merge fix

.github/workflows/pre-release.yml

@@ -62,4 +62,6 @@ jobs:
           context: .
           push: true
           file: ./build_and_push.Dockerfile
-          tags: logspace/langflow:${{ steps.check-version.outputs.version }}
+          tags: |
+            logspace/langflow:${{ steps.check-version.outputs.version }}
+            logspace/langflow:latest-dev

docs/docs/whats-new/a-new-chapter-langflow.mdx

@@ -0,0 +1,98 @@
+# A new chapter for Langflow
+
+# First things first
+
+Thank you all for being part of the Langflow community. The journey so far has been amazing and we are happy to have you with us.
+
+We have some exciting news to share with you. Langflow is changing, and we want to tell you all about it.
+
+## Where have we been?
+
+We spent the last few months working on a new version of Langflow. We wanted to make it more powerful, more flexible, and easier to use.
+We're moving from version 0.6 straight to 1.0 (preview). This is a big change, and we want to explain why we're doing it and what it means for you.
+
+## Why?
+
+In the past year, we learned a lot from the community and our users. We saw the potential of Langflow and the need for a more powerful and flexible tool for building conversational AI applications (and beyond).
+We realized that Langflow was hiding things from you that would really help you build better and more complex conversational AI applications. So we decided to make a big change.
+
+## The only way to go is forward
+
+From all the people we talked to, we learned that the most important thing for (most of) them is to have a tool that is easy to use, but also powerful and controllable. They also told us that Langflow's transparency could be improved.
+
+In those points, we saw an opportunity to make Langflow much more powerful and flexible, while also making it easier to use and understand.
+
+One key change you'll notice is that projects now require you to define Inputs and Outputs.
+This is a big change, but it's also a big improvement.
+It allows you to define the structure of your conversation and the data that flows through it.
+This makes it easier to understand and control your conversation.
+
+
+This change comes with a new way of visualizing your projects. Before 1.0 you would connect Components to ultimately build one final Component that was processed behind the scenes.
+Now, each step of the process is defined by you, is visible on the canvas, and can be monitored and controlled by you. This makes it so that Composition is now just another way of building in Langflow. **Now data flows through your project more transparently**.
+
+
+The caveat is existing projects may need some new Components to get them back to their full functionality.
+[We've made this as easy as possible](../migration/compatibility), and there will be improvements to it as we get feedback in our Discord server and on GitHub.
+
+## Custom Interactions
+
+The moment we decided to make this change, we saw the potential to make Langflow even more yours.
+By having a clear definition of Inputs and Outputs, we could build the experience around that which led us to create the **Interaction Panel**.
+
+
+When building a project testing and debugging is crucial. The Interaction Panel is a tool that changes dynamically based on the Inputs and Outputs you defined in your project.
+
+
+For example, let's say you are building a simple RAG application. Generally, you have an Input, some references that come from a Vector Store Search, a Prompt and the answer.
+Now, you could plug the output of your Prompt into a [Text Output](../components/outputs#Text-Output), rename that to "Prompt Result" and see the output of your Prompt in the Interaction Panel.
+
+{/* Add image here of the described above */}
+
+This is just one example of how the Interaction Panel can help you build and debug your projects.
+
+We have many planned features for the Interaction Panel, and we're excited to see how you use it and what you think of it.
+
+## An easier start
+
+The experience for the first-time user is also something we wanted to improve.
+
+Meet the new and improved **New Project** screen. It's now easier to start a new project, and you can choose from a list of starter projects to get you started.
+
+{/* Add new project image */}
+
+We wanted to create start projects that would help you learn about new features and also give you a head start on your projects.
+
+For now, we have:
+
+- **Basic Prompting**: A simple project that shows you how to use the Prompt Component.
+- **Data Ingestion**: A project that shows you how to ingest files into a Vector Store.
+- **RAG**: A project that shows you how to use a Vector Store Search and a Prompt to build a simple RAG application.
+
+As always, your feedback is invaluable, so please let us know what you think of the new starter projects and what you would like to see in the future.
+
+## Less is more
+
+We added many new Components to Langflow and updated some of the existing ones, and we will deprecate some of them.
+
+The idea is that Langflow has evolved, and we want to make sure that the Components you use are the best they can be.
+Some of them don't work well with the others, and some of them are just not needed anymore.
+
+We are working on a list of Components that will be deprecated.
+In the preview stages of 1.0, we will have a smaller list of Components so that we make sure that the ones we have are the best they can be.
+Regardless, community feedback is very important in this matter, so please let us know what you think of the new Components and which ones you miss.
+
+We are aiming at having a more stable and reliable set of Components that helps you get quickly to useful results.
+This also means that your contributions in the [Langflow Store](https://langflow.store) and throughout the community are more important than ever.
+
+## What's next?
+
+Langflow went through a big change, and we are excited to see how you use it and what you think of it.
+
+We plan to add more types of Input and Output like Image and Audio, and we also plan to add more Components to help you build more complex projects.
+
+We also have some experimental features like a State Management System (so cool!) and a new way of building Grouped Components that we are excited to show you.
+
+## Reach out
+
+One last time, we want to thank you for being part of the Langflow community. Your feedback is invaluable, and we want to hear from you.

poetry.lock

@@ -602,7 +602,7 @@ name = "build"
 version = "1.1.1"
 description = "A simple, correct Python build frontend"
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">=3.8"
 files = [
     {file = "build-1.1.1-py3-none-any.whl", hash = "sha256:8ed0851ee76e6e38adce47e4bee3b51c771d86c64cf578d0c2245567ee200e73"},
     {file = "build-1.1.1.tar.gz", hash = "sha256:8eea65bb45b1aac2e734ba2cc8dad3a6d97d97901a395bd0ed3e7b46953d2a31"},
@@ -617,8 +617,9 @@ tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
-test = ["filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
+test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
-typing = ["importlib-metadata (>=5.1)", "mypy (>=1.5.0,<1.6.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+uv = ["uv (>=0.1.18)"]
 virtualenv = ["virtualenv (>=20.0.35)"]
 
 [[package]]
@@ -2584,9 +2585,9 @@ files = [
 
 [package.dependencies]
 google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0.dev0"
-google-auth = ">=1.19.0,<3.0.0.dev0"
+google-auth = ">=1.32.0,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0.dev0"
-google-auth-httplib2 = ">=0.1.0"
+google-auth-httplib2 = ">=0.2.0,<1.0.0"
-httplib2 = ">=0.15.0,<1.dev0"
+httplib2 = ">=0.19.0,<1.dev0"
 uritemplate = ">=3.0.1,<5"
 
 [[package]]
@@ -3338,13 +3339,13 @@ typer = ">=0.9.0,<0.10.0"
 
 [[package]]
 name = "ipykernel"
-version = "6.29.3"
+version = "6.29.4"
 description = "IPython Kernel for Jupyter"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "ipykernel-6.29.3-py3-none-any.whl", hash = "sha256:5aa086a4175b0229d4eca211e181fb473ea78ffd9869af36ba7694c947302a21"},
+    {file = "ipykernel-6.29.4-py3-none-any.whl", hash = "sha256:1181e653d95c6808039c509ef8e67c4126b3b3af7781496c7cbfb5ed938a27da"},
-    {file = "ipykernel-6.29.3.tar.gz", hash = "sha256:e14c250d1f9ea3989490225cc1a542781b095a18a19447fcf2b5eaf7d0ac5bd2"},
+    {file = "ipykernel-6.29.4.tar.gz", hash = "sha256:3d44070060f9475ac2092b760123fadf105d2e2493c24848b6691a7c4f42af5c"},
 ]
 
 [package.dependencies]
@@ -3884,6 +3885,23 @@ langchain-core = ">=0.1.28,<0.2.0"
 [package.extras]
 extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
 
+[[package]]
+name = "langchain-text-splitters"
+version = "0.0.1"
+description = "LangChain text splitting utilities"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
+    {file = "langchain_text_splitters-0.0.1-py3-none-any.whl", hash = "sha256:f5b802f873f5ff6a8b9259ff34d53ed989666ef4e1582e6d1adb3b5520e3839a"},
+    {file = "langchain_text_splitters-0.0.1.tar.gz", hash = "sha256:ac459fa98799f5117ad5425a9330b21961321e30bc19a2a2f9f761ddadd62aa1"},
+]
+
+[package.dependencies]
+langchain-core = ">=0.1.28,<0.2.0"
+
+[package.extras]
+extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
+
 [[package]]
 name = "langdetect"
 version = "1.0.9"
@@ -5451,18 +5469,18 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 
 [[package]]
 name = "opentelemetry-api"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Python API"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_api-1.23.0-py3-none-any.whl", hash = "sha256:cc03ea4025353048aadb9c64919099663664672ea1c6be6ddd8fee8e4cd5e774"},
+    {file = "opentelemetry_api-1.24.0-py3-none-any.whl", hash = "sha256:0f2c363d98d10d1ce93330015ca7fd3a65f60be64e05e30f557c61de52c80ca2"},
-    {file = "opentelemetry_api-1.23.0.tar.gz", hash = "sha256:14a766548c8dd2eb4dfc349739eb4c3893712a0daa996e5dbf945f9da665da9d"},
+    {file = "opentelemetry_api-1.24.0.tar.gz", hash = "sha256:42719f10ce7b5a9a73b10a4baf620574fb8ad495a9cbe5c18d76b75d8689c67e"},
 ]
 
 [package.dependencies]
 deprecated = ">=1.2.6"
-importlib-metadata = ">=6.0,<7.0"
+importlib-metadata = ">=6.0,<=7.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp"
@@ -5481,27 +5499,27 @@ opentelemetry-exporter-otlp-proto-http = "1.23.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-common"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Protobuf encoding"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_exporter_otlp_proto_common-1.23.0-py3-none-any.whl", hash = "sha256:2a9e7e9d5a8b026b572684b6b24dcdefcaa58613d5ce3d644130b0c373c056c1"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.24.0-py3-none-any.whl", hash = "sha256:e51f2c9735054d598ad2df5d3eca830fecfb5b0bda0a2fa742c9c7718e12f641"},
-    {file = "opentelemetry_exporter_otlp_proto_common-1.23.0.tar.gz", hash = "sha256:35e4ea909e7a0b24235bd0aaf17fba49676527feb1823b46565ff246d5a1ab18"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.24.0.tar.gz", hash = "sha256:5d31fa1ff976cacc38be1ec4e3279a3f88435c75b38b1f7a099a1faffc302461"},
 ]
 
 [package.dependencies]
-opentelemetry-proto = "1.23.0"
+opentelemetry-proto = "1.24.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-grpc"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_exporter_otlp_proto_grpc-1.23.0-py3-none-any.whl", hash = "sha256:40f9e3e7761eb34f2a1001f4543028783ac26e2db27e420d5374f2cca0182dad"},
+    {file = "opentelemetry_exporter_otlp_proto_grpc-1.24.0-py3-none-any.whl", hash = "sha256:f40d62aa30a0a43cc1657428e59fcf82ad5f7ea8fff75de0f9d9cb6f739e0a3b"},
-    {file = "opentelemetry_exporter_otlp_proto_grpc-1.23.0.tar.gz", hash = "sha256:aa1a012eea5342bfef51fcf3f7f22601dcb0f0984a07ffe6025b2fbb6d91a2a9"},
+    {file = "opentelemetry_exporter_otlp_proto_grpc-1.24.0.tar.gz", hash = "sha256:217c6e30634f2c9797999ea9da29f7300479a94a610139b9df17433f915e7baa"},
 ]
 
 [package.dependencies]
@@ -5509,9 +5527,9 @@ deprecated = ">=1.2.6"
 googleapis-common-protos = ">=1.52,<2.0"
 grpcio = ">=1.0.0,<2.0.0"
 opentelemetry-api = ">=1.15,<2.0"
-opentelemetry-exporter-otlp-proto-common = "1.23.0"
+opentelemetry-exporter-otlp-proto-common = "1.24.0"
-opentelemetry-proto = "1.23.0"
+opentelemetry-proto = "1.24.0"
-opentelemetry-sdk = ">=1.23.0,<1.24.0"
+opentelemetry-sdk = ">=1.24.0,<1.25.0"
 
 [package.extras]
 test = ["pytest-grpc"]
@@ -5541,13 +5559,13 @@ test = ["responses (>=0.22.0,<0.25)"]
 
 [[package]]
 name = "opentelemetry-instrumentation"
-version = "0.44b0"
+version = "0.45b0"
 description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation-0.44b0-py3-none-any.whl", hash = "sha256:79560f386425176bcc60c59190064597096114c4a8e5154f1cb281bb4e47d2fc"},
+    {file = "opentelemetry_instrumentation-0.45b0-py3-none-any.whl", hash = "sha256:06c02e2c952c1b076e8eaedf1b82f715e2937ba7eeacab55913dd434fbcec258"},
-    {file = "opentelemetry_instrumentation-0.44b0.tar.gz", hash = "sha256:8213d02d8c0987b9b26386ae3e091e0477d6331673123df736479322e1a50b48"},
+    {file = "opentelemetry_instrumentation-0.45b0.tar.gz", hash = "sha256:6c47120a7970bbeb458e6a73686ee9ba84b106329a79e4a4a66761f933709c7e"},
 ]
 
 [package.dependencies]
@@ -5557,47 +5575,45 @@ wrapt = ">=1.0.0,<2.0.0"
 
 [[package]]
 name = "opentelemetry-instrumentation-asgi"
-version = "0.44b0"
+version = "0.45b0"
 description = "ASGI instrumentation for OpenTelemetry"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation_asgi-0.44b0-py3-none-any.whl", hash = "sha256:0d95c84a8991008c8a8ac35e15d43cc7768a5bb46f95f129e802ad2990d7c366"},
+    {file = "opentelemetry_instrumentation_asgi-0.45b0-py3-none-any.whl", hash = "sha256:8be1157ed62f0db24e45fdf7933c530c4338bd025c5d4af7830e903c0756021b"},
-    {file = "opentelemetry_instrumentation_asgi-0.44b0.tar.gz", hash = "sha256:72d4d28ec7ccd551eac11edc5ae8cac3586c0a228467d6a95fad7b6d4edd597a"},
+    {file = "opentelemetry_instrumentation_asgi-0.45b0.tar.gz", hash = "sha256:97f55620f163fd3d20323e9fd8dc3aacc826c03397213ff36b877e0f4b6b08a6"},
 ]
 
 [package.dependencies]
 asgiref = ">=3.0,<4.0"
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.44b0"
+opentelemetry-instrumentation = "0.45b0"
-opentelemetry-semantic-conventions = "0.44b0"
+opentelemetry-semantic-conventions = "0.45b0"
-opentelemetry-util-http = "0.44b0"
+opentelemetry-util-http = "0.45b0"
 
 [package.extras]
 instruments = ["asgiref (>=3.0,<4.0)"]
-test = ["opentelemetry-instrumentation-asgi[instruments]", "opentelemetry-test-utils (==0.44b0)"]
 
