feat: CV Batches system with AI extraction, matching, and slide-in chat

ai_service.py

@@ -456,3 +456,160 @@ def chat(user_message: str, conversation_history: list = None, context: str = ""
     messages.append({"role": "user", "content": user_message})
     
     return llm_chat(messages, temperature=0.5, max_tokens=2000)
+
+
+# ============================================================
+# BATCH FUNCTIONS — extract requirements, match candidates, batch chat
+# ============================================================
+
+EXTRACT_REQUIREMENTS_PROMPT = """You are a requirements analyst. Analyze the following document and extract the job positions and their requirements.
+
+Return ONLY a valid JSON object with this structure:
+{
+  "batch_name": "Short name for this batch (from the document title or first heading)",
+  "description": "Brief description of what this batch is for (1-2 sentences)",
+  "positions": [
+    {
+      "job_title": "Position title",
+      "num_positions": 1,
+      "required_skills": ["skill1", "skill2"],
+      "required_years": 5,
+      "required_certs": ["cert1"],
+      "nice_to_have": ["skill3"],
+      "disqualifiers": ["something that would disqualify a candidate"],
+      "description": "Brief description of the role"
+    }
+  ]
+}
+
+Rules:
+- Extract ALL positions mentioned in the document.
+- If a field is not specified, use empty string "" or empty array [].
+- Be precise about required skills — distinguish must-haves from nice-to-haves.
+- If no positions are found, return an empty positions array.
+- Return ONLY the JSON, no other text.
+
+Document text:
+---
+__DOC_TEXT__
+---"""
+
+def extract_requirements(doc_text: str) -> dict:
+    """Extract job requirements from a document using AI."""
+    max_chars = 15000
+    if len(doc_text) > max_chars:
+        doc_text = doc_text[:max_chars] + "\n[...truncated...]"
+    
+    prompt = EXTRACT_REQUIREMENTS_PROMPT.replace("__DOC_TEXT__", doc_text)
+    messages = [
+        {"role": "system", "content": "You are a requirements analyst that outputs only valid JSON. Make sure all string values are properly escaped."},
+        {"role": "user", "content": prompt}
+    ]
+    
+    for max_tokens in [4000, 6000, 8000]:
+        try:
+            resp = llm_chat(messages, temperature=0.1, max_tokens=max_tokens)
+            return extract_json(resp)
+        except (ValueError, json.JSONDecodeError):
+            if max_tokens == 8000:
+                raise
+            continue
+
+
+MATCH_PROMPT = """You are a CV matching specialist. You are given a job position's requirements and a list of candidates with their skills, experience, education, and certifications.
+
+For each candidate, determine:
+1. A match score (0-100) based on how well they meet the requirements
+2. Whether they are a good fit (score >= 60)
+3. A brief reasoning for the match or mismatch
+4. If they are a close match (score 50-79), suggest how their CV could be realigned (reworded) to better fit — without fabricating skills they don't have
+
+Return ONLY a valid JSON array of matching candidates:
+[
+  {
+    "candidate_id": "the UUID",
+    "candidate_name": "First Last",
+    "match_score": 85,
+    "fit": true,
+    "reasoning": "Strong match: has 7 years Python, AWS cert, Kubernetes experience",
+    "realignment_suggestion": "Emphasize microservices architecture experience over generic 'distributed systems' wording; reorder skills to put AWS and Kubernetes first"
+  }
+]
+
+Only include candidates with match_score >= 40. Sort by match_score descending.
+Return ONLY the JSON array, no other text.
+
+Position Requirements:
+__POSITION__
+
+Candidates:
+__CANDIDATES__"""
+
+def match_candidates_for_position(position: dict, candidates: list) -> list:
+    """Match candidates against a single position's requirements using AI."""
+    # Build a compact summary of each candidate for the LLM
+    cand_summaries = []
+    for c in candidates:
+        skills = ", ".join([s.get("skill_name", "") for s in c.get("skills", [])[:15]])
+        exp = "; ".join([f"{e.get('position','')} at {e.get('company','')}" for e in c.get("experience", [])[:5]])
+        certs = ", ".join([cert.get("name", "") for cert in c.get("certifications", [])[:5]])
+        edu = "; ".join([f"{e.get('degree','')} {e.get('field_of_study','')} at {e.get('institution','')}" for e in c.get("education", [])[:3]])
+        
+        cand_summaries.append(f"""Candidate ID: {c.get('id', 'N/A')}
+Name: {c.get('first_name', '')} {c.get('last_name', '')}
+Skills: {skills}
+Experience: {exp}
+Certifications: {certs}
+Education: {edu}
+Summary: {c.get('summary', '')[:200]}""")
+    
+    position_json = json.dumps(position, indent=2)
+    candidates_text = "\n\n---\n\n".join(cand_summaries)
+    
+    prompt = MATCH_PROMPT.replace("__POSITION__", position_json).replace("__CANDIDATES__", candidates_text)
+    messages = [
+        {"role": "system", "content": "You are a CV matching specialist that outputs only valid JSON. Make sure all string values are properly escaped."},
+        {"role": "user", "content": prompt}
+    ]
+    
+    for max_tokens in [4000, 6000, 8000]:
+        try:
+            resp = llm_chat(messages, temperature=0.1, max_tokens=max_tokens)
+            result = extract_json(resp)
+            if isinstance(result, list):
+                return result
+            elif isinstance(result, dict) and 'candidates' in result:
+                return result['candidates']
+            return [result]
+        except (ValueError, json.JSONDecodeError):
+            if max_tokens == 8000:
+                raise
+            continue
+    return []
+
+
+BATCH_CHAT_SYSTEM = """You are an AI assistant helping a user manage a CV batch. You have context about the batch (name, description, positions, and matched candidates).
+
+You can help the user with:
+1. Discussing which candidates are best for specific positions
+2. Suggesting CV realignment — rewording a candidate's experience to better match a position (without fabricating)
+3. Answering questions about candidate qualifications
+4. Recommending which candidates to approve or remove
+
+Be concise and direct. When suggesting changes, be specific about what to change and why.
+
+Batch context:
+__BATCH_CONTEXT__"""
+
+def batch_chat(user_message: str, batch_context: str, conversation_history: list = None) -> str:
+    """Context-aware chat for a specific batch."""
+    system_content = BATCH_CHAT_SYSTEM.replace("__BATCH_CONTEXT__", batch_context)
+    messages = [{"role": "system", "content": system_content}]
+    
+    if conversation_history:
+        for msg in conversation_history[-10:]:
+            messages.append({"role": msg["role"], "content": msg["content"]})
+    
+    messages.append({"role": "user", "content": user_message})
+    
+    return llm_chat(messages, temperature=0.5, max_tokens=3000)

