Reenable option to run Danswer without Gen AI (#906)

backend/danswer/chat/process_message.py

@@ -21,6 +21,7 @@ from danswer.chat.models import QADocsResponse
 from danswer.chat.models import StreamingError
 from danswer.configs.chat_configs import CHUNK_SIZE
 from danswer.configs.chat_configs import DEFAULT_NUM_CHUNKS_FED_TO_CHAT
+from danswer.configs.constants import DISABLED_GEN_AI_MSG
 from danswer.configs.constants import MessageType
 from danswer.db.chat import create_db_search_doc
 from danswer.db.chat import create_new_chat_message
@@ -36,6 +37,7 @@ from danswer.db.models import SearchDoc as DbSearchDoc
 from danswer.db.models import User
 from danswer.document_index.factory import get_default_document_index
 from danswer.indexing.models import InferenceChunk
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.interfaces import LLM
 from danswer.llm.utils import get_default_llm_token_encode
@@ -61,10 +63,18 @@ def generate_ai_chat_response(
     history: list[ChatMessage],
     context_docs: list[LlmDoc],
     doc_id_to_rank_map: dict[str, int],
-    llm: LLM,
+    llm: LLM | None,
     llm_tokenizer: Callable,
     all_doc_useful: bool,
 ) -> Iterator[DanswerAnswerPiece | CitationInfo | StreamingError]:
+    if llm is None:
+        try:
+            llm = get_default_llm()
+        except GenAIDisabledException:
+            # Not an error if it's a user configuration
+            yield DanswerAnswerPiece(answer_piece=DISABLED_GEN_AI_MSG)
+            return
+
     if query_message.prompt is None:
         raise RuntimeError("No prompt received for generating Gen AI answer.")
 
@@ -171,7 +181,11 @@ def stream_chat_message(
                 "Must specify a set of documents for chat or specify search options"
             )
 
-        llm = get_default_llm()
+        try:
+            llm = get_default_llm()
+        except GenAIDisabledException:
+            llm = None
+
         llm_tokenizer = get_default_llm_token_encode()
         document_index = get_default_document_index()
 

backend/danswer/configs/app_configs.py

@@ -20,7 +20,6 @@ APP_API_PREFIX = os.environ.get("API_PREFIX", "")
 #####
 BLURB_SIZE = 128  # Number Encoder Tokens included in the chunk blurb
 GENERATIVE_MODEL_ACCESS_CHECK_FREQ = 86400  # 1 day
-# CURRENTLY DOES NOT FULLY WORK, DON'T USE THIS
 DISABLE_GENERATIVE_AI = os.environ.get("DISABLE_GENERATIVE_AI", "").lower() == "true"
 
 

backend/danswer/configs/constants.py

@@ -47,6 +47,14 @@ SECTION_SEPARATOR = "\n\n"
 INDEX_SEPARATOR = "==="
 
 
+# Messages
+DISABLED_GEN_AI_MSG = (
+    "Your System Admin has disabled the Generative AI functionalities of Danswer.\n"
+    "Please contact them if you wish to have this enabled.\n"
+    "You can still use Danswer as a search engine."
+)
+
+
 class DocumentSource(str, Enum):
     # Special case, document passed in via Danswer APIs without specifying a source type
     INGESTION_API = "ingestion_api"

backend/danswer/danswerbot/slack/blocks.py

@@ -12,6 +12,7 @@ from slack_sdk.models.blocks import RadioButtonsElement
 from slack_sdk.models.blocks import SectionBlock
 
 from danswer.chat.models import DanswerQuote
+from danswer.configs.app_configs import DISABLE_GENERATIVE_AI
 from danswer.configs.constants import DocumentSource
 from danswer.configs.constants import SearchFeedbackType
 from danswer.configs.danswerbot_configs import DANSWER_BOT_NUM_DOCS_TO_DISPLAY
@@ -106,8 +107,11 @@ def build_documents_blocks(
     message_id: int | None,
     num_docs_to_display: int = DANSWER_BOT_NUM_DOCS_TO_DISPLAY,
 ) -> list[Block]:
+    header_text = (
+        "Retrieved Documents" if DISABLE_GENERATIVE_AI else "Reference Documents"
+    )
     seen_docs_identifiers = set()
-    section_blocks: list[Block] = [HeaderBlock(text="Reference Documents")]
+    section_blocks: list[Block] = [HeaderBlock(text=header_text)]
     included_docs = 0
     for rank, d in enumerate(documents):
         if d.document_id in seen_docs_identifiers:
@@ -208,6 +212,9 @@ def build_qa_response_blocks(
     favor_recent: bool,
     skip_quotes: bool = False,
 ) -> list[Block]:
+    if DISABLE_GENERATIVE_AI:
+        return []
+
     quotes_blocks: list[Block] = []
 
