feat: add retry logic for transient failures

- @with_retry decorator and retry_async() function
- Exponential backoff with jitter
- Retries on: timeout, connection errors, HTTP 429/5xx
- Web search tool now retries on network failures
- Configurable via RETRY_MAX_ATTEMPTS, RETRY_BASE_DELAY, RETRY_MAX_DELAY
- 29 new tests (205 total passing)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

CHANGELOG.md

@@ -7,6 +7,22 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.4.2] - 2026-01-11
+
+### Added
+- Retry logic for transient failures with exponential backoff
+  - `src/shared/retry.py` - `@with_retry` decorator and `retry_async()` function
+  - Retries on: timeout, connection errors, HTTP 429/5xx
+  - Configurable: `RETRY_MAX_ATTEMPTS`, `RETRY_BASE_DELAY`, `RETRY_MAX_DELAY`
+- Web search tool now automatically retries on network failures
+- 29 retry tests (205 total tests passing)
+
+## [0.4.1] - 2026-01-11
+
+### Fixed
+- Replace `litellm` with `tiktoken` for token counting (dependency conflict with pydantic-ai)
+- Update documentation (README.md, architecture.md) with conversation layer info
+
 ## [0.4.0] - 2026-01-11
 
 ### Added
@@ -15,7 +31,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - SQLite (dev) and PostgreSQL (prod) support via async engines
   - Lazy database initialization pattern
 - Context management infrastructure
-  - Token counting utilities using `litellm`
+  - Token counting utilities using `tiktoken`
   - Context summarization at 80% token threshold
   - XML-tagged context prompt building for agent injection
 - REST API for multi-turn conversations
@@ -24,7 +40,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - `GET /conversations/{id}` - Get conversation with history
   - `POST /conversations/{id}/messages` - Add message (triggers agent)
   - `DELETE /conversations/{id}` - Delete conversation
-- New dependencies: `sqlalchemy[asyncio]~=2.0.36`, `aiosqlite~=0.21.0`, `litellm~=1.57.0`
+- New dependencies: `sqlalchemy[asyncio]~=2.0.36`, `aiosqlite~=0.21.0`, `tiktoken>=0.12.0`
 - Config settings: `database_url`, `summarization_threshold`, `keep_recent_messages`
 - 19 conversation tests, 6 token counting tests (176 total tests passing)
 

README.md

@@ -4,8 +4,9 @@ A Claude Code-inspired development assistant powered by local LLMs via Ollama.
 
 ## Features
 
-- **Explore Agent** - Search, read, and understand codebases
+- **3 Agents** - Explore (read-only), Plan (architecture), Task (orchestrator)
-- **8 Tools** - File read/write, glob, grep, bash, web search
+- **8 Tools** - File read/write/edit, glob, grep, bash, web search
+- **Conversations** - Multi-turn memory with context summarization
 - **Streaming** - Real-time response display
 - **Self-hosted** - Runs on your own hardware with Ollama
 
@@ -74,11 +75,33 @@ webber-cli chat -d /path/to/project
 | `bash` | Full bash with safety controls |
 | `web_search` | Search web via SearXNG |
 
+## Agents
+
+| Agent | Purpose | Tools |
+|-------|---------|-------|
+| **Explore** | Fast codebase navigation, search | Read-only (glob, grep, read, bash_readonly) |
+| **Plan** | Design implementation strategies | Read-only (same as Explore) |
+| **Task** | Autonomous multi-step execution | All tools + spawn_agent |
+
+## API Endpoints
+
+```bash
+# Stateless agent execution
+POST /agents/run          # Execute agent, get response
+POST /agents/stream       # Execute with SSE streaming
+GET  /agents/             # List available agents
+
+# Stateful conversations (multi-turn memory)
+POST /conversations/              # Create conversation
+GET  /conversations/              # List conversations
+POST /conversations/{id}/messages # Add message, get agent response
+```
+
 ## Versioning
 
 This project uses prefixed tags for independent release cycles:
 
-- `api/v0.3.0` - Triggers API Docker build and deployment
+- `api/v0.4.0` - Triggers API Docker build and deployment
 - `cli/v0.1.0` - Triggers CLI installer build (future)
 
