Metadata-Version: 2.4
Name: conproxy
Version: 0.2.1
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Rust
Requires-Dist: langchain-core>=0.1,<1.0 ; extra == 'langchain'
Requires-Dist: llama-index-core>=0.10,<1.0 ; extra == 'llama-index'
Provides-Extra: langchain
Provides-Extra: llama-index
Provides-Extra: onnx
Provides-Extra: persist
Summary: Python SDK for conproxy — retrieval-leg cache for agentic RAG
License: MIT
Requires-Python: >=3.10
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Documentation, https://github.com/jmcgrath207/conproxy/blob/main/docs/sdk-python.md
Project-URL: Homepage, https://github.com/jmcgrath207/conproxy
Project-URL: Repository, https://github.com/jmcgrath207/conproxy

# conproxy

Retrieval-leg cache for **agentic RAG**. Native Rust bindings: in-process `Engine` or gRPC `ConproxyClient`.

Not an LLM-answer cache (that's GPTCache / RedisVL). Hits skip embed + upstream search when agents re-query.

```bash
pip install conproxy
```

```python
from conproxy import Engine

engine = Engine(config="conproxy.toml")
result = await engine.query("how does X work", top_k=10)
# result.cache_status: 1=hit, 2=miss, 3=stale, 4=frozen
```

Talk to a running daemon instead:

```python
from conproxy import ConproxyClient

client = ConproxyClient(grpc_url="http://localhost:9999")
resp = client.query("how does X work", top_k=5)
```

Extras: `pip install conproxy[langchain]` · `pip install conproxy[llama-index]`

- Docs: [Python SDK](https://github.com/jmcgrath207/conproxy/blob/main/docs/sdk-python.md) · [Engine](https://github.com/jmcgrath207/conproxy/blob/main/docs/engine.md)
- Source: [github.com/jmcgrath207/conproxy](https://github.com/jmcgrath207/conproxy)

