[KM-383] [CEX] [AI] Deployment AI Engine / BE

.streamlit/config.toml

@@ -0,0 +1,7 @@
+[server]
+enableXsrfProtection = false
+enableCORS = false
+maxUploadSize = 3
+
+[theme]
+base="light"

externals/observability/langfuse.py

@@ -6,11 +6,11 @@ from langfuse import Langfuse
 from langchain_core.callbacks.base import BaseCallbackHandler
 
 
-langfuse = Langfuse(
-    secret_key=os.environ.get('ss__langfuse__secret_key'), 
-    public_key=os.environ.get('ss__langfuse__public_key'), 
-    host=os.environ.get('langfuse__host'),
-)
+# langfuse = Langfuse(
+#     secret_key=os.environ.get('ss__langfuse__secret_key'), 
+#     public_key=os.environ.get('ss__langfuse__public_key'), 
+#     host=os.environ.get('langfuse__host'),
+# )
 
 
 langfuse_handler = BaseCallbackHandler()

pyproject.toml

@@ -29,3 +29,8 @@ dependencies = [
     "sqlalchemy>=2.0.45",
     "uvicorn>=0.40.0",
 ]
+
+[dependency-groups]
+dev = [
+    "streamlit>=1.54.0",
+]

services/agentic/profile_scoring.py

@@ -1,4 +1,5 @@
 import traceback
+from uuid import uuid4
 from typing import List
 from langchain_core.prompts import ChatPromptTemplate
 
@@ -6,7 +7,8 @@ from config.constant import ProfileFieldTypes
 # from externals.databases.pg_crud import get_criteria_id, create_cv_filter, create_cv_matching, get_matching_id, create_cv_score, get_scoring_id
 from externals.databases.pg_models import CVProfile, CVWeight, CVFilter, CVScore, CVMatching
 from services.llms.LLM import model_4o_2
-from services.base.BaseGenerator import BaseAIGenerator, MetadataObservability
+# from services.base.BaseGenerator import BaseAIGenerator, MetadataObservability
+from services.base.BaseGenerator_v2 import BaseAIGenerator, MetadataObservability
 from services.models.data_model import AIProfile
 from services.models.data_model import (
                                             AIMatchProfile, 
@@ -89,13 +91,14 @@ def comparison_parser(profile:AIProfile, criteria:Criteria):
     for k, v in criteria.items():
         print(f" key comparison: {k}")
         op = helper_get_operator(k)
-        if 'gpa' in k or 'yoe' in k:
+        if ('gpa' in k or 'yoe' in k) and (profile.get(k) is not None) and (v is not None):
             judges = helper_judge_scoring(a_profile=profile.get(k), 
                                             b_criteria=v,
                                             rules=op)
+            comparison += f"\n| {k} | {profile.get(k)} | {v} | {op} | {judges} |"
         else:
             judges = '???'
-        comparison += f"\n| {k} | {profile.get(k)} | {v} | {op} | {judges} |"
+            comparison += f"\n| {k} | {profile.get(k)} | NA | NA | False |"
     return comparison
 
 
@@ -403,14 +406,15 @@ class AgenticScoringService:
         llm = model_4o_2.with_structured_output(AIMatchProfile)
 
         gen_ai = BaseAIGenerator(
-            task_name=self._ai_matching.__name__,
+            task_name="ai matching",
             prompt=prompt,
             llm=llm,
             input_llm=input_llm,
             metadata_observability=MetadataObservability(
                 fullname=self.user.full_name,
-                task_id=str(self.user.user_id),
+                task_id=str(uuid4()),
                 agent=self._ai_matching.__name__,
+                user_id=self.user.email
             )
         )
 

services/base/BaseGenerator.py

@@ -1,3 +1,6 @@
+import os
+from config.constant import LangfuseConstants 
+from langfuse.langchain import CallbackHandler
 from pydantic import BaseModel
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_openai import AzureChatOpenAI
@@ -13,6 +16,7 @@ from typing import Dict
 from services.llms.LLM import model_5mini, model_4omini
 from utils.decorator import trace_runtime
 from utils.logger import get_logger
+from langfuse import get_client, Langfuse
 
 logger = get_logger("base generator")
 
@@ -21,6 +25,7 @@ class MetadataObservability(BaseModel):
     fullname: str
     task_id: str
     agent: str
+    user_id: str
 
 
 class BaseAIGenerator:
@@ -31,26 +36,44 @@ class BaseAIGenerator:
                  metadata_observability: MetadataObservability,
                  llm: AzureChatOpenAI = model_5mini | model_4omini,
                  ):
-        self.name = task_name
+        self.metadata_observability = metadata_observability
         self.llm = llm
         self.prompt = prompt
         self.input_llm = input_llm
-        self.metadata_observability = metadata_observability
+        self.name = task_name
 
-    def _get_langfuse_handler(self):
+    def _get_langfuse_client(self):
         try:
-            import os
-            from config.constant import LangfuseConstants  # adjust import path if needed
             os.environ["LANGFUSE_PUBLIC_KEY"] = LangfuseConstants.PUBLIC_KEY
             os.environ["LANGFUSE_SECRET_KEY"] = LangfuseConstants.SECRET_KEY
             os.environ["LANGFUSE_HOST"] = LangfuseConstants.HOST or "https://us.cloud.langfuse.com"
-
-            from langfuse.langchain import CallbackHandler
-            return CallbackHandler()
+            langfuse = Langfuse()
+            return langfuse
         except Exception as e:
             logger.warning(f"⚠️ Langfuse unavailable, skipping observability: {e}")
             return None
 
