mirror of
https://github.com/semantica-agi/semantica.git
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Derek TapleyandCursor
f0aa581318
* feat(integrations): add LangChain integration — retriever, vectorstore, tools Co-authored-by: Cursor <cursoragent@cursor.com> * fix(langchain): address Qodo review on HybridSearch hits and tools Read nested HybridSearch metadata so retriever/vectorstore Documents are not empty, make the agent tools real BaseTool subclasses, and stop slicing tool JSON into invalid payloads. Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>
68 lines
1.9 KiB
Markdown
68 lines
1.9 KiB
Markdown
# Semantica × LangChain
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Drop Semantica into existing LangChain / LangGraph pipelines: GraphRAG-style
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retrieval, a `VectorStore` adapter, and agent tools.
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## Install
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```bash
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pip install semantica[langchain]
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# or just the core adapter dependency:
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pip install langchain-core
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```
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## Retriever (GraphRAG)
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```python
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from integrations.langchain import SemanticaRetriever
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from semantica.context import ContextGraph
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from semantica.vector_store import HybridSearch
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graph = ContextGraph()
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hybrid = HybridSearch()
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retriever = SemanticaRetriever(graph=graph, hybrid=hybrid, hops=2, top_k=10)
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# Use with any LangChain chain that accepts a retriever:
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from langchain.chains import RetrievalQA
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qa = RetrievalQA.from_chain_type(llm=llm, retriever=retriever)
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```
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Hybrid search seeds retrieval; then graph edges are walked `hops` steps so
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results go beyond flat vector similarity.
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## VectorStore
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```python
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from integrations.langchain import SemanticaVectorStore
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store = SemanticaVectorStore(hybrid=hybrid)
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store.add_texts(["document one", "document two"], metadatas=[{"source": "a"}, {"source": "b"}])
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docs = store.similarity_search("document", k=2)
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docs, scores = store.similarity_search_with_score("document", k=2)
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```
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## Agent tools (LangGraph / tool-calling agents)
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```python
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from integrations.langchain import SemanticaKGTool, SemanticaDecisionTool
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from langgraph.prebuilt import create_react_agent
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tools = [
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SemanticaKGTool(graph),
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SemanticaDecisionTool(graph),
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]
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agent = create_react_agent(model, tools)
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```
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- `semantica_query_graph` — query the shared context graph (keyword / NL)
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- `semantica_query_decisions` — search the recorded decision log
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## Compatibility
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- Requires `langchain-core >= 0.3`.
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- All classes degrade gracefully when `langchain-core` is absent: they remain
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importable (carrying the full Semantica API), and `build()` returns `None`,
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so agents can branch on `LANGCHAIN_AVAILABLE`.
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