 ## Requirements

webber-api/docs/COVERAGE.md

@@ -126,7 +126,7 @@ Last updated: 2026-01-11
 | **Todo tracking** | CLI | Built-in task list (`/todo`) | Medium |
 | **Git integration** | CLI | Auto-commit, branch management | Medium |
 | **Agent handoff** | Orchestration | Explore → Plan → Task workflow | High |
-| **Retry logic** | Infrastructure | Auto-retry on tool failures | Low |
+| ~~**Retry logic**~~ | Infrastructure | ✅ Auto-retry with exponential backoff | Low |
 
 ### Low Priority
 
@@ -151,11 +151,12 @@ Last updated: 2026-01-11
 | Task agent tests | 15 | 15 | ✅ |
 | Conversation tests | 19 | 19 | ✅ |
 | Token tests | 6 | 6 | ✅ |
+| Retry tests | 29 | 29 | ✅ |
 | Security tests | 14 | 14 | ✅ |
 | Integration tests | 10 | 10 | ✅ Agent + real LLM |
 | E2E tests | 12 | 12 | ✅ Full API workflow |
 
-**Total: 176 tests passing**
+**Total: 205 tests passing**
 
 **Test breakdown:**
 - Read/Glob/Grep tools: 17 tests
@@ -168,6 +169,7 @@ Last updated: 2026-01-11
 - Task agent: 15 tests
 - Conversations: 19 tests
 - Tokens: 6 tests
+- Retry: 29 tests
 - Security: 14 tests
 - Health checks: 2 tests
 - Integration (LLM): 10 tests

webber-api/docs/architecture.md

@@ -24,18 +24,30 @@ webber/
 ├── src/
 │   ├── main.py              # App entry point (NO routes)
 │   │
+│   ├── db/                  # Database layer
+│   │   ├── __init__.py      # Exports: Database, get_database, get_session
+│   │   ├── database.py      # SQLAlchemy async engine, session factory
+│   │   └── models.py        # Base declarative model
+│   │
 │   ├── shared/              # Cross-cutting concerns
 │   │   ├── base.py          # BaseController, BaseSchema
 │   │   ├── config.py        # Pydantic Settings
 │   │   ├── logging.py       # @logged decorator, trace_span
 │   │   ├── exceptions.py    # Custom exception hierarchy
 │   │   ├── auth.py          # API key validation
-│   │   └── context.py       # UserProvider singleton
+│   │   ├── context.py       # UserProvider singleton
+│   │   └── tokens.py        # Token counting utilities (litellm)
 │   │
 │   └── domains/             # Feature domains
 │       ├── router.py        # Root router (composes all)
 │       ├── health/          # Health endpoints
 │       ├── auth/            # Authentication
+│       ├── conversations/   # Multi-turn conversation memory
+│       │   ├── models.py    # Conversation, Message SQLAlchemy models
+│       │   ├── schemas.py   # Pydantic request/response models
+│       │   ├── service.py   # ConversationService business logic
+│       │   ├── router.py    # REST API endpoints
+│       │   └── summarize.py # Context summarization logic
 │       ├── agents/          # Agent orchestration
 │       │   ├── explore/     # Codebase navigation
 │       │   ├── plan/        # Implementation design
@@ -201,6 +213,13 @@ All settings via environment variables or `.env`:
 | ALLOWED_PATHS | [] | Paths accessible to tools |
 | SESSION_TTL_HOURS | 24 | Session expiry |
 | MAX_CONTEXT_TOKENS | 128000 | Max context window |
+| DATABASE_URL | sqlite+aiosqlite:///./webber.db | Database connection URL |
+| SUMMARIZATION_THRESHOLD | 0.8 | Summarize at N% of max tokens |
+| SUMMARIZATION_TARGET_TOKENS | 500 | Target summary size |
+| KEEP_RECENT_MESSAGES | 6 | Messages to keep unsummarized |
+| RETRY_MAX_ATTEMPTS | 3 | Max retry attempts for transient failures |
+| RETRY_BASE_DELAY | 1.0 | Base delay between retries (seconds) |
+| RETRY_MAX_DELAY | 30.0 | Maximum delay between retries (seconds) |
 
 ---
 
@@ -250,6 +269,53 @@ Tools are sandboxed operations agents can invoke:
 
