Delete backend

backend/agents/matcher.py

@@ -1,26 +0,0 @@
-# matcher.py
-
-from sentence_transformers import SentenceTransformer, util
-import re
-from collections import Counter
-
-model = SentenceTransformer("BAAI/bge-small-en-v1.5")
-
-def compute_match(resume_text: str, job_desc: str) -> float:
-    emb_resume = model.encode(resume_text, convert_to_tensor=True, normalize_embeddings=True)
-    emb_job = model.encode(job_desc, convert_to_tensor=True, normalize_embeddings=True)
-    score = util.cos_sim(emb_resume, emb_job).item()
-    return round(float(score), 3)
-
-def extract_keywords(text, top_n=20):
-    stopwords = set([
-        "the","and","a","an","to","of","in","for","on","with",
-        "at","by","from","or","is","are","as","this","that",
-        "your","you","be","has","have","will","can","may","our"
-    ])
-    text = re.sub(r"[^a-zA-Z0-9\s]", "", text)
-    words = text.lower().split()
-    words = [w for w in words if w not in stopwords and len(w) > 2]
-    counter = Counter(words)
-    keywords = [word for word, _ in counter.most_common(top_n)]
-    return keywords

backend/agents/normalizer.py

@@ -1,13 +0,0 @@
-from typing import List, Dict
-
-def normalize_job(raw: Dict, source: str) -> Dict:
-    return {
-        "id": str(raw.get("id", "")),
-        "source": source,
-        "title": raw.get("title") or raw.get("position", ""),
-        "company": raw.get("company", ""),
-        "description": raw.get("description", ""),
-        "skills": raw.get("skills") or raw.get("tags", []),
-        "url": raw.get("url", ""),
-        "date": raw.get("date", ""),
-    }

backend/agents/rapidapi_freelancer.py

@@ -1,28 +0,0 @@
-import os
-import requests
-from .normalizer import normalize_job
-
-RAPIDAPI_KEY = os.getenv("RAPIDAPI_KEY")
-
-def fetch_freelancer_jobs(query="AI", limit=5):
-    url = "https://freelancer-com.p.rapidapi.com/projects/search"   # Example endpoint
-    headers = {
-        "X-RapidAPI-Key": RAPIDAPI_KEY,
-        "X-RapidAPI-Host": "freelancer-com.p.rapidapi.com"
-    }
-    params = {"q": query, "limit": limit}
-    response = requests.get(url, headers=headers, params=params)
-    jobs = response.json().get("projects", [])
-
-    normalized = []
-    for job in jobs[:limit]:
-        normalized.append(normalize_job({
-            "id": job.get("id"),
-            "title": job.get("title"),
-            "company": "Freelancer Client",
-            "description": job.get("description"),
-            "skills": [s["name"] for s in job.get("jobs", [])],
-            "url": f"https://www.freelancer.com/projects/{job.get('seo_url')}",
-            "date": job.get("submitdate")
-        }, "Freelancer"))
-    return normalized

backend/agents/rapidapi_linkedin.py

@@ -1,28 +0,0 @@
-import os
-import requests
-from .normalizer import normalize_job
-
-RAPIDAPI_KEY = os.getenv("RAPIDAPI_KEY")
-
-def fetch_linkedin_jobs(query="software engineer", limit=5):
-    url = "https://linkedin-jobs-search.p.rapidapi.com/"   # Example endpoint
-    headers = {
-        "X-RapidAPI-Key": RAPIDAPI_KEY,
-        "X-RapidAPI-Host": "linkedin-jobs-search.p.rapidapi.com"
-    }
-    payload = {"search_terms": query, "location": "remote", "page": "1"}
-    response = requests.post(url, headers=headers, json=payload)
-    jobs = response.json()
-
-    normalized = []
-    for job in jobs[:limit]:
-        normalized.append(normalize_job({
-            "id": job.get("job_id"),
-            "title": job.get("job_title"),
-            "company": job.get("company_name"),
-            "description": job.get("job_description"),
-            "skills": job.get("job_skills", []),
-            "url": job.get("linkedin_url"),
-            "date": job.get("posted_date")
-        }, "LinkedIn"))
-    return normalized

backend/agents/rapidapi_upwork.py

@@ -1,28 +0,0 @@
-import os
-import requests
-from .normalizer import normalize_job
-
-RAPIDAPI_KEY = os.getenv("RAPIDAPI_KEY")
-
-def fetch_upwork_jobs(query="python developer", limit=5):
-    url = "https://upwork-api.p.rapidapi.com/search/jobs"   # Example endpoint
-    headers = {
-        "X-RapidAPI-Key": RAPIDAPI_KEY,
-        "X-RapidAPI-Host": "upwork-api.p.rapidapi.com"
-    }
-    params = {"q": query, "page": "1"}
-    response = requests.get(url, headers=headers, params=params)
-    jobs = response.json().get("jobs", [])
-
-    normalized = []
-    for job in jobs[:limit]:
-        normalized.append(normalize_job({
-            "id": job.get("id"),
-            "title": job.get("title"),
-            "company": "Upwork Client",
-            "description": job.get("description"),
-            "skills": job.get("skills", []),
-            "url": f"https://www.upwork.com/jobs/{job.get('id')}",
-            "date": job.get("date_created")
-        }, "Upwork"))
-    return normalized

backend/agents/remoteok_agent.py

@@ -1,8 +0,0 @@
-import requests
-from .normalizer import normalize_job
-
-def fetch_remoteok_jobs(limit=10):
-    url = "https://remoteok.com/api"
-    res = requests.get(url, headers={"User-Agent": "MATCHHIVE"})
-    jobs = res.json()[1:]  # skip metadata
-    return [normalize_job(job, "RemoteOK") for job in jobs[:limit]]

backend/agents/resume_parser.py

@@ -1,10 +0,0 @@
-import pdfplumber, docx, os
-
-def extract_text(file_path: str) -> str:
-    if file_path.endswith(".pdf"):
-        with pdfplumber.open(file_path) as pdf:
-            return " ".join(page.extract_text() or "" for page in pdf.pages)
-    elif file_path.endswith(".docx"):
-        doc = docx.Document(file_path)
-        return " ".join(p.text for p in doc.paragraphs)
-    return ""