add dockerfile

separated code

main.py

@@ -1,12 +1,10 @@
 from jobs import getJobs
-from ai import generate
-from google.genai.errors import ServerError, ClientError
 from alert import send_email
-import json
-import time
+from filter import filter_jobs
 import os
 import logging
 from random import shuffle
+import pandas as pd
 
 logging.basicConfig(
     level=logging.WARNING, format="%(asctime)s - %(levelname)s - %(message)s"
@@ -16,110 +14,31 @@ SENDER = os.getenv("smtp_email")
 PASSWORD = os.getenv("smtp_password")
 RECEIVER = os.getenv("receiver_email")
 api_keys = os.getenv("api_keys").split(",")
-
-good_fit_jobs = []
-
-# stats
-total_fail = 0
-total_fail_overload = 0
-total_overload = 0
-total_empty_response = 0
-total_fail_empty_response = 0
-
 shuffle(api_keys)
 
+all_jobs = pd.DataFrame()
+good_fit_jobs = []
+
 with open("instruction.txt", "r") as f:
     CV = f.read()
 
 
-def get_jobs(job_title, cv, results_wanted, hours_old):
-    global total_fail, total_fail_overload, total_overload, total_empty_response, total_fail_empty_response
-    key_number = 0
-
+def get_jobs(job_title, results_wanted, hours_old):
+    global all_jobs
     jobs = getJobs(job_title, results_wanted, hours_old)
-    for i, job in jobs.iterrows():
-        print("index is :", i)  # for debugging
-
-        if (i + 1) % 10 == 0 and i != 0:
-            logging.warning("sleeping to avoid API rate limits")
-            time.sleep(60)
-        try_count = 3
-
-        while try_count > 0:
-
-            try:
-                cleaned_description = "\n".join(
-                    [line for line in job["description"].splitlines() if line.strip()]
-                )
-                ai_response = generate(cleaned_description, cv, api_keys[key_number])
-                ai_response_dict = json.loads(ai_response)
-                break
-
-            except json.JSONDecodeError as e:
-                try_count -= 1
-                total_empty_response += 1
-                if try_count == 0:
-                    total_fail += 1
-                    total_fail_empty_response += 1
-
-                logging.warning("Sleeping after JSONDecodeError")
-                time.sleep(6)
-
-            except ServerError as e:
-
-                if e.details["error"]["code"] == 503:
-                    try_count -= 1
-                    total_overload += 1
-                    if try_count == 0:
-                        total_fail += 1
-                        total_fail_overload += 1
-                    logging.warning("sleeping to after The model is overloaded.")
-                    print(e.details)
-                    time.sleep(10)
-                else:
-                    logging.critical(e.details)
-                    return 1
-
-            except ClientError as e:
-                if e.details["error"]["code"] == 429:
-                    logging.warning("api limit hit")
-                    key_number += 1
-                    if key_number > len(api_keys) - 1:
-                        logging.critical("All api keys hit the limit")
-                        return 1
-                else:
-                    logging.critical(e.details)
-                    return 1
-
-        else:
-            logging.critical("All attempts failed")
-            continue
-
-        if ai_response_dict["percentage"] > 50:
-            good_fit_jobs.append(
-                {
-                    "title": job["title"],
-                    "url": job["job_url"],
-                    "percentage": ai_response_dict["percentage"],
-                    "why I'm I a good fit": ai_response_dict["why I'm I a good fit"],
-                    "what I'm I missing": ai_response_dict["what I'm I missing"],
-                }
-            )
-
-
-def print_stats():
-    stats = f"""total fail: {total_fail}
-total empty responses: {total_empty_response} fail: {total_fail_empty_response}
-Total overloads:       {total_overload}       fail: {total_fail_overload}"""
-    print(stats)
+    all_jobs = pd.concat([all_jobs, jobs], ignore_index=True)
 
 
 if __name__ == "__main__":
-    get_jobs("devops", CV, results_wanted=30, hours_old=2)
-    get_jobs("backend", CV, results_wanted=30, hours_old=2)
-    get_jobs("software engineer", CV, results_wanted=30, hours_old=2)
+    get_jobs("devops", results_wanted=30, hours_old=2)
+    get_jobs("backend", results_wanted=30, hours_old=2)
+    get_jobs("software engineer", results_wanted=30, hours_old=2)
+    get_jobs("cloud", results_wanted=30, hours_old=2)
+    get_jobs("sre", results_wanted=30, hours_old=2)
+    get_jobs("intern", results_wanted=30, hours_old=2)
+    all_jobs.drop_duplicates(inplace=True, ignore_index=True)
+    filter_jobs(all_jobs, CV, api_keys, good_fit_jobs)
     if len(good_fit_jobs) > 0:
         send_email(SENDER, RECEIVER, PASSWORD, good_fit_jobs)
     else:
         print("no good fit jobs")
-    print_stats()