 ---
 
+## Database Layer
+
+SQLAlchemy 2.0 async with lazy initialization pattern.
+
+### Supported Databases
+- **Development**: SQLite via `aiosqlite`
+- **Production**: PostgreSQL via `asyncpg`
+
+### Pattern
+```python
+from src.db import get_session
+from sqlalchemy.ext.asyncio import AsyncSession
+
+async def my_endpoint(session: AsyncSession = Depends(get_session)):
+    # Session auto-commits on success, rollbacks on exception
+    result = await session.execute(query)
+```
+
+Tables are created lazily on first `get_session()` call.
+
+---
+
+## Conversation API
+
+Multi-turn conversation memory with automatic context summarization.
+
+### Endpoints
+| Endpoint | Method | Description |
+|----------|--------|-------------|
+| `/conversations/` | POST | Create new conversation |
+| `/conversations/` | GET | List user's conversations |
+| `/conversations/{id}` | GET | Get conversation with history |
+| `/conversations/{id}/messages` | POST | Add message, triggers agent |
+| `/conversations/{id}` | DELETE | Delete conversation |
+
+### Models
+- **Conversation**: User session with agent type, working directory
+- **Message**: Individual messages with role, content, token count
+
+### Context Summarization
+When total tokens exceed 80% of `MAX_CONTEXT_TOKENS`:
+1. Keep last 6 messages intact
+2. Summarize older messages into a single summary message
+3. Mark old messages as summarized (soft delete)
+
+---
+
 ## Authentication Flow
 
 1. Client sends `X-API-Key` header

webber-api/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "webber-api"
-version = "0.4.0"
+version = "0.4.2"
 description = "Webber API - Multi-Agent AI Development Server"
 authors = [
     {name = "jpmschweitzer"}

webber-api/requirements.txt

@@ -31,4 +31,4 @@ sqlalchemy[asyncio]~=2.0.36
 aiosqlite~=0.21.0                      # SQLite async driver (dev)
 
 # Token counting
-litellm~=1.57.0                        # Multi-model token counting
+tiktoken>=0.12.0                       # OpenAI tokenizer (used for estimation)

webber-api/src/domains/tools/search/web.py

@@ -9,6 +9,7 @@ import httpx
 from src.domains.tools.base import BaseTool, ToolResult
 from src.shared.config import get_settings
 from src.shared.logging import logged, get_logger
+from src.shared.retry import retry_async
 
 logger = get_logger(__name__)
 
@@ -73,6 +74,24 @@ IMPORTANT:
         self.searxng_url = (searxng_url or settings.searxng_url).rstrip("/")
         self.timeout = timeout or settings.searxng_timeout
         self.max_results = max_results
+        # Retry settings
+        self.retry_max_attempts = settings.retry_max_attempts
+        self.retry_base_delay = settings.retry_base_delay
+        self.retry_max_delay = settings.retry_max_delay
+
+    async def _fetch_search_results(self, params: dict) -> dict:
+        """
+        Fetch search results from SearXNG.
+
+        This method is wrapped with retry logic for transient failures.
+        """
+        async with httpx.AsyncClient(timeout=self.timeout) as client:
+            response = await client.get(
+                f"{self.searxng_url}/search",
+                params=params,
+            )
+            response.raise_for_status()
+            return response.json()
 
     @logged()
     async def execute(
@@ -111,16 +130,15 @@ IMPORTANT:
             params["categories"] = categories
 
         try:
-            async with httpx.AsyncClient(timeout=self.timeout) as client:
+            data = await retry_async(
-                response = await client.get(
+                self._fetch_search_results,
-                    f"{self.searxng_url}/search",
+                params,
-                    params=params,
+                max_attempts=self.retry_max_attempts,
+                base_delay=self.retry_base_delay,
+                max_delay=self.retry_max_delay,
             )
-                response.raise_for_status()
-                data = response.json()
-
         except httpx.TimeoutException:
-            return self._error(f"Search timed out after {self.timeout}s")
+            return self._error(f"Search timed out after {self.timeout}s (all retries exhausted)")
         except httpx.HTTPStatusError as e:
             return self._error(f"Search failed: HTTP {e.response.status_code}")
         except httpx.RequestError as e:

webber-api/src/shared/config.py

@@ -90,6 +90,11 @@ class Settings(BaseSettings):
     summarization_target_tokens: int = 500  # Target summary size
     keep_recent_messages: int = 6  # Messages to keep unsummarized (3 turns)
 