 [[package]]
 name = "opentelemetry-instrumentation-fastapi"
-version = "0.44b0"
+version = "0.45b0"
 description = "OpenTelemetry FastAPI Instrumentation"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_instrumentation_fastapi-0.44b0-py3-none-any.whl", hash = "sha256:4441482944bea6676816668d56deb94af990e8c6e9582c581047e5d84c91d3c9"},
+    {file = "opentelemetry_instrumentation_fastapi-0.45b0-py3-none-any.whl", hash = "sha256:77d9c123a363129148f5f66d44094f3d67aaaa2b201396d94782b4a7f9ce4314"},
-    {file = "opentelemetry_instrumentation_fastapi-0.44b0.tar.gz", hash = "sha256:67ed10b93ad9d35238ae0be73cf8acbbb65a4a61fb7444d0aee5b0c492e294db"},
+    {file = "opentelemetry_instrumentation_fastapi-0.45b0.tar.gz", hash = "sha256:5a6b91e1c08a01601845fcfcfdefd0a2aecdb3c356d4a436a3210cb58c21487e"},
 ]
 
 [package.dependencies]
 opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.44b0"
+opentelemetry-instrumentation = "0.45b0"
-opentelemetry-instrumentation-asgi = "0.44b0"
+opentelemetry-instrumentation-asgi = "0.45b0"
-opentelemetry-semantic-conventions = "0.44b0"
+opentelemetry-semantic-conventions = "0.45b0"
-opentelemetry-util-http = "0.44b0"
+opentelemetry-util-http = "0.45b0"
 
 [package.extras]
 instruments = ["fastapi (>=0.58,<1.0)"]
-test = ["httpx (>=0.22,<1.0)", "opentelemetry-instrumentation-fastapi[instruments]", "opentelemetry-test-utils (==0.44b0)", "requests (>=2.23,<3.0)"]
 
 [[package]]
 name = "opentelemetry-instrumentation-httpx"
@@ -5622,13 +5638,13 @@ test = ["opentelemetry-instrumentation-httpx[instruments]", "opentelemetry-sdk (
 
 [[package]]
 name = "opentelemetry-proto"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Python Proto"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_proto-1.23.0-py3-none-any.whl", hash = "sha256:4c017deca052cb287a6003b7c989ed8b47af65baeb5d57ebf93dde0793f78509"},
+    {file = "opentelemetry_proto-1.24.0-py3-none-any.whl", hash = "sha256:bcb80e1e78a003040db71ccf83f2ad2019273d1e0828089d183b18a1476527ce"},
-    {file = "opentelemetry_proto-1.23.0.tar.gz", hash = "sha256:e6aaf8b7ace8d021942d546161401b83eed90f9f2cc6f13275008cea730e4651"},
+    {file = "opentelemetry_proto-1.24.0.tar.gz", hash = "sha256:ff551b8ad63c6cabb1845ce217a6709358dfaba0f75ea1fa21a61ceddc78cab8"},
 ]
 
 [package.dependencies]
@@ -5636,40 +5652,40 @@ protobuf = ">=3.19,<5.0"
 
 [[package]]
 name = "opentelemetry-sdk"
-version = "1.23.0"
+version = "1.24.0"
 description = "OpenTelemetry Python SDK"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "opentelemetry_sdk-1.23.0-py3-none-any.whl", hash = "sha256:a93c96990ac0f07c6d679e2f1015864ff7a4f5587122dd5af968034436efb1fd"},
+    {file = "opentelemetry_sdk-1.24.0-py3-none-any.whl", hash = "sha256:fa731e24efe832e98bcd90902085b359dcfef7d9c9c00eb5b9a18587dae3eb59"},
-    {file = "opentelemetry_sdk-1.23.0.tar.gz", hash = "sha256:9ddf60195837b59e72fd2033d6a47e2b59a0f74f0ec37d89387d89e3da8cab7f"},
+    {file = "opentelemetry_sdk-1.24.0.tar.gz", hash = "sha256:75bc0563affffa827700e0f4f4a68e1e257db0df13372344aebc6f8a64cde2e5"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.23.0"
+opentelemetry-api = "1.24.0"
-opentelemetry-semantic-conventions = "0.44b0"
+opentelemetry-semantic-conventions = "0.45b0"
 typing-extensions = ">=3.7.4"
 
 [[package]]
 name = "opentelemetry-semantic-conventions"
-version = "0.44b0"
+version = "0.45b0"
 description = "OpenTelemetry Semantic Conventions"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -9631,22 +9647,24 @@ files = [
 
 [[package]]
 name = "weaviate-client"
-version = "3.26.2"
+version = "4.5.4"
 description = "A python native Weaviate client"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "weaviate-client-3.26.2.tar.gz", hash = "sha256:63ec70839b64909810a64aa7b3e5b85088462e93c7e2ed3c32ebefb702f36723"},
+    {file = "weaviate-client-4.5.4.tar.gz", hash = "sha256:fc53dc73cd53df453c5e6dc758e49a6a1549212d6670ddd013392107120692f8"},
-    {file = "weaviate_client-3.26.2-py3-none-any.whl", hash = "sha256:ca43bfb9c06b8ae3fd938dc9158acd93d4cbf4622192e173333e1ff63cf97164"},
+    {file = "weaviate_client-4.5.4-py3-none-any.whl", hash = "sha256:f6d3a6b759e5aa0d3350067490526ea38b9274ae4043b4a3ae0064c28d56883f"},
 ]
 
 [package.dependencies]
 authlib = ">=1.2.1,<2.0.0"
+grpcio = ">=1.57.0,<2.0.0"
+grpcio-health-checking = ">=1.57.0,<2.0.0"
+grpcio-tools = ">=1.57.0,<2.0.0"
+httpx = "0.27.0"
+pydantic = ">=2.5.0,<3.0.0"
 requests = ">=2.30.0,<3.0.0"
-validators = ">=0.21.2,<1.0.0"
+validators = "0.22.0"
-
-[package.extras]
-grpc = ["grpcio (>=1.57.0,<2.0.0)", "grpcio-tools (>=1.57.0,<2.0.0)"]
 
 [[package]]
 name = "websocket-client"

pyproject.toml

@@ -7,7 +7,6 @@ maintainers = [
     "Carlos Coelho <carlos@logspace.ai>",
     "Cristhian Zanforlin <cristhian.lousa@gmail.com>",
     "Gabriel Almeida <gabriel@logspace.ai>",
-    "Gustavo Schaedler <gustavopoa@gmail.com>",
     "Igor Carvalho <igorr.ackerman@gmail.com>",
     "Lucas Eduoli <lucaseduoli@gmail.com>",
     "Otávio Anovazzi <otavio2204@gmail.com>",

src/backend/base/langflow/alembic/versions/006b3990db50_add_unique_constraints.py

@@ -26,13 +26,13 @@ def upgrade() -> None:
     flow_constraints = inspector.get_unique_constraints("flow")
     user_constraints = inspector.get_unique_constraints("user")
     try:
-        if not any(constraint["name"] == "uq_apikey_id" for constraint in api_key_constraints):
+        if not any(constraint["column_names"] == ["id"] for constraint in api_key_constraints):
             with op.batch_alter_table("apikey", schema=None) as batch_op:
                 batch_op.create_unique_constraint("uq_apikey_id", ["id"])
-        if not any(constraint["name"] == "uq_flow_id" for constraint in flow_constraints):
+        if not any(constraint["column_names"] == ["id"] for constraint in flow_constraints):
             with op.batch_alter_table("flow", schema=None) as batch_op:
                 batch_op.create_unique_constraint("uq_flow_id", ["id"])
-        if not any(constraint["name"] == "uq_user_id" for constraint in user_constraints):
+        if not any(constraint["column_names"] == ["id"] for constraint in user_constraints):
             with op.batch_alter_table("user", schema=None) as batch_op:
                 batch_op.create_unique_constraint("uq_user_id", ["id"])
     except Exception as e:

src/backend/base/langflow/base/io/chat.py

@@ -2,6 +2,7 @@ import warnings
 from typing import Optional, Union
 
 from langflow.field_typing import Text
+from langflow.helpers.record import records_to_text
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.memory import add_messages
 from langflow.schema import Record
@@ -21,6 +22,7 @@ class ChatComponent(CustomComponent):
             "sender": {
                 "options": ["Machine", "User"],
                 "display_name": "Sender Type",
+                "advanced": True,
             },
             "sender_name": {"display_name": "Sender Name"},
             "session_id": {
@@ -31,6 +33,13 @@ class ChatComponent(CustomComponent):
             "return_record": {
                 "display_name": "Return Record",
                 "info": "Return the message as a record containing the sender, sender_name, and session_id.",
+                "advanced": True,
+            },
+            "record_template": {
+                "display_name": "Record Template",
+                "multiline": True,
+                "info": "In case of Message being a Record, this template will be used to convert it to text.",
+                "advanced": True,
             },
         }
 
@@ -74,9 +83,10 @@ class ChatComponent(CustomComponent):
         self,
         sender: Optional[str] = "User",
         sender_name: Optional[str] = "User",
-        input_value: Optional[str] = None,
+        input_value: Optional[Union[str, Record]] = None,
         session_id: Optional[str] = None,
         return_record: Optional[bool] = False,
+        record_template: Optional[str] = "Text: {text}\nData: {data}",
     ) -> Union[Text, Record]:
         input_value_record: Optional[Record] = None
         if return_record:
@@ -94,6 +104,8 @@ class ChatComponent(CustomComponent):
                         "session_id": session_id,
                     },
                 )
+        elif isinstance(input_value, Record):
+            input_value = records_to_text(template=record_template, records=input_value)
         if not input_value:
             input_value = ""
         if return_record and input_value_record:

src/backend/base/langflow/base/io/text.py

@@ -1,18 +1,28 @@
-from typing import Optional
+from typing import Optional, Union
 
 from langflow.field_typing import Text
+from langflow.helpers.record import records_to_text
 from langflow.interface.custom.custom_component import CustomComponent
+from langflow.schema.schema import Record
 
 
 class TextComponent(CustomComponent):
     display_name = "Text Component"
     description = "Used to pass text to the next component."
 
-    field_config = {
+    def build_config(self):
-        "input_value": {"display_name": "Value", "multiline": True},
+        return {
-    }
+            "input_value": {"display_name": "Value", "input_types": ["Record"], "info": "Text or Record to be passed."},
+            "record_template": {"display_name": "Record Template", "multiline": True},
+        }
 
-    def build(self, input_value: Optional[str] = "") -> Text:
+    def build(
+        self,
+        input_value: Optional[Union[Text, Record]] = "",
+        record_template: Optional[str] = "Text: {text}\nData: {data}",
+    ) -> Text:
+        if isinstance(input_value, Record):
+            input_value = records_to_text(template=record_template, records=input_value)
         self.status = input_value
         if not input_value:
             input_value = ""

src/backend/base/langflow/components/__init__.py

@@ -1,18 +1,17 @@
 __all__ = [
     "agents",
     "chains",
-    "data",
     "documentloaders",
     "embeddings",
     "experimental",
-    "helpers",
     "inputs",
     "memories",
     "model_specs",
-    "models",
     "outputs",
     "retrievers",
     "textsplitters",
     "toolkits",
+    "tools",
+    "vectorsearch",
     "vectorstores",
 ]

src/backend/base/langflow/components/agents/__init__.py

@@ -5,6 +5,7 @@ from .OpenAIConversationalAgent import ConversationalAgent
 from .SQLAgent import SQLAgentComponent
 from .VectorStoreAgent import VectorStoreAgentComponent
 from .VectorStoreRouterAgent import VectorStoreRouterAgentComponent
+from .XMLAgent import XMLAgentComponent
 
 __all__ = [
     "AgentInitializerComponent",
@@ -14,4 +15,5 @@ __all__ = [
     "SQLAgentComponent",
     "VectorStoreAgentComponent",
     "VectorStoreRouterAgentComponent",
+    "XMLAgentComponent",
 ]

src/backend/base/langflow/components/data/APIRequest.py

@@ -10,11 +10,11 @@ from langflow.schema import Record
 
 class APIRequest(CustomComponent):
     display_name: str = "API Request"
-    description: str = "Make an HTTP request to the given URL."
+    description: str = "Make HTTP requests given one or more URLs."
     output_types: list[str] = ["Record"]
     documentation: str = "https://docs.langflow.org/components/utilities#api-request"
     field_config = {
-        "urls": {"display_name": "URLs", "info": "The URLs to make the request to."},
+        "urls": {"display_name": "URLs", "info": "URLs to make requests to."},
         "method": {
             "display_name": "Method",
             "info": "The HTTP method to use.",

src/backend/base/langflow/components/data/Directory.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class DirectoryComponent(CustomComponent):
     display_name = "Directory"
-    description = "Load Text Files from a Directory and Convert Them to Records."
+    description = "Recursively load files from a directory."
 
     def build_config(self) -> Dict[str, Any]:
         return {

src/backend/base/langflow/components/data/File.py

@@ -1,4 +1,5 @@
-from typing import Any, Dict, List
+from pathlib import Path
+from typing import Any, Dict
 
 from langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_record
 from langflow.interface.custom.custom_component import CustomComponent
@@ -7,12 +8,12 @@ from langflow.schema import Record
 
 class FileComponent(CustomComponent):
     display_name = "Files"
-    description = "Read Text Files"
+    description = "A generic file loader."
 
     def build_config(self) -> Dict[str, Any]:
         return {
-            "paths": {
+            "path": {
-                "display_name": "Paths",
+                "display_name": "Path",
                 "field_type": "file",
                 "file_types": TEXT_FILE_TYPES,
                 "info": f"Supported file types: {', '.join(TEXT_FILE_TYPES)}",
@@ -26,7 +27,8 @@ class FileComponent(CustomComponent):
 
     def load_file(self, path: str, silent_errors: bool = False) -> Record:
         resolved_path = self.resolve_path(path)
-        extension = resolved_path.split(".")[-1]
+        path_obj = Path(resolved_path)
+        extension = path_obj.suffix[1:].lower()
         if extension == "doc":
             raise ValueError("doc files are not supported. Please save as .docx")
         if extension not in TEXT_FILE_TYPES:
@@ -37,9 +39,9 @@ class FileComponent(CustomComponent):
 
     def build(
         self,
-        paths: List[str],
+        path: str,
         silent_errors: bool = False,
-    ) -> List[Record]:
+    ) -> Record:
-        records = [self.load_file(path, silent_errors) for path in paths]
+        record = self.load_file(path, silent_errors)
-        self.status = records
+        self.status = record
-        return records
+        return record