+    def _get_langfuse_config(self):
+        try:
+            os.environ["LANGFUSE_PUBLIC_KEY"] = LangfuseConstants.PUBLIC_KEY
+            os.environ["LANGFUSE_SECRET_KEY"] = LangfuseConstants.SECRET_KEY
+            os.environ["LANGFUSE_HOST"] = LangfuseConstants.HOST or "https://us.cloud.langfuse.com"
+            
+            handler = CallbackHandler(update_trace=True)
+
+            return {
+                "callbacks": [handler],
+                "metadata": {
+                    "langfuse_session_id": self.metadata_observability.task_id,
+                    "langfuse_user_id": self.metadata_observability.fullname,
+                    "langfuse_tags": [self.metadata_observability.agent],
+                    "langfuse_trace_name": self.name,
+                },
+            }
+        except Exception as e:
+            logger.warning(f"⚠️ Langfuse unavailable, skipping observability: {e}")
+            return {}
+
     @retry(
         reraise=True,
         stop=stop_after_attempt(2),
@@ -72,35 +95,60 @@ class BaseAIGenerator:
     @trace_runtime
     async def agenerate(self):
         try:
-            handler = self._get_langfuse_handler()
-            config = {"callbacks": [handler]} if handler else {}
+            config = self._get_langfuse_config()
             chain = self.prompt | self.llm
-
-            output = await self._asafe_invoke(
-                chain=chain,
-                input_llm=self.input_llm,
-                config=config,
-            )
-            return output
-
-        except Exception as e:
+            langfuse_client = self._get_langfuse_client()
+            trace_id = Langfuse.create_trace_id(seed=self.metadata_observability.task_id)
+
+            with langfuse_client.start_as_current_observation(
+                as_type='generation',
+                name=self.name,
+                metadata=self.metadata_observability,
+                input=self.input_llm,
+                trace_context={"trace_id": trace_id},
+            ) as span:
+                span.update_trace(
+                    name=self.name,
+                    user_id=self.metadata_observability.user_id)
+                output = await self._asafe_invoke(
+                    chain=chain,
+                    input_llm=self.input_llm,
+                    config=config,
+                )
+                span.update_trace(output=output)
+                return output
+
+
+        except Exception:
             logger.exception("❌ BaseGenerator agenerate error")
             return None
 
     @trace_runtime
     async def generate(self):
         try:
-            handler = self._get_langfuse_handler()
-            config = {"callbacks": [handler]} if handler else {}
+            config = self._get_langfuse_config()
             chain = self.prompt | self.llm
-
-            output = self._safe_invoke(
-                chain=chain,
-                input_llm=self.input_llm,
-                config=config,
-            )
-            return output
-
-        except Exception as e:
+            langfuse_client = self._get_langfuse_client()
+            trace_id = Langfuse.create_trace_id(seed=self.metadata_observability.task_id)
+
+            with langfuse_client.start_as_current_observation(
+                as_type='generation',
+                name=self.name,
+                metadata=self.metadata_observability,
+                input=self.input_llm,
+                trace_context={"trace_id": trace_id},
+            ) as span:
+                span.update_trace(
+                    name=self.name,
+                    user_id=self.metadata_observability.user_id)
+                output = self._safe_invoke(
+                    chain=chain,
+                    input_llm=self.input_llm,
+                    config=config,
+                )
+                span.update_trace(output=output)
+                return output
+
+        except Exception:
             logger.exception("❌ BaseGenerator generate error")
             return None