database.py

@@ -181,6 +181,61 @@ CREATE INDEX IF NOT EXISTS idx_certifications_candidate ON certifications(candid
 CREATE INDEX IF NOT EXISTS idx_generated_cvs_candidate ON generated_cvs(candidate_id);
 CREATE INDEX IF NOT EXISTS idx_generated_cvs_requirement ON generated_cvs(requirement_request_id);
 CREATE INDEX IF NOT EXISTS idx_chat_messages_conversation ON chat_messages(conversation_id);
+
+-- ============================================================
+-- CV BATCHES — group candidates for a specific requirement
+-- ============================================================
+
+-- Main batch table (one per requirement document or manual creation)
+CREATE TABLE IF NOT EXISTS cv_batches (
+    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
+    name VARCHAR(255) NOT NULL,
+    description TEXT,
+    -- Raw text of the uploaded requirements document (backend-only, AI use)
+    -- Null for manually created batches
+    requirements_text TEXT,
+    -- JSON array of positions extracted from the document
+    -- [{job_title, num_positions, required_skills, required_years, required_certs, description}]
+    positions JSONB DEFAULT '[]',
+    -- draft = still working, active = matching done, exported = CVs generated
+    status VARCHAR(50) DEFAULT 'draft',
+    created_at TIMESTAMPTZ DEFAULT NOW(),
+    updated_at TIMESTAMPTZ DEFAULT NOW()
+);
+
+-- Batch items (candidates linked to a batch)
+CREATE TABLE IF NOT EXISTS batch_items (
+    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
+    batch_id UUID REFERENCES cv_batches(id) ON DELETE CASCADE,
+    candidate_id UUID REFERENCES candidates(id) ON DELETE CASCADE,
+    -- Which position in the batch this candidate is matched to (free text)
+    position_title VARCHAR(255),
+    -- AI match score 0-100
+    match_score INTEGER DEFAULT 0,
+    -- AI reasoning for the match
+    match_reasoning TEXT,
+    -- Realigned CV data (JSON — the reworded CV for this specific post)
+    realigned_cv_data JSONB,
+    -- proposed = AI suggested, approved = user confirmed, removed = user rejected
+    status VARCHAR(50) DEFAULT 'proposed',
+    -- Path to generated PDF after generation
+    generated_cv_path TEXT,
+    created_at TIMESTAMPTZ DEFAULT NOW(),
+    updated_at TIMESTAMPTZ DEFAULT NOW()
+);
+
+-- Batch chat (messages per batch's discussion)
+CREATE TABLE IF NOT EXISTS batch_chat (
+    id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
+    batch_id UUID REFERENCES cv_batches(id) ON DELETE CASCADE,
+    role VARCHAR(50) NOT NULL,    -- 'user' or 'assistant'
+    content TEXT NOT NULL,
+    created_at TIMESTAMPTZ DEFAULT NOW()
+);
+
+CREATE INDEX IF NOT EXISTS idx_batch_items_batch ON batch_items(batch_id);
+CREATE INDEX IF NOT EXISTS idx_batch_items_candidate ON batch_items(candidate_id);
+CREATE INDEX IF NOT EXISTS idx_batch_chat_batch ON batch_chat(batch_id);
 """
 
 

main.py

@@ -12,6 +12,7 @@ from fastapi.middleware.cors import CORSMiddleware
 from pathlib import Path
 
 import database as db
+from database import Json
 from config import get_settings
 from doc_parser import extract_text
 import ai_service as ai
@@ -826,6 +827,254 @@ async def render_generated_cv_pdf(gen_id: str):
     return await _do_render_pdf(template_schema, full_data, str(row["generation_date"]))
 
 
+# ============================================================
+# CV BATCHES
+# ============================================================
+
+@app.get("/api/batches")
+async def list_batches():
+    """List all CV batches."""
+    rows = db.query("SELECT * FROM cv_batches ORDER BY created_at DESC")
+    return {"batches": [dict(r) for r in rows]}
+
+
+@app.post("/api/batches")
+async def create_batch(request: Request):
+    """Create a new batch manually (name + description only)."""
+    body = await request.json()
+    name = body.get("name", "").strip()
+    if not name:
+        raise HTTPException(400, "Batch name is required")
+    row = db.execute(
+        "INSERT INTO cv_batches (name, description) VALUES (%s, %s) RETURNING *",
+        (name, body.get("description", ""))
+    )
+    return dict(row)
+
+
+@app.post("/api/batches/upload")
+async def upload_batch_document(file: UploadFile = File(...)):
+    """Upload a requirements document, extract positions with AI, create a batch."""
+    # Extract text from the document
+    content = await file.read()
+    import tempfile
+    with tempfile.NamedTemporaryFile(delete=False, suffix=f"_{file.filename}") as tmp:
+        tmp.write(content)
+        tmp_path = tmp.name
+    try:
+        doc_text = extract_text(tmp_path)
+    finally:
+        os.unlink(tmp_path)
+    
+    if not doc_text or len(doc_text.strip()) < 50:
+        raise HTTPException(400, "Could not extract enough text from the document")
+    
+    # AI extracts requirements
+    try:
+        result = ai.extract_requirements(doc_text)
+    except Exception as e:
+        # If AI fails, create the batch with just the raw text
+        result = {"batch_name": file.filename.replace(".pdf", "").replace(".docx", ""), "description": "AI extraction failed — edit manually", "positions": []}
+    
+    batch_name = result.get("batch_name", file.filename)
+    description = result.get("description", "")
+    positions = result.get("positions", [])
+    
+    row = db.execute(
+        "INSERT INTO cv_batches (name, description, requirements_text, positions) VALUES (%s, %s, %s, %s) RETURNING *",
+        (batch_name, description, doc_text, Json(positions))
+    )
+    return dict(row)
+
+
+@app.get("/api/batches/{batch_id}")
+async def get_batch(batch_id: str):
+    """Get a single batch with its items."""
+    batch = db.query("SELECT * FROM cv_batches WHERE id = %s", (batch_id,), fetch='one')
+    if not batch:
+        raise HTTPException(404, "Batch not found")
+    
+    items = db.query("""
+        SELECT bi.*, c.first_name, c.last_name, c.email
+        FROM batch_items bi
+        JOIN candidates c ON bi.candidate_id = c.id
+        WHERE bi.batch_id = %s
+        ORDER BY bi.position_title, bi.match_score DESC
+    """, (batch_id,))
+    
+    chat = db.query("SELECT * FROM batch_chat WHERE batch_id = %s ORDER BY created_at ASC", (batch_id,))
+    
+    return {
+        "batch": dict(batch),
+        "items": [dict(r) for r in items],
+        "chat": [dict(r) for r in chat]
+    }
+
+
+@app.put("/api/batches/{batch_id}")
+async def update_batch(batch_id: str, request: Request):
+    """Update batch name/description."""
+    body = await request.json()
+    row = db.execute(
+        """UPDATE cv_batches SET name = %s, description = %s, updated_at = NOW()
+           WHERE id = %s RETURNING *""",
+        (body.get("name"), body.get("description"), batch_id)
+    )
+    if not row:
+        raise HTTPException(404, "Batch not found")
+    return dict(row)
+
+
+@app.delete("/api/batches/{batch_id}")
+async def delete_batch(batch_id: str):
+    """Delete a batch (cascades to items and chat)."""
+    db.execute("DELETE FROM cv_batches WHERE id = %s", (batch_id,))
+    return {"success": True}
+
+
+@app.post("/api/batches/{batch_id}/analyze")
+async def analyze_batch(batch_id: str):
+    """Run AI matching against all candidates for each position in the batch."""
+    batch = db.query("SELECT * FROM cv_batches WHERE id = %s", (batch_id,), fetch='one')
+    if not batch:
+        raise HTTPException(404, "Batch not found")
+    
+    positions = batch["positions"] or []
+    if not positions:
+        raise HTTPException(400, "No positions defined in this batch")
+    
+    # Fetch all candidates with their full data
+    candidates_raw = db.query("SELECT * FROM candidates ORDER BY created_at DESC")
+    candidates = []
+    for c in candidates_raw:
+        c_dict = dict(c)
+        c_dict["skills"] = [dict(s) for s in db.query("SELECT * FROM skills WHERE candidate_id = %s", (c["id"],))]
+        c_dict["experience"] = [dict(e) for e in db.query("SELECT * FROM experience WHERE candidate_id = %s", (c["id"],))]
+        c_dict["education"] = [dict(e) for e in db.query("SELECT * FROM education WHERE candidate_id = %s", (c["id"],))]
+        c_dict["certifications"] = [dict(cert) for cert in db.query("SELECT * FROM certifications WHERE candidate_id = %s", (c["id"],))]
+        candidates.append(c_dict)
+    
+    if not candidates:
+        raise HTTPException(400, "No candidates in the database to match against")
+    
+    # Clear existing proposed items for this batch
+    db.execute("DELETE FROM batch_items WHERE batch_id = %s AND status = 'proposed'", (batch_id,))
+    
+    total_matched = 0
+    for position in positions:
+        try:
+            matches = ai.match_candidates_for_position(position, candidates)
+        except Exception as e:
+            print(f"Match error for position {position.get('job_title', '?')}: {e}")
+            continue
+        
+        for match in matches:
+            candidate_id = match.get("candidate_id")
+            if not candidate_id:
+                continue
+            # Verify candidate exists
+            exists = db.query("SELECT 1 FROM candidates WHERE id = %s", (candidate_id,), fetch='one')
+            if not exists:
+                continue
+            
+            db.execute(
+                """INSERT INTO batch_items (batch_id, candidate_id, position_title, match_score, match_reasoning, realigned_cv_data, status)
+                   VALUES (%s, %s, %s, %s, %s, %s, 'proposed')""",
+                (batch_id, candidate_id,
+                 position.get("job_title", ""),
+                 match.get("match_score", 0),
+                 match.get("reasoning", ""),
+                 Json({"realignment_suggestion": match.get("realignment_suggestion", "")}))
+            )
+            total_matched += 1
+    
+    # Update batch status
+    db.execute("UPDATE cv_batches SET status = 'active', updated_at = NOW() WHERE id = %s", (batch_id,))
+    
+    return {"success": True, "matched": total_matched}
+
+
+@app.put("/api/batches/{batch_id}/items/{item_id}")
+async def update_batch_item(batch_id: str, item_id: str, request: Request):
+    """Update a batch item (approve, remove, edit realignment)."""
+    body = await request.json()
+    row = db.execute(
+        """UPDATE batch_items SET status = %s, realigned_cv_data = %s, updated_at = NOW()
+           WHERE id = %s AND batch_id = %s RETURNING *""",
+        (body.get("status", "proposed"), Json(body.get("realigned_cv_data")), item_id, batch_id)
+    )
+    if not row:
+        raise HTTPException(404, "Batch item not found")
+    return dict(row)
+
+
+@app.delete("/api/batches/{batch_id}/items/{item_id}")
+async def delete_batch_item(batch_id: str, item_id: str):
+    """Delete a batch item."""
+    db.execute("DELETE FROM batch_items WHERE id = %s AND batch_id = %s", (item_id, batch_id))
+    return {"success": True}
+
+
+@app.post("/api/batches/{batch_id}/chat")
+async def batch_chat_endpoint(batch_id: str, request: Request):
+    """Send a message to the batch chat and get AI response."""
+    body = await request.json()
+    user_message = body.get("message", "").strip()
+    if not user_message:
+        raise HTTPException(400, "Message is required")
+    
+    batch = db.query("SELECT * FROM cv_batches WHERE id = %s", (batch_id,), fetch='one')
+    if not batch:
+        raise HTTPException(404, "Batch not found")
+    
+    # Save user message
+    db.execute(
+        "INSERT INTO batch_chat (batch_id, role, content) VALUES (%s, 'user', %s)",
+        (batch_id, user_message)
+    )
+    
+    # Build batch context for AI
+    items = db.query("""
+        SELECT bi.*, c.first_name, c.last_name
+        FROM batch_items bi
+        JOIN candidates c ON bi.candidate_id = c.id
+        WHERE bi.batch_id = %s AND bi.status != 'removed'
+        ORDER BY bi.position_title, bi.match_score DESC
+    """, (batch_id,))
+    
+    context_parts = [
+        f"Batch: {batch['name']}",
+        f"Description: {batch.get('description', '')}",
+        f"Positions: {json.dumps(batch.get('positions', []), indent=2)}",
+        f"\nMatched Candidates:",
+    ]
+    for item in items:
+        context_parts.append(
+            f"  - {item['first_name']} {item['last_name']} → {item['position_title']} "
+            f"(score: {item['match_score']}, status: {item['status']})"
+        )
+    
+    batch_context = "\n".join(context_parts)
+    
+    # Get chat history
+    history = db.query("SELECT role, content FROM batch_chat WHERE batch_id = %s ORDER BY created_at ASC", (batch_id,))
+    history_list = [dict(r) for r in history]
+    
+    # Get AI response
+    try:
+        ai_response = ai.batch_chat(user_message, batch_context, history_list)
+    except Exception as e:
+        ai_response = f"Sorry, I couldn't process that: {str(e)}"
+    
+    # Save AI response
+    db.execute(
+        "INSERT INTO batch_chat (batch_id, role, content) VALUES (%s, 'assistant', %s)",
+        (batch_id, ai_response)
+    )
+    
+    return {"response": ai_response}
+
+
 # ============================================================
 # SERVE FRONTEND
 # ============================================================

static/app.js

@@ -19,7 +19,7 @@ document.querySelectorAll('.nav-link').forEach(link => {
     if (page === 'templates') loadCarboneTemplates();
     if (page === 'requirements') loadRequirements();
     if (page === 'generated') loadGeneratedCVs();
-    if (page === 'chat') loadChat();
+    if (page === 'batches') loadBatches();
   });
 });
 

static/batches.js

@@ -0,0 +1,379 @@
+// CV Batches - Frontend
+let currentBatchId = null;
+
+// ============================================================
+// NAV — load batches when page is shown
+// ============================================================
+const batchNavObserver = new MutationObserver(() => {
+  if (document.getElementById('page-batches') && document.getElementById('page-batches').classList.contains('active')) {
+    loadBatches();
+  }
+});
+document.addEventListener('DOMContentLoaded', () => {
+  const bp = document.getElementById('page-batches');
+  if (bp) {
+    if (bp.classList.contains('active')) loadBatches();
+    batchNavObserver.observe(bp, { attributes: true, attributeFilter: ['class'] });
+  }
+});
+
+// ============================================================
+// LIST BATCHES
+// ============================================================
+async function loadBatches() {
+  const list = document.getElementById('batches-list');
+  if (!list) return;
+  list.innerHTML = '<div class="loading">Loading...</div>';
+  
+  try {
+    const resp = await fetch('/api/batches');
+    const data = await resp.json();
+    if (!data.batches || !data.batches.length) {
+      list.innerHTML = '<p class="text-muted">No batches yet. Create one manually or upload a requirements document.</p>';
+      return;
+    }
+    list.innerHTML = data.batches.map(b => `
+      <div class="card mb-16" style="cursor:pointer" onclick="openBatch('${b.id}')">
+        <div class="card-header">
+          <span class="card-title">${b.name}</span>
+          <span class="badge badge-${b.status === 'active' ? 'green' : b.status === 'exported' ? 'blue' : 'orange'}">${b.status}</span>
+        </div>
+        ${b.description ? '<p class="text-sm text-muted" style="margin-top:8px">' + escapeHtml(b.description) + '</p>' : ''}
+        <div class="text-muted text-sm" style="margin-top:8px">
+          Created: ${new Date(b.created_at).toLocaleDateString()}
+          ${b.positions && b.positions.length ? ' · Positions: ' + b.positions.length : ''}
+        </div>
+      </div>
+    `).join('');
+  } catch (e) {
+    list.innerHTML = '<p class="text-muted">Error: ' + e.message + '</p>';
+  }
+}
+
+// ============================================================
+// CREATE BATCH (manual)
+// ============================================================
+function showCreateBatchModal() {
+  const body = `
+    <div class="form-group">
+      <label>Batch Name</label>
+      <input type="text" id="new-batch-name" placeholder="e.g. Senior DevOps Team">
+    </div>
+    <div class="form-group">
+      <label>Description</label>
+      <textarea id="new-batch-desc" placeholder="What is this batch for?"></textarea>
+    </div>
+    <button class="btn" onclick="createBatch()">Create</button>
+  `;
+  showModal(body, 'New Batch');
+}
+
+async function createBatch() {
+  const name = document.getElementById('new-batch-name').value.trim();
+  if (!name) { toast('Name required', 'error'); return; }
+  const description = document.getElementById('new-batch-desc').value.trim();
+  
+  try {
+    const resp = await fetch('/api/batches', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({ name, description })
+    });
+    const data = await resp.json();
+    closeModal();
+    toast('Batch created');
+    openBatch(data.id);
+  } catch (e) {
+    toast('Error: ' + e.message, 'error');
+  }
+}
+
+// ============================================================
+// UPLOAD DOCUMENT to create batch
+// ============================================================
+function showUploadBatchModal() {
+  const body = `
+    <div class="upload-zone" id="batch-upload-zone" onclick="document.getElementById('batch-file-input').click()">
+      <p style="font-size:16px; margin-bottom:8px">Drop requirements document here or click to browse</p>
+      <p class="text-muted text-sm">PDF, DOCX, or TXT — AI will extract job positions automatically</p>
+    </div>
+    <input type="file" id="batch-file-input" accept=".pdf,.docx,.doc,.txt,.rtf" style="display:none" onchange="uploadBatchDoc(this.files[0])">
+    <div id="batch-upload-status" style="margin-top:12px"></div>
+  `;
+  showModal(body, 'Upload Requirements Document');
+  
+  // Setup drag-and-drop
+  const zone = document.getElementById('batch-upload-zone');
+  zone.addEventListener('dragover', e => { e.preventDefault(); zone.classList.add('dragover'); });
+  zone.addEventListener('dragleave', () => zone.classList.remove('dragover'));
+  zone.addEventListener('drop', e => {
+    e.preventDefault();
+    zone.classList.remove('dragover');
+    if (e.dataTransfer.files.length) uploadBatchDoc(e.dataTransfer.files[0]);
+  });
+}
+
+async function uploadBatchDoc(file) {
+  if (!file) return;
+  const status = document.getElementById('batch-upload-status');
+  status.innerHTML = '<div class="loading"><span class="spinner"></span> Extracting requirements with AI... this may take 30-60 seconds</div>';
+  
+  const formData = new FormData();
+  formData.append('file', file);
+  
+  try {
+    const resp = await fetch('/api/batches/upload', { method: 'POST', body: formData });
+    const data = await resp.json();
+    if (resp.ok) {
+      status.innerHTML = '<div class="toast success" style="position:relative">Batch created! Extracted ' + (data.positions?.length || 0) + ' positions.</div>';
+      setTimeout(() => {
+        closeModal();
+        openBatch(data.id);
+      }, 1500);
+      toast('Batch created from document');
+    } else {
+      status.innerHTML = '<div class="toast error" style="position:relative">Upload failed: ' + (data.detail || 'Unknown error') + '</div>';
+    }
+  } catch (e) {
+    status.innerHTML = '<div class="toast error" style="position:relative">Upload failed: ' + e.message + '</div>';
+  }
+}
+
+// ============================================================
+// BATCH DETAIL VIEW
+// ============================================================
+let currentBatch = null;
+
+async function openBatch(batchId) {
+  currentBatchId = batchId;
+  document.getElementById('batches-list-view').style.display = 'none';
+  const detail = document.getElementById('batch-detail-view');
+  detail.style.display = 'block';
+  detail.innerHTML = '<div class="loading">Loading batch...</div>';
+  
+  try {
+    const resp = await fetch('/api/batches/' + batchId);
+    const data = await resp.json();
+    currentBatch = data;
+    renderBatchDetail(data);
+  } catch (e) {
+    detail.innerHTML = '<p class="text-muted">Error: ' + e.message + '</p>';
+  }
+}
+
+function renderBatchDetail(data) {
+  const batch = data.batch;
+  const items = data.items || [];
+  
+  // Group items by position
+  const byPosition = {};
+  items.forEach(item => {
+    const pos = item.position_title || 'Unassigned';
+    if (!byPosition[pos]) byPosition[pos] = [];
+    byPosition[pos].push(item);
+  });
+  
+  // Build positions HTML
+  const positions = batch.positions || [];
+  let positionsHtml = '';
+  if (positions.length) {
+    positionsHtml = '<div class="card mb-16"><div class="card-header"><span class="card-title">Positions</span></div>';
+    positions.forEach(p => {
+      const posItems = byPosition[p.job_title] || [];
+      positionsHtml += `
+        <div style="margin-bottom:20px">
+          <h4 style="color:var(--accent)">${escapeHtml(p.job_title || '')} ${p.num_positions > 1 ? '×' + p.num_positions : ''}</h4>
+          ${p.description ? '<p class="text-sm text-muted">' + escapeHtml(p.description) + '</p>' : ''}
+          ${p.required_skills && p.required_skills.length ? '<div class="text-sm">Required: ' + p.required_skills.map(s => '<span class="badge badge-blue">' + escapeHtml(s) + '</span>').join(' ') + '</div>' : ''}
+          ${p.required_years ? '<div class="text-sm text-muted">Min years: ' + p.required_years + '</div>' : ''}
+          ${p.required_certs && p.required_certs.length ? '<div class="text-sm">Certs: ' + p.required_certs.map(c => '<span class="badge badge-orange">' + escapeHtml(c) + '</span>').join(' ') + '</div>' : ''}
+          ${posItems.length ? `
+            <div style="margin-top:12px">
+              ${posItems.map(item => `
+                <div class="skill-row" style="margin-bottom:8px">
+                  <div>
+                    <strong>${escapeHtml(item.first_name || '')} ${escapeHtml(item.last_name || '')}</strong>
+                    <span class="badge badge-${item.match_score >= 70 ? 'green' : item.match_score >= 50 ? 'orange' : 'red'}">${item.match_score}%</span>
+                    <span class="badge badge-${item.status === 'approved' ? 'green' : item.status === 'removed' ? 'red' : 'orange'}">${item.status}</span>
+                    ${item.match_reasoning ? '<div class="text-muted text-sm" style="margin-top:4px">' + escapeHtml(item.match_reasoning) + '</div>' : ''}
+                  </div>
+                  <div class="flex gap-8">
+                    ${item.status !== 'approved' ? '<button class="btn btn-sm btn-green" onclick="approveItem(\'' + item.id + '\')">Approve</button>' : ''}
+                    ${item.status !== 'removed' ? '<button class="btn btn-sm btn-danger" onclick="removeItem(\'' + item.id + '\')">Remove</button>' : ''}
+                  </div>
+                </div>
+              `).join('')}
+            </div>
+          ` : '<p class="text-muted text-sm">No candidates matched yet. Click "Analyze & Match" to find candidates.</p>'}
+        </div>
+      `;
+    });
+    positionsHtml += '</div>';
+  }
+  
+  // Unassigned items
+  const unassigned = byPosition['Unassigned'] || [];
+  if (unassigned.length) {
+    positionsHtml += '<div class="card mb-16"><div class="card-header"><span class="card-title">Unassigned</span></div>';
+    positionsHtml += unassigned.map(item => `
+      <div class="skill-row">
+        <div><strong>${escapeHtml(item.first_name || '')} ${escapeHtml(item.last_name || '')}</strong> <span class="badge badge-orange">${item.match_score}%</span></div>
+        <div class="flex gap-8">
+          <button class="btn btn-sm btn-danger" onclick="removeItem('${item.id}')">Remove</button>
+        </div>
+      </div>
+    `).join('');
+    positionsHtml += '</div>';
+  }
+  
+  document.getElementById('batch-detail-view').innerHTML = `
+    <div class="flex-between mb-16">
+      <div>
+        <h2>${escapeHtml(batch.name)}</h2>
+        <p class="text-muted text-sm">${escapeHtml(batch.description || '')}</p>
+      </div>
+      <div class="flex gap-8">
+        <button class="btn" onclick="analyzeBatch()">Analyze & Match</button>
+        <button class="btn btn-outline" onclick="openBatchChat()">Discuss</button>
+        <button class="btn btn-danger" onclick="deleteBatch()">Delete</button>
+        <button class="btn btn-outline" onclick="closeBatchDetail()">Back</button>
+      </div>
+    </div>
+    ${positionsHtml}
+  `;
+}
+
+function closeBatchDetail() {
+  document.getElementById('batches-list-view').style.display = 'block';
+  document.getElementById('batch-detail-view').style.display = 'none';
+  currentBatchId = null;
+  closeBatchChat();
+  loadBatches();
+}
+
+// ============================================================
+// ANALYZE & MATCH
+// ============================================================
+async function analyzeBatch() {
+  if (!currentBatchId) return;
+  toast('Analyzing candidates... this may take a minute');
+  
+  try {
+    const resp = await fetch('/api/batches/' + currentBatchId + '/analyze', { method: 'POST' });
+    const data = await resp.json();
+    if (resp.ok) {
+      toast('Matched ' + data.matched + ' candidates');
+      openBatch(currentBatchId);
+    } else {
+      toast('Error: ' + (data.detail || 'Analysis failed'), 'error');
+    }
+  } catch (e) {
+    toast('Error: ' + e.message, 'error');
+  }
+}
+
+// ============================================================
+// APPROVE / REMOVE ITEMS
+// ============================================================
+async function approveItem(itemId) {
+  await fetch('/api/batches/' + currentBatchId + '/items/' + itemId, {
+    method: 'PUT',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({ status: 'approved' })
+  });
+  toast('Candidate approved');
+  openBatch(currentBatchId);
+}
+
+async function removeItem(itemId) {
+  await fetch('/api/batches/' + currentBatchId + '/items/' + itemId, {
+    method: 'PUT',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({ status: 'removed' })
+  });
+  toast('Candidate removed');
+  openBatch(currentBatchId);
+}
+
+// ============================================================
+// DELETE BATCH
+// ============================================================
+async function deleteBatch() {
+  if (!currentBatchId || !confirm('Delete this batch and all its items?')) return;
+  await fetch('/api/batches/' + currentBatchId, { method: 'DELETE' });
+  toast('Batch deleted');
+  closeBatchDetail();
+}
+
+// ============================================================
+// BATCH CHAT (slide-in panel)
+// ============================================================
+function openBatchChat() {
+  const panel = document.getElementById('batch-chat-panel');
+  panel.style.display = 'flex';
+  renderBatchChatMessages(currentBatch?.chat || []);
+}
+
+function closeBatchChat() {
+  document.getElementById('batch-chat-panel').style.display = 'none';
+}
+
+function renderBatchChatMessages(messages) {
+  const container = document.getElementById('batch-chat-messages');
+  if (!messages.length) {
+    container.innerHTML = '<div class="text-muted">Start discussing this batch with the AI...</div>';
+    return;
+  }
+  container.innerHTML = messages.map(m => `
+    <div class="chat-msg ${m.role}">
+      <div class="bubble">${escapeHtml(m.content)}</div>
+    </div>
+  `).join('');
+  container.scrollTop = container.scrollHeight;
+}
+
+async function sendBatchChat() {
+  const input = document.getElementById('batch-chat-input');
+  const message = input.value.trim();
+  if (!message || !currentBatchId) return;
+  
+  input.value = '';
+  // Show user message immediately
+  const container = document.getElementById('batch-chat-messages');
+  container.innerHTML += `<div class="chat-msg user"><div class="bubble">${escapeHtml(message)}</div></div>`;
+  container.scrollTop = container.scrollHeight;
+  
+  // Show loading
+  container.innerHTML += '<div class="chat-msg assistant" id="chat-loading"><div class="bubble">Thinking...</div></div>';
+  container.scrollTop = container.scrollHeight;
+  
+  try {
+    const resp = await fetch('/api/batches/' + currentBatchId + '/chat', {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({ message })
+    });
+    const data = await resp.json();
+    
+    // Remove loading and show response
+    document.getElementById('chat-loading')?.remove();
+    container.innerHTML += `<div class="chat-msg assistant"><div class="bubble">${escapeHtml(data.response)}</div></div>`;
+    container.scrollTop = container.scrollHeight;
+  } catch (e) {
+    document.getElementById('chat-loading')?.remove();
+    toast('Chat error: ' + e.message, 'error');
+  }
+}
+
+// Enter key to send in chat
+document.addEventListener('DOMContentLoaded', () => {
+  const input = document.getElementById('batch-chat-input');
+  if (input) {
+    input.addEventListener('keydown', e => {
+      if (e.key === 'Enter' && !e.shiftKey) {
+        e.preventDefault();
+        sendBatchChat();
+      }
+    });
+  }
+});

