apunkt/SurfSense
1
0
Fork 0
mirror of https://github.com/MODSetter/SurfSense.git synced 2026-05-08 23:32:40 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

Merge main to Llamaindex-chatui

Browse source
This commit is contained in:
Utkarsh-Patel-13 2025-07-25 19:41:05 -07:00
commit f006a76587
104 changed files with 12412 additions and 7680 deletions
Download patch file Download diff file Expand all files Collapse all files

29
surfsense_backend/app/agents/researcher/qna_agent/nodes.py
View file

@ -1,18 +1,21 @@
from app.services.reranker_service import RerankerService
from .configuration import Configuration
from langchain_core.runnables import RunnableConfig
from .state import State
from typing import Any, Dict
from .prompts import get_qna_citation_system_prompt, get_qna_no_documents_system_prompt
from typing import Any
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.runnables import RunnableConfig
from app.services.reranker_service import RerankerService
from ..utils import (
optimize_documents_for_token_limit,
calculate_token_count,
format_documents_section,
optimize_documents_for_token_limit,
)
from .configuration import Configuration
from .prompts import get_qna_citation_system_prompt, get_qna_no_documents_system_prompt
from .state import State
async def rerank_documents(state: State, config: RunnableConfig) -> Dict[str, Any]:
async def rerank_documents(state: State, config: RunnableConfig) -> dict[str, Any]:
"""
Rerank the documents based on relevance to the user's question.
@ -71,13 +74,13 @@ async def rerank_documents(state: State, config: RunnableConfig) -> Dict[str, An
f"Reranked {len(reranked_docs)} documents for Q&A query: {user_query}"
)
except Exception as e:
print(f"Error during reranking: {str(e)}")
print(f"Error during reranking: {e!s}")
# Use original docs if reranking fails
return {"reranked_documents": reranked_docs}
async def answer_question(state: State, config: RunnableConfig) -> Dict[str, Any]:
async def answer_question(state: State, config: RunnableConfig) -> dict[str, Any]:
"""
Answer the user's question using the provided documents.
@ -122,7 +125,8 @@ async def answer_question(state: State, config: RunnableConfig) -> Dict[str, Any
# Use initial system prompt for token calculation
initial_system_prompt = get_qna_citation_system_prompt()
base_messages = state.chat_history + [
base_messages = [
*state.chat_history,
SystemMessage(content=initial_system_prompt),
HumanMessage(content=base_human_message_template),
]
@ -173,7 +177,8 @@ async def answer_question(state: State, config: RunnableConfig) -> Dict[str, Any
"""
# Create final messages for the LLM
messages_with_chat_history = state.chat_history + [
messages_with_chat_history = [
*state.chat_history,
SystemMessage(content=system_prompt),
HumanMessage(content=human_message_content),
]