     ai_answer_header = HeaderBlock(text="AI Answer")

backend/danswer/llm/exceptions.py

@@ -0,0 +1,4 @@
+class GenAIDisabledException(Exception):
+    def __init__(self, message: str = "Generative AI has been turned off") -> None:
+        self.message = message
+        super().__init__(self.message)

backend/danswer/llm/factory.py

@@ -1,9 +1,11 @@
+from danswer.configs.app_configs import DISABLE_GENERATIVE_AI
 from danswer.configs.chat_configs import QA_TIMEOUT
 from danswer.configs.model_configs import FAST_GEN_AI_MODEL_VERSION
 from danswer.configs.model_configs import GEN_AI_MODEL_PROVIDER
 from danswer.configs.model_configs import GEN_AI_MODEL_VERSION
 from danswer.llm.chat_llm import DefaultMultiLLM
 from danswer.llm.custom_llm import CustomModelServer
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.gpt_4_all import DanswerGPT4All
 from danswer.llm.interfaces import LLM
 from danswer.llm.utils import get_gen_ai_api_key
@@ -18,6 +20,9 @@ def get_default_llm(
 ) -> LLM:
     """A single place to fetch the configured LLM for Danswer
     Also allows overriding certain LLM defaults"""
+    if DISABLE_GENERATIVE_AI:
+        raise GenAIDisabledException()
+
     if gen_ai_model_version_override:
         model_version = gen_ai_model_version_override
     else:

backend/danswer/main.py

@@ -231,6 +231,9 @@ def get_application() -> FastAPI:
             if GEN_AI_API_ENDPOINT:
                 logger.info(f"Using LLM Endpoint: {GEN_AI_API_ENDPOINT}")
 
+            # Any additional model configs logged here
+            get_default_llm().log_model_configs()
+
         if MULTILINGUAL_QUERY_EXPANSION:
             logger.info(
                 f"Using multilingual flow with languages: {MULTILINGUAL_QUERY_EXPANSION}"
@@ -258,9 +261,6 @@ def get_application() -> FastAPI:
                 logger.info("GPU is not available")
             logger.info(f"Torch Threads: {torch.get_num_threads()}")
 
-        # This is for the LLM, most LLMs will not need warming up
-        get_default_llm().log_model_configs()
-
         logger.info("Verifying query preprocessing (NLTK) data is downloaded")
         nltk.download("stopwords", quiet=True)
         nltk.download("wordnet", quiet=True)

backend/danswer/one_shot_answer/answer_question.py

@@ -29,6 +29,7 @@ from danswer.one_shot_answer.factory import get_question_answer_model
 from danswer.one_shot_answer.models import DirectQARequest
 from danswer.one_shot_answer.models import OneShotQAResponse
 from danswer.one_shot_answer.models import QueryRephrase
+from danswer.one_shot_answer.qa_block import no_gen_ai_response
 from danswer.one_shot_answer.qa_utils import combine_message_thread
 from danswer.search.models import RerankMetricsContainer
 from danswer.search.models import RetrievalMetricsContainer
@@ -191,8 +192,12 @@ def stream_answer_objects(
         llm_version=llm_override,
     )
 
-    full_prompt_str = qa_model.build_prompt(
+    full_prompt_str = (
-        query=query_msg.message, history_str=history_str, context_chunks=llm_chunks
+        qa_model.build_prompt(
+            query=query_msg.message, history_str=history_str, context_chunks=llm_chunks
+        )
+        if qa_model is not None
+        else "Gen AI Disabled"
     )
 
