fix: Fix rerank_documents node in sub_section_writer & qna_agent

This commit is contained in:
DESKTOP-RTLN3BA\$punk 2025-07-03 14:09:36 -07:00
parent 3e1db2ac6b
commit 671984acbd
6 changed files with 2708 additions and 1923 deletions

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@ -2,11 +2,10 @@ import asyncio
import json
from typing import Any, Dict, List
from app.db import async_session_maker
from app.utils.connector_service import ConnectorService
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.runnables import RunnableConfig
from pydantic import BaseModel, Field
from sqlalchemy.ext.asyncio import AsyncSession
from .configuration import Configuration, SearchMode
@ -15,6 +14,7 @@ from .state import State
from .sub_section_writer.graph import graph as sub_section_writer_graph
from .sub_section_writer.configuration import SubSectionType
from .qna_agent.graph import graph as qna_agent_graph
from .utils import AnswerOutline, get_connector_emoji, get_connector_friendly_name
from app.utils.query_service import QueryService
@ -24,7 +24,6 @@ from langgraph.types import StreamWriter
from sqlalchemy.future import select
from app.db import Document, SearchSpace
async def fetch_documents_by_ids(
document_ids: List[int],
user_id: str,
@ -252,16 +251,6 @@ async def fetch_documents_by_ids(
return [], []
class Section(BaseModel):
"""A section in the answer outline."""
section_id: int = Field(..., description="The zero-based index of the section")
section_title: str = Field(..., description="The title of the section")
questions: List[str] = Field(..., description="Questions to research for this section")
class AnswerOutline(BaseModel):
"""The complete answer outline with all sections."""
answer_outline: List[Section] = Field(..., description="List of sections in the answer outline")
async def write_answer_outline(state: State, config: RunnableConfig, writer: StreamWriter) -> Dict[str, Any]:
"""
Create a structured answer outline based on the user query.
@ -379,6 +368,7 @@ async def write_answer_outline(state: State, config: RunnableConfig, writer: Str
print(f"Raw response: {response.content}")
raise
async def fetch_relevant_documents(
research_questions: List[str],
user_id: str,
@ -746,37 +736,6 @@ async def fetch_relevant_documents(
# Return deduplicated documents
return deduplicated_docs
def get_connector_emoji(connector_name: str) -> str:
"""Get an appropriate emoji for a connector type."""
connector_emojis = {
"YOUTUBE_VIDEO": "📹",
"EXTENSION": "🧩",
"CRAWLED_URL": "🌐",
"FILE": "📄",
"SLACK_CONNECTOR": "💬",
"NOTION_CONNECTOR": "📘",
"GITHUB_CONNECTOR": "🐙",
"LINEAR_CONNECTOR": "📊",
"TAVILY_API": "🔍",
"LINKUP_API": "🔗"
}
return connector_emojis.get(connector_name, "🔎")
def get_connector_friendly_name(connector_name: str) -> str:
"""Convert technical connector IDs to user-friendly names."""
connector_friendly_names = {
"YOUTUBE_VIDEO": "YouTube",
"EXTENSION": "Browser Extension",
"CRAWLED_URL": "Web Pages",
"FILE": "Files",
"SLACK_CONNECTOR": "Slack",
"NOTION_CONNECTOR": "Notion",
"GITHUB_CONNECTOR": "GitHub",
"LINEAR_CONNECTOR": "Linear",
"TAVILY_API": "Tavily Search",
"LINKUP_API": "Linkup Search"
}
return connector_friendly_names.get(connector_name, connector_name)
async def process_sections(state: State, config: RunnableConfig, writer: StreamWriter) -> Dict[str, Any]:
"""
@ -969,6 +928,7 @@ async def process_sections(state: State, config: RunnableConfig, writer: StreamW
"final_written_report": final_written_report
}
async def process_section_with_documents(
section_id: int,
section_title: str,
@ -1106,7 +1066,6 @@ async def process_section_with_documents(
return f"Error processing section: {section_title}. Details: {str(e)}"
async def reformulate_user_query(state: State, config: RunnableConfig, writer: StreamWriter) -> Dict[str, Any]:
"""
Reforms the user query based on the chat history.
@ -1124,6 +1083,7 @@ async def reformulate_user_query(state: State, config: RunnableConfig, writer: S
"reformulated_query": reformulated_query
}
async def handle_qna_workflow(state: State, config: RunnableConfig, writer: StreamWriter) -> Dict[str, Any]:
"""
Handle the QNA research workflow.

