Cv reader + matching project (#13)

Co-authored-by: Stanislav Sava <[email protected]>
Co-authored-by: Dragos Dit <[email protected]>

LLM/llm_models.py

@@ -16,6 +16,9 @@ orchestrator_model = LLMProvider(base_provider, base_model).get_model()
 supabase_model = LLMProvider(base_provider, base_model).get_model()
 websearch_model = LLMProvider(base_provider, base_model).get_model()
 
+# CV analyzer uses the same HF/opensource model as orchestrator
+cv_analyzer_model = LLMProvider(base_provider, base_model).get_model()
+
 context_compression_model = LLMProvider(LLMProviderType.OPENAI, LLMModelType.openai.gpt_5_1).get_model()
 metaprompting_model = LLMProvider(LLMProviderType.OPENAI, LLMModelType.openai.gpt_5_1).get_model()
 

UI/app_interface.py

@@ -7,9 +7,11 @@ from typing import Any, Callable, Deque, Dict, Optional
 
 import gradio as gr  # type: ignore
 
-from .render_plan_html import render_plan_html
 from third_party_tools.text_to_audio_file import text_to_audio_file
 
+from .cv_interface import CVInterface
+from .render_plan_html import render_plan_html
+
 
 class EastSyncInterface:
     """
@@ -32,21 +34,69 @@ class EastSyncInterface:
         )
 
         self._app_css = self._compose_css()
-    
+        self._cv_interface = CVInterface(self)
+        self._analysis_result: Optional[Any] = None  # Store analysis result for async updates
+        self._analysis_error: Optional[str] = None  # Store analysis error if any
+        self._analysis_running: bool = False  # Track if analysis is currently running
+        self._cached_processing_state: Optional[str] = None  # Cache processing state HTML
+        
+        # Dynamic processing steps tracking
+        self._processing_steps: list[str] = []  # Current processing steps
+        self._processing_steps_lock = Lock()
+        self._processing_mode: Optional[str] = None  # "project", "extract", or "match"
+
     # ---------------------- HELPER METHODS ----------------------
 
+    def start_processing(self, mode: str):
+        """Start processing mode and reset steps. Mode: 'project', 'extract', or 'match'."""
+        with self._processing_steps_lock:
+            self._processing_steps = []
+            self._processing_mode = mode
+            self._analysis_running = True
+            self._analysis_result = None
+            self._analysis_error = None
+            self._cached_processing_state = None
+
+    def stop_processing(self):
+        """Stop processing mode and clear steps."""
+        with self._processing_steps_lock:
+            self._processing_mode = None
+            self._analysis_running = False
+
+    def add_processing_step(self, step: str):
+        """Add a new processing step to the dynamic list."""
+        with self._processing_steps_lock:
+            # Avoid duplicates
+            if step not in self._processing_steps:
+                self._processing_steps.append(step)
+                # Invalidate cache so next render picks up new steps
+                self._cached_processing_state = None
+
+    def get_processing_steps(self) -> list[str]:
+        """Get current processing steps."""
+        with self._processing_steps_lock:
+            return list(self._processing_steps)
+
     def register_agent_action(self, action: str, args: Optional[Dict[str, Any]] = None):
         import datetime
         timestamp = datetime.datetime.now().strftime("%H:%M:%S")
         with self._action_log_lock:
             # Keep the high-contrast aesthetic but clean up the formatting
-            msg = f'<span class="console-timestamp">{timestamp}</span> <span style="color:var(--arc-yellow)">>></span> {html.escape(str(action))}'
+            msg = f'<span class="console-timestamp">{timestamp}</span> <span style="color:var(--arc-yellow)">>></span> <span style="color:var(--text-main); opacity:0.9;">{html.escape(str(action))}</span>'
             if args:
                 args_str = str(args)
                 if len(args_str) > 80:
                     args_str = args_str[:80] + "..."
-                msg += f' <span style="color:var(--text-dim)">:: {html.escape(args_str)}</span>'
+                msg += f' <span style="color:var(--text-main); opacity:0.7;">:: {html.escape(args_str)}</span>'
             self._action_log.appendleft(f'<div class="console-line">{msg}</div>')
+        
+        # Add to processing steps if we're in processing mode (check INSIDE lock to avoid race condition)
+        with self._processing_steps_lock:
+            if self._processing_mode is not None:
+                action_str = str(action)
+                if action_str not in self._processing_steps:
+                    self._processing_steps.append(action_str)
+                    self._cached_processing_state = None
 
     def get_action_log_text(self) -> str:
         with self._action_log_lock:
@@ -65,6 +115,52 @@ class EastSyncInterface:
         audio_out = gr.update(value=audio_path, visible=is_audio)
         html_out = render_plan_html(result)
         return html_out, audio_out
+    
+    def set_analysis_result(self, result: Any):
+        """Store analysis result for async display."""
+        self._analysis_result = result
+        self._analysis_error = None
+    
+    def set_analysis_error(self, error: str):
+        """Store analysis error for async display."""
+        self._analysis_error = error
+        self._analysis_result = None
+    
+    def get_analysis_output(self) -> Optional[str]:
+        """Get the current analysis output (result, error, or processing state).
+        Returns None if no update is needed."""
+        # Check result/error first (these are set by the agent thread)
+        if self._analysis_result is not None:
+            self.stop_processing()  # Mark as complete
+            return self.render_analysis_result(self._analysis_result)
+        elif self._analysis_error is not None:
+            self.stop_processing()  # Mark as complete
+            return self.render_error_state(self._analysis_error)
+        
+        # Check processing mode inside the lock for thread safety
+        with self._processing_steps_lock:
+            mode = self._processing_mode
+            is_running = self._analysis_running
+        
+        # If not running and no result/error, don't update
+        if not is_running:
+            return None
+        
+        # Render dynamic processing state based on mode
+        if mode == "project":
+            return self.render_project_processing_state()
+        elif mode in ("extract", "match"):
+            return self.render_processing_state(mode)
+        elif mode is not None:
+            return self.render_project_processing_state()  # fallback
+        else:
+            return None  # No processing mode set
+        summary_text = result.get('corny_summary', '')
+        audio_path = text_to_audio_file(summary_text)
+        is_audio = audio_path is not None
+        audio_out = gr.update(value=audio_path, visible=is_audio)
+        html_out = render_plan_html(result)
+        return html_out, audio_out
 
     def render_idle_state(self) -> str:
         # The style is handled inside render_plan_html.py CSS for consistency.
@@ -85,8 +181,173 @@ class EastSyncInterface:
 
     def reset_prompt_value(self) -> str:
         return self.SAMPLE_PROMPT
+    
+    def render_project_processing_state(self) -> str:
+        """Render animated processing state for project analysis with dynamic steps."""
+        # Get current processing steps (dynamic)
+        current_steps = self.get_processing_steps()
+        
+        # Build steps HTML - show only actual steps that have been added
+        if current_steps:
+            steps_html = "".join([
+                f'<div style="padding: 12px; margin: 8px 0; background: rgba(85,255,0,0.08); border-left: 3px solid var(--arc-green); color: #FFFFFF; font-size: 14px; font-weight: 500;">✓ {html.escape(step)}</div>'
+                for step in current_steps[:-1]  # Previous steps (completed) - WHITE text
+            ])
+            # Current step (in progress) - with animation
+            if current_steps:
+                current_step = current_steps[-1]
+                steps_html += f'<div style="padding: 12px; margin: 8px 0; background: rgba(255,127,0,0.15); border-left: 3px solid var(--arc-orange); color: var(--arc-orange); font-size: 14px; font-weight: 600; animation: pulse 1.5s ease-in-out infinite;">⏳ {html.escape(current_step)}</div>'
+        else:
+            steps_html = '<div style="padding: 12px; margin: 8px 0; background: rgba(255,255,255,0.02); border-left: 3px solid var(--arc-cyan); color: var(--text-main); opacity:0.9; font-size: 14px; animation: pulse 1.5s ease-in-out infinite;">⏳ Initializing analysis...</div>'
+        
+        step_count = len(current_steps) if current_steps else 0
+        
+        return f"""
+        <style>
+            @keyframes pulse {{
+                0%, 100% {{ opacity: 1; }}
+                50% {{ opacity: 0.5; }}
+            }}
+            @keyframes spin {{
+                from {{ transform: rotate(0deg); }}
+                to {{ transform: rotate(360deg); }}
+            }}
+            @keyframes progress {{
+                0% {{ width: 0%; }}
+                100% {{ width: 100%; }}
+            }}
+        </style>
+        <div style="display: flex; align-items: center; justify-content: center; min-height: 70vh; padding: 40px;">
+            <div style="max-width: 800px; width: 100%;">
+                <div style="background: var(--bg-panel); border: 2px solid var(--arc-orange); border-radius: 4px; padding: 48px; text-align: center;">
+                    
+                    <!-- Animated Icon -->
+                    <div style="margin-bottom: 32px;">
+                        <div style="width: 80px; height: 80px; margin: 0 auto; border: 4px solid var(--arc-orange); border-top-color: transparent; border-radius: 50%; animation: spin 1s linear infinite;"></div>
+                    </div>
+                    
+                    <!-- Title -->
+                    <h2 style="color: var(--arc-orange); margin: 0 0 16px 0; font-size: 24px; font-weight: 700; animation: pulse 2s ease-in-out infinite;">
+                        🚀 INITIATING ANALYSIS
+                    </h2>
+                    
+                    <!-- Subtitle -->
+                    <p style="color: var(--text-main); font-size: 15px; margin-bottom: 32px; opacity: 0.9;">
+                        Analyzing project requirements and generating deployment plan... Monitor system logs for real-time updates.
+                    </p>
+                    
+                    <!-- Progress Bar -->
+                    <div style="width: 100%; height: 4px; background: rgba(255,255,255,0.1); border-radius: 2px; overflow: hidden; margin-bottom: 32px;">
+                        <div style="height: 100%; background: linear-gradient(90deg, var(--arc-red), var(--arc-orange), var(--arc-yellow), var(--arc-green)); animation: progress 4s ease-in-out infinite;"></div>
+                    </div>
+                    
+                    <!-- Processing Steps (DYNAMIC) -->
+                    <div style="text-align: left; max-width: 600px; margin: 0 auto; padding: 24px; background: rgba(0,0,0,0.3); border-radius: 4px; min-height: 150px;">
+                        <div style="color: var(--arc-orange); font-size: 12px; text-transform: uppercase; letter-spacing: 1px; margin-bottom: 16px; font-weight: 600; display: flex; justify-content: space-between;">
+                            <span>ANALYSIS PIPELINE:</span>
+                            <span style="color: var(--arc-cyan);">{step_count} step{"s" if step_count != 1 else ""}</span>
+                        </div>
+                        <div style="max-height: 300px; overflow-y: auto;">
+                            {steps_html}
+                        </div>
+                    </div>
+                    
+                    <!-- Info Note -->
+                    <div style="margin-top: 32px; padding: 16px; background: rgba(255,127,0,0.05); border: 1px solid rgba(255,127,0,0.2); border-radius: 4px;">
+                        <div style="color: var(--arc-orange); font-size: 13px;">
+                            ⏱️ <strong style="color: var(--text-main);">Estimated Time:</strong> <span style="color: var(--text-main); opacity: 0.9;">45-90 seconds (depending on project complexity)</span>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+        """
+    
+    def render_processing_state(self, mode: str = "extract") -> str:
+        """Render animated processing state for CV analysis with dynamic steps."""
+        title = "📊 EXTRACTING SKILLS" if mode == "extract" else "🎯 ANALYZING CV + MATCHING PROJECTS"
+        
+        # Get current processing steps (dynamic)
+        current_steps = self.get_processing_steps()
+        
+        # Build steps HTML - show only actual steps that have been added
+        if current_steps:
+            steps_html = "".join([
+                f'<div style="padding: 12px; margin: 8px 0; background: rgba(85,255,0,0.08); border-left: 3px solid var(--arc-green); color: #FFFFFF; font-size: 14px; font-weight: 500;">✓ {html.escape(step)}</div>'
+                for step in current_steps[:-1]  # Previous steps (completed) - WHITE text
+            ])
+            # Current step (in progress) - with animation
+            if current_steps:
+                current_step = current_steps[-1]
+                steps_html += f'<div style="padding: 12px; margin: 8px 0; background: rgba(0,255,255,0.15); border-left: 3px solid var(--arc-cyan); color: var(--arc-cyan); font-size: 14px; font-weight: 600; animation: pulse 1.5s ease-in-out infinite;">⏳ {html.escape(current_step)}</div>'
+        else:
+            steps_html = '<div style="padding: 12px; margin: 8px 0; background: rgba(255,255,255,0.02); border-left: 3px solid var(--arc-cyan); color: var(--text-main); opacity:0.9; font-size: 14px; animation: pulse 1.5s ease-in-out infinite;">⏳ Initializing...</div>'
+        
+        step_count = len(current_steps) if current_steps else 0
+        
+        return f"""
+        <style>
+            @keyframes pulse {{
+                0%, 100% {{ opacity: 1; }}
+                50% {{ opacity: 0.5; }}
+            }}
+            @keyframes spin {{
+                from {{ transform: rotate(0deg); }}
+                to {{ transform: rotate(360deg); }}
+            }}
+            @keyframes progress {{
+                0% {{ width: 0%; }}
+                100% {{ width: 100%; }}
+            }}
+        </style>
+        <div style="display: flex; align-items: center; justify-content: center; min-height: 70vh; padding: 40px;">
+            <div style="max-width: 800px; width: 100%;">
+                <div style="background: var(--bg-panel); border: 2px solid var(--arc-orange); border-radius: 4px; padding: 48px; text-align: center;">
+                    
+                    <!-- Animated Icon -->
+                    <div style="margin-bottom: 32px;">
+                        <div style="width: 80px; height: 80px; margin: 0 auto; border: 4px solid var(--arc-orange); border-top-color: transparent; border-radius: 50%; animation: spin 1s linear infinite;"></div>
+                    </div>
+                    
+                    <!-- Title -->
+                    <h2 style="color: var(--arc-orange); margin: 0 0 16px 0; font-size: 24px; font-weight: 700; animation: pulse 2s ease-in-out infinite;">
+                        {title}
+                    </h2>
+                    
+                    <!-- Subtitle -->
+                    <p style="color: var(--text-main); font-size: 15px; margin-bottom: 32px; opacity: 0.9;">
+                        Processing document... Please monitor the system logs for real-time updates.
+                    </p>
+                    
+                    <!-- Progress Bar -->
+                    <div style="width: 100%; height: 4px; background: rgba(255,255,255,0.1); border-radius: 2px; overflow: hidden; margin-bottom: 32px;">
+                        <div style="height: 100%; background: linear-gradient(90deg, var(--arc-orange), var(--arc-yellow), var(--arc-green)); animation: progress 3s ease-in-out infinite;"></div>
+                    </div>
+                    
+                    <!-- Processing Steps (DYNAMIC) -->
+                    <div style="text-align: left; max-width: 600px; margin: 0 auto; padding: 24px; background: rgba(0,0,0,0.3); border-radius: 4px; min-height: 150px;">
+                        <div style="color: var(--arc-cyan); font-size: 12px; text-transform: uppercase; letter-spacing: 1px; margin-bottom: 16px; font-weight: 600; display: flex; justify-content: space-between;">
+                            <span>PROCESSING PIPELINE:</span>
+                            <span style="color: var(--arc-orange);">{step_count} step{"s" if step_count != 1 else ""}</span>
+                        </div>
+                        <div style="max-height: 300px; overflow-y: auto;">
+                            {steps_html}
+                        </div>
+                    </div>
+                    
+                    <!-- Info Note -->
+                    <div style="margin-top: 32px; padding: 16px; background: rgba(0,255,255,0.05); border: 1px solid rgba(0,255,255,0.2); border-radius: 4px;">
+                        <div style="color: var(--arc-cyan); font-size: 13px;">
+                            ⏱️ <strong style="color: var(--text-main);">Estimated Time:</strong> <span style="color: var(--text-main); opacity: 0.9;">{('20-30 seconds' if mode == 'extract' else '30-45 seconds')}</span>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+        """
+
 
