Jira tool tweaks

README.md

@@ -2,7 +2,14 @@
 
 ## How to Use
 
-# via Bundle URLs
+### Via prebuilt docker image
+You can use the prebuilt docker image that is based on the official langflow image but include the ClearPoint langflow-lib and the required dependencies.
+
+```bash
+docker run --rm -it -p 7860:7860 ghcr.io/clearpointnz/langflow-lib:v0.1.0
+```
+
+### via Bundle URLs
 Components can be pulled into your Langflow instance by setting the `LANGFLOW_BUNDLE_URLS` environment variable to the URL of this repository.
 
 For example:
@@ -13,8 +20,9 @@ Note: The command above will not persist any workflows or configuration. Use for
 
 Many of these components require additional Python packages to be installed. These will need to be available in your Langflow instance. See the `comps_requirements.txt` file for a list of dependencies.
 
-# Via custom docker image
-Alternatively you can build a custom docker container with the depencies and the components installed. For example:
+
+### Via custom docker image
+Alternatively you can build a custom docker container with the dependencies and the components installed. For example:
 
 ``` dockerfile
 FROM langflowai/langflow:latest
@@ -33,4 +41,8 @@ COPY components/ /app/components/
 ENV LANGFLOW_COMPONENTS_PATH=/app/components
 
 CMD ["langflow", "run"]
-```
+```
+
+## Development
+You can use the included Docker compose file to build and run langflow with the components for testing and development. It includes creation of a volume for persisting data and configuration.
+

components/ClearPoint Jira/jira_add_comment.py

@@ -47,16 +47,25 @@ class JiraAddCommentComponent(Component):
         Output(
             name="results", 
             display_name="Results", 
-            method="add_issue",
+            method="add_comment_to_issue",
             info="The results of the Jira comment add operation."
         )
     ]
 
-    def add_issue(self) -> Data:
+    def add_comment_to_issue(self) -> Data:
+        # HACK: make copy of inputs to avoid race condition. not guareenteed to work.  See https://github.com/langflow-ai/langflow/issues/8791
+        issue_key = self.issue_key
+        comment_text = self.comment_text
+
+        # create the JIRA client
         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)                                   
+        # add the comment to the issue
+        response = jira.add_comment(issue_key, comment_text)                                   
+
+        # build a results payload
+        results = {"comment_id": response["id"], "status": "Comment added successfully"}
 
-        self.status = results.raw
-        return Data(data=results.raw)
+        self.status = results.results
+        return Data(data=results.results)
 

components/ClearPoint Jira/jira_add_label.py

@@ -55,18 +55,25 @@ class JiraAddLabelToIssueComponent(Component):
     ]
 
     def add_label(self) -> Data:
+        # HACK: make copy of inputs to avoid race condition. not guareenteed to work.  See https://github.com/langflow-ai/langflow/issues/8791
+        issue_key = self.issue_key
+        label = self.label
+
+        # create the JIRA client
         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)
+        # grab the current labels for the issue
+        issue = jira.issue(issue_key, fields='labels')
 
         # add the label to the issue
-        issue.fields.labels.append(self.label)
+        issue.fields.labels.append(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                                
+        # build a results payload
+        results = {"issue_key": issue_key, "labels":  issue.fields.labels, "status": "Label added successfully"}
 
-        self.status = issue.raw
-        return Data(data=issue.raw)
+        self.status = results
+        return Data(data=results)
 

components/ClearPoint Jira/jira_search_issues_component.py

@@ -65,11 +65,17 @@ class JiraSearchIssuesComponent(Component):
     ]
 
     def search_issues(self) -> List[Data]:
+        # HACK: make copy of inputs to avoid race condition. not guareenteed to work.  See https://github.com/langflow-ai/langflow/issues/8791
+        jql_query = self.jql_query
+        issue_fields = self.issue_fields
+
+        # create the JIRA client
         jira = JIRA(server=self.JIRA_SERVER_URL, basic_auth=(self.JIRA_USERNAME, self.JIRA_API_KEY))
 
-
-        issues = jira.search_issues(self.jql_query, fields=self.issue_fields,json_result=True)
+        # do the search
+        issues = jira.search_issues(jql_query, fields=self.issue_fields,json_result=True)
 
+        # build list of issues, flattening fields if requested
         issues_list = []        
         for issue in issues["issues"]:
 
@@ -85,11 +91,16 @@ def search_issues(self) -> List[Data]:
         return issues_list
 
     def build_dataframe(self) -> DataFrame:
+        # trigger the saerch
         issues = self.search_issues()
+
+        # convert results to list of dict
         rows = []
         for issue in issues:
             rows.append(dict(issue.data))
 
+        # convert list of dict to DataFrame
         df_result = DataFrame(rows)
-        self.status = df_result  # store in self.status for logs
+
+        self.status = df_result  
         return df_result    

compose.yaml

@@ -0,0 +1,18 @@
+# Docker compose file for local dev/testing of langflow-lib with peristence of config/flows
+services:
+  langflow:
+    build: .
+    # container is set up to run as user so need to run as root so that can write to config dir
+    user: root
+    # tty true so taht all logs are printed
+    tty: true
+    ports:
+      - "7860:7860"    
+    environment:      
+      - LANGFLOW_CONFIG_DIR=/app/langflow
+      - LANGFLOW_SAVE_DB_IN_CONFIG_DIR=true
+      - DO_NOT_TRACK=true
+    volumes:
+      - langflowlib-dev-data:/app/langflow
+volumes:  
+  langflowlib-dev-data: