⚡ Build optimization: Python 3.11 + CPU torch + lazy load

README.md

@@ -1,12 +1,33 @@
 ---
-title: Cv Matching Engine
-emoji: 🦀
-colorFrom: yellow
-colorTo: gray
+title: CV Matching Engine
+emoji: ⚡
+colorFrom: red
+colorTo: indigo
 sdk: gradio
-sdk_version: 6.12.0
+sdk_version: 5.9.1
+python_version: "3.11"
 app_file: app.py
-pinned: false
+pinned: true
+license: apache-2.0
+short_description: PDF CV → Semantic NLP → Hybrid Scoring → Explainable Ranking
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ⚡ CV Matching Engine
+
+PDF CV dosyalarını yükle, iş ilanını gir — anında semantik analiz, hibrit skor ve XAI ile sıralama.
+
+## Özellikler
+- 📄 PDF CV ayrıştırma (dual-column destekli)
+- 🧠 100+ canonical skill ontolojisi (Türkçe dahil)
+- 🔢 Sentence-BERT semantik embedding
+- ⚖️ Ayarlanabilir hibrit skor (Semantic + Skill + Deneyim)
+- 🔍 Explainable AI — Neden bu skor?
+- 📊 Plotly interaktif dashboard
+
+## Kullanım
+1. PDF CV dosyalarını yükle (çoklu seçim desteklenir)
+2. İş ilanı açıklamasını gir
+3. Ağırlık slider'larını ayarla (opsiyonel)
+4. **▶ ANALİZİ BAŞLAT** butonuna tıkla
+
+Geliştiren: [cihatyldz](https://huggingface.co/cihatyldz)

app.py

@@ -0,0 +1,801 @@
+# ═══════════════════════════════════════════════════════════════════════════
+# CV MATCHING ENGINE — Hugging Face Space
+# Auto-generated from notebook
+# ═══════════════════════════════════════════════════════════════════════════
+
+import os, re, json, warnings, tempfile
+
+# ════════════════════════════════════════════════════════════════════════════
+# MONKEY-PATCH: gradio_client bug fix
+# gradio 4.44.0'ın get_type() fonksiyonu additionalProperties=True (bool)
+# durumunu işleyemiyor, "TypeError: argument of type bool is not iterable"
+# veriyor. Aşağıdaki patch bool/None schema'ları "Any" olarak işler.
+# ════════════════════════════════════════════════════════════════════════════
+import gradio_client.utils as _gcu
+_orig_get_type = _gcu.get_type
+def _safe_get_type(schema):
+    if not isinstance(schema, dict):
+        return "Any"
+    return _orig_get_type(schema)
+_gcu.get_type = _safe_get_type
+
+_orig_json_schema = _gcu._json_schema_to_python_type
+def _safe_json_schema(schema, defs=None):
+    if not isinstance(schema, dict):
+        return "Any"
+    return _orig_json_schema(schema, defs)
+_gcu._json_schema_to_python_type = _safe_json_schema
+
+import fitz
+import spacy
+import gradio as gr
+import pandas as pd
+import numpy as np
+import plotly.graph_objects as go
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+from collections import defaultdict
+from typing import List, Dict
+
+warnings.filterwarnings("ignore")
+
+# ── Model yükleme — LAZY LOAD ───────────────────────────────────────────────
+# Modeller startup'ta değil, ilk kullanımda yüklenir. Bu sayede:
+#   - Space çabuk başlar (timeout yemez)
+#   - RAM verimli kullanılır
+#   - HF cache'i ikinci başlatmada modelleri tekrar indirmez
+_nlp = None
+_embed_model = None
+
+def get_nlp():
+    global _nlp
+    if _nlp is None:
+        print("[INFO] spaCy modeli yükleniyor (ilk kullanım)...")
+        _nlp = spacy.load("en_core_web_sm")
+    return _nlp
+
+def get_embed_model():
+    global _embed_model
+    if _embed_model is None:
+        print("[INFO] Sentence-BERT modeli yükleniyor (ilk kullanım)...")
+        _embed_model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+    return _embed_model
+
+print("[INFO] App başlatıldı — modeller lazy load modunda.")
+
+# ────────────────────────────────────────────────────────────────────────────
+# SKILL ONTOLOJİSİ
+# ────────────────────────────────────────────────────────────────────────────
+SKILL_ONTOLOGY: Dict[str, List[str]] = {
+    "python"         : ["python3", "python 3", "py", "cpython"],
+    "java"           : ["java se", "java ee", "java 8", "java 11", "java 17", "jvm", "openjdk"],
+    "c#"             : ["csharp", "c sharp", ".net c#", "dotnet csharp"],
+    "c++"            : ["cpp", "c plus plus", "c/c++"],
+    "c"              : ["c language", "c programming", "ansi c", "embedded c"],
+    "javascript"     : ["js", "ecmascript", "es6", "es2015", "vanilla js"],
+    "typescript"     : ["ts", "typed javascript"],
+    "kotlin"         : ["kotlin jvm", "kotlin android"],
+    "swift"          : ["swift ios", "swiftui", "apple swift"],
+    "go"             : ["golang", "go language"],
+    "rust"           : ["rust lang", "rust programming"],
+    "php"            : ["php7", "php8"],
+    "ruby"           : ["ruby on rails", "ror", "rails"],
+    "scala"          : ["scala jvm", "akka"],
+    "r"              : ["rstudio", "r programming", "r language"],
+    "matlab"         : ["matlab/simulink", "simulink", "mathworks"],
+    "dart"           : ["dart flutter"],
+    "bash"           : ["shell scripting", "bash scripting", "shell script", "sh", "zsh"],
+    "powershell"     : ["ps1", "windows powershell", "pwsh"],
+    "vba"            : ["visual basic for applications", "excel vba"],
+    "react"          : ["reactjs", "react.js", "react hooks", "next.js", "nextjs"],
+    "angular"        : ["angularjs", "angular 2+", "angular cli", "ng"],
+    "vue"            : ["vuejs", "vue.js", "vue 3", "nuxt", "nuxt.js"],
+    "svelte"         : ["sveltekit"],
+    "html"           : ["html5"],
+    "css"            : ["css3", "scss", "sass", "less"],
+    "tailwind"       : ["tailwindcss", "tailwind css"],
+    "bootstrap"      : ["bootstrap 5", "bootstrap css"],
+    "graphql"        : ["graphql api", "apollo graphql"],
+    "node.js"        : ["nodejs", "node js", "express", "express.js", "expressjs"],
+    "django"         : ["django rest", "drf", "django framework"],
+    "flask"          : ["flask api", "flask python"],
+    "fastapi"        : ["fast api", "fastapi python"],
+    "spring boot"    : ["spring", "spring framework", "spring mvc", "spring security"],
+    "asp.net"        : ["asp net", "asp.net core", ".net core", "dotnet core", "aspnet", "mvc .net"],
+    "laravel"        : ["laravel php", "laravel framework"],
+    "rest api"       : ["restful api", "rest", "restful", "web api", "http api"],
+    "microservices"  : ["micro services", "soa", "distributed systems"],
+    "android"        : ["android development", "android studio", "android sdk"],
+    "ios"            : ["ios development", "xcode", "objective-c"],
+    "flutter"        : ["flutter dart", "flutter mobile"],
+    "react native"   : ["react-native", "rn mobile"],
+    "sql"            : ["structured query language", "ansi sql"],
+    "mysql"          : ["mysql database", "mysql server"],
+    "postgresql"     : ["postgres", "psql", "postgresql database"],
+    "mssql"          : ["sql server", "microsoft sql server", "t-sql", "tsql", "ms sql"],
+    "oracle"         : ["oracle database", "oracle db", "pl/sql", "plsql"],
+    "sqlite"         : ["sqlite3"],
+    "mongodb"        : ["mongo", "mongo db", "mongodb atlas"],
+    "redis"          : ["redis cache", "redis server"],
+    "cassandra"      : ["apache cassandra", "cql"],
+    "elasticsearch"  : ["elastic search", "elk stack", "opensearch"],
+    "dynamodb"       : ["aws dynamodb", "amazon dynamodb"],
+    "neo4j"          : ["graph database", "cypher query"],
+    "firebase"       : ["firebase realtime", "firestore"],
+    "aws"            : ["amazon web services", "amazon aws", "ec2", "s3", "lambda",
+                        "rds", "eks", "ecs", "sagemaker", "cloudwatch"],
+    "azure"          : ["microsoft azure", "azure cloud", "azure devops",
+                        "azure functions", "aks", "azure blob", "azure sql"],
+    "google cloud"   : ["gcp", "google cloud platform", "gke", "bigquery",
+                        "cloud run", "vertex ai"],
+    "docker"         : ["containerization", "container", "dockerfile", "docker-compose"],
+    "kubernetes"     : ["k8s", "helm", "kubectl", "container orchestration", "openshift"],
+    "git"            : ["github", "gitlab", "bitbucket", "version control", "git flow"],
+    "jenkins"        : ["jenkins ci", "jenkins pipeline"],
+    "github actions" : ["gh actions", "github ci", "github workflow"],
+    "gitlab ci"      : ["gitlab cicd", "gitlab pipeline"],
+    "terraform"      : ["hashicorp terraform", "infrastructure as code", "iac"],
+    "ansible"        : ["ansible playbook", "ansible automation"],
+    "prometheus"     : ["prometheus monitoring"],
+    "grafana"        : ["grafana dashboard", "grafana monitoring"],
+    "nginx"          : ["nginx server", "nginx reverse proxy"],
+    "linux"          : ["ubuntu", "centos", "debian", "rhel", "red hat",
+                        "linux server", "unix", "linux administration"],
+    "apache spark"   : ["spark", "pyspark", "spark streaming"],
+    "hadoop"         : ["apache hadoop", "hdfs", "mapreduce", "hive"],
+    "kafka"          : ["apache kafka", "kafka streaming", "event streaming"],
+    "airflow"        : ["apache airflow", "airflow dag"],
+    "dbt"            : ["data build tool", "dbt core"],
+    "etl"            : ["extract transform load", "data pipeline", "data integration"],
+    "data warehouse" : ["snowflake", "redshift", "bigquery", "azure synapse", "data lake"],
+    "data analysis"  : ["veri analizi", "data analytics", "exploratory data analysis",
+                        "eda", "data mining", "veri madenciliği"],
+    "pandas"         : ["pandas dataframe", "pandas python"],
+    "numpy"          : ["numpy array", "numerical python"],
+    "tableau"        : ["tableau desktop", "tableau server"],
+    "power bi"       : ["powerbi", "microsoft power bi", "power bi desktop"],
+    "machine learning": ["ml", "makine öğrenmesi", "makine öğrenimi",
+                          "supervised learning", "unsupervised learning",
+                          "classification", "regression", "clustering"],
+    "deep learning"  : ["dl", "derin öğrenme", "neural network", "ann", "dnn",
+                         "cnn", "rnn", "lstm", "gru"],
+    "natural language processing": ["nlp", "doğal dil işleme", "text mining",
+                          "transformers", "text classification", "ner", "sentiment analysis"],
+    "computer vision": ["cv", "image processing", "görüntü işleme", "opencv",
+                         "object detection", "yolo", "image classification"],
+    "reinforcement learning": ["rl", "pekiştirmeli öğrenme", "dqn", "ppo"],
+    "large language model": ["llm", "gpt", "bert", "llama", "fine-tuning", "rag",
+                          "prompt engineering", "chatgpt", "gemini", "mistral"],
+    "tensorflow"     : ["tf", "keras", "tensorflow 2"],
+    "pytorch"        : ["torch", "pytorch lightning"],
+    "scikit-learn"   : ["sklearn", "scikit learn"],
+    "hugging face"   : ["huggingface", "transformers library", "hf hub"],
+    "langchain"      : ["lang chain", "langchain python"],
+    "xgboost"        : ["extreme gradient boosting", "xgb", "lightgbm", "lgbm", "catboost"],
+    "time series"    : ["zaman serisi", "forecasting", "talep tahmini",
+                         "arima", "sarima", "prophet"],
+    "cybersecurity"  : ["siber güvenlik", "information security", "bilgi güvenliği"],
+    "penetration testing": ["pentest", "ethical hacking", "metasploit", "burp suite"],
+    "soc"            : ["security operations center", "siem", "soc analyst", "splunk"],
+    "devsecops"      : ["dev sec ops", "sast", "dast"],
+    "identity management": ["iam", "active directory", "ldap", "sso", "okta"],
+    "software architecture": ["yazılım mimarisi", "solution architecture",
+                          "system design", "design patterns", "solid principles"],
+    "unit testing"   : ["tdd", "test driven development", "junit", "pytest",
+                         "nunit", "xunit", "jest"],
+    "agile"          : ["scrum", "kanban", "sprint", "backlog", "çevik", "safe"],
+    "sap"            : ["sap erp", "sap s/4hana", "sap hana", "sap abap",
+                         "sap bw", "sap fi", "sap mm", "sap sd"],
+    "salesforce"     : ["salesforce crm", "apex salesforce", "soql"],
+    "microsoft dynamics": ["dynamics 365", "dynamics crm", "business central"],
+    "servicenow"     : ["service now", "itsm servicenow"],
+    "jira"           : ["jira software", "atlassian jira", "confluence"],
+    "selenium"       : ["selenium webdriver", "selenium automation"],
+    "cypress"        : ["cypress testing", "cypress e2e"],
+    "playwright"     : ["playwright testing", "playwright e2e"],
+    "postman"        : ["postman api testing", "api testing"],
+    "qa"             : ["quality assurance", "kalite güvencesi", "test automation"],
+    "networking"     : ["tcp/ip", "dns", "dhcp", "routing", "switching", "cisco"],
+    "windows server" : ["windows server 2019", "windows server 2022", "iis"],
+    "virtualization" : ["vmware", "vsphere", "hyper-v", "virtualbox", "proxmox"],
+    "iot"            : ["internet of things", "nesnelerin interneti", "mqtt"],
+    "embedded systems": ["gömülü sistemler", "rtos", "freertos", "microcontroller"],
+    "arduino"        : ["arduino uno", "arduino ide"],
+    "raspberry pi"   : ["rpi", "raspberry pi os"],
+    "fpga"           : ["vhdl", "verilog", "xilinx"],
+    "ros"            : ["robot operating system", "ros2"],
+    "control systems": ["kontrol sistemleri", "pid controller", "pid", "control theory"],
+    "robotics"       : ["robot programlama", "robot kinematics"],
+    "plc"            : ["programmable logic controller", "siemens plc", "ladder logic", "scada"],
+    "solidworks"     : ["cad", "catia", "autocad", "fusion 360"],
+    "supply chain"   : ["tedarik zinciri", "logistics", "lojistik", "scm"],
+    "vehicle routing": ["vrp", "route optimization", "güzergah optimizasyonu"],
+    "demand forecasting": ["talep tahmini", "demand planning", "inventory forecasting"],
+    "warehouse management": ["wms", "depo yönetimi"],
+    "operations research": ["yöneylem araştırması", "linear programming",
+                             "optimization", "mathematical optimization"],
+    "project management": ["proje yönetimi", "pmp", "prince2", "waterfall"],
+    "team leadership" : ["takım liderliği", "people management", "tech lead", "mentoring"],
+}
+
+SKILL_CATEGORIES: Dict[str, str] = {
+    "python":"Prog. Dili","java":"Prog. Dili","c#":"Prog. Dili","c++":"Prog. Dili",
+    "c":"Prog. Dili","javascript":"Prog. Dili","typescript":"Prog. Dili",
+    "kotlin":"Prog. Dili","swift":"Prog. Dili","go":"Prog. Dili","rust":"Prog. Dili",
+    "php":"Prog. Dili","ruby":"Prog. Dili","scala":"Prog. Dili","r":"Prog. Dili",
+    "matlab":"Prog. Dili","dart":"Prog. Dili","bash":"Prog. Dili",
+    "powershell":"Prog. Dili","vba":"Prog. Dili",
+    "react":"Web Frontend","angular":"Web Frontend","vue":"Web Frontend",
+    "svelte":"Web Frontend","html":"Web Frontend","css":"Web Frontend",
+    "tailwind":"Web Frontend","bootstrap":"Web Frontend","graphql":"Web Frontend",
+    "node.js":"Backend","django":"Backend","flask":"Backend","fastapi":"Backend",
+    "spring boot":"Backend","asp.net":"Backend","laravel":"Backend",
+    "rest api":"Backend","microservices":"Backend",
+    "android":"Mobil","ios":"Mobil","flutter":"Mobil","react native":"Mobil",
+    "sql":"Veritabanı","mysql":"Veritabanı","postgresql":"Veritabanı",
+    "mssql":"Veritabanı","oracle":"Veritabanı","sqlite":"Veritabanı",
+    "mongodb":"Veritabanı","redis":"Veritabanı","cassandra":"Veritabanı",
+    "elasticsearch":"Veritabanı","dynamodb":"Veritabanı","neo4j":"Veritabanı",
+    "firebase":"Veritabanı",
+    "aws":"Bulut","azure":"Bulut","google cloud":"Bulut",
