Improve mobile responsiveness

.gitignore

@@ -211,6 +211,8 @@ htmlcov/
 nosetests.xml
 coverage.xml
 develop/
+web/playwright-report/
+web/test-results/
 
 # ============================================
 # Jupyter Notebook

deeptutor/api/routers/attachments.py

@@ -46,9 +46,7 @@ def _content_disposition(filename: str, *, disposition: str = "inline") -> str:
     # Quotes / backslashes break the simple-quoted-string form; collapse them.
     ascii_fallback = ascii_fallback.replace('"', "_").replace("\\", "_")
     encoded = quote(filename, safe="")
-    return (
-        f'{disposition}; filename="{ascii_fallback}"; filename*=UTF-8\'\'{encoded}'
-    )
+    return f"{disposition}; filename=\"{ascii_fallback}\"; filename*=UTF-8''{encoded}"
 
 
 @router.get("/{session_id}/{attachment_id}/{filename:path}")

deeptutor/api/routers/knowledge.py

@@ -168,9 +168,7 @@ def _save_uploaded_files(
                     except OSError:
                         pass
 
-                error_message = (
-                    f"Validation failed for file '{original_filename}': {format_exception_message(e)}"
-                )
+                error_message = f"Validation failed for file '{original_filename}': {format_exception_message(e)}"
                 logger.error(error_message, exc_info=True)
                 raise HTTPException(status_code=400, detail=error_message) from e
     except Exception:

deeptutor/api/routers/notebook.py

@@ -41,9 +41,7 @@ class AddRecordRequest(BaseModel):
     """Add record request"""
 
     notebook_ids: list[str]
-    record_type: Literal[
-        "solve", "question", "research", "chat", "co_writer", "tutorbot"
-    ]
+    record_type: Literal["solve", "question", "research", "chat", "co_writer", "tutorbot"]
     title: str
     summary: str = ""
     user_query: str

deeptutor/api/routers/question.py

@@ -486,12 +486,14 @@ async def log_pusher():
 
             # Log additional context if available
             try:
-                if "result" in locals():
+                local_vars = locals()
+                if "result" in local_vars:
+                    result_value = local_vars["result"]
                     logger.error(
-                        f"Result type: {type(result)}, result keys: {result.keys() if isinstance(result, dict) else 'N/A'}"
+                        f"Result type: {type(result_value)}, result keys: {result_value.keys() if isinstance(result_value, dict) else 'N/A'}"
                     )
-                    if isinstance(result, dict) and "validation" in result:
-                        validation = result["validation"]
+                    if isinstance(result_value, dict) and "validation" in result_value:
+                        validation = result_value["validation"]
                         logger.error(f"Validation type: {type(validation)}")
                         if isinstance(validation, dict):
                             logger.error(f"Validation keys: {validation.keys()}")

deeptutor/api/routers/solve.py

@@ -6,6 +6,7 @@
 """
 
 import asyncio
+from pathlib import Path
 import re
 from typing import Any
 

deeptutor/knowledge/manager.py

@@ -253,7 +253,9 @@ def update_kb_status(
             # permanently carrying a "completed" progress banner.
             kb_config.pop("progress", None)
             if progress is not None:
-                kb_config["last_completed_at"] = progress.get("timestamp") or datetime.now().isoformat()
+                kb_config["last_completed_at"] = (
+                    progress.get("timestamp") or datetime.now().isoformat()
+                )
         elif progress is not None:
             kb_config["progress"] = progress
 

deeptutor/knowledge/progress_tracker.py

@@ -134,7 +134,9 @@ def _save_progress(self, progress: dict):
                 f.flush()
             temp_progress_file.replace(self.progress_file)
         except Exception as e:
-            _get_logger().warning("Failed to persist progress snapshot for '%s': %s", self.kb_name, e)
+            _get_logger().warning(
+                "Failed to persist progress snapshot for '%s': %s", self.kb_name, e
+            )
 
