remove untested providers

Author: lucebert

src/shared/retrieval.py

@@ -14,9 +14,8 @@
 
 from shared.configuration import BaseConfiguration
 
-## Encoder constructors
-
 
+## Encoder constructors
 def make_text_encoder(model: str) -> Embeddings:
     """Connect to the configured text encoder."""
     provider, model = model.split("/", maxsplit=1)
@@ -25,44 +24,11 @@ def make_text_encoder(model: str) -> Embeddings:
             from langchain_openai import OpenAIEmbeddings
 
             return OpenAIEmbeddings(model=model)
-        case "cohere":
-            from langchain_cohere import CohereEmbeddings
-
-            return CohereEmbeddings(model=model)  # type: ignore
         case _:
             raise ValueError(f"Unsupported embedding provider: {provider}")
 
 
 ## Retriever constructors
-
-
-@contextmanager
-def make_elastic_retriever(
-    configuration: BaseConfiguration, embedding_model: Embeddings
-) -> Generator[VectorStoreRetriever, None, None]:
-    """Configure this agent to connect to a specific elastic index."""
-    from langchain_elasticsearch import ElasticsearchStore
-
-    connection_options = {}
-    if configuration.retriever_provider == "elastic-local":
-        connection_options = {
-            "es_user": os.environ["ELASTICSEARCH_USER"],
-            "es_password": os.environ["ELASTICSEARCH_PASSWORD"],
-        }
-
-    else:
-        connection_options = {"es_api_key": os.environ["ELASTICSEARCH_API_KEY"]}
-
-    vstore = ElasticsearchStore(
-        **connection_options,  # type: ignore
-        es_url=os.environ["ELASTICSEARCH_URL"],
-        index_name="langchain_index",
-        embedding=embedding_model,
-    )
-
-    yield vstore.as_retriever(search_kwargs=configuration.search_kwargs)
-
-
 @contextmanager
 def make_pinecone_retriever(
     configuration: BaseConfiguration, embedding_model: Embeddings
@@ -75,22 +41,6 @@ def make_pinecone_retriever(
     )
     yield vstore.as_retriever(search_kwargs=configuration.search_kwargs)
 
-
-@contextmanager
-def make_mongodb_retriever(
-    configuration: BaseConfiguration, embedding_model: Embeddings
-) -> Generator[VectorStoreRetriever, None, None]:
-    """Configure this agent to connect to a specific MongoDB Atlas index & namespaces."""
-    from langchain_mongodb.vectorstores import MongoDBAtlasVectorSearch
-
-    vstore = MongoDBAtlasVectorSearch.from_connection_string(
-        os.environ["MONGODB_URI"],
-        namespace="langgraph_retrieval_agent.default",
-        embedding=embedding_model,
-    )
-    yield vstore.as_retriever(search_kwargs=configuration.search_kwargs)
-
-
 @contextmanager
 def make_retriever(
     config: RunnableConfig,
@@ -99,18 +49,10 @@ def make_retriever(
     configuration = BaseConfiguration.from_runnable_config(config)
     embedding_model = make_text_encoder(configuration.embedding_model)
     match configuration.retriever_provider:
-        case "elastic" | "elastic-local":
-            with make_elastic_retriever(configuration, embedding_model) as retriever:
-                yield retriever
-
         case "pinecone":
             with make_pinecone_retriever(configuration, embedding_model) as retriever:
                 yield retriever
 
-        case "mongodb":
-            with make_mongodb_retriever(configuration, embedding_model) as retriever:
-                yield retriever
-
         case _:
             raise ValueError(
                 "Unrecognized retriever_provider in configuration. "