+    "docker":"DevOps","kubernetes":"DevOps","git":"DevOps","jenkins":"DevOps",
+    "github actions":"DevOps","gitlab ci":"DevOps","terraform":"DevOps",
+    "ansible":"DevOps","prometheus":"DevOps","grafana":"DevOps",
+    "nginx":"DevOps","linux":"DevOps",
+    "apache spark":"Veri Müh.","hadoop":"Veri Müh.","kafka":"Veri Müh.",
+    "airflow":"Veri Müh.","dbt":"Veri Müh.","etl":"Veri Müh.",
+    "data warehouse":"Veri Müh.","data analysis":"Veri Müh.",
+    "pandas":"Veri Müh.","numpy":"Veri Müh.","tableau":"Veri Müh.","power bi":"Veri Müh.",
+    "machine learning":"Yapay Zeka","deep learning":"Yapay Zeka",
+    "natural language processing":"Yapay Zeka","computer vision":"Yapay Zeka",
+    "reinforcement learning":"Yapay Zeka","large language model":"Yapay Zeka",
+    "tensorflow":"Yapay Zeka","pytorch":"Yapay Zeka","scikit-learn":"Yapay Zeka",
+    "hugging face":"Yapay Zeka","langchain":"Yapay Zeka",
+    "xgboost":"Yapay Zeka","time series":"Yapay Zeka",
+    "cybersecurity":"Siber Güv.","penetration testing":"Siber Güv.",
+    "soc":"Siber Güv.","devsecops":"Siber Güv.","identity management":"Siber Güv.",
+    "software architecture":"Yazılım Mimarisi","unit testing":"Yazılım Mimarisi",
+    "agile":"Yazılım Mimarisi",
+    "sap":"ERP/CRM","salesforce":"ERP/CRM","microsoft dynamics":"ERP/CRM",
+    "servicenow":"ERP/CRM","jira":"ERP/CRM",
+    "selenium":"Testing/QA","cypress":"Testing/QA","playwright":"Testing/QA",
+    "postman":"Testing/QA","qa":"Testing/QA",
+    "networking":"Sistem/Altyapı","windows server":"Sistem/Altyapı",
+    "virtualization":"Sistem/Altyapı",
+    "iot":"IoT/Gömülü","embedded systems":"IoT/Gömülü",
+    "arduino":"IoT/Gömülü","raspberry pi":"IoT/Gömülü","fpga":"IoT/Gömülü",
+    "ros":"Robotik","control systems":"Robotik","robotics":"Robotik",
+    "plc":"Robotik","solidworks":"Robotik",
+    "supply chain":"Lojistik","vehicle routing":"Lojistik",
+    "demand forecasting":"Lojistik","warehouse management":"Lojistik",
+    "operations research":"Lojistik",
+    "project management":"Soft Skill","team leadership":"Soft Skill",
+}
+
+SYNONYM_TO_CANONICAL: Dict[str, str] = {}
+for canonical, synonyms in SKILL_ONTOLOGY.items():
+    SYNONYM_TO_CANONICAL[canonical] = canonical
+    for syn in synonyms:
+        SYNONYM_TO_CANONICAL[syn.lower()] = canonical
+
+SCORE_WEIGHTS = {"semantic": 0.55, "skill_overlap": 0.35, "experience": 0.10}
+
+# ── Utility functions ────────────────────────────────────────────────────────
+def extract_text_from_pdf(pdf_path, dual_column=False):
+    doc = fitz.open(pdf_path)
+    full_text = ""
+    for page in doc:
+        if dual_column:
+            w = page.rect.width
+            full_text += page.get_text("text", clip=fitz.Rect(0,0,w/2,page.rect.height))
+            full_text += page.get_text("text", clip=fitz.Rect(w/2,0,w,page.rect.height))
+        else:
+            full_text += page.get_text("text")
+    doc.close()
+    return re.sub(r"\s+", " ", full_text).strip()
+
+def extract_skills(text):
+    text_lower = text.lower()
+    canonical_found = set()
+    for term, canonical in SYNONYM_TO_CANONICAL.items():
+        if re.search(r"\b" + re.escape(term) + r"\b", text_lower):
+            canonical_found.add(canonical)
+    by_category = defaultdict(list)
+    for skill in canonical_found:
+        by_category[SKILL_CATEGORIES.get(skill, "Diğer")].append(skill)
+    return {"canonical_skills": sorted(canonical_found), "by_category": dict(by_category)}
+
+def get_embedding(text):
+    return get_embed_model().encode(text, show_progress_bar=False)
+
+def compute_semantic_similarity(t1, t2):
+    return float(cosine_similarity([get_embedding(t1)], [get_embedding(t2)])[0][0])
+
+def skill_overlap_score(cv_skills, job_skills):
+    if not job_skills: return 0.0
+    s1, s2 = set(cv_skills), set(job_skills)
+    return len(s1 & s2) / len(s1 | s2) if (s1 | s2) else 0.0
+
+def extract_experience_years(text):
+    m = re.search(r"(\d+)\+?\s*(?:years?|yıl)\s*(?:of\s+)?(?:experience|deneyim)", text.lower())
+    return float(m.group(1)) if m else 0.0
+
+def hybrid_score(sem, skill, exp, req_years, weights):
+    exp_sc = min(exp / req_years, 1.0) if req_years > 0 else 1.0
+    return weights["semantic"]*sem + weights["skill_overlap"]*skill + weights["experience"]*exp_sc, exp_sc
+
+def evaluate_candidate(cv_text, job_description, job_skills, req_years, name, weights):
+    cv_sr  = extract_skills(cv_text)
+    cv_skills = cv_sr["canonical_skills"]
+    sem    = compute_semantic_similarity(cv_text, job_description)
+    jac    = skill_overlap_score(cv_skills, job_skills)
+    exp    = extract_experience_years(cv_text)
+    final, exp_sc = hybrid_score(sem, jac, exp, req_years, weights)
+    matched = sorted(set(cv_skills) & set(job_skills))
+    missing = sorted(set(job_skills) - set(cv_skills))
+    extra   = sorted(set(cv_skills) - set(job_skills))
+    verdict = ("🟢 Güçlü Eşleşme" if final>=0.75 else
+               "🟡 Orta Eşleşme"  if final>=0.55 else "🔴 Zayıf Eşleşme")
+    return {"name":name,"cv_skills":cv_skills,"skill_by_category":cv_sr["by_category"],
+            "semantic_score":round(sem,4),"skill_score":round(jac,4),
+            "experience_years":exp,"experience_score":round(exp_sc,4),
+            "final_score":round(final,4),
+            "explanation":{"verdict":verdict,"matched_skills":matched,
+                           "missing_skills":missing,"extra_skills":extra}}
+
+# ── HTML / Plotly helpers ────────────────────────────────────────────────────
+def make_score_pill(score):
+    cls = "score-high" if score>=0.75 else "score-mid" if score>=0.55 else "score-low"
+    return f"<span class='score-pill {cls}'>{score:.3f}</span>"
+
+def make_skill_tags(skills, kind):
+    if not skills: return "<span style='color:#3d5878;font-size:0.8rem'>—</span>"
+    return " ".join(f"<span class='skill-tag skill-{kind}'>{s}</span>" for s in skills)
+
+def make_progress_bar(label, value, color="#00d4aa"):
+    pct = int(value*100)
+    return (f"<div class='prog-bar-wrap'><div class='prog-bar-label'>"
+            f"<span>{label}</span><span style='font-family:var(--font-mono);color:{color}'>{value:.4f}</span></div>"
+            f"<div class='prog-bar-track'><div class='prog-bar-fill' style='width:{pct}%;background:{color};'></div></div></div>")
+
+PLOTLY_LAYOUT = dict(
+    paper_bgcolor="rgba(13,24,41,0)", plot_bgcolor="rgba(13,24,41,0)",
+    font=dict(family="Rajdhani, Inter, sans-serif", color="#6b8ab0"),
+    title_font=dict(family="Rajdhani, sans-serif", color="#00d4aa", size=16),
+    margin=dict(l=20,r=20,t=50,b=20),
+    colorway=["#00d4aa","#f59e0b","#a78bfa","#ef4444","#22c55e"],
+)
+
+def plotly_ranking_bar(df):
+    colors = ["#22c55e" if s>=0.75 else "#f59e0b" if s>=0.55 else "#ef4444" for s in df["Final Skor"]]
+    fig = go.Figure(go.Bar(
+        x=df["Final Skor"], y=df["Aday"], orientation="h",
+        marker_color=colors, text=[f"{s:.3f}" for s in df["Final Skor"]],
+        textposition="outside", textfont=dict(family="JetBrains Mono",color="#e2eaf6",size=12)))
+    fig.add_vline(x=0.75,line_dash="dot",line_color="rgba(34,197,94,0.5)",
+                  annotation_text="Güçlü",annotation_font_color="#22c55e")
+    fig.add_vline(x=0.55,line_dash="dot",line_color="rgba(245,158,11,0.5)",
+                  annotation_text="Orta",annotation_font_color="#f59e0b")
+    fig.update_layout(**PLOTLY_LAYOUT,title="🏆 Nihai Aday Sıralaması",
+                      xaxis=dict(range=[0,1.05],gridcolor="rgba(30,48,80,0.8)",title="Skor"),
+                      yaxis=dict(autorange="reversed",gridcolor="rgba(30,48,80,0.8)"),
+                      height=max(280,len(df)*62))
+    return fig
+
+def plotly_component_stacked(df):
+    w = SCORE_WEIGHTS
