docs: update docstrings (#565)

embedchain/apps/OpenSourceApp.py

@@ -15,43 +15,64 @@ gpt4all_model = None
 @register_deserializable
 class OpenSourceApp(EmbedChain):
     """
-    The OpenSource app.
-    Same as App, but uses an open source embedding model and LLM.
+    The embedchain Open Source App.
+    Comes preconfigured with the best open source LLM, embedding model, database.
 
-    Has two function: add and query.
-
-    adds(data_type, url): adds the data from the given URL to the vector db.
+    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: OpenSourceAppConfig = None,
+        llm_config: BaseLlmConfig = None,
         chromadb_config: Optional[ChromaDbConfig] = None,
         system_prompt: Optional[str] = None,
     ):
         """
-        :param config: OpenSourceAppConfig instance to load as configuration. Optional.
-        `ef` defaults to open source.
-        :param system_prompt: System prompt string. Optional.
+        Initialize a new `CustomApp` instance.
+        Since it's opinionated you don't have to choose a LLM, database and embedder.
+        However, you can configure those.
+
+        :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: OpenSourceAppConfig, optional
+        :param llm_config: Allows you to configure the LLM, e.g. how many documents to return.
+        example: `from embedchain.config import LlmConfig`, defaults to None
+        :type llm_config: BaseLlmConfig, optional
+        :param chromadb_config: Allows you to configure the open source database,
+        example: `from embedchain.config import ChromaDbConfig`, defaults to None
+        :type chromadb_config: Optional[ChromaDbConfig], optional
+        :param system_prompt: System prompt that will be provided to the LLM as such.
+        Please don't use for the time being, as it's not supported., defaults to None
+        :type system_prompt: Optional[str], optional
+        :raises TypeError: `OpenSourceAppConfig` or `LlmConfig` invalid.
         """
         logging.info("Loading open source embedding model. This may take some time...")  # noqa:E501
         if not config:
             config = OpenSourceAppConfig()
 
         if not isinstance(config, OpenSourceAppConfig):
-            raise ValueError(
+            raise TypeError(
                 "OpenSourceApp needs a OpenSourceAppConfig passed to it. "
                 "You can import it with `from embedchain.config import OpenSourceAppConfig`"
             )
 
-        if not config.model:
-            raise ValueError("OpenSourceApp needs a model to be instantiated. Maybe you passed the wrong config type?")
+        if not llm_config:
+            llm_config = BaseLlmConfig(model="orca-mini-3b.ggmlv3.q4_0.bin")
+        elif not isinstance(llm_config, BaseLlmConfig):
+            raise TypeError(
+                "The LlmConfig passed to OpenSourceApp is invalid. "
+                "You can import it with `from embedchain.config import LlmConfig`"
+            )
+        elif not llm_config.model:
+            llm_config.model = "orca-mini-3b.ggmlv3.q4_0.bin"
 
-        logging.info("Successfully loaded open source embedding model.")
-
-        llm = GPT4ALLLlm(config=BaseLlmConfig(model="orca-mini-3b.ggmlv3.q4_0.bin"))
+        llm = GPT4ALLLlm(config=llm_config)
         embedder = GPT4AllEmbedder(config=BaseEmbedderConfig(model="all-MiniLM-L6-v2"))
+        logging.error("Successfully loaded open source embedding model.")
         database = ChromaDB(config=chromadb_config)
 
         super().__init__(config, llm=llm, db=database, embedder=embedder, system_prompt=system_prompt)