src/backend/base/langflow/components/data/FileLoader.py

@@ -1,117 +0,0 @@
-from typing import List
-
-from langflow.interface.custom.custom_component import CustomComponent
-from langflow.schema import Record
-from langflow.utils.constants import LOADERS_INFO
-
-
-class FileLoaderComponent(CustomComponent):
-    display_name: str = "File Loader"
-    description: str = "Generic File Loader"
-
-    def build_config(self):
-        loader_options = ["Automatic"] + [loader_info["name"] for loader_info in LOADERS_INFO]
-
-        file_types = []
-        suffixes = []
-
-        for loader_info in LOADERS_INFO:
-            if "allowedTypes" in loader_info:
-                file_types.extend(loader_info["allowedTypes"])
-                suffixes.extend([f".{ext}" for ext in loader_info["allowedTypes"]])
-
-        return {
-            "file_path": {
-                "display_name": "File Path",
-                "required": True,
-                "field_type": "file",
-                "file_types": [
-                    "json",
-                    "txt",
-                    "csv",
-                    "jsonl",
-                    "html",
-                    "htm",
-                    "conllu",
-                    "enex",
-                    "msg",
-                    "pdf",
-                    "srt",
-                    "eml",
-                    "md",
-                    "mdx",
-                    "pptx",
-                    "docx",
-                ],
-                "suffixes": [
-                    ".json",
-                    ".txt",
-                    ".csv",
-                    ".jsonl",
-                    ".html",
-                    ".htm",
-                    ".conllu",
-                    ".enex",
-                    ".msg",
-                    ".pdf",
-                    ".srt",
-                    ".eml",
-                    ".md",
-                    ".mdx",
-                    ".pptx",
-                    ".docx",
-                ],
-                # "file_types" : file_types,
-                # "suffixes": suffixes,
-            },
-            "loader": {
-                "display_name": "Loader",
-                "is_list": True,
-                "required": True,
-                "options": loader_options,
-                "value": "Automatic",
-            },
-            "code": {"show": False},
-        }
-
-    def build(self, file_path: str, loader: str) -> List[Record]:
-        file_type = file_path.split(".")[-1]
-
-        # Map the loader to the correct loader class
-        selected_loader_info = None
-        for loader_info in LOADERS_INFO:
-            if loader_info["name"] == loader:
-                selected_loader_info = loader_info
-                break
-
-        if selected_loader_info is None and loader != "Automatic":
-            raise ValueError(f"Loader {loader} not found in the loader info list")
-
-        if loader == "Automatic":
-            # Determine the loader based on the file type
-            default_loader_info = None
-            for info in LOADERS_INFO:
-                if "defaultFor" in info and file_type in info["defaultFor"]:
-                    default_loader_info = info
-                    break
-
-            if default_loader_info is None:
-                raise ValueError(f"No default loader found for file type: {file_type}")
-
-            selected_loader_info = default_loader_info
-        if isinstance(selected_loader_info, dict):
-            loader_import: str = selected_loader_info["import"]
-        else:
-            raise ValueError(f"Loader info for {loader} is not a dict\nLoader info:\n{selected_loader_info}")
-        module_name, class_name = loader_import.rsplit(".", 1)
-
-        try:
-            # Import the loader class
-            loader_module = __import__(module_name, fromlist=[class_name])
-            loader_instance = getattr(loader_module, class_name)
-        except ImportError as e:
-            raise ValueError(f"Loader {loader} could not be imported\nLoader info:\n{selected_loader_info}") from e
-
-        result = loader_instance(file_path=file_path)
-        docs = result.load()
-        return self.to_records(docs)

src/backend/base/langflow/components/data/URL.py

@@ -8,7 +8,7 @@ from langflow.schema import Record
 
 class URLComponent(CustomComponent):
     display_name = "URL"
-    description = "Load URLs and convert them to records."
+    description = "Fetch text content given one or more URLs."
 
     def build_config(self) -> Dict[str, Any]:
         return {
@@ -22,4 +22,5 @@ class URLComponent(CustomComponent):
         loader = WebBaseLoader(web_paths=urls)
         docs = loader.load()
         records = self.to_records(docs)
+        self.status = records
         return records

src/backend/base/langflow/components/data/__init__.py

@@ -1,7 +1,7 @@
 from .APIRequest import APIRequest
 from .Directory import DirectoryComponent
 from .File import FileComponent
-from .FileLoader import FileLoaderComponent
+
 from .URL import URLComponent
 
-__all__ = ["APIRequest", "DirectoryComponent", "FileComponent", "FileLoaderComponent", "URLComponent"]
+__all__ = ["APIRequest", "DirectoryComponent", "FileComponent", "URLComponent"]

src/backend/base/langflow/components/embeddings/CohereEmbeddings.py

@@ -2,7 +2,7 @@ from typing import Optional
 
 from langchain_community.embeddings.cohere import CohereEmbeddings
 
-from langflow.interface.custom.custom_component import CustomComponent
+from langflow.custom import CustomComponent
 
 
 class CohereEmbeddingsComponent(CustomComponent):

src/backend/base/langflow/components/experimental/__init__.py

@@ -1,23 +1,27 @@
 from .ClearMessageHistory import ClearMessageHistoryComponent
 from .ExtractDataFromRecord import ExtractKeyFromRecordComponent
-from .Listen import ListenComponent
+from .FlowTool import FlowToolComponent
 from .ListFlows import ListFlowsComponent
+from .Listen import ListenComponent
 from .MergeRecords import MergeRecordsComponent
 from .Notify import NotifyComponent
+from .PythonFunction import PythonFunctionComponent
 from .RunFlow import RunFlowComponent
 from .RunnableExecutor import RunnableExecComponent
 from .SQLExecutor import SQLExecutorComponent
+from .SubFlow import SubFlowComponent
 
 __all__ = [
     "ClearMessageHistoryComponent",
     "ExtractKeyFromRecordComponent",
-    "ListenComponent",
+    "FlowToolComponent",
     "ListFlowsComponent",
+    "ListenComponent",
     "MergeRecordsComponent",
-    "MessageHistoryComponent",
     "NotifyComponent",
+    "PythonFunctionComponent",
     "RunFlowComponent",
     "RunnableExecComponent",
     "SQLExecutorComponent",
-    "TextToRecordComponent",
+    "SubFlowComponent",
 ]

src/backend/base/langflow/components/helpers/CreateRecord.py

@@ -2,16 +2,16 @@ from langflow.interface.custom.custom_component import CustomComponent
 from langflow.schema import Record
 
 
-class TextToRecordComponent(CustomComponent):
+class CreateRecordComponent(CustomComponent):
-    display_name = "Text to Record"
+    display_name = "Create Record"
-    description = "A component to create a record from Text."
+    description = "A component to create a record."
     beta: bool = True
 
     def build_config(self):
         return {
             "data": {
                 "display_name": "Data",
-                "info": "The data to convert to a record.",
+                "info": "Data to contruct the record.",
                 "input_types": ["Text"],
             }
         }

src/backend/base/langflow/components/helpers/DocumentToRecord.py

@@ -7,8 +7,8 @@ from langflow.schema import Record
 
 
 class DocumentToRecordComponent(CustomComponent):
-    display_name = "Documents to Records"
+    display_name = "Documents To Records"
-    description = "Convert documents to records."
+    description = "Convert LangChain Documents into Records."
 
     field_config = {
         "documents": {"display_name": "Documents"},

src/backend/base/langflow/components/helpers/IDGenerator.py

@@ -6,7 +6,7 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 class UUIDGeneratorComponent(CustomComponent):
     documentation: str = "http://docs.langflow.org/components/custom"
-    display_name = "Unique ID Generator"
+    display_name = "ID Generator"
     description = "Generates a unique ID."
 
     def update_build_config(

src/backend/base/langflow/components/helpers/MessageHistory.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class MessageHistoryComponent(CustomComponent):
     display_name = "Message History"
-    description = "Used to retrieve stored messages."
+    description = "Used to retrieve stored chat messages."
     beta: bool = True
 
     def build_config(self):
@@ -30,7 +30,7 @@ class MessageHistoryComponent(CustomComponent):
 
     def build(
         self,
-        sender: Optional[str] = None,
+        sender: Optional[str] = "Machine",
         sender_name: Optional[str] = None,
         session_id: Optional[str] = None,
         n_messages: int = 5,

src/backend/base/langflow/components/helpers/RecordsToText.py

@@ -4,9 +4,9 @@ from langflow.interface.custom.custom_component import CustomComponent
 from langflow.schema import Record
 
 
-class RecordsAsTextComponent(CustomComponent):
+class RecordsToTextComponent(CustomComponent):
-    display_name = "Records to Text"
+    display_name = "Records To Text"
-    description = "Converts Records into single piece of text using a template."
+    description = "Convert Records into plain text using a pre-defined template."
 
     def build_config(self):
         return {

src/backend/base/langflow/components/helpers/UpdateRecord.py

@@ -4,7 +4,7 @@ from langflow.schema import Record
 
 class UpdateRecordComponent(CustomComponent):
     display_name = "Update Record"
-    description = "Updates a record with new data."
+    description = "Updates a Record with new data. Akin to a Python dictionary update."
 
     def build_config(self):
         return {

src/backend/base/langflow/components/helpers/__init__.py

@@ -2,8 +2,6 @@ from .CustomComponent import Component
 from .DocumentToRecord import DocumentToRecordComponent
 from .IDGenerator import UUIDGeneratorComponent
 from .MessageHistory import MessageHistoryComponent
-from .PythonFunction import PythonFunctionComponent
-from .RecordsAsText import RecordsAsTextComponent
 from .TextToRecord import TextToRecordComponent
 from .UpdateRecord import UpdateRecordComponent
 
@@ -13,7 +11,7 @@ __all__ = [
     "DocumentToRecordComponent",
     "UUIDGeneratorComponent",
     "PythonFunctionComponent",
-    "RecordsAsTextComponent",
+    "RecordsToTextComponent",
     "TextToRecordComponent",
     "MessageHistoryComponent",
 ]

src/backend/base/langflow/components/inputs/ChatInput.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class ChatInput(ChatComponent):
     display_name = "Chat Input"
-    description = "Used to get user input from the chat."
+    description = "Capture user inputs from the chat interface."
     icon = "ChatInput"
 
     def build(

src/backend/base/langflow/components/inputs/JSONInput.py

@@ -1,30 +0,0 @@
-import ast
-import json
-
-from langflow.custom import CustomComponent
-from langflow.schema import Record
-
-
-class JSONInputComponent(CustomComponent):
-    display_name = "JSON Input"
-    description = "Load a JSON object as input."
-
-    def build_config(self):
-        return {
-            "json_str": {
-                "display_name": "JSON String",
-                "multiline": True,
-                "info": "The JSON string to load.",
-            }
-        }
-
-    def build(self, json_str: str) -> Record:
-        try:
-            data = json.loads(json_str)
-        except json.JSONDecodeError:
-            try:
-                data = ast.literal_eval(json_str)
-            except (SyntaxError, ValueError):
-                raise ValueError("Invalid JSON string.")
-        record = Record(data=data)
-        return record

src/backend/base/langflow/components/inputs/Prompt.py

@@ -6,7 +6,7 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 class PromptComponent(CustomComponent):
     display_name: str = "Prompt"
-    description: str = "A component for creating prompts using templates"
+    description: str = "A component for creating prompt templates using dynamic variables."
     icon = "terminal-square"
 
     def build_config(self):

src/backend/base/langflow/components/inputs/TextInput.py

@@ -6,7 +6,21 @@ from langflow.field_typing import Text
 
 class TextInput(TextComponent):
     display_name = "Text Input"
-    description = "Used to pass text input to the next component."
+    description = "Capture Text or Record and send text inputs."
 
-    def build(self, input_value: Optional[str] = "") -> Text:
+    def build_config(self):
-        return super().build(input_value=input_value)
+        return {
+            "input_value": {
+                "display_name": "Value",
+                "input_types": ["Record"],
+                "info": "Text or Record to be passed as input.",
+            },
+            "record_template": {"display_name": "Record Template", "multiline": True},
+        }
+
+    def build(
+        self,
+        input_value: Optional[str] = "",
+        record_template: Optional[str] = "{text}",
+    ) -> Text:
+        return super().build(input_value=input_value, record_template=record_template)

src/backend/base/langflow/components/inputs/__init__.py

@@ -2,4 +2,4 @@ from .ChatInput import ChatInput
 from .Prompt import PromptComponent
 from .TextInput import TextInput
 
-__all__ = ["ChatInput", "TextInput", "PromptComponent"]
+__all__ = ["ChatInput", "PromptComponent", "TextInput"]

src/backend/base/langflow/components/model_specs/CTransformersSpecs.py

@@ -1,33 +0,0 @@
-from typing import Dict, Optional
-
-from langchain_community.llms.ctransformers import CTransformers
-
-from langflow.interface.custom.custom_component import CustomComponent
-
-
-class CTransformersComponent(CustomComponent):
-    display_name = "CTransformers"
-    description = "C Transformers LLM models"
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/ctransformers"
-
-    def build_config(self):
-        return {
-            "model": {"display_name": "Model", "required": True},
-            "model_file": {
-                "display_name": "Model File",
-                "required": False,
-                "field_type": "file",
-                "file_types": [".bin"],
-            },
-            "model_type": {"display_name": "Model Type", "required": True},
-            "config": {
-                "display_name": "Config",
-                "advanced": True,
-                "required": False,
-                "field_type": "dict",
-                "value": '{"top_k":40,"top_p":0.95,"temperature":0.8,"repetition_penalty":1.1,"last_n_tokens":64,"seed":-1,"max_new_tokens":256,"stop":"","stream":"False","reset":"True","batch_size":8,"threads":-1,"context_length":-1,"gpu_layers":0}',
-            },
-        }
-
-    def build(self, model: str, model_file: str, model_type: str, config: Optional[Dict] = None) -> CTransformers:
-        return CTransformers(model=model, model_file=model_file, model_type=model_type, config=config)  # type: ignore

src/backend/base/langflow/components/model_specs/ChatAnthropicSpecs.py

@@ -3,8 +3,8 @@ from typing import Callable, Optional, Union
 from langchain_community.chat_models.anthropic import ChatAnthropic
 from pydantic.v1.types import SecretStr
 
