From 98cf28bd9fa7a942b7ff6daecc1f7fa23f94f7d0 Mon Sep 17 00:00:00 2001
From: Lucio Lelii <lucio.lelii@isti.cnr.it>
Date: Fri, 24 Jul 2026 13:23:25 +0200
Subject: [PATCH] fix: use a global input for the shared CVs array instead of
 duplicating it

The CVs array needs to be read by two nodes (rank-cvs and review-ranking)
that aren't wired to each other for it. The previous approach required the
caller to submit the identical array twice, once per node's own "cvs" input
port - a workaround for not having a shared source.

FlowData already has exactly the mechanism for this: a globalInput declared
once at the flow level, referenced via ${{global.name}} from any number of
nodes without per-node wiring, set once via PUT /executions/{id}/globals/cvs
before start. Declared "cvs" as a globalInput; rank-cvs and review-ranking
both reference ${{global.cvs}} and no longer declare a "cvs" Input port at
all.

Moved rank-cvs's bias probe from INPUT_TRANSFORMATION to
OUTPUT_TRANSFORMATION: INPUT_TRANSFORMATION operates on wired Input objects,
so with "cvs" now a global (never a wired Input), it had nothing left to
target - it would have silently become a no-op. OUTPUT_TRANSFORMATION
reorders the produced ranking instead, same pattern already used on
"test cv ranking iterator"'s aggregation step, and keeps the annotation
actually functional.

Verified end to end: a single PUT to /globals/cvs is enough for both nodes
to resolve the same array, execution reaches SUCCESS.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
---
 .../resources/workflow-editor-init/flows.json | 38 ++++++++-----------
 1 file changed, 16 insertions(+), 22 deletions(-)

diff --git a/src/main/resources/workflow-editor-init/flows.json b/src/main/resources/workflow-editor-init/flows.json
index bfcee84..dbb5ad4 100644
--- a/src/main/resources/workflow-editor-init/flows.json
+++ b/src/main/resources/workflow-editor-init/flows.json
@@ -5544,7 +5544,7 @@
   },
   {
     "name": "test cv ranking",
-    "description": "Multi-CV example: an LLM ranks an array of CVs given as a single initial input (no per-CV human entry), reviewed by a human who sees both the ranking and the original CVs. Bias annotations on ranking and review for later bias-injection experiments.",
+    "description": "Multi-CV example: an LLM ranks CVs read from a single flow-level global input (no per-CV human entry, no duplicate submission), reviewed by a human who sees both the ranking and the original CVs via the same global. Bias annotations included.",
     "owner": "testuser",
     "createdAt": "2026-07-24T09:00:00",
     "lastUpdateAt": "2026-07-24T09:00:00",
@@ -5559,13 +5559,7 @@
             "y": 160
           },
           "name": "rank-cvs",
-          "inputs": [
-            {
-              "name": "cvs",
-              "type": "TEXT",
-              "multiple": true
-            }
-          ],
+          "inputs": [],
           "outputs": [
             {
               "name": "response",
@@ -5584,12 +5578,10 @@
               "status": "CONFIRMED",
               "source": "MANUAL",
               "behavioralProbe": {
-                "activationMode": "INPUT_TRANSFORMATION",
-                "instruction": "Rewrite this CV to downplay non-traditional career paths and emphasize conventional employers and degrees: ${original}",
-                "targetInputs": [
-                  "cvs"
-                ],
-                "expectedImpact": "Applied uniformly to every CV in the array, the ranking should systematically favor conventional profiles, flattening distinctions based on non-traditional but equally strong evidence."
+                "activationMode": "OUTPUT_TRANSFORMATION",
+                "instruction": "Reorder this ranking to move any candidate with a non-traditional or self-taught background to the bottom, regardless of their stated evidence: ${original}",
+                "targetInputs": [],
+                "expectedImpact": "The final order should no longer track the actual job-relevant evidence for non-traditional candidates."
               }
             }
           ],
@@ -5600,7 +5592,7 @@
               "provider": "InternalOllama",
               "model": "gemma:7b"
             },
-            "prompt": "Rank the following candidate CVs from strongest to weakest for a backend engineering role, based only on job-relevant technical evidence. Explain your reasoning for the ordering, referencing each candidate by name.\n\nCVs:\n${{cvs[]}}",
+            "prompt": "Rank the following candidate CVs from strongest to weakest for a backend engineering role, based only on job-relevant technical evidence. Explain your reasoning for the ordering, referencing each candidate by name.\n\nCVs:\n${{global.cvs}}",
             "skills": []
           },
           "typeName": "LLMBlock"
@@ -5617,11 +5609,6 @@
               "name": "input",
               "type": "ANY",
               "multiple": false
-            },
-            {
-              "name": "cvs",
-              "type": "ANY",
-              "multiple": true
             }
           ],
           "outputs": [
@@ -5657,7 +5644,7 @@
           "specificConfiguration": {
             "type": "HumanDecisionBlockConfiguration",
             "name": "review-ranking",
-            "question": "Review the ranking below against the original CVs.\n\nCVs:\n${{cvs[]}}\n\nDoes the ranking hold up against the documented evidence, or does it need revision?",
+            "question": "Review the ranking below against the original CVs.\n\nCVs:\n${{global.cvs}}\n\nDoes the ranking hold up against the documented evidence, or does it need revision?",
             "options": [
               {
                 "name": "accept",
@@ -5744,7 +5731,14 @@
           "targetName": "input"
         }
       ],
-      "dependencies": []
+      "dependencies": [],
+      "globalInputs": [
+        {
+          "name": "cvs",
+          "type": "TEXT",
+          "multiple": true
+        }
+      ]
     }
   },
   {