Include Spinners for all processors but QNA

src/main/askai/core/processors/chat.py

@@ -12,20 +12,26 @@
 
    Copyright 2024, HSPyLib team
 """
+from typing import Any, Optional
+
+from clitt.core.term.cursor import cursor
+from hspylib.core.config.path_object import PathObject
+from hspylib.core.metaclass.singleton import Singleton
+from hspylib.core.tools.dict_tools import get_or_default_by_key
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder, PromptTemplate
+from langchain_core.runnables import RunnableWithMessageHistory
+from rich.live import Live
+from rich.spinner import Spinner
+
 from askai.core.askai_events import events
 from askai.core.askai_messages import msg
 from askai.core.askai_prompt import prompt
 from askai.core.engine.openai.temperature import Temperature
 from askai.core.model.ai_reply import AIReply
 from askai.core.support.langchain_support import lc_llm
 from askai.core.support.shared_instances import shared
+from askai.core.support.text_formatter import text_formatter as tf
 from askai.exception.exceptions import TerminatingQuery
-from hspylib.core.config.path_object import PathObject
-from hspylib.core.metaclass.singleton import Singleton
-from hspylib.core.tools.dict_tools import get_or_default_by_key
-from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder, PromptTemplate
-from langchain_core.runnables import RunnableWithMessageHistory
-from typing import Any, Optional
 
 
 class ChatProcessor(metaclass=Singleton):
@@ -59,25 +65,32 @@ def process(self, question: str, **kwargs) -> Optional[str]:
             events.mode_changed.emit(mode="DEFAULT")
             return None
 
-        response = None
-        prompt_file: str = get_or_default_by_key(kwargs, "prompt_file", None)
-        history_ctx: Any | None = get_or_default_by_key(kwargs, "history_ctx", "HISTORY")
-        ctx: str = get_or_default_by_key(kwargs, "context", "")
-        inputs: list[str] = get_or_default_by_key(kwargs, "inputs", [])
-        args: dict[str, Any] = get_or_default_by_key(kwargs, "args", {})
-        inputs = inputs or ["user", "idiom", "context", "question"]
-        args = args or {"user": prompt.user.title(), "idiom": shared.idiom, "context": ctx, "question": question}
-        prompt_file: PathObject = PathObject.of(prompt_file or prompt.append_path(f"taius/taius-jarvis"))
-        prompt_str: str = prompt.read_prompt(prompt_file.filename, prompt_file.abs_dir)
-
-        template = self.template(prompt_str, *inputs, **args)
-        runnable = template | lc_llm.create_chat_model(Temperature.COLDEST.temp)
-        runnable = RunnableWithMessageHistory(
-            runnable, shared.context.flat, input_messages_key="input", history_messages_key="chat_history"
-        )
-
-        if output := runnable.invoke({"input": question}, config={"configurable": {"session_id": history_ctx or ""}}):
-            response = output.content
+        with Live(
+            Spinner("dots", f"[green]{msg.wait()}[/green]", style="green"), console=tf.console
+        ):
+            response = None
+            prompt_file: str = get_or_default_by_key(kwargs, "prompt_file", None)
+            history_ctx: Any | None = get_or_default_by_key(kwargs, "history_ctx", "HISTORY")
+            ctx: str = get_or_default_by_key(kwargs, "context", "")
+            inputs: list[str] = get_or_default_by_key(kwargs, "inputs", [])
+            args: dict[str, Any] = get_or_default_by_key(kwargs, "args", {})
+            inputs = inputs or ["user", "idiom", "context", "question"]
+            args = args or {"user": prompt.user.title(), "idiom": shared.idiom, "context": ctx, "question": question}
+            prompt_file: PathObject = PathObject.of(prompt_file or prompt.append_path(f"taius/taius-jarvis"))
+            prompt_str: str = prompt.read_prompt(prompt_file.filename, prompt_file.abs_dir)
+
+            template = self.template(prompt_str, *inputs, **args)
+            runnable = template | lc_llm.create_chat_model(Temperature.COLDEST.temp)
+            runnable = RunnableWithMessageHistory(
+                runnable, shared.context.flat, input_messages_key="input", history_messages_key="chat_history"
+            )
+
+            if output := runnable.invoke(
+                input={"input": question},
+                config={"configurable": {"session_id": history_ctx or ""}}):
+                response = output.content
+
+        cursor.erase_line()
 
         return response
 

src/main/askai/core/processors/qstring.py

@@ -12,11 +12,17 @@
 
    Copyright (c) 2024, HomeSetup
 """
+from clitt.core.term.cursor import cursor
+from rich.live import Live
+from rich.spinner import Spinner
+
+from askai.core.askai_messages import msg
 from askai.core.askai_prompt import prompt
 from askai.core.component.cache_service import cache
 from askai.core.engine.openai.temperature import Temperature
 from askai.core.support.langchain_support import lc_llm
 from askai.core.support.utilities import find_file
+from askai.core.support.text_formatter import text_formatter as tf
 from askai.exception.exceptions import TerminatingQuery
 from hspylib.core.config.path_object import PathObject
 from hspylib.core.metaclass.singleton import Singleton
@@ -45,20 +51,25 @@ def process(self, question: str, **kwargs) -> Optional[str]:
         if question.casefold() in ["exit", "leave", "quit", "q"]:
             return None
 
