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README.md

@@ -5,7 +5,7 @@ app_file: app.py
 requirements: requirements.txt
 python_version: 3.12
 sdk: gradio
-sdk_version: 6.0.2
+sdk_version: 6.1.0
 ---
 
 # AnkiGen - Anki Card Generator
@@ -77,7 +77,7 @@ uv run python -m ankigen_core.cli -p "Python Lists" --no-confirm
 - `-p, --prompt`: Subject/topic (required)
 - `--topics`: Number of topics (auto-detected if omitted)
 - `--cards-per-topic`: Cards per topic (auto-detected if omitted)
-- `--model`: Model choice (`gpt-4.1` or `gpt-4.1-nano`)
+- `--model`: Model choice (`gpt-5.2-auto`, `gpt-5.2-instant`, or `gpt-5.2-thinking`)
 - `-o, --output`: Output file path
 - `--format`: Export format (`apkg` or `csv`)
 - `--no-confirm`: Skip confirmation prompt
@@ -134,4 +134,4 @@ BSD 2-Clause License
 
 - Gradio library for the web interface
 - OpenAI for GPT models
-- Card design principles from ["An Opinionated Guide to Using Anki Correctly"](https://www.lesswrong.com/posts/7Q7DPSk4iGFJd8DRk/an-opinionated-guide-to-using-anki-correctly)
+- Card design principles from ["An Opinionated Guide to Using Anki Correctly"](https://www.lesswrong.com/posts/7Q7DPSk4iGFJd8DRk/an-opinionated-guide-to-using-anki-correctly)

ankigen_core/agents/base.py

@@ -36,7 +36,8 @@ class AgentConfig:
 
     name: str
     instructions: str
-    model: str = "gpt-5.1"
+    model: str = "gpt-5.2"
+    reasoning_effort: Optional[str] = None
     temperature: float = 0.7
     max_tokens: Optional[int] = None
     timeout: float = 30.0
@@ -67,17 +68,21 @@ class BaseAgentWrapper:
 
             set_default_openai_client(self.openai_client, use_for_tracing=False)
 
-            # Create model settings with temperature and GPT-5.1 reasoning support
+            # Create model settings with temperature and optional reasoning effort
             model_settings_kwargs = {"temperature": self.config.temperature}
+            effort = self.config.reasoning_effort
+            if effort in ("auto", "", None):
+                effort = None
 
-            # GPT-5.1 (not chat-latest) supports reasoning_effort
+            # GPT-5.x (not chat-latest) supports reasoning_effort
             if (
-                self.config.model.startswith("gpt-5")
+                effort
+                and self.config.model.startswith("gpt-5")
                 and "chat-latest" not in self.config.model
             ):
                 from openai.types.shared import Reasoning
 
-                model_settings_kwargs["reasoning"] = Reasoning(effort="none")
+                model_settings_kwargs["reasoning"] = Reasoning(effort=effort)
 
             model_settings = ModelSettings(**model_settings_kwargs)
 

ankigen_core/agents/config.py

@@ -91,7 +91,7 @@ class AgentConfigManager:
 
             # Default models for each agent type
             default_models = {
-                "subject_expert_model": "gpt-5.1",
+                "subject_expert_model": "gpt-5.2",
             }
 
             # Simple mapping: agent_name -> agent_name_model
@@ -111,7 +111,8 @@ class AgentConfigManager:
                 config = AgentConfig(
                     name=agent_data.get("name", agent_name),
                     instructions=agent_data.get("instructions", ""),
-                    model=agent_data.get("model", "gpt-5.1"),
+                    model=agent_data.get("model", "gpt-5.2"),
+                    reasoning_effort=agent_data.get("reasoning_effort"),
                     temperature=agent_data.get("temperature", 0.7),
                     max_tokens=agent_data.get("max_tokens"),
                     timeout=agent_data.get("timeout", 30.0),
@@ -176,7 +177,8 @@ class AgentConfigManager:
                 config = AgentConfig(
                     name=agent_name,
                     instructions=agent_data.get("instructions", ""),
-                    model=agent_data.get("model", "gpt-5.1"),
+                    model=agent_data.get("model", "gpt-5.2"),
+                    reasoning_effort=agent_data.get("reasoning_effort"),
                     temperature=agent_data.get("temperature", 0.7),
                     max_tokens=agent_data.get("max_tokens"),
                     timeout=agent_data.get("timeout", 30.0),

ankigen_core/agents/integration.py

@@ -21,7 +21,12 @@ class AgentOrchestrator:
 
         self.subject_expert = None
 
-    async def initialize(self, api_key: str, model_overrides: Dict[str, str] = None):
+    async def initialize(
+        self,
+        api_key: str,
+        model_overrides: Dict[str, str] = None,
+        reasoning_overrides: Dict[str, Optional[str]] = None,
+    ):
         """Initialize the agent system"""
         try:
             # Initialize OpenAI client
@@ -29,6 +34,7 @@ class AgentOrchestrator:
             self.openai_client = self.client_manager.get_client()
 
             # Set up model overrides if provided
+            config_manager = None
             if model_overrides:
                 from ankigen_core.agents.config import get_config_manager
 
@@ -36,6 +42,17 @@ class AgentOrchestrator:
                 config_manager.update_models(model_overrides)
                 logger.info(f"Applied model overrides: {model_overrides}")
 
