FireworksEmbeddings Class — langchain Architecture

Architecture documentation for the FireworksEmbeddings class in embeddings.py from the langchain codebase.

Class python

Entity Profile

Dependency Diagram

graph TD
  05a5ceb6_bb67_31c9_56dc_02ecd3bcd54c["FireworksEmbeddings"]
  b1e4f760_c634_d3bf_ca9a_db7ab899cc4a["Embeddings"]
  05a5ceb6_bb67_31c9_56dc_02ecd3bcd54c -->|extends| b1e4f760_c634_d3bf_ca9a_db7ab899cc4a
  ef8bd060_1412_c5a1_3e01_0225f85f271a["embeddings.py"]
  05a5ceb6_bb67_31c9_56dc_02ecd3bcd54c -->|defined in| ef8bd060_1412_c5a1_3e01_0225f85f271a
  5a5faf33_c650_84d5_61be_041a8639920c["validate_environment()"]
  05a5ceb6_bb67_31c9_56dc_02ecd3bcd54c -->|method| 5a5faf33_c650_84d5_61be_041a8639920c
  a054a7f3_c61b_f844_c3fa_603487684a6a["embed_documents()"]
  05a5ceb6_bb67_31c9_56dc_02ecd3bcd54c -->|method| a054a7f3_c61b_f844_c3fa_603487684a6a
  a3b5d131_3f6a_fea9_c9d9_afa9affb5436["embed_query()"]
  05a5ceb6_bb67_31c9_56dc_02ecd3bcd54c -->|method| a3b5d131_3f6a_fea9_c9d9_afa9affb5436

Relationship Graph

Source Code

libs/partners/fireworks/langchain_fireworks/embeddings.py lines 8–107

class FireworksEmbeddings(BaseModel, Embeddings):
    """Fireworks embedding model integration.

    Setup:

        Install `langchain_fireworks` and set environment variable
        `FIREWORKS_API_KEY`.

        ```bash
        pip install -U langchain_fireworks
        export FIREWORKS_API_KEY="your-api-key"
        ```

    Key init args — completion params:
        model:
            Name of Fireworks model to use.

    Key init args — client params:
        fireworks_api_key:
            Fireworks API key.

    See full list of supported init args and their descriptions in the params section.

    Instantiate:

        ```python
        from langchain_fireworks import FireworksEmbeddings

        model = FireworksEmbeddings(
            model="nomic-ai/nomic-embed-text-v1.5"
            # Use FIREWORKS_API_KEY env var or pass it in directly
            # fireworks_api_key="..."
        )
        ```

    Embed multiple texts:

        ```python
        vectors = embeddings.embed_documents(["hello", "goodbye"])
        # Showing only the first 3 coordinates
        print(len(vectors))
        print(vectors[0][:3])
        ```
        ```python
        2
        [-0.024603435769677162, -0.007543657906353474, 0.0039630369283258915]
        ```

    Embed single text:

        ```python
        input_text = "The meaning of life is 42"
        vector = embeddings.embed_query("hello")
        print(vector[:3])
        ```
        ```python
        [-0.024603435769677162, -0.007543657906353474, 0.0039630369283258915]
        ```
    """

    client: OpenAI = Field(default=None, exclude=True)  # type: ignore[assignment]

    fireworks_api_key: SecretStr = Field(
        alias="api_key",
        default_factory=secret_from_env(
            "FIREWORKS_API_KEY",
            default="",
        ),
    )
    """Fireworks API key.

    Automatically read from env variable `FIREWORKS_API_KEY` if not provided.
    """

    model: str = "nomic-ai/nomic-embed-text-v1.5"

    model_config = ConfigDict(
        populate_by_name=True,
        arbitrary_types_allowed=True,
    )