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Feature: adjusted to handle individual rag config

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This commit is contained in:
weberm1 2025-05-23 10:47:27 +02:00
parent 4189459ae2
commit b7023eb564
1 changed files with 33 additions and 15 deletions
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48
backend/open_webui/utils/middleware.py
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@ -549,7 +549,7 @@ async def chat_image_generation_handler(
async def chat_completion_files_handler(
request: Request, body: dict, user: UserModel
request: Request, body: dict, user: UserModel, model_knowledge
) -> tuple[dict, dict[str, list]]:
sources = []
@ -587,6 +587,20 @@ async def chat_completion_files_handler(
queries = [get_last_user_message(body["messages"])]
try:
# check if individual rag config is used
rag_config = {}
if model_knowledge and not model_knowledge[0].get("rag_config").get("DEFAULT_RAG_SETTINGS", True):
rag_config = model_knowledge[0].get("rag_config")
k=rag_config.get("TOP_K", request.app.state.config.TOP_K)
reranking_model = rag_config.get("RAG_RERANKING_MODEL", request.app.state.config.RAG_RERANKING_MODEL)
reranking_function=request.app.state.rf[reranking_model] if reranking_model else None
k_reranker=rag_config.get("TOP_K_RERANKER", request.app.state.config.TOP_K_RERANKER)
r=rag_config.get("RELEVANCE THRESHOLD", request.app.state.config.RELEVANCE_THRESHOLD)
hybrid_search=rag_config.get("ENABLE_RAG_HYBRID_SEARCH", request.app.state.config.ENABLE_RAG_HYBRID_SEARCH)
full_context=rag_config.get("RAG_FULL_CONTEXT", request.app.state.config.RAG_FULL_CONTEXT)
embedding_model = rag_config.get("RAG_EMBEDDING_MODEL", request.app.state.config.RAG_EMBEDDING_MODEL)
# Offload get_sources_from_files to a separate thread
loop = asyncio.get_running_loop()
with ThreadPoolExecutor() as executor:
@ -596,15 +610,15 @@ async def chat_completion_files_handler(
request=request,
files=files,
queries=queries,
embedding_function=lambda query, prefix: request.app.state.EMBEDDING_FUNCTION(
embedding_function=lambda query, prefix: request.app.state.EMBEDDING_FUNCTION[embedding_model](
query, prefix=prefix, user=user
),
k=request.app.state.config.TOP_K,
reranking_function=request.app.state.rf,
k_reranker=request.app.state.config.TOP_K_RERANKER,
r=request.app.state.config.RELEVANCE_THRESHOLD,
hybrid_search=request.app.state.config.ENABLE_RAG_HYBRID_SEARCH,
full_context=request.app.state.config.RAG_FULL_CONTEXT,
k=k,
reranking_function=reranking_function,
k_reranker=k_reranker,
r=r,
hybrid_search=hybrid_search,
full_context=full_context,
),
)
except Exception as e:
@ -862,7 +876,7 @@ async def process_chat_payload(request, form_data, user, metadata, model):
log.exception(e)
try:
form_data, flags = await chat_completion_files_handler(request, form_data, user)
form_data, flags = await chat_completion_files_handler(request, form_data, user, model_knowledge)
sources.extend(flags.get("sources", []))
except Exception as e:
log.exception(e)
@ -898,20 +912,24 @@ async def process_chat_payload(request, form_data, user, metadata, model):
f"With a 0 relevancy threshold for RAG, the context cannot be empty"
)
# Adjusted RAG template step to use knowledge-base-specific configuration
rag_template_config = request.app.state.config.RAG_TEMPLATE
if model_knowledge and not model_knowledge[0].get("rag_config").get("DEFAULT_RAG_SETTINGS", True):
rag_template_config = model_knowledge[0].get("rag_config").get(
"RAG_TEMPLATE", request.app.state.config.RAG_TEMPLATE
)
# Workaround for Ollama 2.0+ system prompt issue
# TODO: replace with add_or_update_system_message
if model.get("owned_by") == "ollama":
form_data["messages"] = prepend_to_first_user_message_content(
rag_template(
request.app.state.config.RAG_TEMPLATE, context_string, prompt
),
rag_template(rag_template_config, context_string, prompt),
form_data["messages"],
)
else:
form_data["messages"] = add_or_update_system_message(
rag_template(
request.app.state.config.RAG_TEMPLATE, context_string, prompt
),
rag_template(rag_template_config, context_string, prompt),
form_data["messages"],
)