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Documentation Index

Fetch the complete documentation index at: https://docs.upsonic.ai/llms.txt

Use this file to discover all available pages before exploring further.

Enable caching to store and reuse task responses for similar inputs, reducing API costs and improving performance.

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Quick Start

from upsonic import Agent, Task

agent = Agent(model="anthropic/claude-sonnet-4-5")
task = Task(
    description="Summarize this article about AI advancements",
    enable_cache=True
)

agent.print_do(task)

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Cache Methods

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Vector Search (Default)

Uses semantic similarity to find cached responses for similar inputs. 
from upsonic import Agent, Task

agent = Agent(model="anthropic/claude-sonnet-4-5")
task = Task(
    description="Analyze this text about climate change",
    enable_cache=True,
    cache_method="vector_search",
    cache_threshold=0.8  # Higher = stricter matching
)

agent.print_do(task)

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LLM Call

Uses an LLM to determine if cached responses are applicable. 
from upsonic import Agent, Task

agent = Agent(model="anthropic/claude-sonnet-4-5")
task = Task(
    description="Analyze this text about renewable energy",
    enable_cache=True,
    cache_method="llm_call"
)

agent.print_do(task)

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Configuration Options

ParameterTypeDefaultDescription
enable_cacheboolFalseEnable/disable caching
cache_methodstr"vector_search""vector_search" or "llm_call"
cache_thresholdfloat0.7Similarity threshold (0.0-1.0)
cache_duration_minutesint60Cache expiration time
cache_embedding_providerAnyAuto-detectedCustom embedding provider

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Full Example

from upsonic import Agent, Task

agent = Agent(model="anthropic/claude-sonnet-4-5")
task = Task(
    description="Explain quantum computing",
    enable_cache=True,
    cache_method="vector_search",
    cache_threshold=0.75,
    cache_duration_minutes=120
)

agent.print_do(task)

# Check if response came from cache
cache_stats = task.get_cache_stats()
if cache_stats.get('cache_hit'):
    print("Response retrieved from cache!")
else:
    print("Fresh response generated")

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Task Cache Methods

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get_cache_stats()

Get cache statistics including hit rate and configuration. 
stats = task.get_cache_stats()
print(f"Hit rate: {stats['hit_rate']}")
print(f"Total entries: {stats['total_entries']}")
Returns:
  • total_entries: Number of cached entries
  • cache_hits: Number of cache hits
  • cache_misses: Number of cache misses
  • hit_rate: Cache hit rate (0.0-1.0)
  • cache_method: Current cache method
  • cache_threshold: Current threshold
  • cache_hit: Whether last request was a cache hit
  • session_id: Current session ID

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clear_cache()

Clear all cache entries. 
task.clear_cache()

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Best Practices

  • Threshold Tuning: Start with 0.7, increase for stricter matching
  • Duration: Set based on how often your data changes
  • Method Choice: Use vector_search for speed, llm_call for accuracy
  • Embedding Provider: Auto-detected if not specified