] is None:
-                del result[key]
-        result["type"] = result.pop("field_type")
-        result["list"] = result.pop("is_list")
-        return result
-
-
-class Template(BaseModel):
-    type_name: str
-    fields: list[Field]
-
-    def to_dict(self):
-        result = {field.name: field.to_dict() for field in self.fields}
-        result["_type"] = self.type_name  # type: ignore
-        return result
-
-
-class FrontendNode(BaseModel):
-    template: Template
-    description: str
-    base_classes: list
-    name: str = ""
-
-    def to_dict(self):
-        return {
-            self.name: {
-                "template": self.template.to_dict(),
-                "description": self.description,
-                "base_classes": self.base_classes,
-            }
-        }
diff --git a/src/backend/langflow/utils/util.py b/src/backend/langflow/utils/util.py
index 3717bcba6..59a19eb33 100644
--- a/src/backend/langflow/utils/util.py
+++ b/src/backend/langflow/utils/util.py
@@ -1,23 +1,54 @@
-import ast
 import importlib
 import inspect
 import re
-from typing import Dict, Optional, Union
-
-from langchain.agents.load_tools import (
-    _BASE_TOOLS,
-    _EXTRA_LLM_TOOLS,
-    _EXTRA_OPTIONAL_TOOLS,
-    _LLM_TOOLS,
-)
-
-
-from langchain.agents.tools import Tool
-
+from typing import Dict, Optional
 
 from langflow.utils import constants
 
 
+def build_template_from_parameters(
+    name: str, type_to_loader_dict: Dict, add_function: bool = False
+):
+    # Retrieve the function that matches the provided name
+    func = None
+    for _, v in type_to_loader_dict.items():
+        if v.__name__ == name:
+            func = v
+            break
+
+    if func is None:
+        raise ValueError(f"{name} not found")
+
+    # Process parameters
+    parameters = func.__annotations__
+    variables = {}
+    for param_name, param_type in parameters.items():
+        if param_name in ["return", "kwargs"]:
+            continue
+
+        variables[param_name] = {
+            "type": param_type.__name__,
+            "default": parameters[param_name].__repr_args__()[0][1],
+            # Op
+            "placeholder": "",
+        }
+
+    # Get the base classes of the return type
+    return_type = parameters.get("return")
+    base_classes = get_base_classes(return_type) if return_type else []
+    if add_function:
+        base_classes.append("function")
+
+    # Get the function's docstring
+    docs = inspect.getdoc(func) or ""
+
+    return {
+        "template": format_dict(variables, name),
+        "description": docs["Description"],  # type: ignore
+        "base_classes": base_classes,
+    }
+
+
 def build_template_from_function(
     name: str, type_to_loader_dict: Dict, add_function: bool = False
 ):
@@ -37,7 +68,7 @@ def build_template_from_function(
 
             variables = {"_type": _type}
             for class_field_items, value in _class.__fields__.items():
-                if class_field_items in ["callback_manager", "requests_wrapper"]:
+                if class_field_items in ["callback_manager"]:
                     continue
                 variables[class_field_items] = {}
                 for name_, value_ in value.__repr_args__():
@@ -67,7 +98,7 @@ def build_template_from_function(
             return {
                 "template": format_dict(variables, name),
                 "description": docs["Description"],
-                "base_classes": get_base_classes(_class),
+                "base_classes": base_classes,
             }
 
 
@@ -128,17 +159,23 @@ def get_base_classes(cls):
     """Get the base classes of a class.
     These are used to determine the output of the nodes.
     """
-    bases = cls.__bases__
-    if not bases:
-        return []
-    else:
+    if bases := cls.__bases__:
         result = []
         for base in bases:
             if any(type in base.__module__ for type in ["pydantic", "abc"]):
                 continue
             result.append(base.__name__)
-            result.extend(get_base_classes(base))
-        return result
+            base_classes = get_base_classes(base)
+            # check if the base_classes are in the result
+            # if not, add them
+            for base_class in base_classes:
+                if base_class not in result:
+                    result.append(base_class)
+    else:
+        result = [cls.__name__]
+    if not result:
+        result = [cls.__name__]
+    return list(set(result + [cls.__name__]))
 
 
 def get_default_factory(module: str, function: str):
@@ -150,118 +187,6 @@ def get_default_factory(module: str, function: str):
     return None
 
 
-def get_tools_dict():
-    """Get the tools dictionary."""
-    from langflow.interface.listing import CUSTOM_TOOLS
-
-    tools = {
-        **_BASE_TOOLS,
-        **_LLM_TOOLS,
-        **{k: v[0] for k, v in _EXTRA_LLM_TOOLS.items()},
-        **{k: v[0] for k, v in _EXTRA_OPTIONAL_TOOLS.items()},
-        **CUSTOM_TOOLS,
-    }
-    return tools
-
-
-def get_tool_by_name(name: str):
-    """Get a tool from the tools dictionary."""
-    tools = get_tools_dict()
-    if name not in tools:
-        raise ValueError(f"{name} not found.")
-    return tools[name]
-
-
-def get_tool_params(tool, **kwargs) -> Union[Dict, None]:
-    # Parse the function code into an abstract syntax tree
-    # Define if it is a function or a class
-    if inspect.isfunction(tool):
-        return get_func_tool_params(tool, **kwargs)
-    elif inspect.isclass(tool):
-        # Get the parameters necessary to
-        # instantiate the class
-        return get_class_tool_params(tool, **kwargs)
-    else:
-        raise ValueError("Tool must be a function or class.")
-
-
-def get_func_tool_params(func, **kwargs) -> Union[Dict, None]:
-    tree = ast.parse(inspect.getsource(func))
-
-    # Iterate over the statements in the abstract syntax tree
-    for node in ast.walk(tree):
-        # Find the first return statement
-        if isinstance(node, ast.Return):
-            tool = node.value
-            if isinstance(tool, ast.Call):
-                if isinstance(tool.func, ast.Name) and tool.func.id == "Tool":
-                    if tool.keywords:
-                        tool_params = {}
-                        for keyword in tool.keywords:
-                            if keyword.arg == "name":
-                                tool_params["name"] = ast.literal_eval(keyword.value)
-                            elif keyword.arg == "description":
-                                tool_params["description"] = ast.literal_eval(
-                                    keyword.value
-                                )
-
-                        return tool_params
-                    return {
-                        "name": ast.literal_eval(tool.args[0]),
-                        "description": ast.literal_eval(tool.args[2]),
-                    }
-                #
-                else:
-                    # get the class object from the return statement
-                    try:
-                        class_obj = eval(
-                            compile(ast.Expression(tool), "<string>", "eval")
-                        )
-                    except Exception:
-                        return None
-
-                    return {
-                        "name": getattr(class_obj, "name"),
-                        "description": getattr(class_obj, "description"),
-                    }
-        # Return None if no return statement was found
-    return None
-
-
-def get_class_tool_params(cls, **kwargs) -> Union[Dict, None]:
-    tree = ast.parse(inspect.getsource(cls))
-
-    tool_params = {}
-
-    # Iterate over the statements in the abstract syntax tree
-    for node in ast.walk(tree):
-        if isinstance(node, ast.ClassDef):
-            # Find the class definition and look for methods
-            for stmt in node.body:
-                if isinstance(stmt, ast.FunctionDef) and stmt.name == "__init__":
-                    # There is no assignment statements in the __init__ method
-                    # So we need to get the params from the function definition
-                    for arg in stmt.args.args:
-                        if arg.arg == "name":
-                            # It should be the name of the class
-                            tool_params[arg.arg] = cls.__name__
-                        elif arg.arg == "self":
-                            continue
-                        # If there is not default value, set it to an empty string
-                        else:
-                            try:
-                                annotation = ast.literal_eval(arg.annotation)  # type: ignore
-                                tool_params[arg.arg] = annotation
-                            except ValueError:
-                                tool_params[arg.arg] = ""
-                # Get the attribute name and the annotation
-                elif cls != Tool and isinstance(stmt, ast.AnnAssign):
-                    # Get the attribute name and the annotation
-                    tool_params[stmt.target.id] = ""  # type: ignore
-
-    return tool_params
-
-
 def get_class_doc(class_name):
     """
     Extracts information from the docstring of a given class.
@@ -354,6 +279,8 @@ def format_dict(d, name: Optional[str] = None):
         # Change type from str to Tool
         value["type"] = "Tool" if key in ["allowed_tools"] else _type
 
+        value["type"] = "int" if key in ["max_value_length"] else value["type"]
+
         # Show or not field
         value["show"] = bool(
             (value["required"] and key not in ["input_variables"])
@@ -365,6 +292,8 @@ def format_dict(d, name: Optional[str] = None):
                 "examples",
                 "temperature",
                 "model_name",
+                "headers",
+                "max_value_length",
             ]
             or "api_key" in key
         )
@@ -375,18 +304,41 @@ def format_dict(d, name: Optional[str] = None):
         )
 
         # Add multline
-        value["multiline"] = key in ["suffix", "prefix", "template", "examples", "code"]
+        value["multiline"] = key in [
+            "suffix",
+            "prefix",
+            "template",
+            "examples",
+            "code",
+            "headers",
+        ]
+
+        # Replace dict type with str
+        if "dict" in value["type"].lower():
+            value["type"] = "code"
+
+        if key == "dict_":
+            value["type"] = "file"
+            value["suffixes"] = [".json", ".yaml", ".yml"]
+            value["fileTypes"] = ["json", "yaml", "yml"]
 