+from langflow.custom import CustomComponent
 from langflow.field_typing import BaseLanguageModel
-from langflow.interface.custom.custom_component import CustomComponent
 
 
 class ChatAnthropicComponent(CustomComponent):
@@ -20,31 +20,48 @@ class ChatAnthropicComponent(CustomComponent):
                 "field_type": "str",
                 "password": True,
             },
-            "anthropic_api_url": {
-                "display_name": "Anthropic API URL",
-                "field_type": "str",
-            },
             "model_kwargs": {
                 "display_name": "Model Kwargs",
                 "field_type": "dict",
                 "advanced": True,
             },
+            "model_name": {
+                "display_name": "Model Name",
+                "field_type": "str",
+                "advanced": False,
+                "required": False,
+                "options": ["claude-3-opus-20240229", "claude-3-sonnet-20240229", "claude-3-haiku-20240307"],
+            },
             "temperature": {
                 "display_name": "Temperature",
                 "field_type": "float",
             },
+            "max_tokens": {
+                "display_name": "Max Tokens",
+                "field_type": "int",
+                "advanced": False,
+                "required": False,
+            },
+            "top_k": {"display_name": "Top K", "field_type": "int", "advanced": True},
+            "top_p": {"display_name": "Top P", "field_type": "float", "advanced": True},
         }
 
     def build(
         self,
         anthropic_api_key: str,
-        anthropic_api_url: Optional[str] = None,
         model_kwargs: dict = {},
+        model_name: str = "claude-3-opus-20240229",
         temperature: Optional[float] = None,
+        max_tokens: Optional[int] = 1024,
+        top_k: Optional[int] = None,
+        top_p: Optional[float] = None,
     ) -> Union[BaseLanguageModel, Callable]:
         return ChatAnthropic(
             anthropic_api_key=SecretStr(anthropic_api_key),
-            anthropic_api_url=anthropic_api_url,
             model_kwargs=model_kwargs,
+            model_name=model_name,
             temperature=temperature,
+            max_tokens=max_tokens,  # type: ignore
+            top_k=top_k,
+            top_p=top_p,
         )

src/backend/base/langflow/components/model_specs/LlamaCppSpecs.py

@@ -1,131 +0,0 @@
-from typing import Any, Dict, List, Optional
-
-from langchain_community.llms.llamacpp import LlamaCpp
-
-from langflow.interface.custom.custom_component import CustomComponent
-
-
-class LlamaCppComponent(CustomComponent):
-    display_name = "LlamaCpp"
-    description = "llama.cpp model."
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/llamacpp"
-
-    def build_config(self):
-        return {
-            "grammar": {"display_name": "Grammar", "advanced": True},
-            "cache": {"display_name": "Cache", "advanced": True},
-            "client": {"display_name": "Client", "advanced": True},
-            "echo": {"display_name": "Echo", "advanced": True},
-            "f16_kv": {"display_name": "F16 KV", "advanced": True},
-            "grammar_path": {"display_name": "Grammar Path", "advanced": True},
-            "last_n_tokens_size": {"display_name": "Last N Tokens Size", "advanced": True},
-            "logits_all": {"display_name": "Logits All", "advanced": True},
-            "logprobs": {"display_name": "Logprobs", "advanced": True},
-            "lora_base": {"display_name": "Lora Base", "advanced": True},
-            "lora_path": {"display_name": "Lora Path", "advanced": True},
-            "max_tokens": {"display_name": "Max Tokens", "advanced": True},
-            "metadata": {"display_name": "Metadata", "advanced": True},
-            "model_kwargs": {"display_name": "Model Kwargs", "advanced": True},
-            "model_path": {
-                "display_name": "Model Path",
-                "field_type": "file",
-                "file_types": [".bin"],
-                "required": True,
-            },
-            "n_batch": {"display_name": "N Batch", "advanced": True},
-            "n_ctx": {"display_name": "N Ctx", "advanced": True},
-            "n_gpu_layers": {"display_name": "N GPU Layers", "advanced": True},
-            "n_parts": {"display_name": "N Parts", "advanced": True},
-            "n_threads": {"display_name": "N Threads", "advanced": True},
-            "repeat_penalty": {"display_name": "Repeat Penalty", "advanced": True},
-            "rope_freq_base": {"display_name": "Rope Freq Base", "advanced": True},
-            "rope_freq_scale": {"display_name": "Rope Freq Scale", "advanced": True},
-            "seed": {"display_name": "Seed", "advanced": True},
-            "stop": {"display_name": "Stop", "advanced": True},
-            "streaming": {"display_name": "Streaming", "advanced": True},
-            "suffix": {"display_name": "Suffix", "advanced": True},
-            "tags": {"display_name": "Tags", "advanced": True},
-            "temperature": {"display_name": "Temperature"},
-            "top_k": {"display_name": "Top K", "advanced": True},
-            "top_p": {"display_name": "Top P", "advanced": True},
-            "use_mlock": {"display_name": "Use Mlock", "advanced": True},
-            "use_mmap": {"display_name": "Use Mmap", "advanced": True},
-            "verbose": {"display_name": "Verbose", "advanced": True},
-            "vocab_only": {"display_name": "Vocab Only", "advanced": True},
-        }
-
-    def build(
-        self,
-        model_path: str,
-        grammar: Optional[str] = None,
-        cache: Optional[bool] = None,
-        client: Optional[Any] = None,
-        echo: Optional[bool] = False,
-        f16_kv: bool = True,
-        grammar_path: Optional[str] = None,
-        last_n_tokens_size: Optional[int] = 64,
-        logits_all: bool = False,
-        logprobs: Optional[int] = None,
-        lora_base: Optional[str] = None,
-        lora_path: Optional[str] = None,
-        max_tokens: Optional[int] = 256,
-        metadata: Optional[Dict] = None,
-        model_kwargs: Dict = {},
-        n_batch: Optional[int] = 8,
-        n_ctx: int = 512,
-        n_gpu_layers: Optional[int] = 1,
-        n_parts: int = -1,
-        n_threads: Optional[int] = 1,
-        repeat_penalty: Optional[float] = 1.1,
-        rope_freq_base: float = 10000.0,
-        rope_freq_scale: float = 1.0,
-        seed: int = -1,
-        stop: Optional[List[str]] = [],
-        streaming: bool = True,
-        suffix: Optional[str] = "",
-        tags: Optional[List[str]] = [],
-        temperature: Optional[float] = 0.8,
-        top_k: Optional[int] = 40,
-        top_p: Optional[float] = 0.95,
-        use_mlock: bool = False,
-        use_mmap: Optional[bool] = True,
-        verbose: bool = True,
-        vocab_only: bool = False,
-    ) -> LlamaCpp:
-        return LlamaCpp(
-            model_path=model_path,
-            grammar=grammar,
-            cache=cache,
-            client=client,
-            echo=echo,
-            f16_kv=f16_kv,
-            grammar_path=grammar_path,
-            last_n_tokens_size=last_n_tokens_size,
-            logits_all=logits_all,
-            logprobs=logprobs,
-            lora_base=lora_base,
-            lora_path=lora_path,
-            max_tokens=max_tokens,
-            metadata=metadata,
-            model_kwargs=model_kwargs,
-            n_batch=n_batch,
-            n_ctx=n_ctx,
-            n_gpu_layers=n_gpu_layers,
-            n_parts=n_parts,
-            n_threads=n_threads,
-            repeat_penalty=repeat_penalty,
-            rope_freq_base=rope_freq_base,
-            rope_freq_scale=rope_freq_scale,
-            seed=seed,
-            stop=stop,
-            streaming=streaming,
-            suffix=suffix,
-            tags=tags,
-            temperature=temperature,
-            top_k=top_k,
-            top_p=top_p,
-            use_mlock=use_mlock,
-            use_mmap=use_mmap,
-            verbose=verbose,
-            vocab_only=vocab_only,
-        )

src/backend/base/langflow/components/model_specs/__init__.py

@@ -4,7 +4,6 @@ from .AnthropicSpecs import AnthropicComponent
 from .AzureChatOpenAISpecs import AzureChatOpenAISpecsComponent
 from .BaiduQianfanChatEndpointsSpecs import QianfanChatEndpointComponent
 from .BaiduQianfanLLMEndpointsSpecs import QianfanLLMEndpointComponent
-from .CTransformersSpecs import CTransformersComponent
 from .ChatAnthropicSpecs import ChatAnthropicComponent
 from .ChatLiteLLMSpecs import ChatLiteLLMComponent
 from .ChatOllamaEndpointSpecs import ChatOllamaComponent
@@ -13,7 +12,6 @@ from .ChatVertexAISpecs import ChatVertexAIComponent
 from .CohereSpecs import CohereComponent
 from .GoogleGenerativeAISpecs import GoogleGenerativeAIComponent
 from .HuggingFaceEndpointsSpecs import HuggingFaceEndpointsComponent
-from .LlamaCppSpecs import LlamaCppComponent
 from .OllamaLLMSpecs import OllamaLLM
 from .VertexAISpecs import VertexAIComponent
 
@@ -24,7 +22,6 @@ __all__ = [
     "AzureChatOpenAISpecsComponent",
     "QianfanChatEndpointComponent",
     "QianfanLLMEndpointComponent",
-    "CTransformersComponent",
     "ChatAnthropicComponent",
     "ChatLiteLLMComponent",
     "ChatOllamaComponent",
@@ -33,7 +30,6 @@ __all__ = [
     "CohereComponent",
     "GoogleGenerativeAIComponent",
     "HuggingFaceEndpointsComponent",
-    "LlamaCppComponent",
     "OllamaLLM",
     "VertexAIComponent",
 ]

src/backend/base/langflow/components/models/AmazonBedrockModel.py

@@ -10,31 +10,50 @@ class AmazonBedrockComponent(LCModelComponent):
     display_name: str = "Amazon Bedrock"
     description: str = "Generate text using LLM model from Amazon Bedrock."
     icon = "Amazon"
+    field_order = [
+        "model_id",
+        "credentials_profile_name",
+        "region_name",
+        "model_kwargs",
+        "endpoint_url",
+        "cache",
+        "stream",
+        "input_value",
+        "system_message",
+    ]
 
     def build_config(self):
         return {
             "model_id": {
                 "display_name": "Model Id",
                 "options": [
-                    "ai21.j2-grande-instruct",
+                    "amazon.titan-text-express-v1",
-                    "ai21.j2-jumbo-instruct",
+                    "amazon.titan-text-lite-v1",
-                    "ai21.j2-mid",
+                    "amazon.titan-embed-text-v1",
-                    "ai21.j2-mid-v1",
+                    "amazon.titan-embed-image-v1",
-                    "ai21.j2-ultra",
+                    "amazon.titan-image-generator-v1",
-                    "ai21.j2-ultra-v1",
-                    "anthropic.claude-instant-v1",
-                    "anthropic.claude-v1",
                     "anthropic.claude-v2",
+                    "anthropic.claude-v2:1",
+                    "anthropic.claude-3-sonnet-20240229-v1:0",
+                    "anthropic.claude-3-haiku-20240307-v1:0",
+                    "anthropic.claude-instant-v1",
+                    "ai21.j2-mid-v1",
+                    "ai21.j2-ultra-v1",
                     "cohere.command-text-v14",
+                    "cohere.command-light-text-v14",
+                    "cohere.embed-english-v3",
+                    "cohere.embed-multilingual-v3",
+                    "meta.llama2-13b-chat-v1",
+                    "meta.llama2-70b-chat-v1",
+                    "mistral.mistral-7b-instruct-v0:2",
+                    "mistral.mixtral-8x7b-instruct-v0:1",
                 ],
             },
             "credentials_profile_name": {"display_name": "Credentials Profile Name"},
-            "streaming": {"display_name": "Streaming", "field_type": "bool"},
             "endpoint_url": {"display_name": "Endpoint URL"},
             "region_name": {"display_name": "Region Name"},
             "model_kwargs": {"display_name": "Model Kwargs"},
             "cache": {"display_name": "Cache"},
-            "code": {"advanced": True},
             "input_value": {"display_name": "Input"},
             "system_message": {"display_name": "System Message", "info": "System message to pass to the model."},
             "stream": {
@@ -52,7 +71,6 @@ class AmazonBedrockComponent(LCModelComponent):
         region_name: Optional[str] = None,
         model_kwargs: Optional[dict] = None,
         endpoint_url: Optional[str] = None,
-        streaming: bool = False,
         cache: Optional[bool] = None,
         stream: bool = False,
     ) -> Text:
@@ -63,7 +81,7 @@ class AmazonBedrockComponent(LCModelComponent):
                 region_name=region_name,
                 model_kwargs=model_kwargs,
                 endpoint_url=endpoint_url,
-                streaming=streaming,
+                streaming=stream,
                 cache=cache,
             )  # type: ignore
         except Exception as e:

src/backend/base/langflow/components/models/AnthropicModel.py

@@ -17,15 +17,17 @@ class AnthropicLLM(LCModelComponent):
             "model": {
                 "display_name": "Model Name",
                 "options": [
+                    "claude-3-opus-20240229",
+                    "claude-3-sonnet-20240229",
+                    "claude-3-haiku-20240307",
                     "claude-2.1",
                     "claude-2.0",
                     "claude-instant-1.2",
                     "claude-instant-1",
-                    # Add more models as needed
                 ],
                 "info": "https://python.langchain.com/docs/integrations/chat/anthropic",
                 "required": True,
-                "value": "claude-2.1",
+                "value": "claude-3-opus-20240229",
             },
             "anthropic_api_key": {
                 "display_name": "Anthropic API Key",
@@ -43,8 +45,8 @@ class AnthropicLLM(LCModelComponent):
                 "field_type": "float",
                 "value": 0.7,
             },
-            "api_endpoint": {
+            "anthropic_api_url": {
-                "display_name": "API Endpoint",
+                "display_name": "Anthropic API URL",
                 "info": "Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.",
             },
             "code": {"show": False},
@@ -67,12 +69,12 @@ class AnthropicLLM(LCModelComponent):
         anthropic_api_key: Optional[str] = None,
         max_tokens: Optional[int] = None,
         temperature: Optional[float] = None,
-        api_endpoint: Optional[str] = None,
+        anthropic_api_url: Optional[str] = None,
         stream: bool = False,
     ) -> Text:
         # Set default API endpoint if not provided
-        if not api_endpoint:
+        if not anthropic_api_url:
-            api_endpoint = "https://api.anthropic.com"
+            anthropic_api_url = "https://api.anthropic.com"
 
         try:
             output = ChatAnthropic(
@@ -80,7 +82,7 @@ class AnthropicLLM(LCModelComponent):
                 anthropic_api_key=(SecretStr(anthropic_api_key) if anthropic_api_key else None),
                 max_tokens_to_sample=max_tokens,  # type: ignore
                 temperature=temperature,
-                anthropic_api_url=api_endpoint,
+                anthropic_api_url=anthropic_api_url,
             )
         except Exception as e:
             raise ValueError("Could not connect to Anthropic API.") from e

src/backend/base/langflow/components/models/AzureOpenAIModel.py

@@ -8,7 +8,7 @@ from langflow.field_typing import Text
 
 
 class AzureChatOpenAIComponent(LCModelComponent):
-    display_name: str = "AzureOpenAI"
+    display_name: str = "Azure OpenAI"
     description: str = "Generate text using LLM model from Azure OpenAI."
     documentation: str = "https://python.langchain.com/docs/integrations/llms/azure_openai"
     beta = False

src/backend/base/langflow/components/models/BaiduQianfanChatModel.py

@@ -8,7 +8,7 @@ from langflow.field_typing import Text
 
 
 class QianfanChatEndpointComponent(LCModelComponent):
-    display_name: str = "QianfanChat"
+    display_name: str = "Qianfan"
     description: str = (
         "Generate text using Baidu Qianfan chat models. Get more detail from "
         "https://python.langchain.com/docs/integrations/chat/baidu_qianfan_endpoint."

