Renamed apps/CustomApp.py to follow snake case convention (#678)

2023-09-27 04:59:46 +05:30
parent b8a838aee1
commit 4eb2c0e123
3 changed files with 2 additions and 2 deletions
--- a/embedchain/apps/custom_app.py
+++ b/embedchain/apps/custom_app.py
@@ -0,0 +1,83 @@
+from typing import Optional
+
+from embedchain.config import CustomAppConfig
+from embedchain.embedchain import EmbedChain
+from embedchain.embedder.base import BaseEmbedder
+from embedchain.helper.json_serializable import register_deserializable
+from embedchain.llm.base import BaseLlm
+from embedchain.vectordb.base import BaseVectorDB
+
+
+@register_deserializable
+class CustomApp(EmbedChain):
+    """
+    Embedchain's custom app allows for most flexibility.
+
+    You can craft your own mix of various LLMs, vector databases and embedding model/functions.
+
+    Methods:
+    add(source, data_type): adds the data from the given URL to the vector db.
+    query(query): finds answer to the given query using vector database and LLM.
+    chat(query): finds answer to the given query using vector database and LLM, with conversation history.
+    """
+
+    def __init__(
+        self,
+        config: Optional[CustomAppConfig] = None,
+        llm: BaseLlm = None,
+        db: BaseVectorDB = None,
+        embedder: BaseEmbedder = None,
+        system_prompt: Optional[str] = None,
+    ):
+        """
+        Initialize a new `CustomApp` instance. You have to choose a LLM, database and embedder.
+
+        :param config: Config for the app instance. This is the most basic configuration,
+        that does not fall into the LLM, database or embedder category, defaults to None
+        :type config: Optional[CustomAppConfig], optional
+        :param llm: LLM Class instance. example: `from embedchain.llm.openai import OpenAILlm`, defaults to None
+        :type llm: BaseLlm
+        :param db: The database to use for storing and retrieving embeddings,
+        example: `from embedchain.vectordb.chroma_db import ChromaDb`, defaults to None
+        :type db: BaseVectorDB
+        :param embedder: The embedder (embedding model and function) use to calculate embeddings.
+        example: `from embedchain.embedder.gpt4all_embedder import GPT4AllEmbedder`, defaults to None
+        :type embedder: BaseEmbedder
+        :param system_prompt: System prompt that will be provided to the LLM as such, defaults to None
+        :type system_prompt: Optional[str], optional
+        :raises ValueError: LLM, database or embedder has not been defined.
+        :raises TypeError: LLM, database or embedder is not a valid class instance.
+        """
+        # Config is not required, it has a default
+        if config is None:
+            config = CustomAppConfig()
+
+        if llm is None:
+            raise ValueError("LLM must be provided for custom app. Please import from `embedchain.llm`.")
+        if db is None:
+            raise ValueError("Database must be provided for custom app. Please import from `embedchain.vectordb`.")
+        if embedder is None:
+            raise ValueError("Embedder must be provided for custom app. Please import from `embedchain.embedder`.")
+
+        if not isinstance(config, CustomAppConfig):
+            raise TypeError(
+                "Config is not a `CustomAppConfig` instance. "
+                "Please make sure the type is right and that you are passing an instance."
+            )
+        if not isinstance(llm, BaseLlm):
+            raise TypeError(
+                "LLM is not a `BaseLlm` instance. "
+                "Please make sure the type is right and that you are passing an instance."
+            )
+        if not isinstance(db, BaseVectorDB):
+            raise TypeError(
+                "Database is not a `BaseVectorDB` instance. "
+                "Please make sure the type is right and that you are passing an instance."
+            )
+        if not isinstance(embedder, BaseEmbedder):
+            raise TypeError(
+                "Embedder is not a `BaseEmbedder` instance. "
+                "Please make sure the type is right and that you are passing an instance."
+            )
+
+        super().__init__(config=config, llm=llm, db=db, embedder=embedder, system_prompt=system_prompt)