+    names = df["Aday"].tolist()
+    fig = go.Figure()
+    fig.add_trace(go.Bar(name="Semantik",x=names,y=(df["Semantic"]*w["semantic"]).tolist(),marker_color="#00d4aa",opacity=0.9))
+    fig.add_trace(go.Bar(name="Skill Overlap",x=names,y=(df["Skill Overlap"]*w["skill_overlap"]).tolist(),marker_color="#a78bfa",opacity=0.9))
+    fig.add_trace(go.Bar(name="Deneyim",x=names,y=(df["Deneyim (Yıl)"].apply(lambda x:min(x/3,1))*w["experience"]).tolist(),marker_color="#f59e0b",opacity=0.9))
+    fig.update_layout(**PLOTLY_LAYOUT,barmode="stack",title="📊 Skor Bileşeni Dağılımı",
+                      xaxis=dict(gridcolor="rgba(30,48,80,0.8)"),
+                      yaxis=dict(gridcolor="rgba(30,48,80,0.8)",title="Katkı"),
+                      legend=dict(bgcolor="rgba(13,24,41,0.8)",bordercolor="#1e3050",borderwidth=1),
+                      height=360)
+    return fig
+
+def plotly_skill_gap(df):
+    names = df["Aday"].tolist()
+    fig = go.Figure()
+    fig.add_trace(go.Bar(name="Eşleşen ✅",x=names,y=df["Eşleşen Skill"].tolist(),marker_color="rgba(34,197,94,0.8)"))
+    fig.add_trace(go.Bar(name="Eksik ❌",x=names,y=df["Eksik Skill"].tolist(),marker_color="rgba(239,68,68,0.7)"))
+    fig.update_layout(**PLOTLY_LAYOUT,barmode="group",title="🔍 Skill Gap Analizi",
+                      xaxis=dict(gridcolor="rgba(30,48,80,0.8)"),
+                      yaxis=dict(gridcolor="rgba(30,48,80,0.8)",title="Skill Sayısı"),
+                      legend=dict(bgcolor="rgba(13,24,41,0.8)",bordercolor="#1e3050",borderwidth=1),
+                      height=340)
+    return fig
+
+def plotly_scatter(df):
+    fig = go.Figure(go.Scatter(
+        x=df["Semantic"],y=df["Skill Overlap"],mode="markers+text",
+        text=df["Aday"].apply(lambda n:n.split()[0]),textposition="top center",
+        textfont=dict(family="Rajdhani",color="#e2eaf6",size=12),
+        marker=dict(size=18,color=df["Final Skor"],
+                    colorscale=[[0,"#ef4444"],[0.5,"#f59e0b"],[1,"#00d4aa"]],
+                    showscale=True,colorbar=dict(title="Final Skor",tickfont=dict(color="#6b8ab0")),
+                    line=dict(width=1,color="#1e3050")),
+        hovertemplate="<b>%{text}</b><br>Semantic: %{x:.3f}<br>Skill: %{y:.3f}<extra></extra>"))
+    fig.update_layout(**PLOTLY_LAYOUT,title="🔵 Semantic vs Skill Dağılımı",
+                      xaxis=dict(title="Semantic Similarity",gridcolor="rgba(30,48,80,0.8)",range=[0,1]),
+                      yaxis=dict(title="Skill Overlap (Jaccard)",gridcolor="rgba(30,48,80,0.8)",range=[0,1]),
+                      height=360)
+    return fig
+
+def build_ranking_table(df):
+    rows = ""
+    for _,r in df.iterrows():
+        verdict = r["Değerlendirme"]
+        badge_cls = "verdict-strong" if "🟢" in verdict else "verdict-mid" if "🟡" in verdict else "verdict-weak"
+        badge_txt = "Güçlü" if "🟢" in verdict else "Orta" if "🟡" in verdict else "Zayıf"
+        rows += (f"<tr><td><span class='rank-num'>#{r['Sıra']}</span></td>"
+                 f"<td><strong style='color:var(--text-primary)'>{r['Aday']}</strong></td>"
+                 f"<td>{make_score_pill(r['Final Skor'])}</td>"
+                 f"<td><span style='font-family:var(--font-mono);color:var(--text-muted)'>{r['Semantic']:.3f}</span></td>"
+                 f"<td><span style='font-family:var(--font-mono);color:var(--text-muted)'>{r['Skill Overlap']:.3f}</span></td>"
+                 f"<td><span style='font-family:var(--font-mono);color:var(--amber)'>{int(r['Deneyim (Yıl)'])} yıl</span></td>"
+                 f"<td><span style='color:var(--green)'>{int(r['Eşleşen Skill'])}</span> / "
+                 f"<span style='color:var(--red)'>{int(r['Eksik Skill'])}</span></td>"
+                 f"<td><span class='score-pill {badge_cls}'>{badge_txt}</span></td></tr>")
+    return ("<table class='rank-table'><thead><tr>"
+            "<th>Sıra</th><th>Aday</th><th>Final Skor</th>"
+            "<th>Semantik</th><th>Skill</th><th>Deneyim</th>"
+            "<th>Eşleşen/Eksik</th><th>Durum</th></tr></thead>"
+            f"<tbody>{rows}</tbody></table>")
+
+_empty_cat_html = "<span style='color:var(--text-dim);font-size:0.85rem'>Bulunamadı</span>"
+
+def build_xai_panel(result):
+    exp   = result["explanation"]
+    verdict = exp["verdict"]
+    badge_cls = "verdict-strong" if "🟢" in verdict else "verdict-mid" if "🟡" in verdict else "verdict-weak"
+    sem   = result["semantic_score"]
+    skill = result["skill_score"]
+    expsc = result["experience_score"]
+    final = result["final_score"]
+    w     = SCORE_WEIGHTS
+    bars  = (make_progress_bar(f"Semantik Benzerlik  (×{w['semantic']})",sem*w["semantic"],"#00d4aa") +
+             make_progress_bar(f"Skill Örtüşmesi     (×{w['skill_overlap']})",skill*w["skill_overlap"],"#a78bfa") +
+             make_progress_bar(f"Deneyim Bonusu      (×{w['experience']})",expsc*w["experience"],"#f59e0b"))
+    cats  = result.get("skill_by_category",{})
+    cat_html = "".join(
+        f"<div style='margin-bottom:10px'><div style='font-family:var(--font-display);font-size:0.75rem;letter-spacing:1px;color:var(--text-dim);text-transform:uppercase;margin-bottom:5px'>{cat}</div>{make_skill_tags(skills,'extra')}</div>"
+        for cat,skills in cats.items())
+    return (f"<div style='display:grid;grid-template-columns:1fr 1fr;gap:20px'>"
+            f"<div><div class='panel-title'>📊 Skor Analizi</div>"
+            f"<div class='score-grid'>"
+            f"<div class='score-card'><div class='val'>{final:.3f}</div><div class='lbl'>Final Skor</div></div>"
+            f"<div class='score-card'><div class='val' style='color:#a78bfa'>{sem:.3f}</div><div class='lbl'>Semantik</div></div>"
+            f"<div class='score-card'><div class='val' style='color:#f59e0b'>{skill:.3f}</div><div class='lbl'>Skill</div></div>"
+            f"<div class='score-card'><div class='val' style='color:#22c55e'>{result['experience_years']:.0f} yıl</div><div class='lbl'>Deneyim</div></div>"
+            f"</div><div style='margin:16px 0 8px'><div class='panel-title' style='font-size:0.85rem'>⚖️ Bileşen Katkıları</div></div>"
+            f"{bars}"
+            f"<div style='margin-top:16px;padding:12px 16px;border-radius:8px' class='{badge_cls}'>"
+            f"<div style='font-family:var(--font-display);font-weight:700;font-size:1rem;letter-spacing:1px'>{verdict}</div></div></div>"
+            f"<div><div class='panel-title'>🔍 Skill Gap Analizi</div>"
+            f"<div style='margin-bottom:14px'><div style='font-family:var(--font-display);font-size:0.78rem;letter-spacing:1px;color:var(--green);margin-bottom:6px'>✅ EŞLEŞEN ({len(exp['matched_skills'])})</div>{make_skill_tags(exp['matched_skills'],'match')}</div>"
+            f"<div style='margin-bottom:14px'><div style='font-family:var(--font-display);font-size:0.78rem;letter-spacing:1px;color:var(--red);margin-bottom:6px'>❌ EKSİK ({len(exp['missing_skills'])})</div>{make_skill_tags(exp['missing_skills'],'missing')}</div>"
+            f"<hr class='section-divider'><div class='panel-title' style='font-size:0.85rem'>📚 CV Kategorileri</div>{cat_html or _empty_cat_html}</div></div>")
+
+# ── Globals ─────────────────────────────────────────────────────────────────
+_last_results = []
+
+# ── Main callback ────────────────────────────────────────────────────────────
+def run_analysis(pdf_files, job_desc, sem_weight, skill_weight, exp_weight, required_years, dual_col):
+    global _last_results
+    ERR = lambda msg: (f"<div class='log-box'><span class='log-warn'>{msg}</span></div>",
+                       None,None,None,None,gr.update(choices=[],value=None),
+                       f"<div class='log-box'><span class='log-warn'>{msg}</span></div>")
+    if not pdf_files: return ERR("⚠ Lütfen en az bir PDF CV yükleyin.")