     # Create the first User query message
@@ -207,10 +212,14 @@ def stream_answer_objects(
         commit=True,
     )
 
-    response_packets = qa_model.answer_question_stream(
+    response_packets = (
-        prompt=full_prompt_str,
+        qa_model.answer_question_stream(
-        llm_context_docs=llm_chunks,
+            prompt=full_prompt_str,
-        metrics_callback=llm_metrics_callback,
+            llm_context_docs=llm_chunks,
+            metrics_callback=llm_metrics_callback,
+        )
+        if qa_model is not None
+        else no_gen_ai_response()
     )
 
     # Capture outputs and errors

backend/danswer/one_shot_answer/factory.py

@@ -1,6 +1,7 @@
 from danswer.configs.chat_configs import QA_PROMPT_OVERRIDE
 from danswer.configs.chat_configs import QA_TIMEOUT
 from danswer.db.models import Prompt
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.one_shot_answer.interfaces import QAModel
 from danswer.one_shot_answer.qa_block import QABlock
@@ -19,18 +20,21 @@ def get_question_answer_model(
     chain_of_thought: bool = False,
     llm_version: str | None = None,
     qa_model_version: str | None = QA_PROMPT_OVERRIDE,
-) -> QAModel:
+) -> QAModel | None:
     if chain_of_thought:
         raise NotImplementedError("COT has been disabled")
 
     system_prompt = prompt.system_prompt if prompt is not None else None
     task_prompt = prompt.task_prompt if prompt is not None else None
 
-    llm = get_default_llm(
+    try:
-        api_key=api_key,
+        llm = get_default_llm(
-        timeout=timeout,
+            api_key=api_key,
-        gen_ai_model_version_override=llm_version,
+            timeout=timeout,
-    )
+            gen_ai_model_version_override=llm_version,
+        )
+    except GenAIDisabledException:
+        return None
 
     if qa_model_version == "weak":
         qa_handler: QAHandler = WeakLLMQAHandler(

backend/danswer/one_shot_answer/qa_block.py

@@ -13,6 +13,7 @@ from danswer.chat.models import LlmDoc
 from danswer.chat.models import LLMMetricsContainer
 from danswer.chat.models import StreamingError
 from danswer.configs.chat_configs import MULTILINGUAL_QUERY_EXPANSION
+from danswer.configs.constants import DISABLED_GEN_AI_MSG
 from danswer.indexing.models import InferenceChunk
 from danswer.llm.interfaces import LLM
 from danswer.llm.utils import check_number_of_tokens
@@ -252,6 +253,10 @@ def build_dummy_prompt(
     ).strip()
 
 
+def no_gen_ai_response() -> Iterator[DanswerAnswerPiece]:
+    yield DanswerAnswerPiece(answer_piece=DISABLED_GEN_AI_MSG)
+
+
 class QABlock(QAModel):
     def __init__(self, llm: LLM, qa_handler: QAHandler) -> None:
         self._llm = llm

backend/danswer/secondary_llm_flows/answer_validation.py

@@ -1,3 +1,4 @@
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
 from danswer.prompts.answer_validation import ANSWER_VALIDITY_PROMPT
@@ -41,12 +42,17 @@ def get_answer_validity(
             return False
         return True  # If something is wrong, let's not toss away the answer
 
+    try:
+        llm = get_default_llm()
+    except GenAIDisabledException:
+        return True
+
     if not answer:
         return False
 
     messages = _get_answer_validation_messages(query, answer)
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(messages)
-    model_output = get_default_llm().invoke(filled_llm_prompt)
+    model_output = llm.invoke(filled_llm_prompt)
     logger.debug(model_output)
 
     validity = _extract_validity(model_output)

backend/danswer/secondary_llm_flows/chat_session_naming.py

@@ -1,5 +1,6 @@
 from danswer.chat.chat_utils import combine_message_chain
 from danswer.db.models import ChatMessage
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.interfaces import LLM
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
@@ -23,7 +24,12 @@ def get_renamed_conversation_name(
         return messages
 
     if llm is None:
-        llm = get_default_llm()
+        try:
+            llm = get_default_llm()
+        except GenAIDisabledException:
+            # This may be longer than what the LLM tends to produce but is the most
+            # clear thing we can do
+            return full_history[0].message
 
     history_str = combine_message_chain(full_history)
 

backend/danswer/secondary_llm_flows/choose_search.py

@@ -5,6 +5,7 @@ from langchain.schema import SystemMessage
 from danswer.chat.chat_utils import combine_message_chain
 from danswer.configs.chat_configs import DISABLE_LLM_CHOOSE_SEARCH
 from danswer.db.models import ChatMessage
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.interfaces import LLM
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
@@ -68,15 +69,20 @@ def check_if_need_search(
     if disable_llm_check:
         return True
 
