mirror of
https://github.com/hanzoai/python-sdk.git
synced 2026-10-23 20:23:00 +00:00
feat: Add streaming, rate limiting, and enhanced testing to hanzo dev
Major improvements: - Streaming responses with real-time feedback - Smart rate limiting with exponential backoff - Error recovery with circuit breaker pattern - Comprehensive test suite (all tests passing) - Fixed CI/CD pipeline issues - TypeWriter effect for code display - Adaptive rate limits per API provider Performance: - Prevents API overuse with smart throttling - Automatic fallback on rate limit errors - Burst protection and cooldown periods - Per-API customized limits Version bump to 0.3.21
This commit is contained in:
@@ -1,6 +1,6 @@
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[project]
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name = "hanzo"
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version = "0.3.20"
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version = "0.3.21"
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description = "Hanzo AI - Complete AI Infrastructure Platform with CLI, Router, MCP, and Agent Runtime"
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authors = [
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{name = "Hanzo AI", email = "[email protected]"},
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@@ -26,7 +26,7 @@ from .utils.output import console
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from .interactive.repl import HanzoREPL
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# Version
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__version__ = "0.3.20"
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__version__ = "0.3.21"
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@click.group(invoke_without_command=True)
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@@ -929,21 +929,14 @@ Examples:
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# Try smart fallback if no specific model configured
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if not hasattr(self.orchestrator, 'orchestrator_model') or \
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self.orchestrator.orchestrator_model == "auto":
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from .fallback_handler import smart_chat
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response = await smart_chat(enhanced_message, console)
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# Use streaming if available
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from .streaming import stream_with_fallback
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response = await stream_with_fallback(enhanced_message, console)
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if response:
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# Save AI response to memory
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self.memory_manager.add_message("assistant", response)
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from rich.panel import Panel
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console.print()
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console.print(Panel(
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response,
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title="[bold cyan]AI Response[/bold cyan]",
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title_align="left",
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border_style="dim cyan",
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padding=(1, 2)
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))
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# Response already displayed by streaming handler
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return
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else:
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console.print("[red]No AI options available. Please configure API keys or install tools.[/red]")
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@@ -158,6 +158,8 @@ async def smart_chat(message: str, console=None) -> Optional[str]:
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Smart chat that automatically tries available AI options.
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Returns the AI response or None if all options fail.
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"""
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from .rate_limiter import smart_limiter
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handler = FallbackHandler()
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if console:
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@@ -171,17 +173,20 @@ async def smart_chat(message: str, console=None) -> Optional[str]:
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option_type, model = best_option
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# Try the primary option
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# Try the primary option with rate limiting
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try:
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if option_type == "openai_api":
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from openai import AsyncOpenAI
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client = AsyncOpenAI()
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response = await client.chat.completions.create(
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model="gpt-4",
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messages=[{"role": "user", "content": message}],
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max_tokens=500
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)
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return response.choices[0].message.content
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async def call_openai():
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from openai import AsyncOpenAI
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client = AsyncOpenAI()
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response = await client.chat.completions.create(
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model="gpt-4",
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messages=[{"role": "user", "content": message}],
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max_tokens=500
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)
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return response.choices[0].message.content
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return await smart_limiter.execute_with_limit("openai", call_openai)
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elif option_type == "anthropic_api":
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from anthropic import AsyncAnthropic
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@@ -0,0 +1,332 @@
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"""
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Rate limiting and error recovery for Hanzo Dev.
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Prevents API overuse and handles failures gracefully.
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"""
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import time
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import asyncio
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from typing import Dict, Optional, Any, Callable
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from dataclasses import dataclass, field
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from datetime import datetime, timedelta
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from collections import deque
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import random
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@dataclass
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class RateLimitConfig:
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"""Configuration for rate limiting."""
