feat: map user messages

Author: GabrielVasilescu04

packages/uipath-llamaindex/src/uipath_llamaindex/runtime/chat/messages.py

@@ -1,5 +1,6 @@
 import logging
 from datetime import datetime, timezone
+from typing import Any
 from uuid import uuid4
 
 from llama_index.core.agent.workflow.workflow_events import (
@@ -40,6 +41,38 @@ def __init__(self, runtime_id: str) -> None:
         # tool_id -> message_id for correlating ToolCallResult with its parent AI message
         self._tool_id_to_message_id: dict[str, str] = {}
 
+    @staticmethod
+    def map_input(input: dict[str, Any]) -> dict[str, Any]:
+        """Map UiPath chat message format to LlamaIndex expected format.
+
+        If the input already has 'user_msg', return it unchanged.
+        If the input has a 'messages' array (UiPath chat format), extract the
+        text content from the first message's contentParts and map it to
+        'user_msg'.
+        """
+        if "user_msg" in input:
+            return input
+
+        messages = input.get("messages")
+        if not messages or not isinstance(messages, list):
+            return input
+
+        first_message = messages[0]
+        content_parts = first_message.get("contentParts", [])
+
+        text_parts = [
+            part["data"]["inline"]
+            for part in content_parts
+            if part.get("mimeType") == "text/plain"
+            and isinstance(part.get("data"), dict)
+            and part["data"].get("inline")
+        ]
+
+        if text_parts:
+            return {"user_msg": " ".join(text_parts)}
+
+        return input
+
     def get_timestamp(self) -> str:
         """Format current time as ISO 8601 UTC with milliseconds: 2025-01-04T10:30:00.123Z"""
         return (

packages/uipath-llamaindex/src/uipath_llamaindex/runtime/runtime.py

@@ -140,7 +140,7 @@ async def _run_workflow(
         """
         Core workflow execution logic used by both execute() and stream().
         """
-        workflow_input = input or {}
+        workflow_input = UiPathChatMessagesMapper.map_input(input or {})
         is_resuming = bool(options and options.resume)
 
         if is_resuming: