Added Jira and other helper components.

components/ClearPoint General/data_conditional_router_component.py

@@ -0,0 +1,85 @@
+from langflow.custom import Component
+from langflow.io import  DropdownInput, IntInput, Output, DataInput, StrInput
+from langflow.schema.message import Data
+from evalidate import Expr
+
+
+class DataConditionalRouterComponent(Component):
+    display_name = "Data If-Else"
+    description = "Routes an Data to a corresponding output based on a boolean expression."
+    icon = "split"
+    name = "DataConditionalRouter"
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.__iteration_updated = False
+
+    inputs = [
+        DataInput(
+            name="input_data",
+            display_name="Input",
+            info="The primary text input for the operation.",
+            required=True,
+        ),
+        StrInput(
+            name="eval_expression",
+            display_name="Eval Expression",
+            info="The boolean expression to eval the input data against.",
+            required=True,
+        ),
+        IntInput(
+            name="max_iterations",
+            display_name="Max Iterations",
+            info="The maximum number of iterations for the conditional router.",
+            value=10,
+            advanced=True,
+        ),
+        DropdownInput(
+            name="default_route",
+            display_name="Default Route",
+            options=["true_result", "false_result"],
+            info="The default route to take when max iterations are reached.",
+            value="false_result",
+            advanced=True,
+        ),       
+    ]
+
+    outputs = [
+        Output(display_name="True", name="true_result", method="true_response"),        
+        Output(display_name="False", name="false_result", method="false_response"),
+    ]
+
+    def _pre_run_setup(self):
+        self.__iteration_updated = False
+
+    def iterate_and_stop_once(self, route_to_stop: str):
+        if not self.__iteration_updated:
+            self.update_ctx({f"{self._id}_iteration": self.ctx.get(f"{self._id}_iteration", 0) + 1})
+            self.__iteration_updated = True
+            if self.ctx.get(f"{self._id}_iteration", 0) >= self.max_iterations and route_to_stop == self.default_route:
+                route_to_stop = "true_result" if route_to_stop == "false_result" else "false_result"
+            self.stop(route_to_stop)
+
+    def true_response(self) -> Data:       
+        # TODO: Proper error handling. Should check for bool result and handle EvalException
+        result = Expr(self.eval_expression).eval(self.input_data.data)
+
+        if result:
+            self.status = self.input_data
+            self.iterate_and_stop_once("false_result")
+            return self.input_data
+        self.iterate_and_stop_once("true_result")
+        return Data(text="Eval is not true,.")
+
+    def false_response(self) -> Data:
+        # TODO: Proper error handling. Should check for bool result and handle EvalException
+        result = Expr(self.eval_expression).eval(self.input_data.data)
+
+        if not result:
+            self.status = self.input_data
+            self.iterate_and_stop_once("true_result")
+            return self.input_data
+        self.iterate_and_stop_once("false_result")
+        return Data(text="Eval is not false.")
+
+

components/ClearPoint General/first_row_component.py

@@ -0,0 +1,27 @@
+from langflow.custom import Component
+from langflow.io import DataFrameInput, Output
+from langflow.schema import Data
+
+
+class FirstRowComponent(Component):
+    display_name = "First row"
+    description = "Takes the first row of a Dataframe and converts it to a Data object"   
+    icon = "list-start"
+    name = "FirstRowComponent"
+
+    inputs = [
+        DataFrameInput(
+            name="input_dataframe",
+            display_name="Dataframe",
+            info="This is the input DataFrame"
+        ),
+    ]
+
+    outputs = [
+        Output(display_name="Data", name="output_data", method="build_output"),
+    ]
+
+    def build_output(self) -> Data:
+        data = self.input_dataframe.to_data_list()[0] # TODO empty list checking and handling
+        self.status = data
+        return data

components/ClearPoint General/json_to_data_component.py

@@ -0,0 +1,24 @@
+from langflow.custom import Component
+from langflow.io import Output, MultilineInput
+from langflow.schema import Data
+import json
+
+
+class JsonStringToDataComponent(Component):
+    display_name = "JSON to Data"
+    description = "This component converts a JSON string to a Data object."
+    icon = "file-json"
+    name = "JsonStringToData"
+
+    inputs = [
+        MultilineInput(name="json_string", display_name="JSON string"),
+    ]
+
+    outputs = [
+        Output(name="json_as_data", display_name="JSON as Data", method="convert_json_to_data")
+    ]
+
+    def convert_json_to_data(self) -> Data:
+        data = Data(data=json.loads(self.json_string))
+        self.status = data
+        return data