+            if reasoning_overrides:
+                if config_manager is None:
+                    from ankigen_core.agents.config import get_config_manager
+
+                    config_manager = get_config_manager()
+                for agent_name, effort in reasoning_overrides.items():
+                    config_manager.update_agent_config(
+                        agent_name, reasoning_effort=effort
+                    )
+                logger.info(f"Applied reasoning overrides: {reasoning_overrides}")
+
             logger.info("Agent system initialized successfully (simplified pipeline)")
 
         except Exception as e:

ankigen_core/agents/schemas.py

@@ -173,7 +173,7 @@ class AutoConfigSchema(BaseModel):
     )
     model_choice: str = Field(
         ...,
-        description="Recommended model: 'gpt-5.1' for all tasks (uses reasoning_effort=none for speed)",
+        description="Recommended model: 'gpt-5.2-auto', 'gpt-5.2-instant', or 'gpt-5.2-thinking'",
     )
 
     # Analysis metadata

ankigen_core/agents/token_tracker.py

@@ -48,7 +48,7 @@ class TokenTracker:
 
         Args:
             messages: List of message dicts (each with 'role', 'content', optional 'name')
-            model: OpenAI model identifier (e.g., 'gpt-4.1', 'gpt-4o')
+            model: OpenAI model identifier (e.g., 'gpt-5.2', 'gpt-4o')
 
         Returns:
             Total tokens required to send these messages to the model

ankigen_core/auto_config.py

@@ -53,7 +53,8 @@ Consider:
 4. Determine content type: concepts (theory/understanding), syntax (code/commands), api (library usage), practical (hands-on skills)
 5. TOPIC DECOMPOSITION: Break down the subject into distinct subtopics that together provide comprehensive coverage
 6. Recommend cloze cards for syntax/code, basic cards for concepts
-7. Choose model based on complexity: gpt-4.1 for complex topics, gpt-4.1-nano for basic/simple
+7. Choose model based on complexity: gpt-5.2-thinking for complex topics, gpt-5.2-instant for basic/simple, gpt-5.2-auto for mixed scope
+   - Valid model_choice values: "gpt-5.2-auto", "gpt-5.2-instant", "gpt-5.2-thinking"
 
 TOPIC DECOMPOSITION (topics_list):
 You MUST provide a topics_list - a list of distinct subtopics that together cover the subject comprehensively.
@@ -96,7 +97,7 @@ Provide a brief rationale for your choices."""
         try:
             config = await structured_agent_call(
                 openai_client=openai_client,
-                model="gpt-5.1",
+                model="gpt-5.2",
                 instructions=system_prompt,
                 user_input=user_prompt,
                 output_type=AutoConfigSchema,
@@ -128,7 +129,7 @@ Provide a brief rationale for your choices."""
                 cards_per_topic=8,
                 learning_preferences="Focus on fundamental concepts and core principles with practical examples",
                 generate_cloze=False,
-                model_choice="gpt-5.1",
+                model_choice="gpt-5.2-auto",
                 subject_type="concepts",
                 scope="medium",
                 rationale="Using default settings due to analysis error",

ankigen_core/card_generator.py

@@ -30,19 +30,19 @@ logger.info("Agent system loaded successfully")
 # --- Constants --- (Moved from app.py)
 AVAILABLE_MODELS = [
     {
-        "value": "gpt-5.1",
-        "label": "GPT-5.1 (Best Quality)",
-        "description": "Latest model with adaptive reasoning, 400K context",
+        "value": "gpt-5.2-auto",
+        "label": "GPT-5.2 Auto",
+        "description": "Adaptive reasoning",
     },
     {
-        "value": "gpt-4.1",
-        "label": "GPT-4.1 (Legacy)",
-        "description": "Previous generation, large context window",
+        "value": "gpt-5.2-instant",
+        "label": "GPT-5.2 Instant",
+        "description": "Fast, minimal reasoning",
     },
     {
-        "value": "gpt-4.1-nano",
-        "label": "GPT-4.1 Nano (Legacy Fast)",
-        "description": "Previous generation, ultra-fast",
+        "value": "gpt-5.2-thinking",
+        "label": "GPT-5.2 Thinking",
+        "description": "Higher reasoning effort",
     },
 ]
 
@@ -60,6 +60,32 @@ GENERATION_MODES = [
 # Legacy functions removed - all card generation now handled by agent system
 
 
+def _parse_model_selection(model_selection: str) -> tuple[str, str | None]:
+    """Parse model selection into model name and reasoning effort."""
+    if not model_selection:
+        return "gpt-5.2", None
+
+    normalized = model_selection.strip().lower()
+    if normalized == "gpt-5.2-auto":
+        return "gpt-5.2", None
+    if normalized == "gpt-5.2-instant":
+        return "gpt-5.2", "none"
+    if normalized == "gpt-5.2-thinking":
+        return "gpt-5.2", "high"
+
+    if "gpt-5.2" in normalized:
+        if "instant" in normalized:
+            return "gpt-5.2", "none"
+        if "thinking" in normalized:
+            return "gpt-5.2", "high"
+        if "auto" in normalized:
+            return "gpt-5.2", None
+        return "gpt-5.2", None
+
+    # Fallback for direct model names
+    return model_selection, None
+
+
 def _map_generation_mode_to_subject(generation_mode: str, subject: str) -> str:
     """Map UI generation mode to agent subject."""
     if generation_mode == "subject":
@@ -145,8 +171,13 @@ async def orchestrate_card_generation(
         token_tracker = get_token_tracker()
         orchestrator = AgentOrchestrator(client_manager)
 
