feat(bot): add backup models

backend/.env.example

@@ -2,6 +2,10 @@ BOT__TOKEN=<BOT__TOKEN>
 
 SITE__URL=<SITE__URL>
 
+# Leave ANTHROPIC_API_KEY empty to disable the Anthropic backup.
+ANTHROPIC_API_KEY=
+ANTHROPIC_MODEL=claude-opus-4-8
+
 LOG__LEVEL=INFO
 LOG__LEVEL_EXTERNAL=WARNING
 LOG__SHOW_TIME=false

backend/pyproject.toml

@@ -10,7 +10,7 @@ dependencies = [
     "aiogram>=3.24.0",
     "convex>=0.7.0",
     "httpx>=0.27",
-    "pydantic-ai-slim[google]>=1.44.0",
+    "pydantic-ai-slim[google,anthropic]>=1.44.0",
     "pydantic-settings>=2.12.0",
     "rich>=14.2.0",
     "xkcdpass>=1.19.0",

backend/src/bot/handlers/message/handler.py

@@ -28,8 +28,10 @@ from bot.modules.ai import (
     get_follow_ups,
     stream_response,
 )
+from bot.user_lock import get_user_lock
 from utils import env
 from utils.convex import ConvexClient
+from utils.logging import logger
 
 router = Router()
 convex = ConvexClient(env.convex_url)
@@ -53,9 +55,7 @@ async def _enqueue_room_upload(
             },
         )
     except Exception as e:  # noqa: BLE001
-        from utils.logging import logger as _logger  # noqa: PLC0415
+        logger.warning(f"Failed to enqueue room upload: {e}")
-
-        _logger.warning(f"Failed to enqueue room upload: {e}")
 
 
 def schedule_room_uploads(
@@ -235,7 +235,10 @@ class ProxyStreamingState:
 
 
 async def send_long_message(
-    bot: Bot, chat_id: int, text: str, reply_markup: ReplyKeyboardMarkup | None = None
+    bot: Bot,
+    chat_id: int,
+    text: str,
+    reply_markup: ReplyKeyboardMarkup | ReplyKeyboardRemove | None = None,
 ) -> int | None:
     parts = split_message(text)
     first_id: int | None = None
@@ -256,15 +259,34 @@ async def process_message_from_web(  # noqa: C901, PLR0912, PLR0913, PLR0915
     convex_chat_id: str,
     images_base64: list[str] | None = None,
     images_media_types: list[str] | None = None,
+    pending_generation_id: str | None = None,
 ) -> None:
     user = await convex.query("users:getById", {"userId": convex_user_id})
 
     if not user or not user.get("geminiApiKey"):
         return
 
-    tg_chat_id = user["telegramChatId"].value if user.get("telegramChatId") else None
     is_summarize = text == "/summarize"
 
+    if not is_summarize:
+        user_message_args: dict = {
+            "chatId": convex_chat_id,
+            "role": "user",
+            "content": text,
+            "source": "web",
+        }
+        if images_base64 and images_media_types:
+            user_message_args["imagesBase64"] = images_base64
+            user_message_args["imagesMediaTypes"] = images_media_types
+        await convex.mutation("messages:createFromBackend", user_message_args)
+
+    if pending_generation_id:
+        await convex.mutation(
+            "pendingGenerations:remove", {"id": pending_generation_id}
+        )
+
+    tg_chat_id = user["telegramChatId"].value if user.get("telegramChatId") else None
+
     if tg_chat_id and not is_summarize:
         if images_base64 and images_media_types:
             if len(images_base64) == 1:
@@ -339,7 +361,7 @@ async def process_message_from_web(  # noqa: C901, PLR0912, PLR0913, PLR0915
     system_prompt = SUMMARIZE_PROMPT if is_summarize else user.get("systemPrompt")
     if system_prompt and inject_content:
         system_prompt = system_prompt.replace("{theory_database}", inject_content)
-    text_agent = create_text_agent(
+    text_agent = await create_text_agent(
         api_key=api_key,
         model_name=model_name,
         system_prompt=system_prompt,
@@ -386,13 +408,21 @@ async def process_message_from_web(  # noqa: C901, PLR0912, PLR0913, PLR0915
         if state:
             await state.flush()
 
+        follow_ups: list[str] = []
+        try:
             full_history = [*history, {"role": "assistant", "content": final_answer}]
-        follow_up_model = user.get("followUpModel", "gemini-2.5-flash-lite")
+            follow_up_model = user.get("followUpModel", "gemini-3.1-flash-lite")
             follow_up_prompt = user.get("followUpPrompt")
             follow_up_agent = create_follow_up_agent(
-            api_key=api_key, model_name=follow_up_model, system_prompt=follow_up_prompt
+                api_key=api_key,
+                model_name=follow_up_model,
+                system_prompt=follow_up_prompt,
             )
-        follow_ups = await get_follow_ups(follow_up_agent, full_history, chat_images)
+            follow_ups = await get_follow_ups(
+                follow_up_agent, full_history, chat_images
+            )
+        except Exception as e:  # noqa: BLE001
+            logger.warning(f"Follow-up generation failed: {e}")
 
         if state:
             await state.stop_typing()
@@ -425,7 +455,11 @@ async def process_message_from_web(  # noqa: C901, PLR0912, PLR0913, PLR0915
         if tg_chat_id and processing_msg:
             with contextlib.suppress(Exception):
                 await processing_msg.delete()
-            keyboard = make_follow_up_keyboard(follow_ups)
+            keyboard = (
+                make_follow_up_keyboard(follow_ups)
+                if follow_ups
+                else ReplyKeyboardRemove()
+            )
             sent_id = await send_long_message(bot, tg_chat_id, final_answer, keyboard)
             if sent_id is not None:
                 with contextlib.suppress(Exception):
@@ -485,6 +519,7 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
     model_name = user.get("model", "gemini-3-pro-preview")
     convex_user_id = user["_id"]
 