         # Replace default value with actual value
         if "default" in value:
             value["value"] = value["default"]
             value.pop("default")
 
+        if key == "headers":
+            value[
+                "value"
+            ] = """{'Authorization':
+            'Bearer <token>'}"""
         # Add options to openai
         if name == "OpenAI" and key == "model_name":
             value["options"] = constants.OPENAI_MODELS
+            value["list"] = True
         elif name == "OpenAIChat" and key == "model_name":
             value["options"] = constants.CHAT_OPENAI_MODELS
+            value["list"] = True
 
     return d
 
diff --git a/src/frontend/public/favicon.ico b/src/frontend/public/favicon.ico
new file mode 100644
index 000000000..0612ba9b3
Binary files /dev/null and b/src/frontend/public/favicon.ico differ
diff --git a/src/frontend/public/index.html b/src/frontend/public/index.html
index 57757fb21..b2e9c4b82 100644
--- a/src/frontend/public/index.html
+++ b/src/frontend/public/index.html
@@ -4,7 +4,8 @@
     <meta charset="UTF-8">
     <meta http-equiv="X-UA-Compatible" content="IE=edge">
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>LangFLow</title>
+    <link rel="icon" href="%PUBLIC_URL%/favicon.ico" />
+    <title>LangFlow</title>
 </head>
 <body id='body' style="width: 100%; height:100%">
     <noscript>You need to enable JavaScript to run this app.</noscript>
diff --git a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx
index c4b4346fa..d2d561ae3 100644
--- a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx
+++ b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx
@@ -11,6 +11,9 @@ import { ParameterComponentType } from "../../../../types/components";
 import FloatComponent from "../../../../components/floatComponent";
 import Dropdown from "../../../../components/dropdownComponent";
 import CodeAreaComponent from "../../../../components/codeAreaComponent";
+import InputFileComponent from "../../../../components/inputFileComponent";
+import { TabsContext } from "../../../../contexts/tabsContext";
+import IntComponent from "../../../../components/intComponent";
 
 export default function ParameterComponent({
 	left,
@@ -43,6 +46,7 @@ export default function ParameterComponent({
 	const { reactFlowInstance } = useContext(typesContext);
 	let disabled =
 		reactFlowInstance?.getEdges().some((e) => e.targetHandle === id) ?? false;
+	const { save } = useContext(TabsContext);
 
 	return (
 		<div
@@ -50,11 +54,17 @@ export default function ParameterComponent({
 			className="w-full flex flex-wrap justify-between items-center bg-gray-50 dark:bg-gray-800 dark:text-white mt-1 px-5 py-2"
 		>
 			<>
-				<div className="text-sm truncate">
+				<div className={"text-sm truncate w-full " + (left ? "" : "text-end")}>
 					{title}
 					<span className="text-red-600">{required ? " *" : ""}</span>
 				</div>
-				{left && (type === "str" || type === "bool" || type === "float"||type=="code") ? (
+				{left &&
+				(type === "str" ||
+					type === "bool" ||
+					type === "float" ||
+					type === "code" ||
+					type === "file" ||
+					type === "int") ? (
 					<></>
 				) : (
 					<Tooltip title={tooltipTitle + (required ? " (required)" : "")}>
@@ -92,6 +102,7 @@ export default function ParameterComponent({
 								}
 								onChange={(t: string[]) => {
 									data.node.template[name].value = t;
+									save();
 								}}
 							/>
 						) : data.node.template[name].multiline ? (
@@ -100,15 +111,17 @@ export default function ParameterComponent({
 								value={data.node.template[name].value ?? ""}
 								onChange={(t: string) => {
 									data.node.template[name].value = t;
+									save();
 								}}
 							/>
 						) : (
 							<InputComponent
 								disabled={disabled}
-								password={data.node.template[name].password ?? true}
+								password={data.node.template[name].password ?? false}
 								value={data.node.template[name].value ?? ""}
 								onChange={(t) => {
 									data.node.template[name].value = t;
+									save();
 								}}
 							/>
 						)}
@@ -121,6 +134,7 @@ export default function ParameterComponent({
 							setEnabled={(t) => {
 								data.node.template[name].value = t;
 								setEnabled(t);
+								save();
 							}}
 						/>
 					</div>
@@ -130,6 +144,7 @@ export default function ParameterComponent({
 						value={data.node.template[name].value ?? ""}
 						onChange={(t) => {
 							data.node.template[name].value = t;
+							save();
 						}}
 					/>
 				) : left === true &&
@@ -146,6 +161,30 @@ export default function ParameterComponent({
 						value={data.node.template[name].value ?? ""}
 						onChange={(t: string) => {
 							data.node.template[name].value = t;
+							save();
+						}}
+					/>
+				) : left === true && type === "file" ? (
+					<InputFileComponent
+						disabled={disabled}
+						value={data.node.template[name].value ?? ""}
+						onChange={(t: string) => {
+							data.node.template[name].value = t;
+						}}
+						fileTypes={data.node.template[name].fileTypes}
+						suffixes={data.node.template[name].suffixes}
+						onFileChange={(t: string) => {
+							data.node.template[name].content = t;
+							save();
+						}}
+					></InputFileComponent>
+				) : left === true && type === "int" ? (
+					<IntComponent
+						disabled={disabled}
+						value={data.node.template[name].value ?? ""}
+						onChange={(t) => {
+							data.node.template[name].value = t;
+							save();
 						}}
 					/>
 				) : (
diff --git a/src/frontend/src/CustomNodes/GenericNode/index.tsx b/src/frontend/src/CustomNodes/GenericNode/index.tsx
index 6e3aa6e67..0f9feeb7e 100644
--- a/src/frontend/src/CustomNodes/GenericNode/index.tsx
+++ b/src/frontend/src/CustomNodes/GenericNode/index.tsx
@@ -71,7 +71,7 @@ export default function GenericNode({
 							<div key={idx}>
 								{idx === 0 ? (
 									<div className="px-5 py-2 mt-2 dark:text-white text-center">
-										Inputs:
+										Inputs
 									</div>
 								) : (
 									<></>
@@ -101,7 +101,7 @@ export default function GenericNode({
 							</div>
 						))}
 					<div className="px-5 py-2 mt-2 dark:text-white text-center">
-						Output:
+						Output
 					</div>
 					<ParameterComponent
 						data={data}
@@ -109,7 +109,7 @@ export default function GenericNode({
 						title={data.type}
 						tooltipTitle={`Type: ${data.node.base_classes.join(" | ")}`}
 						id={[data.type, data.id, ...data.node.base_classes].join("|")}
-						type={"str"}
+						type={data.node.base_classes.join("|")}
 						left={false}
 					/>
 				</>
diff --git a/src/frontend/src/components/chatComponent/index.tsx b/src/frontend/src/components/chatComponent/index.tsx
index b285186f3..561282291 100644
--- a/src/frontend/src/components/chatComponent/index.tsx
+++ b/src/frontend/src/components/chatComponent/index.tsx
@@ -103,7 +103,7 @@ export default function Chat({ flow, reactFlowInstance }: ChatType) {
 						setLockChat(false);
 					})
 					.catch((error) => {
-						setErrorData({ title: error.message ?? "unknow error" });
+						setErrorData({ title: error.message ?? "Unknown Error", list: [error.response.data.detail]});
 						setLockChat(false);
 					});
 			} else {
diff --git a/src/frontend/src/components/codeAreaComponent/index.tsx b/src/frontend/src/components/codeAreaComponent/index.tsx
index 95aa720b0..756296970 100644
--- a/src/frontend/src/components/codeAreaComponent/index.tsx
+++ b/src/frontend/src/components/codeAreaComponent/index.tsx
@@ -23,7 +23,7 @@ export default function CodeAreaComponent({
 			<div className="w-full flex items-center gap-3">
 				<span
 					className={
-						"truncate block max-w-full text-gray-500 px-3 py-2 rounded-md border border-gray-300 dark:border-gray-700 shadow-sm focus:border-indigo-500 focus:ring-indigo-500 sm:text-sm" +
+						"truncate block w-full text-gray-500 px-3 py-2 rounded-md border border-gray-300 dark:border-gray-700 shadow-sm focus:border-indigo-500 focus:ring-indigo-500 sm:text-sm" +
 						(disabled ? " bg-gray-200" : "")
 					}
 				>
diff --git a/src/frontend/src/components/inputFileComponent/index.tsx b/src/frontend/src/components/inputFileComponent/index.tsx
new file mode 100644
index 000000000..36d13e918
--- /dev/null
+++ b/src/frontend/src/components/inputFileComponent/index.tsx
@@ -0,0 +1,85 @@
+import { DocumentMagnifyingGlassIcon } from "@heroicons/react/24/outline";
+import { useContext, useEffect, useState } from "react";
+import { alertContext } from "../../contexts/alertContext";
+import { FileComponentType } from "../../types/components";
+
+export default function InputFileComponent({
+	value,
+	onChange,
+	disabled,
+	suffixes,
+	fileTypes,
+	onFileChange
+}: FileComponentType) {
+	const [myValue, setMyValue] = useState(value);
+	const { setErrorData } = useContext(alertContext);
+	useEffect(() => {
+		if (disabled) {
+			setMyValue("");
+			onChange("");
+			onFileChange("")
+		}
+	}, [disabled, onChange]);
+
+	function attachFile(fileReadEvent: ProgressEvent<FileReader>) {
+		fileReadEvent.preventDefault();
+		const file = fileReadEvent.target.result;
+		onFileChange(file as string)
+	}
+
+	function checkFileType(fileName:string):boolean{
+		for (let index = 0; index < suffixes.length; index++) {
+			if(fileName.endsWith(suffixes[index])){
+				return true
+			}
+		}
+		return false
+	}
+
+	const handleButtonClick = () => {
+		const input = document.createElement("input");
+		input.type = "file";
+		input.accept = suffixes.join(",");
+		input.style.display = "none";
+		input.multiple = false;
+		input.onchange = (e: Event) => {
+			const file = (e.target as HTMLInputElement).files?.[0];
+			const fileData = new FileReader();
+			fileData.onload = attachFile;
+			if (file && checkFileType(file.name)) {
+				fileData.readAsDataURL(file);
+				setMyValue(file.name);
+				onChange(file.name);
+			} else {
+				setErrorData({
+					title:
+						"Please select a valid file. Only files this files are allowed:",
+					list: fileTypes,
+				});
+			}
+		};
+		input.click();
+	};
+
+	return (
+		<div
+			className={
+				disabled ? "pointer-events-none cursor-not-allowed w-full" : "w-full"
+			}
+		>
+			<div className="w-full flex items-center gap-3">
+				<span
+					className={
+						"truncate block w-full text-gray-500 px-3 py-2 rounded-md border border-gray-300 dark:border-gray-700 shadow-sm focus:border-indigo-500 focus:ring-indigo-500 sm:text-sm" +
+						(disabled ? " bg-gray-200" : "")
+					}
+				>
+					{myValue !== "" ? myValue : "No file"}
+				</span>
+				<button onClick={handleButtonClick}>
+					<DocumentMagnifyingGlassIcon className="w-8 h-8  hover:text-blue-600" />
+				</button>
+			</div>
+		</div>
+	);
+}
diff --git a/src/frontend/src/components/intComponent/index.tsx b/src/frontend/src/components/intComponent/index.tsx
new file mode 100644
index 000000000..520a78c0d
--- /dev/null
+++ b/src/frontend/src/components/intComponent/index.tsx
@@ -0,0 +1,38 @@
+import { useEffect, useState } from "react";
+import { FloatComponentType } from "../../types/components";
+
+export default function IntComponent({
+	value,
+	onChange,
+	disabled,
+}: FloatComponentType) {
+	const [myValue, setMyValue] = useState(value ?? "");
+	useEffect(() => {
+		if (disabled) {
+			setMyValue("");
+			onChange("");
+		}
+	}, [disabled, onChange]);
+	return (
+		<div className={disabled ? "pointer-events-none cursor-not-allowed w-full" : "w-full"}>
+			<input
+				onKeyDown={(event) => {
+                    if (event.key !== 'Backspace' && event.key !== 'Enter' && event.key !== 'Delete' && event.key !== 'ArrowLeft' && event.key !== 'ArrowRight' && !/^[-]?\d*$/.test(event.key)) {
+                        event.preventDefault();
+                    }
+				}}
+				type="number"
+				value={myValue}
+				className={
+					"block w-full form-input dark:bg-gray-900 arrow-hide dark:border-gray-600 rounded-md border-gray-300 shadow-sm focus:border-indigo-500 focus:ring-indigo-500 sm:text-sm" +
+					(disabled ? " bg-gray-200 dark:bg-gray-700" : "")
+				}
+				placeholder="Type a integer number"
+				onChange={(e) => {
+					setMyValue(e.target.value);
+					onChange(e.target.value);
+				}}
+			/>
+		</div>
+	);
+}
diff --git a/src/frontend/src/contexts/tabsContext.tsx b/src/frontend/src/contexts/tabsContext.tsx
index 10c0b943e..a11f0339d 100644
--- a/src/frontend/src/contexts/tabsContext.tsx
+++ b/src/frontend/src/contexts/tabsContext.tsx
@@ -5,6 +5,7 @@ import { normalCaseToSnakeCase } from "../utils";
 import { alertContext } from "./alertContext";
 