+    if not job_desc.strip(): return ERR("⚠ İş ilanı boş olamaz.")
+    total = sem_weight + skill_weight + exp_weight or 1
+    weights = {"semantic":sem_weight/total,"skill_overlap":skill_weight/total,"experience":exp_weight/total}
+    candidates, log_lines = [], ["<span class='log-info'>► Analiz başlatıldı...</span>"]
+    for f in pdf_files:
+        path = f.name if hasattr(f,"name") else f
+        fname = os.path.basename(path)
+        try:
+            text = extract_text_from_pdf(path, dual_column=dual_col)
+            candidates.append({"name":fname.replace(".pdf",""),"text":text})
+            log_lines.append(f"<span class='log-ok'>✔ Yüklendi: {fname}</span>")
+        except Exception as e:
+            log_lines.append(f"<span class='log-warn'>✘ Hata ({fname}): {e}</span>")
+    if not candidates:
+        lh = "<div class='log-box'>"+"<br>".join(log_lines)+"</div>"
+        return lh,None,None,None,None,gr.update(choices=[],value=None),lh
+    job_skills = extract_skills(job_desc)["canonical_skills"]
+    results = []
+    for cand in candidates:
+        res = evaluate_candidate(cand["text"],job_desc,job_skills,required_years,cand["name"],weights)
+        results.append(res)
+        log_lines.append(f"<span class='log-ok'>✔ {cand['name']} → {res['final_score']:.3f}</span>")
+    _last_results = results
+    df = pd.DataFrame([{"Sıra":0,"Aday":r["name"],"Final Skor":r["final_score"],
+                         "Semantic":r["semantic_score"],"Skill Overlap":r["skill_score"],
+                         "Deneyim (Yıl)":r["experience_years"],
+                         "Eşleşen Skill":len(r["explanation"]["matched_skills"]),
+                         "Eksik Skill":len(r["explanation"]["missing_skills"]),
+                         "Değerlendirme":r["explanation"]["verdict"],
+                         "_raw":r} for r in results])
+    df = df.sort_values("Final Skor",ascending=False).reset_index(drop=True)
+    df["Sıra"] = df.index+1
+    log_lines.append(f"<span class='log-ok'>✔ Tamamlandı — {len(candidates)} aday değerlendirildi.</span>")
+    log_html = "<div class='log-box'>"+"<br>".join(log_lines)+"</div>"
+    return (build_ranking_table(df),plotly_ranking_bar(df),plotly_component_stacked(df),
+            plotly_skill_gap(df),plotly_scatter(df),
+            gr.update(choices=[r["name"] for r in results],value=results[0]["name"]),log_html)
+
+def show_xai(selected_name):
+    if not selected_name or not _last_results:
+        return "<div class='log-box'><span class='log-warn'>Önce analiz çalıştırın.</span></div>"
+    result = next((r for r in _last_results if r["name"]==selected_name),None)
+    return build_xai_panel(result) if result else "<div class='log-box'>Aday bulunamadı.</div>"
+
+# ── CSS (inline) ────────────────────────────────────────────────────────────
+CUSTOM_CSS = r"""
+
+@import url('https://fonts.googleapis.com/css2?family=Rajdhani:wght@400;500;600;700&family=JetBrains+Mono:wght@400;500&family=Inter:wght@300;400;500&display=swap');
+
+:root {
+    --bg-primary:   #060d1a;
+    --bg-card:      #0d1829;
+    --bg-input:     #111e33;
+    --bg-hover:     #162440;
+    --border:       #1e3050;
+    --border-glow:  #00d4aa40;
+    --teal:         #00d4aa;
+    --teal-dim:     #00a886;
+    --amber:        #f59e0b;
+    --amber-dim:    #d97706;
+    --red:          #ef4444;
+    --green:        #22c55e;
+    --text-primary: #e2eaf6;
+    --text-muted:   #6b8ab0;
+    --text-dim:     #3d5878;
+    --font-display: 'Rajdhani', sans-serif;
+    --font-mono:    'JetBrains Mono', monospace;
+    --font-body:    'Inter', sans-serif;
+    --radius:       8px;
+    --shadow:       0 4px 24px rgba(0,0,0,0.6);
+    --glow:         0 0 20px rgba(0,212,170,0.15);
+}
+
+/* ── Global ── */
+body, .gradio-container { background: var(--bg-primary) !important; color: var(--text-primary) !important; font-family: var(--font-body) !important; }
+.gradio-container { max-width: 100% !important; width: 100% !important; padding: 0 16px !important; margin: 0 auto !important; }
+
+
+/* ── Header Banner ── */
+#hero-banner {
+    background: linear-gradient(135deg, #0d1829 0%, #061224 50%, #0a1f10 100%);
+    border: 1px solid var(--border);
+    border-bottom: 2px solid var(--teal);
+    border-radius: var(--radius);
+    padding: 28px 36px;
+    margin-bottom: 20px;
+    position: relative;
+    overflow: hidden;
+    box-shadow: var(--shadow), var(--glow);
+}
+#hero-banner::before {
+    content: '';
+    position: absolute; top: 0; left: 0; right: 0; bottom: 0;
+    background: repeating-linear-gradient(90deg, transparent, transparent 40px, rgba(0,212,170,0.02) 40px, rgba(0,212,170,0.02) 41px),
+                repeating-linear-gradient(0deg, transparent, transparent 40px, rgba(0,212,170,0.02) 40px, rgba(0,212,170,0.02) 41px);
+    pointer-events: none;
+}
+#hero-banner h1 { font-family: var(--font-display) !important; font-size: 2.4rem !important; font-weight: 700 !important; color: var(--teal) !important; letter-spacing: 2px !important; margin: 0 0 6px 0 !important; text-shadow: 0 0 30px rgba(0,212,170,0.4); }
+#hero-banner p  { font-family: var(--font-body) !important; color: var(--text-muted) !important; font-size: 0.9rem !important; margin: 0 !important; letter-spacing: 0.5px; }
+.hero-badge { display: inline-block; background: rgba(0,212,170,0.1); border: 1px solid var(--teal); color: var(--teal); font-family: var(--font-mono); font-size: 0.7rem; padding: 2px 10px; border-radius: 20px; margin-right: 8px; letter-spacing: 1px; }
+
+/* ── Tabs ── */
+.tab-nav { background: var(--bg-card) !important; border: 1px solid var(--border) !important; border-radius: var(--radius) !important; padding: 4px !important; margin-bottom: 16px !important; }
+.tab-nav button { font-family: var(--font-display) !important; font-size: 0.95rem !important; font-weight: 600 !important; letter-spacing: 1px !important; color: var(--text-muted) !important; background: transparent !important; border: none !important; border-radius: 6px !important; padding: 10px 20px !important; transition: all 0.2s !important; }
+.tab-nav button:hover { color: var(--teal) !important; background: rgba(0,212,170,0.08) !important; }
+.tab-nav button.selected { color: var(--bg-primary) !important; background: var(--teal) !important; box-shadow: 0 0 15px rgba(0,212,170,0.3) !important; }
+
+/* ── Cards / Panels ── */
+.panel-card {
+    background: var(--bg-card);
+    border: 1px solid var(--border);
+    border-radius: var(--radius);
+    padding: 20px 24px;
+    box-shadow: var(--shadow);
+}
+.panel-title {
+    font-family: var(--font-display);
+    font-size: 1.1rem;
+    font-weight: 700;
+    letter-spacing: 1.5px;
+    color: var(--teal);
+    text-transform: uppercase;
+    border-bottom: 1px solid var(--border);
+    padding-bottom: 10px;
+    margin-bottom: 14px;
+}
+
+/* ── Inputs ── */
+textarea, input[type='text'] {
+    background: var(--bg-input) !important;
+    border: 1px solid var(--border) !important;
+    color: var(--text-primary) !important;
+    font-family: var(--font-body) !important;
+    border-radius: 6px !important;
