Adding fastembed with claude instant

llm-server/enums/embedding_provider.py

@@ -6,3 +6,5 @@ class EmbeddingProvider(Enum):
     BARD = "bard"
     azure = "azure"
     llama2 = "llama2"
+    openchat = "openchat"
+    fastembed = "fastembed"

llm-server/requirements.txt

@@ -50,7 +50,7 @@ hpack==4.0.0
 httpcore==0.18.0
 httptools==0.6.1
 httpx==0.25.0
-huggingface-hub==0.17.3
+huggingface-hub==0.19.4
 humanfriendly==10.0
 Hypercorn==0.15.0
 hyperframe==6.0.1
@@ -143,7 +143,7 @@ sympy==1.12
 taskgroup==0.0.0a4
 tenacity==8.2.3
 tiktoken==0.5.1
-tokenizers==0.14.1
+tokenizers==0.15.0
 tomli==2.0.1
 tqdm==4.66.1
 trio==0.23.1
@@ -166,4 +166,6 @@ wrapt==1.16.0
 wsproto==1.2.0
 yarl==1.9.2
 zipp==3.17.0
-lxml==4.9.3
+lxml==4.9.3
+fastembed==0.1.3
+anthropic==0.7.8

llm-server/shared/utils/opencopilot_utils/embedding_type.py

@@ -7,4 +7,4 @@ class EmbeddingProvider(Enum):
     azure = "azure"
     llama2 = "llama2"
     openchat = "openchat"
-
+    fastembed = "fastembed"

llm-server/shared/utils/opencopilot_utils/get_embeddings.py

@@ -6,20 +6,24 @@
 from .embedding_type import EmbeddingProvider
 from langchain.embeddings.base import Embeddings
 from utils.get_logger import CustomLogger
+from langchain.embeddings.fastembed import FastEmbedEmbeddings
 
 
 logger = CustomLogger(module_name=__name__)
 
 LOCAL_IP = os.getenv("LOCAL_IP", "host.docker.internal")
 
+
 @lru_cache(maxsize=1)
 def get_embeddings():
-    embedding_provider = os.environ.get("EMBEDDING_PROVIDER", EmbeddingProvider.OPENAI.value)
+    embedding_provider = os.environ.get(
+        "EMBEDDING_PROVIDER", EmbeddingProvider.OPENAI.value
+    )
 
     if embedding_provider == EmbeddingProvider.azure.value:
         deployment = os.environ.get("AZURE_OPENAI_EMBEDDING_MODEL_NAME")
         client = os.environ.get("AZURE_OPENAI_API_TYPE")
-        
+
         # These keys should be set
         # os.environ["OPENAI_API_TYPE"] = "azure"
         # os.environ["OPENAI_API_BASE"] = "https://<your-endpoint.openai.azure.com/"
@@ -32,19 +36,26 @@ def get_embeddings():
             client=client,
             chunk_size=8,
         )
-    
+
     elif embedding_provider == EmbeddingProvider.openchat.value:
         logger.info("Got ollama embedding provider", provider=embedding_provider)
         return OllamaEmbeddings(base_url=f"{LOCAL_IP}:11434", model="openchat")
-
-    elif embedding_provider == EmbeddingProvider.OPENAI.value or embedding_provider is None:
+
+    elif (
+        embedding_provider == EmbeddingProvider.OPENAI.value
+        or embedding_provider is None
+    ):
         if embedding_provider is None:
             warnings.warn("No embedding provider specified. Defaulting to OpenAI.")
         return OpenAIEmbeddings()
+    elif embedding_provider == EmbeddingProvider.fastembed.value:
+        return FastEmbedEmbeddings()
 
     else:
-        available_providers = ", ".join([service.value for service in EmbeddingProvider])
+        available_providers = ", ".join(
+            [service.value for service in EmbeddingProvider]
+        )
         raise ValueError(
             f"Embedding service '{embedding_provider}' is not currently available. "
             f"Available services: {available_providers}"
-        )
+        )