dummy_state route

{config → app/helpers}/exercise_standardizer.py

@@ -1,9 +1,9 @@
-# exercise_standardizer.py
-import gradio as gr
+# app/helpers/exercise_standardizer.py
 from langchain_core.prompts import ChatPromptTemplate
 from typing import Any
+from app.helpers.update_standardized_markdown import dummy_state
 from config.format_mappings import FORMAT_MAPPINGS
-from utils.state_manager import standardized_format_state
+
 
 
 async def standardize_exercise(user_query: str, exercise_format: str, template: ChatPromptTemplate, llm: Any) -> str:
@@ -27,7 +27,7 @@ async def standardize_exercise(user_query: str, exercise_format: str, template:
     response = await llm.ainvoke(std_messages)
     standardized_exercise = getattr(response, "content", response)
 
-    standardized_format_state.value = standardized_exercise
+    dummy_state.update(value=standardized_exercise)
 
     return standardized_exercise
 

app/helpers/update_standardized_markdown.py

@@ -0,0 +1,8 @@
+# app/helpers/update_standardized_markdown
+import gradio as gr
+
+dummy_state = gr.Textbox(visible=False, label="Most recent reformatting", show_label=False)
+
+async def update_standardized_markdown(text_from_dummy):
+    new_markdown = f"#### Most Recent Standardized Format\n{text_from_dummy}"
+    return new_markdown

chains/diagnoser/diagnoser_chain.py

@@ -3,7 +3,6 @@ import asyncio
 from pydantic import BaseModel
 from typing import Any, List
 from langchain_core.prompts.chat import ChatPromptTemplate
-from config.exercise_standardizer import standardize_exercise
 
 
 class DiagnoserChain(BaseModel):

chains/diagnoser/runner.py

@@ -2,7 +2,7 @@
 import asyncio
 
 from config.chain_configs import chain_configs
-from config.exercise_standardizer import standardize_exercise
+from app.helpers.exercise_standardizer import standardize_exercise
 from config.llm_config import llms
 
 

chains/distractors/distractors_chain.py

@@ -3,7 +3,6 @@ import asyncio
 from pydantic import BaseModel
 from typing import Any
 from langchain_core.prompts.chat import ChatPromptTemplate
-from config.exercise_standardizer import standardize_exercise
 
 
 class DistractorsChain(BaseModel):

chains/distractors/runner.py

@@ -2,7 +2,7 @@
 import asyncio
 
 from config.chain_configs import chain_configs
-from config.exercise_standardizer import standardize_exercise
+from app.helpers.exercise_standardizer import standardize_exercise
 from config.llm_config import llms
 
 async def run_distractors(

main.py

@@ -1,59 +1,18 @@
 # main.py
 import gradio as gr
 import logging
-from utils.state_manager import standardized_format_state
+
+from app.helpers import update_standardized_markdown
+from app.helpers.update_standardized_markdown import dummy_state
 from app.ui.diagnoser_tab import build_diagnoser_tab
 from app.ui.distractors_tab import build_distractors_tab
 from chains.diagnoser.runner import run_diagnoser
 from chains.distractors.runner import run_distractors
 from utils.auth import login as auth_login
-from config.chain_configs import chain_configs
-from config.llm_config import llms
 
 logger = logging.getLogger(__name__)
 
 
-# A generic async runner for simple chains (currently not used)
-async def run_chain(chain_name: str, input_variables: dict, selected_model: str):
-    try:
-        chain_config = chain_configs.get(chain_name)
-        if not chain_config:
-            raise KeyError(f"Chain '{chain_name}' not found.")
-
-        # Override the LLM based on user selection.
-        chosen_llm = llms.get(selected_model)
-        if not chosen_llm:
-            raise KeyError(f"LLM '{selected_model}' is not configured.")
-
-        # Instantiate the chain with the chosen LLM.
-        if chain_name == "diagnoser":
-            chain_instance = chain_config["class"](
-                template_standardize=chain_config["template_standardize"],
-                template_diagnose=chain_config["template_diagnose"],
-                llm=chosen_llm,
-            )
-        elif chain_name == "distractors":
-            chain_instance = chain_config["class"](
-                template=chain_config["template"],
-                llm=chosen_llm,
-            )
-        else:
-            raise KeyError(f"Chain '{chain_name}' is not implemented.")
-
-        result = await chain_instance.run(input_variables["user_query"])
-        content = result.content if hasattr(result, "content") else result
-        # Replace literal "\n" (backslash-n) with actual newline characters.
-        formatted_content = content.replace("\\n", "\n")
-
-        logger.info(f"Chain '{chain_name}' executed successfully.")
-
-        return formatted_content
-
-
-    except Exception as e:
-        logger.error(f"Error in run_chain for '{chain_name}': {e}")
-        return f"Error: {e}"
-
 
 # -------------------------------
 # Build the Gradio Interface
@@ -69,6 +28,7 @@ with gr.Blocks() as interface:
     # --- Main App (initially hidden) ---
     with gr.Column(visible=False, elem_id="main_app") as app_container:
         # --- Standardized Exercise/Studytext Display (Initially Invisible Because it's empty) ---
+
         standardized_format_display = gr.Markdown("", visible=True)
 
         gr.Markdown("## Pick the tab for your task of choice")
@@ -126,9 +86,9 @@ with gr.Blocks() as interface:
         outputs=[login_container, app_container, login_error]
     )
 
-    standardized_format_state.change(
-        fn=lambda text: gr.update(value="#### Here's the most recent standardized format" + f"\n{standardized_format_state}"),  # ✅ Only update value, no need to toggle visibility
-        inputs=[standardized_format_state],
+    dummy_state.change(
+        fn=update_standardized_markdown,
+        inputs=[dummy_state],
         outputs=[standardized_format_display]
     )
 

utils/state_manager.py

@@ -1,5 +0,0 @@
-# utils.state_manager.py
-import gradio as gr
-
-# Global state variable for standardized formats
-standardized_format_state = gr.State("")