-        logger.info(f"Using {model_name} for SubjectExpertAgent")
-        await orchestrator.initialize(api_key_input, {"subject_expert": model_name})
+        model_name_resolved, reasoning_effort = _parse_model_selection(model_name)
+        logger.info(f"Using {model_name_resolved} for SubjectExpertAgent")
+        await orchestrator.initialize(
+            api_key_input,
+            {"subject_expert": model_name_resolved},
+            {"subject_expert": reasoning_effort},
+        )
 
         agent_subject = _map_generation_mode_to_subject(generation_mode, subject)
         context = _build_generation_context(generation_mode, source_text)

ankigen_core/cli.py

@@ -143,7 +143,7 @@ async def generate_cards_from_config(
             generation_mode="subject",
             source_text="",
             url_input="",
-            model_name=config.get("model_choice", "gpt-5.1"),
+            model_name=config.get("model_choice", "gpt-5.2-auto"),
             topic_number=config.get("topic_number", 3),
             cards_per_topic=config.get("cards_per_topic", 5),
             preference_prompt=config.get("preference_prompt", ""),
@@ -221,7 +221,7 @@ def export_cards(
 @click.option(
     "--model",
     type=click.Choice(
-        ["gpt-5.1", "gpt-4.1", "gpt-4.1-nano"],
+        ["gpt-5.2-auto", "gpt-5.2-instant", "gpt-5.2-thinking"],
         case_sensitive=False,
     ),
     help="Model to use for generation (auto-selected if not specified)",

ankigen_core/llm_interface.py

@@ -129,7 +129,7 @@ async def structured_agent_call(
 
     Args:
         openai_client: AsyncOpenAI client instance
-        model: Model name (e.g., "gpt-5.1", "gpt-5.1-chat-latest")
+        model: Model name (e.g., "gpt-5.2", "gpt-5.2-chat-latest")
         instructions: System instructions for the agent
         user_input: User prompt/input
         output_type: Pydantic model class for structured output
@@ -155,10 +155,10 @@ async def structured_agent_call(
     # 2. Set up the OpenAI client for agents SDK
     set_default_openai_client(openai_client, use_for_tracing=False)
 
-    # 3. Build model settings with GPT-5.1 reasoning support
+    # 3. Build model settings with GPT-5.x reasoning support
     model_settings_kwargs: dict = {"temperature": temperature}
 
-    # GPT-5.1 (not chat-latest) supports reasoning_effort
+    # GPT-5.x (not chat-latest) supports reasoning_effort
     if model.startswith("gpt-5") and "chat-latest" not in model:
         from openai.types.shared import Reasoning
 

app.py

@@ -65,8 +65,9 @@ except (AttributeError, ImportError):
 # CSS for the interface (moved to module level for Gradio 6 compatibility)
 custom_css = """
     #footer {display:none !important}
+    .gradio-container {max-width: 100% !important; padding: 0 24px;}
     .tall-dataframe {min-height: 500px !important}
-    .contain {max-width: 100% !important; margin: auto;}
+    .contain {width: 100% !important; max-width: 100% !important; margin: 0 auto; box-sizing: border-box;}
     .output-cards {border-radius: 8px; box-shadow: 0 4px 6px -1px rgba(0,0,0,0.1);}
     .hint-text {font-size: 0.9em; color: #666; margin-top: 4px;}
     .export-group > .gradio-group { margin-bottom: 0 !important; padding-bottom: 5px !important; }
@@ -158,170 +159,187 @@ def create_ankigen_interface(theme=None, css=None, js=None):
             gr.Markdown("# 📚 AnkiGen - Anki Card Generator")
             gr.Markdown("#### Generate Anki flashcards using AI.")
 
