Persona enhancements

backend/danswer/danswerbot/slack/blocks.py

@@ -185,6 +185,7 @@ def build_qa_response_blocks(
     source_filters: list[DocumentSource] | None,
     time_cutoff: datetime | None,
     favor_recent: bool,
+    skip_quotes: bool = False,
 ) -> list[Block]:
     quotes_blocks: list[Block] = []
 
@@ -232,8 +233,9 @@ def build_qa_response_blocks(
     if filter_block is not None:
         response_blocks.append(filter_block)
 
-    response_blocks.extend(
+    response_blocks.extend([answer_block, feedback_block])
-        [answer_block, feedback_block] + quotes_blocks + [DividerBlock()]
+    if not skip_quotes:
-    )
+        response_blocks.extend(quotes_blocks)
+    response_blocks.append(DividerBlock())
 
     return response_blocks

backend/danswer/danswerbot/slack/handlers/handle_message.py

@@ -104,6 +104,8 @@ def handle_message(
             document_set.name for document_set in persona.document_sets
         ]
 
+    should_respond_even_with_no_docs = persona.num_chunks == 0 if persona else False
+
     # List of user id to send message to, if None, send to everyone in channel
     send_to: list[str] | None = None
     respond_tag_only = False
@@ -257,7 +259,7 @@ def handle_message(
             logger.debug(answer.answer)
         return True
 
-    if not answer.top_documents:
+    if not answer.top_documents and not should_respond_even_with_no_docs:
         logger.error(f"Unable to answer question: '{msg}' - no documents found")
         # Optionally, respond in thread with the error message, Used primarily
         # for debugging purposes
@@ -288,6 +290,7 @@ def handle_message(
         source_filters=answer.source_type,
         time_cutoff=answer.time_cutoff,
         favor_recent=answer.favor_recent,
+        skip_quotes=persona is not None,  # currently Personas don't support quotes
     )
 
     # Get the chunks fed to the LLM only, then fill with other docs
@@ -298,10 +301,14 @@ def handle_message(
         doc for idx, doc in enumerate(top_docs) if idx not in llm_doc_inds
     ]
     priority_ordered_docs = llm_docs + remaining_docs
-    document_blocks = build_documents_blocks(
+    document_blocks = (
+        build_documents_blocks(
             documents=priority_ordered_docs,
             query_event_id=answer.query_event_id,
         )
+        if priority_ordered_docs
+        else []
+    )
 
     try:
         respond_in_thread(

backend/danswer/direct_qa/answer_question.py

@@ -54,6 +54,13 @@ def _get_qa_model(persona: Persona | None) -> QAModel:
     return get_default_qa_model()
 
 
+def _dummy_search_generator() -> Iterator[list[InferenceChunk] | list[bool]]:
+    """Mimics the interface of `full_chunk_search_generator` but returns empty lists
+    without actually running retrieval / re-ranking."""
+    yield cast(list[InferenceChunk], [])
+    yield cast(list[bool], [])
+
+
 @log_function_time()
 def answer_qa_query(
     new_message_request: NewMessageRequest,
@@ -91,6 +98,7 @@ def answer_qa_query(
         not persona.apply_llm_relevance_filter if persona else None
     )
     persona_num_chunks = persona.num_chunks if persona else None
+    persona_retrieval_disabled = persona.num_chunks == 0 if persona else False
     if persona:
         logger.info(f"Using persona: {persona.name}")
         logger.info(
@@ -113,6 +121,7 @@ def answer_qa_query(
     if disable_generative_answer:
         predicted_flow = QueryFlow.SEARCH
 
+    if not persona_retrieval_disabled:
         top_chunks, llm_chunk_selection = full_chunk_search(
             query=retrieval_request,
             document_index=get_default_document_index(),
@@ -121,6 +130,10 @@ def answer_qa_query(
         )
 
         top_docs = chunks_to_search_docs(top_chunks)
+    else:
+        top_chunks = []
+        llm_chunk_selection = []
+        top_docs = []
 
     partial_response = partial(
         QAResponse,
@@ -133,7 +146,7 @@ def answer_qa_query(
         favor_recent=retrieval_request.favor_recent,
     )
 