services/base/BaseGenerator_v2.py

@@ -0,0 +1,169 @@
+from langfuse import get_client, Langfuse, propagate_attributes
+from langfuse.langchain import CallbackHandler
+import os
+from config.constant import LangfuseConstants 
+from pydantic import BaseModel
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_openai import AzureChatOpenAI
+from tenacity import (
+    retry,
+    stop_after_attempt,
+    wait_exponential,
+    retry_if_exception_type
+)
+from typing import Dict
+from services.llms.LLM import model_5mini, model_4omini
+from utils.decorator import trace_runtime
+from utils.logger import get_logger
+
+logger = get_logger("base generator")
+
+# Set environment variables at module level
+os.environ["LANGFUSE_PUBLIC_KEY"] = LangfuseConstants.PUBLIC_KEY
+os.environ["LANGFUSE_SECRET_KEY"] = LangfuseConstants.SECRET_KEY
+os.environ["LANGFUSE_HOST"] = LangfuseConstants.HOST or "https://us.cloud.langfuse.com"
+
+
+class MetadataObservability(BaseModel):
+    fullname: str
+    task_id: str
+    agent: str
+    user_id: str
+
+
+class BaseAIGenerator:
+    def __init__(self,
+                 task_name: str,
+                 prompt: ChatPromptTemplate,
+                 input_llm: Dict,
+                 metadata_observability: MetadataObservability,
+                 llm: AzureChatOpenAI = model_5mini | model_4omini,
+                 ):
+        self.metadata_observability = metadata_observability
+        self.llm = llm
+        self.prompt = prompt
+        self.input_llm = input_llm
+        self.name = task_name
+
+    def _get_langfuse_client(self):
+        try:
+            # Environment variables already set at module level
+            return get_client()
+        except Exception as e:
+            logger.warning(f"⚠️ Langfuse unavailable, skipping observability: {e}")
+            return None
+
+    def _get_langfuse_config(self):
+        try:
+            # Environment variables already set at module level
+            handler = CallbackHandler()
+            
+            return {
+                "callbacks": [handler],
+                "metadata": {
+                    "langfuse_session_id": self.metadata_observability.task_id,
+                    "langfuse_user_id": self.metadata_observability.user_id,
+                    "langfuse_tags": [self.metadata_observability.agent],
+                },
+            }
+        except Exception as e:
+            logger.warning(f"⚠️ Langfuse unavailable, skipping observability: {e}")
+            return {}
+
+    @retry(
+        reraise=True,
+        stop=stop_after_attempt(2),
+        wait=wait_exponential(multiplier=1, min=1, max=5),
+        retry=retry_if_exception_type(Exception)
+    )
+    async def _asafe_invoke(self, chain, input_llm, config):
+        return await chain.ainvoke(input_llm, config=config)
+
+    @retry(
+        reraise=True,
+        stop=stop_after_attempt(2),
+        wait=wait_exponential(multiplier=1, min=1, max=5),
+        retry=retry_if_exception_type(Exception)
+    )
+    def _safe_invoke(self, chain, input_llm, config):
+        return chain.invoke(input_llm, config=config)
+
+    @trace_runtime
+    async def agenerate(self):
+        try:
+            config = self._get_langfuse_config()
+            chain = self.prompt | self.llm
+            langfuse_client = self._get_langfuse_client()
+            
+            if not langfuse_client:
+                return await self._asafe_invoke(chain, self.input_llm, config)
+            
+            trace_id = Langfuse.create_trace_id(seed=self.metadata_observability.task_id)
+
+            with langfuse_client.start_as_current_observation(
+                as_type="generation",
+                name=self.name,
+                trace_context={"trace_id": trace_id},
+                metadata=self.metadata_observability,
+            ) as span:
+                with propagate_attributes(
+                    user_id=self.metadata_observability.user_id,
+                    session_id=self.metadata_observability.task_id,
+                    tags=[self.metadata_observability.agent],
+                ):
+                    span.update_trace(
+                        input=self.input_llm,
+                    )
+                    
+                    output = await self._asafe_invoke(
+                        chain=chain,
+                        input_llm=self.input_llm,
+                        config=config,
+                    )
+                    
+                    span.update_trace(output=output)
+                    return output
+
+        except Exception:
+            logger.exception("❌ BaseGenerator agenerate error")
+            return None
+
+    @trace_runtime
+    def generate(self):
+        try:
+            config = self._get_langfuse_config()
+            chain = self.prompt | self.llm
+            langfuse_client = self._get_langfuse_client()
+            
+            if not langfuse_client:
+                return self._safe_invoke(chain, self.input_llm, config)
+            
+            trace_id = Langfuse.create_trace_id(seed=self.metadata_observability.task_id)
+
+            with langfuse_client.start_as_current_observation(
+                as_type="generation",
+                name=self.name,
+                trace_context={"trace_id": trace_id},
+                metadata=self.metadata_observability,
+            ) as span:
+                with propagate_attributes(
+                    user_id=self.metadata_observability.user_id,
+                    session_id=self.metadata_observability.task_id,
+                    tags=[self.metadata_observability.agent],
+                ):
+                    span.update_trace(
+                        input=self.input_llm,
+                    )
+                    
+                    output = self._safe_invoke(
+                        chain=chain,
+                        input_llm=self.input_llm,
+                        config=config,
+                    )
+                    
+                    span.update_trace(output=output)
+                    return output
+
+        except Exception:
+            logger.exception("❌ BaseGenerator generate error")
+            return None

services/knowledge/extract_profile.py

@@ -5,7 +5,8 @@ from typing import TypedDict, List, Dict, Union
 from langchain_core.prompts import ChatPromptTemplate
 
 from services.models.data_model import AIProfile, RawProfile, Profiles
-from services.base.BaseGenerator import BaseAIGenerator, MetadataObservability
+# from services.base.BaseGenerator import BaseAIGenerator, MetadataObservability
+from services.base.BaseGenerator_v2 import BaseAIGenerator, MetadataObservability
 from services.llms.LLM import model_5mini, model_4o_2
 from utils.decorator import trace_runtime
 from utils.logger import get_logger
@@ -16,6 +17,7 @@ logger = get_logger("profile extraction")
 from sqlalchemy.ext.asyncio import AsyncSession
 from externals.databases.pg_crud import (
     get_file_by_filename,
+    get_profile_by_filename,
     mark_file_extracted,
     create_profile,
 )
@@ -47,6 +49,9 @@ class KnowledgeExtractService:
 
         if file.is_extracted:
             logger.info(f"ℹ️ File already extracted: {filename}")
+            existing = await get_profile_by_filename(self.db, filename=filename, current_user=self.user)
+            if existing:
+                return existing
 
         # 2️⃣ Download PDF
         pdf_bytes: bytes = await download_blob_by_filename(
@@ -133,8 +138,12 @@ class KnowledgeExtractService:
 
     **Instructions**:
     1. Read the provided CV and extract information needed based on expected output.
-    2. Reformat the extracted info using correct word spacing.
-    3. Do not verbose, just return the final answer.
+    2. Be Careful when to extract information for gpa_edu_1, univ_edu_1, major_edu_1 or gpa_edu_2, univ_edu_2, major_edu_2 or gpa_edu_3, univ_edu_3, major_edu_3
+        ..._edu_1 is only for bachelor/undergraduate/sarjana degree
+        ..._edu_2 is only for master/postgraduate degree
+        ..._edu_3 is only for doctor/phd degree
+    3. Reformat the extracted info using correct word spacing.
+    4. Do not verbose, just return the final answer.
     """.strip()
             prompt = ChatPromptTemplate.from_template(extract_one_profile_prompt)
             input_llm = {
@@ -144,14 +153,15 @@ class KnowledgeExtractService:
             llm = model_4o_2.with_structured_output(AIProfile)
 
             gen_ai = BaseAIGenerator(
-                task_name=self.extract.__name__,
+                task_name="extract profile",
                 prompt=prompt,
                 input_llm=input_llm,
                 llm=llm,
                 metadata_observability=MetadataObservability(
                     fullname=self.user.full_name,
-                    task_id=str(self.user.user_id),
+                    task_id=str(uuid4()),
                     agent=self.extract.__name__,
+                    user_id=self.user.email,
                 )
             )
             result = await gen_ai.agenerate()

services/models/data_model.py

@@ -32,15 +32,15 @@ class AIProfile(TypedDict):
     fullname: str = Field(description="Fullname of the candidate", default="-")
     # gender: str = Field(description="Gender of the candidate, if available", default="null")
     # age: int = Field(description="Age in number")
-    gpa_edu_1: float = Field(description="""GPA of candidate's bachelor degree, if exists.""", default=0)
+    gpa_edu_1: float = Field(description="""GPA of candidate's bachelor degree (same like sarjana, s1, undergradute), if exists.""", default=0)
     univ_edu_1: str = Field(description="""University where candidate take bachelor degree, if exists.""", default="-")
     major_edu_1: str = Field(description="""Major of candidate's bachelor degree, if exists.""", default="-")
     