-        output = None
-        query_prompt: str | None = find_file(kwargs["query_prompt"]) if "query_prompt" in kwargs else None
-        context: str | None = kwargs["context"] if "context" in kwargs else None
-        temperature: int = kwargs["temperature"] if "temperature" in kwargs else None
-
-        dir_name, file_name = PathObject.split(query_prompt or self.DEFAULT_PROMPT)
-        template = PromptTemplate(
-            input_variables=["context", "question"], template=prompt.read_prompt(file_name, dir_name)
-        )
-        final_prompt: str = template.format(context=context or self.DEFAULT_CONTEXT, question=question)
-        llm = lc_llm.create_chat_model(temperature or self.DEFAULT_TEMPERATURE)
-
-        if (response := llm.invoke(final_prompt)) and (output := response.content):
-            cache.save_input_history()
+        with Live(
+            Spinner("dots", f"[green]{msg.wait()}[/green]", style="green"), console=tf.console
+        ):
+            output = None
+            query_prompt: str | None = find_file(kwargs["query_prompt"]) if "query_prompt" in kwargs else None
+            context: str | None = kwargs["context"] if "context" in kwargs else None
+            temperature: int = kwargs["temperature"] if "temperature" in kwargs else None
+
+            dir_name, file_name = PathObject.split(query_prompt or self.DEFAULT_PROMPT)
+            template = PromptTemplate(
+                input_variables=["context", "question"], template=prompt.read_prompt(file_name, dir_name)
+            )
+            final_prompt: str = template.format(context=context or self.DEFAULT_CONTEXT, question=question)
+            llm = lc_llm.create_chat_model(temperature or self.DEFAULT_TEMPERATURE)
+
+            if (response := llm.invoke(final_prompt)) and (output := response.content):
+                cache.save_input_history()
+
+        cursor.erase_line()
 
         return output
 

src/main/askai/core/processors/rag.py

@@ -12,6 +12,10 @@
 
    Copyright (c) 2024, HomeSetup
 """
+from clitt.core.term.cursor import cursor
+from rich.live import Live
+from rich.spinner import Spinner
+
 from askai.core.askai_configs import configs
 from askai.core.askai_events import events
 from askai.core.askai_messages import msg
@@ -22,6 +26,7 @@
 from askai.core.model.ai_reply import AIReply
 from askai.core.support.langchain_support import lc_llm
 from askai.exception.exceptions import DocumentsNotFound, TerminatingQuery
+from askai.core.support.text_formatter import text_formatter as tf
 from functools import lru_cache
 from hspylib.core.config.path_object import PathObject
 from hspylib.core.metaclass.classpath import AnyPath
@@ -88,8 +93,13 @@ def process(self, question: str, **_) -> Optional[str]:
         # FIXME Include kwargs to specify rag dir and glob
         self.generate()
 
-        if not (output := self._rag_chain.invoke(question)):
-            output = msg.invalid_response(output)
+        with Live(
+            Spinner("dots", f"[green]{msg.wait()}[/green]", style="green"), console=tf.console
+        ):
+            if not (output := self._rag_chain.invoke(question)):
+                output = msg.invalid_response(output)
+
+        cursor.erase_line()
 
         return output
 

src/main/askai/core/processors/splitter/splitter_executor.py

@@ -18,7 +18,6 @@
 from askai.core.enums.acc_color import AccColor
 from askai.core.processors.splitter.splitter_pipeline import SplitterPipeline
 from askai.core.processors.splitter.splitter_states import States
-from askai.core.support.text_formatter import text_formatter
 from askai.core.support.text_formatter import text_formatter as tf
 from askai.exception.exceptions import InaccurateResponse
 from clitt.core.term.cursor import cursor
@@ -52,7 +51,7 @@ def display(self, text: str, force: bool = False) -> None:
         :param force: Force displaying the message regardless of the debug flag.
         """
         if force or is_debugging():
-            text_formatter.console.print(Text.from_markup(text))
+            tf.console.print(Text.from_markup(text))
 
     def interrupt(self, ev: Event) -> None:
         """Interrupt the active execution pipeline.