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remove lite_llm; distinguish if first message or whole conversation in chat querifier; Add info to README

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Niklas Müller 2024-06-23 19:27:11 +02:00
parent 889816a9a5
commit 49796a4657
2 changed files with 11 additions and 5 deletions
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3
.env
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@ -42,6 +42,5 @@ LLM_API_KEY=placeholder
# valid Language options - "en" "de" "multi" # valid Language options - "en" "de" "multi"
LLM_LANGUAGE=de LLM_LANGUAGE=de
# LLM Model to be used - "mistral", "phi3", "llama3", etc. # LLM Model to be used - "mistral", "phi3", "llama3", etc. (Check available with <ip_of_ollama_instance>:11434/api/tags)
LLM_MODEL_NAME=mistral LLM_MODEL_NAME=mistral

13
rag-chat-backend/src/endpoints/llm.py
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@ -38,7 +38,6 @@ SEARCH_COMPONENT = IndexSearchComponent(os_client=OS_INTERFACE)
PROMPTS = LLM.prompt_obj PROMPTS = LLM.prompt_obj
llm_component_name = "ollama-llm" llm_component_name = "ollama-llm"
selected_language = "german" selected_language = "german"
lite_llm = os.getenv("LITE_LLM")
stream_llms = ["fu"] stream_llms = ["fu"]
@ -97,7 +96,15 @@ def chat(stream_response, messages, tags=None, languages: str = None, start_date
raise HTTPException(status_code=400, detail="Invalid format for 'messages'") raise HTTPException(status_code=400, detail="Invalid format for 'messages'")
# provides you a query based on the whole chat # provides you a query based on the whole chat
query = LLM.llm_chat_querifier(chat=messages) if len(messages) <= 2:
if messages[0]["role"] == "user":
query = messages[0]["content"]
elif messages[1]["role"] == "user":
query = messages[1]["content"]
else:
query = LLM.llm_chat_querifier(chat=messages)
else:
query = LLM.llm_chat_querifier(chat=messages)
logger.info("Generated query: '%s'", query) logger.info("Generated query: '%s'", query)
# creating a new dashboard logger at the start of the project # creating a new dashboard logger at the start of the project
@ -137,7 +144,7 @@ def chat(stream_response, messages, tags=None, languages: str = None, start_date
# check if chat is allowed for selected llm # check if chat is allowed for selected llm
logger.info("Stream response: %s", stream_response) logger.info("Stream response: %s", stream_response)
if stream_response == "true": if stream_response == "true":
if lite_llm == "true" or llm_component_name in stream_llms: if llm_component_name in stream_llms:
answer = LLM.llm_chat_request( answer = LLM.llm_chat_request(
chat=messages, chat=messages,
context=formatted_context, context=formatted_context,