-            with gr.Accordion("Configuration Settings", open=True):
-                with gr.Row():
-                    with gr.Column(scale=1):
-                        generation_mode = gr.Radio(
-                            choices=[
-                                ("Single Subject", "subject"),
-                            ],
-                            value="subject",
-                            label="Generation Mode",
-                            info="Choose how you want to generate content",
-                            visible=False,  # Hidden since only one mode exists
-                        )
-                        with gr.Group() as subject_mode:
-                            subject = gr.Textbox(
-                                label="Subject",
-                                placeholder="e.g., 'Basic SQL Concepts'",
-                            )
+            with gr.Tabs(selected="setup") as main_tabs:
+                with gr.Tab("Setup", id="setup"):
+                    with gr.Accordion("Configuration Settings", open=True):
+                        with gr.Row():
+                            with gr.Column(scale=1):
+                                generation_mode = gr.Radio(
+                                    choices=[
+                                        ("Single Subject", "subject"),
+                                    ],
+                                    value="subject",
+                                    label="Generation Mode",
+                                    info="Choose how you want to generate content",
+                                    visible=False,  # Hidden since only one mode exists
+                                )
+                                with gr.Group() as subject_mode:
+                                    subject = gr.Textbox(
+                                        label="Subject",
+                                        placeholder="e.g., 'Basic SQL Concepts'",
+                                    )
+                                api_key_input = gr.Textbox(
+                                    label="OpenAI API Key",
+                                    type="password",
+                                    placeholder="Enter your OpenAI API key (sk-...)",
+                                    value=os.getenv("OPENAI_API_KEY", ""),
+                                    info="Your key is used solely for processing your requests.",
+                                    elem_id="api-key-textbox",
+                                )
+
+                                # Context7 Library Documentation
+                                library_accordion = gr.Accordion(
+                                    "Library Documentation (optional)", open=True
+                                )
+                                with library_accordion:
+                                    library_name_input = gr.Textbox(
+                                        label="Library Name",
+                                        placeholder="e.g., 'react', 'tensorflow', 'pandas'",
+                                        info="Fetch up-to-date documentation for this library",
+                                    )
+                                    library_topic_input = gr.Textbox(
+                                        label="Documentation Focus (optional)",
+                                        placeholder="e.g., 'hooks', 'data loading', 'transforms'",
+                                        info="Specific topic within the library to focus on",
+                                    )
+                            with gr.Column(scale=1):
+                                with gr.Accordion("Advanced Settings", open=True):
+                                    model_choices_ui = [
+                                        (m["label"], m["value"])
+                                        for m in AVAILABLE_MODELS
+                                    ]
+                                    default_model_value = next(
+                                        (
+                                            m["value"]
+                                            for m in AVAILABLE_MODELS
+                                            if m["value"] == "gpt-5.2-auto"
+                                        ),
+                                        AVAILABLE_MODELS[0]["value"],
+                                    )
+                                    model_choice = gr.Dropdown(
+                                        choices=model_choices_ui,
+                                        value=default_model_value,
+                                        label="Model Selection",
+                                        info="Select AI model for generation",
+                                        allow_custom_value=True,
+                                    )
+                                    topic_number = gr.Slider(
+                                        label="Number of Topics",
+                                        minimum=2,
+                                        maximum=20,
+                                        step=1,
+                                        value=2,
+                                    )
+                                    cards_per_topic = gr.Slider(
+                                        label="Cards per Topic",
+                                        minimum=2,
+                                        maximum=30,
+                                        step=1,
+                                        value=3,
+                                    )
+                                    total_cards_preview = gr.Markdown(
+                                        f"**Total cards:** {2 * 3}"
+                                    )
+                                    preference_prompt = gr.Textbox(
+                                        label="Learning Preferences",
+                                        placeholder="e.g., 'Beginner focus'",
+                                        lines=3,
+                                    )
+                                    generate_cloze_checkbox = gr.Checkbox(
+                                        label="Generate Cloze Cards",
+                                        value=True,
+                                    )
+
+                        with gr.Row():
                             auto_fill_btn = gr.Button(
                                 "Auto-fill",
                                 variant="secondary",
                             )
-                        api_key_input = gr.Textbox(
-                            label="OpenAI API Key",
-                            type="password",
-                            placeholder="Enter your OpenAI API key (sk-...)",
-                            value=os.getenv("OPENAI_API_KEY", ""),
-                            info="Your key is used solely for processing your requests.",
-                            elem_id="api-key-textbox",
+                            generate_button = gr.Button(
+                                "Generate Cards", variant="primary"
+                            )
+                        status_markdown = gr.Markdown("")
+                        log_output = gr.Textbox(
+                            label="Live Logs",
+                            lines=8,
+                            interactive=False,
                         )
+                        generation_active = gr.State(False)
+                        log_timer = gr.Timer(2)
 