-    gpa_edu_2: float = Field(description="""GPA of candidate's master degree, if exists.""", default=0)
+    gpa_edu_2: float = Field(description="""GPA of candidate's master degree (same like master, s2, postgraduate), if exists.""", default=0)
     univ_edu_2: str = Field(description="""University where candidate take master degree, if exists.""", default="-")
     major_edu_2: str = Field(description="""Major of candidate's master degree, if exists.""", default="-")
     
-    gpa_edu_3: float = Field(description="""GPA of candidate's doctoral or phd degree, if exists.""", default=0)
+    gpa_edu_3: float = Field(description="""GPA of candidate's doctoral or phd degree (same like phd, s3, doctoral), if exists.""", default=0)
     univ_edu_3: str = Field(description="""University where candidate take doctoral or phd degree, if exists.""", default="-")
     major_edu_3: str = Field(description="""Major of candidate's doctoral or phd degree, if exists.""", default="-")
     

streamlit_app.py

@@ -0,0 +1,725 @@
+import os
+import dotenv
+dotenv.load_dotenv()
+import json
+import requests
+import streamlit as st
+
+# ─────────────────────────────────────────────
+# CONFIG
+# ─────────────────────────────────────────────
+BASE_URL = os.environ.get("BACKEND_BASE_URL", "http://localhost:8000")
+
+st.set_page_config(
+    page_title="Candidate Explorer",
+    page_icon="🔍",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+# ─────────────────────────────────────────────
+# GLOBAL CSS
+# ─────────────────────────────────────────────
+st.markdown(
+    """
+    <style>
+    /* ── Global ─────────────────────────────── */
+    html, body, [class*="css"] {
+        font-family: 'Inter', 'Segoe UI', sans-serif;
+        color: #333e4a;
+        background-color: #ffffff;
+    }
+
+    /* ── Sidebar ─────────────────────────────── */
+    [data-testid="stSidebar"] {
+        background-color: #f4f6ff;
+        border-right: 1px solid #c7cef5;
+    }
+    [data-testid="stSidebar"] h1,
+    [data-testid="stSidebar"] h2,
+    [data-testid="stSidebar"] h3,
+    [data-testid="stSidebar"] label {
+        color: #435cdc !important;
+    }
+
+    /* ── Buttons ─────────────────────────────── */
+    .stButton > button {
+        background-color: #435cdc;
+        color: #ffffff;
+        border: none;
+        border-radius: 8px;
+        padding: 0.5rem 1.25rem;
+        font-weight: 600;
+        transition: background-color 0.2s ease;
+    }
+    .stButton > button:hover {
+        background-color: #7b8de7;
+        color: #ffffff;
+    }
+    .stButton > button:focus {
+        outline: 2px solid #c7cef5;
+    }
+
+    /* ── Tabs ─────────────────────────────────── */
+    [data-baseweb="tab-list"] {
+        gap: 8px;
+        border-bottom: 2px solid #c7cef5;
+    }
+    [data-baseweb="tab"] {
+        border-radius: 8px 8px 0 0;
+        padding: 0.5rem 1.25rem;
+        font-weight: 600;
+        color: #7b8de7;
+        background: transparent;
+    }
+    [aria-selected="true"][data-baseweb="tab"] {
+        color: #435cdc !important;
+        border-bottom: 3px solid #435cdc !important;
+        background: #f4f6ff;
+    }
+
+    /* ── Inputs ──────────────────────────────── */
+    [data-testid="stTextInput"] input,
+    [data-testid="stSelectbox"] select,
+    textarea {
+        border-radius: 8px !important;
+        border: 1.5px solid #c7cef5 !important;
+        color: #333e4a !important;
+    }
+    [data-testid="stTextInput"] input:focus,
+    textarea:focus {
+        border-color: #435cdc !important;
+        box-shadow: 0 0 0 2px #c7cef5;
+    }
+
+    /* ── File uploader ───────────────────────── */
+    [data-testid="stFileUploader"] {
+        border: 2px dashed #7b8de7;
+        border-radius: 10px;
+        background: #f4f6ff;
+        padding: 1rem;
+    }
+
+    /* ── Metric cards ────────────────────────── */
+    .scorecard-wrap {
+        display: flex;
+        gap: 1rem;
+        margin-bottom: 1.5rem;
+    }
+    .scorecard-card {
+        flex: 1;
+        background: #f4f6ff;
+        border: 1.5px solid #c7cef5;
+        border-radius: 12px;
+        padding: 1.25rem 1.5rem;
+        box-shadow: 0 2px 8px rgba(67,92,220,0.07);
+        text-align: center;
+    }
+    .scorecard-card .sc-label {
+        font-size: 0.82rem;
+        font-weight: 600;
+        color: #7b8de7;
+        text-transform: uppercase;
+        letter-spacing: 0.04em;
+        margin-bottom: 0.4rem;
+    }
+    .scorecard-card .sc-value {
+        font-size: 2rem;
+        font-weight: 800;
+        color: #435cdc;
+        line-height: 1.1;
+    }
+    .scorecard-card .sc-sub {
+        font-size: 0.78rem;
+        color: #7b8de7;
+        margin-top: 0.2rem;
+    }
+
+    /* ── Badge ───────────────────────────────── */
+    .badge-success {
+        background: #c7cef5; color: #435cdc;
+        border-radius: 99px; padding: 2px 10px;
+        font-size: 0.78rem; font-weight: 700;
+    }
+    .badge-warn {
+        background: #fff3c4; color: #a07c00;
+        border-radius: 99px; padding: 2px 10px;
+        font-size: 0.78rem; font-weight: 700;
+    }
+    .badge-error {
+        background: #fde8e8; color: #c0392b;
+        border-radius: 99px; padding: 2px 10px;
+        font-size: 0.78rem; font-weight: 700;
+    }
+
+    /* ── Section header ──────────────────────── */
+    .section-title {
+        font-size: 1.15rem;
+        font-weight: 700;
+        color: #435cdc;
+        margin-bottom: 0.75rem;
+        display: flex;
+        align-items: center;
+        gap: 0.4rem;
+    }
+    .section-title::after {
+        content: '';
+        flex: 1;
+        height: 2px;
+        background: linear-gradient(90deg, #c7cef5, transparent);
+        margin-left: 0.5rem;
+    }
+
+    /* ── Login card ──────────────────────────── */
+    .login-card {
+        max-width: 420px;
+        margin: 4rem auto;
+        padding: 2.5rem 2rem;
+        background: #ffffff;
+        border-radius: 16px;
+        box-shadow: 0 4px 32px rgba(67,92,220,0.13);
+        border: 1.5px solid #c7cef5;
+    }
+    .login-card h1 {
+        color: #435cdc;
+        font-size: 1.8rem;
+        font-weight: 800;
+        margin-bottom: 0.25rem;
+    }
+    .login-card p {
+        color: #7b8de7;
+        font-size: 0.95rem;
+        margin-bottom: 1.5rem;
+    }
+
+    /* ── Divider ─────────────────────────────── */
+    hr.styled { border: none; border-top: 1.5px solid #c7cef5; margin: 1.2rem 0; }
+
+    /* ── JSON output ─────────────────────────── */
+    .profile-json {
+        background: #f4f6ff;
+        border-radius: 10px;
+        border: 1.5px solid #c7cef5;
+        padding: 1rem 1.25rem;
+        font-size: 0.85rem;