+    if llm is None:
+        try:
+            llm = get_default_llm()
+        except GenAIDisabledException:
+            # If Generative AI is turned off the always run Search as Danswer is being used
+            # as just a search engine
+            return True
+
     history_str = combine_message_chain(history)
 
     prompt_msgs = _get_search_messages(
         question=query_message.message, history_str=history_str
     )
 
-    if llm is None:
-        llm = get_default_llm()
-
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(prompt_msgs)
     require_search_output = llm.invoke(filled_llm_prompt)
 

backend/danswer/secondary_llm_flows/chunk_usefulness.py

@@ -1,5 +1,6 @@
 from collections.abc import Callable
 
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
 from danswer.prompts.llm_chunk_filter import CHUNK_FILTER_PROMPT
@@ -30,14 +31,20 @@ def llm_eval_chunk(query: str, chunk_content: str) -> bool:
             return False
         return True
 
+    # If Gen AI is disabled, none of the messages are more "useful" than any other
+    # All are marked not useful (False) so that the icon for Gen AI likes this answer
+    # is not shown for any result
+    try:
+        llm = get_default_llm(use_fast_llm=True, timeout=5)
+    except GenAIDisabledException:
+        return False
+
     messages = _get_usefulness_messages()
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(messages)
     # When running in a batch, it takes as long as the longest thread
     # And when running a large batch, one may fail and take the whole timeout
     # instead cap it to 5 seconds
-    model_output = get_default_llm(use_fast_llm=True, timeout=5).invoke(
+    model_output = llm.invoke(filled_llm_prompt)
-        filled_llm_prompt
-    )
     logger.debug(model_output)
 
     return _extract_usefulness(model_output)

backend/danswer/secondary_llm_flows/query_expansion.py

@@ -3,6 +3,7 @@ from typing import cast
 
 from danswer.chat.chat_utils import combine_message_chain
 from danswer.db.models import ChatMessage
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.interfaces import LLM
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
@@ -28,9 +29,17 @@ def llm_multilingual_query_expansion(query: str, language: str) -> str:
 
         return messages
 
+    try:
+        llm = get_default_llm(use_fast_llm=True, timeout=5)
+    except GenAIDisabledException:
+        logger.warning(
+            "Unable to perform multilingual query expansion, Gen AI disabled"
+        )
+        return query
+
     messages = _get_rephrase_messages()
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(messages)
-    model_output = get_default_llm().invoke(filled_llm_prompt)
+    model_output = llm.invoke(filled_llm_prompt)
     logger.debug(model_output)
 
     return model_output
@@ -81,12 +90,25 @@ def history_based_query_rephrase(
     llm: LLM | None = None,
     size_heuristic: int = 200,
     punctuation_heuristic: int = 10,
+    skip_first_rephrase: bool = False,
 ) -> str:
     user_query = cast(str, query_message.message)
 
     if not user_query:
         raise ValueError("Can't rephrase/search an empty query")
 
+    if llm is None:
+        try:
+            llm = get_default_llm()
+        except GenAIDisabledException:
+            # If Generative AI is turned off, just return the original query
+            return user_query
+
+    # For some use cases, the first query should be untouched. Later queries must be rephrased
+    # due to needing context but the first query has no context.
+    if skip_first_rephrase and not history:
+        return user_query
+
     # If it's a very large query, assume it's a copy paste which we may want to find exactly
     # or at least very closely, so don't rephrase it
     if len(user_query) >= size_heuristic:
@@ -103,9 +125,6 @@ def history_based_query_rephrase(
         question=user_query, history_str=history_str
     )
 