+    async with get_user_lock(convex_user_id):
         proxy_config = get_proxy_config(chat_id)
         proxy_state: ProxyStreamingState | None = None
 
@@ -515,7 +550,8 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
         if inject_connections:
             for conn in inject_connections:
                 db = await convex.query(
-                "inject:getDatabaseById", {"injectDatabaseId": conn["injectDatabaseId"]}
+                    "inject:getDatabaseById",
+                    {"injectDatabaseId": conn["injectDatabaseId"]},
                 )
                 if db and db.get("content"):
                     inject_content += db["content"] + "\n\n"
@@ -550,7 +586,7 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
         system_prompt = user.get("systemPrompt")
         if system_prompt and inject_content:
             system_prompt = system_prompt.replace("{theory_database}", inject_content)
-    text_agent = create_text_agent(
+        text_agent = await create_text_agent(
             api_key=api_key,
             model_name=model_name,
             system_prompt=system_prompt,
@@ -558,7 +594,9 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
         )
 
         agent_deps = (
-        AgentDeps(user_id=convex_user_id, api_key=api_key, rag_db_names=rag_db_names)
+            AgentDeps(
+                user_id=convex_user_id, api_key=api_key, rag_db_names=rag_db_names
+            )
             if rag_db_names
             else None
         )
@@ -571,7 +609,9 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
                 proxy_config.target_chat_id, "..."
             )
             proxy_state = ProxyStreamingState(
-            proxy_config.proxy_bot, proxy_config.target_chat_id, proxy_processing_msg
+                proxy_config.proxy_bot,
+                proxy_config.target_chat_id,
+                proxy_processing_msg,
             )
 
         try:
@@ -601,13 +641,24 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
             if proxy_state:
                 await proxy_state.flush()
 
-        full_history = [*history[:-1], {"role": "assistant", "content": final_answer}]
+            follow_ups: list[str] = []
-        follow_up_model = user.get("followUpModel", "gemini-2.5-flash-lite")
+            try:
+                full_history = [
+                    *history[:-1],
+                    {"role": "assistant", "content": final_answer},
+                ]
+                follow_up_model = user.get("followUpModel", "gemini-3.1-flash-lite")
                 follow_up_prompt = user.get("followUpPrompt")
                 follow_up_agent = create_follow_up_agent(
-            api_key=api_key, model_name=follow_up_model, system_prompt=follow_up_prompt
+                    api_key=api_key,
+                    model_name=follow_up_model,
+                    system_prompt=follow_up_prompt,
                 )
-        follow_ups = await get_follow_ups(follow_up_agent, full_history, chat_images)
+                follow_ups = await get_follow_ups(
+                    follow_up_agent, full_history, chat_images
+                )
+            except Exception as e:  # noqa: BLE001
+                logger.warning(f"Follow-up generation failed: {e}")
 
             await state.stop_typing()
 
@@ -624,7 +675,11 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
             with contextlib.suppress(Exception):
                 await processing_msg.delete()
 
-        keyboard = make_follow_up_keyboard(follow_ups)
+            keyboard = (
+                make_follow_up_keyboard(follow_ups)
+                if follow_ups
+                else ReplyKeyboardRemove()
+            )
             await send_long_message(bot, chat_id, final_answer, keyboard)
 
             if proxy_state and proxy_config:
@@ -649,7 +704,9 @@ async def process_message(  # noqa: C901, PLR0912, PLR0913, PLR0915
                 },
             )
             with contextlib.suppress(Exception):
-            await processing_msg.edit_text(html.quote(error_msg[:TELEGRAM_MAX_LENGTH]))
+                await processing_msg.edit_text(
+                    html.quote(error_msg[:TELEGRAM_MAX_LENGTH])
+                )
             if proxy_state:
                 with contextlib.suppress(Exception):
                     await proxy_state.message.edit_text(error_msg[:TELEGRAM_MAX_LENGTH])

backend/src/bot/modules/ai/agent.py

@@ -1,3 +1,5 @@
+import asyncio
+import time
 from collections.abc import Awaitable, Callable
 from dataclasses import dataclass
 
@@ -11,6 +13,8 @@ from pydantic_ai import (
     TextPart,
     UserPromptPart,
 )
+from pydantic_ai.models import Model
+from pydantic_ai.models.fallback import FallbackModel
 from pydantic_ai.models.google import GoogleModel
 from pydantic_ai.providers.google import GoogleProvider
 
@@ -24,6 +28,113 @@ from .prompts import DEFAULT_FOLLOW_UP
 StreamCallback = Callable[[str], Awaitable[None]]
 convex = ConvexClient(env.convex_url)
 