 const TabsContextInitialValue: TabsContextType = {
+	save:()=>{},
 	tabIndex: 0,
 	setTabIndex: (index: number) => {},
 	flows: [],
@@ -16,7 +17,7 @@ const TabsContextInitialValue: TabsContextType = {
 	uploadFlow: () => {},
 	lockChat: false,
 	setLockChat:(prevState:boolean)=>{},
-	hardReset:()=>{}
+	hardReset:()=>{},
 };
 
 export const TabsContext = createContext<TabsContextType>(
@@ -35,15 +36,20 @@ export function TabsProvider({ children }: { children: ReactNode }) {
 		newNodeId.current = newNodeId.current + 1;
 		return newNodeId.current;
 	}
+	function save(){
+		if (flows.length !== 0)
+		window.localStorage.setItem(
+			"tabsData",
+			JSON.stringify({ tabIndex, flows, id, nodeId: newNodeId.current })
+		);
+	}
 	useEffect(() => {
 		//save tabs locally
-		if (flows.length !== 0)
-			window.localStorage.setItem(
-				"tabsData",
-				JSON.stringify({ tabIndex, flows, id, nodeId: newNodeId.current })
-			);
+		save()
 	}, [flows, id, tabIndex, newNodeId]);
 
+
+
 	useEffect(() => {
 		//get tabs locally saved
 		let cookie = window.localStorage.getItem("tabsData");
@@ -177,6 +183,7 @@ export function TabsProvider({ children }: { children: ReactNode }) {
 	return (
 		<TabsContext.Provider
 			value={{
+				save,
 				hardReset,
 				lockChat,
 				setLockChat,
diff --git a/src/frontend/src/types/components/index.ts b/src/frontend/src/types/components/index.ts
index 3f7fbf551..9ba96d8c0 100644
--- a/src/frontend/src/types/components/index.ts
+++ b/src/frontend/src/types/components/index.ts
@@ -39,6 +39,15 @@ export type TextAreaComponentType = {
 	value: string;
 };
 
+export type FileComponentType = {
+	disabled: boolean;
+	onChange: (value: string[] | string) => void;
+	value: string;
+	suffixes:Array<string>;
+	fileTypes:Array<string>;
+	onFileChange:(value: string) => void;
+};
+
 export type DisclosureComponentType = {
 	children: ReactNode;
 	button: {
diff --git a/src/frontend/src/types/tabs/index.ts b/src/frontend/src/types/tabs/index.ts
index e872a3f58..625073fb3 100644
--- a/src/frontend/src/types/tabs/index.ts
+++ b/src/frontend/src/types/tabs/index.ts
@@ -1,6 +1,7 @@
 import { FlowType } from "../flow";
 
 export type TabsContextType = {
+	save:()=>void;
 	tabIndex: number;
 	setTabIndex: (index: number) => void;
 	flows: Array<FlowType>;
diff --git a/src/frontend/src/utils.ts b/src/frontend/src/utils.ts
index 796cd6de4..dc59c6640 100644
--- a/src/frontend/src/utils.ts
+++ b/src/frontend/src/utils.ts
@@ -5,8 +5,10 @@ import {
   LightBulbIcon,
   CommandLineIcon,
   WrenchScrewdriverIcon,
+  WrenchIcon,
   ComputerDesktopIcon,
   Bars3CenterLeftIcon,
+  GiftIcon,
   PaperClipIcon,
   QuestionMarkCircleIcon,
 } from "@heroicons/react/24/outline";
@@ -88,6 +90,8 @@ export const nodeNames:{[char: string]: string} = {
   advanced: "Advanced",
   chat: "Chat",
   docloaders:"Document Loader",
+  toolkits:"Toolkits",
+  wrappers:"Wrappers",
   unknown:"Unknown"
 };
 
@@ -97,10 +101,12 @@ export const nodeIcons:{[char: string]: React.ForwardRefExoticComponent<React.SV
   memories: CpuChipIcon,
   llms: LightBulbIcon,
   prompts: CommandLineIcon,
-  tools: WrenchScrewdriverIcon,
+  tools: WrenchIcon,
   advanced: ComputerDesktopIcon,
   chat: Bars3CenterLeftIcon,
   docloaders:Bars3CenterLeftIcon,
+  toolkits:WrenchScrewdriverIcon,
+  wrappers:GiftIcon,
   unknown:QuestionMarkCircleIcon
 };
 
diff --git a/tests/conftest.py b/tests/conftest.py
index 5fe1de280..e6eb3562f 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+
 import pytest
 from fastapi.testclient import TestClient
 
