history added to agent flow

backend/onyx/agents/agent_search/deep_search_a/main/nodes/agent_path_decision.py

@@ -8,6 +8,9 @@ from onyx.agents.agent_search.deep_search_a.main.operations import logger
 from onyx.agents.agent_search.deep_search_a.main.states import MainState
 from onyx.agents.agent_search.deep_search_a.main.states import RoutingDecision
 from onyx.agents.agent_search.models import AgentSearchConfig
+from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
+    build_history_prompt,
+)
 from onyx.agents.agent_search.shared_graph_utils.prompts import AGENT_DECISION_PROMPT
 from onyx.agents.agent_search.shared_graph_utils.prompts import (
     AGENT_DECISION_PROMPT_AFTER_SEARCH,
@@ -29,6 +32,8 @@ def agent_path_decision(state: MainState, config: RunnableConfig) -> RoutingDeci
         agent_a_config.perform_initial_search_path_decision
     )
 
+    history = build_history_prompt(config["metadata"]["config"].message_history)
+
     logger.debug(f"--------{now_start}--------DECIDING TO SEARCH OR GO TO LLM---")
 
     if perform_initial_search_path_decision:
@@ -53,12 +58,14 @@ def agent_path_decision(state: MainState, config: RunnableConfig) -> RoutingDeci
         )
 
         agent_decision_prompt = AGENT_DECISION_PROMPT_AFTER_SEARCH.format(
-            question=question, sample_doc_str=sample_doc_str
+            question=question, sample_doc_str=sample_doc_str, history=history
         )
 
     else:
         sample_doc_str = ""
-        agent_decision_prompt = AGENT_DECISION_PROMPT.format(question=question)
+        agent_decision_prompt = AGENT_DECISION_PROMPT.format(
+            question=question, history=history
+        )
 
     msg = [HumanMessage(content=agent_decision_prompt)]
 

backend/onyx/agents/agent_search/deep_search_a/main/nodes/generate_initial_answer.py

@@ -19,6 +19,9 @@ from onyx.agents.agent_search.deep_search_a.main.operations import (
 from onyx.agents.agent_search.deep_search_a.main.states import InitialAnswerUpdate
 from onyx.agents.agent_search.deep_search_a.main.states import MainState
 from onyx.agents.agent_search.models import AgentSearchConfig
+from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
+    build_history_prompt,
+)
 from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
     trim_prompt_piece,
 )
@@ -58,6 +61,9 @@ def generate_initial_answer(
     agent_a_config = cast(AgentSearchConfig, config["metadata"]["config"])
     question = agent_a_config.search_request.query
     persona_prompt = get_persona_prompt(agent_a_config.search_request.persona)
+
+    history = build_history_prompt(agent_a_config.message_history)
+
     sub_question_docs = state["documents"]
     all_original_question_documents = state["all_original_question_documents"]
 
@@ -160,7 +166,7 @@ def generate_initial_answer(
         doc_context = trim_prompt_piece(
             model.config,
             doc_context,
-            base_prompt + sub_question_answer_str + persona_specification,
+            base_prompt + sub_question_answer_str + persona_specification + history,
         )
 
         msg = [
@@ -172,6 +178,7 @@ def generate_initial_answer(
                     ),
                     relevant_docs=format_docs(relevant_docs),
                     persona_specification=persona_specification,
+                    history=history,
                 )
             )
         ]

backend/onyx/agents/agent_search/deep_search_a/main/nodes/generate_refined_answer.py

@@ -16,6 +16,9 @@ from onyx.agents.agent_search.deep_search_a.main.operations import (
 from onyx.agents.agent_search.deep_search_a.main.states import MainState
 from onyx.agents.agent_search.deep_search_a.main.states import RefinedAnswerUpdate
 from onyx.agents.agent_search.models import AgentSearchConfig
+from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
+    build_history_prompt,
+)
 from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
     trim_prompt_piece,
 )
@@ -56,6 +59,8 @@ def generate_refined_answer(
     question = agent_a_config.search_request.query
     persona_prompt = get_persona_prompt(agent_a_config.search_request.persona)
 
+    history = build_history_prompt(agent_a_config.message_history)
+
     initial_documents = state["documents"]
     revised_documents = state["refined_documents"]
 
