fix: make webhook api call honor webhook component as input (langflow…

…-ai#2511)

* refactor(base.py): refactor logic to find start_component_id based on multiple keywords for improved flexibility and readability

* feat(schema.py): add WebhookInput component type to INPUT_COMPONENTS list for handling webhook inputs in the graph schema

* refactor(base.py): refactor logic to determine start_component_id based on webhook or chat component presence in input vertices

* refactor: prioritize webhook component for determining start_component_id

* feat(utils.py): add function find_start_component_id to find component ID based on priority list of input types

* refactor(graph/base.py): refactor logic to find start component id in Graph class for better readability and maintainability

* test(test_webhook.py): override pytest fixture to check for OpenAI API key in environment variables before running tests

* test(test_webhook.py): update webhook json

* feat(schema.py): update WebhookInput component type name

* refactor: log package run telemetry in simplified_run_flow

* test: add test for webhook flow on run endpoint

* refactor(graph/base.py): skip unbuilt vertices when getting vertex outputs in Graph class

* refactor: simplify data_input assignment in LCTextSplitterComponent

* refactor: remove unused build method in CharacterTextSplitterComponent

* refactor: update imports in CharacterTextSplitter.py

src/backend/base/langflow/api/v1/endpoints.py

@@ -214,11 +214,13 @@ async def simplified_run_flow(
         return result
 
     except ValueError as exc:
-        end_time = time.perf_counter()
         background_tasks.add_task(
             telemetry_service.log_package_run,
             RunPayload(
-                runIsWebhook=False, runSeconds=int(end_time - start_time), runSuccess=False, runErrorMessage=str(exc)
+                runIsWebhook=False,
+                runSeconds=int(time.perf_counter() - start_time),
+                runSuccess=False,
+                runErrorMessage=str(exc),
             ),
         )
         if "badly formed hexadecimal UUID string" in str(exc):
@@ -234,7 +236,10 @@ async def simplified_run_flow(
         background_tasks.add_task(
             telemetry_service.log_package_run,
             RunPayload(
-                runIsWebhook=False, runSeconds=int(end_time - start_time), runSuccess=False, runErrorMessage=str(exc)
+                runIsWebhook=False,
+                runSeconds=int(time.perf_counter() - start_time),
+                runSuccess=False,
+                runErrorMessage=str(exc),
             ),
         )
         raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(exc)) from exc

src/backend/base/langflow/base/textsplitters/model.py

@@ -1,7 +1,7 @@
 from abc import abstractmethod
 from typing import Any
-from langchain_text_splitters import TextSplitter
 
+from langchain_text_splitters import TextSplitter
 
 from langflow.custom import Component
 from langflow.io import Output
@@ -29,7 +29,7 @@ def split_data(self) -> list[Data]:
         documents = []
 
         if not isinstance(data_input, list):
-            data_input: list[Any] = [data_input]
+            data_input = [data_input]
 
         for _input in data_input:
             if isinstance(_input, Data):

src/backend/base/langflow/components/textsplitters/CharacterTextSplitter.py

@@ -1,10 +1,9 @@
-from typing import List, Any
+from typing import Any
 
 from langchain_text_splitters import CharacterTextSplitter, TextSplitter
 
 from langflow.base.textsplitters.model import LCTextSplitterComponent
-from langflow.inputs import IntInput, DataInput, MessageTextInput
-from langflow.schema import Data
+from langflow.inputs import DataInput, IntInput, MessageTextInput
 from langflow.utils.util import unescape_string
 
 
@@ -53,27 +52,3 @@ def build_text_splitter(self) -> TextSplitter:
             chunk_size=self.chunk_size,
             separator=separator,
         )
-
-    def build(
-        self,
-        inputs: List[Data],
-        chunk_overlap: int = 200,
-        chunk_size: int = 1000,
-        separator: str = "\n",
-    ) -> List[Data]:
-        # separator may come escaped from the frontend
-        separator = unescape_string(separator)
-        documents = []
-        for _input in inputs:
-            if isinstance(_input, Data):
-                documents.append(_input.to_lc_document())
-            else:
-                documents.append(_input)
-        docs = CharacterTextSplitter(
-            chunk_overlap=chunk_overlap,
-            chunk_size=chunk_size,
-            separator=separator,
-        ).split_documents(documents)
-        data = self.to_data(docs)
-        self.status = data
-        return data