+        color: #333e4a;
+        white-space: pre-wrap;
+        word-break: break-word;
+        max-height: 500px;
+        overflow-y: auto;
+    }
+
+    /* ── Table ───────────────────────────────── */
+    [data-testid="stDataFrame"] {
+        border-radius: 10px;
+        overflow: hidden;
+        border: 1.5px solid #c7cef5;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
+
+# ─────────────────────────────────────────────
+# SESSION STATE INIT
+# ─────────────────────────────────────────────
+for key, default in [
+    ("token", None),
+    ("user", None),
+    ("upload_results", []),
+    ("extract_result", None),
+    ("user_files", []),
+]:
+    if key not in st.session_state:
+        st.session_state[key] = default
+
+
+# ─────────────────────────────────────────────
+# API HELPERS
+# ─────────────────────────────────────────────
+def _headers():
+    return {"Authorization": f"Bearer {st.session_state.token}"}
+
+
+def api_login(email: str, password: str):
+    """POST /admin/login — returns (token, error_msg)"""
+    try:
+        resp = requests.post(
+            f"{BASE_URL}/admin/login",
+            data={"username": email, "password": password},
+            timeout=15,
+        )
+        if resp.status_code == 200:
+            return resp.json().get("access_token"), None
+        detail = resp.json().get("detail", resp.text)
+        return None, str(detail)
+    except requests.exceptions.ConnectionError:
+        return None, "Cannot connect to backend. Check BACKEND_BASE_URL."
+    except Exception as e:
+        return None, str(e)
+
+
+def api_get_me():
+    """GET /admin/me — returns user dict"""
+    try:
+        resp = requests.get(f"{BASE_URL}/admin/me", headers=_headers(), timeout=10)
+        if resp.status_code == 200:
+            return resp.json(), None
+        return None, resp.json().get("detail", resp.text)
+    except Exception as e:
+        return None, str(e)
+
+
+def api_get_scorecard():
+    """GET /file/score_card — returns data dict"""
+    try:
+        resp = requests.get(f"{BASE_URL}/file/score_card", headers=_headers(), timeout=10)
+        if resp.status_code == 200:
+            return resp.json().get("data", {}), None
+        return None, resp.json().get("detail", resp.text)
+    except Exception as e:
+        return None, str(e)
+
+
+def api_upload_files(uploaded_files):
+    """POST /file/upload — returns list of results"""
+    try:
+        files = [
+            ("files", (f.name, f.read(), "application/pdf"))
+            for f in uploaded_files
+        ]
+        resp = requests.post(
+            f"{BASE_URL}/file/upload",
+            headers=_headers(),
+            files=files,
+            timeout=60,
+        )
+        if resp.status_code == 201:
+            return resp.json().get("files", []), None
+        return None, resp.json().get("detail", resp.text)
+    except Exception as e:
+        return None, str(e)
+
+
+def api_get_user_files(user_id: str):
+    """GET /file/user/{user_id} — returns list of file dicts"""
+    try:
+        resp = requests.get(
+            f"{BASE_URL}/file/user/{user_id}",
+            headers=_headers(),
+            timeout=10,
+        )
+        if resp.status_code == 200:
+            return resp.json().get("files", []), None
+        return None, resp.json().get("detail", resp.text)
+    except Exception as e:
+        return None, str(e)
+
+
+def api_extract_profile(filename: str):
+    """POST /profile/extract_profile?filename=... — returns profile dict"""
+    try:
+        resp = requests.post(
+            f"{BASE_URL}/profile/extract_profile",
+            headers=_headers(),
+            params={"filename": filename},
+            timeout=120,
+        )
+        if resp.status_code == 200:
+            return resp.json(), None
+        return None, resp.json().get("detail", resp.text)
+    except Exception as e:
+        return None, str(e)
+
+
+def api_delete_file(filename: str):
+    """DELETE /file/{filename}"""
+    try:
+        resp = requests.delete(
+            f"{BASE_URL}/file/{filename}",
+            headers=_headers(),
+            timeout=15,
+        )
+        if resp.status_code == 200:
+            return True, None
+        return False, resp.json().get("detail", resp.text)
+    except Exception as e:
+        return False, str(e)
+
+
+# ─────────────────────────────────────────────
+# UI COMPONENTS
+# ─────────────────────────────────────────────
+def render_scorecard():
+    sc, err = api_get_scorecard()
+    if err:
+        st.warning(f"Could not load scorecard: {err}")
+        return
+
+    total_file = sc.get("total_file", 0)
+    total_extracted = sc.get("total_extracted", 0)
+    pct = sc.get("percent_extracted", 0)
+    # percent_extracted may be a float like 75.0 or string "75%"
+    if isinstance(pct, str):
+        pct_display = pct
+    else:
+        pct_display = f"{pct:.1f}%"
+
+    st.markdown(
+        f"""
+        <div class="scorecard-wrap">
+            <div class="scorecard-card">
+                <div class="sc-label">📁 Total CVs Uploaded</div>
+                <div class="sc-value">{total_file}</div>
+                <div class="sc-sub">files in your workspace</div>
+            </div>
+            <div class="scorecard-card">
+                <div class="sc-label">✅ Profiles Extracted</div>
+                <div class="sc-value">{total_extracted}</div>
+                <div class="sc-sub">structured profiles</div>
+            </div>
+            <div class="scorecard-card">
+                <div class="sc-label">📊 Extraction Rate</div>
+                <div class="sc-value" style="color:#dcc343">{pct_display}</div>
+                <div class="sc-sub">of uploaded CVs processed</div>
+            </div>
+        </div>
+        """,
+        unsafe_allow_html=True,
+    )
+
+
+def render_sidebar():
+    user = st.session_state.user or {}
+    with st.sidebar:
+        st.markdown(
+            f"""
+            <div style="text-align:center;padding:1rem 0 0.5rem;">
+                <div style="font-size:2.5rem;">👤</div>
+                <div style="font-weight:800;font-size:1.1rem;color:#435cdc;">
+                    {user.get('full_name', 'User')}
+                </div>
+                <div style="font-size:0.82rem;color:#7b8de7;margin-top:2px;">
+                    {user.get('email', '')}
+                </div>
+                <span class="badge-success" style="margin-top:6px;display:inline-block;">
+                    {user.get('role', 'user').upper()}
+                </span>
+            </div>
+            <hr class="styled">
+            """,
+            unsafe_allow_html=True,
+        )
+
+        # st.markdown(