+CONTENT_FALLBACK_CHAIN = ["gemini-3.5-pro", "gemini-3.1-pro", "gemini-3.5-flash"]
+FOLLOW_UP_FALLBACK_CHAIN = [
+    "gemini-3.5-flash",
+    "gemini-3.1-flash-lite",
+    "gemini-3.5-flash-lite",
+]
+MODELS_CACHE_TTL_SECONDS = 600.0
+
+_models_cache: dict[str, tuple[float, set[str]]] = {}
+
+
+def _strip_preview(name: str) -> str:
+    return (
+        name.removesuffix("-preview").rstrip("-") if name.endswith("-preview") else name
+    )
+
+
+def _dedup(names: list[str]) -> list[str]:
+    seen: set[str] = set()
+    result: list[str] = []
+    for name in names:
+        if name and name not in seen:
+            seen.add(name)
+            result.append(name)
+    return result
+
+
+def _fetch_google_models(api_key: str) -> set[str]:
+    names: set[str] = set()
+    try:
+        from google import genai  # noqa: PLC0415
+
+        client = genai.Client(api_key=api_key)
+        for model in client.models.list():
+            name = (model.name or "").removeprefix("models/")
+            actions = getattr(model, "supported_actions", None) or getattr(
+                model, "supported_generation_methods", None
+            )
+            if actions and "generateContent" not in actions:
+                continue
+            if name:
+                names.add(name)
+    except Exception as e:  # noqa: BLE001
+        logger.warning(f"Failed to list Google models: {e}")
+    return names
+
+
+async def _available_google_models(api_key: str) -> set[str]:
+    cached = _models_cache.get(api_key)
+    now = time.monotonic()
+    if cached and (now - cached[0]) < MODELS_CACHE_TTL_SECONDS:
+        return cached[1]
+    names = await asyncio.to_thread(_fetch_google_models, api_key)
+    if names:
+        _models_cache[api_key] = (now, names)
+    return names
+
+
+def _pick_from_available(available: set[str]) -> list[str]:
+    gemini = sorted(
+        n for n in available if n.startswith("gemini-") and "preview" not in n
+    )
+    pros = [n for n in gemini if "pro" in n]
+    flashes = [n for n in gemini if "flash" in n]
+    picked = _dedup([*pros[:2], *flashes[:2]])
+    return picked or sorted(available)[:3]
+
+
+def _anthropic_model() -> Model | None:
+    key = env.anthropic_api_key.get_secret_value()
+    if not key:
+        return None
+    from pydantic_ai.models.anthropic import AnthropicModel  # noqa: PLC0415
+    from pydantic_ai.providers.anthropic import AnthropicProvider  # noqa: PLC0415
+
+    return AnthropicModel(env.anthropic_model, provider=AnthropicProvider(api_key=key))
+
+
+def _as_model(models: list[Model]) -> Model:
+    return models[0] if len(models) == 1 else FallbackModel(*models)
+
+
+async def build_content_model(api_key: str, requested_model: str) -> Model:
+    candidates = _dedup(
+        [requested_model, _strip_preview(requested_model), *CONTENT_FALLBACK_CHAIN]
+    )
+    available = await _available_google_models(api_key)
+    if available:
+        live = [name for name in candidates if name in available]
+        candidates = live or _pick_from_available(available) or candidates
+
+    provider = GoogleProvider(api_key=api_key)
+    models: list[Model] = [GoogleModel(name, provider=provider) for name in candidates]
+    anthropic = _anthropic_model()
+    if anthropic:
+        models.append(anthropic)
+    return _as_model(models)
+
+
+def build_follow_up_model(api_key: str, requested_model: str) -> Model:
+    candidates = _dedup(
+        [requested_model, _strip_preview(requested_model), *FOLLOW_UP_FALLBACK_CHAIN]
+    )
+    provider = GoogleProvider(api_key=api_key)
+    models: list[Model] = [GoogleModel(name, provider=provider) for name in candidates]
+    return _as_model(models)
+
 
 @dataclass
 class ImageData:
@@ -51,19 +162,18 @@ RAG_SYSTEM_ADDITION = (
 )
 
 
-def create_text_agent(
+async def create_text_agent(
     api_key: str,
     model_name: str = "gemini-3-pro-preview",
     system_prompt: str | None = None,
     rag_db_names: list[str] | None = None,
 ) -> Agent[AgentDeps, str] | Agent[None, str]:
-    provider = GoogleProvider(api_key=api_key)
+    model = await build_content_model(api_key, model_name)
-    model = GoogleModel(model_name, provider=provider)
     base_prompt = system_prompt or DEFAULT_SYSTEM_PROMPT
 
     if rag_db_names:
         full_prompt = f"{base_prompt}{RAG_SYSTEM_ADDITION} {LATEX_INSTRUCTION}"
-        agent: Agent[None, str] = Agent(
+        agent: Agent[AgentDeps, str] = Agent(
             model, instructions=full_prompt, deps_type=AgentDeps
         )
 
@@ -101,13 +211,15 @@ def create_text_agent(
 
 def create_follow_up_agent(
     api_key: str,
-    model_name: str = "gemini-2.5-flash-lite",
+    model_name: str = "gemini-3.1-flash-lite-preview",
     system_prompt: str | None = None,
 ) -> Agent[None, FollowUpOptions]:
-    provider = GoogleProvider(api_key=api_key)
+    model = build_follow_up_model(api_key, model_name)
-    model = GoogleModel(model_name, provider=provider)
     prompt = system_prompt or DEFAULT_FOLLOW_UP
-    return Agent(model, output_type=FollowUpOptions, instructions=prompt)
+    agent: Agent[None, FollowUpOptions] = Agent(  # ty: ignore[invalid-assignment]
+        model, output_type=FollowUpOptions, instructions=prompt
+    )
+    return agent
 
 
 def build_message_history(history: list[dict[str, str]]) -> list[ModelMessage]:

backend/src/bot/modules/ai/prompts.py

@@ -104,6 +104,100 @@ Example output:
 "3. Usually implemented as swapping randomly selected subtrees of parent trees"
 """
 