-    # ---------------------- TACTICAL CSS (UNCHANGED) ----------------------
+    # ---------------------- TACTICAL CSS ----------------------
 
     def _token_css(self) -> str:
         return """
@@ -301,7 +562,7 @@ class EastSyncInterface:
             min-height: 300px;
             max-height: 40vh;
             overflow-y: auto;
-            color: var(--text-dim);
+            color: var(--text-main);
         }
         .console-line {
             margin-bottom: 8px;
@@ -314,6 +575,17 @@ class EastSyncInterface:
         .console-wrapper::-webkit-scrollbar { width: 8px; }
         .console-wrapper::-webkit-scrollbar-track { background: #08090D; }
         .console-wrapper::-webkit-scrollbar-thumb { background: var(--border-dim); border-radius: 4px; }
+        
+        /* DISABLE GRADIO DEFAULT LOADING OVERLAY */
+        .generating {
+            display: none !important;
+        }
+        .pending {
+            opacity: 1 !important;
+        }
+        .eta-bar {
+            display: none !important;
+        }
         """
 
     def _compose_css(self) -> str:
@@ -367,7 +639,7 @@ class EastSyncInterface:
             with gr.Row(equal_height=True, elem_classes=["main-container"]):
                 
                 # --- LEFT COLUMN: INPUTS ---
-                with gr.Column(scale=3, elem_classes=["input-panel"]):
+                with gr.Column(scale=3, elem_classes=["input-panel"]) as mission_panel:
                     gr.HTML("<div class='ent-header-label'>PROJECT PARAMETERS</div>")
                     
                     input_box = gr.TextArea(
@@ -386,27 +658,175 @@ class EastSyncInterface:
 
                     with gr.Row():
                         btn_cancel = gr.Button("STOP ANALYSIS", elem_classes=["btn-tac-secondary"])
+                    with gr.Row():
+                        btn_cv = gr.Button("📄 CV ANALYSIS", elem_classes=["btn-tac-primary"])
                     
                     gr.HTML("<div style='height:30px'></div>") # Flexible Spacer
                     
                     gr.HTML("<div class='ent-header-label'>ACTIVITY LOG</div>")
                     console = gr.HTML(self.get_action_log_text())
 
+                # --- LEFT COLUMN: CV UPLOAD (hidden by default) ---
+                with gr.Column(scale=3, elem_classes=["input-panel"], visible=False) as cv_upload_panel:
+                    gr.HTML("<div class='ent-header-label'>📄 CV ANALYSIS</div>")
+                    
+                    gr.HTML("""
+                        <div style="padding: 16px; background: rgba(255,127,0,0.1); border: 1px solid var(--arc-orange); border-radius: 4px; margin-bottom: 16px;">
+                            <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 12px;">
+                                <div style="padding: 10px; background: rgba(255,255,255,0.05); border-radius: 4px; border-left: 3px solid var(--arc-cyan);">
+                                    <div style="color: var(--arc-cyan); font-weight: 600; margin-bottom: 6px; font-size: 12px;">📊 EXTRACT SKILLS</div>
+                                    <div style="color: var(--text-dim); font-size: 10px;">
+                                        Parse CV to identify technical skills, experience, certifications.
+                                    </div>
+                                </div>
+                                <div style="padding: 10px; background: rgba(255,255,255,0.05); border-radius: 4px; border-left: 3px solid var(--arc-orange);">
+                                    <div style="color: var(--arc-orange); font-weight: 600; margin-bottom: 6px; font-size: 12px;">🎯 EXTRACT + MATCH</div>
+                                    <div style="color: var(--text-dim); font-size: 10px;">
+                                        Parse CV, rank projects, identify skill gaps.
+                                    </div>
+                                </div>
+                            </div>
+                        </div>
+                    """)
+                    
+                    cv_file_input = gr.File(
+                        label="SELECT CV FILE",
+                        file_types=[".pdf", ".docx", ".doc"],
+                        type="filepath"
+                    )
+                    
+                    with gr.Row():
+                        btn_process_cv = gr.Button("📊 EXTRACT SKILLS", elem_classes=["btn-tac-secondary"])
+                        btn_process_cv_match = gr.Button("🎯 EXTRACT + MATCH PROJECTS", elem_classes=["btn-tac-primary"])
+                    
+                    with gr.Row():
+                        btn_close_cv = gr.Button("← BACK", elem_classes=["btn-tac-secondary"])
+                    
+                    gr.HTML("<div style='height:30px'></div>")
+                    
+                    gr.HTML("<div class='ent-header-label'>SYSTEM LOGS</div>")
+                    console_cv = gr.HTML(self.get_action_log_text())
+
                 # --- RIGHT COLUMN: OUTPUT ---
                 with gr.Column(scale=7, elem_classes=["output-panel"]):
                      output_display = gr.HTML(self.render_idle_state())
 
             # --- Event Bindings ---
-            btn_run.click(self.clear_action_log, outputs=console, queue=False) \
-                   .then(lambda: self.get_action_log_text(), outputs=console) \
-                   .then(analyze_callback, inputs=input_box, outputs=[output_display, output_audio]) \
-                   .then(self.get_action_log_text, outputs=console)
+            
+            # Project Analysis
+            def start_project_analysis():
+                self.start_processing("project")
+                return self.render_project_processing_state()
+            
+            btn_run.click(
+                start_project_analysis,
+                outputs=output_display,
+                queue=False
+            ).then(
+                self.clear_action_log, outputs=console, queue=False
+            ).then(
+                lambda: self.get_action_log_text(), outputs=console
+            ).then(
+                analyze_callback, inputs=input_box, outputs=[output_display, output_audio]
+            ).then(
+                self.get_action_log_text, outputs=console
+            )
             
             btn_reset.click(self.reset_prompt_value, outputs=input_box)
+            
+            # CV Button - Toggle panels
+            def show_cv_interface():
+                return (
+                    gr.update(visible=False),  # Hide mission_panel
+                    gr.update(visible=True),   # Show cv_upload_panel
+                    self._cv_interface.render_cv_upload_interface()  # Update output_display
+                )
+            
+            btn_cv.click(
+                show_cv_interface,
+                outputs=[mission_panel, cv_upload_panel, output_display]
+            )
+            
+            # Close CV Section - Back to mission panel
+            def close_cv_interface():
+                return (
+                    gr.update(visible=True),   # Show mission_panel
+                    gr.update(visible=False),  # Hide cv_upload_panel
+                    self.render_idle_state()   # Reset output_display
+                )
+            
+            btn_close_cv.click(
+                close_cv_interface,
+                outputs=[mission_panel, cv_upload_panel, output_display]
+            )
+            
+            # Standard CV analysis (no project matching)
+            def start_cv_extract():
+                self.start_processing("extract")
+                return self.render_processing_state("extract")
+            
+            def finish_cv_processing():
+                self.stop_processing()
+                return self.get_action_log_text()
+            
+            btn_process_cv.click(
+                start_cv_extract,
+                outputs=output_display,
+                queue=False
+            ).then(
+                self.clear_action_log, outputs=console_cv, queue=False
+            ).then(
+                self._cv_interface.process_cv_upload,
+                inputs=cv_file_input,
+                outputs=output_display
+            ).then(
+                finish_cv_processing, outputs=console_cv
+            )
+            
+            # CV + Project Matching
+            def start_cv_match():
+                self.start_processing("match")
+                return self.render_processing_state("match")
+            
+            btn_process_cv_match.click(
+                start_cv_match,
+                outputs=output_display,
+                queue=False
+            ).then(
+                self.clear_action_log, outputs=console_cv, queue=False
+            ).then(
+                self._cv_interface.process_cv_with_matching,
+                inputs=cv_file_input,
+                outputs=output_display
+            ).then(
+                finish_cv_processing, outputs=console_cv
+            )
 
             btn_cancel.click(cancel_run_callback)
 
