Update backend.py

backend.py

@@ -7,7 +7,7 @@ from langchain.prompts import PromptTemplate
 from langchain_google_genai import GoogleGenerativeAI
 
 
-os.environ["GOOGLE_API_KEY"] = "AIzaSyCYGj5e2eAQbUi9HtuMaW0LDSnDuxLG54U"
+api_key = "AIzaSyCYGj5e2eAQbUi9HtuMaW0LDSnDuxLG54U"
 
 
 class InvoicePipeline:
@@ -19,14 +19,14 @@ class InvoicePipeline:
     # This funcition will help in extracting and run the code, and will produce a dataframe for us
     def run(self) -> pd.DataFrame:
         # We have defined the way the data has to be returned
-        df = pd.DataFrame(
+        df = pd.DataFrame({
             "Invoice ID": pd.Series(dtype = "int"),
             "DESCRIPTION": pd.Series(dtype = "str"),
             "Issue Data": pd.Series(dtype = "str"),
             "UNIT PRICE": pd.Series(dtype = "str"),
             "AMOUNT": pd.Series(dtype = "int"),
             "Bill For": pd.Series(dtype = "str"),
-            "From": pd.Series(dtype =" str"),
+            "From": pd.Series(dtype ="str"),
             "Terms": pd.Series(dtype = "str")}
         )
 
@@ -41,7 +41,7 @@ class InvoicePipeline:
     # The default template that the machine will take
     def _get_default_prompt_template(self) -> PromptTemplate:
         template = """Extract all the following values: Invoice ID, DESCRIPTION, Issue Data,UNIT PRICE, AMOUNT, Bill for, From and Terms for: {pages}
-        Expected Outcome: remove any dollar symbols {{"Invoice ID":"12341234", "DESCRIPTION": "UNIT PRICE", "AMOUNT": "3", "Date": "2/1/2021", "AMOUNT": "100", "Bill For": "Paras", "From": "Coca Cola", "Terms" : "Net for 30 days"}}
+        Expected Outcome: remove any dollar symbols {{"Invoice ID":"12341234", "DESCRIPTION": "UNIT PRICE", "AMOUNT": "3", "Date": "2/1/2021", "AMOUNT": "100", "Bill For": "Dev", "From": "Coca Cola", "Terms" : "Net for 30 days"}}
         """
 
         prompt_template = PromptTemplate(input_variables = ["pages"], template = template)
@@ -58,6 +58,4 @@ class InvoicePipeline:
 
     def _extract_data_from_llm(self, raw_data:str) -> str:
         resp = self._llm(self._prompt_template.format(pages = raw_data))
-        return resp
-
-        
+        return resp