Feat/improve simple reasoning

libs/kotaemon/kotaemon/contribs/promptui/tunnel.py

@@ -17,8 +17,7 @@
 BINARY_REMOTE_NAME = f"frpc_{platform.system().lower()}_{machine.lower()}"
 EXTENSION = ".exe" if os.name == "nt" else ""
 BINARY_URL = (
-    "some-endpoint.com"
-    f"/kotaemon/tunneling/{VERSION}/{BINARY_REMOTE_NAME}{EXTENSION}"
+    "some-endpoint.com" f"/kotaemon/tunneling/{VERSION}/{BINARY_REMOTE_NAME}{EXTENSION}"
 )
 
 BINARY_FILENAME = f"{BINARY_REMOTE_NAME}_v{VERSION}"

libs/kotaemon/kotaemon/llms/chats/langchain_based.py

@@ -194,7 +194,6 @@ def _get_lc_class(self):
 
 
 class AzureChatOpenAI(LCChatMixin, ChatLLM):  # type: ignore
-
     def __init__(
         self,
         azure_endpoint: str | None = None,

libs/ktem/ktem/components.py

@@ -1,4 +1,5 @@
 """Common components, some kind of config"""
+
 import logging
 from functools import cache
 from pathlib import Path
@@ -71,7 +72,7 @@ def settings(self) -> dict:
         }
 
     def options(self) -> dict:
-        """Present a list of models"""
+        """Present a dict of models"""
         return self._models
 
     def get_random_name(self) -> str:

libs/ktem/ktem/index/file/pipelines.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import logging
 import shutil
 import warnings
 from collections import defaultdict
@@ -8,7 +9,7 @@
 from pathlib import Path
 from typing import Optional
 
-from ktem.components import embeddings, filestorage_path, llms
+from ktem.components import embeddings, filestorage_path
 from ktem.db.models import engine
 from llama_index.vector_stores import (
     FilterCondition,
@@ -25,10 +26,12 @@
 from kotaemon.base import RetrievedDocument
 from kotaemon.indices import VectorIndexing, VectorRetrieval
 from kotaemon.indices.ingests import DocumentIngestor
-from kotaemon.indices.rankings import BaseReranking, LLMReranking
+from kotaemon.indices.rankings import BaseReranking
 
 from .base import BaseFileIndexIndexing, BaseFileIndexRetriever
 
+logger = logging.getLogger(__name__)
+
 
 @lru_cache
 def dev_settings():
@@ -67,7 +70,7 @@ class DocumentRetrievalPipeline(BaseFileIndexRetriever):
     vector_retrieval: VectorRetrieval = VectorRetrieval.withx(
         embedding=embeddings.get_default(),
     )
-    reranker: BaseReranking = LLMReranking.withx(llm=llms.get_lowest_cost())
+    reranker: BaseReranking
     get_extra_table: bool = False
 
     def run(
@@ -153,7 +156,23 @@ def run(
 
     @classmethod
     def get_user_settings(cls) -> dict:
+        from ktem.components import llms
+
+        try:
+            reranking_llm = llms.get_lowest_cost_name()
+            reranking_llm_choices = list(llms.options().keys())
+        except Exception as e:
+            logger.error(e)
+            reranking_llm = None
+            reranking_llm_choices = []
+
         return {
+            "reranking_llm": {
+                "name": "LLM for reranking",
+                "value": reranking_llm,
+                "component": "dropdown",
+                "choices": reranking_llm_choices,
+            },
             "separate_embedding": {
                 "name": "Use separate embedding",
                 "value": False,
@@ -185,7 +204,7 @@ def get_user_settings(cls) -> dict:
             },
             "use_reranking": {
                 "name": "Use reranking",
-                "value": True,
+                "value": False,
                 "choices": [True, False],
                 "component": "checkbox",
             },
@@ -199,7 +218,10 @@ def get_pipeline(cls, user_settings, index_settings, selected):
             settings: the settings of the app
             kwargs: other arguments
         """
-        retriever = cls(get_extra_table=user_settings["prioritize_table"])
+        retriever = cls(
+            get_extra_table=user_settings["prioritize_table"],
+            reranker=user_settings["reranking_llm"],
+        )
         if not user_settings["use_reranking"]:
             retriever.reranker = None  # type: ignore
 