@@ -10,6 +11,9 @@ def pytest_configure():
     pytest.COMPLEX_EXAMPLE_PATH = (
         Path(__file__).parent.absolute() / "data" / "complex_example.json"
     )
+    pytest.OPENAPI_EXAMPLE_PATH = (
+        Path(__file__).parent.absolute() / "data" / "Openapi.json"
+    )
 
     pytest.CODE_WITH_SYNTAX_ERROR = """
 def get_text():
diff --git a/tests/data/Openapi.json b/tests/data/Openapi.json
new file mode 100644
index 000000000..d51404bbb
--- /dev/null
+++ b/tests/data/Openapi.json
@@ -0,0 +1,445 @@
+{
+    "description": "",
+    "name": "openapi",
+    "id": "1",
+    "data": {
+        "nodes": [
+            {
+                "width": 384,
+                "height": 311,
+                "id": "dndnode_19",
+                "type": "genericNode",
+                "position": {
+                    "x": -207.85635949789724,
+                    "y": -105.73915116823618
+                },
+                "data": {
+                    "type": "JsonToolkit",
+                    "node": {
+                        "template": {
+                            "spec": {
+                                "required": true,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "password": false,
+                                "name": "spec",
+                                "type": "JsonSpec",
+                                "list": false
+                            },
+                            "_type": "JsonToolkit"
+                        },
+                        "description": "Toolkit for interacting with a JSON spec.",
+                        "base_classes": [
+                            "BaseToolkit"
+                        ]
+                    },
+                    "id": "dndnode_19",
+                    "value": null
+                },
+                "selected": false,
+                "positionAbsolute": {
+                    "x": -207.85635949789724,
+                    "y": -105.73915116823618
+                },
+                "dragging": false
+            },
+            {
+                "width": 384,
+                "height": 351,
+                "id": "dndnode_32",
+                "type": "genericNode",
+                "position": {
+                    "x": 745.308873444751,
+                    "y": -37.007911201107675
+                },
+                "data": {
+                    "type": "OpenAPIToolkit",
+                    "node": {
+                        "template": {
+                            "json_agent": {
+                                "required": true,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "password": false,
+                                "name": "json_agent",
+                                "type": "AgentExecutor",
+                                "list": false
+                            },
+                            "requests_wrapper": {
+                                "required": true,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "password": false,
+                                "name": "requests_wrapper",
+                                "type": "RequestsWrapper",
+                                "list": false
+                            },
+                            "_type": "OpenAPIToolkit"
+                        },
+                        "description": "Toolkit for interacting with a OpenAPI api.",
+                        "base_classes": [
+                            "BaseToolkit"
+                        ]
+                    },
+                    "id": "dndnode_32",
+                    "value": null
+                },
+                "selected": false,
+                "positionAbsolute": {
+                    "x": 745.308873444751,
+                    "y": -37.007911201107675
+                },
+                "dragging": false
+            },
+            {
+                "width": 384,
+                "height": 351,
+                "id": "dndnode_33",
+                "type": "genericNode",
+                "position": {
+                    "x": 281.30887344475104,
+                    "y": 2.9920887988923255
+                },
+                "data": {
+                    "type": "JsonAgent",
+                    "node": {
+                        "template": {
+                            "toolkit": {
+                                "required": true,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "password": false,
+                                "name": "toolkit",
+                                "type": "BaseToolkit",
+                                "list": false
+                            },
+                            "llm": {
+                                "required": true,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "password": false,
+                                "name": "llm",
+                                "type": "BaseLanguageModel",
+                                "list": false
+                            },
+                            "_type": "JsonAgent"
+                        },
+                        "description": "Construct a json agent from an LLM and tools.",
+                        "base_classes": [
+                            "AgentExecutor"
+                        ]
+                    },
+                    "id": "dndnode_33",
+                    "value": null
+                },
+                "selected": false,
+                "dragging": false,
+                "positionAbsolute": {
+                    "x": 281.30887344475104,
+                    "y": 2.9920887988923255
+                }
+            },
+            {
+                "width": 384,
+                "height": 349,
+                "id": "dndnode_34",
+                "type": "genericNode",
+                "position": {
+                    "x": 301.30887344475104,
+                    "y": 532.9920887988924
+                },
+                "data": {
+                    "type": "RequestsWrapper",
+                    "node": {
+                        "template": {
+                            "headers": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": true,
+                                "value": "{'Authorization':\n            'Bearer <token>'}",
+                                "password": false,
+                                "name": "headers",
+                                "type": "code",
+                                "list": false
+                            },
+                            "aiosession": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "password": false,
+                                "name": "aiosession",
+                                "type": "ClientSession",
+                                "list": false
+                            },
+                            "_type": "RequestsWrapper"
+                        },
+                        "description": "Lightweight wrapper around requests library.",
+                        "base_classes": [
+                            "RequestsWrapper"
+                        ]
+                    },
+                    "id": "dndnode_34",
+                    "value": null
+                },
+                "positionAbsolute": {
+                    "x": 301.30887344475104,
+                    "y": 532.9920887988924
+                }
+            },
+            {
+                "width": 384,
+                "height": 407,
+                "id": "dndnode_35",
+                "type": "genericNode",
+                "position": {
+                    "x": -754.691126555249,
+                    "y": -37.00791120110762
+                },
+                "data": {
+                    "type": "JsonSpec",
+                    "node": {
+                        "template": {
+                            "dict_": {
+                                "required": true,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "value": "api-with-examples.yaml",
+                                "suffixes": [
+                                    ".json",
+                                    ".yaml",
+                                    ".yml"
+                                ],
+                                "password": false,
+                                "name": "dict_",
+                                "type": "file",
+                                "list": false,
+                                "fileTypes": [
+                                    "json",
+                                    "yaml",
+                                    "yml"
+                                ],
+                                "content": "data:application/x-yaml;base64,openapi: "3.0.0"
info:
  title: Simple API overview
  version: 2.0.0
paths:
  /:
    get:
      operationId: listVersionsv2
      summary: List API versions
      responses:
        '200':
          description: |-
            200 response
          content:
            application/json:
              examples: 
                foo:
                  value:
                    {
                      "versions": [
                        {
                            "status": "CURRENT",
                            "updated": "2011-01-21T11:33:21Z",
                            "id": "v2.0",
                            "links": [
                                {
                                    "href": "http://127.0.0.1:8774/v2/",
                                    "rel": "self"
                                }
                            ]
                        },
                        {
                            "status": "EXPERIMENTAL",
                            "updated": "2013-07-23T11:33:21Z",
                            "id": "v3.0",
                            "links": [
                                {
                                    "href": "http://127.0.0.1:8774/v3/",
                                    "rel": "self"
                                }
                            ]
                        }
                      ]
                    }
        '300':
          description: |-
            300 response
          content:
            application/json: 
              examples: 
                foo:
                  value: |
                   {
                    "versions": [
                          {
                            "status": "CURRENT",
                            "updated": "2011-01-21T11:33:21Z",
                            "id": "v2.0",
                            "links": [
                                {
                                    "href": "http://127.0.0.1:8774/v2/",
                                    "rel": "self"
                                }
                            ]
                        },
                        {
                            "status": "EXPERIMENTAL",
                            "updated": "2013-07-23T11:33:21Z",
                            "id": "v3.0",
                            "links": [
                                {
                                    "href": "http://127.0.0.1:8774/v3/",
                                    "rel": "self"
                                }
                            ]
                        }
                    ]
                   }
  /v2:
    get:
      operationId: getVersionDetailsv2
      summary: Show API version details
      responses:
        '200':
          description: |-
            200 response
          content:
            application/json: 
              examples:
                foo:
                  value:
                    {
                      "version": {
                        "status": "CURRENT",
                        "updated": "2011-01-21T11:33:21Z",
                        "media-types": [
                          {
                              "base": "application/xml",
                              "type": "application/vnd.openstack.compute+xml;version=2"
                          },
                          {
                              "base": "application/json",
                              "type": "application/vnd.openstack.compute+json;version=2"
                          }
                        ],
                        "id": "v2.0",
                        "links": [
                          {
                              "href": "http://127.0.0.1:8774/v2/",
                              "rel": "self"
                          },
                          {
                              "href": "http://docs.openstack.org/api/openstack-compute/2/os-compute-devguide-2.pdf",
                              "type": "application/pdf",
                              "rel": "describedby"
                          },
                          {
                              "href": "http://docs.openstack.org/api/openstack-compute/2/wadl/os-compute-2.wadl",
                              "type": "application/vnd.sun.wadl+xml",
                              "rel": "describedby"
                          },
                          {
                            "href": "http://docs.openstack.org/api/openstack-compute/2/wadl/os-compute-2.wadl",
                            "type": "application/vnd.sun.wadl+xml",
                            "rel": "describedby"
                          }
                        ]
                      }
                    }
        '203':
          description: |-
            203 response
          content:
            application/json: 
              examples:
                foo:
                  value:
                    {
                      "version": {
                        "status": "CURRENT",
                        "updated": "2011-01-21T11:33:21Z",