+        #     "<div style='font-size:0.78rem;color:#7b8de7;margin-bottom:4px;'>BACKEND</div>",
+        #     unsafe_allow_html=True,
+        # )
+        # st.markdown(
+        #     f"<code style='font-size:0.75rem;color:#435cdc;'>{BASE_URL}</code>",
+        #     unsafe_allow_html=True,
+        # )
+
+        # st.markdown("<hr class='styled'>", unsafe_allow_html=True)
+
+        if st.button("🚪 Logout", use_container_width=True):
+            for key in ["token", "user", "upload_results", "extract_result", "user_files"]:
+                st.session_state[key] = None if key in ("token", "user", "extract_result") else []
+            st.rerun()
+
+
+# ─────────────────────────────────────────────
+# PAGES
+# ─────────────────────────────────────────────
+def page_login():
+    # Center the login card
+    _, col, _ = st.columns([1, 1.4, 1])
+    with col:
+        st.markdown(
+            """
+            <div class="login-card">
+                <h1>🔍 Candidate Explorer</h1>
+                <p>Sign in to manage and analyze candidate CVs.</p>
+            </div>
+            """,
+            unsafe_allow_html=True,
+        )
+
+        with st.form("login_form", clear_on_submit=False):
+            st.markdown(
+                "<div class='section-title'>Sign In</div>", unsafe_allow_html=True
+            )
+            email = st.text_input("Email address", placeholder="you@company.com")
+            password = st.text_input("Password", type="password", placeholder="••••••••")
+            submitted = st.form_submit_button("Sign In →", use_container_width=True)
+
+        if submitted:
+            if not email or not password:
+                st.error("Please enter both email and password.")
+            else:
+                with st.spinner("Signing in…"):
+                    token, err = api_login(email, password)
+                if err:
+                    st.error(f"Login failed: {err}")
+                else:
+                    st.session_state.token = token
+                    user, err2 = api_get_me()
+                    if err2:
+                        st.session_state.user = {"email": email, "full_name": email, "role": "user"}
+                    else:
+                        st.session_state.user = user
+                    st.rerun()
+
+
+def page_main():
+    render_sidebar()
+
+    # ── Page header ──────────────────────────────
+    st.markdown(
+        "<h1 style='color:#435cdc;font-size:1.75rem;font-weight:800;margin-bottom:0.1rem;'>"
+        "🔍 Candidate Explorer"
+        "</h1>"
+        "<p style='color:#7b8de7;margin-top:0;margin-bottom:1.25rem;font-size:0.95rem;'>"
+        "Upload CVs, extract candidate profiles, and track your workspace.</p>",
+        unsafe_allow_html=True,
+    )
+
+    # ── Scorecard ─────────────────────────────────
+    st.markdown("<div class='section-title'>📊 Dashboard Overview</div>", unsafe_allow_html=True)
+    render_scorecard()
+
+    st.markdown("<hr class='styled'>", unsafe_allow_html=True)
+
+    # ── Tabs ──────────────────────────────────────
+    tab_upload, tab_extract = st.tabs(["📁  Upload CV", "🧠  Extract Profile"])
+
+    # ══════════════════════════════════════════
+    # TAB 1 — UPLOAD
+    # ══════════════════════════════════════════
+    with tab_upload:
+        st.markdown("<br>", unsafe_allow_html=True)
+        st.markdown(
+            "<div class='section-title'>Upload Candidate CVs</div>",
+            unsafe_allow_html=True,
+        )
+
+        uploaded = st.file_uploader(
+            "Drop PDF files here or click to browse",
+            type=["pdf"],
+            accept_multiple_files=True,
+            help="Only PDF files are accepted.",
+        )
+
+        col_btn, col_info = st.columns([1, 3])
+        with col_btn:
+            do_upload = st.button("⬆️  Upload", use_container_width=True, disabled=not uploaded)
+
+        if do_upload and uploaded:
+            with st.spinner(f"Uploading {len(uploaded)} file(s)…"):
+                results, err = api_upload_files(uploaded)
+            if err:
+                st.error(f"Upload failed: {err}")
+            else:
+                st.session_state.upload_results = results
+                # Refresh user files list
+                user = st.session_state.user or {}
+                uid = str(user.get("user_id", ""))
+                if uid:
+                    files, _ = api_get_user_files(uid)
+                    st.session_state.user_files = files or []
+                st.rerun()
+
+        # ── Results table ──
+        if st.session_state.upload_results:
+            st.markdown("<hr class='styled'>", unsafe_allow_html=True)
+            st.markdown(
+                "<div class='section-title'>Upload Results</div>",
+                unsafe_allow_html=True,
+            )
+            for r in st.session_state.upload_results:
+                fname = r.get("filename", r.get("name", ""))
+                status = r.get("status", "uploaded")
+                badge_cls = "badge-success" if "success" in status.lower() or status == "uploaded" else "badge-error"
+                st.markdown(
+                    f"<span class='badge-success'>✓</span>&nbsp;"
+                    f"<strong style='color:#333e4a;'>{fname}</strong>&nbsp;"
+                    f"<span class='{badge_cls}'>{status}</span>",
+                    unsafe_allow_html=True,
+                )
+
+        # ── Existing files ──
+        st.markdown("<hr class='styled'>", unsafe_allow_html=True)
+        st.markdown(
+            "<div class='section-title'>Your Uploaded Files</div>",
+            unsafe_allow_html=True,
+        )
+
+        user = st.session_state.user or {}
+        uid = str(user.get("user_id", ""))
+
+        col_refresh, _ = st.columns([1, 5])
+        with col_refresh:
+            if st.button("🔄 Refresh List", use_container_width=True):
+                if uid:
+                    files, err = api_get_user_files(uid)
+                    if err:
+                        st.warning(f"Could not load files: {err}")
+                    else:
+                        st.session_state.user_files = files or []
+
+        if not st.session_state.user_files and uid:
+            # Auto-load on first visit
+            files, _ = api_get_user_files(uid)
+            st.session_state.user_files = files or []
+
+        if st.session_state.user_files:
+            rows = []
+            for f in st.session_state.user_files:
+                rows.append(
+                    {
+                        "Filename": f.get("filename", ""),
+                        "Type": f.get("file_type", ""),
+                        "Extracted": "✅" if f.get("is_extracted") else "⏳",
