Feat/regenerate answer (#7)
* Add regen button and repharasing question on regen * Stop appending regen messages to history, allow only one * Add dynamic conversation state * Allow reasoning pipeline to manipulate state --------- Co-authored-by: albert <albert@cinnamon.is> Co-authored-by: Duc Nguyen (john) <trungduc1992@gmail.com>
This commit is contained in:
parent
e67a25c0bd
commit
43a18ba070
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@ -15,8 +15,6 @@ from decouple import config
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from kotaemon.loaders.utils.gpt4v import generate_gpt4v
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logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO"))
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def request_adobe_service(file_path: str, output_path: str = "") -> str:
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"""Main function to call the adobe service, and unzip the results.
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@ -17,6 +17,7 @@ class BaseApp:
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The main application contains app-level information:
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- setting state
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- dynamic conversation state
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- user id
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Also contains registering methods for:
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@ -9,6 +9,7 @@ from ktem.db.models import Conversation, engine
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from sqlmodel import Session, select
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from .chat_panel import ChatPanel
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from .common import STATE
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from .control import ConversationControl
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from .report import ReportIssue
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@ -21,6 +22,7 @@ class ChatPage(BasePage):
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def on_building_ui(self):
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with gr.Row():
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self.chat_state = gr.State(STATE)
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with gr.Column(scale=1):
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self.chat_control = ConversationControl(self._app)
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@ -62,12 +64,13 @@ class ChatPage(BasePage):
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self.chat_control.conversation_id,
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self.chat_panel.chatbot,
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self._app.settings_state,
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self.chat_state,
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]
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+ self._indices_input,
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outputs=[
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self.chat_panel.text_input,
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self.chat_panel.chatbot,
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self.info_panel,
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self.chat_state,
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],
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show_progress="minimal",
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).then(
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@ -75,6 +78,33 @@ class ChatPage(BasePage):
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inputs=[
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self.chat_control.conversation_id,
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self.chat_panel.chatbot,
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self.chat_state,
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]
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+ self._indices_input,
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outputs=None,
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)
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self.chat_panel.regen_btn.click(
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fn=self.regen_fn,
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inputs=[
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self.chat_control.conversation_id,
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self.chat_panel.chatbot,
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self._app.settings_state,
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self.chat_state,
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]
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+ self._indices_input,
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outputs=[
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self.chat_panel.chatbot,
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self.info_panel,
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self.chat_state,
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],
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show_progress="minimal",
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).then(
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fn=self.update_data_source,
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inputs=[
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self.chat_control.conversation_id,
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self.chat_panel.chatbot,
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self.chat_state,
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]
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+ self._indices_input,
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outputs=None,
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@ -94,6 +124,7 @@ class ChatPage(BasePage):
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self.chat_control.conversation,
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self.chat_control.conversation_rn,
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self.chat_panel.chatbot,
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self.chat_state,
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]
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+ self._indices_input,
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show_progress="hidden",
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@ -109,12 +140,13 @@ class ChatPage(BasePage):
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self.chat_panel.chatbot,
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self._app.settings_state,
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self._app.user_id,
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self.chat_state,
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]
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+ self._indices_input,
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outputs=None,
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)
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def update_data_source(self, convo_id, messages, *selecteds):
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def update_data_source(self, convo_id, messages, state, *selecteds):
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"""Update the data source"""
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if not convo_id:
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gr.Warning("No conversation selected")
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@ -133,6 +165,7 @@ class ChatPage(BasePage):
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result.data_source = {
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"selected": selecteds_,
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"messages": messages,
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"state": state,
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"likes": deepcopy(data_source.get("likes", [])),
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}
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session.add(result)
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@ -152,17 +185,22 @@ class ChatPage(BasePage):
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session.add(result)
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session.commit()
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def create_pipeline(self, settings: dict, *selecteds):
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def create_pipeline(self, settings: dict, state: dict, *selecteds):
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"""Create the pipeline from settings
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Args:
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settings: the settings of the app
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is_regen: whether the regen button is clicked
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selected: the list of file ids that will be served as context. If None, then
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consider using all files
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Returns:
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the pipeline objects
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- the pipeline objects
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"""
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reasoning_mode = settings["reasoning.use"]