                        "media-types": [
                          {
                              "base": "application/xml",
                              "type": "application/vnd.openstack.compute+xml;version=2"
                          },
                          {
                              "base": "application/json",
                              "type": "application/vnd.openstack.compute+json;version=2"
                          }
                        ],
                        "id": "v2.0",
                        "links": [
                          {
                              "href": "http://23.253.228.211:8774/v2/",
                              "rel": "self"
                          },
                          {
                              "href": "http://docs.openstack.org/api/openstack-compute/2/os-compute-devguide-2.pdf",
                              "type": "application/pdf",
                              "rel": "describedby"
                          },
                          {
                              "href": "http://docs.openstack.org/api/openstack-compute/2/wadl/os-compute-2.wadl",
                              "type": "application/vnd.sun.wadl+xml",
                              "rel": "describedby"
                          }
                        ]
                      }
                    }
"
+                            },
+                            "max_value_length": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "value": "4000",
+                                "password": false,
+                                "name": "max_value_length",
+                                "type": "int",
+                                "list": false
+                            },
+                            "_type": "JsonSpec"
+                        },
+                        "description": "",
+                        "base_classes": [
+                            "Tool",
+                            "JsonSpec"
+                        ]
+                    },
+                    "id": "dndnode_35",
+                    "value": null
+                },
+                "selected": false,
+                "dragging": false,
+                "positionAbsolute": {
+                    "x": -754.691126555249,
+                    "y": -37.00791120110762
+                }
+            },
+            {
+                "width": 384,
+                "height": 563,
+                "id": "dndnode_36",
+                "type": "genericNode",
+                "position": {
+                    "x": -310.69112655524896,
+                    "y": 514.9920887988924
+                },
+                "data": {
+                    "type": "OpenAIChat",
+                    "node": {
+                        "template": {
+                            "cache": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "password": false,
+                                "name": "cache",
+                                "type": "bool",
+                                "list": false
+                            },
+                            "verbose": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "value": false,
+                                "password": false,
+                                "name": "verbose",
+                                "type": "bool",
+                                "list": false
+                            },
+                            "client": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "password": false,
+                                "name": "client",
+                                "type": "Any",
+                                "list": false
+                            },
+                            "model_name": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "value": "gpt-3.5-turbo",
+                                "password": false,
+                                "name": "model_name",
+                                "type": "str",
+                                "list": false
+                            },
+                            "model_kwargs": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "password": false,
+                                "name": "model_kwargs",
+                                "type": "code",
+                                "list": false
+                            },
+                            "openai_api_key": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": true,
+                                "multiline": false,
+                                "password": false,
+                                "name": "openai_api_key",
+                                "type": "str",
+                                "list": false,
+                                "value": "sk-"
+                            },
+                            "max_retries": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "value": 6,
+                                "password": false,
+                                "name": "max_retries",
+                                "type": "int",
+                                "list": false
+                            },
+                            "prefix_messages": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "password": false,
+                                "name": "prefix_messages",
+                                "type": "Any",
+                                "list": true
+                            },
+                            "streaming": {
+                                "required": false,
+                                "placeholder": "",
+                                "show": false,
+                                "multiline": false,
+                                "value": false,
+                                "password": false,
+                                "name": "streaming",
+                                "type": "bool",
+                                "list": false
+                            },
+                            "_type": "OpenAIChat"
+                        },
+                        "description": "Wrapper around OpenAI Chat large language models.To use, you should have the ``openai`` python package installed, and theenvironment variable ``OPENAI_API_KEY`` set with your API key.Any parameters that are valid to be passed to the openai.create call can be passedin, even if not explicitly saved on this class.",
+                        "base_classes": [
+                            "BaseLanguageModel",
+                            "BaseLLM"
+                        ]
+                    },
+                    "id": "dndnode_36",
+                    "value": null
+                },
+                "selected": false,
+                "dragging": false,
+                "positionAbsolute": {
+                    "x": -310.69112655524896,
+                    "y": 514.9920887988924
+                }
+            }
+        ],
+        "edges": [
+            {
+                "source": "dndnode_19",
+                "sourceHandle": "JsonToolkit|dndnode_19|BaseToolkit",
+                "target": "dndnode_33",
+                "targetHandle": "BaseToolkit|toolkit|dndnode_33",
+                "className": "animate-pulse",
+                "id": "reactflow__edge-dndnode_19JsonToolkit|dndnode_19|BaseToolkit-dndnode_33BaseToolkit|toolkit|dndnode_33",
+                "selected": false
+            },
+            {
+                "source": "dndnode_33",
+                "sourceHandle": "JsonAgent|dndnode_33|AgentExecutor",
+                "target": "dndnode_32",
+                "targetHandle": "AgentExecutor|json_agent|dndnode_32",
+                "className": "animate-pulse",
+                "id": "reactflow__edge-dndnode_33JsonAgent|dndnode_33|AgentExecutor-dndnode_32AgentExecutor|json_agent|dndnode_32",
+                "selected": false
+            },
+            {
+                "source": "dndnode_34",
+                "sourceHandle": "RequestsWrapper|dndnode_34|RequestsWrapper",
+                "target": "dndnode_32",
+                "targetHandle": "RequestsWrapper|requests_wrapper|dndnode_32",
+                "className": "animate-pulse",
+                "id": "reactflow__edge-dndnode_34RequestsWrapper|dndnode_34|RequestsWrapper-dndnode_32RequestsWrapper|requests_wrapper|dndnode_32",
+                "selected": false
+            },
+            {
+                "source": "dndnode_35",
+                "sourceHandle": "JsonSpec|dndnode_35|Tool|JsonSpec",
+                "target": "dndnode_19",
+                "targetHandle": "JsonSpec|spec|dndnode_19",
+                "className": "animate-pulse",
+                "id": "reactflow__edge-dndnode_35JsonSpec|dndnode_35|Tool|JsonSpec-dndnode_19JsonSpec|spec|dndnode_19",
+                "selected": false
+            },
+            {
+                "source": "dndnode_36",
+                "sourceHandle": "OpenAIChat|dndnode_36|BaseLanguageModel|BaseLLM",
+                "target": "dndnode_33",
+                "targetHandle": "BaseLanguageModel|llm|dndnode_33",
+                "className": "animate-pulse",
+                "id": "reactflow__edge-dndnode_36OpenAIChat|dndnode_36|BaseLanguageModel|BaseLLM-dndnode_33BaseLanguageModel|llm|dndnode_33"
+            }
+        ],
+        "viewport": {
+            "x": 0,
+            "y": 0,
+            "zoom": 1
+        }
+    },
+    "chat": [
+        {
+            "message": "test",
+            "isSend": true
+        }
+    ]
+}
\ No newline at end of file
diff --git a/tests/test_cache.py b/tests/test_cache.py
new file mode 100644
index 000000000..c52ceb38a
--- /dev/null
+++ b/tests/test_cache.py
@@ -0,0 +1,63 @@
+import json
+import tempfile
+from pathlib import Path
+
+import pytest
+from langflow.cache.utils import PREFIX, compute_hash
+from langflow.interface.run import load_langchain_object
+
+
+def get_graph(_type="basic"):
+    """Get a graph from a json file"""
+    if _type == "basic":
+        path = pytest.BASIC_EXAMPLE_PATH
+    elif _type == "complex":
+        path = pytest.COMPLEX_EXAMPLE_PATH
+    elif _type == "openapi":
+        path = pytest.OPENAPI_EXAMPLE_PATH
+
+    with open(path, "r") as f:
+        flow_graph = json.load(f)
+    return flow_graph["data"]
+
+
+@pytest.fixture
+def basic_data_graph():
+    return get_graph()
+
+
+@pytest.fixture
+def complex_data_graph():
+    return get_graph("complex")
+
+
+@pytest.fixture
+def openapi_data_graph():
+    return get_graph("openapi")
+
+
+def langchain_objects_are_equal(obj1, obj2):
+    return str(obj1) == str(obj2)
+
+
+def test_cache_creation(basic_data_graph):
+    # Compute hash for the input data_graph
+    computed_hash = compute_hash(basic_data_graph)
+
+    # Call process_graph function to build and cache the langchain_object
+    _ = load_langchain_object(basic_data_graph)
+
+    # Check if the cache file exists
+    cache_file = Path(tempfile.gettempdir()) / f"{PREFIX}_{computed_hash}.dill"
+    assert cache_file.exists()
+
+
+def test_cache_reuse(basic_data_graph):
+    # Call process_graph function to build and cache the langchain_object
+    result1 = load_langchain_object(basic_data_graph)
+
+    # Call process_graph function again to use the cached langchain_object
+    result2 = load_langchain_object(basic_data_graph)
+
+    # Compare the results to ensure the same langchain_object was used
+    assert langchain_objects_are_equal(result1, result2)
diff --git a/tests/test_creators.py b/tests/test_creators.py
new file mode 100644
index 000000000..5453b57eb
--- /dev/null
+++ b/tests/test_creators.py
@@ -0,0 +1,50 @@
+from typing import Dict, List
+
+import pytest
+from langflow.interface.agents.base import AgentCreator
+from langflow.interface.base import LangChainTypeCreator
+
+
+@pytest.fixture
+def sample_lang_chain_type_creator() -> LangChainTypeCreator:
+    class SampleLangChainTypeCreator(LangChainTypeCreator):
+        type_name: str = "test_type"
+
+        def type_to_loader_dict(self) -> Dict:  # type: ignore
+            return {"test_type": "TestClass"}
+
+        def to_list(self) -> List[str]:
+            return ["node1", "node2"]
+
+        def get_signature(self, name: str) -> Dict:
+            return {
+                "template": {"test_field": {"type": "str"}},
+                "description": "test description",
+                "base_classes": ["base_class1", "base_class2"],
+            }
+
+    return SampleLangChainTypeCreator()
+
+
+@pytest.fixture
+def sample_agent_creator() -> AgentCreator:
+    return AgentCreator()
+
+
+def test_lang_chain_type_creator_to_dict(
+    sample_lang_chain_type_creator: LangChainTypeCreator,
+):
+    type_dict = sample_lang_chain_type_creator.to_dict()
+    assert len(type_dict) == 1
+    assert "test_type" in type_dict
+    assert "node1" in type_dict["test_type"]
+    assert "node2" in type_dict["test_type"]
+    assert "template" in type_dict["test_type"]["node1"]
+    assert "description" in type_dict["test_type"]["node1"]
+    assert "base_classes" in type_dict["test_type"]["node1"]
+
+
+def test_agent_creator_type_to_loader_dict(sample_agent_creator: AgentCreator):
+    type_to_loader_dict = sample_agent_creator.type_to_loader_dict
+    assert len(type_to_loader_dict) > 0
+    assert "JsonAgent"
diff --git a/tests/test_custom_types.py b/tests/test_custom_types.py
index 42da01696..f42421bd1 100644
--- a/tests/test_custom_types.py
+++ b/tests/test_custom_types.py
@@ -1,7 +1,7 @@
 # Test this:
-from langflow.interface.custom_types import PythonFunction
-from langflow.utils import constants
 import pytest
+from langflow.interface.custom.types import PythonFunction
+from langflow.utils import constants
 