-    if disable_generative_answer or not top_docs:
+    if disable_generative_answer or (not top_docs and not persona_retrieval_disabled):
         return partial_response(
             answer=None,
             quotes=None,
@@ -237,6 +250,7 @@ def answer_qa_query_stream(
         not persona.apply_llm_relevance_filter if persona else None
     )
     persona_num_chunks = persona.num_chunks if persona else None
+    persona_retrieval_disabled = persona.num_chunks == 0 if persona else False
     if persona:
         logger.info(f"Using persona: {persona.name}")
         logger.info(
@@ -245,6 +259,10 @@ def answer_qa_query_stream(
             f"num_chunks: {persona_num_chunks}"
         )
 
+    # NOTE: it's not ideal that we're still doing `retrieval_preprocessing` even
+    # if `persona_retrieval_disabled == True`, but it's a bit tricky to separate this
+    # out. Since this flow is being re-worked shortly with the move to chat, leaving it
+    # like this for now.
     retrieval_request, predicted_search_type, predicted_flow = retrieval_preprocessing(
         new_message_request=new_message_request,
         user=user,
@@ -257,10 +275,13 @@ def answer_qa_query_stream(
     if persona:
         predicted_flow = QueryFlow.QUESTION_ANSWER
 
+    if not persona_retrieval_disabled:
         search_generator = full_chunk_search_generator(
             query=retrieval_request,
             document_index=get_default_document_index(),
         )
+    else:
+        search_generator = _dummy_search_generator()
 
     # first fetch and return to the UI the top chunks so the user can
     # immediately see some results
@@ -280,7 +301,9 @@ def answer_qa_query_stream(
     ).dict()
     yield get_json_line(initial_response)
 
-    if not top_chunks:
+    # some personas intentionally don't retrieve any documents, so we should
+    # not return early here
+    if not top_chunks and not persona_retrieval_disabled:
         logger.debug("No Documents Found")
         return
 

backend/danswer/direct_qa/qa_block.py

@@ -26,6 +26,7 @@ from danswer.prompts.direct_qa_prompts import COT_PROMPT
 from danswer.prompts.direct_qa_prompts import JSON_PROMPT
 from danswer.prompts.direct_qa_prompts import LANGUAGE_HINT
 from danswer.prompts.direct_qa_prompts import PARAMATERIZED_PROMPT
+from danswer.prompts.direct_qa_prompts import PARAMATERIZED_PROMPT_WITHOUT_CONTEXT
 from danswer.prompts.direct_qa_prompts import WEAK_LLM_PROMPT
 from danswer.utils.logger import setup_logger
 from danswer.utils.text_processing import clean_up_code_blocks
@@ -210,6 +211,13 @@ class PersonaBasedQAHandler(QAHandler):
     ) -> list[BaseMessage]:
         context_docs_str = build_context_str(context_chunks)
 
+        if not context_chunks:
+            single_message = PARAMATERIZED_PROMPT_WITHOUT_CONTEXT.format(
+                user_query=query,
+                system_prompt=self.system_prompt,
+                task_prompt=self.task_prompt,
+            ).strip()
+        else:
             single_message = PARAMATERIZED_PROMPT.format(
                 context_docs_str=context_docs_str,
                 user_query=query,
@@ -220,9 +228,14 @@ class PersonaBasedQAHandler(QAHandler):
         prompt: list[BaseMessage] = [HumanMessage(content=single_message)]
         return prompt
 
-    def build_dummy_prompt(
+    def build_dummy_prompt(self, retrieval_disabled: bool) -> str:
-        self,
+        if retrieval_disabled:
-    ) -> str:
+            return PARAMATERIZED_PROMPT_WITHOUT_CONTEXT.format(
+                user_query="<USER_QUERY>",
+                system_prompt=self.system_prompt,
+                task_prompt=self.task_prompt,
+            ).strip()
+
         return PARAMATERIZED_PROMPT.format(
             context_docs_str="<CONTEXT_DOCS>",
             user_query="<USER_QUERY>",

backend/danswer/prompts/direct_qa_prompts.py

@@ -137,6 +137,15 @@ CONTEXT:
 RESPONSE:
 """.strip()
 
+PARAMATERIZED_PROMPT_WITHOUT_CONTEXT = f"""
+{{system_prompt}}
+
+{{task_prompt}}
+
+{QUESTION_PAT.upper()} {{user_query}}
+RESPONSE:
+""".strip()
+
 