-            # Live log updates
-            gr.Timer(2).tick(self.get_action_log_text, outputs=console)
+            # Live log updates (both consoles)
+            def update_both_consoles():
+                log_text = self.get_action_log_text()
+                return (log_text, log_text)  # Return same log for both consoles
+            
+            gr.Timer(2).tick(update_both_consoles, outputs=[console, console_cv])
+            
+            # Check for analysis result updates (poll every 1 second)
+            def check_analysis_result():
+                """Check if analysis is complete and update output display."""
+                output = self.get_analysis_output()
+                # Only return if there's an update (None means no update needed)
+                if output is not None:
+                    return output
+                # Return None to skip update (Gradio will handle this)
+                return None
+            
+            # Poll for results - Gradio will skip None returns
+            def poll_with_skip():
+                result = check_analysis_result()
+                # Return the result if not None, otherwise skip update
+                return result if result is not None else gr.update()
+            
+            gr.Timer(1).tick(poll_with_skip, outputs=output_display)
 
         return demo

UI/cv_interface.py

@@ -0,0 +1,263 @@
+from __future__ import annotations
+
+import html
+from typing import Any, Callable, Dict, Optional
+
+from utils.cv_parser import parse_cv
+from utils.cv_project_matcher import match_cv_to_projects
+from utils.skill_extractor import extract_skills_from_cv_text
+
+from .render_cv_html import render_cv_analysis_html
+from .render_cv_matching import render_cv_matching_html
+
+
+class CVInterface:
+    """
+    Handles all CV-related functionality including upload, parsing, skill extraction,
+    and project matching.
+    """
+
+    def __init__(self, main_interface):
+        """
+        Initialize CV interface with reference to main interface for shared functionality.
+        
+        Args:
+            main_interface: Reference to EastSyncInterface instance for accessing
+                          shared methods like register_agent_action, start_processing, etc.
+        """
+        self._main_interface = main_interface
+        self._cv_skills_data: Optional[Dict[str, Any]] = None
+        self._cv_filename: str = "Unknown"
+
+    def render_cv_upload_interface(self) -> str:
+        """Render the CV upload interface instructions for the right panel."""
+        return """
+        <div style="display: flex; align-items: center; justify-content: center; min-height: 60vh; padding: 40px;">
+            <div style="max-width: 900px; width: 100%;">
+                <div style="background: var(--bg-panel); border: 2px solid var(--arc-orange); border-radius: 4px; padding: 40px;">
+                    <div style="display: flex; align-items: center; gap: 16px; margin-bottom: 24px;">
+                        <div style="font-size: 48px;">📄</div>
+                        <div>
+                            <h2 style="color: var(--arc-orange); margin: 0; font-size: 28px; font-weight: 700;">CV ANALYSIS OPTIONS</h2>
+                            <p style="color: var(--text-dim); margin: 8px 0 0 0; font-size: 15px;">
+                                Upload a candidate's CV (PDF or DOCX format) to extract skills and optionally match against projects.
+                            </p>
+                        </div>
+                    </div>
+                    
+                    <div style="margin-top: 32px; padding: 24px; background: rgba(0,0,0,0.4); border-radius: 4px; border: 1px solid var(--border-dim);">
+                        <div style="color: var(--arc-cyan); font-size: 14px; margin-bottom: 20px; text-transform: uppercase; letter-spacing: 1px;">
+                            <strong>TWO ANALYSIS MODES:</strong>
+                        </div>
+                        <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 20px; margin-bottom: 24px;">
+                            <div style="padding: 20px; background: rgba(255,255,255,0.05); border-radius: 4px; border-left: 4px solid var(--arc-cyan);">
+                                <div style="color: var(--arc-cyan); font-weight: 700; margin-bottom: 10px; font-size: 15px;">📊 EXTRACT SKILLS ONLY</div>
+                                <div style="color: var(--text-dim); font-size: 13px; line-height: 1.5;">
+                                    Parse CV to identify technical skills, experience, certifications, and education.
+                                </div>
+                            </div>
+                            <div style="padding: 20px; background: rgba(255,255,255,0.05); border-radius: 4px; border-left: 4px solid var(--arc-orange);">
+                                <div style="color: var(--arc-orange); font-weight: 700; margin-bottom: 10px; font-size: 15px;">🎯 EXTRACT + MATCH PROJECTS</div>
+                                <div style="color: var(--text-dim); font-size: 13px; line-height: 1.5;">
+                                    Parse CV, rank matching projects by skill compatibility, and identify skill gaps.
+                                </div>
+                            </div>
+                        </div>
+                        <div style="color: var(--arc-yellow); font-size: 13px; padding: 16px; background: rgba(255,185,0,0.1); border-radius: 4px; border: 1px solid rgba(255,185,0,0.3);">
+                            <strong>⚠️ Instructions:</strong> Use the file upload on the left panel to select a CV, then choose your desired analysis mode.
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+        """
+
+    def process_cv_upload(self, file_obj) -> str:
+        """Process uploaded CV file and extract skills. Returns main output HTML."""
+        if file_obj is None:
+            return '<div style="color: var(--arc-red); padding: 40px; text-align: center;">⚠️ No file uploaded. Please select a CV file (PDF or DOCX).</div>'
+        
+        try:
+            import os
+            file_name = os.path.basename(file_obj.name) if hasattr(file_obj, 'name') else "unknown"
+            self._cv_filename = file_name
+            
+            # Terminal logging
+            print("\n" + "="*80)
+            print(f"[CV UPLOAD] Processing CV: {file_name}")
+            print("="*80)
+            
+            self._main_interface.register_agent_action("📤 CV Upload Started", {"file": file_name})
+            
+            # Read file content
+            if hasattr(file_obj, 'name'):
+                # Gradio file object
+                file_path = file_obj.name
+                with open(file_path, 'rb') as f:
+                    file_content = f.read()
+            else:
+                # Direct file path
+                file_path = str(file_obj)
+                with open(file_path, 'rb') as f:
+                    file_content = f.read()
+            
+            file_size_kb = len(file_content) / 1024
+            self._main_interface.register_agent_action("📄 Parsing Document", {
+                "size": f"{file_size_kb:.1f}KB",
+                "format": os.path.splitext(file_name)[1].upper()
+            })
+            
+            # Extract text from CV
+            cv_text = parse_cv(file_path=file_path, file_content=file_content, log_callback=self._main_interface.register_agent_action)
+            
+            if not cv_text or len(cv_text.strip()) < 50:
+                self._main_interface.register_agent_action("⚠️ Text Extraction Failed", {"extracted_chars": len(cv_text) if cv_text else 0})
+                print(f"[CV UPLOAD] ❌ ERROR: Text extraction failed - only {len(cv_text) if cv_text else 0} chars extracted")
+                return '<div style="color: var(--arc-red); padding: 40px; text-align: center;">⚠️ Could not extract meaningful text from the CV. Please ensure the file is not corrupted.</div>'
+            
+            word_count = len(cv_text.split())
+            char_count = len(cv_text)
+            self._main_interface.register_agent_action("✅ Text Extracted", {
+                "words": word_count,
+                "characters": char_count,
+                "pages_est": max(1, word_count // 300)  # Rough estimate
+            })
+            
+            self._main_interface.register_agent_action("🤖 AI Analysis Starting", {"status": "Initializing AI-powered skill extraction..."})
+            
+            # Extract skills using LLM with logging callback
+            skills_data = extract_skills_from_cv_text(cv_text, log_callback=self._main_interface.register_agent_action)
+            self._cv_skills_data = skills_data
+            
+            if "error" not in skills_data:
+                total_skills = len(skills_data.get("technical_skills", [])) + len(skills_data.get("soft_skills", []))
+                self._main_interface.register_agent_action("🎯 Skills Extracted", {
+                    "technical_skills": len(skills_data.get("technical_skills", [])),
+                    "soft_skills": len(skills_data.get("soft_skills", [])),
+                    "total": total_skills
+                })
+                print(f"[CV UPLOAD] ✅ SUCCESS: Extracted {total_skills} total skills")
+            else:
+                print(f"[CV UPLOAD] ⚠️ WARNING: Skills extraction completed with errors")
+            
+            print("="*80 + "\n")
+            
+            # Render CV analysis HTML for main display
+            main_output = render_cv_analysis_html(skills_data, file_name)
+            
+            return main_output
+            
+        except Exception as e:
+            error_msg = str(e)
+            self._main_interface.register_agent_action("CV Processing Error", {"error": error_msg})
+            print(f"[CV UPLOAD] ❌ EXCEPTION: {type(e).__name__} - {error_msg}")
+            print("="*80 + "\n")
+            return f'<div style="color: var(--arc-red); padding: 40px; text-align: center;">⚠️ Error processing CV: {html.escape(error_msg)}</div>'
+    
+    def get_extracted_skills(self) -> Optional[Dict[str, Any]]:
+        """Get the most recently extracted skills data."""
+        return self._cv_skills_data
+    
+    def process_cv_with_matching(self, file_obj) -> str:
+        """Process CV and match against projects. Returns main output HTML."""
+        if file_obj is None:
+            return '<div style="color: var(--arc-red); padding: 40px; text-align: center;">⚠️ No file uploaded. Please select a CV file (PDF or DOCX).</div>'
+        
+        try:
+            import os
+            file_name = os.path.basename(file_obj.name) if hasattr(file_obj, 'name') else "unknown"
+            self._cv_filename = file_name
+            
+            # Terminal logging
+            print("\n" + "="*80)
+            print(f"[CV MATCHING] Processing CV with Project Matching: {file_name}")
+            print("="*80)
+            
+            self._main_interface.register_agent_action("📤 CV Upload + Matching Started", {"file": file_name})
+            
+            # Read file content
+            if hasattr(file_obj, 'name'):
+                file_path = file_obj.name
+                with open(file_path, 'rb') as f:
+                    file_content = f.read()
+            else:
+                file_path = str(file_obj)
+                with open(file_path, 'rb') as f:
+                    file_content = f.read()
+            
+            file_size_kb = len(file_content) / 1024
+            self._main_interface.register_agent_action("📄 Parsing Document", {
+                "size": f"{file_size_kb:.1f}KB",
+                "format": os.path.splitext(file_name)[1].upper()
+            })
+            
+            # Extract text from CV
+            cv_text = parse_cv(file_path=file_path, file_content=file_content, log_callback=self._main_interface.register_agent_action)
+            
+            if not cv_text or len(cv_text.strip()) < 50:
+                self._main_interface.register_agent_action("⚠️ Text Extraction Failed", {"extracted_chars": len(cv_text) if cv_text else 0})
+                print(f"[CV MATCHING] ❌ ERROR: Text extraction failed")
+                return '<div style="color: var(--arc-red); padding: 40px; text-align: center;">⚠️ Could not extract meaningful text from the CV.</div>'
+            
+            word_count = len(cv_text.split())
+            char_count = len(cv_text)
+            self._main_interface.register_agent_action("✅ Text Extracted", {
+                "words": word_count,
+                "characters": char_count,
+                "pages_est": max(1, word_count // 300)
+            })
+            
+            self._main_interface.register_agent_action("🤖 AI Analysis Starting", {"status": "Extracting skills from CV..."})
+            
+            # Extract skills using LLM
+            skills_data = extract_skills_from_cv_text(cv_text, log_callback=self._main_interface.register_agent_action)
+            self._cv_skills_data = skills_data
+            
+            if "error" in skills_data:
+                print(f"[CV MATCHING] ⚠️ WARNING: Skills extraction completed with errors")
+                return '<div style="color: var(--arc-red); padding: 40px; text-align: center;">⚠️ Error extracting skills from CV.</div>'
+            
+            total_skills = len(skills_data.get("technical_skills", [])) + len(skills_data.get("soft_skills", []))
+            self._main_interface.register_agent_action("🎯 Skills Extracted", {
+                "technical_skills": len(skills_data.get("technical_skills", [])),
+                "soft_skills": len(skills_data.get("soft_skills", [])),
+                "total": total_skills
+            })
+            print(f"[CV MATCHING] ✅ Skills extracted: {total_skills} total skills")
+            
+            # Match against projects
+            self._main_interface.register_agent_action("🔍 Starting Project Matching", {"status": "Comparing skills with project requirements..."})
+            
+            matched_projects = match_cv_to_projects(skills_data, log_callback=self._main_interface.register_agent_action)
+            
+            if not matched_projects:
+                print(f"[CV MATCHING] ⚠️ No projects found for matching")
+                self._main_interface.register_agent_action("⚠️ No Projects Found", {"status": "No projects available in database"})
+                # Still show CV analysis
+                main_output = render_cv_analysis_html(skills_data, file_name)
+                return main_output
+            
+            # Skip training costs - just show matching results
+            # Set empty training plans for all projects
+            for project in matched_projects:
+                project['training_plans'] = []
+            
+            print(f"[CV MATCHING] ✅ SUCCESS: Matched {len(matched_projects)} projects")
+            self._main_interface.register_agent_action("✅ Matching Complete", {
+                "total_matches": len(matched_projects),
+                "best_match": f"{matched_projects[0]['project_name']} ({matched_projects[0]['match_percentage']}%)"
+            })
+            
+            print("="*80 + "\n")
+            
+            # Render CV matching results for main display
+            main_output = render_cv_matching_html(skills_data, matched_projects, file_name)
+            
+            return main_output
+            
+        except Exception as e:
+            error_msg = str(e)
+            self._main_interface.register_agent_action("CV Matching Error", {"error": error_msg})
+            print(f"[CV MATCHING] ❌ EXCEPTION: {type(e).__name__} - {error_msg}")
+            print("="*80 + "\n")
+            return f'<div style="color: var(--arc-red); padding: 40px; text-align: center;">⚠️ Error processing CV: {html.escape(error_msg)}</div>'

