SemCache (Python SDK)
Zero-cost, low-latency tiered semantic caching SDK for LLMs running local embeddings.
Installation
pip install semcache
Quick Start
from semcache import SemCache, FileStore
# Initialize cache with local file storage
cache = SemCache(
store=FileStore(".semcache/db.json"),
fuzzy_threshold=0.95,
semantic_threshold=0.85
)
# Set an entry (simulate LLM response time of 1500ms)
cache.set(
query="What is the capital of France?",
response="The capital of France is Paris.",
latency_ms=1500,
token_usage={"prompt_tokens": 7, "completion_tokens": 7}
)
# Query semantic matching (instant hit in ~20ms, $0 API cost)
result = cache.get("tell me the capital city of France")
if result:
entry, tier, similarity = result
print(f"Hit Tier: {tier} (Similarity: {similarity:.4f})")
print(f"Response: {entry.response}")
Release files for semc 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| semc-1.0.0.tar.gz | 5.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| semc-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.3 kB
Release files / semc-1.0.0.tar.gz
| Download URL | semc-1.0.0.tar.gz |
|---|---|
| Size | 5.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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| Upload date | |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.10.1
|
Release files / semc-1.0.0-py3-none-any.whl
| Download URL | semc-1.0.0-py3-none-any.whl |
|---|---|
| Size | 5.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.1
|