src/backend/base/langflow/components/models/CTransformersModel.py

@@ -1,59 +0,0 @@
-from typing import Dict, Optional
-
-from langchain_community.llms.ctransformers import CTransformers
-
-from langflow.base.models.model import LCModelComponent
-from langflow.field_typing import Text
-
-
-class CTransformersComponent(LCModelComponent):
-    display_name = "CTransformers"
-    description = "Generate text using CTransformers LLM models"
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/ctransformers"
-
-    def build_config(self):
-        return {
-            "model": {"display_name": "Model", "required": True},
-            "model_file": {
-                "display_name": "Model File",
-                "required": False,
-                "field_type": "file",
-                "file_types": [".bin"],
-            },
-            "model_type": {"display_name": "Model Type", "required": True},
-            "config": {
-                "display_name": "Config",
-                "advanced": True,
-                "required": False,
-                "field_type": "dict",
-                "value": '{"top_k":40,"top_p":0.95,"temperature":0.8,"repetition_penalty":1.1,"last_n_tokens":64,"seed":-1,"max_new_tokens":256,"stop":"","stream":"False","reset":"True","batch_size":8,"threads":-1,"context_length":-1,"gpu_layers":0}',
-            },
-            "input_value": {"display_name": "Input"},
-            "stream": {
-                "display_name": "Stream",
-                "info": "Stream the response from the model.",
-            },
-            "system_message": {
-                "display_name": "System Message",
-                "info": "System message to pass to the model.",
-            },
-        }
-
-    def build(
-        self,
-        model: str,
-        model_file: str,
-        input_value: Text,
-        model_type: str,
-        stream: bool = False,
-        config: Optional[Dict] = None,
-    ) -> Text:
-        output = CTransformers(
-            client=None,
-            model=model,
-            model_file=model_file,
-            model_type=model_type,
-            config=config,  # noqa
-        )
-
-        return self.get_result(runnable=output, stream=stream, input_value=input_value)

src/backend/base/langflow/components/models/LlamaCppModel.py

@@ -1,148 +0,0 @@
-from typing import Any, Dict, List, Optional
-
-from langchain_community.llms.llamacpp import LlamaCpp
-
-from langflow.base.models.model import LCModelComponent
-from langflow.field_typing import Text
-
-
-class LlamaCppComponent(LCModelComponent):
-    display_name = "LlamaCpp"
-    description = "Generate text using llama.cpp model."
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/llamacpp"
-
-    def build_config(self):
-        return {
-            "grammar": {"display_name": "Grammar", "advanced": True},
-            "cache": {"display_name": "Cache", "advanced": True},
-            "client": {"display_name": "Client", "advanced": True},
-            "echo": {"display_name": "Echo", "advanced": True},
-            "f16_kv": {"display_name": "F16 KV", "advanced": True},
-            "grammar_path": {"display_name": "Grammar Path", "advanced": True},
-            "last_n_tokens_size": {
-                "display_name": "Last N Tokens Size",
-                "advanced": True,
-            },
-            "logits_all": {"display_name": "Logits All", "advanced": True},
-            "logprobs": {"display_name": "Logprobs", "advanced": True},
-            "lora_base": {"display_name": "Lora Base", "advanced": True},
-            "lora_path": {"display_name": "Lora Path", "advanced": True},
-            "max_tokens": {"display_name": "Max Tokens", "advanced": True},
-            "metadata": {"display_name": "Metadata", "advanced": True},
-            "model_kwargs": {"display_name": "Model Kwargs", "advanced": True},
-            "model_path": {
-                "display_name": "Model Path",
-                "field_type": "file",
-                "file_types": [".bin"],
-                "required": True,
-            },
-            "n_batch": {"display_name": "N Batch", "advanced": True},
-            "n_ctx": {"display_name": "N Ctx", "advanced": True},
-            "n_gpu_layers": {"display_name": "N GPU Layers", "advanced": True},
-            "n_parts": {"display_name": "N Parts", "advanced": True},
-            "n_threads": {"display_name": "N Threads", "advanced": True},
-            "repeat_penalty": {"display_name": "Repeat Penalty", "advanced": True},
-            "rope_freq_base": {"display_name": "Rope Freq Base", "advanced": True},
-            "rope_freq_scale": {"display_name": "Rope Freq Scale", "advanced": True},
-            "seed": {"display_name": "Seed", "advanced": True},
-            "stop": {"display_name": "Stop", "advanced": True},
-            "streaming": {"display_name": "Streaming", "advanced": True},
-            "suffix": {"display_name": "Suffix", "advanced": True},
-            "tags": {"display_name": "Tags", "advanced": True},
-            "temperature": {"display_name": "Temperature"},
-            "top_k": {"display_name": "Top K", "advanced": True},
-            "top_p": {"display_name": "Top P", "advanced": True},
-            "use_mlock": {"display_name": "Use Mlock", "advanced": True},
-            "use_mmap": {"display_name": "Use Mmap", "advanced": True},
-            "verbose": {"display_name": "Verbose", "advanced": True},
-            "vocab_only": {"display_name": "Vocab Only", "advanced": True},
-            "input_value": {"display_name": "Input"},
-            "stream": {
-                "display_name": "Stream",
-                "info": "Stream the response from the model.",
-            },
-            "system_message": {
-                "display_name": "System Message",
-                "info": "System message to pass to the model.",
-            },
-        }
-
-    def build(
-        self,
-        model_path: str,
-        input_value: Text,
-        grammar: Optional[str] = None,
-        cache: Optional[bool] = None,
-        client: Optional[Any] = None,
-        echo: Optional[bool] = False,
-        f16_kv: bool = True,
-        grammar_path: Optional[str] = None,
-        last_n_tokens_size: Optional[int] = 64,
-        logits_all: bool = False,
-        logprobs: Optional[int] = None,
-        lora_base: Optional[str] = None,
-        lora_path: Optional[str] = None,
-        max_tokens: Optional[int] = 256,
-        metadata: Optional[Dict] = None,
-        model_kwargs: Dict = {},
-        n_batch: Optional[int] = 8,
-        n_ctx: int = 512,
-        n_gpu_layers: Optional[int] = 1,
-        n_parts: int = -1,
-        n_threads: Optional[int] = 1,
-        repeat_penalty: Optional[float] = 1.1,
-        rope_freq_base: float = 10000.0,
-        rope_freq_scale: float = 1.0,
-        seed: int = -1,
-        stop: Optional[List[str]] = [],
-        streaming: bool = True,
-        suffix: Optional[str] = "",
-        tags: Optional[List[str]] = [],
-        temperature: Optional[float] = 0.8,
-        top_k: Optional[int] = 40,
-        top_p: Optional[float] = 0.95,
-        use_mlock: bool = False,
-        use_mmap: Optional[bool] = True,
-        verbose: bool = True,
-        vocab_only: bool = False,
-        stream: bool = False,
-    ) -> Text:
-        output = LlamaCpp(
-            model_path=model_path,
-            grammar=grammar,
-            cache=cache,
-            client=client,
-            echo=echo,
-            f16_kv=f16_kv,
-            grammar_path=grammar_path,
-            last_n_tokens_size=last_n_tokens_size,
-            logits_all=logits_all,
-            logprobs=logprobs,
-            lora_base=lora_base,
-            lora_path=lora_path,
-            max_tokens=max_tokens,
-            metadata=metadata,
-            model_kwargs=model_kwargs,
-            n_batch=n_batch,
-            n_ctx=n_ctx,
-            n_gpu_layers=n_gpu_layers,
-            n_parts=n_parts,
-            n_threads=n_threads,
-            repeat_penalty=repeat_penalty,
-            rope_freq_base=rope_freq_base,
-            rope_freq_scale=rope_freq_scale,
-            seed=seed,
-            stop=stop,
-            streaming=streaming,
-            suffix=suffix,
-            tags=tags,
-            temperature=temperature,
-            top_k=top_k,
-            top_p=top_p,
-            use_mlock=use_mlock,
-            use_mmap=use_mmap,
-            verbose=verbose,
-            vocab_only=vocab_only,
-        )
-
-        return self.get_result(runnable=output, stream=stream, input_value=input_value)

src/backend/base/langflow/components/models/OllamaModel.py

@@ -13,7 +13,7 @@ from langflow.field_typing import Text
 
 
 class ChatOllamaComponent(LCModelComponent):
-    display_name = "ChatOllama"
+    display_name = "Ollama"
     description = "Generate text using Local LLM for chat with Ollama."
     icon = "Ollama"
 

src/backend/base/langflow/components/models/VertexAiModel.py

@@ -7,7 +7,7 @@ from langflow.field_typing import Text
 
 
 class ChatVertexAIComponent(LCModelComponent):
-    display_name = "ChatVertexAI"
+    display_name = "Vertex AI"
     description = "Generate text using Vertex AI Chat large language models API."
     icon = "VertexAI"
 

src/backend/base/langflow/components/models/__init__.py

@@ -2,11 +2,9 @@ from .AmazonBedrockModel import AmazonBedrockComponent
 from .AnthropicModel import AnthropicLLM
 from .AzureOpenAIModel import AzureChatOpenAIComponent
 from .BaiduQianfanChatModel import QianfanChatEndpointComponent
-from .CTransformersModel import CTransformersComponent
 from .CohereModel import CohereComponent
 from .GoogleGenerativeAIModel import GoogleGenerativeAIComponent
 from .HuggingFaceModel import HuggingFaceEndpointsComponent
-from .LlamaCppModel import LlamaCppComponent
 from .OllamaModel import ChatOllamaComponent
 from .OpenAIModel import OpenAIModelComponent
 from .VertexAiModel import ChatVertexAIComponent
@@ -16,11 +14,9 @@ __all__ = [
     "AnthropicLLM",
     "AzureChatOpenAIComponent",
     "QianfanChatEndpointComponent",
-    "CTransformersComponent",
     "CohereComponent",
     "GoogleGenerativeAIComponent",
     "HuggingFaceEndpointsComponent",
-    "LlamaCppComponent",
     "ChatOllamaComponent",
     "OpenAIModelComponent",
     "ChatVertexAIComponent",

src/backend/base/langflow/components/outputs/ChatOutput.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class ChatOutput(ChatComponent):
     display_name = "Chat Output"
-    description = "Used to send a message to the chat."
+    description = "Used to send a chat message."
     icon = "ChatOutput"
 
     def build(
@@ -17,6 +17,7 @@ class ChatOutput(ChatComponent):
         input_value: Optional[str] = None,
         session_id: Optional[str] = None,
         return_record: Optional[bool] = False,
+        record_template: Optional[str] = "{text}",
     ) -> Union[Text, Record]:
         return super().build(
             sender=sender,
@@ -24,4 +25,5 @@ class ChatOutput(ChatComponent):
             input_value=input_value,
             session_id=session_id,
             return_record=return_record,
+            record_template=record_template,
         )

src/backend/base/langflow/components/outputs/TextOutput.py

@@ -6,11 +6,17 @@ from langflow.field_typing import Text
 
 class TextOutput(TextComponent):
     display_name = "Text Output"
-    description = "Used to pass text output to the next component."
+    description = "Used to send a text output."
 
-    field_config = {
+    def build_config(self):
-        "input_value": {"display_name": "Value"},
+        return {
-    }
+            "input_value": {
+                "display_name": "Value",
+                "input_types": ["Record"],
+                "info": "Text or Record to be passed as output.",
+            },
+            "record_template": {"display_name": "Record Template", "multiline": True},
+        }
 
-    def build(self, input_value: Optional[Text] = "") -> Text:
+    def build(self, input_value: Optional[Text] = "", record_template: str = "{text}") -> Text:
-        return super().build(input_value=input_value)
+        return super().build(input_value=input_value, record_template=record_template)

src/backend/base/langflow/components/retrievers/__init__.py

@@ -2,10 +2,12 @@ from .AmazonKendra import AmazonKendraRetrieverComponent
 from .MetalRetriever import MetalRetrieverComponent
 from .MultiQueryRetriever import MultiQueryRetrieverComponent
 from .VectaraSelfQueryRetriver import VectaraSelfQueryRetriverComponent
+from .VectorStoreRetriever import VectoStoreRetrieverComponent
 
 __all__ = [
     "AmazonKendraRetrieverComponent",
     "MetalRetrieverComponent",
     "MultiQueryRetrieverComponent",
     "VectaraSelfQueryRetriverComponent",
+    "VectoStoreRetrieverComponent",
 ]

src/backend/base/langflow/components/tools/__init__.py

@@ -0,0 +1,5 @@
+from .RetrieverTool import RetrieverToolComponent
+from .SearchAPITool import SearchApiToolComponent
+from .SearchApi import SearchApi
+
+__all__ = ["RetrieverToolComponent", "SearchApiToolComponent", "SearchApi"]

src/backend/base/langflow/components/vectorsearch/AstraDBSearch.py

@@ -23,51 +23,73 @@ class AstraDBSearchComponent(LCVectorStoreComponent):
                 "info": "Input value to search",
             },
             "embedding": {"display_name": "Embedding", "info": "Embedding to use"},
-            "collection_name": {"display_name": "Collection Name", "info": "Collection name"},
+            "collection_name": {
-            "token": {"display_name": "Token", "info": "Token to use", "password": True},
+                "display_name": "Collection Name",
-            "api_endpoint": {"display_name": "API Endpoint", "info": "API Endpoint to use"},
+                "info": "The name of the collection within AstraDB where the vectors will be stored.",
-            "namespace": {"display_name": "Namespace", "info": "Namespace to use", "advanced": True},
+            },
-            "metric": {"display_name": "Metric", "info": "Metric to use", "advanced": True},
+            "token": {
-            "batch_size": {"display_name": "Batch Size", "info": "Batch size to use", "advanced": True},
+                "display_name": "Token",
+                "info": "Authentication token for accessing AstraDB.",
+                "password": True,
+            },
+            "api_endpoint": {
+                "display_name": "API Endpoint",
+                "info": "API endpoint URL for the AstraDB service.",
+            },
+            "namespace": {
+                "display_name": "Namespace",
+                "info": "Optional namespace within AstraDB to use for the collection.",
+                "advanced": True,
+            },
+            "metric": {
+                "display_name": "Metric",
+                "info": "Optional distance metric for vector comparisons in the vector store.",
+                "advanced": True,
+            },
+            "batch_size": {
+                "display_name": "Batch Size",
+                "info": "Optional number of records to process in a single batch.",
+                "advanced": True,
+            },
             "bulk_insert_batch_concurrency": {
                 "display_name": "Bulk Insert Batch Concurrency",
-                "info": "Bulk Insert Batch Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations.",
                 "advanced": True,
             },
             "bulk_insert_overwrite_concurrency": {
                 "display_name": "Bulk Insert Overwrite Concurrency",
-                "info": "Bulk Insert Overwrite Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations that overwrite existing records.",
                 "advanced": True,
             },
             "bulk_delete_concurrency": {
                 "display_name": "Bulk Delete Concurrency",
-                "info": "Bulk Delete Concurrency to use",
+                "info": "Optional concurrency level for bulk delete operations.",
                 "advanced": True,
             },
             "setup_mode": {
                 "display_name": "Setup Mode",
-                "info": "Setup mode for the vector store",
+                "info": "Configuration mode for setting up the vector store, with options like “Sync”, “Async”, or “Off”.",
                 "options": ["Sync", "Async", "Off"],
                 "advanced": True,
             },
             "pre_delete_collection": {
                 "display_name": "Pre Delete Collection",
-                "info": "Pre delete collection",
+                "info": "Boolean flag to determine whether to delete the collection before creating a new one.",
                 "advanced": True,
             },
             "metadata_indexing_include": {
                 "display_name": "Metadata Indexing Include",
-                "info": "Metadata Indexing Include",
+                "info": "Optional list of metadata fields to include in the indexing.",
                 "advanced": True,
             },
             "metadata_indexing_exclude": {
                 "display_name": "Metadata Indexing Exclude",
-                "info": "Metadata Indexing Exclude",
+                "info": "Optional list of metadata fields to exclude from the indexing.",
                 "advanced": True,
             },
             "collection_indexing_policy": {
                 "display_name": "Collection Indexing Policy",
-                "info": "Collection Indexing Policy",
+                "info": "Optional dictionary defining the indexing policy for the collection.",
                 "advanced": True,
             },
         }
@@ -77,9 +99,9 @@ class AstraDBSearchComponent(LCVectorStoreComponent):
         embedding: Embeddings,
         collection_name: str,
         input_value: Text,
+        token: str,
+        api_endpoint: str,
         search_type: str = "Similarity",
-        token: Optional[str] = None,
-        api_endpoint: Optional[str] = None,
         namespace: Optional[str] = None,
         metric: Optional[str] = None,
         batch_size: Optional[int] = None,