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reasoning_cls = reasonings[reasoning_mode]
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reasoning_id = reasoning_cls.get_info()["id"]
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# get retrievers
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retrievers = []
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for index in self._app.index_manager.indices:
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@ -172,13 +210,17 @@ class ChatPage(BasePage):
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iretrievers = index.get_retriever_pipelines(settings, index_selected)
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retrievers += iretrievers
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reasoning_mode = settings["reasoning.use"]
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reasoning_cls = reasonings[reasoning_mode]
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pipeline = reasoning_cls.get_pipeline(settings, retrievers)
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# prepare states
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reasoning_state = {
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"app": deepcopy(state["app"]),
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"pipeline": deepcopy(state.get(reasoning_id, {})),
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}
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return pipeline
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pipeline = reasoning_cls.get_pipeline(settings, reasoning_state, retrievers)
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async def chat_fn(self, conversation_id, chat_history, settings, *selecteds):
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return pipeline, reasoning_state
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async def chat_fn(self, conversation_id, chat_history, settings, state, *selecteds):
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"""Chat function"""
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chat_input = chat_history[-1][0]
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chat_history = chat_history[:-1]
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@ -186,7 +228,7 @@ class ChatPage(BasePage):
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queue: asyncio.Queue[Optional[dict]] = asyncio.Queue()
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# construct the pipeline
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pipeline = self.create_pipeline(settings, *selecteds)
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pipeline, reasoning_state = self.create_pipeline(settings, state, *selecteds)
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pipeline.set_output_queue(queue)
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asyncio.create_task(pipeline(chat_input, conversation_id, chat_history))
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@ -198,7 +240,8 @@ class ChatPage(BasePage):
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try:
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response = queue.get_nowait()
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except Exception:
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yield "", chat_history + [(chat_input, text or "Thinking ...")], refs
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state[pipeline.get_info()["id"]] = reasoning_state["pipeline"]
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yield chat_history + [(chat_input, text or "Thinking ...")], refs, state
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continue
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if response is None:
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@ -208,6 +251,7 @@ class ChatPage(BasePage):
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if "output" in response:
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text += response["output"]
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if "evidence" in response:
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if response["evidence"] is None:
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refs = ""
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@ -218,4 +262,25 @@ class ChatPage(BasePage):
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print(f"Len refs: {len(refs)}")
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len_ref = len(refs)
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yield "", chat_history + [(chat_input, text)], refs
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state[pipeline.get_info()["id"]] = reasoning_state["pipeline"]
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yield chat_history + [(chat_input, text)], refs, state
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async def regen_fn(
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self, conversation_id, chat_history, settings, state, *selecteds
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):
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"""Regen function"""
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if not chat_history:
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gr.Warning("Empty chat")
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yield chat_history, "", state
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return
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state["app"]["regen"] = True
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async for chat, refs, state in self.chat_fn(
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conversation_id, chat_history, settings, state, *selecteds
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):
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new_state = deepcopy(state)
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new_state["app"]["regen"] = False
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yield chat, refs, new_state
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else:
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state["app"]["regen"] = False
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yield chat_history, "", state
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@ -19,6 +19,7 @@ class ChatPanel(BasePage):
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placeholder="Chat input", scale=15, container=False
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)
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self.submit_btn = gr.Button(value="Send", scale=1, min_width=10)
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self.regen_btn = gr.Button(value="Regen", scale=1, min_width=10)
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def submit_msg(self, chat_input, chat_history):
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"""Submit a message to the chatbot"""
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4
libs/ktem/ktem/pages/chat/common.py
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4
libs/ktem/ktem/pages/chat/common.py
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DEFAULT_APPLICATION_STATE = {"regen": False}
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STATE = {
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"app": DEFAULT_APPLICATION_STATE,
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}
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@ -5,6 +5,8 @@ from ktem.app import BasePage
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from ktem.db.models import Conversation, engine
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from sqlmodel import Session, select
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from .common import STATE
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logger = logging.getLogger(__name__)
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@ -159,12 +161,14 @@ class ConversationControl(BasePage):
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name = result.name
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selected = result.data_source.get("selected", {})
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chats = result.data_source.get("messages", [])
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state = result.data_source.get("state", STATE)
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except Exception as e:
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logger.warning(e)
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id_ = ""
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name = ""
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selected = {}
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chats = []
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state = STATE
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indices = []
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for index in self._app.index_manager.indices:
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@ -173,7 +177,7 @@ class ConversationControl(BasePage):
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continue
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indices.append(selected.get(str(index.id), []))
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return id_, id_, name, chats, *indices
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return id_, id_, name, chats, state, *indices
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def rename_conv(self, conversation_id, new_name, user_id):
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"""Rename the conversation"""
