Open OKC13 opened 1 month ago
Yes, it is possible to deploy a local embedding API on Server A and a reranker API (Llama Index) on Server B, with Server B accessing Server A.
Here is a high-level approach to achieve this:
Deploy Embedding API on Server A:
Deploy Reranker API on Server B:
Network Configuration:
Here is a simplified example of how you might configure the reranker API on Server B to access the embedding API on Server A:
# On Server B (Reranker API)
import requests
# URL of the embedding API on Server A
embedding_api_url = "http://server-a:8000/embedding"
def get_embedding(text):
response = requests.post(embedding_api_url, json={"text": text})
return response.json()
# Example usage
text = "Example text to embed"
embedding = get_embedding(text)
print(embedding)
Additionally, the LlamafileEmbedding
class from the LlamaIndex framework can be used to handle embedding requests. Here is an example of how you might use it:
from llama_index.embeddings.llamafile.base import LlamafileEmbedding
# Configure the LlamafileEmbedding to point to the embedding API on Server A
embedding_service = LlamafileEmbedding(base_url="http://server-a:8000")
# Example usage
text = "Example text to embed"
embedding = embedding_service._get_text_embedding(text)
print(embedding)
Ensure that the embedding API on Server A is running and accessible from Server B. You can use tools like Docker and Docker Compose to manage and deploy these services as described in the document [1][2].
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LlamafileEmbedding can only load embeddings related to llamafile, right?How about the reranker API? How to solve it?
The LlamafileEmbedding
class is designed to interact with an embedding API, but it is not limited to embeddings related to Llamafile. You can configure it to point to any embedding API by setting the base_url
parameter.
For the reranker API, you can use the LlamaIndex
framework to handle reranking tasks. Here is an example of how you can set up the reranker API to use embeddings from the embedding API on Server A:
LlamafileEmbedding
class to use the embedding API on Server A:from llama_index.embeddings.llamafile.base import LlamafileEmbedding
# URL of the embedding API on Server A
server_a_url = "http://server-a-address:8080"
# Create an instance of LlamafileEmbedding with the base_url set to Server A's URL
embedding_instance = LlamafileEmbedding(base_url=server_a_url)
# Example usage
query = "example query"
embedding = embedding_instance._get_query_embedding(query)
print(embedding)
You can create a custom reranker class that uses the embeddings obtained from the LlamafileEmbedding
instance. Here is a simplified example:
from llama_index import Reranker
class CustomReranker(Reranker):
def __init__(self, embedding_instance):
self.embedding_instance = embedding_instance
def rerank(self, documents, query):
query_embedding = self.embedding_instance._get_query_embedding(query)
# Implement your reranking logic here using the query_embedding and document embeddings
# For example, you can calculate similarity scores and sort the documents
ranked_documents = sorted(documents, key=lambda doc: self.calculate_similarity(query_embedding, doc.embedding))
return ranked_documents
def calculate_similarity(self, query_embedding, doc_embedding):
# Implement your similarity calculation logic here
return sum(q * d for q, d in zip(query_embedding, doc_embedding))
# Example usage
embedding_instance = LlamafileEmbedding(base_url=server_a_url)
reranker = CustomReranker(embedding_instance)
documents = [...] # List of documents with their embeddings
query = "example query"
ranked_documents = reranker.rerank(documents, query)
print(ranked_documents)
In this example, replace "http://server-a-address:8080"
with the actual URL of Server A where the embedding API is hosted. This will configure the LlamafileEmbedding
instance to send requests to Server A for embeddings, and the CustomReranker
class will use these embeddings to rerank the documents.
This approach allows you to deploy the embedding API on Server A and the reranker API on Server B, with Server B accessing the embeddings from Server A [1].
To continue talking to Dosu, mention @dosu.
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Question
I want to deploy the embedding API on Server A and then deploy the Llama Index on Server B, with Server B accessing Server A.