+    transition: border-color 0.2s, box-shadow 0.2s !important;
+}
+textarea:focus, input[type='text']:focus {
+    border-color: var(--teal) !important;
+    box-shadow: 0 0 0 2px rgba(0,212,170,0.15) !important;
+    outline: none !important;
+}
+label, .label-wrap span { font-family: var(--font-display) !important; font-weight: 600 !important; letter-spacing: 0.8px !important; color: var(--text-muted) !important; font-size: 0.85rem !important; }
+
+/* ── Buttons ── */
+button.primary-btn, #analyze-btn {
+    background: linear-gradient(135deg, var(--teal) 0%, var(--teal-dim) 100%) !important;
+    color: var(--bg-primary) !important;
+    font-family: var(--font-display) !important;
+    font-size: 1rem !important;
+    font-weight: 700 !important;
+    letter-spacing: 2px !important;
+    border: none !important;
+    border-radius: var(--radius) !important;
+    padding: 14px 32px !important;
+    cursor: pointer !important;
+    transition: all 0.2s !important;
+    box-shadow: 0 4px 20px rgba(0,212,170,0.3) !important;
+    width: 100% !important;
+}
+button.primary-btn:hover, #analyze-btn:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 8px 30px rgba(0,212,170,0.45) !important;
+}
+.secondary-btn {
+    background: transparent !important;
+    color: var(--teal) !important;
+    border: 1px solid var(--teal) !important;
+    font-family: var(--font-display) !important;
+    font-weight: 600 !important;
+    letter-spacing: 1px !important;
+    border-radius: 6px !important;
+    padding: 8px 20px !important;
+    transition: all 0.2s !important;
+}
+.secondary-btn:hover { background: rgba(0,212,170,0.1) !important; }
+
+/* ── File Upload ── */
+.upload-zone {
+    background: var(--bg-input) !important;
+    border: 2px dashed var(--border) !important;
+    border-radius: var(--radius) !important;
+    transition: border-color 0.2s, background 0.2s !important;
+}
+.upload-zone:hover { border-color: var(--teal) !important; background: rgba(0,212,170,0.05) !important; }
+.upload-zone .icon { color: var(--teal) !important; }
+
+/* ── Slider ── */
+input[type='range'] { accent-color: var(--teal) !important; }
+
+/* ── Score Cards (HTML içinde) ── */
+.score-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(140px, 1fr)); gap: 12px; margin: 12px 0; }
+.score-card {
+    background: var(--bg-input);
+    border: 1px solid var(--border);
+    border-radius: 8px;
+    padding: 14px 16px;
+    text-align: center;
+    position: relative;
+    overflow: hidden;
+}
+.score-card::after {
+    content: '';
+    position: absolute; bottom: 0; left: 0; right: 0; height: 3px;
+    background: linear-gradient(90deg, var(--teal), var(--amber));
+}
+.score-card .val { font-family: var(--font-mono); font-size: 1.8rem; font-weight: 500; color: var(--teal); }
+.score-card .lbl { font-family: var(--font-display); font-size: 0.7rem; letter-spacing: 1px; color: var(--text-muted); text-transform: uppercase; margin-top: 4px; }
+
+.verdict-strong { background: rgba(34,197,94,0.12);  border: 1px solid rgba(34,197,94,0.4);  color: #22c55e; }
+.verdict-mid    { background: rgba(245,158,11,0.12); border: 1px solid rgba(245,158,11,0.4); color: #f59e0b; }
+.verdict-weak   { background: rgba(239,68,68,0.12);  border: 1px solid rgba(239,68,68,0.4);  color: #ef4444; }
+
+/* ── Skill Tags ── */
+.skill-tag {
+    display: inline-block;
+    font-family: var(--font-mono);
+    font-size: 0.72rem;
+    padding: 3px 10px;
+    border-radius: 20px;
+    margin: 3px;
+}
+.skill-match   { background: rgba(34,197,94,0.15);  border: 1px solid rgba(34,197,94,0.5);  color: #22c55e; }
+.skill-missing { background: rgba(239,68,68,0.12);  border: 1px solid rgba(239,68,68,0.4);  color: #ef4444; }
+.skill-extra   { background: rgba(0,212,170,0.1);   border: 1px solid rgba(0,212,170,0.35); color: #00d4aa; }
+
+/* ── Progress Bar ── */
+.prog-bar-wrap { margin: 8px 0; }
+.prog-bar-label { font-family: var(--font-display); font-size: 0.78rem; letter-spacing: 0.5px; color: var(--text-muted); display: flex; justify-content: space-between; margin-bottom: 4px; }
+.prog-bar-track { background: var(--bg-input); border-radius: 4px; height: 8px; overflow: hidden; }
+.prog-bar-fill  { height: 100%; border-radius: 4px; transition: width 0.6s ease; }
+
+/* ── Ranking Table ── */
+.rank-table { width: 100%; border-collapse: collapse; font-family: var(--font-body); font-size: 0.88rem; }
+.rank-table thead tr { background: rgba(0,212,170,0.08); border-bottom: 2px solid var(--teal); }
+.rank-table th { font-family: var(--font-display); font-weight: 700; letter-spacing: 1px; color: var(--teal); padding: 12px 14px; text-align: left; font-size: 0.8rem; text-transform: uppercase; }
+.rank-table td { padding: 12px 14px; border-bottom: 1px solid var(--border); color: var(--text-primary); vertical-align: middle; }
+.rank-table tr:hover td { background: var(--bg-hover); }
+.rank-num { font-family: var(--font-mono); font-size: 1.1rem; color: var(--teal); font-weight: 500; }
+.score-pill { font-family: var(--font-mono); font-size: 0.85rem; font-weight: 500; padding: 4px 12px; border-radius: 20px; }
+.score-high { background: rgba(34,197,94,0.15);  color: #22c55e; }
+.score-mid  { background: rgba(245,158,11,0.15); color: #f59e0b; }
+.score-low  { background: rgba(239,68,68,0.12);  color: #ef4444; }
+
+/* ── Status / Log ── */
+.log-box { background: var(--bg-input); border: 1px solid var(--border); border-radius: 6px; padding: 14px 18px; font-family: var(--font-mono); font-size: 0.8rem; color: var(--text-muted); line-height: 1.8; max-height: 120px; overflow-y: auto; }
+.log-ok   { color: var(--green); }
+.log-warn { color: var(--amber); }
+.log-info { color: var(--teal); }
+
+/* ── Dividers ── */
+.section-divider { border: none; border-top: 1px solid var(--border); margin: 18px 0; }
+
+/* ── Scrollbar ── */
+::-webkit-scrollbar { width: 6px; height: 6px; }
+::-webkit-scrollbar-track { background: var(--bg-card); }
+::-webkit-scrollbar-thumb { background: var(--border); border-radius: 3px; }
+::-webkit-scrollbar-thumb:hover { background: var(--teal-dim); }
+
+"""
+
+HERO_HTML = """<div id='hero-banner'><h1>⚡ CV MATCHING ENGINE</h1>
+<p>PDF CV'leri yükle · İş ilanını gir · Semantik analiz & XAI ile sırala</p>
+<div style='margin-top:14px'><span class='hero-badge'>SEMANTIC NLP</span>
+<span class='hero-badge'>SKILL ONTOLOGY</span><span class='hero-badge'>HYBRID SCORING</span>
+<span class='hero-badge'>EXPLAINABLE AI</span></div></div>"""
+
+with gr.Blocks(css=CUSTOM_CSS, title="CV Matching Engine") as demo:
+    gr.HTML(HERO_HTML)
+    with gr.Row():
+        with gr.Column(scale=1, min_width=310):
+            gr.HTML("<div class='panel-title'>📂 CV YÜKLEME</div>")
+            pdf_input = gr.File(label="PDF CV Dosyaları",file_types=[".pdf"],file_count="multiple")
+            gr.HTML("<div style='margin-top:20px' class='panel-title'>📋 İŞ İLANI</div>")
+            job_input = gr.Textbox(label="İş Tanımı",placeholder="Aranan pozisyon ve beceriler...",lines=7,
+                value="""We are looking for a Senior C# Developer with ASP.NET Core, Azure, SQL Server.