components/ClearPoint General/logger_component.py

@@ -0,0 +1,56 @@
+from langflow.custom import Component
+from langflow.io import HandleInput, Output, StrInput
+from langflow.schema import Data, DataFrame, Message
+
+
+class LoggerComponent(Component):
+    display_name = "Logger"
+    description = "Logs the passed in object and then passes it on unchanged."
+    icon = "bug"
+    name = "LoggerComponent"
+
+    inputs = [
+         StrInput(
+            name="log_message",
+            display_name="Log Message",
+            info="The message to log before the object.",
+            required=True,
+        ),
+        HandleInput(
+            name="input_object",
+            display_name="Input",
+            input_types=["DataFrame", "Data", "Message"],
+            info="Accepts either a DataFrame, a Data object or a Message.",
+            required=True,
+        ),
+    ]
+
+    outputs = [
+        Output(display_name="Data", name="output_data", method="build_data_output"),
+        Output(display_name="DataFrame", name="output_dataframe", method="build_dataframe_output"),
+        Output(display_name="Message", name="output_message", method="build_message_output"),
+    ]
+
+    def _log_object(self):
+        log_msg = f"{self.log_message} {self.input_object}"
+        self.log(log_msg,"LoggerComponent")
+        print(log_msg)
+        self.status = self.log_message
+
+    def build_data_output(self) -> Data:
+        if not isinstance(self.input_object,Data):
+            raise Exception("Input was not a Data object!")
+        self._log_object()
+        return self.input_object
+
+    def build_dataframe_output(self) -> DataFrame:
+        if not isinstance(self.input_object,DataFrame):
+            raise Exception("Input was not a DataFrame object!")
+        self._log_object()
+        return self.input_object    
+
+    def build_message_output(self) -> Message:
+        if not isinstance(self.input_object,Message):
+            raise Exception("Input was not a Message object!")
+        self._log_object()
+        return self.input_object      

components/ClearPoint Jira/jira_add_comment.py

@@ -0,0 +1,62 @@
+from langflow.custom import Component
+from langflow.io import Output, SecretStrInput, MessageTextInput,StrInput,BoolInput,MultilineInput
+from jira import JIRA
+from typing import List
+from langflow.schema import Data, DataFrame
+
+
+class JiraAddCommentComponent(Component):
+    display_name = "Jira Add comment"
+    description = (
+        "Adds a comment to a Jira issue."
+    )
+    icon = "jira"
+    name = "JiraAddCommentComponent"
+
+    inputs = [
+         StrInput(
+            name="JIRA_SERVER_URL",
+            display_name="Jira Server URL",
+            required=True,
+        ),
+        StrInput(
+            name="JIRA_USERNAME",
+            display_name="Jira Username",
+            required=True,
+        ),
+        SecretStrInput(
+            name="JIRA_API_KEY",
+            display_name="Jira API Key",
+            required=True,
+        ),
+        MessageTextInput(
+            name="issue_key",
+            display_name="Issue Key",
+            info="The key of the issue to update.",
+            required=True,
+            tool_mode=True,
+        ),
+        MultilineInput(name="comment_text", 
+                       display_name="Comment Text",
+                       info="Text of the comment to add to the issue.",
+                       required=True,
+                       tool_mode=True),       
+    ]
+
+    outputs = [
+        Output(
+            name="results", 
+            display_name="Results", 
+            method="add_issue",
+            info="The results of the Jira comment add operation."
+        )
+    ]
+
+    def add_issue(self) -> Data:
+        jira = JIRA(server=self.JIRA_SERVER_URL, basic_auth=(self.JIRA_USERNAME, self.JIRA_API_KEY))
+
+        results = jira.add_comment(self.issue_key,self.comment_text)                                   
+
+        self.status = results.raw
+        return Data(data=results.raw)
+

components/ClearPoint Jira/jira_add_label.py

@@ -0,0 +1,72 @@
+from langflow.custom import Component
+from langflow.io import Output, SecretStrInput, MessageTextInput,StrInput,BoolInput,MultilineInput
+from jira import JIRA
+from typing import List
+from langflow.schema import Data, DataFrame
+
+
+class JiraAddLabelToIssueComponent(Component):
+    display_name = "Jira Add label to issue"
+    description = (
+        "Adds a label to a Jira issue."
+    )
+    icon = "jira"
+    name = "JiraAddLabelToIssueComponent"
+
+    inputs = [
+         StrInput(
+            name="JIRA_SERVER_URL",
+            display_name="Jira Server URL",
+            required=True,
+        ),
+        StrInput(
+            name="JIRA_USERNAME",
+            display_name="Jira Username",
+            required=True,
+        ),
+        SecretStrInput(
+            name="JIRA_API_KEY",
+            display_name="Jira API Key",
+            required=True,
+        ),
+        MessageTextInput(
+            name="issue_key",
+            display_name="Issue Key",
+            info="The key of the issue to add the label to.",
+            required=True,
+            tool_mode=True,
+        ),
+        MessageTextInput(
+            name="label",
+            display_name="Label",
+            info="The label to add to the issue.",
+            required=True,
+            tool_mode=True,
+        ),    
+    ]
+
+    outputs = [
+        Output(
+            name="results", 
+            display_name="Results", 
+            method="add_label",
+            info="The results of the Jira label add operation."
+        )
+    ]
+
+    def add_label(self) -> Data:
+        jira = JIRA(server=self.JIRA_SERVER_URL, basic_auth=(self.JIRA_USERNAME, self.JIRA_API_KEY))
+
+        # grab the issue
+        issue = jira.issue(self.issue_key)
+
+        # add the label to the issue
+        issue.fields.labels.append(self.label)
+        # update issue with the new label
+        issue.update(fields={"labels": issue.fields.labels})   
+
+        issue = jira.issue(self.issue_key) # load the updated issue so we can get raw data TODO: add logic to avoid this second call                                
+
+        self.status = issue.raw
+        return Data(data=issue.raw)
+