start building out specific job-candidate match functionality

main.py

@@ -18,7 +18,7 @@ from localStoragePy import localStoragePy
 localStorage = localStoragePy('pathfinder', 'text')
 
 from scrape_onet import get_onet_code, get_onet_description, get_onet_tasks
-from match_utils import neighborhoods, get_resume, skillNER, sim_result_loop, get_links, coSkillEmbed
+from match_utils import neighborhoods, get_resume, skillNER, sim_result_loop, get_links, coSkillEmbed, sim_result_loop_jobFinder
 from user_utils import Hash
 
 # APP SETUP
@@ -143,19 +143,22 @@ def get_matches(request: Request):
 @app.post('/find-my-match/', response_class=HTMLResponse)
 async def post_matches(request: Request, bt: BackgroundTasks, resume: UploadFile = File(...)):
     
-    resume = get_resume(resume)
-    username = localStorage.getItem('username')
-    db = pd.read_csv('static/res_embeddings.csv')
-    
     def add_data_to_db(resume, db, username):
         embeds = format(coSkillEmbed(resume)).replace('[[','').replace(']]','').split(',')
         db.iloc[db['username']== username,5:] = embeds
         db.to_csv('static/res_embeddings.csv', index=False)
+
+    resume = get_resume(resume)
+    username = localStorage.getItem('username')
+    db = pd.read_csv('static/res_embeddings.csv')
     
     skills = await skillNER(resume)
     simResults = await sim_result_loop(resume)
     links = get_links(simResults[0])
 
+    job_matches = await sim_result_loop_jobFinder(resume)
+    print(job_matches)
+
     bt.add_task(add_data_to_db, resume, db, username)
 
     return templates.TemplateResponse('find_my_match.html', context={'request': request, 'resume': resume, 'skills': skills, 'simResults': simResults[0], 'links': links})
@@ -195,4 +198,8 @@ async def post_matches(request: Request, bt: BackgroundTasks, jobdesc: UploadFil
 def find_hire(request: Request):
     jobselection = str(request.url).split("=")[1].replace('HTTP/1.1', '').replace("-", " ")
     print(jobselection)
-    return templates.TemplateResponse('find_hire.html', context={'request': request, 'jobselection': jobselection})
+    return templates.TemplateResponse('find_hire.html', context={'request': request, 'jobselection': jobselection})
+
+@app.get("/find-job/", response_class=HTMLResponse)
+def find_job(request: Request):
+    pass

match_utils.py

@@ -118,3 +118,23 @@ def get_links(simResults):
     titles = simResults["JobTitle"]
     [links.append("https://www.onetonline.org/link/summary/" + get_onet_code(title)) for title in titles]
     return links
+
+async def sim_result_loop_jobFinder(resume):
+    embeds = coSkillEmbed(resume)
+    def cosine(A, B):
+        return np.dot(A,B)/(norm(A)*norm(B))
+    def format_sim(sim):
+        return "{:0.2f}".format(sim)
+    jobdat = pd.read_csv('static/jd_embeddings.csv')
+    jobembeds = jobdat.iloc[:,5:].dropna()
+    simResults = []
+    [simResults.append(cosine(np.array(embeds), np.array(jobembeds.iloc[i,:]))) for i in range(len(jobembeds))]
+    simResults = pd.DataFrame(simResults)
+    simResults['job_id'] = jobdat['id']
+    simResults = simResults.iloc[:,[1,0]]
+    simResults.columns = ['job_id', 'Similarity']
+    simResults = simResults.sort_values(by = "Similarity", ascending = False)
+    simResults.reset_index(drop=True, inplace=True)
+    for x in range(len(simResults)):
+        simResults.iloc[x,1] = format_sim(simResults.iloc[x,1])
+    return simResults