-                        # Context7 Library Documentation
-                        library_accordion = gr.Accordion(
-                            "Library Documentation (optional)", open=False
-                        )
-                        with library_accordion:
-                            library_name_input = gr.Textbox(
-                                label="Library Name",
-                                placeholder="e.g., 'react', 'tensorflow', 'pandas'",
-                                info="Fetch up-to-date documentation for this library",
-                            )
-                            library_topic_input = gr.Textbox(
-                                label="Documentation Focus (optional)",
-                                placeholder="e.g., 'hooks', 'data loading', 'transforms'",
-                                info="Specific topic within the library to focus on",
-                            )
-                    with gr.Column(scale=1):
-                        with gr.Accordion("Advanced Settings", open=False):
-                            model_choices_ui = [
-                                (m["label"], m["value"]) for m in AVAILABLE_MODELS
-                            ]
-                            default_model_value = next(
-                                (
-                                    m["value"]
-                                    for m in AVAILABLE_MODELS
-                                    if "nano" in m["value"].lower()
-                                ),
-                                AVAILABLE_MODELS[0]["value"],
-                            )
-                            model_choice = gr.Dropdown(
-                                choices=model_choices_ui,
-                                value=default_model_value,
-                                label="Model Selection",
-                                info="Select AI model for generation",
-                                allow_custom_value=True,
-                            )
-                            topic_number = gr.Slider(
-                                label="Number of Topics",
-                                minimum=2,
-                                maximum=20,
-                                step=1,
-                                value=2,
-                            )
-                            cards_per_topic = gr.Slider(
-                                label="Cards per Topic",
-                                minimum=2,
-                                maximum=30,
-                                step=1,
-                                value=3,
-                            )
-                            preference_prompt = gr.Textbox(
-                                label="Learning Preferences",
-                                placeholder="e.g., 'Beginner focus'",
-                                lines=3,
-                            )
-                            generate_cloze_checkbox = gr.Checkbox(
-                                label="Generate Cloze Cards (Experimental)",
-                                value=False,
-                            )
+                with gr.Tab("Results", id="results"):
+                    with gr.Group() as cards_output:
+                        gr.Markdown("### Generated Cards")
+                        with gr.Accordion("Output Format", open=False):
                             gr.Markdown(
-                                "*Cards are generated by the subject expert agent with a quick self-review to catch obvious gaps.*"
+                                "Cards: Index, Topic, Type, Q, A, Explanation, Example, Prerequisites, Outcomes, Difficulty. Export: CSV, .apkg",
                             )
-
-            generate_button = gr.Button("Generate Cards", variant="primary")
-
-            with gr.Group() as cards_output:
-                gr.Markdown("### Generated Cards")
-                with gr.Accordion("Output Format", open=False):
-                    gr.Markdown(
-                        "Cards: Index, Topic, Type, Q, A, Explanation, Example, Prerequisites, Outcomes, Difficulty. Export: CSV, .apkg",
-                    )
-                    with gr.Accordion("Example Card Format", open=False):
-                        gr.Code(
-                            label="Example Card",
-                            value='{"front": ..., "back": ..., "metadata": ...}',
-                            language="json",
+                            with gr.Accordion("Example Card Format", open=False):
+                                gr.Code(
+                                    label="Example Card",
+                                    value='{"front": ..., "back": ..., "metadata": ...}',
+                                    language="json",
+                                )
+                        output = gr.DataFrame(
+                            value=example_data,
+                            headers=[
+                                "Index",
+                                "Topic",
+                                "Card_Type",
+                                "Question",
+                                "Answer",
+                                "Explanation",
+                                "Example",
+                                "Prerequisites",
+                                "Learning_Outcomes",
+                                "Difficulty",
+                            ],
+                            datatype=[
+                                "number",
+                                "str",
+                                "str",
+                                "str",
+                                "str",
+                                "str",
+                                "str",
+                                "str",
+                                "str",
+                                "str",
+                            ],
+                            interactive=True,
+                            elem_classes="tall-dataframe",
+                            wrap=True,
+                            column_widths=[
+                                50,
+                                100,
+                                80,
+                                200,
+                                200,
+                                250,
+                                200,
+                                150,
+                                150,
+                                100,
+                            ],
+                        )
+                        total_cards_html = gr.HTML(
+                            value="<div><b>Total Cards Generated:</b> <span id='total-cards-count'>0</span></div>",
+                            visible=False,
                         )
-                output = gr.DataFrame(
-                    value=example_data,
-                    headers=[
-                        "Index",
-                        "Topic",
-                        "Card_Type",
-                        "Question",
-                        "Answer",
-                        "Explanation",
-                        "Example",
-                        "Prerequisites",
-                        "Learning_Outcomes",
-                        "Difficulty",
-                    ],
-                    datatype=[
-                        "number",
-                        "str",
-                        "str",
-                        "str",
-                        "str",
-                        "str",
-                        "str",
-                        "str",
-                        "str",
-                        "str",
-                    ],
-                    interactive=True,
-                    elem_classes="tall-dataframe",
-                    wrap=True,
-                    column_widths=[
-                        50,
-                        100,
-                        80,
-                        200,
-                        200,
-                        250,
-                        200,
-                        150,
-                        150,
-                        100,
-                    ],
-                )
-                total_cards_html = gr.HTML(
-                    value="<div><b>Total Cards Generated:</b> <span id='total-cards-count'>0</span></div>",
-                    visible=False,
-                )
 
-                # Token usage display
-                token_usage_html = gr.HTML(
-                    value="<div style='margin-top: 8px;'><b>Token Usage:</b> <span id='token-usage-display'>No usage data</span></div>",
-                    visible=True,
-                )
+                        # Token usage display
+                        token_usage_html = gr.HTML(
+                            value="<div style='margin-top: 8px;'><b>Token Usage:</b> <span id='token-usage-display'>No usage data</span></div>",
+                            visible=True,
+                        )
 
-                # Export buttons
-                with gr.Row(elem_classes="export-group"):
-                    export_csv_button = gr.Button("Export to CSV")
-                    export_apkg_button = gr.Button("Export to .apkg")
-                download_file_output = gr.File(label="Download Deck", visible=False)
+                        # Export buttons
+                        with gr.Row(elem_classes="export-group"):
+                            export_csv_button = gr.Button("Export to CSV")
+                            export_apkg_button = gr.Button("Export to .apkg")
+                        download_file_output = gr.File(
+                            label="Download Deck", visible=False
+                        )
 
             # --- Event Handlers --- (Updated to use functions from ankigen_core)
             generation_mode.change(
@@ -339,6 +357,26 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                 ],
             )
 