libs/ktem/ktem/pages/settings.py

@@ -87,6 +87,28 @@ def on_building_ui(self):
             self.reasoning_tab()
 
     def on_subscribe_public_events(self):
+        """
+        Subscribes to public events related to user management.
+
+        This function is responsible for subscribing to the "onSignIn" event, which is
+        triggered when a user signs in. It registers two event handlers for this event.
+
+        The first event handler, "load_setting", is responsible for loading the user's
+        settings when they sign in. It takes the user ID as input and returns the
+        settings state and a list of component outputs. The progress indicator for this
+        event is set to "hidden".
+
+        The second event handler, "get_name", is responsible for retrieving the
+        username of the current user. It takes the user ID as input and returns the
+        username if it exists, otherwise it returns "___". The progress indicator for
+        this event is also set to "hidden".
+
+        Parameters:
+            self (object): The instance of the class.
+
+        Returns:
+            None
+        """
         if self._app.f_user_management:
             self._app.subscribe_event(
                 name="onSignIn",
@@ -290,3 +312,12 @@ def components(self) -> list:
     def component_names(self):
         """Get the setting components"""
         return self._settings_keys
+
+    def _on_app_created(self):
+        if not self._app.f_user_management:
+            self._app.app.load(
+                self.load_setting,
+                inputs=self._user_id,
+                outputs=[self._settings_state] + self.components(),
+                show_progress="hidden",
+            )

libs/ktem/ktem/reasoning/simple.py

@@ -159,6 +159,7 @@ class AnswerWithContextPipeline(BaseComponent):
     qa_table_template: str = DEFAULT_QA_TABLE_PROMPT
     qa_chatbot_template: str = DEFAULT_QA_CHATBOT_PROMPT
 
+    enable_citation: bool = False
     system_prompt: str = ""
     lang: str = "English"  # support English and Japanese
 
@@ -200,7 +201,8 @@ async def run(  # type: ignore
             lang=self.lang,
         )
 
-        if evidence:
+        citation_task = None
+        if evidence and self.enable_citation:
             citation_task = asyncio.create_task(
                 self.citation_pipeline.ainvoke(context=evidence, question=question)
             )
@@ -226,7 +228,7 @@ async def run(  # type: ignore
 
         # retrieve the citation
         print("Waiting for citation task")
-        if evidence:
+        if citation_task is not None:
             citation = await citation_task
         else:
             citation = None
@@ -353,7 +355,15 @@ def get_pipeline(cls, settings, retrievers):
         _id = cls.get_info()["id"]
 
         pipeline = FullQAPipeline(retrievers=retrievers)
-        pipeline.answering_pipeline.llm = llms.get_highest_accuracy()
+        pipeline.answering_pipeline.llm = llms[
+            settings[f"reasoning.options.{_id}.main_llm"]
+        ]
+        pipeline.answering_pipeline.citation_pipeline.llm = llms[
+            settings[f"reasoning.options.{_id}.citation_llm"]
+        ]
+        pipeline.answering_pipeline.enable_citation = settings[
+            f"reasoning.options.{_id}.highlight_citation"
+        ]
         pipeline.answering_pipeline.lang = {"en": "English", "ja": "Japanese"}.get(
             settings["reasoning.lang"], "English"
         )
@@ -384,7 +394,7 @@ def get_user_settings(cls) -> dict:
         return {
             "highlight_citation": {
                 "name": "Highlight Citation",
-                "value": True,
+                "value": False,
                 "component": "checkbox",
             },
             "citation_llm": {