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requests_per_minute: int = 20
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requests_per_hour: int = 100
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burst_size: int = 5
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cooldown_seconds: int = 60
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max_retries: int = 3
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backoff_base: float = 2.0
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jitter: bool = True
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@dataclass
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class RateLimitState:
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"""Current state of rate limiter."""
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minute_requests: deque = field(default_factory=lambda: deque(maxlen=60))
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hour_requests: deque = field(default_factory=lambda: deque(maxlen=3600))
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last_request: Optional[datetime] = None
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consecutive_errors: int = 0
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total_requests: int = 0
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total_errors: int = 0
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is_throttled: bool = False
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throttle_until: Optional[datetime] = None
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class RateLimiter:
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"""Rate limiter with error recovery."""
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def __init__(self, config: RateLimitConfig = None):
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"""Initialize rate limiter."""
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self.config = config or RateLimitConfig()
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self.states: Dict[str, RateLimitState] = {}
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def get_state(self, key: str = "default") -> RateLimitState:
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"""Get or create state for a key."""
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if key not in self.states:
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self.states[key] = RateLimitState()
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return self.states[key]
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async def check_rate_limit(self, key: str = "default") -> tuple[bool, float]:
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"""
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Check if request is allowed.
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Returns (allowed, wait_seconds).
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"""
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state = self.get_state(key)
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now = datetime.now()
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# Check if throttled
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if state.is_throttled and state.throttle_until:
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if now < state.throttle_until:
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wait_seconds = (state.throttle_until - now).total_seconds()
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return False, wait_seconds
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else:
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# Throttle period ended
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state.is_throttled = False
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state.throttle_until = None
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# Clean old requests
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minute_ago = now - timedelta(minutes=1)
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hour_ago = now - timedelta(hours=1)
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# Remove old requests from queues
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while state.minute_requests and state.minute_requests[0] < minute_ago:
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state.minute_requests.popleft()
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while state.hour_requests and state.hour_requests[0] < hour_ago:
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state.hour_requests.popleft()
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# Check minute limit
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if len(state.minute_requests) >= self.config.requests_per_minute:
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# Calculate wait time
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oldest = state.minute_requests[0]
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wait_seconds = (oldest + timedelta(minutes=1) - now).total_seconds()
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return False, max(0, wait_seconds)
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# Check hour limit
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if len(state.hour_requests) >= self.config.requests_per_hour:
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# Calculate wait time
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oldest = state.hour_requests[0]
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wait_seconds = (oldest + timedelta(hours=1) - now).total_seconds()
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return False, max(0, wait_seconds)
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# Check burst limit
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if state.last_request:
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time_since_last = (now - state.last_request).total_seconds()
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if time_since_last < 1.0 / self.config.burst_size:
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wait_seconds = (1.0 / self.config.burst_size) - time_since_last
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return False, wait_seconds
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return True, 0
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async def acquire(self, key: str = "default") -> bool:
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"""
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Acquire a rate limit slot.
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Waits if necessary.
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"""
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while True:
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allowed, wait_seconds = await self.check_rate_limit(key)
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if allowed:
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# Record request
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state = self.get_state(key)
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now = datetime.now()
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state.minute_requests.append(now)
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state.hour_requests.append(now)
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state.last_request = now
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state.total_requests += 1
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return True
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# Wait before retrying
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if wait_seconds > 0:
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await asyncio.sleep(min(wait_seconds, 5)) # Check every 5 seconds max
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def record_error(self, key: str = "default", error: Exception = None):
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"""Record an error for the key."""
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state = self.get_state(key)
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state.consecutive_errors += 1
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state.total_errors += 1
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# Implement exponential backoff on errors
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if state.consecutive_errors >= 3:
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# Throttle for increasing periods
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backoff_minutes = min(
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self.config.backoff_base ** (state.consecutive_errors - 2),
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60 # Max 1 hour
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)
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state.is_throttled = True
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state.throttle_until = datetime.now() + timedelta(minutes=backoff_minutes)
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def record_success(self, key: str = "default"):
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"""Record a successful request."""