 # User the following for easy viewing of prompts
 if __name__ == "__main__":

backend/danswer/server/features/persona/api.py

@@ -131,12 +131,13 @@ def get_persona(
 def build_final_template_prompt(
     system_prompt: str,
     task_prompt: str,
+    retrieval_disabled: bool = False,
     _: User | None = Depends(current_user),
 ) -> PromptTemplateResponse:
     return PromptTemplateResponse(
         final_prompt_template=PersonaBasedQAHandler(
             system_prompt=system_prompt, task_prompt=task_prompt
-        ).build_dummy_prompt()
+        ).build_dummy_prompt(retrieval_disabled=retrieval_disabled)
     )
 
 

backend/danswer/server/features/persona/models.py

@@ -21,6 +21,7 @@ class PersonaSnapshot(BaseModel):
     description: str
     system_prompt: str
     task_prompt: str
+    num_chunks: int | None
     document_sets: list[DocumentSet]
     llm_model_version_override: str | None
 
@@ -32,6 +33,7 @@ class PersonaSnapshot(BaseModel):
             description=persona.description or "",
             system_prompt=persona.system_text or "",
             task_prompt=persona.hint_text or "",
+            num_chunks=persona.num_chunks,
             document_sets=[
                 DocumentSet.from_model(document_set_model)
                 for document_set_model in persona.document_sets

web/src/app/admin/personas/PersonaEditor.tsx

@@ -2,7 +2,7 @@
 
 import { DocumentSet } from "@/lib/types";
 import { Button, Divider, Text } from "@tremor/react";
-import { ArrayHelpers, FieldArray, Form, Formik } from "formik";
+import { ArrayHelpers, ErrorMessage, FieldArray, Form, Formik } from "formik";
 
 import * as Yup from "yup";
 import { buildFinalPrompt, createPersona, updatePersona } from "./lib";
@@ -13,6 +13,7 @@ import Link from "next/link";
 import { useEffect, useState } from "react";
 import {
   BooleanFormField,
+  ManualErrorMessage,
   SelectorFormField,
   TextFormField,
 } from "@/components/admin/connectors/Field";
@@ -46,12 +47,18 @@ export function PersonaEditor({
   const { popup, setPopup } = usePopup();
 
   const [finalPrompt, setFinalPrompt] = useState<string | null>("");
+  const [finalPromptError, setFinalPromptError] = useState<string>("");
 
   const triggerFinalPromptUpdate = async (
     systemPrompt: string,
-    taskPrompt: string
+    taskPrompt: string,
+    retrievalDisabled: boolean
   ) => {
-    const response = await buildFinalPrompt(systemPrompt, taskPrompt);
+    const response = await buildFinalPrompt(
+      systemPrompt,
+      taskPrompt,
+      retrievalDisabled
+    );
     if (response.ok) {
       setFinalPrompt((await response.json()).final_prompt_template);
     }
@@ -63,7 +70,8 @@ export function PersonaEditor({
     if (isUpdate) {
       triggerFinalPromptUpdate(
         existingPersona.system_prompt,
-        existingPersona.task_prompt
+        existingPersona.task_prompt,
+        existingPersona.num_chunks === 0
       );
     }
   }, []);
@@ -78,6 +86,7 @@ export function PersonaEditor({
           description: existingPersona?.description ?? "",
           system_prompt: existingPersona?.system_prompt ?? "",
           task_prompt: existingPersona?.task_prompt ?? "",
+          disable_retrieval: (existingPersona?.num_chunks ?? 5) === 0,
           document_set_ids:
             existingPersona?.document_sets?.map(
               (documentSet) => documentSet.id
@@ -88,36 +97,68 @@ export function PersonaEditor({
           llm_model_version_override:
             existingPersona?.llm_model_version_override ?? null,
         }}
-        validationSchema={Yup.object().shape({
+        validationSchema={Yup.object()
+          .shape({
             name: Yup.string().required("Must give the Persona a name!"),
             description: Yup.string().required(
               "Must give the Persona a description!"
             ),
-          system_prompt: Yup.string().required(
+            system_prompt: Yup.string(),
-            "Must give the Persona a system prompt!"
+            task_prompt: Yup.string(),
-          ),
+            disable_retrieval: Yup.boolean().required(),
-          task_prompt: Yup.string().required(
-            "Must give the Persona a task prompt!"
-          ),
             document_set_ids: Yup.array().of(Yup.number()),
             num_chunks: Yup.number().max(20).nullable(),
             apply_llm_relevance_filter: Yup.boolean().required(),
             llm_model_version_override: Yup.string().nullable(),
-        })}
+          })
+          .test(
+            "system-prompt-or-task-prompt",
+            "Must provide at least one of System Prompt or Task Prompt",
+            (values) => {
+              const systemPromptSpecified = values.system_prompt
+                ? values.system_prompt.length > 0
+                : false;
+              const taskPromptSpecified = values.task_prompt
+                ? values.task_prompt.length > 0
+                : false;
+              if (systemPromptSpecified || taskPromptSpecified) {
+                setFinalPromptError("");
+                return true;
+              } // Return true if at least one field has a value
+
+              setFinalPromptError(
+                "Must provide at least one of System Prompt or Task Prompt"
+              );
+            }
+          )}
         onSubmit={async (values, formikHelpers) => {
+          if (finalPromptError) {
+            setPopup({
+              type: "error",
+              message: "Cannot submit while there are errors in the form!",
+            });
+            return;
+          }
+
           formikHelpers.setSubmitting(true);
 