+Nice to have: Docker, Kubernetes, React.""")
+            gr.HTML("<div style='margin-top:20px' class='panel-title'>⚙️ SKOR AĞIRLIKLARI</div>")
+            sem_w   = gr.Slider(0.0,1.0,value=0.55,step=0.05,label="Semantik Benzerlik")
+            skill_w = gr.Slider(0.0,1.0,value=0.35,step=0.05,label="Skill Örtüşmesi")
+            exp_w   = gr.Slider(0.0,1.0,value=0.10,step=0.05,label="Deneyim Bonusu")
+            gr.HTML("<div style='margin-top:16px' class='panel-title'>🔧 SEÇENEKLER</div>")
+            req_years = gr.Slider(0,15,value=3,step=0.5,label="Gerekli Deneyim (Yıl)")
+            dual_col  = gr.Checkbox(label="İki sütunlu CV formatı",value=False)
+            analyze_btn = gr.Button("▶ ANALİZİ BAŞLAT",elem_id="analyze-btn",variant="primary")
+            gr.HTML("<div style='margin-top:16px' class='panel-title'>📟 DURUM</div>")
+            status_out = gr.HTML("<div class='log-box'><span style='color:var(--text-dim)'>Hazır.</span></div>")
+        with gr.Column(scale=3):
+            with gr.Tabs():
+                with gr.Tab("🏆  Sıralama"):
+                    gr.HTML("<div style='margin-bottom:12px' class='panel-title'>ADAY SIRALAMA TABLOSU</div>")
+                    table_out = gr.HTML(value="<div class='log-box' style='text-align:center;padding:40px'><span style='color:var(--text-dim);font-family:var(--font-display);letter-spacing:2px'>PDF CV yükleyip analizi başlatın</span></div>")
+                    gr.HTML("<div style='margin-top:24px' class='panel-title'>📊 SKOR GRAFİĞİ</div>")
+                    bar_plot = gr.Plot(label="")
+                with gr.Tab("📊  Dashboard"):
+                    with gr.Row():
+                        stack_plot   = gr.Plot(label="")
+                        scatter_plot = gr.Plot(label="")
+                    with gr.Row():
+                        gap_plot = gr.Plot(label="")
+                with gr.Tab("🔍  XAI Detay"):
+                    gr.HTML("<div style='margin-bottom:14px' class='panel-title'>AÇIKLANAB İ LİR AI — ADAY DETAY ANALİZİ</div>")
+                    xai_selector = gr.Dropdown(choices=[],label="Aday Seçin",interactive=True)
+                    xai_out = gr.HTML(value="<div class='log-box' style='text-align:center;padding:40px'><span style='color:var(--text-dim)'>Analiz tamamlandıktan sonra aday seçin</span></div>")
+    analyze_btn.click(fn=run_analysis,
+                      inputs=[pdf_input,job_input,sem_w,skill_w,exp_w,req_years,dual_col],
+                      outputs=[table_out,bar_plot,stack_plot,gap_plot,scatter_plot,xai_selector,status_out])
+    xai_selector.change(fn=show_xai,inputs=[xai_selector],outputs=[xai_out])
+
+if __name__ == "__main__":
+    demo.launch()

gradio_app_css.py

@@ -0,0 +1,215 @@
+# Auto-generated CSS module
+CUSTOM_CSS = r'''
+
+@import url('https://fonts.googleapis.com/css2?family=Rajdhani:wght@400;500;600;700&family=JetBrains+Mono:wght@400;500&family=Inter:wght@300;400;500&display=swap');
+
+:root {
+    --bg-primary:   #060d1a;
+    --bg-card:      #0d1829;
+    --bg-input:     #111e33;
+    --bg-hover:     #162440;
+    --border:       #1e3050;
+    --border-glow:  #00d4aa40;
+    --teal:         #00d4aa;
+    --teal-dim:     #00a886;
+    --amber:        #f59e0b;
+    --amber-dim:    #d97706;
+    --red:          #ef4444;
+    --green:        #22c55e;
+    --text-primary: #e2eaf6;
+    --text-muted:   #6b8ab0;
+    --text-dim:     #3d5878;
+    --font-display: 'Rajdhani', sans-serif;
+    --font-mono:    'JetBrains Mono', monospace;
+    --font-body:    'Inter', sans-serif;
+    --radius:       8px;
+    --shadow:       0 4px 24px rgba(0,0,0,0.6);
+    --glow:         0 0 20px rgba(0,212,170,0.15);
+}
+
+/* ── Global ── */
+body, .gradio-container { background: var(--bg-primary) !important; color: var(--text-primary) !important; font-family: var(--font-body) !important; }
+.gradio-container { max-width: 100% !important; width: 100% !important; padding: 0 16px !important; margin: 0 auto !important; }
+
+
+/* ── Header Banner ── */
+#hero-banner {
+    background: linear-gradient(135deg, #0d1829 0%, #061224 50%, #0a1f10 100%);
+    border: 1px solid var(--border);
+    border-bottom: 2px solid var(--teal);
+    border-radius: var(--radius);
+    padding: 28px 36px;
+    margin-bottom: 20px;
+    position: relative;
+    overflow: hidden;
+    box-shadow: var(--shadow), var(--glow);
+}
+#hero-banner::before {
+    content: '';
+    position: absolute; top: 0; left: 0; right: 0; bottom: 0;
+    background: repeating-linear-gradient(90deg, transparent, transparent 40px, rgba(0,212,170,0.02) 40px, rgba(0,212,170,0.02) 41px),
+                repeating-linear-gradient(0deg, transparent, transparent 40px, rgba(0,212,170,0.02) 40px, rgba(0,212,170,0.02) 41px);
+    pointer-events: none;
+}
+#hero-banner h1 { font-family: var(--font-display) !important; font-size: 2.4rem !important; font-weight: 700 !important; color: var(--teal) !important; letter-spacing: 2px !important; margin: 0 0 6px 0 !important; text-shadow: 0 0 30px rgba(0,212,170,0.4); }
+#hero-banner p  { font-family: var(--font-body) !important; color: var(--text-muted) !important; font-size: 0.9rem !important; margin: 0 !important; letter-spacing: 0.5px; }
+.hero-badge { display: inline-block; background: rgba(0,212,170,0.1); border: 1px solid var(--teal); color: var(--teal); font-family: var(--font-mono); font-size: 0.7rem; padding: 2px 10px; border-radius: 20px; margin-right: 8px; letter-spacing: 1px; }
+
+/* ── Tabs ── */
+.tab-nav { background: var(--bg-card) !important; border: 1px solid var(--border) !important; border-radius: var(--radius) !important; padding: 4px !important; margin-bottom: 16px !important; }
+.tab-nav button { font-family: var(--font-display) !important; font-size: 0.95rem !important; font-weight: 600 !important; letter-spacing: 1px !important; color: var(--text-muted) !important; background: transparent !important; border: none !important; border-radius: 6px !important; padding: 10px 20px !important; transition: all 0.2s !important; }
+.tab-nav button:hover { color: var(--teal) !important; background: rgba(0,212,170,0.08) !important; }
+.tab-nav button.selected { color: var(--bg-primary) !important; background: var(--teal) !important; box-shadow: 0 0 15px rgba(0,212,170,0.3) !important; }
+
+/* ── Cards / Panels ── */
+.panel-card {
+    background: var(--bg-card);
+    border: 1px solid var(--border);
+    border-radius: var(--radius);
+    padding: 20px 24px;
+    box-shadow: var(--shadow);
+}
+.panel-title {
+    font-family: var(--font-display);
+    font-size: 1.1rem;
+    font-weight: 700;
+    letter-spacing: 1.5px;
+    color: var(--teal);
+    text-transform: uppercase;
+    border-bottom: 1px solid var(--border);