     def update(
         self,

deeptutor/services/config/context_window_detection.py

@@ -145,7 +145,9 @@ async def _detect_from_models_endpoint(
             async with session.get(url, headers=headers) as response:
                 if response.status != 200:
                     if on_log is not None:
-                        on_log(f"`GET {url}` returned HTTP {response.status}; skipping metadata detection.")
+                        on_log(
+                            f"`GET {url}` returned HTTP {response.status}; skipping metadata detection."
+                        )
                     return None
                 payload = await response.json()
     except Exception as exc:

deeptutor/services/config/test_runner.py

@@ -215,10 +215,7 @@ async def _test_llm(self, run: TestRun, catalog: dict[str, Any]) -> None:
         )
         run.emit(
             "context_window",
-            (
-                f"Context window set to {detection.context_window} tokens "
-                f"({detection.source})."
-            ),
+            (f"Context window set to {detection.context_window} tokens ({detection.source})."),
             context_window=detection.context_window,
             source=detection.source,
             detail=detection.detail,

deeptutor/services/llm/factory.py

@@ -3,8 +3,8 @@
 from __future__ import annotations
 
 import asyncio
-import contextlib
 from collections.abc import AsyncGenerator, Mapping
+import contextlib
 from types import SimpleNamespace
 from typing import Any, TypedDict
 
@@ -184,12 +184,16 @@ def _resolve_call_config(
 
 
 def _capability_binding(config: LLMConfig, provider_spec: Any) -> str:
-    backend = getattr(provider_spec, "backend", "openai_compat") if provider_spec else "openai_compat"
+    backend = (
+        getattr(provider_spec, "backend", "openai_compat") if provider_spec else "openai_compat"
+    )
     if backend == "anthropic":
         return "anthropic"
     if backend == "azure_openai":
         return "azure_openai"
-    return getattr(provider_spec, "name", None) or config.provider_name or config.binding or "openai"
+    return (
+        getattr(provider_spec, "name", None) or config.provider_name or config.binding or "openai"
+    )
 
 
 def _build_messages(
@@ -312,7 +316,9 @@ async def complete(
         image_data=image_data,
     )
     retry_delays = _build_retry_delays(max_retries, retry_delay, exponential_backoff)
-    extra_kwargs = _sanitize_call_kwargs(binding=capability_binding, model=config.model, kwargs=kwargs)
+    extra_kwargs = _sanitize_call_kwargs(
+        binding=capability_binding, model=config.model, kwargs=kwargs
+    )
 
     try:
         response = await provider.chat_with_retry(
@@ -325,7 +331,9 @@ async def complete(
         raise map_error(exc, provider=config.provider_name) from exc
 
     if response.finish_reason == "error":
-        raise map_error(RuntimeError(response.content or "LLM request failed"), provider=config.provider_name)
+        raise map_error(
+            RuntimeError(response.content or "LLM request failed"), provider=config.provider_name
+        )
     return response.content or ""
 
 
@@ -366,7 +374,9 @@ async def stream(
         image_data=image_data,
     )
     retry_delays = _build_retry_delays(max_retries, retry_delay, exponential_backoff)
-    extra_kwargs = _sanitize_call_kwargs(binding=capability_binding, model=config.model, kwargs=kwargs)
+    extra_kwargs = _sanitize_call_kwargs(
+        binding=capability_binding, model=config.model, kwargs=kwargs
+    )
 
     queue: asyncio.Queue[str | BaseException | None] = asyncio.Queue()
     saw_output = False

deeptutor/services/llm/provider_core/anthropic_provider.py

@@ -41,6 +41,7 @@ def __init__(
         self._supports_prompt_caching = supports_prompt_caching
 
         from anthropic import AsyncAnthropic
+
         from deeptutor.services.llm.utils import sanitize_url
 