+                        "Uploaded": str(f.get("uploaded_at", ""))[:19],
+                    }
+                )
+            st.dataframe(rows, use_container_width=True, hide_index=True)
+        else:
+            st.info("No files uploaded yet.")
+
+    # ══════════════════════════════════════════
+    # TAB 2 — EXTRACT PROFILE
+    # ══════════════════════════════════════════
+    with tab_extract:
+        st.markdown("<br>", unsafe_allow_html=True)
+        st.markdown(
+            "<div class='section-title'>Extract Structured Profile from CV</div>",
+            unsafe_allow_html=True,
+        )
+
+        # Load files if needed
+        user = st.session_state.user or {}
+        uid = str(user.get("user_id", ""))
+        if not st.session_state.user_files and uid:
+            files, _ = api_get_user_files(uid)
+            st.session_state.user_files = files or []
+
+        file_options = [f.get("filename", "") for f in st.session_state.user_files if f.get("filename")]
+
+        if not file_options:
+            st.info("No CVs found. Upload files first in the **Upload CV** tab.")
+        else:
+            col_sel, col_ex = st.columns([3, 1])
+            with col_sel:
+                chosen = st.selectbox(
+                    "Select a CV file to extract",
+                    options=file_options,
+                    help="Choose a PDF you have already uploaded.",
+                )
+            with col_ex:
+                st.markdown("<div style='margin-top:1.72rem;'></div>", unsafe_allow_html=True)
+                do_extract = st.button("🧠  Extract", use_container_width=True)
+
+            if do_extract and chosen:
+                with st.spinner(f"Extracting profile from **{chosen}**… this may take a moment."):
+                    result, err = api_extract_profile(chosen)
+                if err:
+                    st.error(f"Extraction failed: {err}")
+                    st.session_state.extract_result = None
+                else:
+                    st.session_state.extract_result = result
+                    # Refresh files to update is_extracted flag
+                    if uid:
+                        files, _ = api_get_user_files(uid)
+                        st.session_state.user_files = files or []
+                    st.rerun()
+
+        # ── Display extracted profile ──
+        if st.session_state.extract_result:
+            st.markdown("<hr class='styled'>", unsafe_allow_html=True)
+            result = st.session_state.extract_result
+
+            # Try to highlight key fields
+            fullname = result.get("fullname") or result.get("full_name", "")
+            if fullname:
+                st.markdown(
+                    f"<div style='background:#c7cef5;border-radius:10px;padding:0.75rem 1.2rem;"
+                    f"margin-bottom:1rem;'>"
+                    f"<span style='color:#435cdc;font-weight:800;font-size:1.1rem;'>👤 {fullname}</span>"
+                    f"</div>",
+                    unsafe_allow_html=True,
+                )
+
+            col_l, col_r = st.columns(2)
+
+            with col_l:
+                st.markdown("<div class='section-title'>Education</div>", unsafe_allow_html=True)
+                for i in range(1, 4):
+                    univ = result.get(f"univ_edu_{i}", "")
+                    major = result.get(f"major_edu_{i}", "")
+                    gpa = result.get(f"gpa_edu_{i}", "")
+                    if univ or major:
+                        gpa_str = f" · GPA {gpa}" if gpa else ""
+                        st.markdown(
+                            f"<div style='margin-bottom:0.5rem;padding:0.6rem 1rem;"
+                            f"background:#f4f6ff;border-radius:8px;border-left:3px solid #435cdc;'>"
+                            f"<strong style='color:#333e4a;'>{univ or '—'}</strong><br>"
+                            f"<span style='color:#7b8de7;font-size:0.85rem;'>{major or ''}{gpa_str}</span>"
+                            f"</div>",
+                            unsafe_allow_html=True,
+                        )
+
+                st.markdown("<div class='section-title' style='margin-top:1rem;'>Experience</div>", unsafe_allow_html=True)
+                yoe = result.get("yoe")
+                domicile = result.get("domicile", "")
+                st.markdown(
+                    f"<div style='padding:0.6rem 1rem;background:#f4f6ff;border-radius:8px;"
+                    f"border-left:3px solid #dcc343;'>"
+                    f"<span style='color:#333e4a;font-weight:600;'>Years of Experience:</span> "
+                    f"<span style='color:#435cdc;font-weight:800;'>{yoe if yoe is not None else '—'}</span><br>"
+                    f"<span style='color:#333e4a;font-weight:600;'>Domicile:</span> "
+                    f"<span style='color:#435cdc;'>{domicile or '—'}</span>"
+                    f"</div>",
+                    unsafe_allow_html=True,
+                )
+
+            with col_r:
+                def _tag_list(label, items, color="#c7cef5", text_color="#435cdc"):
+                    if not items:
+                        return
+                    st.markdown(
+                        f"<div class='section-title'>{label}</div>",
+                        unsafe_allow_html=True,
+                    )
+                    tags = "".join(
+                        f"<span style='background:{color};color:{text_color};border-radius:99px;"
+                        f"padding:3px 10px;font-size:0.78rem;font-weight:600;margin:2px;display:inline-block;'>"
+                        f"{t}</span>"
+                        for t in items
+                    )
+                    st.markdown(
+                        f"<div style='margin-bottom:0.75rem;line-height:2;'>{tags}</div>",
+                        unsafe_allow_html=True,
+                    )
+
+                _tag_list("💻 Hard Skills", result.get("hardskills", []))
+                _tag_list("🤝 Soft Skills", result.get("softskills", []), "#f4f6ff", "#333e4a")
+                _tag_list("🏆 Certifications", result.get("certifications", []), "#fff3c4", "#a07c00")
+                _tag_list("🏢 Business Domains", result.get("business_domain", []), "#c7cef5", "#435cdc")
+
+            # Raw JSON toggle
+            with st.expander("📄 Raw JSON response"):
+                st.markdown(
+                    f"<div class='profile-json'>{json.dumps(result, indent=2, default=str)}</div>",
+                    unsafe_allow_html=True,
+                )
+
+
+# ─────────────────────────────────────────────
+# ROUTER
+# ─────────────────────────────────────────────
+if st.session_state.token:
+    page_main()
+else:
+    page_login()

