[Feature] Add support for RAG evaluation (#1154)

Co-authored-by: Deven Patel <deven298@yahoo.com>
Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>

embedchain/utils/eval.py

@@ -0,0 +1,17 @@
+from enum import Enum
+from typing import Optional
+
+from pydantic import BaseModel
+
+
+class EvalMetric(Enum):
+    CONTEXT_RELEVANCY = "context_relevancy"
+    ANSWER_RELEVANCY = "answer_relevancy"
+    GROUNDEDNESS = "groundedness"
+
+
+class EvalData(BaseModel):
+    question: str
+    contexts: list[str]
+    answer: str
+    ground_truth: Optional[str] = None  # Not used as of now

embedchain/utils/misc.py

@@ -201,7 +201,8 @@ def detect_datatype(source: Any) -> DataType:
     formatted_source = format_source(str(source), 30)
 
     if url:
-        from langchain.document_loaders.youtube import ALLOWED_NETLOCK as YOUTUBE_ALLOWED_NETLOCS
+        from langchain.document_loaders.youtube import \
+            ALLOWED_NETLOCK as YOUTUBE_ALLOWED_NETLOCS
 
         if url.netloc in YOUTUBE_ALLOWED_NETLOCS:
             logging.debug(f"Source of `{formatted_source}` detected as `youtube_video`.")