Create app.py

app.py

@@ -0,0 +1,87 @@
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.messages import HumanMessage
+from langchain_core.messages import AIMessage
+from langchain.memory import ChatMessageHistory
+from langchain_openai import AzureChatOpenAI
+from pypdf import PdfReader
+import os
+import gradio as gr
+
+# chat = AzureChatOpenAI(azure_deployment = "GPT-3")
+
+def extract_text( pdf_path):
+    # creating a pdf reader object
+    reader = PdfReader(pdf_path)
+    all_text = ""
+
+    for page in reader.pages:
+        all_text += page.extract_text()
+    return all_text
+
+def get_response( candidate, resume, jd, chat_history):
+    
+    resume = extract_text(resume)
+    jd = extract_text(jd)
+
+    prompt = ChatPromptTemplate.from_messages(
+        [
+            (
+                "system",
+                """Your Task is Perform as intelligent interviewer, Your Task is ask question to the resume's candidate by following candidate Answer.
+                  at the end exit with greeting to the candidate.
+                **Ask question follow up on the candidate response. get chat history.**
+                """,
+            ),
+            MessagesPlaceholder(variable_name="messages"),
+        ]
+    )
+
+    chain = prompt | chat  
+
+
+    answer = chain.invoke(
+        {
+            "messages": [
+                HumanMessage(
+                    content=f" job description :{jd}\n Resume :{resume}"
+                ),
+                AIMessage(content=f"Perform as intelligent interviewer, Your Task is ask question to the resume's candidate by following candidate Answer:"),
+                HumanMessage(content=candidate),
+            ],
+        }
+    )
+    # print("INTERVIEWER :", answer.content)
+    # chat_history.append({"candidate":candidate,"interviewer":answer.content })
+
+    result = answer.content
+    chat_history.append({'candidate':candidate, "interviewer": result})
+    print("chat_history", chat_history)
+    return "", chat_history
+
+def gradio_interface() -> None:
+    """Create a Gradio interface for the chatbot."""
+    with gr.Blocks(css = "style.css" ,theme="freddyaboulton/test-blue") as demo:
+
+        gr.HTML("""<center class="darkblue" text-align:center;padding:30px;'><center>
+        <center><h1 class ="center" style="color:#fff">ADOPLE AI</h1></center>
+        <br><center><h1 style="color:#fff">Screening Assistant Chatbot</h1></center>""")
+
+        chatbot = gr.Chatbot()
+
+        with gr.Row():
+            with gr.Column(scale=1):    
+                msg = gr.Textbox(label="Question")
+      
+        with gr.Row():
+            with gr.Column(scale=0.15):
+                resume = gr.File(label="Resume")
+            with gr.Column(scale=0.15):
+                jd = gr.File(label="Job Description")
+            with gr.Column(scale=0.85):
+                clear = gr.ClearButton([msg, chatbot])
+
+        msg.submit(get_response, [msg, chatbot, resume, jd], [msg, chatbot])
+
+    demo.launch(debug =True, share=True)   
+
+gradio_interface()