+    # Retry logic
+    retry_max_attempts: int = 3  # Max retry attempts for transient failures
+    retry_base_delay: float = 1.0  # Base delay in seconds
+    retry_max_delay: float = 30.0  # Maximum delay in seconds
+
     model_config = SettingsConfigDict(
         env_file=".env",
         case_sensitive=False,

webber-api/src/shared/retry.py

@@ -0,0 +1,215 @@
+"""
+Retry utilities for handling transient failures.
+
+Provides decorators and helpers for automatic retry with exponential backoff.
+"""
+import asyncio
+import random
+from collections.abc import Awaitable, Callable
+from functools import wraps
+from typing import Any, TypeVar
+
+import httpx
+
+from src.shared.logging import get_logger
+
+logger = get_logger(__name__)
+
+T = TypeVar("T")
+
+
+# Exceptions that should trigger a retry
+RETRYABLE_EXCEPTIONS = (
+    httpx.TimeoutException,
+    httpx.ConnectError,
+    httpx.ReadError,
+    httpx.WriteError,
+    httpx.ConnectTimeout,
+    httpx.ReadTimeout,
+    httpx.WriteTimeout,
+    httpx.PoolTimeout,
+    ConnectionError,
+    TimeoutError,
+    OSError,  # Covers many network-related errors
+)
+
+
+def is_retryable_http_status(status_code: int) -> bool:
+    """
+    Check if an HTTP status code should trigger a retry.
+
+    Retryable:
+    - 429 Too Many Requests (rate limited)
+    - 500 Internal Server Error
+    - 502 Bad Gateway
+    - 503 Service Unavailable
+    - 504 Gateway Timeout
+    """
+    return status_code in (429, 500, 502, 503, 504)
+
+
+def is_retryable_exception(exc: Exception) -> bool:
+    """Check if an exception should trigger a retry."""
+    if isinstance(exc, RETRYABLE_EXCEPTIONS):
+        return True
+
+    # Check for retryable HTTP status codes
+    if isinstance(exc, httpx.HTTPStatusError):
+        return is_retryable_http_status(exc.response.status_code)
+
+    return False
+
+
+def calculate_backoff(
+    attempt: int,
+    base_delay: float = 1.0,
+    max_delay: float = 60.0,
+    jitter: bool = True,
+) -> float:
+    """
+    Calculate exponential backoff delay with optional jitter.
+
+    Args:
+        attempt: Current attempt number (0-indexed)
+        base_delay: Base delay in seconds
+        max_delay: Maximum delay in seconds
+        jitter: Add random jitter to prevent thundering herd
+
+    Returns:
+        Delay in seconds
+    """
+    # Exponential backoff: base_delay * 2^attempt
+    delay = min(base_delay * (2 ** attempt), max_delay)
+
+    if jitter:
+        # Add up to 25% random jitter
+        delay = delay * (0.75 + random.random() * 0.5)
+
+    return delay
+
+
+def with_retry(
+    max_attempts: int = 3,
+    base_delay: float = 1.0,
+    max_delay: float = 60.0,
+    retryable_exceptions: tuple[type[Exception], ...] | None = None,
+) -> Callable[[Callable[..., Awaitable[T]]], Callable[..., Awaitable[T]]]:
+    """
+    Decorator for async functions that should retry on transient failures.
+
+    Args:
+        max_attempts: Maximum number of attempts (including initial)
+        base_delay: Base delay between retries in seconds
+        max_delay: Maximum delay between retries in seconds
+        retryable_exceptions: Additional exceptions to retry on
+
+    Returns:
+        Decorated function with retry logic
+
+    Example:
+        @with_retry(max_attempts=3, base_delay=1.0)
+        async def fetch_data():
+            async with httpx.AsyncClient() as client:
+                response = await client.get(url)
+                return response.json()
+    """
+    extra_exceptions = retryable_exceptions or ()
+
+    def decorator(func: Callable[..., Awaitable[T]]) -> Callable[..., Awaitable[T]]:
+        @wraps(func)
+        async def wrapper(*args: Any, **kwargs: Any) -> T:
+            last_exception: Exception | None = None
+
+            for attempt in range(max_attempts):
+                try:
+                    return await func(*args, **kwargs)
+
+                except (*RETRYABLE_EXCEPTIONS, *extra_exceptions) as e:
+                    last_exception = e
+                    should_retry = True
+
+                except httpx.HTTPStatusError as e:
+                    last_exception = e
+                    should_retry = is_retryable_http_status(e.response.status_code)
+
+                except Exception:
+                    # Non-retryable exception, re-raise immediately
+                    raise
+
+                if should_retry and attempt < max_attempts - 1:
+                    delay = calculate_backoff(attempt, base_delay, max_delay)
+                    logger.warning(
+                        f"Retry {attempt + 1}/{max_attempts - 1} for {func.__name__} "
+                        f"after {delay:.2f}s due to: {last_exception}"
+                    )
+                    await asyncio.sleep(delay)
+                elif not should_retry:
+                    # Non-retryable HTTP error
+                    raise last_exception  # type: ignore
+
+            # All retries exhausted
+            logger.error(
+                f"All {max_attempts} attempts failed for {func.__name__}: {last_exception}"
+            )
+            raise last_exception  # type: ignore
+
+        return wrapper
+    return decorator
+
+
+async def retry_async(
+    func: Callable[..., Awaitable[T]],
+    *args: Any,
+    max_attempts: int = 3,
+    base_delay: float = 1.0,
+    max_delay: float = 60.0,
+    **kwargs: Any,
+) -> T:
+    """
+    Retry an async function with exponential backoff.
+
+    Alternative to decorator when you need per-call control.
+
+    Args:
+        func: Async function to call
+        *args: Positional arguments for func
+        max_attempts: Maximum number of attempts
+        base_delay: Base delay between retries
+        max_delay: Maximum delay between retries
+        **kwargs: Keyword arguments for func
+
+    Returns:
+        Result of func
+
+    Raises:
+        Last exception if all retries fail
+
+    Example:
+        result = await retry_async(
+            fetch_data,
+            url,
+            max_attempts=5,
+            timeout=30,
+        )
+    """
+    last_exception: Exception | None = None
+
+    for attempt in range(max_attempts):
+        try:
+            return await func(*args, **kwargs)
+
+        except Exception as e:
+            last_exception = e
+
+            if not is_retryable_exception(e):
+                raise
+
+            if attempt < max_attempts - 1:
+                delay = calculate_backoff(attempt, base_delay, max_delay)
+                logger.warning(
+                    f"Retry {attempt + 1}/{max_attempts - 1} "
+                    f"after {delay:.2f}s due to: {e}"
+                )
+                await asyncio.sleep(delay)
+
+    raise last_exception  # type: ignore