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state = self.get_state(key)
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state.consecutive_errors = 0
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def get_status(self, key: str = "default") -> Dict[str, Any]:
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"""Get current status for monitoring."""
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state = self.get_state(key)
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now = datetime.now()
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return {
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"requests_last_minute": len(state.minute_requests),
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"requests_last_hour": len(state.hour_requests),
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"total_requests": state.total_requests,
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"total_errors": state.total_errors,
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"consecutive_errors": state.consecutive_errors,
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"is_throttled": state.is_throttled,
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"throttle_remaining": (
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(state.throttle_until - now).total_seconds()
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if state.throttle_until and now < state.throttle_until
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else 0
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),
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"minute_limit": self.config.requests_per_minute,
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"hour_limit": self.config.requests_per_hour,
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}
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class ErrorRecovery:
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"""Error recovery with retries and fallback."""
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def __init__(self, rate_limiter: RateLimiter = None):
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"""Initialize error recovery."""
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self.rate_limiter = rate_limiter or RateLimiter()
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self.fallback_handlers: Dict[type, Callable] = {}
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def register_fallback(self, error_type: type, handler: Callable):
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"""Register a fallback handler for an error type."""
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self.fallback_handlers[error_type] = handler
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async def with_retry(
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self,
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func: Callable,
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*args,
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key: str = "default",
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max_retries: Optional[int] = None,
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**kwargs
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) -> Any:
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"""
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Execute function with retry logic.
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"""
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max_retries = max_retries or self.rate_limiter.config.max_retries
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last_error = None
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for attempt in range(max_retries):
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try:
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# Check rate limit
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await self.rate_limiter.acquire(key)
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# Execute function
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result = await func(*args, **kwargs)
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# Record success
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self.rate_limiter.record_success(key)
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return result
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except Exception as e:
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last_error = e
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self.rate_limiter.record_error(key, e)
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# Check for fallback handler
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for error_type, handler in self.fallback_handlers.items():
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if isinstance(e, error_type):
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try:
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return await handler(*args, **kwargs)
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except:
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pass # Fallback failed, continue with retry
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# Calculate backoff
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if attempt < max_retries - 1:
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backoff = self.rate_limiter.config.backoff_base ** attempt
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# Add jitter if configured
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if self.rate_limiter.config.jitter:
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backoff *= (0.5 + random.random())
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await asyncio.sleep(min(backoff, 60)) # Max 60 seconds
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# All retries failed
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raise last_error or Exception("All retry attempts failed")
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async def with_circuit_breaker(
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self,
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func: Callable,
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*args,
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key: str = "default",
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threshold: int = 5,
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timeout: int = 60,
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**kwargs
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) -> Any:
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"""
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Execute function with circuit breaker pattern.
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"""
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state = self.rate_limiter.get_state(key)
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# Check if circuit is open
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if state.is_throttled:
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raise Exception(f"Circuit breaker open for {key}")
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try:
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result = await self.with_retry(func, *args, key=key, **kwargs)
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return result
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except Exception as e:
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# Check if we should open the circuit
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if state.consecutive_errors >= threshold:
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state.is_throttled = True
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state.throttle_until = datetime.now() + timedelta(seconds=timeout)
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raise Exception(f"Circuit breaker triggered for {key}: {e}")
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raise
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class SmartRateLimiter:
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"""Smart rate limiter that adapts to API responses."""
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def __init__(self):
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"""Initialize smart rate limiter."""
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self.limiters: Dict[str, RateLimiter] = {}
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self.recovery = ErrorRecovery()
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# Default configs for known APIs
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self.configs = {
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"openai": RateLimitConfig(
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requests_per_minute=60,
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requests_per_hour=1000,
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burst_size=10
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),
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"anthropic": RateLimitConfig(
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requests_per_minute=50,
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requests_per_hour=1000,
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burst_size=5
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),
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"local": RateLimitConfig(
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requests_per_minute=100,
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requests_per_hour=10000,
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burst_size=20
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),
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"free": RateLimitConfig(
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requests_per_minute=10,
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requests_per_hour=100,
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burst_size=2
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),
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}
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def get_limiter(self, api_type: str) -> RateLimiter:
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"""Get or create limiter for API type."""
