upload github well compiled files (#1)

- upload github well compiled files (a26db82602b82ba45fe7e51dd6073c0961edaebd)

langchain/manager.py

@@ -0,0 +1,39 @@
+from abc import abstractmethod, ABC
+
+from langchain.embeddings.base import Embeddings as LCEmbeddings
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.llms import AzureOpenAI
+from langchain.base_language import BaseLanguageModel
+
+from core.lifecycle import Lifecycle
+
+
+class BaseLangChainManager(Lifecycle, ABC):
+    def __init__(self) -> None:
+        super().__init__()
+
+    @abstractmethod
+    def get_embedding(self) -> LCEmbeddings:
+        pass
+
+    @abstractmethod
+    def get_llm(self) -> BaseLanguageModel:
+        pass
+
+
+class LangChainAzureManager(BaseLangChainManager):
+    def __init__(self) -> None:
+        super().__init__()
+
+    # Override
+    def get_embedding(self) -> LCEmbeddings:
+        return OpenAIEmbeddings(client=None, chunk_size=1)
+
+    # Override
+    def get_llm(self) -> BaseLanguageModel:
+        return AzureOpenAI(
+            deployment_name="text-davinci-003",
+            # model_name="text-davinci-003",
+            model="text-davinci-003",
+            client=None,
+        )

llama/context.py

@@ -0,0 +1,61 @@
+from llama_index import ServiceContext, LLMPredictor, LangchainEmbedding
+from type import Optional
+from core.lifecycle import Lifecycle
+from langchain.manager import BaseLangChainManager
+
+
+class ServiceContextManager(Lifecycle):
+    service_context: Optional[ServiceContext]
+
+    def __init__(self, manager: BaseLangChainManager) -> None:
+        super().__init__()
+        self.manager = manager
+        self.service_context = None
+
+    def get_service_context(self) -> ServiceContext:
+        if self.lifecycle_state.is_started():
+            raise KeyError(
+                "incorrect lifecycle state: {}".format(self.lifecycle_state.phase)
+            )
+        if self.service_context is None:
+            raise ValueError(
+                "service context is not ready, check for lifecycle statement"
+            )
+        return self.service_context
+
+    def do_init(self) -> None:
+        # define embedding
+        embedding = LangchainEmbedding(self.manager.get_embedding())
+        # define LLM
+        llm_predictor = LLMPredictor(llm=self.manager.get_llm())
+        # configure service context
+        self.service_context = ServiceContext.from_defaults(
+            llm_predictor=llm_predictor, embed_model=embedding
+        )
+
+    def do_start(self) -> None:
+        pass
+
+    def do_stop(self) -> None:
+        pass
+
+    def do_dispose(self) -> None:
+        pass
+
+
+class StorageContextManager(Lifecycle):
+    def __init__(self, dataset_path: Optional[str] = "./dataset") -> None:
+        super().__init__()
+        self.dataset_path = dataset_path
+
+    def do_init(self) -> None:
+        pass
+
+    def do_start(self) -> None:
+        pass
+
+    def do_stop(self) -> None:
+        pass
+
+    def do_dispose(self) -> None:
+        pass

llama/index.py

@@ -0,0 +1,18 @@
+from core.lifecycle import Lifecycle
+from llama.context import ServiceContextManager
+from llama_index.indices.vector_store import VectorStoreIndex
+from typing import Optional
+
+
+class IndexManager(Lifecycle):
+    index: Optional[VectorStoreIndex]
+
+    def __init__(self, context_manager: ServiceContextManager) -> None:
+        super().__init__()
+        self.index = None
+        self.context_manager = context_manager
+
+    def get_index(self) -> Optional[VectorStoreIndex]:
+        if not self.lifecycle_state.is_started():
+            raise Exception("Lifecycle state is not correct")
+        return self.index

llama/vector_storage.py

@@ -0,0 +1,18 @@
+from core.lifecycle import Lifecycle
+
+
+class VectorStorageManager(Lifecycle):
+    def __init__(self) -> None:
+        super().__init__()
+
+    def do_init(self) -> None:
+        pass
+
+    def do_start(self) -> None:
+        pass
+
+    def do_stop(self) -> None:
+        pass
+
+    def do_dispose(self) -> None:
+        pass