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@ -1,8 +1,8 @@
from app.utils.reranker_service import RerankerService
from .configuration import Configuration
from langchain_core.runnables import RunnableConfig
from .state import State
from typing import Any, Dict
from app.config import config as app_config
from .prompts import get_qna_citation_system_prompt, get_qna_no_documents_system_prompt
from langchain_core.messages import HumanMessage, SystemMessage
from ..utils import (
@ -35,7 +35,7 @@ async def rerank_documents(state: State, config: RunnableConfig) -> Dict[str, An
}
# Get reranker service from app config
reranker_service = getattr(app_config, "reranker_service", None)
reranker_service = RerankerService.get_reranker_instance()
# Use documents as is if no reranker service is available
reranked_docs = documents

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@ -2,7 +2,7 @@ from .configuration import Configuration
from langchain_core.runnables import RunnableConfig
from .state import State
from typing import Any, Dict
from app.config import config as app_config
from app.utils.reranker_service import RerankerService
from .prompts import get_citation_system_prompt, get_no_documents_system_prompt
from langchain_core.messages import HumanMessage, SystemMessage
from .configuration import SubSectionType
@ -35,7 +35,7 @@ async def rerank_documents(state: State, config: RunnableConfig) -> Dict[str, An
}
# Get reranker service from app config
reranker_service = getattr(app_config, "reranker_service", None)
reranker_service = RerankerService.get_reranker_instance()
# Use documents as is if no reranker service is available
reranked_docs = documents

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@ -1,7 +1,18 @@
from typing import List, Dict, Any, Tuple, NamedTuple
from langchain_core.messages import BaseMessage
from pydantic import BaseModel, Field
from litellm import token_counter, get_model_info
class Section(BaseModel):
"""A section in the answer outline."""
section_id: int = Field(..., description="The zero-based index of the section")
section_title: str = Field(..., description="The title of the section")
questions: List[str] = Field(..., description="Questions to research for this section")
class AnswerOutline(BaseModel):
"""The complete answer outline with all sections."""
answer_outline: List[Section] = Field(..., description="List of sections in the answer outline")
class DocumentTokenInfo(NamedTuple):
"""Information about a document and its token cost."""
@ -9,6 +20,40 @@ class DocumentTokenInfo(NamedTuple):
document: Dict[str, Any]
formatted_content: str
token_count: int
def get_connector_emoji(connector_name: str) -> str:
"""Get an appropriate emoji for a connector type."""
connector_emojis = {
"YOUTUBE_VIDEO": "📹",
"EXTENSION": "🧩",
"CRAWLED_URL": "🌐",
"FILE": "📄",
"SLACK_CONNECTOR": "💬",
"NOTION_CONNECTOR": "📘",
"GITHUB_CONNECTOR": "🐙",
"LINEAR_CONNECTOR": "📊",
"TAVILY_API": "🔍",
"LINKUP_API": "🔗"
}
return connector_emojis.get(connector_name, "🔎")
def get_connector_friendly_name(connector_name: str) -> str:
"""Convert technical connector IDs to user-friendly names."""
connector_friendly_names = {
"YOUTUBE_VIDEO": "YouTube",
"EXTENSION": "Browser Extension",
"CRAWLED_URL": "Web Pages",
"FILE": "Files",
"SLACK_CONNECTOR": "Slack",
"NOTION_CONNECTOR": "Notion",
"GITHUB_CONNECTOR": "GitHub",
"LINEAR_CONNECTOR": "Linear",
"TAVILY_API": "Tavily Search",
"LINKUP_API": "Linkup Search"
}
return connector_friendly_names.get(connector_name, connector_name)
def convert_langchain_messages_to_dict(messages: List[BaseMessage]) -> List[Dict[str, str]]:

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@ -80,16 +80,16 @@ class RerankerService:
return documents
@staticmethod
def get_reranker_instance(config=None) -> Optional['RerankerService']:
def get_reranker_instance() -> Optional['RerankerService']:
"""
Get a reranker service instance based on configuration
Get a reranker service instance from the global configuration.
Args:
config: Configuration object that may contain a reranker_instance
Returns:
Optional[RerankerService]: A reranker service instance or None
Optional[RerankerService]: A reranker service instance if configured, None otherwise
"""
if config and hasattr(config, 'reranker_instance') and config.reranker_instance:
from app.config import config
if hasattr(config, 'reranker_instance') and config.reranker_instance:
return RerankerService(config.reranker_instance)
return None
return None

4512
surfsense_backend/uv.lock generated

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