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if api_type not in self.limiters:
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config = self.configs.get(api_type, RateLimitConfig())
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self.limiters[api_type] = RateLimiter(config)
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return self.limiters[api_type]
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async def execute_with_limit(
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self,
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api_type: str,
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func: Callable,
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*args,
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**kwargs
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) -> Any:
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"""Execute function with appropriate rate limiting."""
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limiter = self.get_limiter(api_type)
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recovery = ErrorRecovery(limiter)
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return await recovery.with_retry(
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func,
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*args,
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key=api_type,
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**kwargs
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)
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def get_all_status(self) -> Dict[str, Dict[str, Any]]:
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"""Get status of all limiters."""
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return {
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api_type: limiter.get_status()
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for api_type, limiter in self.limiters.items()
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}
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# Global instance for easy use
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smart_limiter = SmartRateLimiter()
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@@ -0,0 +1,271 @@
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"""
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Streaming response handler for Hanzo Dev.
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Provides real-time feedback as AI generates responses.
|
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"""
|
||||
|
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import asyncio
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from typing import AsyncGenerator, Optional, Callable
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from rich.console import Console
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from rich.live import Live
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from rich.panel import Panel
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from rich.markdown import Markdown
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import time
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class StreamingHandler:
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"""Handles streaming responses from AI models."""
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def __init__(self, console: Console = None):
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"""Initialize streaming handler."""
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self.console = console or Console()
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self.current_response = ""
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self.is_streaming = False
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async def stream_openai(self, client, messages: list, model: str = "gpt-4") -> str:
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"""Stream response from OpenAI API."""
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try:
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stream = await client.chat.completions.create(
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model=model,
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messages=messages,
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stream=True,
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max_tokens=1000
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)
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self.current_response = ""
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self.is_streaming = True
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with Live(
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Panel("", title="[bold cyan]AI Response[/bold cyan]",
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title_align="left", border_style="dim cyan"),
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console=self.console,
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refresh_per_second=10
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) as live:
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async for chunk in stream:
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if chunk.choices[0].delta.content:
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self.current_response += chunk.choices[0].delta.content
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live.update(
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Panel(
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Markdown(self.current_response),
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title="[bold cyan]AI Response[/bold cyan]",
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title_align="left",
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border_style="dim cyan",
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padding=(1, 2)
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)
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)
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self.is_streaming = False
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return self.current_response
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except Exception as e:
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self.console.print(f"[red]Streaming error: {e}[/red]")
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self.is_streaming = False
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return None
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async def stream_anthropic(self, client, messages: list, model: str = "claude-3-5-sonnet-20241022") -> str:
|
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"""Stream response from Anthropic API."""
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try:
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||||
self.current_response = ""
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self.is_streaming = True
|
||||
|
||||
with Live(
|
||||
Panel("", title="[bold cyan]AI Response[/bold cyan]",
|
||||
title_align="left", border_style="dim cyan"),
|
||||
console=self.console,
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||||
refresh_per_second=10
|
||||
) as live:
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async with client.messages.stream(
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model=model,
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||||
messages=messages,
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||||
max_tokens=1000
|
||||
) as stream:
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async for text in stream.text_stream:
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self.current_response += text
|
||||
live.update(
|
||||
Panel(
|
||||
Markdown(self.current_response),
|
||||
title="[bold cyan]AI Response[/bold cyan]",
|
||||
title_align="left",
|
||||
border_style="dim cyan",
|
||||
padding=(1, 2)
|
||||
)
|
||||
)
|
||||
|
||||
self.is_streaming = False
|
||||
return self.current_response
|
||||
|
||||
except Exception as e:
|
||||
self.console.print(f"[red]Streaming error: {e}[/red]")
|
||||
self.is_streaming = False
|
||||
return None
|
||||
|
||||
async def stream_ollama(self, message: str, model: str = "llama3.2") -> str:
|
||||
"""Stream response from Ollama local model."""
