From 88f0b5a0a4289609c31bdb5c4ef5d03f7281692d Mon Sep 17 00:00:00 2001
From: Lars <Lars@stommer.de>
Date: Sat, 11 Apr 2026 10:13:03 +0200
Subject: [PATCH] fix: Add workflow node outputs as placeholders in inline
 templates
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ISSUE: Inline templates referencing node outputs ({{ node_id.analysis_core }},
{{ node_id.signal_xyz }}) were not resolved - AI received empty data from
previous workflow stages.

ROOT CAUSE: load_prompt_template() only loaded system placeholders
(name, age, etc.) but not node execution results from context['node_results'].

FIX:
- Extract node outputs from context['node_results']
- Add as placeholders: node_id.analysis_core, node_id.signal_xyz, node_id.question_xyz
- Format matches PlaceholderPicker extraction logic
- Debug logging shows which node placeholders are added

TESTING:
- System placeholder test: ✅ SUCCESS (name, age, geschlecht resolved)
- Node output placeholders: Fixed (previously missing)
- User workflow: Join → Analysis → End now receives upstream data

Part 3: Inline Prompts - placeholder resolution completion
---
 backend/workflow_executor.py | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/backend/workflow_executor.py b/backend/workflow_executor.py
index d585bae..a516727 100644
--- a/backend/workflow_executor.py
+++ b/backend/workflow_executor.py
@@ -893,6 +893,37 @@ async def load_prompt_template(node: WorkflowNode, context: Dict[str, Any]) -> s
     except Exception as e:
         logger.error(f"❌ CRITICAL: Failed to load placeholders for workflow: {e}", exc_info=True)
 
+    # Add workflow node outputs as placeholders (Part 3: Inline Prompts)
+    # Format: node_id.analysis_core, node_id.signal_xyz, node_id.question_xyz
+    node_results = context.get("node_results", {})
+    if node_results:
+        logger.info(f"🔍 DEBUG: Adding {len(node_results)} node outputs as placeholders")
+        for node_id, node_state in node_results.items():
+            # analysis_core
+            if hasattr(node_state, 'analysis_core') and node_state.analysis_core:
+                key = f"{node_id}.analysis_core"
+                variables[key] = node_state.analysis_core
+                logger.debug(f"  Added placeholder: {key} = {node_state.analysis_core[:50]}...")
+
+            # decision_signals (keyed by question ID)
+            if hasattr(node_state, 'decision_signals') and node_state.decision_signals:
+                for signal_id, signal_value in node_state.decision_signals.items():
+                    # Signal placeholder: node_id.signal_question_id
+                    signal_key = f"{node_id}.signal_{signal_id}"
+                    variables[signal_key] = signal_value
+                    logger.debug(f"  Added placeholder: {signal_key} = {signal_value}")
+
+            # Question texts (from graph metadata if available)
+            # NOTE: Question text placeholders are populated from graph in PlaceholderPicker
+            # Here we only add if available in node_state metadata
+            if hasattr(node_state, 'metadata') and isinstance(node_state.metadata, dict):
+                questions = node_state.metadata.get('questions', [])
+                for q in questions:
+                    if isinstance(q, dict) and 'id' in q and 'question' in q:
+                        question_key = f"{node_id}.question_{q['id']}"
+                        variables[question_key] = q['question']
+                        logger.debug(f"  Added placeholder: {question_key}")
+
     # Load catalog for |d modifier support
     try:
         catalog = get_placeholder_catalog(profile_id)