         client_kw: dict[str, Any] = {"max_retries": 0}

deeptutor/services/llm/provider_core/azure_openai_provider.py

@@ -160,7 +160,9 @@ async def _timed_stream():
                 stream_iter = stream.__aiter__()
                 while True:
                     try:
-                        yield await asyncio.wait_for(stream_iter.__anext__(), timeout=idle_timeout_s)
+                        yield await asyncio.wait_for(
+                            stream_iter.__anext__(), timeout=idle_timeout_s
+                        )
                     except StopAsyncIteration:
                         break
 

deeptutor/services/llm/provider_core/base.py

@@ -4,10 +4,10 @@
 
 from abc import ABC, abstractmethod
 import asyncio
+from collections.abc import Awaitable, Callable, Sequence
 from dataclasses import dataclass, field
 import json
 from typing import Any
-from collections.abc import Awaitable, Callable, Sequence
 
 from loguru import logger
 

deeptutor/services/llm/provider_core/github_copilot_provider.py

@@ -2,8 +2,8 @@
 
 from __future__ import annotations
 
-import time
 from collections.abc import Awaitable, Callable
+import time
 from typing import Any
 
 import httpx
@@ -66,7 +66,9 @@ async def _exchange_token(self) -> str:
             )
 
         timeout = httpx.Timeout(20.0, connect=20.0)
-        async with httpx.AsyncClient(timeout=timeout, follow_redirects=True, trust_env=True) as client:
+        async with httpx.AsyncClient(
+            timeout=timeout, follow_redirects=True, trust_env=True
+        ) as client:
             response = await client.get(
                 DEFAULT_COPILOT_TOKEN_URL,
                 headers={

deeptutor/services/llm/provider_core/openai_codex_provider.py

@@ -3,16 +3,20 @@
 from __future__ import annotations
 
 import asyncio
+from collections.abc import Awaitable, Callable
 import hashlib
 import json
-from collections.abc import Awaitable, Callable
 from typing import Any
 
 import httpx
 from loguru import logger
 
 from deeptutor.services.llm.provider_core.base import LLMProvider, LLMResponse, ToolCallRequest
-from deeptutor.services.llm.provider_core.openai_responses import consume_sse, convert_messages, convert_tools
+from deeptutor.services.llm.provider_core.openai_responses import (
+    consume_sse,
+    convert_messages,
+    convert_tools,
+)
 
 DEFAULT_CODEX_URL = "https://chatgpt.com/backend-api/codex/responses"
 DEFAULT_ORIGINATOR = "DeepTutor"
@@ -138,7 +142,9 @@ def _strip_model_prefix(model: str) -> str:
 
 def _build_headers(account_id: Any, token: Any) -> dict[str, str]:
     if not token:
-        raise RuntimeError("OpenAI Codex is not logged in. Run `deeptutor provider login openai-codex`.")
+        raise RuntimeError(
+            "OpenAI Codex is not logged in. Run `deeptutor provider login openai-codex`."
+        )
     headers = {
         "Authorization": f"Bearer {token}",
         "OpenAI-Beta": "responses=experimental",
@@ -163,7 +169,9 @@ async def _request_codex(
         async with client.stream("POST", url, headers=headers, json=body) as response:
             if response.status_code != 200:
                 text = await response.aread()
-                raise RuntimeError(_friendly_error(response.status_code, text.decode("utf-8", "ignore")))
+                raise RuntimeError(
+                    _friendly_error(response.status_code, text.decode("utf-8", "ignore"))
+                )
             return await consume_sse(response, on_content_delta)
 
 

deeptutor/services/llm/provider_core/openai_compat_provider.py

@@ -9,9 +9,9 @@
 import asyncio
 from collections.abc import Awaitable, Callable
 import hashlib
-import time
 import secrets
 import string
+import time
 from typing import TYPE_CHECKING, Any
 import uuid
 