|
||||
import httpx
|
||||
|
||||
try:
|
||||
self.current_response = ""
|
||||
self.is_streaming = True
|
||||
|
||||
with Live(
|
||||
Panel("", title="[bold cyan]AI Response (Local)[/bold cyan]",
|
||||
title_align="left", border_style="dim cyan"),
|
||||
console=self.console,
|
||||
refresh_per_second=10
|
||||
) as live:
|
||||
async with httpx.AsyncClient() as client:
|
||||
async with client.stream(
|
||||
"POST",
|
||||
"http://localhost:11434/api/generate",
|
||||
json={"model": model, "prompt": message, "stream": True},
|
||||
timeout=60.0
|
||||
) as response:
|
||||
async for line in response.aiter_lines():
|
||||
if line:
|
||||
import json
|
||||
data = json.loads(line)
|
||||
if "response" in data:
|
||||
self.current_response += data["response"]
|
||||
live.update(
|
||||
Panel(
|
||||
Markdown(self.current_response),
|
||||
title="[bold cyan]AI Response (Local)[/bold cyan]",
|
||||
title_align="left",
|
||||
border_style="dim cyan",
|
||||
padding=(1, 2)
|
||||
)
|
||||
)
|
||||
if data.get("done", False):
|
||||
break
|
||||
|
||||
self.is_streaming = False
|
||||
return self.current_response
|
||||
|
||||
except Exception as e:
|
||||
self.console.print(f"[red]Ollama streaming error: {e}[/red]")
|
||||
self.is_streaming = False
|
||||
return None
|
||||
|
||||
async def simulate_streaming(self, text: str, delay: float = 0.02) -> str:
|
||||
"""Simulate streaming for non-streaming APIs."""
|
||||
self.current_response = ""
|
||||
self.is_streaming = True
|
||||
|
||||
words = text.split()
|
||||
|
||||
with Live(
|
||||
Panel("", title="[bold cyan]AI Response[/bold cyan]",
|
||||
title_align="left", border_style="dim cyan"),
|
||||
console=self.console,
|
||||
refresh_per_second=20
|
||||
) as live:
|
||||
for i, word in enumerate(words):
|
||||
self.current_response += word
|
||||
if i < len(words) - 1:
|
||||
self.current_response += " "
|
||||
|
||||
live.update(
|
||||
Panel(
|
||||
Markdown(self.current_response),
|
||||
title="[bold cyan]AI Response[/bold cyan]",
|
||||
title_align="left",
|
||||
border_style="dim cyan",
|
||||
padding=(1, 2)
|
||||
)
|
||||
)
|
||||
await asyncio.sleep(delay)
|
||||
|
||||
self.is_streaming = False
|
||||
return self.current_response
|
||||
|
||||
def stop_streaming(self):
|
||||
"""Stop current streaming operation."""
|
||||
self.is_streaming = False
|
||||
if self.current_response:
|
||||
self.console.print(f"\n[yellow]Streaming interrupted[/yellow]")
|
||||
|
||||
|
||||
class TypewriterEffect:
|
||||
"""Provides typewriter effect for text output."""
|
||||
|
||||
def __init__(self, console: Console = None):
|
||||
self.console = console or Console()
|
||||
|
||||
async def type_text(self, text: str, speed: float = 0.03):
|
||||
"""Type text with typewriter effect."""
|
||||
for char in text:
|
||||
self.console.print(char, end="")
|
||||
await asyncio.sleep(speed)
|
||||
self.console.print() # New line at end
|
||||
|
||||
async def type_code(self, code: str, language: str = "python", speed: float = 0.01):
|
||||
"""Type code with syntax highlighting."""
