Append attachments content to last message (#17993)

api/db/services/dialog_service.py

@@ -828,7 +828,7 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
         kwargs.setdefault("knowledge", "")
     gen_conf = dialog.llm_setting
 
-    system_content = prompt_config["system"].format(**kwargs) + text_attachments_content
+    system_content = prompt_config["system"].format(**kwargs)
     # If knowledge was retrieved but the template has no {knowledge}
     # placeholder, auto-append it so the LLM still sees the context.
     if knowledges and "{knowledge}" not in prompt_config.get("system", ""):
@@ -838,6 +838,8 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
     if knowledges and (prompt_config.get("quote", True) and kwargs.get("quote", True)):
         prompt4citation = citation_prompt()
     msg.extend([{"role": m["role"], "content": re.sub(r"##\d+\$\$", "", m["content"])} for m in messages if m["role"] != "system"])
+    if text_attachments_content and msg:
+        msg[-1]["content"] += text_attachments_content
     used_token_count, msg = message_fit_in(msg, int(max_tokens * 0.95))
     if llm_model_config["model_type"] == "chat" and image_attachments:
         convert_last_user_msg_to_multimodal(msg, image_attachments, factory)
@@ -1882,6 +1884,8 @@ async def rag_agent(dialog, messages, stream=True, **kwargs):
     factory = chat_mdl.model_config.get("llm_factory", "") if chat_mdl.model_config else ""
     text_attachments_content, image_attachments, image_files = get_files_content(messages[-1], model_type)
     agent_messages = deepcopy(messages)
+    if text_attachments_content and agent_messages:
+        agent_messages[-1]["content"] += text_attachments_content
     if model_type == "chat" and image_attachments:
         convert_last_user_msg_to_multimodal(agent_messages, image_attachments, factory)
     use_web_search = _should_use_web_search(prompt_config, kwargs.get("internet"))

rag/advanced_rag/agentic_rag.py

@@ -574,20 +574,9 @@ class RAGTools:
 
         if self.tool_started_sink is not None:
             self.tool_started_sink()
-        if self.text_attachments_content:
-            self.kbinfos = {
-                "chunks": [
-                    {
-                        "id": "chat_attachment",
-                        "chunk_id": "chat_attachment",
-                        "doc_id": "chat_attachment",
-                        "docnm_kwd": "Chat attachment",
-                        "content_with_weight": self.text_attachments_content,
-                    }
-                ],
-                "doc_aggs": [{"doc_id": "chat_attachment", "doc_name": "Chat attachment", "count": 1}],
-            }
         messages = [{"role": "user", "content": question}] if question else []
+        if self.text_attachments_content and messages:
+            messages[-1]["content"] += self.text_attachments_content
         final = ""
         async for kind, delta in _split_think_stream(run_agentic_rag(self, messages)):
             if kind == "answer":

rag/advanced_rag/harness/orchestrator/agentic.py

@@ -143,8 +143,6 @@ async def agentic_research(state: dict, tools) -> dict:
         if action == "ANSWER_PARTIAL":
             return _finalize(ctx, tools, partial=True)
         if action == "ABSTAIN":
-            if getattr(tools, "text_attachments_content", ""):
-                return {"verdict": verdict.__dict__, "kbinfos": tools.kbinfos}
             tools.kbinfos["chunks"] = []
             return {"verdict": verdict.__dict__, "abstain": True}
         if action == "REPLAN":

rag/advanced_rag/harness/orchestrator/decompose.py

@@ -186,8 +186,6 @@ async def decompose_and_search(state: dict, tools) -> dict:
         if action in ("ANSWER", "ANSWER_PARTIAL"):
             return _finalize(ctx, tools, partial=action == "ANSWER_PARTIAL", loop=completed_cycles)
         if action == "ABSTAIN":
-            if getattr(tools, "text_attachments_content", ""):
-                return {"verdict": verdict.__dict__, "kbinfos": tools.kbinfos}
             tools.kbinfos["chunks"] = []
             return {"verdict": verdict.__dict__, "abstain": True, "loop": completed_cycles}
         if action == "FALLBACK_LLM":

test/unit_test/rag/advanced_rag/test_agentic_rag.py

@@ -1,5 +1,3 @@
-from copy import deepcopy
-
 import pytest
 
 from rag.advanced_rag.agentic_rag import RAGTools
@@ -13,11 +11,10 @@ class FakeChatModel:
 
 
 @pytest.mark.asyncio
-async def test_rag_tool_adds_text_attachment_as_evidence(monkeypatch):
+async def test_rag_tool_adds_text_attachment_to_user_question(monkeypatch):
     captured = {}
 
     async def fake_run_agentic_rag(tools, messages):
-        captured["kbinfos"] = deepcopy(tools.kbinfos)
         captured["messages"] = messages
         yield "answer"
 
@@ -26,6 +23,4 @@ async def test_rag_tool_adds_text_attachment_as_evidence(monkeypatch):
     tools = RAGTools([], FakeChatModel(), text_attachments_content="attached facts")
 
     assert await tools.rag("What is attached?") == "answer"
-    assert captured["messages"] == [{"role": "user", "content": "What is attached?"}]
-    assert captured["kbinfos"]["chunks"][0]["docnm_kwd"] == "Chat attachment"
-    assert captured["kbinfos"]["chunks"][0]["content_with_weight"] == "attached facts"
+    assert captured["messages"] == [{"role": "user", "content": "What is attached?attached facts"}]