+          // if disable_retrieval is set, set num_chunks to 0
+          // to tell the backend to not fetch any documents
+          const numChunks = values.disable_retrieval
+            ? 0
+            : values.num_chunks || 5;
+
           let response;
           if (isUpdate) {
             response = await updatePersona({
               id: existingPersona.id,
               ...values,
-              num_chunks: values.num_chunks || null,
+              num_chunks: numChunks,
             });
           } else {
             response = await createPersona({
               ...values,
-              num_chunks: values.num_chunks || null,
+              num_chunks: numChunks,
             });
           }
           if (response.ok) {
@@ -163,8 +204,13 @@ export function PersonaEditor({
                 }
                 onChange={(e) => {
                   setFieldValue("system_prompt", e.target.value);
-                  triggerFinalPromptUpdate(e.target.value, values.task_prompt);
+                  triggerFinalPromptUpdate(
+                    e.target.value,
+                    values.task_prompt,
+                    values.disable_retrieval
+                  );
                 }}
+                error={finalPromptError}
               />
 
               <TextFormField
@@ -178,7 +224,26 @@ export function PersonaEditor({
                   setFieldValue("task_prompt", e.target.value);
                   triggerFinalPromptUpdate(
                     values.system_prompt,
-                    e.target.value
+                    e.target.value,
+                    values.disable_retrieval
+                  );
+                }}
+                error={finalPromptError}
+              />
+
+              <BooleanFormField
+                name="disable_retrieval"
+                label="Disable Retrieval"
+                subtext={`
+                If set, the Persona will not fetch any context documents to aid in the response. 
+                Instead, it will only use the supplied system and task prompts plus the user 
+                query in order to generate a response`}
+                onChange={(e) => {
+                  setFieldValue("disable_retrieval", e.target.checked);
+                  triggerFinalPromptUpdate(
+                    values.system_prompt,
+                    values.task_prompt,
+                    e.target.checked
                   );
                 }}
               />
@@ -195,7 +260,11 @@ export function PersonaEditor({
 
               <Divider />
 
-              <SectionHeader>What data should I have access to?</SectionHeader>
+              {!values.disable_retrieval && (
+                <>
+                  <SectionHeader>
+                    What data should I have access to?
+                  </SectionHeader>
 
                   <FieldArray
                     name="document_set_ids"
@@ -212,10 +281,10 @@ export function PersonaEditor({
                               >
                                 Document Sets
                               </Link>{" "}
-                          that this Persona should search through. If none are
+                              that this Persona should search through. If none
-                          specified, the Persona will search through all
+                              are specified, the Persona will search through all
-                          available documents in order to try and response to
+                              available documents in order to try and response
-                          queries.
+                              to queries.
                             </>
                           </SubLabel>
                         </div>
@@ -250,7 +319,9 @@ export function PersonaEditor({
                                   }
                                 }}
                               >
-                            <div className="my-auto">{documentSet.name}</div>
+                                <div className="my-auto">
+                                  {documentSet.name}
+                                </div>
                               </div>
                             );
                           })}
@@ -260,6 +331,8 @@ export function PersonaEditor({
                   />
 
                   <Divider />
+                </>
+              )}
 
               {llmOverrideOptions.length > 0 && defaultLLM && (
                 <>
@@ -296,18 +369,23 @@ export function PersonaEditor({
 