src/backend/base/langflow/components/vectorsearch/__init__.py

@@ -0,0 +1,25 @@
+from .AstraDBSearch import AstraDBSearchComponent
+from .ChromaSearch import ChromaSearchComponent
+from .FAISSSearch import FAISSSearchComponent
+from .MongoDBAtlasVectorSearch import MongoDBAtlasSearchComponent
+from .PineconeSearch import PineconeSearchComponent
+from .QdrantSearch import QdrantSearchComponent
+from .RedisSearch import RedisSearchComponent
+from .SupabaseVectorStoreSearch import SupabaseSearchComponent
+from .VectaraSearch import VectaraSearchComponent
+from .WeaviateSearch import WeaviateSearchVectorStore
+from .pgvectorSearch import PGVectorSearchComponent
+
+__all__ = [
+    "AstraDBSearchComponent",
+    "ChromaSearchComponent",
+    "FAISSSearchComponent",
+    "MongoDBAtlasSearchComponent",
+    "PineconeSearchComponent",
+    "QdrantSearchComponent",
+    "RedisSearchComponent",
+    "SupabaseSearchComponent",
+    "VectaraSearchComponent",
+    "WeaviateSearchVectorStore",
+    "PGVectorSearchComponent",
+]

src/backend/base/langflow/components/vectorstores/AstraDB.py

@@ -16,53 +16,78 @@ class AstraDBVectorStoreComponent(CustomComponent):
 
     def build_config(self):
         return {
-            "inputs": {"display_name": "Inputs", "info": "Inputs to AstraDB"},
+            "inputs": {
+                "display_name": "Inputs",
+                "info": "Optional list of records to be processed and stored in the vector store.",
+            },
             "embedding": {"display_name": "Embedding", "info": "Embedding to use"},
-            "collection_name": {"display_name": "Collection Name", "info": "Collection name"},
+            "collection_name": {
-            "token": {"display_name": "Token", "info": "Token to use", "password": True},
+                "display_name": "Collection Name",
-            "api_endpoint": {"display_name": "API Endpoint", "info": "API Endpoint to use"},
+                "info": "The name of the collection within AstraDB where the vectors will be stored.",
-            "namespace": {"display_name": "Namespace", "info": "Namespace to use", "advanced": True},
+            },
-            "metric": {"display_name": "Metric", "info": "Metric to use", "advanced": True},
+            "token": {
-            "batch_size": {"display_name": "Batch Size", "info": "Batch size to use", "advanced": True},
+                "display_name": "Token",
+                "info": "Authentication token for accessing AstraDB.",
+                "password": True,
+            },
+            "api_endpoint": {
+                "display_name": "API Endpoint",
+                "info": "API endpoint URL for the AstraDB service.",
+            },
+            "namespace": {
+                "display_name": "Namespace",
+                "info": "Optional namespace within AstraDB to use for the collection.",
+                "advanced": True,
+            },
+            "metric": {
+                "display_name": "Metric",
+                "info": "Optional distance metric for vector comparisons in the vector store.",
+                "advanced": True,
+            },
+            "batch_size": {
+                "display_name": "Batch Size",
+                "info": "Optional number of records to process in a single batch.",
+                "advanced": True,
+            },
             "bulk_insert_batch_concurrency": {
                 "display_name": "Bulk Insert Batch Concurrency",
-                "info": "Bulk Insert Batch Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations.",
                 "advanced": True,
             },
             "bulk_insert_overwrite_concurrency": {
                 "display_name": "Bulk Insert Overwrite Concurrency",
-                "info": "Bulk Insert Overwrite Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations that overwrite existing records.",
                 "advanced": True,
             },
             "bulk_delete_concurrency": {
                 "display_name": "Bulk Delete Concurrency",
-                "info": "Bulk Delete Concurrency to use",
+                "info": "Optional concurrency level for bulk delete operations.",
                 "advanced": True,
             },
             "setup_mode": {
                 "display_name": "Setup Mode",
-                "info": "Setup mode for the vector store",
+                "info": "Configuration mode for setting up the vector store, with options like “Sync”, “Async”, or “Off”.",
                 "options": ["Sync", "Async", "Off"],
                 "advanced": True,
             },
             "pre_delete_collection": {
                 "display_name": "Pre Delete Collection",
-                "info": "Pre delete collection",
+                "info": "Boolean flag to determine whether to delete the collection before creating a new one.",
                 "advanced": True,
             },
             "metadata_indexing_include": {
                 "display_name": "Metadata Indexing Include",
-                "info": "Metadata Indexing Include",
+                "info": "Optional list of metadata fields to include in the indexing.",
                 "advanced": True,
             },
             "metadata_indexing_exclude": {
                 "display_name": "Metadata Indexing Exclude",
-                "info": "Metadata Indexing Exclude",
+                "info": "Optional list of metadata fields to exclude from the indexing.",
                 "advanced": True,
             },
             "collection_indexing_policy": {
                 "display_name": "Collection Indexing Policy",
-                "info": "Collection Indexing Policy",
+                "info": "Optional dictionary defining the indexing policy for the collection.",
                 "advanced": True,
             },
         }
@@ -70,17 +95,17 @@ class AstraDBVectorStoreComponent(CustomComponent):
     def build(
         self,
         embedding: Embeddings,
+        token: str,
+        api_endpoint: str,
         collection_name: str,
         inputs: Optional[List[Record]] = None,
-        token: Optional[str] = None,
-        api_endpoint: Optional[str] = None,
         namespace: Optional[str] = None,
         metric: Optional[str] = None,
         batch_size: Optional[int] = None,
         bulk_insert_batch_concurrency: Optional[int] = None,
         bulk_insert_overwrite_concurrency: Optional[int] = None,
         bulk_delete_concurrency: Optional[int] = None,
-        setup_mode: str = "Sync",
+        setup_mode: str = "Async",
         pre_delete_collection: bool = False,
         metadata_indexing_include: Optional[List[str]] = None,
         metadata_indexing_exclude: Optional[List[str]] = None,

src/backend/base/langflow/components/vectorstores/__init__.py

@@ -1,44 +1,26 @@
+from .AstraDB import AstraDBVectorStoreComponent
 from .Chroma import ChromaComponent
-from .ChromaSearch import ChromaSearchComponent
 from .FAISS import FAISSComponent
-from .FAISSSearch import FAISSSearchComponent
 from .MongoDBAtlasVector import MongoDBAtlasComponent
-from .MongoDBAtlasVectorSearch import MongoDBAtlasSearchComponent
 from .Pinecone import PineconeComponent
-from .PineconeSearch import PineconeSearchComponent
 from .Qdrant import QdrantComponent
-from .QdrantSearch import QdrantSearchComponent
 from .Redis import RedisComponent
-from .RedisSearch import RedisSearchComponent
 from .SupabaseVectorStore import SupabaseComponent
-from .SupabaseVectorStoreSearch import SupabaseSearchComponent
 from .Vectara import VectaraComponent
-from .VectaraSearch import VectaraSearchComponent
 from .Weaviate import WeaviateVectorStoreComponent
-from .WeaviateSearch import WeaviateSearchVectorStore
 from .pgvector import PGVectorComponent
-from .pgvectorSearch import PGVectorSearchComponent
 
 __all__ = [
+    "AstraDBVectorStoreComponent",
     "ChromaComponent",
-    "ChromaSearchComponent",
     "FAISSComponent",
-    "FAISSSearchComponent",
     "MongoDBAtlasComponent",
-    "MongoDBAtlasSearchComponent",
     "PineconeComponent",
-    "PineconeSearchComponent",
     "QdrantComponent",
-    "QdrantSearchComponent",
     "RedisComponent",
-    "RedisSearchComponent",
     "SupabaseComponent",
-    "SupabaseSearchComponent",
     "VectaraComponent",
-    "VectaraSearchComponent",
     "WeaviateVectorStoreComponent",
-    "WeaviateSearchVectorStore",
     "base",
     "PGVectorComponent",
-    "PGVectorSearchComponent",
 ]

src/backend/base/langflow/interface/custom/code_parser/code_parser.py

@@ -237,10 +237,28 @@ class CodeParser:
 
     def parse_return_statement(self, node: ast.FunctionDef) -> bool:
         """
-        Parses the return statement of a function or method node.
+        Parses the return statement of a function or method node, including nested returns.
         """
 
-        return any(isinstance(n, ast.Return) for n in node.body)
+        def has_return(node):
+            if isinstance(node, ast.Return):
+                return True
+            elif isinstance(node, ast.If):
+                return any(has_return(child) for child in node.body) or any(has_return(child) for child in node.orelse)
+            elif isinstance(node, ast.Try):
+                return (
+                    any(has_return(child) for child in node.body)
+                    or any(has_return(child) for child in node.handlers)
+                    or any(has_return(child) for child in node.finalbody)
+                )
+            elif isinstance(node, (ast.For, ast.While)):
+                return any(has_return(child) for child in node.body) or any(has_return(child) for child in node.orelse)
+            elif isinstance(node, ast.With):
+                return any(has_return(child) for child in node.body)
+            else:
+                return False
+
+        return any(has_return(child) for child in node.body)
 
     def parse_assign(self, stmt):
         """

src/backend/base/langflow/interface/initialize/utils.py

@@ -32,6 +32,8 @@ def check_tools_in_params(params: Dict):
 
 def instantiate_from_template(class_object, params: Dict):
     from_template_params = {"template": params.pop("prompt", params.pop("template", ""))}
+
+    from_template_params.update(params)
     if not from_template_params.get("template"):
         raise ValueError("Prompt template is required")
     return class_object.from_template(**from_template_params)

src/backend/base/langflow/interface/llms/base.py

@@ -4,6 +4,7 @@ from loguru import logger
 
 from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import llm_type_to_cls_dict
+from langflow.services.deps import get_settings_service
 from langflow.template.frontend_node.llms import LLMFrontendNode
 from langflow.utils.util import build_template_from_class
 
@@ -33,10 +34,11 @@ class LLMCreator(LangChainTypeCreator):
             return None
 
     def to_list(self) -> List[str]:
+        settings_service = get_settings_service()
         return [
             llm.__name__
             for llm in self.type_to_loader_dict.values()
-            # if llm.__name__ in settings_service.settings.LLMS or settings_service.settings.DEV
+            if llm.__name__ in settings_service.settings.LLMS or settings_service.settings.DEV
         ]
 
 

src/backend/langflow/version/version.py

@@ -1,7 +1,7 @@
 from importlib import metadata
 
 try:
-    __version__ = metadata.version(__package__)
+    __version__ = metadata.version("langflow")
 except metadata.PackageNotFoundError:
     __version__ = ""
 del metadata

src/frontend/package-lock.json

@@ -55,7 +55,7 @@
         "react-cookie": "^4.1.1",
         "react-dom": "^18.2.0",
         "react-error-boundary": "^4.0.11",
-        "react-icons": "^4.10.1",
+        "react-icons": "^5.0.1",
         "react-laag": "^2.0.5",
         "react-markdown": "^8.0.7",
         "react-router-dom": "^6.15.0",
@@ -9363,9 +9363,9 @@
       }
     },
     "node_modules/react-icons": {
-      "version": "4.12.0",
+      "version": "5.0.1",
-      "resolved": "https://registry.npmjs.org/react-icons/-/react-icons-4.12.0.tgz",
+      "resolved": "https://registry.npmjs.org/react-icons/-/react-icons-5.0.1.tgz",
-      "integrity": "sha512-IBaDuHiShdZqmfc/TwHu6+d6k2ltNCf3AszxNmjJc1KUfXdEeRJOKyNvLmAHaarhzGmTSVygNdyu8/opXv2gaw==",
+      "integrity": "sha512-WqLZJ4bLzlhmsvme6iFdgO8gfZP17rfjYEJ2m9RsZjZ+cc4k1hTzknEz63YS1MeT50kVzoa1Nz36f4BEx+Wigw==",
       "peerDependencies": {
         "react": "*"
       }

src/frontend/package.json

@@ -50,7 +50,7 @@
     "react-cookie": "^4.1.1",
     "react-dom": "^18.2.0",
     "react-error-boundary": "^4.0.11",
-    "react-icons": "^4.10.1",
+    "react-icons": "^5.0.1",
     "react-laag": "^2.0.5",
     "react-markdown": "^8.0.7",
     "react-router-dom": "^6.15.0",

src/frontend/src/CustomNodes/GenericNode/index.tsx

@@ -211,10 +211,12 @@ export default function GenericNode({
     }
   }, [validationStatus, validationStatus?.params]);
 
-  // const showNode = data.showNode ?? true;
-
   const [showNode, setShowNode] = useState(data.showNode ?? true);
 
+  useEffect(() => {
+    setShowNode(data.showNode ?? true);
+  }, [data.showNode]);
+
   const nameEditable = true;
 
   const emojiRegex = /\p{Emoji}/u;
@@ -438,7 +440,7 @@ export default function GenericNode({
                             event.preventDefault();
                           }}
                           data-testid={"title-" + data.node?.display_name}
-                          className="generic-node-tooltip-div text-primary"
+                          className="generic-node-tooltip-div cursor-text text-primary"
                         >
                           {data.node?.display_name}
                         </div>

src/frontend/src/components/DropdownButtonComponent/index.tsx

@@ -13,6 +13,8 @@ export default function DropdownButton({
   firstButtonName,
   onFirstBtnClick,
   options,
+  plusButton = false,
+  dropdownOptions = true,
 }: dropdownButtonPropsType): JSX.Element {
   const [showOptions, setShowOptions] = useState<boolean>(false);
 