webber-api/src/shared/tokens.py

@@ -1,53 +1,64 @@
 """
 Token counting utilities for context management.
 
-Uses litellm for accurate multi-model token counting.
+Uses tiktoken for token counting. While tiktoken is OpenAI's tokenizer,
+cl100k_base encoding provides reasonable estimates for most LLMs.
 """
+from functools import lru_cache
+
 from src.shared.logging import get_logger
 
 logger = get_logger(__name__)
 
-# Default model for token counting (Mistral Nemo)
+
-DEFAULT_MODEL = "mistral/mistral-nemo"
+@lru_cache(maxsize=1)
+def _get_encoding():
+    """Get tiktoken encoding (cached)."""
+    import tiktoken
+    # cl100k_base is used by GPT-4 and provides reasonable estimates for most models
+    return tiktoken.get_encoding("cl100k_base")
 
 
-def count_tokens(text: str, model: str = DEFAULT_MODEL) -> int:
+def count_tokens(text: str) -> int:
     """
     Count tokens in a text string.
 
     Args:
         text: Text to count tokens for
-        model: Model identifier for tokenizer selection
 
     Returns:
         Token count
     """
     try:
-        from litellm import token_counter
+        encoding = _get_encoding()
-        return token_counter(model=model, text=text)
+        return len(encoding.encode(text))
     except Exception as e:
-        # Fallback to rough estimate if litellm fails
+        # Fallback to rough estimate if tiktoken fails
         logger.warning(f"Token counting failed, using estimate: {e}")
         return len(text) // 4
 
 
-def count_message_tokens(
+def count_message_tokens(messages: list[dict[str, str]]) -> int:
-    messages: list[dict[str, str]],
-    model: str = DEFAULT_MODEL
-) -> int:
     """
     Count tokens for a list of chat messages.
 
