Update app.py

app.py

@@ -104,12 +104,22 @@ vectordb = Chroma.from_documents(
 # define retriever
 retriever = vectordb.as_retriever(search_kwargs={"k": 2}, search_type="mmr")
 
-class FinalAnswer(BaseModel):
+class Answer(BaseModel):
     question: str = Field(description="the original question")
     answer: str = Field(description="the extracted answer")
 
-# Assuming you have a parser for the FinalAnswer class
-parser = PydanticOutputParser(pydantic_object=FinalAnswer)
+# Set up a PydanticOutputParser
+parser = PydanticOutputParser(pydantic_object=Answer)
+
+
+parser = PydanticOutputParser(pydantic_object=Answer)
+
+# Create a prompt with format instructions
+prompt = PromptTemplate(
+    template="Answer the user query.\n{format_instructions}\n{query}\n",
+    input_variables=["query"],
+    partial_variables={"format_instructions": parser.get_format_instructions()},
+)
 
 template = """
 Your name is Greta and you are a recycling chatbot with the objective to anwer questions from user in English or Spanish /