UI/render_cv_html.py

@@ -0,0 +1,384 @@
+"""Render CV analysis results in tactical-themed HTML format."""
+
+from __future__ import annotations
+
+import html
+from typing import Any, Dict
+
+
+def render_cv_analysis_html(skills_data: Dict[str, Any], filename: str = "Unknown") -> str:
+    """
+    Renders CV analysis data into a Tactical-themed card layout similar to project analysis.
+    
+    Args:
+        skills_data: Dictionary containing extracted skills and candidate information
+        filename: Name of the CV file
+        
+    Returns:
+        HTML string for display
+    """
+    
+    # Internal CSS
+    css = """
+    <style>
+        .cv-report-wrapper {
+            width: 100%;
+            min-height: 70vh;
+            display: flex;
+            flex-direction: column;
+        }
+        
+        .cv-header-section {
+            margin-bottom: 24px;
+            padding: 0 4px;
+            border-bottom: 1px solid var(--border-dim);
+            padding-bottom: 16px;
+        }
+        
+        .cv-main-card {
+            background: var(--bg-card);
+            border: 1px solid var(--border-dim);
+            border-left: 4px solid var(--arc-orange);
+            padding: 24px;
+            margin-bottom: 24px;
+        }
+        
+        .cv-grid {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(350px, 1fr));
+            gap: 20px;
+            margin-top: 24px;
+        }
+        
+        .cv-section-card {
+            background: var(--bg-card);
+            border: 1px solid var(--border-dim);
+            padding: 20px;
+            transition: border-color 0.2s;
+        }
+        
+        .cv-section-card:hover {
+            border-color: var(--arc-yellow);
+            box-shadow: 0 4px 24px rgba(0,0,0,0.4);
+        }
+        
+        .cv-section-title {
+            font-size: 13px;
+            color: var(--arc-yellow);
+            text-transform: uppercase;
+            letter-spacing: 1.5px;
+            margin-bottom: 16px;
+            font-weight: 700;
+            display: flex;
+            align-items: center;
+            gap: 8px;
+        }
+        
+        .cv-section-title::before {
+            content: "";
+            width: 4px;
+            height: 16px;
+            background: var(--arc-yellow);
+            box-shadow: 0 0 8px var(--arc-yellow);
+        }
+        
+        .cv-skill-tag {
+            display: inline-block;
+            background: var(--bg-panel);
+            border: 1px solid var(--border-dim);
+            padding: 8px 14px;
+            margin: 4px;
+            border-radius: 4px;
+            font-family: var(--font-mono);
+            font-size: 13px;
+            font-weight: 600;
+            transition: all 0.2s;
+        }
+        
+        .cv-skill-tag.technical {
+            color: var(--arc-green);
+            border-color: var(--arc-green);
+        }
+        
+        .cv-skill-tag.soft {
+            color: var(--arc-cyan);
+            border-color: var(--arc-cyan);
+        }
+        
+        .cv-skill-tag.domain {
+            color: var(--arc-orange);
+            border-color: var(--arc-orange);
+        }
+        
+        .cv-skill-tag:hover {
+            background: var(--bg-void);
+            box-shadow: 0 0 12px currentColor;
+        }
+        
+        .cv-info-item {
+            display: flex;
+            align-items: flex-start;
+            padding: 10px 0;
+            border-bottom: 1px solid rgba(255,255,255,0.05);
+        }
+        
+        .cv-info-item:last-child {
+            border-bottom: none;
+        }
+        
+        .cv-info-label {
+            font-size: 12px;
+            color: var(--text-main);
+            font-weight: 600;
+            text-transform: uppercase;
+            min-width: 120px;
+            margin-right: 16px;
+            opacity: 0.9;
+        }
+        
+        .cv-info-value {
+            color: var(--text-main);
+            font-size: 14px;
+            flex: 1;
+        }
+        
+        .cv-summary-box {
+            background: rgba(255, 127, 0, 0.08);
+            border: 1px solid var(--arc-orange);
+            border-radius: 4px;
+            padding: 16px;
+            margin-bottom: 24px;
+        }
+        
+        .cv-summary-text {
+            color: var(--text-main);
+            line-height: 1.7;
+            font-size: 15px;
+            opacity: 0.95;
+        }
+        
+        .cv-stats-bar {
+            display: flex;
+            gap: 24px;
+            background: rgba(255,255,255,0.05);
+            border: 1px solid var(--border-dim);
+            padding: 16px 24px;
+            margin-bottom: 24px;
+            flex-wrap: wrap;
+        }
+        
+        .cv-stat-item {
+            display: flex;
+            flex-direction: column;
+            gap: 4px;
+        }
+        
+        .cv-stat-label {
+            font-size: 11px;
+            color: var(--text-main);
+            font-weight: 600;
+            letter-spacing: 0.5px;
+            text-transform: uppercase;
+            opacity: 0.9;
+        }
+        
+        .cv-stat-value {
+            font-size: 20px;
+            color: var(--text-main);
+            font-weight: 700;
+            font-family: var(--font-mono);
+        }
+        
+        .cv-list {
+            list-style: none;
+            padding: 0;
+            margin: 0;
+        }
+        
+        .cv-list-item {
+            padding: 8px 0;
+            padding-left: 24px;
+            position: relative;
+            color: var(--text-main);
+            font-size: 14px;
+            opacity: 0.9;
+        }
+        
+        .cv-list-item::before {
+            content: "▸";
+            position: absolute;
+            left: 0;
+            color: var(--arc-orange);
+            font-weight: bold;
+        }
+        
+        .cv-error-box {
+            background: rgba(255, 42, 42, 0.08);
+            border: 1px solid var(--arc-red);
+            border-radius: 4px;
+            padding: 20px;
+            color: var(--arc-red);
+            text-align: center;
+            font-family: var(--font-mono);
+        }
+    </style>
+    """
+    
+    # Check for errors
+    if "error" in skills_data:
+        error_msg = html.escape(skills_data.get("summary", "Unknown error occurred"))
+        return f"""
+        {css}
+        <div class="cv-report-wrapper">
+            <div class="cv-error-box">
+                <h3 style="margin: 0 0 12px 0;">⚠️ CV ANALYSIS FAILED</h3>
+                <p style="margin: 0;">{error_msg}</p>
+            </div>
+        </div>
+        """
+    
+    # Extract data
+    tech_skills = skills_data.get("technical_skills", [])
+    soft_skills = skills_data.get("soft_skills", [])
+    experience_years = skills_data.get("experience_years", "unknown")
+    recent_roles = skills_data.get("recent_roles", [])
+    education = skills_data.get("education", [])
+    certifications = skills_data.get("certifications", [])
+    domain_expertise = skills_data.get("domain_expertise", [])
+    summary = skills_data.get("summary", "")
+    
+    # Calculate stats
+    total_skills = len(tech_skills) + len(soft_skills)
+    
+    # Build HTML
+    html_parts = [css, '<div class="cv-report-wrapper">']
+    
+    # Header
+    safe_filename = html.escape(filename)
+    html_parts.append(f"""
+    <div class="cv-header-section">
+        <div style="display: flex; justify-content: space-between; align-items: flex-end; flex-wrap: wrap; gap: 16px;">
+            <div>
+                <h2 style="margin:0; color:white; font-size:24px; letter-spacing: 0.5px;">CV ANALYSIS REPORT</h2>
+                <div style="color:var(--arc-yellow); font-family:var(--font-mono); font-size: 14px; margin-top:6px;">SOURCE: {safe_filename}</div>
+            </div>
+            <div style="font-family: var(--font-mono); font-size: 12px; color: var(--text-main); text-align: right;">
+                <div>STATUS: <span style="color:var(--arc-green)">PROCESSED</span></div>
+                <div>TIMESTAMP: {html.escape(str(__import__('datetime').datetime.now().strftime('%Y-%m-%d %H:%M')))}</div>
+            </div>
+        </div>
+    </div>
+    """)
+    
+    # Stats Bar
+    html_parts.append(f"""
+    <div class="cv-stats-bar">
+        <div class="cv-stat-item">
+            <div class="cv-stat-label">Total Skills</div>
+            <div class="cv-stat-value" style="color: var(--arc-cyan);">{total_skills}</div>
+        </div>
+        <div style="width: 1px; height: 32px; background: var(--border-dim);"></div>
+        <div class="cv-stat-item">
+            <div class="cv-stat-label">Technical</div>
+            <div class="cv-stat-value" style="color: var(--arc-green);">{len(tech_skills)}</div>
+        </div>
+        <div style="width: 1px; height: 32px; background: var(--border-dim);"></div>
+        <div class="cv-stat-item">
+            <div class="cv-stat-label">Soft Skills</div>
+            <div class="cv-stat-value" style="color: var(--arc-cyan);">{len(soft_skills)}</div>
+        </div>
+        <div style="width: 1px; height: 32px; background: var(--border-dim);"></div>
+        <div class="cv-stat-item">
+            <div class="cv-stat-label">Experience</div>
+            <div class="cv-stat-value" style="color: var(--arc-orange);">{html.escape(str(experience_years))}</div>
+        </div>
+    </div>
+    """)
+    
+    # Summary
+    if summary:
+        safe_summary = html.escape(summary)
+        html_parts.append(f"""
+        <div class="cv-summary-box">
+            <div style="font-size: 12px; color: var(--arc-orange); font-weight: 700; text-transform: uppercase; margin-bottom: 12px; letter-spacing: 1px;">
+                📄 CANDIDATE PROFILE SUMMARY
+            </div>
+            <div class="cv-summary-text">{safe_summary}</div>
+        </div>
+        """)
+    
+    # Skills Grid
+    html_parts.append('<div class="cv-grid">')
+    
+    # Technical Skills Card
+    if tech_skills:
+        html_parts.append('<div class="cv-section-card">')
+        html_parts.append('<div class="cv-section-title">💻 Technical Skills</div>')
+        html_parts.append('<div style="margin-top: 12px;">')
+        for skill in tech_skills:
+            safe_skill = html.escape(skill)
+            html_parts.append(f'<span class="cv-skill-tag technical">{safe_skill}</span>')
+        html_parts.append('</div></div>')
+    
+    # Soft Skills Card
+    if soft_skills:
+        html_parts.append('<div class="cv-section-card">')
+        html_parts.append('<div class="cv-section-title">🤝 Soft Skills</div>')
+        html_parts.append('<div style="margin-top: 12px;">')
+        for skill in soft_skills:
+            safe_skill = html.escape(skill)
+            html_parts.append(f'<span class="cv-skill-tag soft">{safe_skill}</span>')
+        html_parts.append('</div></div>')
+    
+    # Domain Expertise Card
+    if domain_expertise:
+        html_parts.append('<div class="cv-section-card">')
+        html_parts.append('<div class="cv-section-title">🎯 Domain Expertise</div>')
+        html_parts.append('<div style="margin-top: 12px;">')
+        for domain in domain_expertise:
+            safe_domain = html.escape(domain)
+            html_parts.append(f'<span class="cv-skill-tag domain">{safe_domain}</span>')
+        html_parts.append('</div></div>')
+    
+    # Experience Card
+    if recent_roles or experience_years != "unknown":
+        html_parts.append('<div class="cv-section-card">')
+        html_parts.append('<div class="cv-section-title">💼 Professional Experience</div>')
+        if experience_years != "unknown":
+            html_parts.append(f'<div class="cv-info-item">')
+            html_parts.append(f'<div class="cv-info-label">Years</div>')
+            html_parts.append(f'<div class="cv-info-value" style="color: var(--arc-orange); font-weight: 600;">{html.escape(str(experience_years))}</div>')
+            html_parts.append('</div>')
+        if recent_roles:
+            html_parts.append('<div style="margin-top: 12px;"><ul class="cv-list">')
+            for role in recent_roles[:5]:  # Limit to 5 roles
+                safe_role = html.escape(role)
+                html_parts.append(f'<li class="cv-list-item">{safe_role}</li>')
+            html_parts.append('</ul></div>')
+        html_parts.append('</div>')
+    
+    # Education Card
+    if education:
+        html_parts.append('<div class="cv-section-card">')
+        html_parts.append('<div class="cv-section-title">🎓 Education</div>')
+        html_parts.append('<ul class="cv-list">')
+        for edu in education:
+            safe_edu = html.escape(edu)
+            html_parts.append(f'<li class="cv-list-item">{safe_edu}</li>')
+        html_parts.append('</ul></div>')
+    
+    # Certifications Card
+    if certifications:
+        html_parts.append('<div class="cv-section-card">')
+        html_parts.append('<div class="cv-section-title">📜 Certifications</div>')
+        html_parts.append('<ul class="cv-list">')
+        for cert in certifications:
+            safe_cert = html.escape(cert)
+            html_parts.append(f'<li class="cv-list-item">{safe_cert}</li>')
+        html_parts.append('</ul></div>')
+    
+    html_parts.append('</div>')  # Close grid
+    html_parts.append('</div>')  # Close wrapper
+    
+    return ''.join(html_parts)
+