 
 def test_python_function():
diff --git a/tests/test_endpoints.py b/tests/test_endpoints.py
index 36daa926e..570bf554e 100644
--- a/tests/test_endpoints.py
+++ b/tests/test_endpoints.py
@@ -1,5 +1,5 @@
-from langflow.interface.listing import CUSTOM_TOOLS
 from fastapi.testclient import TestClient
+from langflow.interface.tools.constants import CUSTOM_TOOLS
 
 
 def test_get_all(client: TestClient):
diff --git a/tests/test_frontend_nodes.py b/tests/test_frontend_nodes.py
new file mode 100644
index 000000000..673bdaec0
--- /dev/null
+++ b/tests/test_frontend_nodes.py
@@ -0,0 +1,57 @@
+import pytest
+from langflow.template.base import FrontendNode, Template, TemplateField
+
+
+@pytest.fixture
+def sample_template_field() -> TemplateField:
+    return TemplateField(name="test_field", field_type="str")
+
+
+@pytest.fixture
+def sample_template(sample_template_field: TemplateField) -> Template:
+    return Template(type_name="test_template", fields=[sample_template_field])
+
+
+@pytest.fixture
+def sample_frontend_node(sample_template: Template) -> FrontendNode:
+    return FrontendNode(
+        template=sample_template,
+        description="test description",
+        base_classes=["base_class1", "base_class2"],
+        name="test_frontend_node",
+    )
+
+
+def test_template_field_defaults(sample_template_field: TemplateField):
+    assert sample_template_field.field_type == "str"
+    assert sample_template_field.required is False
+    assert sample_template_field.placeholder == ""
+    assert sample_template_field.is_list is False
+    assert sample_template_field.show is True
+    assert sample_template_field.multiline is False
+    assert sample_template_field.value is None
+    assert sample_template_field.suffixes == []
+    assert sample_template_field.file_types == []
+    assert sample_template_field.content is None
+    assert sample_template_field.password is False
+    assert sample_template_field.name == "test_field"
+
+
+def test_template_to_dict(
+    sample_template: Template, sample_template_field: TemplateField
+):
+    template_dict = sample_template.to_dict()
+    assert template_dict["_type"] == "test_template"
+    assert len(template_dict) == 2  # _type and test_field
+    assert "test_field" in template_dict
+    assert "type" in template_dict["test_field"]
+    assert "required" in template_dict["test_field"]
+
+
+def test_frontend_node_to_dict(sample_frontend_node: FrontendNode):
+    node_dict = sample_frontend_node.to_dict()
+    assert len(node_dict) == 1
+    assert "test_frontend_node" in node_dict
+    assert "description" in node_dict["test_frontend_node"]
+    assert "template" in node_dict["test_frontend_node"]
+    assert "base_classes" in node_dict["test_frontend_node"]
diff --git a/tests/test_graph.py b/tests/test_graph.py
index dfb0e2323..0ea2d0f51 100644
--- a/tests/test_graph.py
+++ b/tests/test_graph.py
@@ -1,15 +1,35 @@
 import json
-from langflow.graph.graph import Edge, Graph, Node
+
 import pytest
-from langflow.utils.payload import build_json, get_root_node
 from langchain.agents import AgentExecutor
+from langflow.graph import Edge, Graph, Node
+from langflow.graph.nodes import (
+    AgentNode,
+    ChainNode,
+    FileToolNode,
+    LLMNode,
+    PromptNode,
+    ToolkitNode,
+    ToolNode,
+    WrapperNode,
+)
+from langflow.utils.payload import build_json, get_root_node
 
 # Test cases for the graph module
 
+# now we have three types of graph:
+# BASIC_EXAMPLE_PATH, COMPLEX_EXAMPLE_PATH, OPENAPI_EXAMPLE_PATH
 
-def get_graph(basic=True):
+
+def get_graph(_type="basic"):
     """Get a graph from a json file"""
-    path = pytest.BASIC_EXAMPLE_PATH if basic else pytest.COMPLEX_EXAMPLE_PATH
+    if _type == "basic":
+        path = pytest.BASIC_EXAMPLE_PATH
+    elif _type == "complex":
+        path = pytest.COMPLEX_EXAMPLE_PATH
+    elif _type == "openapi":
+        path = pytest.OPENAPI_EXAMPLE_PATH
+
     with open(path, "r") as f:
         flow_graph = json.load(f)
     data_graph = flow_graph["data"]
@@ -18,26 +38,94 @@ def get_graph(basic=True):
     return Graph(nodes, edges)
 
 
-def test_get_nodes_with_target():
+@pytest.fixture
+def basic_graph():
+    return get_graph()
+
+
+@pytest.fixture
+def complex_graph():
+    return get_graph("complex")
+
+
+@pytest.fixture
+def openapi_graph():
+    return get_graph("openapi")
+
+
+def get_node_by_type(graph, node_type):
+    """Get a node by type"""
+    return next((node for node in graph.nodes if isinstance(node, node_type)), None)
+
+
+def test_graph_structure(basic_graph):
+    assert isinstance(basic_graph, Graph)
+    assert len(basic_graph.nodes) > 0
+    assert len(basic_graph.edges) > 0
+    for node in basic_graph.nodes:
+        assert isinstance(node, Node)
+    for edge in basic_graph.edges:
+        assert isinstance(edge, Edge)
+        assert edge.source in basic_graph.nodes
+        assert edge.target in basic_graph.nodes
+
+
+def test_circular_dependencies(basic_graph):
+    assert isinstance(basic_graph, Graph)
+
+    def check_circular(node, visited):
+        visited.add(node)
+        neighbors = basic_graph.get_nodes_with_target(node)
+        for neighbor in neighbors:
+            if neighbor in visited:
+                return True
+            if check_circular(neighbor, visited.copy()):
+                return True
+        return False
+
+    for node in basic_graph.nodes:
+        assert not check_circular(node, set())
+
+
+def test_invalid_node_types():
+    graph_data = {
+        "nodes": [
+            {
+                "id": "1",
+                "data": {
+                    "node": {
+                        "base_classes": ["BaseClass"],
+                        "template": {
+                            "_type": "InvalidNodeType",
+                        },
+                    },
+                },
+            },
+        ],
+        "edges": [],
+    }
+    with pytest.raises(Exception):
+        Graph(graph_data["nodes"], graph_data["edges"])
+
+
+def test_get_nodes_with_target(basic_graph):
     """Test getting connected nodes"""
-    graph = get_graph()
-    assert isinstance(graph, Graph)
+    assert isinstance(basic_graph, Graph)
     # Get root node
-    root = get_root_node(graph)
+    root = get_root_node(basic_graph)
     assert root is not None
-    connected_nodes = graph.get_nodes_with_target(root)
+    connected_nodes = basic_graph.get_nodes_with_target(root)
     assert connected_nodes is not None
 
 
-def test_get_node_neighbors_basic():
+def test_get_node_neighbors_basic(basic_graph):
     """Test getting node neighbors"""
 
-    graph = get_graph(basic=True)
-    assert isinstance(graph, Graph)
+    assert isinstance(basic_graph, Graph)
     # Get root node
-    root = get_root_node(graph)
+    root = get_root_node(basic_graph)
     assert root is not None
-    neighbors = graph.get_node_neighbors(root)
+    neighbors = basic_graph.get_node_neighbors(root)
     assert neighbors is not None
     assert isinstance(neighbors, dict)
     # Root Node is an Agent, it requires an LLMChain and tools
@@ -56,7 +144,7 @@ def test_get_node_neighbors_basic():
         for neighbor, val in neighbors.items()
         if "Chain" in neighbor.data["type"] and val
     )
-    chain_neighbors = graph.get_node_neighbors(chain)
+    chain_neighbors = basic_graph.get_node_neighbors(chain)
     assert chain_neighbors is not None
     assert isinstance(chain_neighbors, dict)
     # Check if there is a LLM in the chain's neighbors
@@ -73,15 +161,13 @@ def test_get_node_neighbors_basic():
     )
 
