fix: Make from_template_and_variables async for backwards compatibili…

…ty, add sync version, add tests and small fixes (#4500)

* Refactor `trace_name` property to use `_id` instead of `_vertex.id` for component identification

* Handle missing session_id attribute in component and agent classes

* Add SUPPORTED_VERSIONS constant for version tracking in tests

* Add utility to download components from GitHub in integration tests

* Rename TestComponent to ComponentForTesting to avoid conflict with pytest

* test: enhance PromptComponent tests for version support

Add parameterized testing for supported versions and a validation for the latest PromptComponent. This improves test coverage and ensures compatibility across different versions.

* refactor: move build_component_instance_for_tests utility to integration utils

* Make `from_template_and_variables` async for backwards compatibility and add sync version

* Refactor `PromptComponent` to use `Message.from_template` method across starter projects JSON files.

* add await to `from_template_and_variables` call

* Add async test for message prompt serialization and update cache directory handling

- Introduced `async` in `test_message_prompt_serialization` for asynchronous message creation.
- Added `test_message_sync_prompt_serialization` for synchronous message testing.
- Updated cache directory paths to "langflow_test" for test isolation.
- Utilized `monkeypatch` to set environment variable for cache directory in `langflow_cache_dir` fixture.

* Add fixture and existence check in test_schema_message.py

- Use `langflow_cache_dir` fixture in `test_message_with_single_image`.
- Add assertion to verify the existence of `second_image`.

* Add base test class to ensure file names are defined for all supported versions

* Remove default value for 'file_name' parameter in 'build_component_instance_for_tests' function

* Enhance `TestPromptComponent` with version-specific file name handling and base class integration

* Refactor test_prompt_component_versions to use FILE_NAMES_MAPPING directly

* Add component version tests and base classes for testing with/without client

* Simplify `build_component_instance_for_tests` by returning `cc_class` directly

* Refactor `TestPromptComponent` to use `ComponentTestBaseWithClient` and remove version tests

* Add assertion for LANGFLOW_CONFIG_DIR in test_message_with_multiple_images

* Refactor: update method call to `from_template` in `langchain_hub.py`

* Handle missing '_id' attribute in 'trace_name' method of custom_component.py

* Optimize `get_and_cache_all_types_dict` call by removing unnecessary thread usage in test.

src/backend/base/langflow/base/agents/agent.py

@@ -139,12 +139,19 @@ async def run_agent(
         if self.chat_history:
             input_dict["chat_history"] = data_to_messages(self.chat_history)
 
+        if hasattr(self, "graph"):
+            session_id = self.graph.session_id
+        elif hasattr(self, "_session_id"):
+            session_id = self._session_id
+        else:
+            session_id = None
+
         agent_message = Message(
             sender=MESSAGE_SENDER_AI,
             sender_name=self.display_name or "Agent",
             properties={"icon": "Bot", "state": "partial"},
             content_blocks=[ContentBlock(title="Agent Steps", contents=[])],
-            session_id=self.graph.session_id,
+            session_id=session_id,
         )
         try:
             result = await process_agent_events(

src/backend/base/langflow/components/langchain_utilities/langchain_hub.py

@@ -105,7 +105,7 @@ async def build_prompt(
         original_params["template"] = prompt_value.to_string()
 
         # Now pass the filtered attributes to the function
-        prompt = Message.from_template_and_variables(**original_params)
+        prompt = Message.from_template(**original_params)
 
         self.status = prompt.text
 

src/backend/base/langflow/components/prompts/prompt.py

@@ -22,7 +22,7 @@ class PromptComponent(Component):
     ]
 
     async def build_prompt(self) -> Message:
-        prompt = Message.from_template_and_variables(**self._attributes)
+        prompt = Message.from_template(**self._attributes)
         self.status = prompt.text
         return prompt
 

src/backend/base/langflow/custom/custom_component/component.py

@@ -792,22 +792,28 @@ async def _build_without_tracing(self):
 
     async def build_results(self):
         """Build the results of the component."""
+        if hasattr(self, "graph"):
+            session_id = self.graph.session_id
+        elif hasattr(self, "_session_id"):
+            session_id = self._session_id
+        else:
+            session_id = None
         try:
             if self._tracing_service:
                 return await self._build_with_tracing()
             return await self._build_without_tracing()
         except StreamingError as e:
             self.send_error(
                 exception=e.cause,
-                session_id=self.graph.session_id,
+                session_id=session_id,
                 trace_name=getattr(self, "trace_name", None),
                 source=e.source,
             )
             raise e.cause  # noqa: B904
         except Exception as e:
             self.send_error(
                 exception=e,
-                session_id=self.graph.session_id,
+                session_id=session_id,
                 source=Source(id=self._id, display_name=self.display_name, source=self.display_name),
                 trace_name=getattr(self, "trace_name", None),
             )

src/backend/base/langflow/custom/custom_component/custom_component.py

@@ -108,10 +108,12 @@ def set_parameters(self, parameters: dict) -> None:
 
     @property
     def trace_name(self) -> str:
-        if self._vertex is None:
-            msg = "Vertex is not set"
+        if hasattr(self, "_id") and self._id is None:
+            msg = "Component id is not set"
             raise ValueError(msg)
-        return f"{self.display_name} ({self._vertex.id})"
+        if hasattr(self, "_id"):
+            return f"{self.display_name} ({self._id})"
+        return f"{self.display_name}"
 
     def update_state(self, name: str, value: Any) -> None:
         if not self._vertex:

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json

@@ -423,7 +423,7 @@
                 "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 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    ]\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_and_variables(**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 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    ]\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"
               },
               "template": {
                 "advanced": false,

src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json

@@ -462,7 +462,7 @@
                 "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 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    ]\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_and_variables(**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 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    ]\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"
               },
               "instructions": {
                 "advanced": false,