@@ -23,28 +25,33 @@ export default function DropdownButton({
           <Button
             id="new-project-btn"
             variant="primary"
-            className="relative pr-10"
+            className={"relative" + dropdownOptions ? "" : " pr-10"}
             onClick={(event) => {
               event.stopPropagation();
               event.preventDefault();
               onFirstBtnClick();
             }}
           >
+            {plusButton && (
+              <IconComponent name="Plus" className="main-page-nav-button" />
+            )}
             {firstButtonName}
-            <div
+            {dropdownOptions && (
-              className="absolute right-2 items-center text-muted-foreground"
+              <div
-              onClick={(event) => {
+                className="absolute right-2 items-center text-muted-foreground"
-                event.stopPropagation();
+                onClick={(event) => {
-                event.preventDefault();
+                  event.stopPropagation();
-                setShowOptions(!showOptions);
+                  event.preventDefault();
-              }}
+                  setShowOptions(!showOptions);
-            >
+                }}
-              {!showOptions ? (
+              >
-                <IconComponent name="ChevronDown" />
+                {!showOptions ? (
-              ) : (
+                  <IconComponent name="ChevronDown" />
-                <IconComponent name="ChevronUp" />
+                ) : (
-              )}
+                  <IconComponent name="ChevronUp" />
-            </div>
+                )}
+              </div>
+            )}
           </Button>
         </DropdownMenuTrigger>
         <DropdownMenuContent

src/frontend/src/components/IOview/index.tsx

@@ -120,7 +120,7 @@ export default function IOView({
       {/* TODO ADAPT TO ALL TYPES OF INPUTS AND OUTPUTS */}
       <BaseModal.Header description={CHAT_FORM_DIALOG_SUBTITLE}>
         <div className="flex items-center">
-          <span className="pr-2">Chat</span>
+          <span className="pr-2">Interaction Panel</span>
           <IconComponent
             name="prompts"
             className="h-6 w-6 pl-1 text-foreground"

src/frontend/src/components/headerComponent/index.tsx

@@ -1,5 +1,6 @@
 import { useContext, useEffect } from "react";
-import { FaDiscord, FaGithub, FaTwitter } from "react-icons/fa";
+import { FaDiscord, FaGithub } from "react-icons/fa";
+import { RiTwitterXFill } from "react-icons/ri";
 import { Link, useLocation, useNavigate, useParams } from "react-router-dom";
 import AlertDropdown from "../../alerts/alertDropDown";
 import { USER_PROJECTS_HEADER } from "../../constants/constants";
@@ -127,7 +128,7 @@ export default function Header(): JSX.Element {
             rel="noreferrer"
             className="text-muted-foreground"
           >
-            <FaTwitter className="side-bar-button-size" />
+            <RiTwitterXFill className="side-bar-button-size" />
           </a>
           <a
             href="https://discord.gg/EqksyE2EX9"

src/frontend/src/components/inputComponent/index.tsx

@@ -99,12 +99,16 @@ export default function InputComponent({
                 type="text"
                 onBlur={onInputLostFocus}
                 value={
-                  selectedOption !== "" || !onChange ? selectedOption : value
+                  (selectedOption !== "" || !onChange) && setSelectedOption
+                    ? selectedOption
+                    : value
                 }
                 autoFocus={autoFocus}
                 disabled={disabled}
                 onClick={() => {
-                  (selectedOption !== "" || !onChange) && setShowOptions(true);
+                  (selectedOption !== "" || !onChange) &&
+                    setSelectedOption &&
+                    setShowOptions(true);
                 }}
                 required={required}
                 className={classNames(
@@ -115,8 +119,12 @@ export default function InputComponent({
                     ? " text-clip password "
                     : "",
                   editNode ? " input-edit-node " : "",
-                  password && selectedOption === "" && editNode ? "pr-8" : "",
+                  password && setSelectedOption ? "pr-16" : "",
-                  password && selectedOption === "" && !editNode ? "pr-10" : "",
+                  (!password && setSelectedOption) ||
+                    (password && !setSelectedOption)
+                    ? "pr-8"
+                    : "",
+
                   className!
                 )}
                 placeholder={password && editNode ? "Key" : placeholder}
@@ -179,18 +187,32 @@ export default function InputComponent({
                           setShowOptions(false);
                         }}
                       >
-                        <div className="flex w-full items-center justify-between">
+                        <div className="group flex w-full items-center justify-between">
                           <div className="flex items-center">
-                            <ForwardedIconComponent
+                            <div
-                              name="Check"
                               className={cn(
-                                "mr-2 h-4 w-4 text-primary",
+                                "relative mr-2 h-4 w-4",
                                 selectedOption === option
                                   ? "opacity-100"
                                   : "opacity-0"
                               )}
-                              aria-hidden="true"
+                            >
-                            />
+                              <div className="absolute opacity-100 transition-all group-hover:opacity-0">
+                                <ForwardedIconComponent
+                                  name="Check"
+                                  className="mr-2 h-4 w-4 text-primary"
+                                  aria-hidden="true"
+                                />
+                              </div>
+                              <div className="absolute opacity-0 transition-all group-hover:opacity-100">
+                                <ForwardedIconComponent
+                                  name="X"
+                                  className="mr-2 h-4 w-4 text-status-red"
+                                  aria-hidden="true"
+                                />
+                              </div>
+                            </div>
+
                             {option}
                           </div>
                           {optionButton && optionButton(option)}
@@ -206,10 +228,12 @@ export default function InputComponent({
           <div
             className={cn(
               "pointer-events-auto absolute inset-y-0 h-full w-full cursor-pointer",
-              selectedOption !== "" || !onChange ? "" : "hidden"
+              (selectedOption !== "" || !onChange) && setSelectedOption
+                ? ""
+                : "hidden"
             )}
             onClick={
-              selectedOption !== "" || !onChange
+              (selectedOption !== "" || !onChange) && setSelectedOption
                 ? (e) => {
                     setShowOptions((old) => !old);
                     e.preventDefault();
@@ -221,30 +245,32 @@ export default function InputComponent({
         </>
       )}
 
-      <span
+      {setSelectedOption && (
-        className={cn(
+        <span
-          password && selectedOption === "" ? "right-8" : "right-0",
-          "absolute inset-y-0 flex items-center pr-2.5"
-        )}
-      >
-        <button
-          onClick={() => {
-            setShowOptions(!showOptions);
-          }}
           className={cn(
-            selectedOption !== ""
+            password && selectedOption === "" ? "right-8" : "right-0",
-              ? "text-medium-indigo"
+            "absolute inset-y-0 flex items-center pr-2.5"
-              : "text-muted-foreground",
-            "hover:text-accent-foreground"
           )}
         >
-          <ForwardedIconComponent
+          <button
-            name={optionsIcon}
+            onClick={() => {
-            className={"h-4 w-4"}
+              setShowOptions(!showOptions);
-            aria-hidden="true"
+            }}
-          />
+            className={cn(
-        </button>
+              selectedOption !== ""
-      </span>
+                ? "text-medium-indigo"
+                : "text-muted-foreground",
+              "hover:text-accent-foreground"
+            )}
+          >
+            <ForwardedIconComponent
+              name={optionsIcon}
+              className={"h-4 w-4"}
+              aria-hidden="true"
+            />
+          </button>
+        </span>
+      )}
 
       {password && selectedOption === "" && (
         <button

src/frontend/src/constants/constants.ts

@@ -107,7 +107,7 @@ export const CODE_DIALOG_SUBTITLE =
  * @constant
  */
 export const CHAT_FORM_DIALOG_SUBTITLE =
-  "Set up the input variables defined in prompt templates. Interact with agents and chains.";
+  "Adjust or overwrite input values, inspect outputs or interact through the chat console.";
 
 /**
  * The base text for subtitle of Edit Node Dialog
@@ -732,12 +732,12 @@ export const PRIORITY_SIDEBAR_ORDER = [
   "saved_components",
   "inputs",
   "outputs",
-  "prompts",
   "data",
   "prompt",
   "models",
+  "vectorstores",
+  "vectorsearch",
   "helpers",
-  "experimental",
 ];
 export const NATIVE_CATEGORIES = [
   "inputs",

src/frontend/src/modals/formModal/chatInput/index.tsx

@@ -33,7 +33,7 @@ export default function ChatInput({
     <div className="relative">
       <Textarea
         onKeyDown={(event) => {
-          if (event.key === "Enter" && !lockChat && !event.shiftKey) {
+          if (event.key === "Enter" && !event.nativeEvent.isComposing && !lockChat && !event.shiftKey) {
             sendMessage();
           }
         }}

src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx

@@ -5,7 +5,6 @@ import ShadTooltip from "../../../../components/ShadTooltipComponent";
 import IconComponent from "../../../../components/genericIconComponent";
 import { Input } from "../../../../components/ui/input";
 import { Separator } from "../../../../components/ui/separator";
-import { PRIORITY_SIDEBAR_ORDER } from "../../../../constants/constants";
 import ExportModal from "../../../../modals/exportModal";
 import ShareModal from "../../../../modals/shareModal";
 import useAlertStore from "../../../../stores/alertStore";
@@ -282,35 +281,7 @@ export default function ExtraSidebar(): JSX.Element {
                     </div>
                   </div>
                 )}
-                {index === PRIORITY_SIDEBAR_ORDER.length - 1 && (
-                  <>
-                    <a
-                      target={"_blank"}
-                      href="https://langflow.store"
-                      className="components-disclosure-arrangement"
-                    >
-                      <div className="flex gap-4">
-                        {/* BUG ON THIS ICON */}
-                        <SparklesIcon
-                          strokeWidth={1.5}
-                          className="w-[22px] text-primary"
-                        />
 
-                        <span className="components-disclosure-title">
-                          Discover More
-                        </span>
-                      </div>
-                      <div className="components-disclosure-div">
-                        <div>
-                          <LinkIcon className="h-4 w-4 text-foreground" />
-                        </div>
-                      </div>
-                    </a>
-                    <div className="p-2 px-4 text-sm font-semibold" key={index}>
-                      Legacy Components
-                    </div>
-                  </>
-                )}
                 <DisclosureComponent
                   openDisc={
                     getFilterEdge.length !== 0 || search.length !== 0
@@ -371,6 +342,32 @@ export default function ExtraSidebar(): JSX.Element {
                       ))}
                   </div>
                 </DisclosureComponent>
+                {index === Object.keys(dataFilter).length - 1 && (
+                  <>
+                    <a
+                      target={"_blank"}
+                      href="https://langflow.store"
+                      className="components-disclosure-arrangement"
+                    >
+                      <div className="flex gap-4">
+                        {/* BUG ON THIS ICON */}
+                        <SparklesIcon
+                          strokeWidth={1.5}
+                          className="w-[22px] text-primary"
+                        />
+
+                        <span className="components-disclosure-title">
+                          Discover More
+                        </span>
+                      </div>
+                      <div className="components-disclosure-div">
+                        <div>
+                          <LinkIcon className="h-4 w-4 text-foreground" />
+                        </div>
+                      </div>
+                    </a>
+                  </>
+                )}
               </>
             ) : (
               <div key={index}></div>

src/frontend/src/pages/FlowPage/components/nodeToolbarComponent/index.tsx

@@ -85,7 +85,9 @@ export default function NodeToolbarComponent({
   const [showModalAdvanced, setShowModalAdvanced] = useState(false);
   const [showconfirmShare, setShowconfirmShare] = useState(false);
   const [showOverrideModal, setShowOverrideModal] = useState(false);
-  const [flowComponent, setFlowComponent] = useState<FlowType>();
+  const [flowComponent, setFlowComponent] = useState<FlowType>(
+    createFlowComponent(cloneDeep(data), version)
+  );
 
   const openInNewTab = (url) => {
     window.open(url, "_blank", "noreferrer");
@@ -285,7 +287,13 @@ export default function NodeToolbarComponent({
         event.preventDefault();
         setShowconfirmShare((state) => !state);
       }
-      if (selected && (event.ctrlKey || event.metaKey) && event.key === "q") {
+
+      if (
+        selected &&
+        (event.ctrlKey || event.metaKey) &&
+        event.shiftKey &&
+        event.key === "Q"
+      ) {
         event.preventDefault();
         if (isMinimal) {
           setShowState((show) => !show);
@@ -341,6 +349,10 @@ export default function NodeToolbarComponent({
           title: `${data.id} docs is not available at the moment.`,
         });
       }
+      if (selected && (event.ctrlKey || event.metaKey) && event.key === "j") {
+        event.preventDefault();
+        downloadNode(flowComponent!);
+      }
     }
 
     document.addEventListener("keydown", onKeyDown);
@@ -499,15 +511,17 @@ export default function NodeToolbarComponent({
                   />
                 </SelectItem>
               )}
-              {!hasStore && (
+              {(!hasStore || !hasApiKey || !validApiKey) && (
                 <SelectItem value={"Download"}>
-                  <div className="flex">
+                  <ToolbarSelectItem
-                    <IconComponent
+                    value="Download"
-                      name="Download"
+                    shift={false}
-                      className="relative top-0.5 mr-2 h-4 w-4"
+                    isMac={navigator.userAgent.toUpperCase().includes("MAC")}
-                    />{" "}
+                    icon="Download"
-                    Download{" "}
+                    styleObj={{ iconClasses: "relative top-0.5 mr-2 h-4 w-4" }}
-                  </div>{" "}
+                    keyboardKey={"J"}
+                    dataTestId={"Dowload-button-nodeToolbar"}
+                  />
                 </SelectItem>
               )}
               <SelectItem
@@ -525,24 +539,14 @@ export default function NodeToolbarComponent({
               </SelectItem>
               {isMinimal && (
                 <SelectItem value={"show"}>
-                  <div className="flex">
+                  <ToolbarSelectItem
-                    <IconComponent
+                    icon={showNode ? "Minimize2" : "Maximize2"}
-                      name={showNode ? "Minimize2" : "Maximize2"}
+                    value={showNode ? "Minimize" : "Expand"}
-                      className="relative top-0.5 mr-2 h-4 w-4"
+                    isMac={navigator.userAgent.toUpperCase().includes("MAC")}
-                    />
+                    shift={true}
-                    {showNode ? "Minimize" : "Expand"}
+                    keyboardKey={"Q"}
-                    {navigator.userAgent.toUpperCase().includes("MAC") ? (
+                    dataTestId={"minimize-button-nodeToolbar"}
-                      <IconComponent
+                  />
-                        name="Command"
-                        className="absolute right-[1.25rem] top-[0.65em] h-3.5 w-3.5 stroke-2"
-                      ></IconComponent>
-                    ) : (
-                      <span className="absolute right-[1.30rem] top-[0.40em] stroke-2">
-                        Ctrl +{" "}
-                      </span>
-                    )}
-                    <span className="absolute right-2 top-[0.46em]">Q</span>
-                  </div>
                 </SelectItem>
               )}
               {isGroup && (

src/frontend/src/pages/MainPage/index.tsx

@@ -105,6 +105,8 @@ export default function HomePage(): JSX.Element {
             firstButtonName="New Project"
             onFirstBtnClick={() => setOpenModal(true)}
             options={dropdownOptions}
+            plusButton={true}
+            dropdownOptions={false}
           />
         </div>
       }

src/frontend/src/stores/darkStore.tsx

@@ -4,7 +4,7 @@ import { DarkStoreType } from "../types/zustand/dark";
 
 const startedStars = Number(window.localStorage.getItem("githubStars")) ?? 0;
 
-export const useDarkStore = create<DarkStoreType>((set) => ({
+export const useDarkStore = create<DarkStoreType>((set, get) => ({
   dark: JSON.parse(window.localStorage.getItem("isDark")!) ?? false,
   stars: startedStars,
   version: "",
@@ -15,14 +15,23 @@ export const useDarkStore = create<DarkStoreType>((set) => ({
     });
   },
   refreshStars: () => {
-    if (window.localStorage.getItem("githubStars") !== null) {
+    let lastUpdated = window.localStorage.getItem("githubStarsLastUpdated");
-      set(() => ({ stars: startedStars }));
+    let diff = 0;
-      return;
+    // check if lastUpdated actually exists
+    if (lastUpdated !== null) {
+      diff = Math.abs(new Date().getTime() - new Date(lastUpdated).getTime());
     }
 