+
+REFERENCE_SYSTEM = """
+You are an Examination Engine for solving problem sets, designed for Apple Watch output.
+
+You operate against context bank:
+
+<EXAM_MATERIALS>
+{theory_database}
+</EXAM_MATERIALS>
+
+*** PROTOCOL: BATCH PROCESSING ***
+
+1. **DETECT ALL** problems in input.
+2. **SOLVE ALL** sequentially in one response.
+3. **ORDER:** follow source numbering. Subparts (a, b, c) stay grouped under parent.
+4. **SEPARATOR:** "---" between problems.
+5. **CONTINUATION:** new page after partial solve → don't repeat solved tasks.
+6. **NO PREAMBLE.** Start directly with **Ex. 1**. No "I see the following problems".
+
+*** SOLVING LOGIC ***
+
+This is a PROBLEM-SOLVING engine, not a theory recall engine.
+Every problem gets a full derivation.
+
+- **Honor EXAM_MATERIALS first.** If they specify a formula source, notation,
+ forbidden method, required step or example - comply.
+- Mirror approach exactly: same notation, structure, justification depth, voice.
+- If no match in materials → infer canonical structure from examples and apply.
+- **Show all reasoning** that examples show.
+ Don't skip steps "because obvious" if examples don't skip them.
+- **Brief justifications welcome** when examples use them
+("by symmetry", "since disjoint", "WLOG"). Match voice.
+
+*** APPLE WATCH FORMATTING (strict) ***
+- Line width: MAX 25-30 chars. Force breaks often.
+- Math: `$$...$$` display, `$...$` inline, standard LaTeX.
+"""
+
+CODING_SYSTEM = """
+You help solve programming, algorithms (Python), and systems (Linux/C/OS)
+ exam problems.
+Output is consumed on Apple Watch but answers must be paste-ready into Moodle/code boxes
+
+*** PROTOCOL: BATCH PROCESSING ***
+
+1. **DETECT ALL** problems in image, solve sequentially.
+2. **ORDER:** follow numbering on the page.
+3. **SEPARATOR:** "---" between problems.
+4. **CONTINUATION:** new image = next page, don't repeat solved tasks.
+5. **TEXT OVERRIDE:** user types something (e.g. "fix Q3", "redo b",
+   "explain why not c") → answer that specifically. Fuzzy match typos.
+6. **NO PREAMBLE.** Start directly with **Q1**. No "I see the following...".
+
+*** CORE PRINCIPLES ***
+
+- **Read carefully.** Exam questions are full of traps:
+  off-by-one, "select ALL that apply", forbidden methods, edge cases
+  ("what if input is empty / negative / EOF?"). Slow down on the wording.
+
+- **Bold the final answer** of every problem. User scans for it on a watch.
+
+- **Match what the question actually asks for.** If it asks for "the output",
+  give the output. If it asks "which option", give the letter. If it asks
+  "explain why", explain. Don't dump everything you know.
+
+- **For MCQ / select-all:** evaluate every option explicitly, don't just pick
+  one. Mark each ✓/✗ with a one-line reason. Watch for "almost true but
+  technically wrong" distractors (wrong complexity, off-by-one in distances,
+  wrong constant in Big-O, etc.).
+
+- **For code writing:** output COMPLETE, COPY-PASTEABLE code. No "...",
+  no TODOs, no "rest is similar". Match the starter template EXACTLY:
+  same includes, function names, signatures, return types. Respect
+  constraints stated in the problem - they are graded on those.
+
+- **For traces / step-by-step execution** (sort steps, graph traversal,
+  shell command, register state, whatever): show the state at each step
+  in compact form. Don't summarize ("after 5 iterations..."), show them.
+
+- **For "what does this command/code do" questions:** mentally execute it.
+  State assumptions about environment if relevant (cwd, perms, shell, libc).
+
+- **When something is genuinely ambiguous in the problem,** state your
+  assumption in one line, then proceed. Don't ask back - exam mode.
+
+*** APPLE WATCH FORMATTING ***
+
+- **Prose lines:** ~25–30 chars, force breaks often.
+- **Code blocks:** full width is fine, user scrolls.
+- **Bold** the final answer.
+- No "Hope this helps", no "Let me know if...", no recap at the end.
+- ALWAYS output code and commands inside ``` codeblocks to not trigger LaTeX rendering
+"""
+
 DEFAULT_FOLLOW_UP = (
     "Based on the conversation, suggest 3 short follow-up questions "
     "the user might want to ask. Each option should be under 50 characters."
@@ -124,4 +218,6 @@ PRESETS: dict[str, tuple[str, str]] = {
     "exam": (EXAM_SYSTEM, EXAM_FOLLOW_UP),
     "ragtheory": (RAGTHEORY_SYSTEM, EXAM_FOLLOW_UP),
     "proofs": (PROOFS_SYSTEM, EXAM_FOLLOW_UP),
+    "reference": (REFERENCE_SYSTEM, EXAM_FOLLOW_UP),
+    "code": (CODING_SYSTEM, EXAM_FOLLOW_UP),
 }

backend/src/bot/sync.py

@@ -5,6 +5,7 @@ import time
 from aiogram import Bot
 
 from bot.handlers.message.handler import process_message_from_web
+from bot.user_lock import get_user_lock
 from utils import env
 from utils.collaborative import (
     CollaborativeClient,
@@ -53,6 +54,7 @@ async def start_sync_listener(bot: Bot) -> None:
 
 async def handle_pending_generation(bot: Bot, item: dict, item_id: str) -> None:
     try:
+        async with get_user_lock(item["userId"]):
             await process_message_from_web(
                 convex_user_id=item["userId"],
                 text=item["userMessage"],
@@ -60,6 +62,7 @@ async def handle_pending_generation(bot: Bot, item: dict, item_id: str) -> None:
                 convex_chat_id=item["chatId"],
                 images_base64=item.get("imagesBase64"),
                 images_media_types=item.get("imagesMediaTypes"),
+                pending_generation_id=item_id,
             )
     except Exception as e:  # noqa: BLE001
         logger.error(f"Error processing {item_id}: {e}")

backend/src/bot/user_lock.py

@@ -0,0 +1,11 @@
+import asyncio
+
+_locks: dict[str, asyncio.Lock] = {}
+
+
+def get_user_lock(convex_user_id: str) -> asyncio.Lock:
+    lock = _locks.get(convex_user_id)
+    if lock is None:
+        lock = asyncio.Lock()
+        _locks[convex_user_id] = lock
+    return lock

backend/src/utils/env.py

@@ -36,6 +36,13 @@ class Settings(BaseSettings):
     log: LogSettings
     collaborative: CollaborativeSettings
 
