from_examples() — langchain Function Reference

Architecture documentation for the from_examples() function in semantic_similarity.py from the langchain codebase.

Function python PromptManagement ExampleSelection calls 2 called by 1

Entity Profile

PromptManagement→ ExampleSelection→ from_examples() — langchain Function Reference

Dependency Diagram

graph TD
  3782e76b_1f70_0230_9a04_603cfed2da69["from_examples()"]
  aa3e3447_c66f_695d_1f2e_1163e1aabd18["MaxMarginalRelevanceExampleSelector"]
  3782e76b_1f70_0230_9a04_603cfed2da69 -->|defined in| aa3e3447_c66f_695d_1f2e_1163e1aabd18
  ec98ee18_b513_50bf_3abe_4f8b0800215d["from_examples()"]
  ec98ee18_b513_50bf_3abe_4f8b0800215d -->|calls| 3782e76b_1f70_0230_9a04_603cfed2da69
  ec98ee18_b513_50bf_3abe_4f8b0800215d["from_examples()"]
  3782e76b_1f70_0230_9a04_603cfed2da69 -->|calls| ec98ee18_b513_50bf_3abe_4f8b0800215d
  06f73539_fe12_1c9c_b0b0_60530c6bf341["_example_to_text()"]
  3782e76b_1f70_0230_9a04_603cfed2da69 -->|calls| 06f73539_fe12_1c9c_b0b0_60530c6bf341
  style 3782e76b_1f70_0230_9a04_603cfed2da69 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/example_selectors/semantic_similarity.py lines 268–311

    def from_examples(
        cls,
        examples: list[dict],
        embeddings: Embeddings,
        vectorstore_cls: type[VectorStore],
        k: int = 4,
        input_keys: list[str] | None = None,
        fetch_k: int = 20,
        example_keys: list[str] | None = None,
        vectorstore_kwargs: dict | None = None,
        **vectorstore_cls_kwargs: Any,
    ) -> MaxMarginalRelevanceExampleSelector:
        """Create k-shot example selector using example list and embeddings.

        Reshuffles examples dynamically based on Max Marginal Relevance.

        Args:
            examples: List of examples to use in the prompt.
            embeddings: An initialized embedding API interface, e.g. OpenAIEmbeddings().
            vectorstore_cls: A vector store DB interface class, e.g. FAISS.
            k: Number of examples to select.
            fetch_k: Number of `Document` objects to fetch to pass to MMR algorithm.
            input_keys: If provided, the search is based on the input variables
                instead of all variables.
            example_keys: If provided, keys to filter examples to.
            vectorstore_kwargs: Extra arguments passed to similarity_search function
                of the `VectorStore`.
            vectorstore_cls_kwargs: optional kwargs containing url for vector store

        Returns:
            The ExampleSelector instantiated, backed by a vector store.
        """
        string_examples = [cls._example_to_text(eg, input_keys) for eg in examples]
        vectorstore = vectorstore_cls.from_texts(
            string_examples, embeddings, metadatas=examples, **vectorstore_cls_kwargs
        )
        return cls(
            vectorstore=vectorstore,
            k=k,
            fetch_k=fetch_k,
            input_keys=input_keys,
            example_keys=example_keys,
            vectorstore_kwargs=vectorstore_kwargs,
        )