feat: upgrade import name & fix

To fit ragas & langchain version bump
kubeagi · Mar 1, 2024 · 4652b14 · 4652b14
1 parent 3756c41
commit 4652b14
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Showing 4 changed files with 33 additions and 38 deletions.
diff --git a/libs/core/kubeagi_core/evaluation/ragas_eval.py b/libs/core/kubeagi_core/evaluation/ragas_eval.py
@@ -17,12 +17,12 @@
 import os
 import pandas as pd
 from datasets import Dataset
-from langchain.chat_models import ChatOpenAI
-from langchain.embeddings import OpenAIEmbeddings as BaseOpenAIEmbeddings
+from langchain_openai import ChatOpenAI
+from langchain_openai import OpenAIEmbeddings as BaseOpenAIEmbeddings
 
 from ragas import evaluate
-from ragas.embeddings import RagasEmbeddings
-from ragas.llms import LangchainLLM, RagasLLM
+from ragas.embeddings import BaseRagasEmbeddings
+from ragas.llms import BaseRagasLLM
 from ragas.metrics import (
     AnswerCorrectness,
     AnswerRelevancy,
@@ -34,9 +34,8 @@
 )
 from ragas.evaluation import Result
 from ragas.metrics.base import Metric
-from ragas.utils import NO_KEY
-from ragas.exceptions import OpenAIKeyNotFound
 
+NO_KEY = "NO_KEY"
 
 class RagasEval:
     """
@@ -58,8 +57,8 @@ class RagasEval:
     llm_model: str = "gpt-3.5-turbo"
     embedding_model: str = "text-embedding-ada-002"
 
-    llm: RagasLLM
-    embeddings: RagasEmbeddings
+    llm: BaseRagasLLM
+    embeddings: BaseRagasEmbeddings
 
     def __init__(
         self,
@@ -87,12 +86,10 @@ def __init__(
         )
 
         # Initialize judge llm
-        self.llm = LangchainLLM(
-            llm=ChatOpenAI(
+        self.llm = ChatOpenAI(
                 model_name=self.llm_model,
                 openai_api_key=self.api_key,
                 openai_api_base=self.api_base,
-            )
         )
 
         # Initialize judge embedding
@@ -203,7 +200,7 @@ def _metrics(
 
 
 # OpenAIEmbeddings inherits from
-class OpenAIEmbeddings(BaseOpenAIEmbeddings, RagasEmbeddings):
+class OpenAIEmbeddings(BaseOpenAIEmbeddings, BaseRagasEmbeddings):
     api_key: str = NO_KEY
 
     def __init__(
@@ -226,4 +223,4 @@ def validate_api_key(self):
             if os_env_key != NO_KEY:
                 self.api_key = os_env_key
             else:
-                raise OpenAIKeyNotFound
+                raise ValueError("openai api key must be provided")
diff --git a/libs/ragas_once/pyproject.toml b/libs/ragas_once/pyproject.toml
@@ -2,8 +2,8 @@
 requires = [
     "setuptools>=61.0",
     "setuptools-scm",
-    "ragas==0.0.22",
-    "langchain==0.0.354"
+    "ragas",
+    "langchain"
 ]
 build-backend = "setuptools.build_meta"
 
@@ -22,8 +22,8 @@ classifiers = [
     "Operating System :: OS Independent",
 ]
 dependencies = [
-    "langchain==0.0.354",
-    "ragas==0.0.22",
+    "langchain",
+    "ragas",
 ]
 
 [project.scripts]

diff --git a/libs/ragas_once/src/ragas_once/embeddings/openai.py b/libs/ragas_once/src/ragas_once/embeddings/openai.py
@@ -14,13 +14,12 @@
 
 import os
 
-from langchain.embeddings import OpenAIEmbeddings as BaseOpenAIEmbeddings
-from ragas.embeddings import RagasEmbeddings
-from ragas.exceptions import OpenAIKeyNotFound
-from ragas.utils import NO_KEY
+from langchain_openai.embeddings import OpenAIEmbeddings as BaseOpenAIEmbeddings
+from ragas.embeddings import BaseRagasEmbeddings
 
+NO_KEY = "NO_KEY"
 
-class OpenAIEmbeddings(BaseOpenAIEmbeddings, RagasEmbeddings):
+class OpenAIEmbeddings(BaseOpenAIEmbeddings, BaseRagasEmbeddings):
     api_key: str = NO_KEY
 
     def __init__(
@@ -43,4 +42,4 @@ def validate_api_key(self):
             if os_env_key != NO_KEY:
                 self.api_key = os_env_key
             else:
-                raise OpenAIKeyNotFound
+                raise ValueError("openai api key must be provided")
diff --git a/libs/ragas_once/src/ragas_once/eval.py b/libs/ragas_once/src/ragas_once/eval.py
@@ -16,17 +16,17 @@
 
 import pandas as pd
 from datasets import Dataset
-from langchain.chat_models import ChatOpenAI
+from langchain_openai import ChatOpenAI, OpenAIEmbeddings
 from ragas import evaluate
-from ragas.embeddings import RagasEmbeddings
-from ragas.llms import LangchainLLM, RagasLLM
+from ragas.llms import BaseRagasLLM
+from ragas.embeddings import BaseRagasEmbeddings
 from ragas.metrics import (AnswerCorrectness, AnswerRelevancy,
                            AnswerSimilarity, ContextPrecision, ContextRecall,
                            ContextRelevancy, Faithfulness)
 from ragas.metrics.base import Metric
-from ragas.utils import NO_KEY
 from ragas_once.embeddings.openai import OpenAIEmbeddings
 
+NO_KEY = "NO_KEY"
 
 class RagasEval:
     """
@@ -46,8 +46,8 @@ class RagasEval:
     llm_model: str = "gpt-3.5-turbo"
     embedding_model: str = "text-embedding-ada-002"
 
-    llm: RagasLLM
-    embeddings: RagasEmbeddings
+    llm: BaseRagasLLM
+    embeddings: BaseRagasEmbeddings
 
     def __init__(
         self,
@@ -65,21 +65,20 @@ def __init__(
         )
 
         # Initialize judge llm
-        self.llm = LangchainLLM(
-            llm=ChatOpenAI(
-                model_name=self.llm_model,
-                openai_api_key=self.api_key,
-                openai_api_base=self.api_base,
+        self.llm = ChatOpenAI(
+                model=self.llm_model,
+                api_key=self.api_key,
+                base_url=self.api_base,
             )
-        )
 
         # Initialize judge embedding
         self.embeddings = OpenAIEmbeddings(
-            api_key=self.api_key,
-            api_base=self.api_base,
-            model_name=self.embedding_model,
+                api_key=self.api_key,
+                base_url=self.api_base,
+                model=self.embedding_model,
         )
 
+
     def prepare_dataset(self, dataset: str = NO_KEY) -> Dataset:
         """
         Prepares the dataset for evaluation.