+    anthropic_api_key: SecretStr = Field(
+        default=SecretStr(""), validation_alias=AliasChoices("ANTHROPIC_API_KEY")
+    )
+    anthropic_model: str = Field(
+        default="claude-sonnet-4-5", validation_alias=AliasChoices("ANTHROPIC_MODEL")
+    )
+
     convex_url: str = Field(validation_alias=AliasChoices("CONVEX_SELF_HOSTED_URL"))
     convex_http_url: str = Field(
         default="", validation_alias=AliasChoices("CONVEX_HTTP_URL")

backend/uv.lock

@@ -126,6 +126,25 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
+[[package]]
+name = "anthropic"
+version = "0.105.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "docstring-parser" },
+    { name = "httpx" },
+    { name = "jiter" },
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+    { url = "https://files.pythonhosted.org/packages/93/59/984fd9ece895953dad3e0880a650e766f5a2da2c5514f0eafdaaabbeb5f9/jiter-0.15.0-cp314-cp314t-win_amd64.whl", hash = "sha256:980c256edb05b78a111b99c4de3b1d32e31634b867fd1fc2cf726e7b7bba9854", size = 200055, upload-time = "2026-05-19T10:09:11.367Z" },
+    { url = "https://files.pythonhosted.org/packages/0e/a4/cf8d779feb133a27a2e3bc833bccb9e13aa332cdf820497ebf72c10ce8c3/jiter-0.15.0-cp314-cp314t-win_arm64.whl", hash = "sha256:66b1880df2d01e206e8339769d1c7c1753bcb653efd6289e203f6f24ebada0c0", size = 191244, upload-time = "2026-05-19T10:09:12.74Z" },
+]
+
 [[package]]
 name = "logfire-api"
 version = "4.19.0"
@@ -690,6 +860,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/47/8d/d529b5d697919ba8c11ad626e835d4039be708a35b0d22de83a269a6682c/pyasn1_modules-0.4.2-py3-none-any.whl", hash = "sha256:29253a9207ce32b64c3ac6600edc75368f98473906e8fd1043bd6b5b1de2c14a", size = 181259, upload-time = "2025-03-28T02:41:19.028Z" },
 ]
 
+[[package]]
+name = "pycparser"
+version = "3.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/1b/7d/92392ff7815c21062bea51aa7b87d45576f649f16458d78b7cf94b9ab2e6/pycparser-3.0.tar.gz", hash = "sha256:600f49d217304a5902ac3c37e1281c9fe94e4d0489de643a9504c5cdfdfc6b29", size = 103492, upload-time = "2026-01-21T14:26:51.89Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl", hash = "sha256:b727414169a36b7d524c1c3e31839a521725078d7b2ff038656844266160a992", size = 48172, upload-time = "2026-01-21T14:26:50.693Z" },
+]
+
 [[package]]
 name = "pydantic"
 version = "2.12.5"
@@ -707,23 +886,26 @@ wheels = [
 
 [[package]]
 name = "pydantic-ai-slim"
-version = "1.44.0"
+version = "1.89.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "genai-prices" },
-    { name = "griffe" },
+    { name = "griffelib" },
     { name = "httpx" },
     { name = "opentelemetry-api" },
     { name = "pydantic" },
     { name = "pydantic-graph" },
     { name = "typing-inspection" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/24/73/122aafb9bcad78042e2799649db745c357fc594e112c0ad0d8d183fdc447/pydantic_ai_slim-1.44.0.tar.gz", hash = "sha256:1bda6dbec4b94d8e52e32eb1e4c1da14f4f0202414306c65e2c3b43bebd82407", size = 378362, upload-time = "2026-01-17T01:26:09.64Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/23/91/b2134056eb5debb7cb28e4efe7ca19fc5c7b2935e55b299a30ddad0d7746/pydantic_ai_slim-1.89.1.tar.gz", hash = "sha256:3ed967bff8dec992a907c1d1dabab2034a5f4aee75289de22e88b2ef9def8da6", size = 614728, upload-time = "2026-05-01T19:09:38.551Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/1a/18/2f68a9718843a95c0b4724ab3821ef8f60f7b8ef50e70b3769db3259da81/pydantic_ai_slim-1.44.0-py3-none-any.whl", hash = "sha256:3bf412f43d3ae787350d671f873706ad74603777e04f42411c8fbdf7dced8031", size = 496441, upload-time = "2026-01-17T01:26:00.184Z" },
+    { url = "https://files.pythonhosted.org/packages/95/14/d0f7c8f828c460a517531e0df7cfe9e20f4315da8357a9068caaf0193bbb/pydantic_ai_slim-1.89.1-py3-none-any.whl", hash = "sha256:9e7d615a0a3e48993d067901e596e85708e9c8d1f6bef96c20c340385028d465", size = 780314, upload-time = "2026-05-01T19:09:28.843Z" },
 ]
 
 [package.optional-dependencies]
+anthropic = [
+    { name = "anthropic" },
+]
 google = [
     { name = "google-genai" },
 ]
@@ -783,7 +965,7 @@ wheels = [
 
 [[package]]
 name = "pydantic-graph"
-version = "1.44.0"
+version = "1.89.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "httpx" },
@@ -791,9 +973,9 @@ dependencies = [
     { name = "pydantic" },
     { name = "typing-inspection" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/aa/d9/83f1921633634cb1fd5947ebdc48a992cd1e660d9d0ba10f23450af654b8/pydantic_graph-1.44.0.tar.gz", hash = "sha256:81bb14bb47d3313fd7114f3ae9650dab77729451659e0247d298e1800f997c23", size = 58454, upload-time = "2026-01-17T01:26:12.113Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ea/64/f26c4d17568ab06ae576af0771ad83753cc2661bf9ca5a5698d01404ee20/pydantic_graph-1.89.1.tar.gz", hash = "sha256:99b8ae10fd10400208ee469355969e2dc253a600c3f667a5e790874064846e85", size = 59257, upload-time = "2026-05-01T19:09:40.998Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6f/e6/f9ed700171435309e214cf19012cf3b391d10ec28786d4a567ee315b1acd/pydantic_graph-1.44.0-py3-none-any.whl", hash = "sha256:5affbfe5779f79946de2c6a6524b98e2344982a129b2a1e19d031e76a5bc1e51", size = 72324, upload-time = "2026-01-17T01:26:04.119Z" },
+    { url = "https://files.pythonhosted.org/packages/7e/52/9070e11f52424fe34e2ca96ae122902cab7c4325e2a90b33d44a410843b1/pydantic_graph-1.89.1-py3-none-any.whl", hash = "sha256:2ebce28573e81de9924c2ff68f90f949ccd96bbc2e8dc6cf4bb96208b34fbec0", size = 73065, upload-time = "2026-05-01T19:09:32.912Z" },
 ]
 
