Update Index.py

Index.py

@@ -1,5 +1,5 @@
 from fastapi import FastAPI
-from pydantic import BaseModel
+#from pydantic import BaseModel
 
 # from transformers import pipeline
 from txtai.embeddings import Embeddings
@@ -227,11 +227,11 @@ def _search(query, extractor, question=None):
     return extractor([("answer", query, _prompt(question), False)])[0][1]
 
 
-class ModelOutputEvaluate(BaseModel):
-    question: str
-    answer: str
-    domain: str
-    context: str
+# class ModelOutputEvaluate(BaseModel):
+#     question: str
+#     answer: str
+#     domain: str
+#     context: str
 
 class BasePromptContext:
     def __init__(self):
@@ -271,11 +271,11 @@ Please provide your grading for the correctness and explain you gave the particu
         
         
 class Evaluater:
-    def __init__(self, item: ModelOutputEvaluate):
-        self.question = item.question
-        self.answer = item.answer
-        self.domain = item.domain
-        self.context = item.context
+    def __init__(self, item):
+        self.question = item["question"]
+        self.answer = item["answer"]
+        self.domain = item["domain"]
+        self.context = item["context"]
         self.llm=HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature":1, "max_length":1000000})
 
     def get_prompt_template(self):
@@ -291,8 +291,7 @@ class Evaluater:
         return score
 
 # Create extractor instance
-@app.post("/evaluate/")
-async def create_evaluation_scenario(item: ModelOutputEvaluate):
+def _create_evaluation_scenario(item):
     output = {
         "input": item,
         "score" : Evaluater(item).evaluate()
@@ -301,7 +300,7 @@ async def create_evaluation_scenario(item: ModelOutputEvaluate):
 
 
 @app.get("/rag")
-def rag(domain: str, question: str):
+def rag(domain: str, question: str, evaluate: bool):
     print()
     db_exists = _check_if_db_exists(db_path=f"{os.getcwd()}/index/{domain}/documents")
     print(db_exists)