 
-def test_get_node_neighbors_complex():
+def test_get_node_neighbors_complex(complex_graph):
     """Test getting node neighbors"""
-
-    graph = get_graph(basic=False)
-    assert isinstance(graph, Graph)
+    assert isinstance(complex_graph, Graph)
     # Get root node
-    root = get_root_node(graph)
+    root = get_root_node(complex_graph)
     assert root is not None
-    neighbors = graph.get_nodes_with_target(root)
+    neighbors = complex_graph.get_nodes_with_target(root)
     assert neighbors is not None
     # Neighbors should be a list of nodes
     assert isinstance(neighbors, list)
@@ -92,7 +178,7 @@ def test_get_node_neighbors_complex():
     assert any("Tool" in neighbor.data["type"] for neighbor in neighbors)
     # Now on to the Chain's neighbors
     chain = next(neighbor for neighbor in neighbors if "Chain" in neighbor.data["type"])
-    chain_neighbors = graph.get_nodes_with_target(chain)
+    chain_neighbors = complex_graph.get_nodes_with_target(chain)
     assert chain_neighbors is not None
     # Check if there is a LLM in the chain's neighbors
     assert any("OpenAI" in neighbor.data["type"] for neighbor in chain_neighbors)
@@ -100,7 +186,7 @@ def test_get_node_neighbors_complex():
     assert any("Prompt" in neighbor.data["type"] for neighbor in chain_neighbors)
     # Now on to the Tool's neighbors
     tool = next(neighbor for neighbor in neighbors if "Tool" in neighbor.data["type"])
-    tool_neighbors = graph.get_nodes_with_target(tool)
+    tool_neighbors = complex_graph.get_nodes_with_target(tool)
     assert tool_neighbors is not None
     # Check if there is an Agent in the tool's neighbors
     assert any("Agent" in neighbor.data["type"] for neighbor in tool_neighbors)
@@ -108,7 +194,7 @@ def test_get_node_neighbors_complex():
     agent = next(
         neighbor for neighbor in tool_neighbors if "Agent" in neighbor.data["type"]
     )
-    agent_neighbors = graph.get_nodes_with_target(agent)
+    agent_neighbors = complex_graph.get_nodes_with_target(agent)
     assert agent_neighbors is not None
     # Check if there is a Tool in the agent's neighbors
     assert any("Tool" in neighbor.data["type"] for neighbor in agent_neighbors)
@@ -116,62 +202,57 @@ def test_get_node_neighbors_complex():
     tool = next(
         neighbor for neighbor in agent_neighbors if "Tool" in neighbor.data["type"]
     )
-    tool_neighbors = graph.get_nodes_with_target(tool)
+    tool_neighbors = complex_graph.get_nodes_with_target(tool)
     assert tool_neighbors is not None
     # Check if there is a PythonFunction in the tool's neighbors
     assert any("PythonFunction" in neighbor.data["type"] for neighbor in tool_neighbors)
 
 
-def test_get_node():
+def test_get_node(basic_graph):
     """Test getting a single node"""
-    graph = get_graph()
-    node_id = graph.nodes[0].id
-    node = graph.get_node(node_id)
+    node_id = basic_graph.nodes[0].id
+    node = basic_graph.get_node(node_id)
     assert isinstance(node, Node)
     assert node.id == node_id
 
 
-def test_build_nodes():
+def test_build_nodes(basic_graph):
     """Test building nodes"""
-    graph = get_graph()
-    assert len(graph.nodes) == len(graph._nodes)
-    for node in graph.nodes:
+
+    assert len(basic_graph.nodes) == len(basic_graph._nodes)
+    for node in basic_graph.nodes:
         assert isinstance(node, Node)
 
 
-def test_build_edges():
+def test_build_edges(basic_graph):
     """Test building edges"""
-    graph = get_graph()
-    assert len(graph.edges) == len(graph._edges)
-    for edge in graph.edges:
+    assert len(basic_graph.edges) == len(basic_graph._edges)
+    for edge in basic_graph.edges:
         assert isinstance(edge, Edge)
         assert isinstance(edge.source, Node)
         assert isinstance(edge.target, Node)
 
 
-def test_get_root_node():
+def test_get_root_node(basic_graph, complex_graph):
     """Test getting root node"""
-    graph = get_graph(basic=True)
-    assert isinstance(graph, Graph)
-    root = get_root_node(graph)
+    assert isinstance(basic_graph, Graph)
+    root = get_root_node(basic_graph)
     assert root is not None
     assert isinstance(root, Node)
     assert root.data["type"] == "ZeroShotAgent"
     # For complex example, the root node is a ZeroShotAgent too
-    graph = get_graph(basic=False)
-    assert isinstance(graph, Graph)
-    root = get_root_node(graph)
+    assert isinstance(complex_graph, Graph)
+    root = get_root_node(complex_graph)
     assert root is not None
     assert isinstance(root, Node)
     assert root.data["type"] == "ZeroShotAgent"
 
 
-def test_build_json():
+def test_build_json(basic_graph):
     """Test building JSON from graph"""
-    graph = get_graph()
-    assert isinstance(graph, Graph)
-    root = get_root_node(graph)
-    json_data = build_json(root, graph)
+    assert isinstance(basic_graph, Graph)
+    root = get_root_node(basic_graph)
+    json_data = build_json(root, basic_graph)
     assert isinstance(json_data, dict)
     assert json_data["_type"] == "zero-shot-react-description"
     assert isinstance(json_data["llm_chain"], dict)
@@ -187,38 +268,37 @@ def test_build_json():
     assert all(isinstance(val, str) for val in json_data["return_values"])
 
 
-def test_validate_edges():
+def test_validate_edges(basic_graph):
     """Test validating edges"""
-    graph = get_graph()
-    assert isinstance(graph, Graph)
+
+    assert isinstance(basic_graph, Graph)
     # all edges should be valid
-    assert all(edge.valid for edge in graph.edges)
+    assert all(edge.valid for edge in basic_graph.edges)
 
 
-def test_matched_type():
+def test_matched_type(basic_graph):
     """Test matched type attribute in Edge"""
-    graph = get_graph()
-    assert isinstance(graph, Graph)
+    assert isinstance(basic_graph, Graph)
     # all edges should be valid
-    assert all(edge.valid for edge in graph.edges)
+    assert all(edge.valid for edge in basic_graph.edges)
     # all edges should have a matched_type attribute
-    assert all(hasattr(edge, "matched_type") for edge in graph.edges)
+    assert all(hasattr(edge, "matched_type") for edge in basic_graph.edges)
     # The matched_type attribute should be in the source_types attr
-    assert all(edge.matched_type in edge.source_types for edge in graph.edges)
+    assert all(edge.matched_type in edge.source_types for edge in basic_graph.edges)
 
 
-def test_build_params():
+def test_build_params(basic_graph):
     """Test building params"""
-    graph = get_graph()
-    assert isinstance(graph, Graph)
+
+    assert isinstance(basic_graph, Graph)
     # all edges should be valid
-    assert all(edge.valid for edge in graph.edges)
+    assert all(edge.valid for edge in basic_graph.edges)
     # all edges should have a matched_type attribute
-    assert all(hasattr(edge, "matched_type") for edge in graph.edges)
+    assert all(hasattr(edge, "matched_type") for edge in basic_graph.edges)
     # The matched_type attribute should be in the source_types attr
-    assert all(edge.matched_type in edge.source_types for edge in graph.edges)
+    assert all(edge.matched_type in edge.source_types for edge in basic_graph.edges)
     # Get the root node
-    root = get_root_node(graph)
+    root = get_root_node(basic_graph)
     # Root node is a ZeroShotAgent
     # which requires an llm_chain, allowed_tools and return_values
     assert isinstance(root.params, dict)
@@ -260,7 +340,7 @@ def test_build_params():
     assert isinstance(llm_node.params["model_name"], str)
 
 
-def test_build():
+def test_build(basic_graph, complex_graph):
     """Test Node's build method"""
     # def build(self):
     # # The params dict is used to build the module
@@ -283,18 +363,81 @@ def test_build():
     # # and instantiate it with the params
     # # and return the instance
     # return LANGCHAIN_TYPES_DICT[self.node_type](**self.params)
-    graph = get_graph()
-    assert isinstance(graph, Graph)
+
+    assert isinstance(basic_graph, Graph)
     # Now we test the build method
     # Build the Agent
-    agent = graph.build()
+    agent = basic_graph.build()
     # The agent should be a AgentExecutor
     assert isinstance(agent, AgentExecutor)
 
     # Now we test the complex example
-    graph = get_graph(basic=False)
-    assert isinstance(graph, Graph)
+    assert isinstance(complex_graph, Graph)
     # Now we test the build method
-    agent = graph.build()
+    agent = complex_graph.build()
     # The agent should be a AgentExecutor
     assert isinstance(agent, AgentExecutor)
+
+
+def test_agent_node_build(basic_graph):
+    agent_node = get_node_by_type(basic_graph, AgentNode)
+    assert agent_node is not None
+    built_object = agent_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the AgentNode's build() method
+
+
+def test_tool_node_build(basic_graph):
+    tool_node = get_node_by_type(basic_graph, ToolNode)
+    assert tool_node is not None
+    built_object = tool_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the ToolNode's build() method
+
+
+def test_chain_node_build(complex_graph):
+    chain_node = get_node_by_type(complex_graph, ChainNode)
+    assert chain_node is not None
+    built_object = chain_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the ChainNode's build() method
+
+
+def test_prompt_node_build(complex_graph):
+    prompt_node = get_node_by_type(complex_graph, PromptNode)
+    assert prompt_node is not None
+    built_object = prompt_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the PromptNode's build() method
+
+
+def test_llm_node_build(basic_graph):
+    llm_node = get_node_by_type(basic_graph, LLMNode)
+    assert llm_node is not None
+    built_object = llm_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the LLMNode's build() method
+
+
+def test_toolkit_node_build(openapi_graph):
+    toolkit_node = get_node_by_type(openapi_graph, ToolkitNode)
+    assert toolkit_node is not None
+    built_object = toolkit_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the ToolkitNode's build() method
+
+
+def test_file_tool_node_build(openapi_graph):
+    file_tool_node = get_node_by_type(openapi_graph, FileToolNode)
+    assert file_tool_node is not None
+    built_object = file_tool_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the FileToolNode's build() method
+
+
+def test_wrapper_node_build(openapi_graph):
+    wrapper_node = get_node_by_type(openapi_graph, WrapperNode)
+    assert wrapper_node is not None
+    built_object = wrapper_node.build()
+    assert built_object is not None
+    # Add any further assertions specific to the WrapperNode's build() method
diff --git a/tests/test_loading.py b/tests/test_loading.py
index a824ec4e5..444c85fd9 100644
--- a/tests/test_loading.py
+++ b/tests/test_loading.py
@@ -1,10 +1,10 @@
 import json
-from langflow.graph.graph import Graph
-import pytest
 