 [[package]]
@@ -856,18 +1038,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/25/7a/b0178788f8dc6cafce37a212c99565fa1fe7872c70c6c9c1e1a372d9d88f/rich-14.2.0-py3-none-any.whl", hash = "sha256:76bc51fe2e57d2b1be1f96c524b890b816e334ab4c1e45888799bfaab0021edd", size = 243393, upload-time = "2025-10-09T14:16:51.245Z" },
 ]
 
-[[package]]
-name = "rsa"
-version = "4.9.1"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "pyasn1" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/da/8a/22b7beea3ee0d44b1916c0c1cb0ee3af23b700b6da9f04991899d0c555d4/rsa-4.9.1.tar.gz", hash = "sha256:e7bdbfdb5497da4c07dfd35530e1a902659db6ff241e39d9953cad06ebd0ae75", size = 29034, upload-time = "2025-04-16T09:51:18.218Z" }
-wheels = [
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-]
-
 [[package]]
 name = "sniffio"
 version = "1.3.1"

frontend/src/lib/components/ChatInput.svelte

@@ -1,11 +1,12 @@
 <script lang="ts">
 	interface Props {
 		onsubmit: (message: string) => void;
+		onpasteimage?: (base64: string, mediaType: string) => void;
 		disabled?: boolean;
 		allowEmpty?: boolean;
 	}
 
-	let { onsubmit, disabled = false, allowEmpty = false }: Props = $props();
+	let { onsubmit, onpasteimage, disabled = false, allowEmpty = false }: Props = $props();
 	let value = $state('');
 
 	function handleSubmit(e: Event) {
@@ -16,6 +17,46 @@
 			value = '';
 		}
 	}
+
+	async function fileToCompressedBase64(
+		file: File
+	): Promise<{ base64: string; mediaType: string }> {
+		const bitmap = await createImageBitmap(file);
+		const maxSize = 1920;
+		const scale = Math.min(maxSize / bitmap.width, maxSize / bitmap.height, 1);
+		const canvas = document.createElement('canvas');
+		canvas.width = Math.round(bitmap.width * scale);
+		canvas.height = Math.round(bitmap.height * scale);
+		const ctx = canvas.getContext('2d');
+		if (!ctx) throw new Error('canvas 2d context unavailable');
+		ctx.drawImage(bitmap, 0, 0, canvas.width, canvas.height);
+		bitmap.close();
+		const base64 = canvas.toDataURL('image/jpeg', 0.65).split(',')[1];
+		return { base64, mediaType: 'image/jpeg' };
+	}
+
+	async function handlePaste(e: ClipboardEvent) {
+		if (!onpasteimage || disabled) return;
+		const items = e.clipboardData?.items;
+		if (!items) return;
+		const imageFiles: File[] = [];
+		for (const item of items) {
+			if (item.kind === 'file' && item.type.startsWith('image/')) {
+				const f = item.getAsFile();
+				if (f) imageFiles.push(f);
+			}
+		}
+		if (imageFiles.length === 0) return;
+		e.preventDefault();
+		for (const file of imageFiles) {
+			try {
+				const { base64, mediaType } = await fileToCompressedBase64(file);
+				onpasteimage(base64, mediaType);
+			} catch {
+				// ignore unreadable image
+			}
+		}
+	}
 </script>
 
 <form onsubmit={handleSubmit} class="flex gap-1">
@@ -23,6 +64,7 @@
 		type="text"
 		bind:value
 		{disabled}
+		onpaste={handlePaste}
 		placeholder="..."
 		class="min-w-0 flex-1 rounded bg-neutral-800 px-2 py-1 text-[10px] text-white placeholder-neutral-500 outline-none"
 	/>

frontend/src/lib/components/PendingMessageBubble.svelte

@@ -0,0 +1,48 @@
+<script lang="ts">
+	import { processContent } from '$lib/utils/markdown';
+
+	interface Props {
+		content: string;
+		images?: string[];
+		mediaTypes?: string[];
+	}
+
+	let { content, images = [], mediaTypes = [] }: Props = $props();
+</script>
+
+<div
+	class="prose-mini w-full rounded-lg bg-blue-600 px-2.5 py-1.5 text-[11px] leading-relaxed text-white opacity-60"
+>
+	{#if images.length > 0}
+		<div class="mb-1 flex flex-wrap gap-1">
+			{#each images as img, i (i)}
+				<img
+					src={`data:${mediaTypes[i] ?? 'image/jpeg'};base64,${img}`}
+					alt=""
+					class="max-h-16 rounded"
+				/>
+			{/each}
+		</div>
+	{/if}
+	{#if content}
+		<!-- eslint-disable-next-line svelte/no-at-html-tags -->
+		<div>{@html processContent(content)}</div>
+	{/if}
+	<div class="mt-1 flex items-center gap-1 text-[8px] text-blue-100/80">
+		<svg
+			xmlns="http://www.w3.org/2000/svg"
+			class="h-2.5 w-2.5 animate-spin"
+			fill="none"
+			viewBox="0 0 24 24"
+		>
+			<circle cx="12" cy="12" r="10" stroke="currentColor" stroke-width="3" opacity="0.3" />
+			<path
+				d="M12 2a10 10 0 0 1 10 10"
+				stroke="currentColor"
+				stroke-width="3"
+				stroke-linecap="round"
+			/>
+		</svg>
+		<span>в очереди</span>
+	</div>
+</div>