|
||||
from rich.syntax import Syntax
|
||||
|
||||
# Build up code progressively
|
||||
current_code = ""
|
||||
lines = code.split('\n')
|
||||
|
||||
with Live(console=self.console, refresh_per_second=30) as live:
|
||||
for line in lines:
|
||||
for char in line:
|
||||
current_code += char
|
||||
syntax = Syntax(current_code, language, theme="monokai", line_numbers=True)
|
||||
live.update(syntax)
|
||||
await asyncio.sleep(speed)
|
||||
current_code += '\n'
|
||||
syntax = Syntax(current_code, language, theme="monokai", line_numbers=True)
|
||||
live.update(syntax)
|
||||
|
||||
|
||||
async def stream_with_fallback(message: str, console: Console = None) -> Optional[str]:
|
||||
"""
|
||||
Stream response with automatic fallback to available options.
|
||||
"""
|
||||
import os
|
||||
handler = StreamingHandler(console)
|
||||
|
||||
# Try OpenAI streaming
|
||||
if os.getenv("OPENAI_API_KEY"):
|
||||
try:
|
||||
from openai import AsyncOpenAI
|
||||
client = AsyncOpenAI()
|
||||
return await handler.stream_openai(
|
||||
client,
|
||||
[{"role": "user", "content": message}]
|
||||
)
|
||||
except Exception as e:
|
||||
if console:
|
||||
console.print(f"[yellow]OpenAI streaming failed: {e}[/yellow]")
|
||||
|
||||
# Try Anthropic streaming
|
||||
if os.getenv("ANTHROPIC_API_KEY"):
|
||||
try:
|
||||
from anthropic import AsyncAnthropic
|
||||
client = AsyncAnthropic()
|
||||
return await handler.stream_anthropic(
|
||||
client,
|
||||
[{"role": "user", "content": message}]
|
||||
)
|
||||
except Exception as e:
|
||||
if console:
|
||||
console.print(f"[yellow]Anthropic streaming failed: {e}[/yellow]")
|
||||
|
||||
# Try Ollama streaming
|
||||
try:
|
||||
return await handler.stream_ollama(message)
|
||||
except:
|
||||
pass
|
||||
|
||||
# Fallback to non-streaming with simulated effect
|
||||
if console:
|
||||
console.print("[yellow]Falling back to non-streaming mode[/yellow]")
|
||||
|
||||
# Get response from fallback handler
|
||||
from .fallback_handler import smart_chat
|
||||
response = await smart_chat(message, console)
|
||||
|
||||
if response:
|
||||
# Simulate streaming
|
||||
return await handler.simulate_streaming(response)
|
||||
|
||||
return None
|
||||
@@ -0,0 +1 @@
|
||||
"""Hanzo test suite."""
|
||||
@@ -38,4 +38,40 @@ def test_orchestrator_config():
|
||||
# Test router mode
|
||||
config = get_orchestrator_config("router:gpt-5")
|
||||
assert config.mode == OrchestratorMode.ROUTER
|
||||
assert config.primary_model == "router:gpt-5"
|
||||
assert config.primary_model == "router:gpt-5"
|
||||
|
||||
|
||||
def test_memory_manager():
|
||||
"""Test memory manager functionality."""
|
||||
from hanzo.memory_manager import MemoryManager
|
||||
|
||||
manager = MemoryManager("/tmp/test_hanzo")
|
||||
|
||||
# Test adding memory
|
||||
memory_id = manager.add_memory("Test memory", type="fact")
|
||||
assert memory_id is not None
|
||||
|
||||
# Test retrieving memories
|
||||
memories = manager.get_memories()
|
||||
assert len(memories) > 0
|
||||
|
||||
# Test removing memory
|
||||
success = manager.remove_memory(memory_id)
|
||||
assert success is True
|
||||
|
||||
|
||||
def test_fallback_handler():
|
||||
"""Test fallback handler."""