static/index.html

@@ -20,9 +20,9 @@
       <li><a href="#" class="nav-link" data-page="candidates">Candidates</a></li>
       <li><a href="#" class="nav-link" data-page="upload">Upload CV</a></li>
       <li><a href="#" class="nav-link" data-page="templates">Templates</a></li>
+      <li><a href="#" class="nav-link" data-page="batches">Batches</a></li>
       <li><a href="#" class="nav-link" data-page="requirements">Requirements</a></li>
       <li><a href="#" class="nav-link" data-page="generated">Generated CVs</a></li>
-      <li><a href="#" class="nav-link" data-page="chat">AI Chat</a></li>
     </ul>
   </nav>
 
@@ -105,6 +105,19 @@
       </div>
     </div>
 
+    <!-- BATCHES -->
+    <div id="page-batches" class="page">
+      <div id="batches-list-view">
+        <h2 style="margin-bottom:20px">CV Batches</h2>
+        <div class="flex mb-16 gap-8">
+          <button class="btn" onclick="showCreateBatchModal()">+ New Batch</button>
+          <button class="btn btn-outline" onclick="showUploadBatchModal()">Upload Document</button>
+        </div>
+        <div id="batches-list"></div>
+      </div>
+      <div id="batch-detail-view" style="display:none"></div>
+    </div>
+
     <!-- REQUIREMENTS -->
     <div id="page-requirements" class="page">
       <h2 style="margin-bottom:20px">Requirement Requests</h2>
@@ -119,27 +132,27 @@
       <h2 style="margin-bottom:20px">Generated CVs</h2>
       <div id="generated-list"></div>
     </div>
-
-    <!-- CHAT -->
-    <div id="page-chat" class="page">
-      <h2 style="margin-bottom:20px">AI Chat Assistant</h2>
-      <div class="chat-container">
-        <div class="chat-messages" id="chat-messages">
-          <div class="text-muted">Start a conversation with the AI assistant...</div>
-        </div>
-        <div class="chat-input">
-          <textarea id="chat-input" placeholder="Type your message..." rows="1"></textarea>
-          <button class="btn" onclick="sendChat()">Send</button>
-        </div>
-      </div>
-    </div>
   </main>
 </div>
 
 <!-- Modals -->
 <div class="modal-overlay" id="modal-overlay"></div>
 
-<script src="/static/app.js?v=15"></script>
+<!-- Chat slide-in panel -->
+<div id="batch-chat-panel" class="chat-panel" style="display:none">
+  <div class="chat-panel-header">
+    <h3>Batch Discussion</h3>
+    <button class="btn btn-sm btn-danger" onclick="closeBatchChat()">Close</button>
+  </div>
+  <div class="chat-panel-messages" id="batch-chat-messages"></div>
+  <div class="chat-panel-input">
+    <textarea id="batch-chat-input" placeholder="Type your message..." rows="2"></textarea>
+    <button class="btn" onclick="sendBatchChat()">Send</button>
+  </div>
+</div>
+
+<script src="/static/app.js?v=16"></script>
 <script src="/static/carbone.js?v=16"></script>
+<script src="/static/batches.js?v=1"></script>
 </body>
 </html>

static/style.css

@@ -215,6 +215,45 @@ tr:hover { background: var(--bg-input); }
 .chat-input { display: flex; gap: 8px; }
 .chat-input textarea { flex: 1; min-height: 44px; max-height: 120px; }
 
+/* Slide-in chat panel for batch discussion */
+.chat-panel {
+  position: fixed;
+  top: 0;
+  right: 0;
+  width: 400px;
+  height: 100vh;
+  background: var(--bg-card);
+  border-left: 2px solid var(--border);
+  display: flex;
+  flex-direction: column;
+  z-index: 9999;
+  box-shadow: -4px 0 20px rgba(0,0,0,0.3);
+  transition: transform 0.3s ease;
+}
+.chat-panel-header {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  padding: 12px 16px;
+  border-bottom: 1px solid var(--border);
+}
+.chat-panel-messages {
+  flex: 1;
+  overflow-y: auto;
+  padding: 16px;
+}
+.chat-panel-input {
+  display: flex;
+  gap: 8px;
+  padding: 12px;
+  border-top: 1px solid var(--border);
+}
+.chat-panel-input textarea {
+  flex: 1;
+  min-height: 44px;
+  max-height: 120px;
+}
+
 /* Modal */
 .modal-overlay {
   position: fixed;