frontend/src/lib/convex/messages.ts

@@ -52,8 +52,48 @@ export const create = mutation({
 		followUpOptions: v.optional(v.array(v.string())),
 		isStreaming: v.optional(v.boolean())
 	},
-	returns: v.id('messages'),
+	returns: v.union(v.id('messages'), v.null()),
 	handler: async (ctx, args) => {
+		const drafts: Array<{ base64: string; mediaType: string; id: Id<'photoDrafts'> }> = [];
+		if (args.photoDraftIds && args.photoDraftIds.length > 0) {
+			for (const draftId of args.photoDraftIds) {
+				const draft = await ctx.db.get(draftId);
+				if (draft) {
+					drafts.push({ base64: draft.base64, mediaType: draft.mediaType, id: draft._id });
+				}
+			}
+		}
+
+		if (args.source === 'web' && args.role === 'user') {
+			const chat = await ctx.db.get(args.chatId);
+			if (chat) {
+				const pendingGenId = await ctx.db.insert('pendingGenerations', {
+					userId: chat.userId,
+					chatId: args.chatId,
+					userMessage: args.content,
+					imagesBase64: drafts.length > 0 ? drafts.map((d) => d.base64) : args.imagesBase64,
+					imagesMediaTypes:
+						drafts.length > 0 ? drafts.map((d) => d.mediaType) : args.imagesMediaTypes,
+					createdAt: Date.now()
+				});
+
+				for (let i = 0; i < drafts.length; i++) {
+					await ctx.db.insert('pendingGenerationImages', {
+						pendingGenerationId: pendingGenId,
+						base64: drafts[i].base64,
+						mediaType: drafts[i].mediaType,
+						order: i
+					});
+				}
+			}
+
+			for (const draft of drafts) {
+				await ctx.db.delete(draft.id);
+			}
+
+			return null;
+		}
+
 		const messageId = await ctx.db.insert('messages', {
 			chatId: args.chatId,
 			role: args.role,
@@ -68,16 +108,6 @@ export const create = mutation({
 			isStreaming: args.isStreaming
 		});
 
-		const drafts: Array<{ base64: string; mediaType: string; id: Id<'photoDrafts'> }> = [];
-		if (args.photoDraftIds && args.photoDraftIds.length > 0) {
-			for (const draftId of args.photoDraftIds) {
-				const draft = await ctx.db.get(draftId);
-				if (draft) {
-					drafts.push({ base64: draft.base64, mediaType: draft.mediaType, id: draft._id });
-				}
-			}
-		}
-
 		for (let i = 0; i < drafts.length; i++) {
 			await ctx.db.insert('messageImages', {
 				messageId,
@@ -87,27 +117,6 @@ export const create = mutation({
 			});
 		}
 
-		if (args.source === 'web' && args.role === 'user') {
-			const chat = await ctx.db.get(args.chatId);
-			if (chat) {
-				const pendingGenId = await ctx.db.insert('pendingGenerations', {
-					userId: chat.userId,
-					chatId: args.chatId,
-					userMessage: args.content,
-					createdAt: Date.now()
-				});
-
-				for (let i = 0; i < drafts.length; i++) {
-					await ctx.db.insert('pendingGenerationImages', {
-						pendingGenerationId: pendingGenId,
-						base64: drafts[i].base64,
-						mediaType: drafts[i].mediaType,
-						order: i
-					});
-				}
-			}
-		}
-
 		for (const draft of drafts) {
 			await ctx.db.delete(draft.id);
 		}
@@ -116,6 +125,31 @@ export const create = mutation({
 	}
 });
 
+export const createFromBackend = mutation({
+	args: {
+		chatId: v.id('chats'),
+		role: v.union(v.literal('user'), v.literal('assistant')),
+		content: v.string(),
+		source: v.union(v.literal('telegram'), v.literal('web')),
+		imagesBase64: v.optional(v.array(v.string())),
+		imagesMediaTypes: v.optional(v.array(v.string())),
+		isStreaming: v.optional(v.boolean())
+	},
+	returns: v.id('messages'),
+	handler: async (ctx, args) => {
+		return await ctx.db.insert('messages', {
+			chatId: args.chatId,
+			role: args.role,
+			content: args.content,
+			source: args.source,
+			imagesBase64: args.imagesBase64,
+			imagesMediaTypes: args.imagesMediaTypes,
+			createdAt: Date.now(),
+			isStreaming: args.isStreaming
+		});
+	}
+});
+
 export const update = mutation({
 	args: {
 		messageId: v.id('messages'),

frontend/src/lib/convex/pendingGenerations.ts

@@ -40,6 +40,50 @@ export const list = query({
 	}
 });
 
+export const listByChat = query({
+	args: { chatId: v.id('chats') },
+	returns: v.array(
+		v.object({
+			_id: v.id('pendingGenerations'),
+			_creationTime: v.number(),
+			userMessage: v.string(),
+			imagesBase64: v.optional(v.array(v.string())),
+			imagesMediaTypes: v.optional(v.array(v.string())),
+			createdAt: v.number()
+		})
+	),
+	handler: async (ctx, args) => {
+		const pending = await ctx.db
+			.query('pendingGenerations')
+			.withIndex('by_chat_id', (q) => q.eq('chatId', args.chatId))
+			.order('asc')
+			.collect();
+
+		const result = [];
+		for (const p of pending) {
+			const images = await ctx.db
+				.query('pendingGenerationImages')
+				.withIndex('by_pending_generation_id', (q) => q.eq('pendingGenerationId', p._id))
+				.collect();
+
+			const sortedImages = images.sort((a, b) => a.order - b.order);
+
+			result.push({
+				_id: p._id,
+				_creationTime: p._creationTime,
+				userMessage: p.userMessage,
+				imagesBase64:
+					sortedImages.length > 0 ? sortedImages.map((img) => img.base64) : p.imagesBase64,
+				imagesMediaTypes:
+					sortedImages.length > 0 ? sortedImages.map((img) => img.mediaType) : p.imagesMediaTypes,
+				createdAt: p.createdAt
+			});
+		}
+
+		return result;
+	}
+});
+
 export const create = mutation({
 	args: {
 		userId: v.id('users'),
@@ -61,6 +105,10 @@ export const remove = mutation({
 	args: { id: v.id('pendingGenerations') },
 	returns: v.null(),
 	handler: async (ctx, args) => {
+		const existing = await ctx.db.get(args.id);
+		if (!existing) {
+			return null;
+		}
 		const images = await ctx.db
 			.query('pendingGenerationImages')
 			.withIndex('by_pending_generation_id', (q) => q.eq('pendingGenerationId', args.id))

frontend/src/lib/convex/schema.ts

@@ -65,7 +65,7 @@ export default defineSchema({
 		imagesBase64: v.optional(v.array(v.string())),
 		imagesMediaTypes: v.optional(v.array(v.string())),
 		createdAt: v.number()
-	}),
+	}).index('by_chat_id', ['chatId']),
 
 	pendingGenerationImages: defineTable({
 		pendingGenerationId: v.id('pendingGenerations'),

frontend/src/lib/utils/markdown.ts

@@ -2,8 +2,20 @@ import { Marked } from 'marked';
 
 const marked = new Marked({ breaks: true, gfm: true });
 