-    if llm is None:
-        llm = get_default_llm()
-
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(prompt_msgs)
     rephrased_query = llm.invoke(filled_llm_prompt)
 
@@ -130,13 +149,17 @@ def thread_based_query_rephrase(
     if count_punctuation(user_query) >= punctuation_heuristic:
         return user_query
 
+    if llm is None:
+        try:
+            llm = get_default_llm()
+        except GenAIDisabledException:
+            # If Generative AI is turned off, just return the original query
+            return user_query
+
     prompt_msgs = get_contextual_rephrase_messages(
         question=user_query, history_str=history_str
     )
 
-    if llm is None:
-        llm = get_default_llm()
-
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(prompt_msgs)
     rephrased_query = llm.invoke(filled_llm_prompt)
 

backend/danswer/secondary_llm_flows/query_validation.py

@@ -4,6 +4,7 @@ from collections.abc import Iterator
 from danswer.chat.models import DanswerAnswerPiece
 from danswer.chat.models import StreamingError
 from danswer.configs.chat_configs import DISABLE_LLM_QUERY_ANSWERABILITY
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
 from danswer.prompts.constants import ANSWERABLE_PAT
@@ -48,9 +49,14 @@ def get_query_answerability(
     if skip_check:
         return "Query Answerability Evaluation feature is turned off", True
 
+    try:
+        llm = get_default_llm()
+    except GenAIDisabledException:
+        return "Generative AI is turned off - skipping check", True
+
     messages = get_query_validation_messages(user_query)
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(messages)
-    model_output = get_default_llm().invoke(filled_llm_prompt)
+    model_output = llm.invoke(filled_llm_prompt)
 
     reasoning = extract_answerability_reasoning(model_output)
     answerable = extract_answerability_bool(model_output)
@@ -70,10 +76,21 @@ def stream_query_answerability(
         )
         return
 
+    try:
+        llm = get_default_llm()
+    except GenAIDisabledException:
+        yield get_json_line(
+            QueryValidationResponse(
+                reasoning="Generative AI is turned off - skipping check",
+                answerable=True,
+            ).dict()
+        )
+        return
+
     messages = get_query_validation_messages(user_query)
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(messages)
     try:
-        tokens = get_default_llm().stream(filled_llm_prompt)
+        tokens = llm.stream(filled_llm_prompt)
         reasoning_pat_found = False
         model_output = ""
         hold_answerable = ""

backend/danswer/secondary_llm_flows/source_filter.py

@@ -6,6 +6,7 @@ from sqlalchemy.orm import Session
 from danswer.configs.constants import DocumentSource
 from danswer.db.connector import fetch_unique_document_sources
 from danswer.db.engine import get_sqlalchemy_engine
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
 from danswer.prompts.constants import SOURCES_KEY
@@ -145,13 +146,18 @@ def extract_source_filter(
             logger.warning("LLM failed to provide a valid Source Filter output")
             return None
 
+    try:
+        llm = get_default_llm()
+    except GenAIDisabledException:
+        return None
+
     valid_sources = fetch_unique_document_sources(db_session)
     if not valid_sources:
         return None
 
     messages = _get_source_filter_messages(query=query, valid_sources=valid_sources)
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(messages)
-    model_output = get_default_llm().invoke(filled_llm_prompt)
+    model_output = llm.invoke(filled_llm_prompt)
     logger.debug(model_output)
 
     return _extract_source_filters_from_llm_out(model_output)

backend/danswer/secondary_llm_flows/time_filter.py

@@ -5,6 +5,7 @@ from datetime import timezone
 
 from dateutil.parser import parse
 
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.utils import dict_based_prompt_to_langchain_prompt
 from danswer.prompts.filter_extration import TIME_FILTER_PROMPT
@@ -145,9 +146,14 @@ def extract_time_filter(query: str) -> tuple[datetime | None, bool]:
 
         return None, False
 
+    try:
+        llm = get_default_llm()
+    except GenAIDisabledException:
+        return None, False
+
     messages = _get_time_filter_messages(query)
     filled_llm_prompt = dict_based_prompt_to_langchain_prompt(messages)
-    model_output = get_default_llm().invoke(filled_llm_prompt)
+    model_output = llm.invoke(filled_llm_prompt)
     logger.debug(model_output)
 