@@ -169,13 +174,15 @@ def generate_refined_answer(
         + sub_question_answer_str
         + relevant_docs
         + initial_answer
-        + persona_specification,
+        + persona_specification
+        + history,
     )
 
     msg = [
         HumanMessage(
             content=base_prompt.format(
                 question=question,
+                history=history,
                 answered_sub_questions=remove_document_citations(
                     sub_question_answer_str
                 ),

backend/onyx/agents/agent_search/deep_search_a/main/nodes/initial_sub_question_creation.py

@@ -12,6 +12,9 @@ from onyx.agents.agent_search.deep_search_a.main.operations import logger
 from onyx.agents.agent_search.deep_search_a.main.states import BaseDecompUpdate
 from onyx.agents.agent_search.deep_search_a.main.states import MainState
 from onyx.agents.agent_search.models import AgentSearchConfig
+from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
+    build_history_prompt,
+)
 from onyx.agents.agent_search.shared_graph_utils.prompts import (
     INITIAL_DECOMPOSITION_PROMPT_QUESTIONS,
 )
@@ -47,6 +50,7 @@ def initial_sub_question_creation(
     perform_initial_search_path_decision = (
         agent_a_config.perform_initial_search_path_decision
     )
+    history = build_history_prompt(agent_a_config.message_history)
 
     # Use the initial search results to inform the decomposition
     sample_doc_str = state.get("sample_doc_str", "")
@@ -83,13 +87,13 @@ def initial_sub_question_creation(
 
         decomposition_prompt = (
             INITIAL_DECOMPOSITION_PROMPT_QUESTIONS_AFTER_SEARCH.format(
-                question=question, sample_doc_str=sample_doc_str
+                question=question, sample_doc_str=sample_doc_str, history=history
             )
         )
 
     else:
         decomposition_prompt = INITIAL_DECOMPOSITION_PROMPT_QUESTIONS.format(
-            question=question
+            question=question, history=history
         )
 
     # Start decomposition

backend/onyx/agents/agent_search/deep_search_a/main/nodes/refined_sub_question_creation.py

@@ -14,6 +14,9 @@ from onyx.agents.agent_search.deep_search_a.main.states import (
 )
 from onyx.agents.agent_search.deep_search_a.main.states import MainState
 from onyx.agents.agent_search.models import AgentSearchConfig
+from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
+    build_history_prompt,
+)
 from onyx.agents.agent_search.shared_graph_utils.prompts import DEEP_DECOMPOSE_PROMPT
 from onyx.agents.agent_search.shared_graph_utils.utils import dispatch_separated
 from onyx.agents.agent_search.shared_graph_utils.utils import (
@@ -47,7 +50,7 @@ def refined_sub_question_creation(
 
     question = agent_a_config.search_request.query
     base_answer = state["initial_answer"]
-
+    history = build_history_prompt(agent_a_config.message_history)
     # get the entity term extraction dict and properly format it
     entity_retlation_term_extractions = state["entity_retlation_term_extractions"]
 
@@ -69,6 +72,7 @@ def refined_sub_question_creation(
         HumanMessage(
             content=DEEP_DECOMPOSE_PROMPT.format(
                 question=question,
+                history=history,
                 entity_term_extraction_str=entity_term_extraction_str,
                 base_answer=base_answer,
                 answered_sub_questions="\n - ".join(addressed_question_list),

backend/onyx/agents/agent_search/shared_graph_utils/agent_prompt_ops.py

@@ -4,8 +4,10 @@ from langchain.schema import SystemMessage
 from langchain_core.messages.tool import ToolMessage
 
 from onyx.agents.agent_search.shared_graph_utils.prompts import BASE_RAG_PROMPT_v2
+from onyx.agents.agent_search.shared_graph_utils.prompts import HISTORY_PROMPT
 from onyx.context.search.models import InferenceSection
 from onyx.llm.interfaces import LLMConfig
+from onyx.llm.models import PreviousMessage
 from onyx.llm.utils import get_max_input_tokens
 from onyx.natural_language_processing.utils import get_tokenizer
 from onyx.natural_language_processing.utils import tokenizer_trim_content
@@ -63,3 +65,25 @@ def trim_prompt_piece(config: LLMConfig, prompt_piece: str, reserved_str: str) -
         desired_length=max_tokens - len(llm_tokenizer.encode(reserved_str)),
         tokenizer=llm_tokenizer,
     )
+
+
+def build_history_prompt(message_history: list[PreviousMessage] | None) -> str:
+    if message_history is None:
+        return ""
+    history = ""
+    previous_message_type = None
+    for message in message_history:
+        if "user" in message.message_type:
+            history += f"User: {message.message}\n"
+            previous_message_type = "user"
+        elif "assistant" in message.message_type:
+            # only use the initial agent answer for the history
+            if previous_message_type != "assistant":
+                history += f"You/Agent: {message.message}\n"
+            previous_message_type = "assistant"
+        else:
+            continue
+    if len(history) > 0:
+        return HISTORY_PROMPT.format(history=history)
+    else:
+        return ""