+const CODE_OPEN = '';
+const CODE_CLOSE = '';
+
 export function processLatex(text: string): string {
-	return text
+	const placeholders: string[] = [];
+	const stash = (match: string) => {
+		const token = `${CODE_OPEN}${placeholders.length}${CODE_CLOSE}`;
+		placeholders.push(match);
+		return token;
+	};
+
+	const protectedText = text.replace(/```[\s\S]*?```/g, stash).replace(/`[^`\n]*`/g, stash);
+
+	const rendered = protectedText
 		.replace(/\$\$(.*?)\$\$/gs, (_, tex) => {
 			const encoded = encodeURIComponent(tex.trim());
 			return `<img src="/service/latex?tex=${encoded}&display=1" alt="LaTeX" class="block my-1 max-h-12" />`;
@@ -12,6 +24,11 @@ export function processLatex(text: string): string {
 			const encoded = encodeURIComponent(tex.trim());
 			return `<img src="/service/latex?tex=${encoded}" alt="LaTeX" class="inline-block align-middle max-h-4" />`;
 		});
+
+	return rendered.replace(
+		new RegExp(`${CODE_OPEN}(\\d+)${CODE_CLOSE}`, 'g'),
+		(_, i) => placeholders[Number(i)]
+	);
 }
 
 export function processContent(text: string): string {

frontend/src/routes/[mnemonic]/+page.svelte

@@ -12,6 +12,7 @@
 	import { api } from '$lib/convex/_generated/api';
 	import type { Id } from '$lib/convex/_generated/dataModel';
 	import ChatMessage from '$lib/components/ChatMessage.svelte';
+	import PendingMessageBubble from '$lib/components/PendingMessageBubble.svelte';
 	import ChatInput from '$lib/components/ChatInput.svelte';
 	import FollowUpButtons from '$lib/components/FollowUpButtons.svelte';
 	import StealthOverlay from '$lib/components/StealthOverlay.svelte';
@@ -117,7 +118,16 @@
 		: null;
 	const messagesQuery = $derived(usePolling ? messagesQueryPoll! : messagesQueryWs!);
 
+	const pendingQueryWs = usePolling
+		? null
+		: useQuery(api.pendingGenerations.listByChat, () => (chatId ? { chatId } : 'skip'));
+	const pendingQueryPoll = usePolling
+		? usePollingQuery(api.pendingGenerations.listByChat, () => (chatId ? { chatId } : 'skip'))
+		: null;
+	const pendingQuery = $derived(usePolling ? pendingQueryPoll! : pendingQueryWs!);
+
 	let messages = $derived(messagesQuery.data ?? []);
+	let pendingMessages = $derived(pendingQuery.data ?? []);
 	let lastMessage = $derived(messages[messages.length - 1]);
 	let followUpOptions = $derived(
 		lastMessage?.role === 'assistant' && lastMessage.followUpOptions
@@ -263,12 +273,19 @@
 
 	let prevMessageCount = 0;
 	let prevLastMessageId: string | undefined;
+	let prevPendingCount = 0;
 
 	$effect(() => {
 		const count = messages.length;
 		const lastId = lastMessage?._id;
-		if (count > prevMessageCount || (lastId && lastId !== prevLastMessageId)) {
+		const pendingCount = pendingMessages.length;
+		if (
+			count > prevMessageCount ||
+			pendingCount > prevPendingCount ||
+			(lastId && lastId !== prevLastMessageId)
+		) {
 			prevMessageCount = count;
+			prevPendingCount = pendingCount;
 			prevLastMessageId = lastId;
 			window.scrollTo(0, document.body.scrollHeight);
 		}
@@ -577,7 +594,7 @@
 	{:else}
 		<div class="space-y-1">
 			{#each messages as message, i (message._id)}
-				{#if i === messages.length - 1}
+				{#if i === messages.length - 1 && pendingMessages.length === 0}
 					<div bind:this={lastMessageElement}>
 						<ChatMessage
 							role={message.role}
@@ -593,6 +610,23 @@
 					/>
 				{/if}
 			{/each}
+			{#each pendingMessages as p, i (p._id)}
+				{#if i === pendingMessages.length - 1}
+					<div bind:this={lastMessageElement}>
+						<PendingMessageBubble
+							content={p.userMessage}
+							images={p.imagesBase64 ?? []}
+							mediaTypes={p.imagesMediaTypes ?? []}
+						/>
+					</div>
+				{:else}
+					<PendingMessageBubble
+						content={p.userMessage}
+						images={p.imagesBase64 ?? []}
+						mediaTypes={p.imagesMediaTypes ?? []}
+					/>
+				{/if}
+			{/each}
 		</div>
 
 		{#if followUpOptions.length > 0}
@@ -651,7 +685,11 @@
 					ondismiss={handleDismissSheet}
 				/>
 			{/if}
-			<ChatInput onsubmit={sendMessage} allowEmpty={draftPhotos.length > 0} />
+			<ChatInput
+				onsubmit={sendMessage}
+				onpasteimage={handleCameraCapture}
+				allowEmpty={draftPhotos.length > 0}
+			/>
 		</div>
 	{/if}