Update app.py

app.py

@@ -10,6 +10,10 @@ from langchain.llms import OpenAI
 from langchain.chains.question_answering import load_qa_chain
 from langchain.chat_models import ChatOpenAI
 
+# Set your OpenAI API key here
+OPENAI_API_KEY = 'your_openai_api_key_here'
+os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY
+
 css_style = """
 .gradio-container {
     font-family: "IBM Plex Mono";
@@ -30,10 +34,7 @@ def run(uploaded_files):
     print(all_files)
     return all_files
 
-def createAnswer(files, designation, openaikey):
-    # Set the OpenAI API key as an environment variable
-    os.environ['OPENAI_API_KEY'] = openaikey.strip()
-
+def createAnswer(files, designation):
     # Initialize the Docs object with the OpenAI API key
     docs = Docs(llm='gpt-3.5-turbo')
 
@@ -59,13 +60,10 @@ with gr.Blocks(css=css_style) as demo:
     This tool is under active development and currently uses many tokens - up to 10,000
     for a single query. That is $0.10-0.20 per query, so please be careful!
     Porting it to Llama.cpp soon for saved cost.
-    1. Enter API Key ([What is that?](https://platform.openai.com/account/api-keys))
-    2. Upload your Resumes (Try a few resumes/cv to try < 5)
-    3. Provide Designation for which you are hiring
+    1. Upload your Resumes (Try a few resumes/cv to try < 5)
+    2. Provide Designation for which you are hiring
     """)
 
-    openaikey = gr.Text(
-        label='Your OpenAI Api Key', value="")
     position = gr.Text(
         label='Position/Designation for which you are hiring for', value="")
 
@@ -78,7 +76,7 @@ with gr.Blocks(css=css_style) as demo:
     ask = gr.Button("Find Top Candidate")
     answer = gr.Markdown(label="Result",  elem_classes='answerText')
     ask.click(fn=createAnswer, inputs=[
-              uploaded_files, position, openaikey], outputs=[answer])
+              uploaded_files, position], outputs=[answer])
 
 demo.queue(concurrency_count=20)
 demo.launch(show_error=True)