-from langflow import load_flow_from_json
-from langflow.utils.payload import get_root_node
+import pytest
 from langchain.agents import AgentExecutor
+from langflow import load_flow_from_json
+from langflow.graph import Graph
+from langflow.utils.payload import get_root_node
 
 
 def test_load_flow_from_json():
diff --git a/tests/test_template.py b/tests/test_template.py
new file mode 100644
index 000000000..9f7d78c55
--- /dev/null
+++ b/tests/test_template.py
@@ -0,0 +1,291 @@
+import importlib
+from typing import Dict, List, Optional
+
+import pytest
+from langflow.utils.constants import CHAT_OPENAI_MODELS, OPENAI_MODELS
+from langflow.utils.util import (
+    build_template_from_class,
+    build_template_from_function,
+    format_dict,
+    get_base_classes,
+    get_class_doc,
+    get_default_factory,
+)
+from pydantic import BaseModel
+
+
+# Dummy classes for testing purposes
+class Parent(BaseModel):
+    """Parent Class"""
+
+    parent_field: str
+
+
+class Child(Parent):
+    """Child Class"""
+
+    child_field: int
+
+
+class ExampleClass1(BaseModel):
+    """Example class 1."""
+
+    def __init__(self, data: Optional[List[int]] = None):
+        self.data = data or [1, 2, 3]
+
+
+class ExampleClass2(BaseModel):
+    """Example class 2."""
+
+    def __init__(self, data: Optional[Dict[str, int]] = None):
+        self.data = data or {"a": 1, "b": 2, "c": 3}
+
+
+def example_loader_1() -> ExampleClass1:
+    """Example loader function 1."""
+    return ExampleClass1()
+
+
+def example_loader_2() -> ExampleClass2:
+    """Example loader function 2."""
+    return ExampleClass2()
+
+
+def test_build_template_from_function():
+    type_to_loader_dict = {
+        "example1": example_loader_1,
+        "example2": example_loader_2,
+    }
+
+    # Test with valid name
+    result = build_template_from_function("ExampleClass1", type_to_loader_dict)
+
+    assert "template" in result
+    assert "description" in result
+    assert "base_classes" in result
+
+    # Test with add_function=True
+    result_with_function = build_template_from_function(
+        "ExampleClass1", type_to_loader_dict, add_function=True
+    )
+    assert "function" in result_with_function["base_classes"]
+
+    # Test with invalid name
+    with pytest.raises(ValueError, match=r".* not found"):
+        build_template_from_function("NonExistent", type_to_loader_dict)
+
+
+# Test build_template_from_class
+def test_build_template_from_class():
+    type_to_cls_dict: Dict[str, type] = {"parent": Parent, "child": Child}
+
+    # Test valid input
+    result = build_template_from_class("Child", type_to_cls_dict)
+    assert "template" in result
+    assert "description" in result
+    assert "base_classes" in result
+    assert "Child" in result["base_classes"]
+    assert "Parent" in result["base_classes"]
+    assert result["description"] == "Child Class"
+
+    # Test invalid input
+    with pytest.raises(ValueError, match="InvalidClass not found."):
+        build_template_from_class("InvalidClass", type_to_cls_dict)
+
+
+# Test format_dict
+def test_format_dict():
+    # Test 1: Optional type removal
+    input_dict = {
+        "field1": {"type": "Optional[str]", "required": False},
+    }
+    expected_output = {
+        "field1": {
+            "type": "str",
+            "required": False,
+            "list": False,
+            "show": False,
+            "password": False,
+            "multiline": False,
+        },
+    }
+    assert format_dict(input_dict) == expected_output
+
+    # Test 2: List type processing
+    input_dict = {
+        "field1": {"type": "List[str]", "required": False},
+    }
+    expected_output = {
+        "field1": {
+            "type": "str",
+            "required": False,
+            "list": True,
+            "show": False,
+            "password": False,
+            "multiline": False,
+        },
+    }
+    assert format_dict(input_dict) == expected_output
+
+    # Test 3: Mapping type replacement
+    input_dict = {
+        "field1": {"type": "Mapping[str, int]", "required": False},
+    }
+    expected_output = {
+        "field1": {
+            "type": "code",  # Mapping type is replaced with dict which is replaced with code
+            "required": False,
+            "list": False,
+            "show": False,
+            "password": False,
+            "multiline": False,
+        },
+    }
+    assert format_dict(input_dict) == expected_output
+
+    # Test 4: Replace default value with actual value
+    input_dict = {
+        "field1": {"type": "str", "required": False, "default": "test"},
+    }
+    expected_output = {
+        "field1": {
+            "type": "str",
+            "required": False,
+            "list": False,
+            "show": False,
+            "password": False,
+            "multiline": False,
+            "value": "test",
+        },
+    }
+    assert format_dict(input_dict) == expected_output
+
+    # Test 5: Add password field
+    input_dict = {
+        "field1": {"type": "str", "required": False},
+        "api_key": {"type": "str", "required": False},
+    }
+    expected_output = {
+        "field1": {
+            "type": "str",
+            "required": False,
+            "list": False,
+            "show": False,
+            "password": False,
+            "multiline": False,
+        },
+        "api_key": {
+            "type": "str",
+            "required": False,
+            "list": False,
+            "show": True,
+            "password": True,
+            "multiline": False,
+        },
+    }
+    assert format_dict(input_dict) == expected_output
+
+    # Test 6: Add multiline
+    input_dict = {
+        "field1": {"type": "str", "required": False},
+        "prefix": {"type": "str", "required": False},
+    }
+    expected_output = {
+        "field1": {
+            "type": "str",
+            "required": False,
+            "list": False,
+            "show": False,
+            "password": False,
+            "multiline": False,
+        },
+        "prefix": {
+            "type": "str",
+            "required": False,
+            "list": False,
+            "show": True,
+            "password": False,
+            "multiline": True,
+        },
+    }
+    assert format_dict(input_dict) == expected_output
+
+    # Test 7: Check class name-specific cases (OpenAI, OpenAIChat)
+    input_dict = {
+        "model_name": {"type": "str", "required": False},
+    }
+    expected_output_openai = {
+        "model_name": {
+            "type": "str",
+            "required": False,
+            "list": True,
+            "show": True,
+            "password": False,
+            "multiline": False,
+            "options": OPENAI_MODELS,
+        },
+    }
+    expected_output_openai_chat = {
+        "model_name": {
+            "type": "str",
+            "required": False,
+            "list": True,
+            "show": True,
+            "password": False,
+            "multiline": False,
+            "options": CHAT_OPENAI_MODELS,
+        },
+    }
+    assert format_dict(input_dict, "OpenAI") == expected_output_openai
+    assert format_dict(input_dict, "OpenAIChat") == expected_output_openai_chat
+
+    # Test 8: Replace dict type with str
+    input_dict = {
+        "field1": {"type": "Dict[str, int]", "required": False},
+    }
+    expected_output = {
+        "field1": {
+            "type": "code",
+            "required": False,
+            "list": False,
+            "show": False,
+            "password": False,
+            "multiline": False,
+        },
+    }
+    assert format_dict(input_dict) == expected_output
+
+
+# Test get_base_classes
+def test_get_base_classes():
+    base_classes_parent = get_base_classes(Parent)
+    base_classes_child = get_base_classes(Child)
+
+    assert "Parent" in base_classes_parent
+    assert "Child" in base_classes_child
+    assert "Parent" in base_classes_child
+
+
+# Test get_default_factory
+def test_get_default_factory():
+    module_name = "langflow.utils.util"
+    function_repr = "<function dummy_function>"
+
+    def dummy_function():
+        return "default_value"
+
+    # Add dummy_function to your_module
+    setattr(importlib.import_module(module_name), "dummy_function", dummy_function)
+
+    default_value = get_default_factory(module_name, function_repr)
+
+    assert default_value == "default_value"
+
+
+# Test get_class_doc
+def test_get_class_doc():
+    class_doc_parent = get_class_doc(Parent)
+    class_doc_child = get_class_doc(Child)
+
+    assert class_doc_parent["Description"] == "Parent Class"
+    assert class_doc_child["Description"] == "Child Class"
diff --git a/tests/test_validate_code.py b/tests/test_validate_code.py
index 9cb47f6e1..cacf3669c 100644
--- a/tests/test_validate_code.py
+++ b/tests/test_validate_code.py
@@ -1,12 +1,13 @@
+from unittest import mock
+
+import pytest
 from langflow.utils.validate import (
     create_function,
+    execute_function,
     extract_function_name,
     validate_code,
-    execute_function,
 )
-import pytest
 from requests.exceptions import MissingSchema
-from unittest import mock
 
 
 def test_validate_code():