fixed citations when sections selected

backend/onyx/agents/agent_search/basic/utils.py

@@ -7,6 +7,7 @@
 
 from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
 from onyx.chat.models import LlmDoc
+from onyx.chat.models import OnyxContext
 from onyx.chat.stream_processing.answer_response_handler import AnswerResponseHandler
 from onyx.chat.stream_processing.answer_response_handler import CitationResponseHandler
 from onyx.chat.stream_processing.answer_response_handler import (
@@ -23,7 +24,7 @@ def process_llm_stream(
     should_stream_answer: bool,
     writer: StreamWriter,
     final_search_results: list[LlmDoc] | None = None,
-    displayed_search_results: list[LlmDoc] | None = None,
+    displayed_search_results: list[OnyxContext] | list[LlmDoc] | None = None,
 ) -> AIMessageChunk:
     tool_call_chunk = AIMessageChunk(content="")
 

backend/onyx/agents/agent_search/orchestration/nodes/basic_use_tool_response.py

@@ -9,6 +9,7 @@
 from onyx.agents.agent_search.basic.utils import process_llm_stream
 from onyx.agents.agent_search.models import GraphConfig
 from onyx.chat.models import LlmDoc
+from onyx.chat.models import OnyxContexts
 from onyx.tools.tool_implementations.search.search_tool import (
     SEARCH_DOC_CONTENT_ID,
 )
@@ -50,13 +51,11 @@ def basic_use_tool_response(
         if yield_item.id == FINAL_CONTEXT_DOCUMENTS_ID:
             final_search_results = cast(list[LlmDoc], yield_item.response)
         elif yield_item.id == SEARCH_DOC_CONTENT_ID:
-            search_contexts = yield_item.response.contexts
+            search_contexts = cast(OnyxContexts, yield_item.response).contexts
             for doc in search_contexts:
                 if doc.document_id not in initial_search_results:
                     initial_search_results.append(doc)
 
-            initial_search_results = cast(list[LlmDoc], initial_search_results)
-
     new_tool_call_chunk = AIMessageChunk(content="")
     if not agent_config.behavior.skip_gen_ai_answer_generation:
         stream = llm.stream(
@@ -70,7 +69,9 @@ def basic_use_tool_response(
             True,
             writer,
             final_search_results=final_search_results,
-            displayed_search_results=initial_search_results,
+            # when the search tool is called with specific doc ids, initial search
+            # results are not output. But, we still want i.e. citations to be processed.
+            displayed_search_results=initial_search_results or final_search_results,
         )
 
     return BasicOutput(tool_call_chunk=new_tool_call_chunk)

backend/onyx/chat/answer.py

@@ -183,6 +183,7 @@ def citations_by_subquestion(self) -> dict[SubQuestionKey, list[CitationInfo]]:
         citations_by_subquestion: dict[
             SubQuestionKey, list[CitationInfo]
         ] = defaultdict(list)
+        basic_subq_key = SubQuestionKey(level=BASIC_KEY[0], question_num=BASIC_KEY[1])
         for packet in self.processed_streamed_output:
             if isinstance(packet, CitationInfo):
                 if packet.level_question_num is not None and packet.level is not None:
@@ -192,7 +193,7 @@ def citations_by_subquestion(self) -> dict[SubQuestionKey, list[CitationInfo]]:
                         )
                     ].append(packet)
                 elif packet.level is None:
-                    citations_by_subquestion[BASIC_SQ_KEY].append(packet)
+                    citations_by_subquestion[basic_subq_key].append(packet)
         return citations_by_subquestion
 
     def is_cancelled(self) -> bool:

backend/onyx/chat/stream_processing/utils.py

@@ -3,6 +3,7 @@
 from pydantic import BaseModel
 
 from onyx.chat.models import LlmDoc
+from onyx.chat.models import OnyxContext
 from onyx.context.search.models import InferenceChunk
 
 
@@ -11,7 +12,7 @@ class DocumentIdOrderMapping(BaseModel):
 
 
 def map_document_id_order(
-    chunks: Sequence[InferenceChunk | LlmDoc], one_indexed: bool = True
+    chunks: Sequence[InferenceChunk | LlmDoc | OnyxContext], one_indexed: bool = True
 ) -> DocumentIdOrderMapping:
     order_mapping = {}
     current = 1 if one_indexed else 0

backend/onyx/server/query_and_chat/chat_backend.py

@@ -743,7 +743,7 @@ def upload_files_for_chat(
         # to re-extract it every time we send a message
         if file_type == ChatFileType.DOC:
             extracted_text = extract_file_text(
-                file=file_content_io, # use the bytes we already read
+                file=file_content_io,  # use the bytes we already read
                 file_name=file.filename or "",
             )
             text_file_id = str(uuid.uuid4())

backend/onyx/tools/tool_implementations/search/search_tool.py

@@ -7,7 +7,6 @@
 from sqlalchemy.orm import Session
 
 from onyx.chat.chat_utils import llm_doc_from_inference_section
-from onyx.chat.llm_response_handler import LLMCall
 from onyx.chat.models import AnswerStyleConfig
 from onyx.chat.models import ContextualPruningConfig
 from onyx.chat.models import DocumentPruningConfig
@@ -371,41 +370,6 @@ def build_next_prompt(
             prompt_config=self.prompt_config,
         )
 
-    """Other utility functions"""
-
-    @classmethod
-    def get_search_result(
-        cls, llm_call: LLMCall
-    ) -> tuple[list[LlmDoc], list[LlmDoc]] | None:
-        """
-        Returns the final search results and a map of docs to their original search rank (which is what is displayed to user)
-        """
-        if not llm_call.tool_call_info:
-            return None
-
-        final_search_results = []
-        initial_search_results = []
-
-        for yield_item in llm_call.tool_call_info:
-            if (
-                isinstance(yield_item, ToolResponse)
-                and yield_item.id == FINAL_CONTEXT_DOCUMENTS_ID
-            ):
-                final_search_results = cast(list[LlmDoc], yield_item.response)
-            elif (
-                isinstance(yield_item, ToolResponse)
-                and yield_item.id == SEARCH_DOC_CONTENT_ID
-            ):
-                search_contexts = yield_item.response.contexts
-                # original_doc_search_rank = 1
-                for doc in search_contexts:
-                    if doc.document_id not in initial_search_results:
-                        initial_search_results.append(doc)
-
-                initial_search_results = cast(list[LlmDoc], initial_search_results)
-
-        return final_search_results, initial_search_results
-
 
 # Allows yielding the same responses as a SearchTool without being a SearchTool.
 # SearchTool passed in to allow for access to SearchTool properties.

backend/tests/integration/tests/dev_apis/test_simple_chat_api.py

@@ -1,6 +1,5 @@
 import json
 
-import pytest
 import requests
 
 from onyx.configs.constants import MessageType
@@ -66,9 +65,6 @@ def test_send_message_simple_with_history(reset: None) -> None:
         assert found_doc["metadata"]["document_id"] == doc.id
 
 
-@pytest.mark.xfail(
-    reason="agent search broke this",
-)
 def test_using_reference_docs_with_simple_with_history_api_flow(reset: None) -> None:
     # Creating an admin user (first user created is automatically an admin)
     admin_user: DATestUser = UserManager.create(name="admin_user")