ci: script and workflow to update starter projects (#5195)

.github/workflows/py_autofix.yml

@@ -19,3 +19,25 @@ jobs:
       - uses: autofix-ci/action@ff86a557419858bb967097bfc916833f5647fa8c
       - name: Minimize uv cache
         run: uv cache prune --ci
+
+  update-starter-projects:
+    name: Update Starter Projects
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: "Setup Environment"
+        uses: ./.github/actions/setup-uv
+
+      - name: "Install dependencies"
+        run: |
+          uv sync --frozen
+          uv pip install -e .
+
+      - name: Run starter projects update
+        run: uv run python scripts/ci/update_starter_projects.py
+
+      - uses: autofix-ci/action@ff86a557419858bb967097bfc916833f5647fa8c
+
+      - name: Minimize uv cache
+        run: uv cache prune --ci
+

.github/workflows/style-check-py.yml

@@ -6,10 +6,6 @@ on:
     paths:
       - "**/*.py"
 
-
-
-
-
 jobs:
   lint:
     name: Ruff Style Check

scripts/ci/update_starter_projects.py

@@ -0,0 +1,43 @@
+"""Script to update Langflow starter projects with the latest component versions."""
+
+import asyncio
+import os
+
+import langflow.main  # noqa: F401
+from langflow.initial_setup.setup import (
+    get_project_data,
+    load_starter_projects,
+    update_edges_with_latest_component_versions,
+    update_project_file,
+    update_projects_components_with_latest_component_versions,
+)
+from langflow.interface.types import get_and_cache_all_types_dict
+from langflow.services.deps import get_settings_service
+from langflow.services.utils import initialize_services
+
+
+async def main():
+    """Updates the starter projects with the latest component versions.
+
+    Copies the code from langflow/initial_setup/setup.py. Doesn't use the
+    create_or_update_starter_projects function directly to avoid sql interactions.
+    """
+    await initialize_services(fix_migration=False)
+    all_types_dict = await get_and_cache_all_types_dict(get_settings_service())
+
+    starter_projects = await load_starter_projects()
+    for project_path, project in starter_projects:
+        _, _, _, _, project_data, _, _, _, _ = get_project_data(project)
+        do_update_starter_projects = os.environ.get("LANGFLOW_UPDATE_STARTER_PROJECTS", "true").lower() == "true"
+        if do_update_starter_projects:
+            updated_project_data = update_projects_components_with_latest_component_versions(
+                project_data.copy(), all_types_dict
+            )
+            updated_project_data = update_edges_with_latest_component_versions(updated_project_data)
+            if updated_project_data != project_data:
+                project_data = updated_project_data
+                await update_project_file(project_path, project, updated_project_data)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

src/backend/base/langflow/initial_setup/setup.py

@@ -611,7 +611,13 @@ async def find_existing_flow(session, flow_id, flow_endpoint_name):
     return None
 
 
-async def create_or_update_starter_projects(all_types_dict: dict) -> None:
+async def create_or_update_starter_projects(all_types_dict: dict, *, do_create: bool = True) -> None:
+    """Create or update starter projects.
+
+    Args:
+        all_types_dict (dict): Dictionary containing all component types and their templates
+        do_create (bool, optional): Whether to create new projects. Defaults to True.
+    """
     async with async_session_scope() as session:
         new_folder = await create_starter_folder(session)
         starter_projects = await load_starter_projects()
@@ -639,7 +645,7 @@ async def create_or_update_starter_projects(all_types_dict: dict) -> None:
                     project_data = updated_project_data
                     # We also need to update the project data in the file
                     await update_project_file(project_path, project, updated_project_data)
-            if project_name and project_data:
+            if do_create and project_name and project_data:
                 for existing_project in await get_all_flows_similar_to_project(session, new_folder.id):
                     await session.delete(existing_project)
 

src/backend/base/langflow/initial_setup/starter_projects/Custom Component Maker.json