     Args:
         messages: List of message dicts with 'role' and 'content' keys
-        model: Model identifier for tokenizer selection
 
     Returns:
         Total token count including message overhead
     """
     try:
-        from litellm import token_counter
+        encoding = _get_encoding()
-        return token_counter(model=model, messages=messages)
+        total = 0
+        for msg in messages:
+            # Each message has ~4 tokens overhead for role/formatting
+            total += 4
+            total += len(encoding.encode(msg.get("content", "")))
+            total += len(encoding.encode(msg.get("role", "")))
+        # Add 2 tokens for assistant response priming
+        total += 2
+        return total
     except Exception as e:
         # Fallback to rough estimate
         logger.warning(f"Token counting failed, using estimate: {e}")

webber-api/tests/test_retry.py

@@ -0,0 +1,244 @@
+"""
+Tests for retry utilities.
+"""
+import pytest
+from unittest.mock import AsyncMock, patch
+
+import httpx
+
+from src.shared.retry import (
+    with_retry,
+    retry_async,
+    is_retryable_exception,
+    is_retryable_http_status,
+    calculate_backoff,
+)
+
+
+class TestIsRetryableHttpStatus:
+    """Tests for HTTP status code checking."""
+
+    def test_429_is_retryable(self):
+        """429 Too Many Requests should be retryable."""
+        assert is_retryable_http_status(429) is True
+
+    def test_500_is_retryable(self):
+        """500 Internal Server Error should be retryable."""
+        assert is_retryable_http_status(500) is True
+
+    def test_502_is_retryable(self):
+        """502 Bad Gateway should be retryable."""
+        assert is_retryable_http_status(502) is True
+
+    def test_503_is_retryable(self):
+        """503 Service Unavailable should be retryable."""
+        assert is_retryable_http_status(503) is True
+
+    def test_504_is_retryable(self):
+        """504 Gateway Timeout should be retryable."""
+        assert is_retryable_http_status(504) is True
+
+    def test_400_not_retryable(self):
+        """400 Bad Request should not be retryable."""
+        assert is_retryable_http_status(400) is False
+
+    def test_401_not_retryable(self):
+        """401 Unauthorized should not be retryable."""
+        assert is_retryable_http_status(401) is False
+
+    def test_404_not_retryable(self):
+        """404 Not Found should not be retryable."""
+        assert is_retryable_http_status(404) is False
+
+    def test_200_not_retryable(self):
+        """200 OK should not be retryable."""
+        assert is_retryable_http_status(200) is False
+
+
+class TestIsRetryableException:
+    """Tests for exception checking."""
+
+    def test_timeout_exception_is_retryable(self):
+        """Timeout exceptions should be retryable."""
+        exc = httpx.TimeoutException("timeout")
+        assert is_retryable_exception(exc) is True
+
+    def test_connect_error_is_retryable(self):
+        """Connection errors should be retryable."""
+        exc = httpx.ConnectError("connection failed")
+        assert is_retryable_exception(exc) is True
+
+    def test_connection_error_is_retryable(self):
+        """Python ConnectionError should be retryable."""
+        exc = ConnectionError("connection refused")
+        assert is_retryable_exception(exc) is True
+
+    def test_timeout_error_is_retryable(self):
+        """Python TimeoutError should be retryable."""
+        exc = TimeoutError("timed out")
+        assert is_retryable_exception(exc) is True
+
+    def test_value_error_not_retryable(self):
+        """ValueError should not be retryable."""
+        exc = ValueError("invalid value")
+        assert is_retryable_exception(exc) is False
+
+    def test_key_error_not_retryable(self):
+        """KeyError should not be retryable."""
+        exc = KeyError("missing key")
+        assert is_retryable_exception(exc) is False
+
+
+class TestCalculateBackoff:
+    """Tests for backoff calculation."""
+
+    def test_first_attempt_base_delay(self):
+        """First attempt should use base delay."""
+        delay = calculate_backoff(0, base_delay=1.0, jitter=False)
+        assert delay == 1.0
+
+    def test_second_attempt_doubles(self):
+        """Second attempt should double the delay."""
+        delay = calculate_backoff(1, base_delay=1.0, jitter=False)
+        assert delay == 2.0
+
+    def test_third_attempt_quadruples(self):
+        """Third attempt should quadruple the delay."""
+        delay = calculate_backoff(2, base_delay=1.0, jitter=False)
+        assert delay == 4.0
+
+    def test_max_delay_respected(self):
+        """Delay should not exceed max_delay."""
+        delay = calculate_backoff(10, base_delay=1.0, max_delay=30.0, jitter=False)
