initial commit

app.py

@@ -0,0 +1,133 @@
+import streamlit as st
+from azure.storage.blob import BlobServiceClient
+from azure.cosmos import CosmosClient, exceptions
+import os
+
+st.set_page_config(layout="wide")
+st.markdown(
+"""
+<style>
+    [data-testid=column]{
+        text-align: left;
+        display: flex;
+        align-items: center;
+        justify-content: center;
+    }
+</style>
+""",
+    unsafe_allow_html=True,
+)
+col1, col2 = st.columns([2, 1])
+
+
+col1.title("Interview chatbot evaluations")
+col2.image("https://www.workgenius.com/wp-content/uploads/2023/03/WorkGenius_navy-1.svg")
+
+if "selected_item" not in st.session_state:
+    st.session_state["selected_item"] = None
+
+if "top_number" not in st.session_state:
+    st.session_state["top_number"] = 10
+
+endpoint = "https://wg-candidate-data.documents.azure.com:443/"
+key = os.getenv("CONNECTION_DB")
+client = CosmosClient(endpoint, key)
+database = client.get_database_client("ToDoList")
+container = database.get_container_client("JobData")
+candidate_container = database.get_container_client("Items")
+
+def get_candidates(id, candidate_container):
+    candidate_query = f"""
+    SELECT *
+    FROM c
+    WHERE c.job_description_id = '{id}'
+    """
+    
+    query_result = list(candidate_container.query_items(query=candidate_query, enable_cross_partition_query=True))
+    return query_result
+
+
+def get_open_and_closed_candidates(id, nr_of_candidates, candidate_container):
+    candidate_query = f"""
+    SELECT *
+    FROM c
+    WHERE c.job_description_id = '{id}' AND c.interview_conducted = true
+    """
+    
+    query_result = list(candidate_container.query_items(query=candidate_query, enable_cross_partition_query=True))
+    return nr_of_candidates-len(query_result),len(query_result) 
+
+# endpoint = "https://wg-candidate-data.documents.azure.com:443/"
+# key = os.getenv("CONNECTION_DB")
+# client = CosmosClient(endpoint, key)
+# database = client.get_database_client("ToDoList")
+# container = database.get_container_client("JobData")
+# candidate_container = database.get_container_client("Items")
+if not st.session_state["selected_item"]:
+    txt_input_cols = st.columns(3)
+    with txt_input_cols[0]:
+        st.text_input("Search for job titles", key="title_search")
+    query = f"""
+    SELECT TOP {st.session_state["top_number"]} * 
+    FROM c 
+    WHERE CONTAINS(c.title, '{st.session_state["title_search"]}')
+    ORDER BY c.timestamp DESC
+    """
+    items = list(container.query_items(query=query, enable_cross_partition_query=True))
+    with st.container():
+        col1, col2, col3, col4, col5 = st.columns([2,1,1,1,1])
+        col1.subheader("Job title")
+        col2.subheader("Applicants")
+        col3.subheader("Open")
+        col4.subheader("Completed")
+        col5.subheader("Overview")
+    for i, item in enumerate(items):
+        cols = st.columns([2,1,1,1,1])
+        open, closed = get_open_and_closed_candidates(item["id"], item["number_of_applicants"], candidate_container)
+        with st.container():
+            for j in range(5):
+                with cols[j]:
+                    if(j == 0):
+                        st.text(item["title"])
+                    elif(j == 1):
+                        st.text(item["number_of_applicants"])
+                    elif(j == 2):
+                        st.text(open)
+                    elif(j == 3):
+                        st.text(closed)
+                    elif(j == 4):
+                        if st.button("Go to overview",use_container_width=True,key="btn_row_"+str(i)):
+                            st.session_state["selected_item"] = item
+                            st.rerun()
+    if st.button("Load more"):
+        st.session_state["top_number"] = len(items)+10
+        st.rerun()
+        
+else:
+    job_detail_cols_title = st.columns([1,1,1])
+    with job_detail_cols_title[0]:
+        if st.button("Go back to list view"):
+            st.session_state["selected_item"] = None
+            st.session_state["top_number"] = 10
+            st.rerun()
+    with job_detail_cols_title[1]:
+        st.subheader("Job: " + st.session_state["selected_item"]["title"])
+    candidate_db_items = get_candidates(st.session_state["selected_item"]["id"], candidate_container)
+    job_detail_cols_content = st.columns([1,5,1])
+    with job_detail_cols_content[1]:
+        st.subheader("Recruiter Email: " + st.session_state["selected_item"]["evaluation_email"])
+        if len(st.session_state["selected_item"]["question_one"])>0:
+            st.subheader("First question: " + st.session_state["selected_item"]["question_one"])
+        if  len(st.session_state["selected_item"]["question_two"])>0:
+            st.subheader("Second question: " + st.session_state["selected_item"]["question_two"])
+        if  len(st.session_state["selected_item"]["question_three"])>0:
+            st.subheader("Thrid question: " + st.session_state["selected_item"]["question_three"])
+        for i, can_item in enumerate(candidate_db_items):
+            st.subheader("Candidate: "+can_item["name"])
+            if can_item["interview_conducted"]:
+                st.text("The candidate "+can_item["name"]+ " has already completed the interview and this is the AI summary:")
+                st.text(can_item["ai_summary"])
+            else:
+                st.text("The candidate "+can_item["name"]+ " has not yet completed the interview.")
+                st.text("Link for the interview chatbot:")
+                st.text("https://tensora.ai/workgenius/cv-evaluation2/?job="+can_item["id"])