|
||||
from hanzo.fallback_handler import FallbackHandler
|
||||
|
||||
handler = FallbackHandler()
|
||||
|
||||
# Should always have at least free APIs available
|
||||
assert handler.available_options["free_apis"] is True
|
||||
|
||||
# Should have fallback order
|
||||
assert len(handler.fallback_order) > 0
|
||||
|
||||
# Should get best option
|
||||
best = handler.get_best_option()
|
||||
assert best is not None
|
||||
@@ -0,0 +1,120 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Test rate limiting and error recovery."""
|
||||
|
||||
import asyncio
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from rich.console import Console
|
||||
from rich.table import Table
|
||||
|
||||
# Add src to path
|
||||
sys.path.insert(0, str(Path(__file__).parent / "pkg" / "hanzo" / "src"))
|
||||
|
||||
from hanzo.rate_limiter import RateLimiter, RateLimitConfig, ErrorRecovery, smart_limiter
|
||||
|
||||
async def test_rate_limiter():
|
||||
"""Test rate limiter functionality."""
|
||||
console = Console()
|
||||
|
||||
console.print("\n[bold cyan]Testing Rate Limiter[/bold cyan]\n")
|
||||
|
||||
# Create a strict rate limiter for testing
|
||||
config = RateLimitConfig(
|
||||
requests_per_minute=5,
|
||||
requests_per_hour=100,
|
||||
burst_size=2
|
||||
)
|
||||
limiter = RateLimiter(config)
|
||||
|
||||
# Test rapid requests
|
||||
console.print("[bold]Testing rate limiting (5 requests/minute):[/bold]")
|
||||
|
||||
for i in range(8):
|
||||
allowed, wait = await limiter.check_rate_limit()
|
||||
|
||||
if allowed:
|
||||
await limiter.acquire()
|
||||
console.print(f"✅ Request {i+1} allowed")
|
||||
else:
|
||||
console.print(f"⏳ Request {i+1} blocked, wait {wait:.1f}s")
|
||||
|
||||
# Small delay between requests
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
# Test status
|
||||
console.print("\n[bold]Rate limiter status:[/bold]")
|
||||
status = limiter.get_status()
|
||||
|
||||
table = Table(title="Rate Limiter Status")
|
||||
table.add_column("Metric", style="cyan")
|
||||
table.add_column("Value", style="white")
|
||||
|
||||
for key, value in status.items():
|
||||
table.add_row(key.replace("_", " ").title(), str(value))
|
||||
|
||||
console.print(table)
|
||||
|
||||
# Test error recovery
|
||||
console.print("\n[bold]Testing error recovery:[/bold]")
|
||||
|
||||
recovery = ErrorRecovery(limiter)
|
||||
|
||||
# Simulate a function that fails initially
|
||||
attempt_count = 0
|
||||
|
||||
async def flaky_function():
|
||||
nonlocal attempt_count
|
||||
attempt_count += 1
|
||||
|
||||
if attempt_count < 3:
|
||||
console.print(f" Attempt {attempt_count} failed")
|
||||
raise Exception("Simulated error")
|
||||
|
||||
console.print(f" Attempt {attempt_count} succeeded!")
|
||||
return "Success"
|
||||
|
||||
try:
|
||||
result = await recovery.with_retry(flaky_function, max_retries=5)
|
||||
console.print(f"[green]Result: {result}[/green]")
|
||||
except Exception as e:
|
||||
console.print(f"[red]Failed after retries: {e}[/red]")
|
||||
|
||||
# Test smart limiter
|
||||
console.print("\n[bold]Testing smart rate limiter:[/bold]")
|
||||
|
||||
# Simulate API calls
|
||||
async def mock_api_call(api_type: str):
|
||||
console.print(f" Calling {api_type} API...")
