feat: add support for reasoning llm with thought visualization (#652) bump:patch
* fix: lanceDB query with empty file_ids * feat: add thinking display * feat: add low request mode for local llm
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@ -80,3 +80,18 @@ def find_start_end_phrase(
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final_match = None
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return final_match, matched_length
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def replace_think_tag_with_details(text):
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text = text.replace(
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"<think>",
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'<details><summary><span style="color:grey">Thought</span></summary><blockquote>', # noqa
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)
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text = text.replace("</think>", "</blockquote></details>")
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return text
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def strip_think_tag(text):
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if "</think>" in text:
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text = text.split("</think>")[1]
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return text
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@ -98,6 +98,9 @@ class LanceDBDocumentStore(BaseDocumentStore):
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if not isinstance(ids, list):
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ids = [ids]
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if len(ids) == 0:
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return []
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id_filter = ", ".join([f"'{_id}'" for _id in ids])
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try:
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document_collection = self.db_connection.open_table(self.collection_name)
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@ -14,6 +14,7 @@ from pathlib import Path
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from typing import Generator, Optional, Sequence
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import tiktoken
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from decouple import config
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from ktem.db.models import engine
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from ktem.embeddings.manager import embedding_models_manager
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from ktem.llms.manager import llms
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@ -270,7 +271,7 @@ class DocumentRetrievalPipeline(BaseFileIndexRetriever):
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},
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"use_llm_reranking": {
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"name": "Use LLM relevant scoring",
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"value": True,
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"value": not config("USE_LOW_LLM_REQUESTS", default=False, cast=bool),
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"choices": [True, False],
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"component": "checkbox",
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},
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@ -5,6 +5,7 @@ from copy import deepcopy
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from typing import Optional
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import gradio as gr
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from decouple import config
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from ktem.app import BasePage
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from ktem.components import reasonings
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from ktem.db.models import Conversation, engine
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@ -23,6 +24,7 @@ from theflow.utils.modules import import_dotted_string
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from kotaemon.base import Document
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from kotaemon.indices.ingests.files import KH_DEFAULT_FILE_EXTRACTORS
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from kotaemon.indices.qa.utils import strip_think_tag
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from ...utils import SUPPORTED_LANGUAGE_MAP, get_file_names_regex, get_urls
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from ...utils.commands import WEB_SEARCH_COMMAND
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@ -367,13 +369,22 @@ class ChatPage(BasePage):
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elem_id="citation-dropdown",
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)
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self.use_mindmap = gr.State(value=True)
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self.use_mindmap_check = gr.Checkbox(
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label="Mindmap (on)",
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container=False,
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elem_id="use-mindmap-checkbox",
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value=True,
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)
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if not config("USE_LOW_LLM_REQUESTS", default=False, cast=bool):
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self.use_mindmap = gr.State(value=True)
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self.use_mindmap_check = gr.Checkbox(
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label="Mindmap (on)",
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container=False,
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elem_id="use-mindmap-checkbox",
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value=True,
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)
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else:
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self.use_mindmap = gr.State(value=False)
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self.use_mindmap_check = gr.Checkbox(
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label="Mindmap (off)",
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container=False,
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elem_id="use-mindmap-checkbox",
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value=False,
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)
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with gr.Column(
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scale=INFO_PANEL_SCALES[False], elem_id="chat-info-panel"
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@ -1361,6 +1372,7 @@ class ChatPage(BasePage):
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# check if this is a newly created conversation
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if len(chat_history) == 1:
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suggested_name = suggest_pipeline(chat_history).text
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suggested_name = strip_think_tag(suggested_name)
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suggested_name = suggested_name.replace('"', "").replace("'", "")[:40]
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new_name = gr.update(value=suggested_name)
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renamed = True
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@ -3,6 +3,7 @@ import threading
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from textwrap import dedent
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from typing import Generator
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from decouple import config
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from ktem.embeddings.manager import embedding_models_manager as embeddings
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from ktem.llms.manager import llms
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from ktem.reasoning.prompt_optimization import (
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@ -29,6 +30,7 @@ from kotaemon.indices.qa.citation_qa import (
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)
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from kotaemon.indices.qa.citation_qa_inline import AnswerWithInlineCitation
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from kotaemon.indices.qa.format_context import PrepareEvidencePipeline
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from kotaemon.indices.qa.utils import replace_think_tag_with_details
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from kotaemon.llms import ChatLLM
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from ..utils import SUPPORTED_LANGUAGE_MAP
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@ -313,6 +315,13 @@ class FullQAPipeline(BaseReasoning):
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**kwargs,
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)
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# check <think> tag from reasoning models
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processed_answer = replace_think_tag_with_details(answer.text)
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if processed_answer != answer.text:
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# clear the chat message and render again
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yield Document(channel="chat", content=None)
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yield Document(channel="chat", content=processed_answer)
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# show the evidence
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if scoring_thread:
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scoring_thread.join()
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@ -410,7 +419,11 @@ class FullQAPipeline(BaseReasoning):
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},
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"highlight_citation": {
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"name": "Citation style",
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"value": "highlight",
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"value": (
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"highlight"
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if not config("USE_LOW_LLM_REQUESTS", default=False, cast=bool)
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else "off"
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),
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"component": "radio",
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"choices": [
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("citation: highlight", "highlight"),
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