+            def update_total_cards_preview(topics_value: int, cards_value: int) -> str:
+                """Update the total cards preview based on current sliders."""
+                try:
+                    topics = int(topics_value)
+                    cards = int(cards_value)
+                except (TypeError, ValueError):
+                    return "**Total cards:** —"
+                return f"**Total cards:** {topics * cards}"
+
+            topic_number.change(
+                fn=update_total_cards_preview,
+                inputs=[topic_number, cards_per_topic],
+                outputs=[total_cards_preview],
+            )
+            cards_per_topic.change(
+                fn=update_total_cards_preview,
+                inputs=[topic_number, cards_per_topic],
+                outputs=[total_cards_preview],
+            )
+
             # Define an async wrapper for the orchestrate_card_generation
             async def handle_generate_click(
                 api_key_input_val,
@@ -353,7 +391,7 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                 library_topic_val,
                 progress=gr.Progress(track_tqdm=True),
             ):
-                return await orchestrate_card_generation(
+                output_df, total_html, token_html = await orchestrate_card_generation(
                     client_manager,
                     response_cache,
                     api_key_input_val,
@@ -369,8 +407,47 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                     library_name=library_name_val if library_name_val else None,
                     library_topic=library_topic_val if library_topic_val else None,
                 )
+                return output_df, total_html, token_html, gr.Tabs(selected="results")
+
+            def refresh_logs(active: bool):
+                if not active:
+                    return gr.update()
+                return get_recent_logs()
+
+            log_timer.tick(
+                fn=refresh_logs,
+                inputs=[generation_active],
+                outputs=[log_output],
+            )
+
+            def start_generation_ui():
+                return (
+                    gr.update(
+                        value="**Generating cards...** This can take a bit.",
+                        visible=True,
+                    ),
+                    gr.update(interactive=False),
+                    True,
+                    get_recent_logs(),
+                )
+
+            def finish_generation_ui():
+                return (
+                    gr.update(value="**Ready.**", visible=True),
+                    gr.update(interactive=True),
+                    False,
+                )
 
             generate_button.click(
+                fn=start_generation_ui,
+                inputs=[],
+                outputs=[
+                    status_markdown,
+                    generate_button,
+                    generation_active,
+                    log_output,
+                ],
+            ).then(
                 fn=handle_generate_click,
                 inputs=[
                     api_key_input,
@@ -384,8 +461,12 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                     library_name_input,
                     library_topic_input,
                 ],
-                outputs=[output, total_cards_html, token_usage_html],
+                outputs=[output, total_cards_html, token_usage_html, main_tabs],
                 show_progress="full",
+            ).then(
+                fn=finish_generation_ui,
+                inputs=[],
+                outputs=[status_markdown, generate_button, generation_active],
             )
 
             # Define handler for CSV export (similar to APKG)
@@ -514,11 +595,11 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                 """Handle auto-fill button click to populate all settings"""
                 if not subject_text or not subject_text.strip():
                     gr.Warning("Please enter a subject first")
-                    return [gr.update()] * 8  # Return no updates for all outputs
+                    return [gr.update()] * 9  # Return no updates for all outputs
 
                 if not api_key:
                     gr.Warning("OpenAI API key is required for auto-configuration")
-                    return [gr.update()] * 8
+                    return [gr.update()] * 9
 
                 try:
                     progress(0, desc="Analyzing subject...")
@@ -535,7 +616,13 @@ def create_ankigen_interface(theme=None, css=None, js=None):
 
                     if not config:
                         gr.Warning("Could not generate configuration")
-                        return [gr.update()] * 8
+                        return [gr.update()] * 9
+
+                    topics_value = config.get("topic_number", 3)
+                    cards_value = config.get("cards_per_topic", 5)
+                    total_cards_text = (
+                        f"**Total cards:** {int(topics_value) * int(cards_value)}"
+                    )
 
                     # Return updates for all relevant UI components
                     return (
@@ -545,10 +632,9 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                         gr.update(
                             value=config.get("library_topic", "")
                         ),  # library_topic_input
-                        gr.update(value=config.get("topic_number", 3)),  # topic_number
-                        gr.update(
-                            value=config.get("cards_per_topic", 5)
-                        ),  # cards_per_topic
+                        gr.update(value=topics_value),  # topic_number
+                        gr.update(value=cards_value),  # cards_per_topic
+                        gr.update(value=total_cards_text),  # total_cards_preview
                         gr.update(
                             value=config.get("preference_prompt", "")
                         ),  # preference_prompt
@@ -556,7 +642,7 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                             value=config.get("generate_cloze_checkbox", False)
                         ),  # generate_cloze_checkbox
                         gr.update(
-                            value=config.get("model_choice", "gpt-4.1-nano")
+                            value=config.get("model_choice", "gpt-5.2-auto")
                         ),  # model_choice
                         gr.update(
                             open=True
@@ -566,7 +652,7 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                 except Exception as e:
                     logger.error(f"Auto-configuration failed: {e}", exc_info=True)
                     gr.Error(f"Auto-configuration failed: {str(e)}")
-                    return [gr.update()] * 8
+                    return [gr.update()] * 9
 
             auto_fill_btn.click(
                 fn=handle_auto_fill_click,
@@ -576,6 +662,7 @@ def create_ankigen_interface(theme=None, css=None, js=None):
                     library_topic_input,
                     topic_number,
                     cards_per_topic,
+                    total_cards_preview,
                     preference_prompt,
                     generate_cloze_checkbox,
                     model_choice,