src/backend/base/langflow/graph/graph/base.py

@@ -14,7 +14,7 @@
 from langflow.graph.graph.constants import lazy_load_vertex_dict
 from langflow.graph.graph.runnable_vertices_manager import RunnableVerticesManager
 from langflow.graph.graph.state_manager import GraphStateManager
-from langflow.graph.graph.utils import process_flow
+from langflow.graph.graph.utils import find_start_component_id, process_flow
 from langflow.graph.schema import InterfaceComponentTypes, RunOutputs
 from langflow.graph.vertex.base import Vertex
 from langflow.graph.vertex.types import InterfaceVertex, StateVertex
@@ -335,9 +335,8 @@ async def _run(
             logger.exception(exc)
 
         try:
-            start_component_id = next(
-                (vertex_id for vertex_id in self._is_input_vertices if "chat" in vertex_id.lower()), None
-            )
+            # Prioritize the webhook component if it exists
+            start_component_id = find_start_component_id(self._is_input_vertices)
             await self.process(start_component_id=start_component_id, fallback_to_env_vars=fallback_to_env_vars)
             self.increment_run_count()
         except Exception as exc:
@@ -350,6 +349,8 @@ async def _run(
         # Get the outputs
         vertex_outputs = []
         for vertex in self.vertices:
+            if not vertex._built:
+                continue
             if vertex is None:
                 raise ValueError(f"Vertex {vertex_id} not found")
 

src/backend/base/langflow/graph/graph/utils.py

@@ -1,5 +1,24 @@
-from collections import deque
 import copy
+from collections import deque
+
+PRIORITY_LIST_OF_INPUTS = ["webhook", "chat"]
+
+
+def find_start_component_id(vertices):
+    """
+    Finds the component ID from a list of vertices based on a priority list of input types.
+
+    Args:
+        vertices (list): A list of vertex IDs.
+
+    Returns:
+        str or None: The component ID that matches the highest priority input type, or None if no match is found.
+    """
+    for input_type_str in PRIORITY_LIST_OF_INPUTS:
+        component_id = next((vertex_id for vertex_id in vertices if input_type_str in vertex_id.lower()), None)
+        if component_id:
+            return component_id
+    return None
 
 
 def find_last_node(nodes, edges):

src/backend/base/langflow/graph/schema.py

@@ -54,6 +54,7 @@ class InterfaceComponentTypes(str, Enum, metaclass=ContainsEnumMeta):
     TextInput = "TextInput"
     TextOutput = "TextOutput"
     DataOutput = "DataOutput"
+    WebhookInput = "Webhook"
 
     def __contains__(cls, item):
         try:
@@ -69,6 +70,7 @@ def __contains__(cls, item):
 INPUT_COMPONENTS = [
     InterfaceComponentTypes.ChatInput,
     InterfaceComponentTypes.TextInput,
+    InterfaceComponentTypes.WebhookInput,
 ]
 OUTPUT_COMPONENTS = [
     InterfaceComponentTypes.ChatOutput,

tests/test_webhook.py

@@ -1,6 +1,13 @@
 import tempfile
 from pathlib import Path
 
+import pytest
+
+
+@pytest.fixture(autouse=True)
+def check_openai_api_key_in_environment_variables():
+    pass
+
 
 def test_webhook_endpoint(client, added_webhook_test):
     # The test is as follows:
@@ -28,6 +35,18 @@ def test_webhook_endpoint(client, added_webhook_test):
     assert not file_path.exists()
 
 
+def test_webhook_flow_on_run_endpoint(client, added_webhook_test, created_api_key):
+    endpoint_name = added_webhook_test["endpoint_name"]
+    endpoint = f"api/v1/run/{endpoint_name}?stream=false"
+    # Just test that "Random Payload" returns 202
+    # returns 202
+    payload = {
+        "output_type": "any",
+    }
+    response = client.post(endpoint, headers={"x-api-key": created_api_key.api_key}, json=payload)
+    assert response.status_code == 200, response.json()
+
+
 def test_webhook_with_random_payload(client, added_webhook_test):
     endpoint_name = added_webhook_test["endpoint_name"]
     endpoint = f"api/v1/webhook/{endpoint_name}"