               <Divider />
 
-              <SectionHeader>[Advanced] Retrieval Customization</SectionHeader>
+              {!values.disable_retrieval && (
+                <>
+                  <SectionHeader>
+                    [Advanced] Retrieval Customization
+                  </SectionHeader>
 
                   <TextFormField
                     name="num_chunks"
                     label="Number of Chunks"
                     subtext={
                       <div>
-                    How many chunks should we feed into the LLM when generating
+                        How many chunks should we feed into the LLM when
-                    the final response? Each chunk is ~400 words long. If you
+                        generating the final response? Each chunk is ~400 words
-                    are using gpt-3.5-turbo or other similar models, setting
+                        long. If you are using gpt-3.5-turbo or other similar
-                    this to a value greater than 5 will result in errors at
+                        models, setting this to a value greater than 5 will
-                    query time due to the model&apos;s input length limit.
+                        result in errors at query time due to the model&apos;s
+                        input length limit.
                         <br />
                         <br />
                         If unspecified, will use 5 chunks.
@@ -331,6 +409,8 @@ export function PersonaEditor({
                   />
 
                   <Divider />
+                </>
+              )}
 
               <div className="flex">
                 <Button

web/src/app/admin/personas/lib.ts

@@ -46,10 +46,15 @@ export function deletePersona(personaId: number) {
   });
 }
 
-export function buildFinalPrompt(systemPrompt: string, taskPrompt: string) {
+export function buildFinalPrompt(
+  systemPrompt: string,
+  taskPrompt: string,
+  retrievalDisabled: boolean
+) {
   let queryString = Object.entries({
     system_prompt: systemPrompt,
     task_prompt: taskPrompt,
+    retrieval_disabled: retrievalDisabled,
   })
     .map(
       ([key, value]) =>

web/src/components/admin/connectors/Field.tsx

@@ -30,6 +30,10 @@ export function SubLabel({ children }: { children: string | JSX.Element }) {
   return <div className="text-sm text-gray-300 mb-2">{children}</div>;
 }
 
+export function ManualErrorMessage({ children }: { children: string }) {
+  return <div className="text-red-500 text-sm mt-1">{children}</div>;
+}
+
 export function TextFormField({
   name,
   label,
@@ -40,6 +44,7 @@ export function TextFormField({
   isTextArea = false,
   disabled = false,
   autoCompleteDisabled = true,
+  error,
 }: {
   name: string;
   label: string;
@@ -50,6 +55,7 @@ export function TextFormField({
   isTextArea?: boolean;
   disabled?: boolean;
   autoCompleteDisabled?: boolean;
+  error?: string;
 }) {
   return (
     <div className="mb-4">
@@ -78,11 +84,15 @@ export function TextFormField({
         autoComplete={autoCompleteDisabled ? "off" : undefined}
         {...(onChange ? { onChange } : {})}
       />
+      {error ? (
+        <ManualErrorMessage>{error}</ManualErrorMessage>
+      ) : (
         <ErrorMessage
           name={name}
           component="div"
           className="text-red-500 text-sm mt-1"
         />
+      )}
     </div>
   );
 }
@@ -91,12 +101,14 @@ interface BooleanFormFieldProps {
   name: string;
   label: string;
   subtext?: string;
+  onChange?: (e: React.ChangeEvent<HTMLInputElement>) => void;
 }
 
 export const BooleanFormField = ({
   name,
   label,
   subtext,
+  onChange,
 }: BooleanFormFieldProps) => {
   return (
     <div className="mb-4">
@@ -105,6 +117,7 @@ export const BooleanFormField = ({
           name={name}
           type="checkbox"
           className="mx-3 px-5 w-3.5 h-3.5 my-auto"
+          {...(onChange ? { onChange } : {})}
         />
         <div>
           <Label>{label}</Label>

web/src/components/search/SearchResultsDisplay.tsx

@@ -86,7 +86,8 @@ export const SearchResultsDisplay = ({
   if (
     answer === null &&
     (documents === null || documents.length === 0) &&
-    quotes === null
+    quotes === null &&
+    !isFetching
   ) {
     return (
       <div className="mt-4">

web/src/lib/search/streamingQuestionValidation.ts

@@ -43,7 +43,6 @@ export const questionValidationStreamed = async <T>({
   let previousPartialChunk: string | null = null;
   while (true) {
     const rawChunk = await reader?.read();
-    console.log(rawChunk);
     if (!rawChunk) {
       throw new Error("Unable to process chunk");
     }