-    getRepoStars("logspace-ai", "langflow").then((res) => {
+    // if lastUpdated is null or the difference is greater than 2 hours
-      window.localStorage.setItem("githubStars", res.toString());
+    if (lastUpdated === null || diff > 7200000) {
-      set(() => ({ stars: res }));
+      getRepoStars("logspace-ai", "langflow").then((res) => {
-    });
+        window.localStorage.setItem("githubStars", res.toString());
+        window.localStorage.setItem(
+          "githubStarsLastUpdated",
+          new Date().toString()
+        );
+        set(() => ({ stars: res, lastUpdated: new Date() }));
+      });
+    }
   },
 }));

src/frontend/src/types/components/index.ts

@@ -689,6 +689,8 @@ export type dropdownButtonPropsType = {
   firstButtonName: string;
   onFirstBtnClick: () => void;
   options: Array<{ name: string; onBtnClick: () => void }>;
+  plusButton?: boolean;
+  dropdownOptions?: boolean;
 };
 
 export type IOInputProps = {

src/frontend/src/utils/buildUtils.ts

@@ -119,6 +119,8 @@ export async function buildVertices({
       try {
         onValidateNodes(verticesOrderResponse.verticesToRun);
       } catch (e) {
+        useFlowStore.getState().setIsBuilding(false);
+
         return;
       }
     }

src/frontend/src/utils/reactflowUtils.ts

@@ -1170,7 +1170,7 @@ export function downloadNode(NodeFLow: FlowType) {
     type: "application/json",
   });
   element.href = URL.createObjectURL(file);
-  element.download = `${NodeFLow.name}.json`;
+  element.download = `${NodeFLow?.name??"node"}.json`;
   element.click();
 }
 

src/frontend/src/utils/styleUtils.ts

@@ -236,6 +236,7 @@ export const nodeColors: { [char: string]: string } = {
   embeddings: "#42BAA7",
   documentloaders: "#7AAE42",
   vectorstores: "#AA8742",
+  vectorsearch: "#AA8742",
   textsplitters: "#B47CB5",
   toolkits: "#DB2C2C",
   wrappers: "#E6277A",
@@ -248,6 +249,7 @@ export const nodeColors: { [char: string]: string } = {
   retrievers: "#e6b25a",
   unknown: "#9CA3AF",
   custom_components: "#ab11ab",
+  Record:"#31a3cc"
 };
 
 export const nodeNames: { [char: string]: string } = {
@@ -267,6 +269,7 @@ export const nodeNames: { [char: string]: string } = {
   embeddings: "Embeddings",
   documentloaders: "Loaders",
   vectorstores: "Vector Stores",
+  vectorsearch: "Vector Search",
   toolkits: "Toolkits",
   wrappers: "Wrappers",
   textsplitters: "Text Splitters",
@@ -369,6 +372,7 @@ export const nodeIconsLucide: iconsType = {
   saved_components: GradientSave,
   documentloaders: Paperclip,
   vectorstores: Layers,
+  vectorsearch: Search,
   toolkits: Package2,
   textsplitters: Scissors,
   wrappers: Gift,
@@ -387,7 +391,6 @@ export const nodeIconsLucide: iconsType = {
   Trash2,
   Boxes,
   Network,
-  X,
   XCircle,
   Info,
   CheckCircle2,

src/frontend/tests/end-to-end/assets/ChatTest.json

@@ -0,0 +1,358 @@
+{
+  "id": "3f5e860d-1676-4fba-9d86-06db9f51e43a",
+  "data": {
+    "nodes": [
+      {
+        "id": "ChatInput-7hPDT",
+        "type": "genericNode",
+        "position": {
+          "x": 687,
+          "y": 41.9375
+        },
+        "data": {
+          "type": "ChatInput",
+          "node": {
+            "template": {
+              "code": {
+                "type": "code",
+                "required": true,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Used to get user input from the chat.\"\n    icon = \"ChatInput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "code",
+                "advanced": true,
+                "dynamic": true,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "input_value": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "input_value",
+                "display_name": "Message",
+                "advanced": false,
+                "input_types": ["Text"],
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "return_record": {
+                "type": "bool",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "return_record",
+                "display_name": "Return Record",
+                "advanced": false,
+                "dynamic": false,
+                "info": "Return the message as a record containing the sender, sender_name, and session_id.",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "sender": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": true,
+                "show": true,
+                "multiline": false,
+                "value": "User",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "options": ["Machine", "User"],
+                "name": "sender",
+                "display_name": "Sender Type",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "sender_name": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": "User",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "sender_name",
+                "display_name": "Sender Name",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "session_id": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "session_id",
+                "display_name": "Session ID",
+                "advanced": true,
+                "dynamic": false,
+                "info": "If provided, the message will be stored in the memory.",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "_type": "CustomComponent"
+            },
+            "description": "Used to get user input from the chat.",
+            "icon": "ChatInput",
+            "base_classes": ["Text", "object", "str", "Record"],
+            "display_name": "Chat Input",
+            "documentation": "",
+            "custom_fields": {
+              "sender": null,
+              "sender_name": null,
+              "input_value": null,
+              "session_id": null,
+              "return_record": null
+            },
+            "output_types": ["Text", "Record"],
+            "field_formatters": {},
+            "frozen": false,
+            "field_order": [],
+            "beta": false
+          },
+          "id": "ChatInput-7hPDT"
+        },
+        "selected": false,
+        "width": 384,
+        "height": 569,
+        "positionAbsolute": {
+          "x": 687,
+          "y": 41.9375
+        },
+        "dragging": false
+      },
+      {
+        "id": "ChatOutput-4sm9Z",
+        "type": "genericNode",
+        "position": {
+          "x": 4.939451516507972,
+          "y": 103.3695231904992
+        },
+        "data": {
+          "type": "ChatOutput",
+          "node": {
+            "template": {
+              "code": {
+                "type": "code",
+                "required": true,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Used to send a message to the chat.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "code",
+                "advanced": true,
+                "dynamic": true,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "input_value": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "input_value",
+                "display_name": "Message",
+                "advanced": false,
+                "input_types": ["Text"],
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "return_record": {
+                "type": "bool",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "return_record",
+                "display_name": "Return Record",
+                "advanced": false,
+                "dynamic": false,
+                "info": "Return the message as a record containing the sender, sender_name, and session_id.",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "sender": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": true,
+                "show": true,
+                "multiline": false,
+                "value": "Machine",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "options": ["Machine", "User"],
+                "name": "sender",
+                "display_name": "Sender Type",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "sender_name": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": "AI",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "sender_name",
+                "display_name": "Sender Name",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "session_id": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "session_id",
+                "display_name": "Session ID",
+                "advanced": true,
+                "dynamic": false,
+                "info": "If provided, the message will be stored in the memory.",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "_type": "CustomComponent"
+            },
+            "description": "Used to send a message to the chat.",
+            "icon": "ChatOutput",
+            "base_classes": ["Text", "object", "str", "Record"],
+            "display_name": "Chat Output",
+            "documentation": "",
+            "custom_fields": {
+              "sender": null,
+              "sender_name": null,
+              "input_value": null,
+              "session_id": null,
+              "return_record": null
+            },
+            "output_types": ["Text", "Record"],
+            "field_formatters": {},
+            "frozen": false,
+            "field_order": [],
+            "beta": false
+          },
+          "id": "ChatOutput-4sm9Z"
+        },
+        "selected": true,
+        "width": 384,
+        "height": 569,
+        "positionAbsolute": {
+          "x": 4.939451516507972,
+          "y": 103.3695231904992
+        },
+        "dragging": false
+      }
+    ],
+    "edges": [
+      {
+        "source": "ChatOutput-4sm9Z",
+        "sourceHandle": "{œbaseClassesœ:[œTextœ,œobjectœ,œstrœ,œRecordœ],œdataTypeœ:œChatOutputœ,œidœ:œChatOutput-4sm9Zœ}",
+        "target": "ChatInput-7hPDT",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatInput-7hPDTœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
+        "data": {
+          "targetHandle": {
+            "fieldName": "input_value",
+            "id": "ChatInput-7hPDT",
+            "inputTypes": ["Text"],
+            "type": "str"
+          },
+          "sourceHandle": {
+            "baseClasses": ["Text", "object", "str", "Record"],
+            "dataType": "ChatOutput",
+            "id": "ChatOutput-4sm9Z"
+          }
+        },
+        "style": {
+          "stroke": "#555"
+        },
+        "className": "stroke-gray-900 stroke-connection",
+        "id": "reactflow__edge-ChatOutput-4sm9Z{œbaseClassesœ:[œTextœ,œobjectœ,œstrœ,œRecordœ],œdataTypeœ:œChatOutputœ,œidœ:œChatOutput-4sm9Zœ}-ChatInput-7hPDT{œfieldNameœ:œinput_valueœ,œidœ:œChatInput-7hPDTœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
+      }
+    ],
+    "viewport": {
+      "x": 316.78239920440234,
+      "y": 182.84104875768622,
+      "zoom": 0.6070974421975234
+    }
+  },
+  "description": "flow to test ChatInput and output",
+  "name": "ChatITest",
+  "last_tested_version": "1.0.0a0",
+  "is_component": false
+}

src/frontend/tests/end-to-end/chat_io.spec.ts

@@ -0,0 +1,46 @@
+import { test } from "@playwright/test";
+import { readFileSync } from "fs";
+test.beforeEach(async ({ page }) => {
+  // await page.waitForTimeout(20000);
+  // test.setTimeout(120000);
+});
+test("chat_io_teste", async ({ page }) => {
+  await page.goto("/");
+  await page.locator("span").filter({ hasText: "My Collection" }).isVisible();
+  // Read your file into a buffer.
+  const jsonContent = readFileSync(
+    "tests/end-to-end/assets/ChatTest.json",
+    "utf-8"
+  );
+
+  // Create the DataTransfer and File
+  const dataTransfer = await page.evaluateHandle((data) => {
+    const dt = new DataTransfer();
+    // Convert the buffer to a hex array
+    const file = new File([data], "ChatTest.json", {
+      type: "application/json",
+    });
+    dt.items.add(file);
+    return dt;
+  }, jsonContent);
+
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await page.waitForTimeout(2000);
+
+  await page.getByTestId("blank-flow").click();
+  await page.waitForTimeout(2000);
+
+  // Now dispatch
+  await page.dispatchEvent(
+    '//*[@id="react-flow-id"]/div[1]/div[1]/div',
+    "drop",
+    {
+      dataTransfer,
+    }
+  );
+  await page.getByLabel("fit view").click();
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByPlaceholder("Send a message...").click();
+  await page.getByPlaceholder("Send a message...").fill("teste");
+  await page.getByRole("button").nth(1).click();
+});

src/frontend/tests/end-to-end/codeAreaModalComponent.spec.ts

@@ -25,86 +25,31 @@ test("CodeAreaModalComponent", async ({ page }) => {
   await page.getByTestId("code-button-modal").click();
 
   let value = await page.locator('//*[@id="codeValue"]').inputValue();
-
+  const code =
-  if (
+    'def python_function(text: str) -> str:\n    """This is a default python function that returns the input text"""\n    return text';
-    value !=
+  const wCode =
-    'def python_function(text: str) -> str:    """This is a default python function that returns the input text"""    return text'
+    'def python_function(text: str) -> st:    """This is a default python function that returns the input text"""    return text';
-  ) {
+  const assertCode =
-    expect(false).toBeTruthy();
+    'def python_function(text: str) -> str:    """This is a default python function that returns the input text"""    return text';
-  }
+  await page
-
+    .locator("#CodeEditor div")
+    .filter({ hasText: "def python_function(text: str" })
+    .nth(1)
+    .click();
+  await page.locator("textarea").press("Control+a");
+  await page.locator("textarea").fill(wCode);
   await page.locator('//*[@id="checkAndSaveBtn"]').click();
-
+  await page.waitForTimeout(1000);
-  await page.getByTestId("div-generic-node").click();
-
-  await page.getByTestId("more-options-modal").click();
-  await page.getByTestId("edit-button-modal").click();
-
-  await page.locator('//*[@id="showdescription"]').click();
   expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
+    await page.getByText("invalid syntax (<unknown>, line 1)").isVisible()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showname"]').click();
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeFalsy();
-
-  await page.locator('//*[@id="showreturn_direct"]').click();
-  expect(
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showdescription"]').click();
-  expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
   ).toBeTruthy();
-
+  await page.locator("textarea").press("Control+a");
-  await page.locator('//*[@id="showname"]').click();
+  await page.locator("textarea").fill(wCode);
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeTruthy();
+  await page.locator("textarea").fill(code);
-
+  await page.locator('//*[@id="checkAndSaveBtn"]').click();
-  await page.locator('//*[@id="showreturn_direct"]').click();
+  expect(await page.getByText("Code is ready to run").isVisible()).toBeTruthy();
-  expect(
+  await page.getByTestId("code-button-modal").click();
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
+  expect(await page.locator('//*[@id="codeValue"]').inputValue()).toBe(
-  ).toBeTruthy();
+    assertCode
-
+  );
-  await page.locator('//*[@id="showdescription"]').click();
-  expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showname"]').click();
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeFalsy();
-
-  await page.locator('//*[@id="showreturn_direct"]').click();
-  expect(
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showdescription"]').click();
-  expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
-  ).toBeTruthy();
-
-  await page.locator('//*[@id="showname"]').click();
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeTruthy();
-
-  await page.locator('//*[@id="showreturn_direct"]').click();
-  expect(
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
-  ).toBeTruthy();
-
-  await page.locator('//*[@id="saveChangesBtn"]').click();
-
-  const plusButtonLocator = page.locator('//*[@id="code-input-0"]');
-  const elementCount = await plusButtonLocator.count();
-  if (elementCount === 0) {
-    expect(true).toBeTruthy();
-
-    await page.getByTestId("more-options-modal").click();
-    await page.getByTestId("edit-button-modal").click();
-
-    await page.locator('//*[@id="saveChangesBtn"]').click();
-
-    await page.getByTestId("div-generic-node").click();
-    await page.getByTestId("code-button-modal").click();
-  }
 });

src/frontend/tests/end-to-end/curl_api_generation.spec.ts

@@ -0,0 +1,17 @@
+import { expect, test } from "@playwright/test";
+
+test("curl_api_generation", async ({ page, context }) => {
+  await page.goto("/");
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  await page.getByRole("heading", { name: "Data Ingestion" }).click();
+  await page.waitForTimeout(2000);
+  await page.getByText("API", { exact: true }).click();
+  await page.getByRole("tab", { name: "cURL" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent = await handle.jsonValue();
+  expect(clipboardContent.length).toBeGreaterThan(0);
+});

src/frontend/tests/end-to-end/python_api_generation.spec.ts

@@ -0,0 +1,17 @@
+import { expect, test } from "@playwright/test";
+
+test("python_api_generation", async ({ page, context }) => {
+  await page.goto("/");
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  await page.getByRole("heading", { name: "Data Ingestion" }).click();
+  await page.waitForTimeout(2000);
+  await page.getByText("API", { exact: true }).click();
+  await page.getByRole("tab", { name: "Python API" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent = await handle.jsonValue();
+  expect(clipboardContent.length).toBeGreaterThan(0);
+});

src/frontend/tests/end-to-end/tweaks_test.spec.ts

@@ -0,0 +1,38 @@
+import { expect, test } from "@playwright/test";
+
+test("curl_api_generation", async ({ page, context }) => {
+  await page.goto("/");
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  await page.getByRole("heading", { name: "Data Ingestion" }).click();
+  await page.waitForTimeout(2000);
+  await page.getByText("API", { exact: true }).click();
+  await page.getByRole("tab", { name: "cURL" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent = await handle.jsonValue();
+  const oldValue = clipboardContent;
+  expect(clipboardContent.length).toBeGreaterThan(0);
+  await page.getByRole("tab", { name: "Tweaks" }).click();
+  await page
+    .getByRole("heading", { name: "URL" })
+    .locator("div")
+    .first()
+    .click();
+  await page.getByRole("textbox", { name: "Type something..." }).click();
+  await page
+    .getByRole("textbox", { name: "Type something..." })
+    .press("Control+a");
+  await page.getByRole("textbox", { name: "Type something..." }).fill("teste");
+  await page.getByRole("tab", { name: "cURL" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle2 = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent2 = await handle2.jsonValue();
+  const newValue = clipboardContent2;
+  expect(oldValue).not.toBe(newValue);
+  expect(clipboardContent2.length).toBeGreaterThan(clipboardContent.length);
+});