requirements.txt

@@ -2,11 +2,11 @@
 #    uv pip compile pyproject.toml -o requirements.txt
 aiofiles==24.1.0
     # via gradio
-annotated-doc==0.0.3
+annotated-doc==0.0.4
     # via fastapi
 annotated-types==0.7.0
     # via pydantic
-anyio==4.9.0
+anyio==4.12.0
     # via
     #   gradio
     #   httpx
@@ -14,14 +14,14 @@ anyio==4.9.0
     #   openai
     #   sse-starlette
     #   starlette
-attrs==25.3.0
+attrs==25.4.0
     # via
     #   cyclopts
     #   jsonschema
     #   referencing
-authlib==1.6.5
+authlib==1.6.6
     # via fastmcp
-beartype==0.22.5
+beartype==0.22.9
     # via
     #   py-key-value-aio
     #   py-key-value-shared
@@ -33,31 +33,32 @@ brotli==1.2.0
     #   gradio
 cached-property==2.0.1
     # via genanki
-cachetools==6.2.1
+cachetools==6.2.4
     # via py-key-value-aio
-certifi==2025.6.15
+certifi==2025.11.12
     # via
     #   httpcore
     #   httpx
     #   requests
 cffi==2.0.0
     # via cryptography
-charset-normalizer==3.4.2
+charset-normalizer==3.4.4
     # via requests
 chevron==0.14.0
     # via genanki
-click==8.2.1
+click==8.3.1
     # via
     #   typer
+    #   typer-slim
     #   uvicorn
 colorama==0.4.6
     # via griffe
-cryptography==46.0.1
+cryptography==46.0.3
     # via
     #   authlib
     #   pyjwt
     #   secretstorage
-cyclopts==3.24.0
+cyclopts==4.4.0
     # via fastmcp
 diskcache==5.6.3
     # via py-key-value-aio
@@ -67,33 +68,33 @@ dnspython==2.8.0
     # via email-validator
 docstring-parser==0.17.0
     # via cyclopts
-docutils==0.22.2
+docutils==0.22.4
     # via rich-rst
 email-validator==2.3.0
     # via pydantic
-exceptiongroup==1.3.0
+exceptiongroup==1.3.1
     # via fastmcp
-fastapi==0.120.4
+fastapi==0.125.0
     # via gradio
 fastmcp==2.13.0
     # via ankigen (pyproject.toml)
-ffmpy==0.6.0
+ffmpy==1.0.0
     # via gradio
-filelock==3.18.0
+filelock==3.20.1
     # via huggingface-hub
-frozendict==2.4.6
+frozendict==2.4.7
     # via genanki
-fsspec==2025.5.1
+fsspec==2025.12.0
     # via
     #   gradio-client
     #   huggingface-hub
 genanki==0.13.1
     # via ankigen (pyproject.toml)
-gradio==6.0.2
+gradio==6.1.0
     # via ankigen (pyproject.toml)
 gradio-client==2.0.1
     # via gradio
-griffe==1.7.3
+griffe==1.15.0
     # via openai-agents
 groovy==0.1.2
     # via gradio
@@ -101,7 +102,7 @@ h11==0.16.0
     # via
     #   httpcore
     #   uvicorn
-hf-xet==1.1.5
+hf-xet==1.2.0
     # via huggingface-hub
 httpcore==1.0.9
     # via httpx
@@ -110,16 +111,17 @@ httpx==0.28.1
     #   fastmcp
     #   gradio
     #   gradio-client
+    #   huggingface-hub
     #   mcp
     #   openai
     #   safehttpx
-httpx-sse==0.4.1
+httpx-sse==0.4.3
     # via mcp
-huggingface-hub==0.35.1
+huggingface-hub==1.2.3
     # via
     #   gradio
     #   gradio-client
-idna==3.10
+idna==3.11
     # via
     #   anyio
     #   email-validator
@@ -139,9 +141,9 @@ jeepney==0.9.0
     #   secretstorage
 jinja2==3.1.6
     # via gradio
-jiter==0.10.0
+jiter==0.12.0
     # via openai
-jsonschema==4.24.0
+jsonschema==4.25.1
     # via
     #   mcp
     #   openapi-core
@@ -151,24 +153,24 @@ jsonschema-path==0.3.4
     # via
     #   openapi-core
     #   openapi-spec-validator
-jsonschema-specifications==2025.4.1
+jsonschema-specifications==2025.9.1
     # via
     #   jsonschema
     #   openapi-schema-validator
-keyring==25.6.0
+keyring==25.7.0
     # via py-key-value-aio
 lazy-object-proxy==1.12.0
     # via openapi-spec-validator
 lxml==6.0.2
     # via ankigen (pyproject.toml)
-markdown-it-py==3.0.0
+markdown-it-py==4.0.0
     # via rich
-markupsafe==3.0.2
+markupsafe==3.0.3
     # via
     #   gradio
     #   jinja2
     #   werkzeug
-mcp==1.20.0
+mcp==1.24.0
     # via
     #   fastmcp
     #   openai-agents
@@ -179,17 +181,17 @@ more-itertools==10.8.0
     #   jaraco-classes
     #   jaraco-functools
     #   openapi-core
-numpy==2.3.1
+numpy==2.3.5
     # via
     #   gradio
     #   pandas
-openai==2.8.1
+openai==2.14.0
     # via
     #   ankigen (pyproject.toml)
     #   openai-agents