@@ -920,7 +920,7 @@
                 "show": true,
                 "title_case": false,
                 "type": "code",
-                "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n    display_name: str = \"Prompt\"\n    description: str = \"Create a prompt template with dynamic variables.\"\n    icon = \"prompts\"\n    trace_type = \"prompt\"\n    name = \"Prompt\"\n\n    inputs = [\n        PromptInput(name=\"template\", display_name=\"Template\"),\n        MessageTextInput(\n            name=\"tool_placeholder\",\n            display_name=\"Tool Placeholder\",\n            tool_mode=True,\n            advanced=True,\n            info=\"A placeholder input for tool mode.\",\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n    ]\n\n    async def build_prompt(self) -> Message:\n        prompt = Message.from_template(**self._attributes)\n        self.status = prompt.text\n        return prompt\n\n    def _update_template(self, frontend_node: dict):\n        prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n        custom_fields = frontend_node[\"custom_fields\"]\n        frontend_node_template = frontend_node[\"template\"]\n        _ = process_prompt_template(\n            template=prompt_template,\n            name=\"template\",\n            custom_fields=custom_fields,\n            frontend_node_template=frontend_node_template,\n        )\n        return frontend_node\n\n    def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n        \"\"\"This function is called after the code validation is done.\"\"\"\n        frontend_node = super().post_code_processing(new_frontend_node, current_frontend_node)\n        template = frontend_node[\"template\"][\"template\"][\"value\"]\n        # Kept it duplicated for backwards compatibility\n        _ = process_prompt_template(\n            template=template,\n            name=\"template\",\n            custom_fields=frontend_node[\"custom_fields\"],\n            frontend_node_template=frontend_node[\"template\"],\n        )\n        # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n        # and update the frontend_node with those values\n        update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n        return frontend_node\n\n    def _get_fallback_input(self, **kwargs):\n        return DefaultPromptField(**kwargs)\n"
+                "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n    display_name: str = \"Prompt\"\n    description: str = \"Create a prompt template with dynamic variables.\"\n    icon = \"prompts\"\n    trace_type = \"prompt\"\n    name = \"Prompt\"\n\n    inputs = [\n        PromptInput(name=\"template\", display_name=\"Template\"),\n        MessageTextInput(\n            name=\"tool_placeholder\",\n            display_name=\"Tool Placeholder\",\n            tool_mode=True,\n            advanced=True,\n            info=\"A placeholder input for tool mode.\",\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n    ]\n\n    async def build_prompt(self) -> Message:\n        prompt = Message.from_template(**self._attributes)\n        self.status = prompt.text\n        return prompt\n\n    def _update_template(self, frontend_node: dict):\n        prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n        custom_fields = frontend_node[\"custom_fields\"]\n        frontend_node_template = frontend_node[\"template\"]\n        _ = process_prompt_template(\n            template=prompt_template,\n            name=\"template\",\n            custom_fields=custom_fields,\n            frontend_node_template=frontend_node_template,\n        )\n        return frontend_node\n\n    async def post_code_processing(self, new_frontend_node: dict, current_frontend_node: dict):\n        \"\"\"This function is called after the code validation is done.\"\"\"\n        frontend_node = await super().post_code_processing(new_frontend_node, current_frontend_node)\n        template = frontend_node[\"template\"][\"template\"][\"value\"]\n        # Kept it duplicated for backwards compatibility\n        _ = process_prompt_template(\n            template=template,\n            name=\"template\",\n            custom_fields=frontend_node[\"custom_fields\"],\n            frontend_node_template=frontend_node[\"template\"],\n        )\n        # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n        # and update the frontend_node with those values\n        update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n        return frontend_node\n\n    def _get_fallback_input(self, **kwargs):\n        return DefaultPromptField(**kwargs)\n"
               },
               "template": {
                 "_input_type": "PromptInput",

src/backend/base/langflow/services/tracing/arize_phoenix.py

@@ -269,9 +269,11 @@ class ArizePhoenixTracer(BaseTracer):
         if not self._ready:
             return
 
-    def _convert_to_arize_phoenix_types(self, io_dict: dict[str, Any]):
+    def _convert_to_arize_phoenix_types(self, io_dict: dict[str | Any, Any]) -> dict[str, Any]:
         """Converts data types to Arize/Phoenix compatible formats."""
-        return {key: self._convert_to_arize_phoenix_type(value) for key, value in io_dict.items()}
+        return {
+            str(key): self._convert_to_arize_phoenix_type(value) for key, value in io_dict.items() if key is not None
+        }
 
     def _convert_to_arize_phoenix_type(self, value):
         """Recursively converts a value to a Arize/Phoenix compatible type."""