+        assert delay == 30.0
+
+    def test_jitter_adds_randomness(self):
+        """Jitter should add randomness to delay."""
+        delays = [calculate_backoff(1, base_delay=1.0, jitter=True) for _ in range(10)]
+        # With jitter, delays should vary (not all identical)
+        assert len(set(delays)) > 1
+
+    def test_jitter_within_bounds(self):
+        """Jitter should keep delay within reasonable bounds."""
+        for _ in range(100):
+            delay = calculate_backoff(0, base_delay=2.0, jitter=True)
+            # Attempt 0 with base 2.0 = 2.0, with jitter should be 0.75-1.25x = 1.5-2.5
+            assert 1.5 <= delay <= 2.5
+
+
+class TestWithRetryDecorator:
+    """Tests for the @with_retry decorator."""
+
+    @pytest.mark.anyio
+    async def test_success_on_first_attempt(self):
+        """Function should return on first successful attempt."""
+        call_count = 0
+
+        @with_retry(max_attempts=3)
+        async def successful_func():
+            nonlocal call_count
+            call_count += 1
+            return "success"
+
+        result = await successful_func()
+        assert result == "success"
+        assert call_count == 1
+
+    @pytest.mark.anyio
+    async def test_retry_on_timeout(self):
+        """Should retry on timeout exception."""
+        call_count = 0
+
+        @with_retry(max_attempts=3, base_delay=0.01)
+        async def flaky_func():
+            nonlocal call_count
+            call_count += 1
+            if call_count < 3:
+                raise httpx.TimeoutException("timeout")
+            return "success"
+
+        result = await flaky_func()
+        assert result == "success"
+        assert call_count == 3
+
+    @pytest.mark.anyio
+    async def test_no_retry_on_value_error(self):
+        """Should not retry on non-retryable exceptions."""
+        call_count = 0
+
+        @with_retry(max_attempts=3)
+        async def bad_func():
+            nonlocal call_count
+            call_count += 1
+            raise ValueError("bad value")
+
+        with pytest.raises(ValueError):
+            await bad_func()
+        assert call_count == 1
+
+    @pytest.mark.anyio
+    async def test_exhausted_retries(self):
+        """Should raise last exception after all retries exhausted."""
+        call_count = 0
+
+        @with_retry(max_attempts=3, base_delay=0.01)
+        async def always_fails():
+            nonlocal call_count
+            call_count += 1
+            raise httpx.TimeoutException("always times out")
+
+        with pytest.raises(httpx.TimeoutException):
+            await always_fails()
+        assert call_count == 3
+
+
+class TestRetryAsync:
+    """Tests for the retry_async function."""
+
+    @pytest.mark.anyio
+    async def test_success_on_first_attempt(self):
+        """Function should return on first successful attempt."""
+        async def successful_func():
+            return "success"
+
+        result = await retry_async(successful_func, max_attempts=3)
+        assert result == "success"
+
+    @pytest.mark.anyio
+    async def test_retry_on_connect_error(self):
+        """Should retry on connection errors."""
+        call_count = 0
+
+        async def flaky_func():
+            nonlocal call_count
+            call_count += 1
+            if call_count < 2:
+                raise httpx.ConnectError("connection failed")
+            return "success"
+
+        result = await retry_async(flaky_func, max_attempts=3, base_delay=0.01)
+        assert result == "success"
+        assert call_count == 2
+
+    @pytest.mark.anyio
+    async def test_passes_args_and_kwargs(self):
+        """Should pass arguments to the function."""
+        async def add(a, b, multiplier=1):
+            return (a + b) * multiplier
+
+        result = await retry_async(add, 2, 3, max_attempts=1, multiplier=2)
+        assert result == 10
+
+    @pytest.mark.anyio
+    async def test_no_retry_on_key_error(self):
+        """Should not retry on non-retryable exceptions."""
+        call_count = 0
+
+        async def bad_func():
+            nonlocal call_count
+            call_count += 1
+            raise KeyError("missing")
+
+        with pytest.raises(KeyError):
+            await retry_async(bad_func, max_attempts=3)
+        assert call_count == 1

webber-api/tests/test_tokens.py

@@ -59,7 +59,7 @@ class TestTokenCounting:
     def test_count_message_tokens_empty_list(self):
         """Test counting empty message list."""
         tokens = count_message_tokens([])
-        # litellm may return small overhead even for empty list
+        # tiktoken returns small overhead for empty list (assistant priming)
         assert tokens < 10