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@ -48,6 +48,7 @@ class ReportIssue(BasePage):
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chat_history: list,
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settings: dict,
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user_id: Optional[int],
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chat_state: dict,
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*selecteds
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):
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selecteds_ = {}
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chat={
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"conv_id": conv_id,
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"chat_history": chat_history,
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"chat_state": chat_state,
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"selecteds": selecteds_,
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},
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settings=settings,
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@ -7,7 +7,6 @@ from functools import partial
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import tiktoken
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from ktem.components import llms
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from ktem.reasoning.base import BaseReasoning
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from theflow.settings import settings as flowsettings
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from kotaemon.base import (
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"Answer: "
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)
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DEFAULT_REWRITE_PROMPT = (
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"Given the following question, rephrase and expand it "
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"to help you do better answering. Maintain all information "
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"in the original question. Keep the question as concise as possible. "
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"Give answer in {lang}\n"
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"Original question: {question}\n"
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"Rephrased question: "
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)
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class AnswerWithContextPipeline(BaseComponent):
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"""Answer the question based on the evidence
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@ -287,15 +295,48 @@ class AnswerWithContextPipeline(BaseComponent):
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return answer
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def extract_evidence_images(self, evidence: str):
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"""Util function to extract and isolate images from context/evidence"""
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image_pattern = r"src='(data:image\/[^;]+;base64[^']+)'"
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matches = re.findall(image_pattern, evidence)
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context = re.sub(image_pattern, "", evidence)
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return context, matches
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def extract_evidence_images(self, evidence: str):
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"""Util function to extract and isolate images from context/evidence"""
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image_pattern = r"src='(data:image\/[^;]+;base64[^']+)'"
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matches = re.findall(image_pattern, evidence)
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context = re.sub(image_pattern, "", evidence)
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return context, matches
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class FullQAPipeline(BaseReasoning):
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class RewriteQuestionPipeline(BaseComponent):
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"""Rewrite user question
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Args:
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llm: the language model to rewrite question
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rewrite_template: the prompt template for llm to paraphrase a text input
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lang: the language of the answer. Currently support English and Japanese
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"""
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llm: ChatLLM = Node(default_callback=lambda _: llms.get_lowest_cost())
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rewrite_template: str = DEFAULT_REWRITE_PROMPT
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lang: str = "English"
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async def run(self, question: str) -> Document: # type: ignore
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prompt_template = PromptTemplate(self.rewrite_template)
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prompt = prompt_template.populate(question=question, lang=self.lang)
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messages = [
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SystemMessage(content="You are a helpful assistant"),
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HumanMessage(content=prompt),
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]
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output = ""
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for text in self.llm(messages):
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if "content" in text:
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output += text[1]
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self.report_output({"chat_input": text[1]})
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break
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await asyncio.sleep(0)
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return Document(text=output)
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class FullQAPipeline(BaseComponent):
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"""Question answering pipeline. Handle from question to answer"""
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class Config:
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@ -305,12 +346,18 @@ class FullQAPipeline(BaseReasoning):
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evidence_pipeline: PrepareEvidencePipeline = PrepareEvidencePipeline.withx()
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answering_pipeline: AnswerWithContextPipeline = AnswerWithContextPipeline.withx()
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rewrite_pipeline: RewriteQuestionPipeline = RewriteQuestionPipeline.withx()
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use_rewrite: bool = False
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async def run( # type: ignore
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self, message: str, conv_id: str, history: list, **kwargs # type: ignore
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) -> Document: # type: ignore
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docs = []
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doc_ids = []
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if self.use_rewrite:
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rewrite = await self.rewrite_pipeline(question=message)
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message = rewrite.text
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for retriever in self.retrievers:
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for doc in retriever(text=message):
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if doc.doc_id not in doc_ids:
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@ -402,7 +449,7 @@ class FullQAPipeline(BaseReasoning):
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return answer
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@classmethod
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def get_pipeline(cls, settings, retrievers):
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def get_pipeline(cls, settings, states, retrievers):
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"""Get the reasoning pipeline
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Args:
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pipeline.answering_pipeline.qa_template = settings[
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f"reasoning.options.{_id}.qa_prompt"
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]
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pipeline.use_rewrite = states.get("app", {}).get("regen", False)
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pipeline.rewrite_pipeline.llm = llms.get_lowest_cost()
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pipeline.rewrite_pipeline.lang = {"en": "English", "ja": "Japanese"}.get(
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settings["reasoning.lang"], "English"
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)
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return pipeline
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@classmethod
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Reference in New Issue
Block a user