-openai-agents==0.6.1
+openai-agents==0.6.4
     # via ankigen (pyproject.toml)
-openapi-core==0.19.5
+openapi-core==0.21.0
     # via fastmcp
 openapi-pydantic==0.5.1
     # via fastmcp
@@ -199,26 +201,24 @@ openapi-schema-validator==0.6.3
     #   openapi-spec-validator
 openapi-spec-validator==0.7.2
     # via openapi-core
-orjson==3.10.18
+orjson==3.11.5
     # via gradio
 packaging==25.0
     # via
     #   gradio
     #   gradio-client
     #   huggingface-hub
-pandas==2.3.2
+pandas==2.3.3
     # via
     #   ankigen (pyproject.toml)
     #   gradio
-parse==1.20.2
-    # via openapi-core
 pathable==0.4.4
     # via jsonschema-path
 pathvalidate==3.3.1
     # via py-key-value-aio
-pillow==11.3.0
+pillow==12.0.0
     # via gradio
-platformdirs==4.5.0
+platformdirs==4.5.1
     # via fastmcp
 py-key-value-aio==0.2.8
     # via fastmcp
@@ -239,7 +239,7 @@ pydantic==2.12.4
     #   pydantic-settings
 pydantic-core==2.41.5
     # via pydantic
-pydantic-settings==2.10.1
+pydantic-settings==2.12.0
     # via mcp
 pydub==0.25.1
     # via gradio
@@ -247,21 +247,21 @@ pygments==2.19.2
     # via rich
 pyjwt==2.10.1
     # via mcp
-pyperclip==1.10.0
+pyperclip==1.11.0
     # via fastmcp
 python-dateutil==2.9.0.post0
     # via pandas
-python-dotenv==1.1.1
+python-dotenv==1.2.1
     # via
     #   fastmcp
     #   pydantic-settings
-python-multipart==0.0.20
+python-multipart==0.0.21
     # via
     #   gradio
     #   mcp
 pytz==2025.2
     # via pandas
-pyyaml==6.0.2
+pyyaml==6.0.3
     # via
     #   genanki
     #   gradio
@@ -272,57 +272,57 @@ referencing==0.36.2
     #   jsonschema
     #   jsonschema-path
     #   jsonschema-specifications
-regex==2024.11.6
+regex==2025.11.3
     # via tiktoken
-requests==2.32.4
+requests==2.32.5
     # via
-    #   huggingface-hub
     #   jsonschema-path
     #   openai-agents
     #   tiktoken
 rfc3339-validator==0.1.4
     # via openapi-schema-validator
-rich==14.0.0
+rich==14.2.0
     # via
     #   cyclopts
     #   fastmcp
     #   rich-rst
     #   typer
-rich-rst==1.3.1
+rich-rst==1.3.2
     # via cyclopts
-rpds-py==0.26.0
+rpds-py==0.30.0
     # via
     #   jsonschema
     #   referencing
 safehttpx==0.1.7
     # via gradio
-secretstorage==3.4.0
+secretstorage==3.5.0
     # via keyring
 semantic-version==2.10.0
     # via gradio
 shellingham==1.5.4
-    # via typer
+    # via
+    #   huggingface-hub
+    #   typer
 six==1.17.0
     # via
     #   python-dateutil
     #   rfc3339-validator
 sniffio==1.3.1
-    # via
-    #   anyio
-    #   openai
-soupsieve==2.7
+    # via openai
+soupsieve==2.8.1
     # via beautifulsoup4
-sse-starlette==2.3.6
+sse-starlette==3.0.4
     # via mcp
-starlette==0.49.3
+starlette==0.50.0
     # via
     #   ankigen (pyproject.toml)
     #   fastapi
     #   gradio
     #   mcp
+    #   sse-starlette
 tenacity==9.1.2
     # via ankigen (pyproject.toml)
-tiktoken==0.11.0
+tiktoken==0.12.0
     # via ankigen (pyproject.toml)
 tomlkit==0.13.3
     # via gradio
@@ -330,9 +330,11 @@ tqdm==4.67.1
     # via
     #   huggingface-hub
     #   openai
-typer==0.16.0
+typer==0.20.0
     # via gradio
-types-requests==2.32.4.20250611
+typer-slim==0.20.0
+    # via huggingface-hub
+types-requests==2.32.4.20250913
     # via openai-agents
 typing-extensions==4.15.0
     # via
@@ -343,6 +345,7 @@ typing-extensions==4.15.0
     #   gradio
     #   gradio-client
     #   huggingface-hub
+    #   mcp
     #   openai
     #   openai-agents
     #   openapi-core
@@ -352,22 +355,24 @@ typing-extensions==4.15.0
     #   referencing
     #   starlette
     #   typer
+    #   typer-slim
     #   typing-inspection
 typing-inspection==0.4.2
     # via
+    #   mcp
     #   pydantic
     #   pydantic-settings
-tzdata==2025.2
+tzdata==2025.3
     # via pandas
-urllib3==2.5.0
+urllib3==2.6.2
     # via
     #   requests
     #   types-requests
-uvicorn==0.34.3
+uvicorn==0.38.0
     # via
     #   gradio
     #   mcp
 websockets==15.0.1
     # via fastmcp
-werkzeug==3.1.1
+werkzeug==3.1.4
     # via openapi-core