backend/onyx/agents/agent_search/shared_graph_utils/prompts.py

@@ -2,6 +2,13 @@ UNKNOWN_ANSWER = "I do not have enough information to answer this question."
 
 NO_RECOVERED_DOCS = "No relevant documents recovered"
 
+HISTORY_PROMPT = """\n
+For more context, here is the history of the conversation so far that preceeded this question:
+\n ------- \n
+{history}
+\n ------- \n\n
+"""
+
 REWRITE_PROMPT_MULTI_ORIGINAL = """ \n
     Please convert an initial user question into a 2-3 more appropriate short and pointed search queries for retrievel from a
     document store. Particularly, try to think about resolving ambiguities and make the search queries more specific,
@@ -309,6 +316,7 @@ DEEP_DECOMPOSE_PROMPT = """ \n
     \n ------- \n
     {question}
     \n ------- \n
+    {history}
 
     Here is the initial sub-optimal answer:
     \n ------- \n
@@ -453,6 +461,8 @@ Here is the initial question:
 -------
 {question}
 -------
+{history}
+
 Please formulate your answer as a newline-separated list of questions like so:
  <sub-question>
  <sub-question>
@@ -490,6 +500,7 @@ And here is the initial question that you should think about decomposing:
 {question}
 -------
 
+{history}
 
 Please formulate your answer as a newline-separated list of questions like so:
  <sub-question>
@@ -560,6 +571,7 @@ or address the request, you should choose the 'research' option.
 - If you think the question is very general and does not refer to a contents of a document store, you should choose
 the 'LLM' option.
 - Otherwise, you should choose the 'research' option.
+{history}
 
 Here is the initial question:
 -------
@@ -584,6 +596,7 @@ store to answer or materially help with the request, you should choose the 'rese
 you know the answer/can handle the request, you should choose the 'LLM' option.
 - If the question asks you do do somethng ('please create...', 'write for me...', etc.), you should choose the 'LLM' option.
 - If in doubt, choose the 'research' option.
+{history}
 
 Here is the initial question:
 -------
@@ -688,14 +701,14 @@ INITIAL_RAG_PROMPT = (
     """ \n
 {persona_specification}
 
-Use the information provided below - and only the
-provided information - to answer the provided question.
+Use the information provided below - and only the provided information - to answer the provided question.
 
 The information provided below consists of:
     1) a number of answered sub-questions - these are very important(!) and definitely should be
     considered to answer the question.
     2) a number of documents that were also deemed relevant for the question.
 
+{history}
 IMPORTANT RULES:
  - If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer.
  You may give some additional facts you learned, but do not try to invent an answer.
@@ -739,6 +752,7 @@ INITIAL_RAG_PROMPT_NO_SUB_QUESTIONS = (
 Use the information provided below
 - and only the provided information - to answer the provided question.
 The information provided below consists of a number of documents that were deemed relevant for the question.
+{history}
 
 IMPORTANT RULES:
  - If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer.
@@ -781,7 +795,7 @@ The information provided below consists of:
      particular to update/extend/correct the initial answer!
     information from the revised sub-questions
     3) a number of documents that were also deemed relevant for the question.
-
+{history}
 IMPORTANT RULES:
  - If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer.
  You may give some additional facts you learned, but do not try to invent an answer.
@@ -838,6 +852,7 @@ provided information - to answer the provided question.
 The information provided below consists of:
     1) an initial answer that was given but found to be lacking in some way.
     2) a number of documents that were also deemed relevant for the question.
+{history}
 
 IMPORTANT RULES:
  - If you cannot reliably answer the question solely using the provided information, say that you cannot reliably answer.