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import ollama
import openai
from know_lang_bot.config import EmbeddingConfig, ModelProvider
from typing import Union, List, overload
# Type definitions
EmbeddingVector = List[float]
def _process_ollama_batch(inputs: List[str], model_name: str) -> List[EmbeddingVector]:
"""Helper function to process Ollama embeddings in batch."""
return [
ollama.embed(model=model_name, input=inputs)['embeddings']
]
def _process_openai_batch(inputs: List[str], model_name: str) -> List[EmbeddingVector]:
"""Helper function to process OpenAI embeddings in batch."""
response = openai.embeddings.create(
input=inputs,
model=model_name
)
return [item.embedding for item in response.data]
@overload
def generate_embedding(input: str, config: EmbeddingConfig) -> EmbeddingVector: ...
@overload
def generate_embedding(input: List[str], config: EmbeddingConfig) -> List[EmbeddingVector]: ...
def generate_embedding(
input: Union[str, List[str]],
config: EmbeddingConfig
) -> Union[EmbeddingVector, List[EmbeddingVector]]:
"""
Generate embeddings for single text input or batch of texts.
Args:
input: Single string or list of strings to embed
config: Configuration object containing provider and model information
Returns:
Single embedding vector for single input, or list of embedding vectors for batch input
Raises:
ValueError: If input type is invalid or provider is not supported
RuntimeError: If embedding generation fails
"""
if not input:
raise ValueError("Input cannot be empty")
# Convert single string to list for batch processing
is_single_input = isinstance(input, str)
inputs = [input] if is_single_input else input
try:
if config.model_provider == ModelProvider.OLLAMA:
embeddings = _process_ollama_batch(inputs, config.model_name)
elif config.model_provider == ModelProvider.OPENAI:
openai.api_key = config.api_key
embeddings = _process_openai_batch(inputs, config.model_name)
else:
raise ValueError(f"Unsupported provider: {config.model_provider}")
# Return single embedding for single input
return embeddings[0] if is_single_input else embeddings
except Exception as e:
raise RuntimeError(f"Failed to generate embeddings: {str(e)}") from e |