utils/decorator.py

@@ -5,7 +5,7 @@ import time
 
 from functools import wraps
 from typing import Callable, Any
-from sqlalchemy.exc import OperationalError, InterfaceError
+from sqlalchemy.exc import OperationalError, InterfaceError, PendingRollbackError
 
 def trace_runtime(func: Callable) -> Callable:
     @wraps(func)

uv.lock

@@ -100,6 +100,22 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fb/76/641ae371508676492379f16e2fa48f4e2c11741bd63c48be4b12a6b09cba/aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e", size = 7490, upload-time = "2025-07-03T22:54:42.156Z" },
 ]
 
+[[package]]
+name = "altair"
+version = "6.0.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jinja2" },
+    { name = "jsonschema" },
+    { name = "narwhals" },
+    { name = "packaging" },
+    { name = "typing-extensions", marker = "python_full_version < '3.15'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f7/c0/184a89bd5feba14ff3c41cfaf1dd8a82c05f5ceedbc92145e17042eb08a4/altair-6.0.0.tar.gz", hash = "sha256:614bf5ecbe2337347b590afb111929aa9c16c9527c4887d96c9bc7f6640756b4", size = 763834, upload-time = "2025-11-12T08:59:11.519Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/db/33/ef2f2409450ef6daa61459d5de5c08128e7d3edb773fefd0a324d1310238/altair-6.0.0-py3-none-any.whl", hash = "sha256:09ae95b53d5fe5b16987dccc785a7af8588f2dca50de1e7a156efa8a461515f8", size = 795410, upload-time = "2025-11-12T08:59:09.804Z" },
+]
+
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