UI/render_cv_matching.py

@@ -0,0 +1,387 @@
+"""Render CV project matching results in 3-panel tactical layout."""
+
+from __future__ import annotations
+
+import html
+from typing import Any, Dict, List
+
+
+def render_cv_matching_html(
+    cv_skills_data: Dict[str, Any],
+    matched_projects: List[Dict[str, Any]],
+    filename: str = "Unknown"
+) -> str:
+    """
+    Renders CV matching results in a 3-panel tactical layout.
+    
+    Panel 1: CV Analysis
+    Panel 2: Project Matches (ranked)
+    Panel 3: Training Costs per Project
+    
+    Args:
+        cv_skills_data: Extracted CV skills
+        matched_projects: Projects with match data and training plans
+        filename: CV filename
+        
+    Returns:
+        HTML string for display
+    """
+    
+    # CSS for 3-panel layout
+    css = """
+    <style>
+        .cv-matching-wrapper {
+            width: 100%;
+            min-height: 70vh;
+            display: flex;
+            flex-direction: column;
+        }
+        
+        .cv-matching-header {
+            margin-bottom: 24px;
+            padding: 0 4px;
+            border-bottom: 1px solid var(--border-dim);
+            padding-bottom: 16px;
+        }
+        
+        .cv-matching-panels {
+            display: grid;
+            grid-template-columns: 1fr 1.5fr 1fr;
+            gap: 20px;
+            min-height: 60vh;
+        }
+        
+        @media (max-width: 1400px) {
+            .cv-matching-panels {
+                grid-template-columns: 1fr;
+            }
+        }
+        
+        .cv-panel {
+            background: var(--bg-card);
+            border: 1px solid var(--border-dim);
+            padding: 20px;
+            display: flex;
+            flex-direction: column;
+            max-height: 80vh;
+            overflow-y: auto;
+        }
+        
+        .cv-panel::-webkit-scrollbar { width: 8px; }
+        .cv-panel::-webkit-scrollbar-track { background: var(--bg-void); }
+        .cv-panel::-webkit-scrollbar-thumb { background: var(--border-dim); border-radius: 4px; }
+        
+        .panel-header {
+            font-size: 14px;
+            color: var(--arc-yellow);
+            text-transform: uppercase;
+            letter-spacing: 1.5px;
+            margin-bottom: 20px;
+            font-weight: 700;
+            padding-bottom: 12px;
+            border-bottom: 2px solid var(--arc-yellow);
+            display: flex;
+            align-items: center;
+            gap: 8px;
+        }
+        
+        .cv-summary-compact {
+            background: rgba(255, 127, 0, 0.08);
+            border: 1px solid var(--arc-orange);
+            border-radius: 4px;
+            padding: 12px;
+            margin-bottom: 16px;
+            font-size: 13px;
+            color: var(--text-main);
+            line-height: 1.5;
+            opacity: 0.95;
+        }
+        
+        .skill-badge-small {
+            display: inline-block;
+            background: var(--bg-panel);
+            border: 1px solid var(--border-dim);
+            padding: 4px 8px;
+            margin: 2px;
+            border-radius: 3px;
+            font-size: 11px;
+            font-weight: 600;
+            font-family: var(--font-mono);
+        }
+        
+        .skill-badge-small.technical { color: var(--arc-green); border-color: var(--arc-green); }
+        .skill-badge-small.soft { color: var(--arc-cyan); border-color: var(--arc-cyan); }
+        
+        .project-match-card {
+            background: var(--bg-panel);
+            border: 1px solid var(--border-dim);
+            border-left: 4px solid var(--arc-orange);
+            padding: 16px;
+            margin-bottom: 12px;
+            transition: all 0.2s;
+            cursor: pointer;
+        }
+        
+        .project-match-card:hover {
+            border-left-color: var(--arc-yellow);
+            box-shadow: 0 4px 16px rgba(0,0,0,0.3);
+        }
+        
+        .project-match-card.perfect { border-left-color: var(--arc-green); }
+        .project-match-card.good { border-left-color: var(--arc-cyan); }
+        .project-match-card.partial { border-left-color: var(--arc-yellow); }
+        .project-match-card.low { border-left-color: var(--arc-red); }
+        
+        .match-percentage {
+            font-size: 32px;
+            font-weight: 800;
+            font-family: var(--font-mono);
+            color: var(--text-main);
+            margin-bottom: 8px;
+        }
+        
+        .match-percentage.perfect { color: var(--arc-green); }
+        .match-percentage.good { color: var(--arc-cyan); }
+        .match-percentage.partial { color: var(--arc-yellow); }
+        .match-percentage.low { color: var(--arc-red); }
+        
+        .project-name {
+            font-size: 16px;
+            font-weight: 700;
+            color: var(--text-main);
+            margin-bottom: 8px;
+        }
+        
+        .project-meta {
+            font-size: 11px;
+            color: var(--text-main);
+            font-family: var(--font-mono);
+            margin-bottom: 12px;
+            opacity: 0.9;
+        }
+        
+        .skill-match-bar {
+            display: flex;
+            gap: 8px;
+            align-items: center;
+            font-size: 12px;
+            color: var(--text-main);
+        }
+        
+        .training-cost-card {
+            background: var(--bg-panel);
+            border: 1px solid var(--border-dim);
+            padding: 12px;
+            margin-bottom: 10px;
+        }
+        
+        .training-cost-card.low { border-left: 3px solid var(--arc-green); }
+        .training-cost-card.medium { border-left: 3px solid var(--arc-yellow); }
+        .training-cost-card.high { border-left: 3px solid var(--arc-red); }
+        
+        .cost-project-name {
+            font-size: 13px;
+            font-weight: 700;
+            color: var(--arc-orange);
+            margin-bottom: 8px;
+        }
+        
+        .cost-summary {
+            font-size: 12px;
+            color: var(--text-main);
+            margin-bottom: 10px;
+            opacity: 0.9;
+        }
+        
+        .cost-value {
+            font-size: 20px;
+            font-weight: 700;
+            font-family: var(--font-mono);
+            color: var(--text-main);
+        }
+        
+        .cost-breakdown {
+            font-size: 11px;
+            color: var(--text-main);
+            font-family: var(--font-mono);
+            opacity: 0.9;
+        }
+        
+        .stat-inline {
+            display: inline-flex;
+            align-items: center;
+            gap: 6px;
+            background: rgba(255,255,255,0.05);
+            padding: 4px 8px;
+            border-radius: 3px;
+            font-size: 11px;
+            margin: 2px;
+        }
+        
+        .no-data-message {
+            text-align: center;
+            padding: 40px 20px;
+            color: var(--text-main);
+            font-family: var(--font-mono);
+            font-size: 13px;
+            opacity: 0.9;
+        }
+    </style>
+    """
+    
+    # Extract data
+    tech_skills = cv_skills_data.get("technical_skills", [])
+    soft_skills = cv_skills_data.get("soft_skills", [])
+    experience_years = cv_skills_data.get("experience_years", "unknown")
+    summary = cv_skills_data.get("summary", "")
+    
+    total_skills = len(tech_skills) + len(soft_skills)
+    
+    # Build HTML
+    html_parts = [css, '<div class="cv-matching-wrapper">']
+    
+    # Header
+    safe_filename = html.escape(filename)
+    html_parts.append(f"""
+    <div class="cv-matching-header">
+        <div style="display: flex; justify-content: space-between; align-items: flex-end; flex-wrap: wrap; gap: 16px;">
+            <div>
+                <h2 style="margin:0; color:white; font-size:24px; letter-spacing: 0.5px;">CV + PROJECT MATCHING REPORT</h2>
+                <div style="color:var(--arc-yellow); font-family:var(--font-mono); font-size: 14px; margin-top:6px;">SOURCE: {safe_filename}</div>
+            </div>
+            <div style="font-family: var(--font-mono); font-size: 12px; color: var(--text-main); text-align: right;">
+                <div>PROJECTS ANALYZED: <span style="color:var(--arc-cyan); font-weight:700;">{len(matched_projects)}</span></div>
+                <div>CANDIDATE SKILLS: <span style="color:var(--arc-green); font-weight:700;">{total_skills}</span></div>
+            </div>
+        </div>
+    </div>
+    """)
+    
+    # 3-Panel Grid
+    html_parts.append('<div class="cv-matching-panels">')
+    
+    # ============== PANEL 1: CV ANALYSIS ==============
+    html_parts.append('<div class="cv-panel">')
+    html_parts.append('<div class="panel-header">📄 CANDIDATE PROFILE</div>')
+    
+    # Summary
+    if summary:
+        safe_summary = html.escape(summary)
+        html_parts.append(f'<div class="cv-summary-compact">{safe_summary}</div>')
+    
+    # Stats
+    html_parts.append(f"""
+    <div style="margin-bottom: 20px;">
+        <div class="stat-inline"><strong>Experience:</strong> {html.escape(str(experience_years))}</div>
+        <div class="stat-inline"><strong>Tech Skills:</strong> {len(tech_skills)}</div>
+        <div class="stat-inline"><strong>Soft Skills:</strong> {len(soft_skills)}</div>
+    </div>
+    """)
+    
+    # Skills
+    if tech_skills:
+        html_parts.append('<div style="margin-bottom: 16px;"><div style="font-size:12px; color:var(--arc-yellow); margin-bottom:8px; font-weight:600;">💻 TECHNICAL</div>')
+        for skill in tech_skills[:15]:  # Limit display
+            html_parts.append(f'<span class="skill-badge-small technical">{html.escape(skill)}</span>')
+        if len(tech_skills) > 15:
+            html_parts.append(f'<span class="skill-badge-small technical">+{len(tech_skills) - 15} more</span>')
+        html_parts.append('</div>')
+    
+    if soft_skills:
+        html_parts.append('<div><div style="font-size:12px; color:var(--arc-cyan); margin-bottom:8px; font-weight:600;">🤝 SOFT SKILLS</div>')
+        for skill in soft_skills[:10]:
+            html_parts.append(f'<span class="skill-badge-small soft">{html.escape(skill)}</span>')
+        if len(soft_skills) > 10:
+            html_parts.append(f'<span class="skill-badge-small soft">+{len(soft_skills) - 10} more</span>')
+        html_parts.append('</div>')
+    
+    html_parts.append('</div>')  # Close Panel 1
+    
+    # ============== PANEL 2: PROJECT MATCHES ==============
+    html_parts.append('<div class="cv-panel">')
+    html_parts.append('<div class="panel-header">🎯 PROJECT MATCHES (RANKED)</div>')
+    
+    if matched_projects:
+        for project in matched_projects:
+            match_pct = project['match_percentage']
+            
+            # Determine match level
+            if match_pct >= 90:
+                match_class = "perfect"
+            elif match_pct >= 70:
+                match_class = "good"
+            elif match_pct >= 50:
+                match_class = "partial"
+            else:
+                match_class = "low"
+            
+            project_name = html.escape(project['project_name'])
+            matched_count = project['matched_skills_count']
+            required_count = project['required_skills_count']
+            missing_count = project['missing_skills_count']
+            status = html.escape(project.get('status', 'Unknown'))
+            
+            # Convert budget to int/float for formatting
+            budget = project.get("budget", 0)
+            try:
+                budget_num = float(budget) if budget else 0
+            except (ValueError, TypeError):
+                budget_num = 0
+            
+            html_parts.append(f'<div class="project-match-card {match_class}">')
+            html_parts.append(f'<div class="match-percentage {match_class}">{match_pct}%</div>')
+            html_parts.append(f'<div class="project-name">{project_name}</div>')
+            html_parts.append(f'<div class="project-meta">STATUS: {status} | BUDGET: ${budget_num:,.0f}</div>')
+            html_parts.append(f'<div class="skill-match-bar">')
+            html_parts.append(f'<span style="color:var(--arc-green);">✓ {matched_count} Match</span>')
+            html_parts.append(f'<span style="color:var(--text-main); opacity:0.6;">|</span>')
+            html_parts.append(f'<span style="color:var(--arc-red);">✗ {missing_count} Gap</span>')
+            html_parts.append(f'<span style="color:var(--text-main); opacity:0.6;">|</span>')
+            html_parts.append(f'<span style="color:var(--text-main);">{required_count} Required</span>')
+            html_parts.append('</div></div>')
+    else:
+        html_parts.append('<div class="no-data-message">No projects found for matching.</div>')
+    
+    html_parts.append('</div>')  # Close Panel 2
+    
+    # ============== PANEL 3: SKILL GAPS SUMMARY ==============
+    html_parts.append('<div class="cv-panel">')
+    html_parts.append('<div class="panel-header">⚠️ SKILL GAPS</div>')
+    
+    if matched_projects:
+        # Show missing skills for each project
+        has_gaps = False
+        for project in matched_projects:
+            if project['missing_skills_count'] == 0:
+                continue  # Skip projects with 100% match
+            
+            has_gaps = True
+            project_name = html.escape(project['project_name'])
+            missing_skills = project.get('missing_skills', [])
+            
+            html_parts.append('<div class="training-cost-card">')
+            html_parts.append(f'<div class="cost-project-name">{project_name}</div>')
+            html_parts.append(f'<div class="cost-summary">{project["missing_skills_count"]} skill gap(s)</div>')
+            
+            # List missing skills
+            html_parts.append('<div style="margin-top: 10px;">')
+            for skill in missing_skills[:5]:  # Show max 5
+                skill_name = html.escape(skill)
+                html_parts.append(f'<div style="font-size:12px; color:var(--arc-red); padding:4px 0;">• {skill_name}</div>')
+            if len(missing_skills) > 5:
+                html_parts.append(f'<div style="font-size:12px; color:var(--text-main); opacity:0.8; padding:4px 0;">... and {len(missing_skills) - 5} more</div>')
+            html_parts.append('</div>')
+            html_parts.append('</div>')
+        
+        if not has_gaps:
+            html_parts.append('<div class="no-data-message">✅ Candidate is fully qualified for all projects!<br>No skill gaps detected.</div>')
+    else:
+        html_parts.append('<div class="no-data-message">No data available.</div>')
+    
+    html_parts.append('</div>')  # Close Panel 3
+    
+    html_parts.append('</div>')  # Close panels grid
+    html_parts.append('</div>')  # Close wrapper
+    
+    return ''.join(html_parts)
+

UI/render_plan_html.py

@@ -59,9 +59,10 @@ def render_plan_html(result: Any) -> str:
         .sec-role-badge {
             font-size: 12px;
             font-weight: 700;
-            color: var(--text-dim);
+            color: var(--text-main);
             letter-spacing: 1px;
             text-transform: uppercase;
+            opacity: 0.9;
         }
         
         /* BODY */
@@ -83,7 +84,7 @@ def render_plan_html(result: Any) -> str:
             font-size: 12px;
             color: var(--arc-orange);
             margin-bottom: 20px;
-            opacity: 0.8;
+            opacity: 1.0;
         }
 
         /* SKILL GAPS (Binary State) */
@@ -153,7 +154,7 @@ def render_plan_html(result: Any) -> str:
 
         .sec-item-details { flex-grow: 1; }
         .sec-item-title { font-size: 14px; color: #fff; font-weight: 600; margin-bottom: 4px; line-height: 1.4;}
-        .sec-item-meta { font-size: 12px; color: #99AAB5; font-family: var(--font-mono); }
+        .sec-item-meta { font-size: 12px; color: var(--text-main); font-family: var(--font-mono); opacity: 0.9; }
         
         /* STATS BAR */
         .sec-stats-bar {
@@ -171,10 +172,11 @@ def render_plan_html(result: Any) -> str:
         }
         .sec-stat-label {
             font-size: 11px;
-            color: var(--text-dim);
+            color: var(--text-main);
             font-weight: 600;
             letter-spacing: 0.5px;
             text-transform: uppercase;
+            opacity: 0.9;
         }
         .sec-stat-value {
             font-size: 18px;
@@ -256,7 +258,7 @@ def render_plan_html(result: Any) -> str:
             <h2 style="margin:0; color:white; font-size:24px; letter-spacing: 0.5px;">CAPABILITY ANALYSIS REPORT</h2> 
             <div style="color:var(--arc-yellow); font-family:var(--font-mono); font-size: 14px; margin-top:6px;">PROJECT: {project_name}</div>
         </div>
-        <div style="font-family: var(--font-mono); font-size: 12px; color: var(--text-dim); text-align: right;">
+        <div style="font-family: var(--font-mono); font-size: 12px; color: var(--text-main); text-align: right;">
             <div>STATUS: <span style="color:var(--arc-green)">ACTIVE</span></div>
             <div>HEADCOUNT: {len(team)}</div>
         </div>
@@ -273,7 +275,7 @@ def render_plan_html(result: Any) -> str:
         <div class="sec-divider"></div>
         <div class="sec-stat-group">
             <div class="sec-stat-label">Est. Timeline</div>
-            <div class="sec-stat-value" style="color: var(--arc-orange);">{max_duration:.0f} HRS <span style="font-size:11px; color:var(--text-dim)">(CONCURRENT)</span></div>
+            <div class="sec-stat-value" style="color: var(--arc-orange);">{max_duration:.0f} HRS <span style="font-size:11px; color:var(--text-main); opacity:0.8;">(CONCURRENT)</span></div>
         </div>
         <div class="sec-divider"></div>
         <div class="sec-stat-group">
@@ -341,7 +343,7 @@ def render_plan_html(result: Any) -> str:
         if not training_html and gaps_list:
             training_html = "<div style='font-size:12px; color:var(--arc-red); padding: 4px 0;'>PENDING: CURRICULUM GENERATION REQUIRED</div>"
         elif not training_html:
-            training_html = "<div style='font-size:12px; color:var(--text-dim); padding: 4px 0;'>NO ACTION REQUIRED</div>"
+            training_html = "<div style='font-size:12px; color:var(--text-main); opacity:0.9; padding: 4px 0;'>NO ACTION REQUIRED</div>"
 
         # Assemble Card
         # Create a faux Employee ID

agents/orchestrator_agent/get_agent_name_for_logs.py

@@ -1,5 +1,5 @@
 agent_names_map = {
-    'supabase_agent': '🟦 Supabase Agent',
+    'supabase_agent': 'Supabase Agent',
     'web_search_agent': '🌐 Web Search Agent',
     'orchestrator_agent': ' Orchestrator Agent',
 }

agents/supabase_agent/supabase_agent.py

@@ -1,10 +1,12 @@
 # agents/supabase_agent.py
 
 import os
+
 from smolagents import CodeAgent, MCPClient
+
 from LLM.llm_models import supabase_model
-from .get_supabase_agent_prompt import get_supabase_agent_prompt
 
+from .get_supabase_agent_prompt import get_supabase_agent_prompt
 
 mcp_client_config = {
                 "url": "https://mcp.supabase.com/mcp?project_ref=kzrdiydhjgsaxomkuijq",
@@ -61,7 +63,7 @@ class SupabaseAgent:
         def patched_run(prompt: str, *args, **kwargs):
             if self._agent_start_callback:
                 self._agent_start_callback(
-                    "🟦 Supabase Agent starting with database tasks",
+                    "Supabase Agent starting with database tasks",
                 )
             return original_run(prompt, *args, **kwargs)
 

app.py

@@ -51,8 +51,7 @@ def analyze_and_plan_interface(user_prompt: str):
     if orchestrator_agent is None:
         message = orchestrator_error or "Agent unavailable"
         ui.register_agent_action("System Offline", {"reason": message, "prompt": user_prompt})
-        yield ui.render_error_state(message)
-        return
+        return ui.render_error_state(message)
 
     # Cancel any existing run, if any
     if current_thread and current_thread.is_alive() and current_thread != threading.current_thread():
@@ -60,21 +59,28 @@ def analyze_and_plan_interface(user_prompt: str):
 
     current_thread = threading.current_thread()
 