+    padding-bottom: 10px;
+    margin-bottom: 14px;
+}
+
+/* ── Inputs ── */
+textarea, input[type='text'] {
+    background: var(--bg-input) !important;
+    border: 1px solid var(--border) !important;
+    color: var(--text-primary) !important;
+    font-family: var(--font-body) !important;
+    border-radius: 6px !important;
+    transition: border-color 0.2s, box-shadow 0.2s !important;
+}
+textarea:focus, input[type='text']:focus {
+    border-color: var(--teal) !important;
+    box-shadow: 0 0 0 2px rgba(0,212,170,0.15) !important;
+    outline: none !important;
+}
+label, .label-wrap span { font-family: var(--font-display) !important; font-weight: 600 !important; letter-spacing: 0.8px !important; color: var(--text-muted) !important; font-size: 0.85rem !important; }
+
+/* ── Buttons ── */
+button.primary-btn, #analyze-btn {
+    background: linear-gradient(135deg, var(--teal) 0%, var(--teal-dim) 100%) !important;
+    color: var(--bg-primary) !important;
+    font-family: var(--font-display) !important;
+    font-size: 1rem !important;
+    font-weight: 700 !important;
+    letter-spacing: 2px !important;
+    border: none !important;
+    border-radius: var(--radius) !important;
+    padding: 14px 32px !important;
+    cursor: pointer !important;
+    transition: all 0.2s !important;
+    box-shadow: 0 4px 20px rgba(0,212,170,0.3) !important;
+    width: 100% !important;
+}
+button.primary-btn:hover, #analyze-btn:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 8px 30px rgba(0,212,170,0.45) !important;
+}
+.secondary-btn {
+    background: transparent !important;
+    color: var(--teal) !important;
+    border: 1px solid var(--teal) !important;
+    font-family: var(--font-display) !important;
+    font-weight: 600 !important;
+    letter-spacing: 1px !important;
+    border-radius: 6px !important;
+    padding: 8px 20px !important;
+    transition: all 0.2s !important;
+}
+.secondary-btn:hover { background: rgba(0,212,170,0.1) !important; }
+
+/* ── File Upload ── */
+.upload-zone {
+    background: var(--bg-input) !important;
+    border: 2px dashed var(--border) !important;
+    border-radius: var(--radius) !important;
+    transition: border-color 0.2s, background 0.2s !important;
+}
+.upload-zone:hover { border-color: var(--teal) !important; background: rgba(0,212,170,0.05) !important; }
+.upload-zone .icon { color: var(--teal) !important; }
+
+/* ── Slider ── */
+input[type='range'] { accent-color: var(--teal) !important; }
+
+/* ── Score Cards (HTML içinde) ── */
+.score-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(140px, 1fr)); gap: 12px; margin: 12px 0; }
+.score-card {
+    background: var(--bg-input);
+    border: 1px solid var(--border);
+    border-radius: 8px;
+    padding: 14px 16px;
+    text-align: center;
+    position: relative;
+    overflow: hidden;
+}
+.score-card::after {
+    content: '';
+    position: absolute; bottom: 0; left: 0; right: 0; height: 3px;
+    background: linear-gradient(90deg, var(--teal), var(--amber));
+}
+.score-card .val { font-family: var(--font-mono); font-size: 1.8rem; font-weight: 500; color: var(--teal); }
+.score-card .lbl { font-family: var(--font-display); font-size: 0.7rem; letter-spacing: 1px; color: var(--text-muted); text-transform: uppercase; margin-top: 4px; }
+
+.verdict-strong { background: rgba(34,197,94,0.12);  border: 1px solid rgba(34,197,94,0.4);  color: #22c55e; }
+.verdict-mid    { background: rgba(245,158,11,0.12); border: 1px solid rgba(245,158,11,0.4); color: #f59e0b; }
+.verdict-weak   { background: rgba(239,68,68,0.12);  border: 1px solid rgba(239,68,68,0.4);  color: #ef4444; }
+
+/* ── Skill Tags ── */
+.skill-tag {
+    display: inline-block;
+    font-family: var(--font-mono);
+    font-size: 0.72rem;
+    padding: 3px 10px;
+    border-radius: 20px;
+    margin: 3px;
+}
+.skill-match   { background: rgba(34,197,94,0.15);  border: 1px solid rgba(34,197,94,0.5);  color: #22c55e; }
+.skill-missing { background: rgba(239,68,68,0.12);  border: 1px solid rgba(239,68,68,0.4);  color: #ef4444; }
+.skill-extra   { background: rgba(0,212,170,0.1);   border: 1px solid rgba(0,212,170,0.35); color: #00d4aa; }
+
+/* ── Progress Bar ── */
+.prog-bar-wrap { margin: 8px 0; }
+.prog-bar-label { font-family: var(--font-display); font-size: 0.78rem; letter-spacing: 0.5px; color: var(--text-muted); display: flex; justify-content: space-between; margin-bottom: 4px; }
+.prog-bar-track { background: var(--bg-input); border-radius: 4px; height: 8px; overflow: hidden; }
+.prog-bar-fill  { height: 100%; border-radius: 4px; transition: width 0.6s ease; }
+
+/* ── Ranking Table ── */
+.rank-table { width: 100%; border-collapse: collapse; font-family: var(--font-body); font-size: 0.88rem; }
+.rank-table thead tr { background: rgba(0,212,170,0.08); border-bottom: 2px solid var(--teal); }
+.rank-table th { font-family: var(--font-display); font-weight: 700; letter-spacing: 1px; color: var(--teal); padding: 12px 14px; text-align: left; font-size: 0.8rem; text-transform: uppercase; }
+.rank-table td { padding: 12px 14px; border-bottom: 1px solid var(--border); color: var(--text-primary); vertical-align: middle; }
+.rank-table tr:hover td { background: var(--bg-hover); }
+.rank-num { font-family: var(--font-mono); font-size: 1.1rem; color: var(--teal); font-weight: 500; }
+.score-pill { font-family: var(--font-mono); font-size: 0.85rem; font-weight: 500; padding: 4px 12px; border-radius: 20px; }
+.score-high { background: rgba(34,197,94,0.15);  color: #22c55e; }
+.score-mid  { background: rgba(245,158,11,0.15); color: #f59e0b; }
+.score-low  { background: rgba(239,68,68,0.12);  color: #ef4444; }
+
+/* ── Status / Log ── */
+.log-box { background: var(--bg-input); border: 1px solid var(--border); border-radius: 6px; padding: 14px 18px; font-family: var(--font-mono); font-size: 0.8rem; color: var(--text-muted); line-height: 1.8; max-height: 120px; overflow-y: auto; }
+.log-ok   { color: var(--green); }
+.log-warn { color: var(--amber); }
+.log-info { color: var(--teal); }
+
+/* ── Dividers ── */
+.section-divider { border: none; border-top: 1px solid var(--border); margin: 18px 0; }
+
+/* ── Scrollbar ── */
+::-webkit-scrollbar { width: 6px; height: 6px; }
+::-webkit-scrollbar-track { background: var(--bg-card); }
+::-webkit-scrollbar-thumb { background: var(--border); border-radius: 3px; }
+::-webkit-scrollbar-thumb:hover { background: var(--teal-dim); }
+
+''

requirements.txt

@@ -0,0 +1,13 @@
+--extra-index-url https://download.pytorch.org/whl/cpu
+
+torch==2.2.2+cpu
+
+pymupdf==1.24.10
+spacy==3.7.5
+https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl
+
+sentence-transformers==2.7.0
+scikit-learn==1.5.2
+pandas==2.2.3
+numpy==1.26.4
+plotly==5.24.1