feat(core): add embeddings

.github/workflows/ci.yml

@@ -141,7 +141,7 @@ jobs:
         run: |
           # run with coverage to not execute tests twice
           source venv/bin/activate
-          coverage run -m pytest -v -p no:warnings --junitxml=report.xml 
+          coverage run -m pytest -v -p no:warnings --junitxml=report.xml
           coverage report
           coverage xml
 

packages/ragnarok-common/src/ragnarok_common/embeddings/base.py

@@ -0,0 +1,19 @@
+from abc import ABC, abstractmethod
+
+
+class Embeddings(ABC):
+    """
+    Abstract client for communication with embedding models.
+    """
+
+    @abstractmethod
+    async def embed_text(self, data: list[str]) -> list[list[float]]:
+        """
+        Creates embeddings for the given strings.
+
+        Args:
+            data: List of strings to get embeddings for.
+
+        Returns:
+            List of embeddings for the given strings.
+        """

packages/ragnarok-common/src/ragnarok_common/embeddings/exceptions.py

@@ -0,0 +1,36 @@
+class EmbeddingError(Exception):
+    """
+    Base class for all exceptions raised by the EmbeddingClient.
+    """
+
+    def __init__(self, message: str) -> None:
+        super().__init__(message)
+        self.message = message
+
+
+class EmbeddingConnectionError(EmbeddingError):
+    """
+    Raised when there is an error connecting to the embedding API.
+    """
+
+    def __init__(self, message: str = "Connection error.") -> None:
+        super().__init__(message)
+
+
+class EmbeddingStatusError(EmbeddingError):
+    """
+    Raised when an API response has a status code of 4xx or 5xx.
+    """
+
+    def __init__(self, message: str, status_code: int) -> None:
+        super().__init__(message)
+        self.status_code = status_code
+
+
+class EmbeddingResponseError(EmbeddingError):
+    """
+    Raised when an API response has an invalid schema.
+    """
+
+    def __init__(self, message: str = "Data returned by API invalid for expected schema.") -> None:
+        super().__init__(message)

packages/ragnarok-common/src/ragnarok_common/embeddings/litellm.py

@@ -0,0 +1,85 @@
+from typing import Optional
+
+try:
+    import litellm
+
+    HAS_LITELLM = True
+except ImportError:
+    HAS_LITELLM = False
+
+from ragnarok_common.embeddings.base import Embeddings
+from ragnarok_common.embeddings.exceptions import EmbeddingConnectionError, EmbeddingResponseError, EmbeddingStatusError
+
+
+class LiteLLMEmbeddings(Embeddings):
+    """
+    Client for creating text embeddings using LiteLLM API.
+    """
+
+    def __init__(
+        self,
+        model: str = "text-embedding-3-small",
+        options: Optional[dict] = None,
+        api_base: Optional[str] = None,
+        api_key: Optional[str] = None,
+        api_version: Optional[str] = None,
+    ) -> None:
+        """
+        Constructs the LiteLLMEmbeddingClient.
+
+        Args:
+            model: Name of the [LiteLLM supported model](https://docs.litellm.ai/docs/embedding/supported_embedding)\
+                to be used. Default is "text-embedding-3-small".
+            options: Additional options to pass to the LiteLLM API.
+            api_base: The API endpoint you want to call the model with.
+            api_key: API key to be used. API key to be used. If not specified, an environment variable will be used,
+                for more information, follow the instructions for your specific vendor in the\
+                [LiteLLM documentation](https://docs.litellm.ai/docs/embedding/supported_embedding).
+            api_version: The API version for the call.
+
+        Raises:
+            ImportError: If the litellm package is not installed.
+        """
+        if not HAS_LITELLM:
+            raise ImportError("You need to install litellm package to use LiteLLM models")
+
+        super().__init__()
+        self.model = model
+        self.options = options or {}
+        self.api_base = api_base
+        self.api_key = api_key
+        self.api_version = api_version
+
+    async def embed_text(self, data: list[str]) -> list[list[float]]:
+        """
+        Creates embeddings for the given strings.
+
+        Args:
+            data: List of strings to get embeddings for.
+
+        Returns:
+            List of embeddings for the given strings.
+
+        Raises:
+            EmbeddingConnectionError: If there is a connection error with the embedding API.
+            EmbeddingStatusError: If the embedding API returns an error status code.
+            EmbeddingResponseError: If the embedding API response is invalid.
+        """
+
+        try:
+            response = await litellm.aembedding(
+                input=data,
+                model=self.model,
+                api_base=self.api_base,
+                api_key=self.api_key,
+                api_version=self.api_version,
+                **self.options,
+            )
+        except litellm.openai.APIConnectionError as exc:
+            raise EmbeddingConnectionError() from exc
+        except litellm.openai.APIStatusError as exc:
+            raise EmbeddingStatusError(exc.message, exc.status_code) from exc
+        except litellm.openai.APIResponseValidationError as exc:
+            raise EmbeddingResponseError() from exc
+
+        return [embedding["embedding"] for embedding in response.data]

packages/ragnarok-dev-kit/src/ragnarok_dev_kit/app/main.py

@@ -5,10 +5,10 @@
 import jinja2
 import typer
 from pydantic import BaseModel
+from ragnarok_dev_kit.discovery.prompt_discovery import PromptDiscovery
 
 from ragnarok_common.llms import LiteLLM
 from ragnarok_common.llms.clients import LiteLLMOptions
-from ragnarok_dev_kit.discovery.prompt_discovery import PromptDiscovery
 
 
 class PromptState:
@@ -26,7 +26,7 @@ class PromptState:
                                  "Render Prompt" button and reflects in the "Rendered Prompt" field.
                                  It is used for communication with the LLM.
         llm_model_name (str): The name of the selected LLM model.
-        llm_api_key (str): The API key for the chosen LLM model.
+        llm_api_key (str | None): The API key for the chosen LLM model.
         temp_field_name (str): Temporary field name used internally.
     """
 
@@ -35,7 +35,7 @@ class PromptState:
     dynamic_tb: dict = {}
     current_prompt = None
     llm_model_name: str = ""
-    llm_api_key: str = ""
+    llm_api_key: str | None = ""
     temp_field_name: str = ""
 
 
@@ -170,7 +170,7 @@ def get_input_type_fields(obj: BaseModel) -> list[dict]:
 
 
 @typer_app.command()
-def run_app(prompts_paths: str, llm_model: str, llm_api_key: str = None) -> None:
+def run_app(prompts_paths: str, llm_model: str, llm_api_key: str | None = None) -> None:
     """
     Launches the interactive application for working with Large Language Models (LLMs).
 

packages/ragnarok-dev-kit/src/ragnarok_dev_kit/discovery/prompt_discovery.py

@@ -92,4 +92,3 @@ def discover(self) -> dict:
                     )._asdict()
 
         return result_dict
-