-    yield "⏳ Running...", None
-
-    try:
-        result: Any = orchestrator_agent.analyze_and_plan(
-            user_prompt,
-            ui.register_agent_action,
-            get_is_run_cancelled_flag=lambda: is_run_cancelled
-        )
-        if result is not None:
-            yield ui.render_analysis_result(result)
-    except Exception as exc:
-        yield ui.render_error_state(str(exc))
-    finally:
-        if current_thread == threading.current_thread():
-            current_thread = None
+    def run_agent():
+        try:
+            result: Any = orchestrator_agent.analyze_and_plan(
+                user_prompt,
+                ui.register_agent_action,
+                get_is_run_cancelled_flag=lambda: is_run_cancelled
+            )
+            if result is not None:  # agent didn't get cancelled, keep running
+                ui.set_analysis_result(result)
+        except Exception as exc:
+            ui.set_analysis_error(str(exc))
+        finally:
+            # Stop processing when agent thread completes
+            ui.stop_processing()
+    
+    # Start a brand new thread for the new request
+    # Note: start_processing() was already called by the button handler
+    current_thread = threading.Thread(target=run_agent)
+    current_thread.start()
+
+    # Return processing state - timer will poll for updates
+    return ui.render_project_processing_state()
 
 
 def main():

pyproject.toml

@@ -16,6 +16,10 @@ dependencies = [
 	"ddgs>=9.9.1",
 	"repr>=0.3.1",
 	"typer>=0.20.0",
+	"pypdf>=4.0.0",
+	"python-docx>=1.0.0",
+	"pdfplumber>=0.11.0",
+	"python-multipart>=0.0.6",
 	"elevenlabs>=2.24.0",
 ]
 

utils/cv_parser.py

@@ -0,0 +1,134 @@
+"""CV Parser utility for extracting text from PDF and DOCX files."""
+
+from __future__ import annotations
+
+import io
+from pathlib import Path
+from typing import Optional
+
+
+def _print_terminal_log(action: str, details: str = ""):
+    """Print formatted log to terminal."""
+    timestamp = __import__('datetime').datetime.now().strftime("%H:%M:%S")
+    if details:
+        print(f"[{timestamp}] [CV PARSER] {action} :: {details}")
+    else:
+        print(f"[{timestamp}] [CV PARSER] {action}")
+
+
+def extract_text_from_pdf(file_content: bytes) -> str:
+    """Extract text from PDF file content."""
+    try:
+        import pdfplumber
+        
+        text_content = []
+        with pdfplumber.open(io.BytesIO(file_content)) as pdf:
+            for page in pdf.pages:
+                page_text = page.extract_text()
+                if page_text:
+                    text_content.append(page_text)
+        
+        return "\n\n".join(text_content)
+    except Exception as e:
+        raise ValueError(f"Failed to extract text from PDF: {str(e)}")
+
+
+def extract_text_from_docx(file_content: bytes) -> str:
+    """Extract text from DOCX file content."""
+    try:
+        from docx import Document
+        
+        doc = Document(io.BytesIO(file_content))
+        text_content = []
+        
+        for paragraph in doc.paragraphs:
+            if paragraph.text.strip():
+                text_content.append(paragraph.text)
+        
+        # Also extract text from tables
+        for table in doc.tables:
+            for row in table.rows:
+                for cell in row.cells:
+                    if cell.text.strip():
+                        text_content.append(cell.text)
+        
+        return "\n".join(text_content)
+    except Exception as e:
+        raise ValueError(f"Failed to extract text from DOCX: {str(e)}")
+
+
+def parse_cv(file_path: str | None = None, file_content: bytes | None = None, log_callback=None) -> str:
+    """
+    Parse CV file and extract text content.
+    
+    Args:
+        file_path: Path to the CV file (optional if file_content is provided)
+        file_content: Binary content of the file (optional if file_path is provided)
+    
+    Returns:
+        Extracted text from the CV
+    
+    Raises:
+        ValueError: If file format is not supported or parsing fails
+    """
+    if file_content is None and file_path is None:
+        raise ValueError("Either file_path or file_content must be provided")
+    
+    # Read file if path is provided
+    if file_content is None and file_path:
+        with open(file_path, "rb") as f:
+            file_content = f.read()
+    
+    # Determine file type
+    if file_path:
+        file_extension = Path(file_path).suffix.lower()
+        if log_callback:
+            log_callback("File Type Detection", {"method": "filename", "extension": file_extension})
+    else:
+        # Try to detect from content
+        if file_content and file_content[:4] == b'%PDF':
+            file_extension = '.pdf'
+        elif file_content and file_content[:2] == b'PK':  # ZIP-based format (DOCX)
+            file_extension = '.docx'
+        else:
+            if log_callback:
+                log_callback("⚠️ File Type Detection Failed", {"reason": "Unknown file signature"})
+            raise ValueError("Could not determine file type. Please provide a PDF or DOCX file.")
+        
+        if log_callback:
+            log_callback("File Type Detection", {"method": "content signature", "extension": file_extension})
+    
+    # Extract text based on file type
+    if file_extension == '.pdf':
+        _print_terminal_log("PDF Parsing Started", f"Extracting text from PDF file...")
+        
+        if log_callback:
+            log_callback("PDF Parser", {"status": "Starting PDF text extraction..."})
+        
+        text = extract_text_from_pdf(file_content)
+        pages = text.count('\n\n') + 1
+        
+        _print_terminal_log("PDF Extraction Complete", f"Extracted {pages} pages, {len(text)} characters")
+        
+        if log_callback:
+            log_callback("PDF Extraction Complete", {"pages_extracted": pages})
+        return text
+    elif file_extension in ['.docx', '.doc']:
+        _print_terminal_log("DOCX Parsing Started", f"Extracting text from DOCX file...")
+        
+        if log_callback:
+            log_callback("DOCX Parser", {"status": "Starting DOCX text extraction..."})
+        
+        text = extract_text_from_docx(file_content)
+        paragraphs = len([p for p in text.split('\n') if p.strip()])
+        
+        _print_terminal_log("DOCX Extraction Complete", f"Extracted {paragraphs} paragraphs, {len(text)} characters")
+        
+        if log_callback:
+            log_callback("DOCX Extraction Complete", {"paragraphs": paragraphs})
+        return text
+    else:
+        if log_callback:
+            log_callback("⚠️ Unsupported Format", {"extension": file_extension})
+        raise ValueError(f"Unsupported file format: {file_extension}. Please upload a PDF or DOCX file.")
+

utils/cv_project_matcher.py

@@ -0,0 +1,350 @@
+"""CV to Project Matching - finds best project fits based on skills."""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List, Tuple
+from agents.supabase_agent import SupabaseAgent
+
+
+def _print_terminal_log(action: str, details: str = ""):
+    """Print formatted log to terminal."""
+    timestamp = __import__('datetime').datetime.now().strftime("%H:%M:%S")
+    if details:
+        print(f"[{timestamp}] [CV MATCHER] {action} :: {details}")
+    else:
+        print(f"[{timestamp}] [CV MATCHER] {action}")
+
+
+def get_all_projects_with_skills(log_callback=None) -> List[Dict[str, Any]]:
+    """
+    Fetch all projects with their required skills from Supabase.
+    Creates a fresh agent with MCP tools to call the edge function.
+    
+    Returns:
+        List of projects with their required skills
+    """
+    _print_terminal_log("Fetching Projects", "Creating independent agent for edge function call...")
+    
+    if log_callback:
+        log_callback("📊 Fetching Projects", {"status": "Calling Supabase edge function..."})
+    
+    # Use the fallback method directly (it's proven to work)
+    return _call_edge_function_via_agent(log_callback)
+
+
+def _call_edge_function_via_agent(log_callback=None) -> List[Dict[str, Any]]:
+    """
+    Fallback: Call edge function via agent's underlying model directly.
+    This bypasses the patched run() method that has orchestrator callbacks.
+    """
+    _print_terminal_log("Using Fallback", "Calling via agent's model directly...")
+    
+    try:
+        from LLM.llm_models import supabase_model
+        import os
+        from smolagents import MCPClient
+        
+        # Create our own MCP client (fresh, no callbacks)
+        mcp_client = MCPClient(
+            {
+                "url": "https://mcp.supabase.com/mcp?project_ref=kzrdiydhjgsaxomkuijq",
+                "transport": "streamable-http",
+                "headers": {"Authorization": f"Bearer {os.getenv('SUPABASE_API_KEY')}"},
+            },
+            structured_output=True,
+        )
+        
+        _print_terminal_log("Fresh MCP Client", "Created independent MCP connection")
+        
+        # Get tools
+        tools = mcp_client.get_tools()
+        
+        # Create a minimal agent just for this call (no callbacks)
+        from smolagents import CodeAgent
+        
+        temp_agent = CodeAgent(
+            model=supabase_model,
+            tools=tools,
+            max_steps=10,  # Give it more steps
+            planning_interval=2,
+            additional_authorized_imports=['json', 'requests'],  # Add needed imports
+            instructions="Use the MCP tools available to call edge functions. Do NOT write code to make HTTP requests - use the provided tools."
+        )
+        
+        _print_terminal_log("Temp Agent Created", "Calling edge function...")
+        
+        # Call the agent with a very specific prompt focusing on SQL query
+        prompt = """
+Query the Supabase database to get all projects with their required skills.
+
+Execute a SQL query that:
+1. Selects from the 'projects' table
+2. Joins with 'project_required_skills' table
+3. Joins with 'skills' table
+4. Returns all projects with their id, name, description, status, budget, deadline
+5. Includes an array of required skills for each project
+
+Use execute_sql with the appropriate SELECT query. 
+
+The query should look like:
+SELECT 
+  p.id, p.name, p.description, p.status, p.budget, p.deadline,
+  json_agg(json_build_object('skill_id', s.id, 'skill_name', s.name)) as required_skills
+FROM projects p
+LEFT JOIN project_required_skills prs ON p.id = prs.project_id  
+LEFT JOIN skills s ON prs.skill_id = s.id
+GROUP BY p.id, p.name, p.description, p.status, p.budget, p.deadline
+
+Return the complete result.
+"""
+        result = temp_agent.run(prompt)
+        
+        _print_terminal_log("Agent Completed", "Parsing response...")
+        
+        projects = _parse_projects_from_result(result)
+        
+        _print_terminal_log("Fallback Success", f"Retrieved {len(projects)} projects")
+        
+        if log_callback:
+            log_callback("✅ Projects Retrieved (Fallback)", {"total": len(projects)})
+        
+        return projects
+        
+    except Exception as e:
+        _print_terminal_log(f"❌ Fallback ERROR: {type(e).__name__}", str(e))
+        if log_callback:
+            log_callback("❌ All Methods Failed", {"error": str(e)[:100]})
+        return []
+
+
+def _parse_projects_from_result(result: Any) -> List[Dict[str, Any]]:
+    """Parse projects from various result formats, including untrusted-data wrapped responses."""
+    import json
+    import re
+    
+    projects = []
+    
+    if isinstance(result, dict):
+        if 'projects' in result:
+            projects = result['projects']
+        elif 'data' in result:
+            projects = result['data']
+        else:
+            projects = [result] if result.get('id') else []
+    elif isinstance(result, list):
+        projects = result
+    elif isinstance(result, str):
+        # First, try to extract data from untrusted-data tags
+        untrusted_match = re.search(r'<untrusted-data[^>]*>(.*?)</untrusted-data', result, re.DOTALL)
+        if untrusted_match:
+            data_str = untrusted_match.group(1).strip()
+            _print_terminal_log("Extracted from untrusted-data tags", f"Length: {len(data_str)}")
+            
+            # The extracted content might have extra text before the JSON array
+            # Find the JSON array within it
+            json_array_match = re.search(r'(\[{.*}\])', data_str, re.DOTALL)
+            if json_array_match:
+                json_str = json_array_match.group(1)
+                _print_terminal_log("Found JSON array", f"Length: {len(json_str)}")
+                try:
+                    parsed = json.loads(json_str)
+                    if isinstance(parsed, list):
+                        projects = parsed
+                    elif isinstance(parsed, dict) and 'projects' in parsed:
+                        projects = parsed['projects']
+                except json.JSONDecodeError as e:
+                    _print_terminal_log("⚠️ JSON Parse Error", f"Could not parse JSON array: {str(e)[:100]}")
+            else:
+                # Try parsing the whole extracted content
+                try:
+                    parsed = json.loads(data_str)
+                    if isinstance(parsed, list):
+                        projects = parsed
+                    elif isinstance(parsed, dict) and 'projects' in parsed:
+                        projects = parsed['projects']
+                except json.JSONDecodeError as e:
+                    _print_terminal_log("⚠️ JSON Parse Error", f"Could not parse untrusted-data content: {str(e)[:100]}")
+        else:
+            # No untrusted-data tags, try parsing the whole string as JSON
+            try:
+                parsed = json.loads(result)
+                if isinstance(parsed, dict) and 'projects' in parsed:
+                    projects = parsed['projects']
+                elif isinstance(parsed, list):
+                    projects = parsed
+            except json.JSONDecodeError:
+                # Last resort: try to find JSON array in the string
+                json_match = re.search(r'\[{.*}\]', result, re.DOTALL)
+                if json_match:
+                    try:
+                        projects = json.loads(json_match.group(0))
+                    except json.JSONDecodeError:
+                        pass
+    
+    # Transform the data structure to match expected format
+    if projects:
+        formatted_projects = []
+        for proj in projects:
+            # Convert required_skills format if needed
+            required_skills = proj.get('required_skills', [])
+            if required_skills and isinstance(required_skills, list):
+                # Transform {skill_id, skill_name} to expected format
+                formatted_skills = []
+                for skill in required_skills:
+                    if isinstance(skill, dict):
+                        formatted_skills.append({
+                            'skill_id': skill.get('skill_id'),
+                            'skill': {
+                                'id': skill.get('skill_id'),
+                                'name': skill.get('skill_name', ''),
+                                'description': ''
+                            }
+                        })
+                proj['required_skills'] = formatted_skills
+            
+            formatted_projects.append(proj)
+        
+        projects = formatted_projects
+    
+    return projects
+
+
+def calculate_skill_match(cv_skills: List[str], required_skills: List[Dict[str, Any]]) -> Tuple[float, List[str], List[str]]:
+    """
+    Calculate match percentage between CV skills and required skills.
+    
+    Args:
+        cv_skills: List of skill names from CV
+        required_skills: List of required skill objects from project
+        
+    Returns:
+        Tuple of (match_percentage, matched_skills, missing_skills)
+    """
+    # Normalize CV skills to lowercase for comparison
+    cv_skills_lower = [skill.lower().strip() for skill in cv_skills]
+    
+    # Extract required skill names
+    required_skill_names = []
+    for req_skill in required_skills:
+        if isinstance(req_skill, dict) and 'skill' in req_skill:
+            skill_name = req_skill['skill'].get('name', '')
+        elif isinstance(req_skill, dict) and 'name' in req_skill:
+            skill_name = req_skill['name']
+        else:
+            skill_name = str(req_skill)
+        
+        if skill_name:
+            required_skill_names.append(skill_name)
+    
+    if not required_skill_names:
+        return (100.0, [], [])  # No requirements means perfect match
+    
+    required_skills_lower = [skill.lower().strip() for skill in required_skill_names]
+    
+    # Find matches
+    matched_skills = []
+    missing_skills = []
+    
+    for req_skill, req_skill_lower in zip(required_skill_names, required_skills_lower):
+        # Check for exact or partial matches
+        is_match = False
+        for cv_skill, cv_skill_lower in zip(cv_skills, cv_skills_lower):
+            if (cv_skill_lower == req_skill_lower or 
+                cv_skill_lower in req_skill_lower or 
+                req_skill_lower in cv_skill_lower):
+                is_match = True
+                if req_skill not in matched_skills:
+                    matched_skills.append(req_skill)
+                break
+        
+        if not is_match:
+            missing_skills.append(req_skill)
+    
+    # Calculate percentage
+    match_percentage = (len(matched_skills) / len(required_skill_names)) * 100
+    
+    return (match_percentage, matched_skills, missing_skills)
+
+
+def match_cv_to_projects(cv_skills_data: Dict[str, Any], log_callback=None) -> List[Dict[str, Any]]:
+    """
+    Match CV skills against all projects and rank them.
+    
+    Args:
+        cv_skills_data: Extracted skills from CV
+        log_callback: Optional callback for logging
+        
+    Returns:
+        List of projects with match data, sorted by match percentage
+    """
+    _print_terminal_log("Starting CV Matching", "Analyzing candidate fit across all projects...")
+    
+    if log_callback:
+        log_callback("🎯 Starting Project Matching", {"status": "Comparing CV skills with project requirements"})
+    
+    # Get all CV skills (technical + soft skills)
+    technical_skills = cv_skills_data.get("technical_skills", [])
+    soft_skills = cv_skills_data.get("soft_skills", [])
+    all_cv_skills = technical_skills + soft_skills
+    
+    _print_terminal_log("CV Skills Loaded", f"Technical: {len(technical_skills)}, Soft: {len(soft_skills)}, Total: {len(all_cv_skills)}")
+    
+    # Fetch all projects
+    projects = get_all_projects_with_skills(log_callback)
+    
+    if not projects:
+        _print_terminal_log("⚠️ No Projects Found", "No projects available for matching")
+        if log_callback:
+            log_callback("⚠️ No Projects", {"status": "No projects found in database"})
+        return []
+    
+    # Match each project
+    matched_projects = []
+    
+    for project in projects:
+        project_name = project.get('name', 'Unknown Project')
+        required_skills = project.get('required_skills', [])
+        
+        _print_terminal_log(f"Matching: {project_name}", f"Checking {len(required_skills)} required skills...")
+        
+        # Calculate match
+        match_percentage, matched_skills, missing_skills = calculate_skill_match(
+            all_cv_skills, 
+            required_skills
+        )
+        
+        matched_project = {
+            'project_id': project.get('id'),
+            'project_name': project_name,
+            'description': project.get('description', ''),
+            'budget': project.get('budget', 0),
+            'deadline': project.get('deadline', ''),
+            'status': project.get('status', ''),
+            'match_percentage': round(match_percentage, 1),
+            'matched_skills': matched_skills,
+            'missing_skills': missing_skills,
+            'required_skills_count': len(required_skills) if required_skills else 0,
+            'matched_skills_count': len(matched_skills),
+            'missing_skills_count': len(missing_skills),
+        }
+        
+        matched_projects.append(matched_project)
+        
+        _print_terminal_log(
+            f"Match Result: {project_name}", 
+            f"{match_percentage:.1f}% match ({len(matched_skills)}/{len(required_skills) if required_skills else 0} skills)"
+        )
+    
+    # Sort by match percentage (highest first)
+    matched_projects.sort(key=lambda x: x['match_percentage'], reverse=True)
+    
+    _print_terminal_log("✅ Matching Complete", f"Analyzed {len(matched_projects)} projects, ranked by fit")
+    
+    if log_callback:
+        log_callback("✅ Matching Complete", {
+            "total_projects": len(matched_projects),
+            "best_match": f"{matched_projects[0]['project_name']} ({matched_projects[0]['match_percentage']}%)" if matched_projects else "None"
+        })
+    
+    return matched_projects
+

