[Refactor] Converge Pipeline and App classes (#1021)

Co-authored-by: Deven Patel <deven298@yahoo.com>

embedchain/config/__init__.py

@@ -1,12 +1,11 @@
 # flake8: noqa: F401
 
 from .add_config import AddConfig, ChunkerConfig
-from .apps.app_config import AppConfig
+from .app_config import AppConfig
 from .base_config import BaseConfig
 from .embedder.base import BaseEmbedderConfig
 from .embedder.base import BaseEmbedderConfig as EmbedderConfig
 from .llm.base import BaseLlmConfig
-from .pipeline_config import PipelineConfig
 from .vectordb.chroma import ChromaDbConfig
 from .vectordb.elasticsearch import ElasticsearchDBConfig
 from .vectordb.opensearch import OpenSearchDBConfig

embedchain/config/app_config.py

@@ -15,8 +15,9 @@ class AppConfig(BaseAppConfig):
         self,
         log_level: str = "WARNING",
         id: Optional[str] = None,
+        name: Optional[str] = None,
         collect_metrics: Optional[bool] = True,
-        collection_name: Optional[str] = None,
+        **kwargs,
     ):
         """
         Initializes a configuration class instance for an App. This is the simplest form of an embedchain app.
@@ -28,8 +29,6 @@ class AppConfig(BaseAppConfig):
         :type id: Optional[str], optional
         :param collect_metrics: Send anonymous telemetry to improve embedchain, defaults to True
         :type collect_metrics: Optional[bool], optional
-        :param collection_name: Default collection name. It's recommended to use app.db.set_collection_name() instead,
-        defaults to None
-        :type collection_name: Optional[str], optional
         """
-        super().__init__(log_level=log_level, id=id, collect_metrics=collect_metrics, collection_name=collection_name)
+        self.name = name
+        super().__init__(log_level=log_level, id=id, collect_metrics=collect_metrics, **kwargs)

embedchain/config/pipeline_config.py

@@ -1,38 +0,0 @@
-from typing import Optional
-
-from embedchain.helpers.json_serializable import register_deserializable
-
-from .apps.base_app_config import BaseAppConfig
-
-
-@register_deserializable
-class PipelineConfig(BaseAppConfig):
-    """
-    Config to initialize an embedchain custom `App` instance, with extra config options.
-    """
-
-    def __init__(
-        self,
-        log_level: str = "WARNING",
-        id: Optional[str] = None,
-        name: Optional[str] = None,
-        collect_metrics: Optional[bool] = True,
-    ):
-        """
-        Initializes a configuration class instance for an App. This is the simplest form of an embedchain app.
-        Most of the configuration is done in the `App` class itself.
-
-        :param log_level: Debug level ['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'], defaults to "WARNING"
-        :type log_level: str, optional
-        :param id: ID of the app. Document metadata will have this id., defaults to None
-        :type id: Optional[str], optional
-        :param collect_metrics: Send anonymous telemetry to improve embedchain, defaults to True
-        :type collect_metrics: Optional[bool], optional
-        :param collection_name: Default collection name. It's recommended to use app.db.set_collection_name() instead,
-        defaults to None
-        :type collection_name: Optional[str], optional
-        """
-        self._setup_logging(log_level)
-        self.id = id
-        self.name = name
-        self.collect_metrics = collect_metrics