     return _extract_time_filter_from_llm_out(model_output)

backend/danswer/server/manage/administrative.py

@@ -9,7 +9,6 @@ from fastapi import HTTPException
 from sqlalchemy.orm import Session
 
 from danswer.auth.users import current_admin_user
-from danswer.configs.app_configs import DISABLE_GENERATIVE_AI
 from danswer.configs.app_configs import GENERATIVE_MODEL_ACCESS_CHECK_FREQ
 from danswer.configs.constants import GEN_AI_API_KEY_STORAGE_KEY
 from danswer.db.connector_credential_pair import get_connector_credential_pair
@@ -22,6 +21,7 @@ from danswer.db.models import User
 from danswer.document_index.factory import get_default_document_index
 from danswer.dynamic_configs import get_dynamic_config_store
 from danswer.dynamic_configs.interface import ConfigNotFoundError
+from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_default_llm
 from danswer.llm.utils import get_gen_ai_api_key
 from danswer.llm.utils import test_llm
@@ -100,9 +100,6 @@ def document_hidden_update(
 def validate_existing_genai_api_key(
     _: User = Depends(current_admin_user),
 ) -> None:
-    if DISABLE_GENERATIVE_AI:
-        return
-
     # Only validate every so often
     check_key_time = "genai_api_key_last_check_time"
     kv_store = get_dynamic_config_store()
@@ -120,7 +117,11 @@ def validate_existing_genai_api_key(
 
     genai_api_key = get_gen_ai_api_key()
 
-    llm = get_default_llm(api_key=genai_api_key, timeout=10)
+    try:
+        llm = get_default_llm(api_key=genai_api_key, timeout=10)
+    except GenAIDisabledException:
+        return
+
     is_valid = test_llm(llm)
 
     if not is_valid:
@@ -165,6 +166,9 @@ def store_genai_api_key(
         if not is_valid:
             raise HTTPException(400, "Invalid API key provided")
 
+        get_dynamic_config_store().store(GEN_AI_API_KEY_STORAGE_KEY, request.api_key)
+    except GenAIDisabledException:
+        # If Disable Generative AI is set, no need to verify, just store the key for later use
         get_dynamic_config_store().store(GEN_AI_API_KEY_STORAGE_KEY, request.api_key)
     except RuntimeError as e:
         raise HTTPException(400, str(e))

deployment/docker_compose/docker-compose.dev.yml

@@ -40,6 +40,7 @@ services:
       - DISABLE_LLM_FILTER_EXTRACTION=${DISABLE_LLM_FILTER_EXTRACTION:-}
       - DISABLE_LLM_CHUNK_FILTER=${DISABLE_LLM_CHUNK_FILTER:-}
       - DISABLE_LLM_CHOOSE_SEARCH=${DISABLE_LLM_CHOOSE_SEARCH:-}
+      - DISABLE_GENERATIVE_AI=${DISABLE_GENERATIVE_AI:-}
       # Query Options
       - DOC_TIME_DECAY=${DOC_TIME_DECAY:-}  # Recency Bias for search results, decay at 1 / (1 + DOC_TIME_DECAY * x years)
       - HYBRID_ALPHA=${HYBRID_ALPHA:-}  # Hybrid Search Alpha (0 for entirely keyword, 1 for entirely vector)
@@ -96,6 +97,7 @@ services:
       - DISABLE_LLM_FILTER_EXTRACTION=${DISABLE_LLM_FILTER_EXTRACTION:-}
       - DISABLE_LLM_CHUNK_FILTER=${DISABLE_LLM_CHUNK_FILTER:-}
       - DISABLE_LLM_CHOOSE_SEARCH=${DISABLE_LLM_CHOOSE_SEARCH:-}
+      - DISABLE_GENERATIVE_AI=${DISABLE_GENERATIVE_AI:-}
       # Query Options
       - DOC_TIME_DECAY=${DOC_TIME_DECAY:-}  # Recency Bias for search results, decay at 1 / (1 + DOC_TIME_DECAY * x years)
       - HYBRID_ALPHA=${HYBRID_ALPHA:-}  # Hybrid Search Alpha (0 for entirely keyword, 1 for entirely vector)