@@ -50,9 +50,7 @@
 _RESPONSES_FAILURE_THRESHOLD = 2
 _RESPONSES_PROBE_INTERVAL_S = 300.0
 _THINKING_STYLE_MAP = {
-    "thinking_type": lambda enabled: {
-        "thinking": {"type": "enabled" if enabled else "disabled"}
-    },
+    "thinking_type": lambda enabled: {"thinking": {"type": "enabled" if enabled else "disabled"}},
     "enable_thinking": lambda enabled: {"enable_thinking": enabled},
     "reasoning_split": lambda enabled: {"reasoning_split": enabled},
 }
@@ -713,9 +711,9 @@ async def chat(
             try:
                 return self._parse(await self._client.chat.completions.create(**request_kwargs))
             except Exception as exc:
-                if request_kwargs.get("response_format") is not None and self._is_response_format_error(
-                    exc
-                ):
+                if request_kwargs.get(
+                    "response_format"
+                ) is not None and self._is_response_format_error(exc):
                     binding = self._provider_name or (self._spec.name if self._spec else "openai")
                     disable_response_format_at_runtime(binding, request_kwargs.get("model"))
                     retry_kwargs = dict(request_kwargs)
@@ -786,9 +784,13 @@ async def _timed_stream():
                             except StopAsyncIteration:
                                 break
 
-                    content, tool_calls, finish_reason, usage, reasoning_content = (
-                        await consume_sdk_stream(_timed_stream(), on_content_delta)
-                    )
+                    (
+                        content,
+                        tool_calls,
+                        finish_reason,
+                        usage,
+                        reasoning_content,
+                    ) = await consume_sdk_stream(_timed_stream(), on_content_delta)
                     self._record_responses_success(model, reasoning_effort)
                     return LLMResponse(
                         content=content or None,
@@ -809,9 +811,9 @@ async def _timed_stream():
             try:
                 stream = await self._client.chat.completions.create(**request_kwargs)
             except Exception as exc:
-                if request_kwargs.get("response_format") is not None and self._is_response_format_error(
-                    exc
-                ):
+                if request_kwargs.get(
+                    "response_format"
+                ) is not None and self._is_response_format_error(exc):
                     binding = self._provider_name or (self._spec.name if self._spec else "openai")
                     disable_response_format_at_runtime(binding, request_kwargs.get("model"))
                     retry_kwargs = dict(request_kwargs)

deeptutor/services/llm/provider_core/openai_responses/converters.py

@@ -74,9 +74,7 @@ def convert_user_message(content: Any) -> dict[str, Any]:
             elif item.get("type") == "image_url":
                 url = (item.get("image_url") or {}).get("url")
                 if url:
-                    converted.append(
-                        {"type": "input_image", "image_url": url, "detail": "auto"}
-                    )
+                    converted.append({"type": "input_image", "image_url": url, "detail": "auto"})
         if converted:
             return {"role": "user", "content": converted}
     return {"role": "user", "content": [{"type": "input_text", "text": ""}]}

deeptutor/services/llm/provider_core/openai_responses/parsing.py

@@ -2,8 +2,8 @@
 
 from __future__ import annotations
 
-import json
 from collections.abc import Awaitable, Callable
+import json
 from typing import Any, AsyncGenerator
 
 import httpx

deeptutor/services/rag/service.py

@@ -223,7 +223,9 @@ async def _generate_queries(self, context: str, n: int) -> list[str]:
             )
             raw = await complete(prompt, system_prompt="You are a search query generator.")
             lines = [
-                l.strip().lstrip("0123456789.-) ") for l in raw.strip().split("\n") if l.strip()
+                line.strip().lstrip("0123456789.-) ")
+                for line in raw.strip().split("\n")
+                if line.strip()
             ]
             return lines[:n] if lines else [context[:200]]
         except Exception:

deeptutor/services/session/turn_runtime.py

@@ -600,9 +600,7 @@ async def _run_turn(self, execution: _TurnExecution) -> None:
 
             from deeptutor.utils.document_extractor import extract_documents_from_records
 
-            document_texts, attachment_records = extract_documents_from_records(
-                attachment_records
-            )
+            document_texts, attachment_records = extract_documents_from_records(attachment_records)
             attachments = [
                 Attachment(
                     type=r.get("type", "file"),