Honor user's chat settings when running the extract questions phase

- Add marginally better error handling when GPT gives a messed up respones to the extract questions method
- Remove debug log lines
This commit is contained in:
sabaimran
2023-11-18 13:31:51 -08:00
parent 67156e6aec
commit a8a25ceac2
3 changed files with 46 additions and 21 deletions

View File

@@ -55,6 +55,7 @@ from database.models import (
Entry as DbEntry,
GithubConfig,
NotionConfig,
ChatModelOptions,
)
@@ -669,7 +670,16 @@ async def extract_references_and_questions(
# Infer search queries from user message
with timer("Extracting search queries took", logger):
# If we've reached here, either the user has enabled offline chat or the openai model is enabled.
if await ConversationAdapters.ahas_offline_chat():
offline_chat_config = await ConversationAdapters.aget_offline_chat_conversation_config()
conversation_config = await ConversationAdapters.aget_conversation_config(user)
if conversation_config is None:
conversation_config = await ConversationAdapters.aget_default_conversation_config()
openai_chat_config = await ConversationAdapters.aget_openai_conversation_config()
if (
offline_chat_config
and offline_chat_config.enabled
and conversation_config.model_type == ChatModelOptions.ModelType.OFFLINE.value
):
using_offline_chat = True
offline_chat = await ConversationAdapters.get_offline_chat()
chat_model = offline_chat.chat_model
@@ -681,7 +691,7 @@ async def extract_references_and_questions(
inferred_queries = extract_questions_offline(
defiltered_query, loaded_model=loaded_model, conversation_log=meta_log, should_extract_questions=False
)
elif await ConversationAdapters.has_openai_chat():
elif openai_chat_config and conversation_config.model_type == ChatModelOptions.ModelType.OPENAI.value:
openai_chat_config = await ConversationAdapters.get_openai_chat_config()
openai_chat = await ConversationAdapters.get_openai_chat()
api_key = openai_chat_config.api_key
@@ -690,11 +700,6 @@ async def extract_references_and_questions(
defiltered_query, model=chat_model, api_key=api_key, conversation_log=meta_log
)
logger.info(f"🔍 Inferred queries: {inferred_queries}")
logger.info(f"🔍 Defiltered query: {defiltered_query}")
logger.info(f"using max distance: {d}")
logger.info(f"using filters: {filters_in_query}")
logger.info(f"Max results: {n}")
# Collate search results as context for GPT
with timer("Searching knowledge base took", logger):
result_list = []
@@ -711,20 +716,7 @@ async def extract_references_and_questions(
common=common,
)
)
logger.info(f"🔍 Found {len(result_list)} results")
logger.info(f"Confidence scores: {[item.score for item in result_list]}")
# Dedupe the results again, as duplicates may be returned across queries.
with open("compiled_references_pre_deduped.txt", "w") as f:
for item in compiled_references:
f.write(f"{item}\n")
result_list = text_search.deduplicated_search_responses(result_list)
compiled_references = [item.additional["compiled"] for item in result_list]
with open("compiled_references_deduped.txt", "w") as f:
for item in compiled_references:
f.write(f"{item}\n")
logger.info(f"🔍 Deduped results: {len(result_list)}")
return compiled_references, inferred_queries, defiltered_query