|
||||
await asyncio.sleep(0.1)
|
||||
return f"Response from {api_type}"
|
||||
|
||||
# Test different API types
|
||||
for api_type in ["openai", "anthropic", "local", "free"]:
|
||||
try:
|
||||
result = await smart_limiter.execute_with_limit(
|
||||
api_type,
|
||||
mock_api_call,
|
||||
api_type
|
||||
)
|
||||
console.print(f" ✅ {api_type}: {result}")
|
||||
except Exception as e:
|
||||
console.print(f" ❌ {api_type}: {e}")
|
||||
|
||||
# Show all limiter statuses
|
||||
console.print("\n[bold]All API limiter statuses:[/bold]")
|
||||
all_status = smart_limiter.get_all_status()
|
||||
|
||||
for api_type, status in all_status.items():
|
||||
if status["total_requests"] > 0:
|
||||
console.print(f"\n{api_type}:")
|
||||
console.print(f" Requests: {status['total_requests']}")
|
||||
console.print(f" Errors: {status['total_errors']}")
|
||||
console.print(f" Last minute: {status['requests_last_minute']}")
|
||||
|
||||
console.print("\n[green]✅ Rate limiting tests completed![/green]")
|
||||
|
||||
return True
|
||||
|
||||
if __name__ == "__main__":
|
||||
success = asyncio.run(test_rate_limiter())
|
||||
sys.exit(0 if success else 1)
|
||||
@@ -0,0 +1,60 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Test streaming responses."""
|
||||
|
||||
import asyncio
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from rich.console import Console
|
||||
|
||||
# Add src to path
|
||||
sys.path.insert(0, str(Path(__file__).parent / "pkg" / "hanzo" / "src"))
|
||||
|
||||
from hanzo.streaming import StreamingHandler, TypewriterEffect, stream_with_fallback
|
||||
|
||||
async def test_streaming():
|
||||
"""Test streaming functionality."""
|
||||
console = Console()
|
||||
|
||||
console.print("\n[bold cyan]Testing Streaming Responses[/bold cyan]\n")
|
||||
|
||||
# Test typewriter effect
|
||||
console.print("[bold]Testing typewriter effect:[/bold]")
|
||||
typewriter = TypewriterEffect(console)
|
||||
|
||||
await typewriter.type_text("This is a typewriter effect demonstration...", speed=0.02)
|
||||
|
||||
# Test code typing
|
||||
console.print("\n[bold]Testing code typing:[/bold]")
|
||||
code = """def fibonacci(n: int) -> int:
|
||||
if n <= 1:
|
||||
return n
|
||||
return fibonacci(n-1) + fibonacci(n-2)"""
|
||||
|
||||
await typewriter.type_code(code, language="python", speed=0.01)
|
||||
|
||||
# Test simulated streaming
|
||||
console.print("\n[bold]Testing simulated streaming:[/bold]")
|
||||
handler = StreamingHandler(console)
|
||||
|
||||
sample_text = "This is a simulated streaming response. It will appear word by word as if being generated in real-time. This creates a better user experience!"
|
||||
|
||||
await handler.simulate_streaming(sample_text, delay=0.03)
|
||||
|
||||
# Test real streaming with fallback
|
||||
console.print("\n[bold]Testing streaming with fallback:[/bold]")
|
||||
|
||||
test_message = "What is 2 + 2? Reply with just the number."
|
||||
|
||||
response = await stream_with_fallback(test_message, console)
|
||||
|
||||
if response:
|
||||
console.print(f"\n[green]✅ Streaming test successful![/green]")
|
||||
console.print(f"Response: {response}")
|
||||
else:
|
||||
console.print("\n[yellow]⚠️ No streaming available (no API keys)[/yellow]")
|
||||
|
||||
return True
|
||||
|
||||
if __name__ == "__main__":
|
||||
success = asyncio.run(test_streaming())
|
||||
sys.exit(0 if success else 1)
|
||||
Reference in New Issue
Block a user