utils/cv_training_cost.py

@@ -0,0 +1,186 @@
+"""Training cost estimation for CV project matching."""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List
+from smolagents import CodeAgent
+from LLM.llm_models import websearch_model
+from agents.websearch_agent import WebSearchAgent
+
+
+def _print_terminal_log(action: str, details: str = ""):
+    """Print formatted log to terminal."""
+    timestamp = __import__('datetime').datetime.now().strftime("%H:%M:%S")
+    if details:
+        print(f"[{timestamp}] [TRAINING COST] {action} :: {details}")
+    else:
+        print(f"[{timestamp}] [TRAINING COST] {action}")
+
+
+def estimate_training_costs_for_skills(
+    missing_skills: List[str], 
+    project_name: str,
+    log_callback=None
+) -> List[Dict[str, Any]]:
+    """
+    Estimate training costs for missing skills using websearch.
+    Uses the same logic as project analysis training plan generation.
+    
+    Args:
+        missing_skills: List of skill names that candidate is missing
+        project_name: Name of the project (for context)
+        log_callback: Optional callback for logging
+        
+    Returns:
+        List of training plans with costs
+    """
+    if not missing_skills:
+        return []
+    
+    _print_terminal_log(
+        f"Estimating Training Costs",
+        f"Searching for {len(missing_skills)} missing skills for {project_name}"
+    )
+    
+    if log_callback:
+        log_callback("💰 Training Cost Analysis", {
+            "project": project_name,
+            "missing_skills": len(missing_skills)
+        })
+    
+    training_plans = []
+    
+    try:
+        # Don't use WebSearchAgent - it has the same singleton callback issues
+        # Instead, use default estimates (fast and reliable)
+        _print_terminal_log("Using Default Estimates", "Skipping websearch to avoid callback issues")
+        
+        # Use default estimates for all skills (reliable and fast)
+        for skill in missing_skills[:10]:  # Limit to 10 skills
+            # Extract skill name from dict if needed
+            skill_name = skill.get('skill_name', skill) if isinstance(skill, dict) else skill
+            
+            _print_terminal_log(f"Estimating: {skill_name}", "Using default estimates")
+            
+            if log_callback:
+                log_callback(f"💰 Estimating: {skill_name}", {"status": "Calculating training cost"})
+            
+            training_plans.append({
+                "skill": skill_name,
+                "title": f"{skill_name} - Professional Training",
+                "cost": estimate_default_cost(skill_name),
+                "duration_hours": estimate_default_duration(skill_name),
+                "provider": "Estimated",
+                "source": "default"
+            })
+        
+        _print_terminal_log("✅ Cost Estimation Complete", f"Generated {len(training_plans)} training plans")
+        
+        if log_callback:
+            total_cost = sum(plan['cost'] for plan in training_plans)
+            total_hours = sum(plan['duration_hours'] for plan in training_plans)
+            log_callback("✅ Training Costs Calculated", {
+                "total_plans": len(training_plans),
+                "total_cost": f"${total_cost:,.2f}",
+                "total_hours": total_hours
+            })
+        
+        return training_plans
+        
+    except Exception as e:
+        _print_terminal_log(f"❌ ERROR: {type(e).__name__}", str(e))
+        if log_callback:
+            log_callback("❌ Training Cost Error", {"error": str(e)})
+        
+        # Return default estimates for all skills
+        # Return default estimates
+        result = []
+        for skill in missing_skills[:10]:
+            skill_name = skill.get('skill_name', skill) if isinstance(skill, dict) else skill
+            result.append({
+                "skill": skill_name,
+                "title": f"{skill_name} - Professional Training",
+                "cost": estimate_default_cost(skill_name),
+                "duration_hours": estimate_default_duration(skill_name),
+                "provider": "Estimated",
+                "source": "default"
+            })
+        return result
+
+
+def estimate_default_cost(skill: str) -> float:
+    """Estimate default training cost based on skill complexity."""
+    skill_lower = skill.lower()
+    
+    # High-complexity skills
+    if any(term in skill_lower for term in ['architect', 'senior', 'lead', 'advanced', 'expert']):
+        return 500.0
+    
+    # Medium-complexity technical skills
+    elif any(term in skill_lower for term in ['programming', 'development', 'engineering', 'framework', 'platform']):
+        return 200.0
+    
+    # Soft skills and basic technical skills
+    elif any(term in skill_lower for term in ['communication', 'management', 'leadership', 'teamwork', 'basic']):
+        return 100.0
+    
+    # Default for other skills
+    else:
+        return 150.0
+
+
+def estimate_default_duration(skill: str) -> int:
+    """Estimate default training duration based on skill complexity."""
+    skill_lower = skill.lower()
+    
+    # High-complexity skills
+    if any(term in skill_lower for term in ['architect', 'senior', 'lead', 'advanced', 'expert']):
+        return 40
+    
+    # Medium-complexity technical skills
+    elif any(term in skill_lower for term in ['programming', 'development', 'engineering', 'framework', 'platform']):
+        return 20
+    
+    # Soft skills and basic technical skills
+    elif any(term in skill_lower for term in ['communication', 'management', 'leadership', 'teamwork', 'basic']):
+        return 8
+    
+    # Default for other skills
+    else:
+        return 16
+
+
+def calculate_total_training_cost(matched_projects: List[Dict[str, Any]]) -> Dict[str, Any]:
+    """
+    Calculate total training costs across all matched projects.
+    
+    Args:
+        matched_projects: List of matched projects with training plans
+        
+    Returns:
+        Dictionary with cost statistics
+    """
+    if not matched_projects:
+        return {
+            "total_projects": 0,
+            "total_cost": 0.0,
+            "total_hours": 0,
+            "average_cost_per_project": 0.0
+        }
+    
+    total_cost = 0.0
+    total_hours = 0
+    
+    for project in matched_projects:
+        training_plans = project.get('training_plans', [])
+        for plan in training_plans:
+            total_cost += plan.get('cost', 0)
+            total_hours += plan.get('duration_hours', 0)
+    
+    return {
+        "total_projects": len(matched_projects),
+        "total_cost": total_cost,
+        "total_hours": total_hours,
+        "average_cost_per_project": total_cost / len(matched_projects) if matched_projects else 0.0
+    }
+

utils/skill_extractor.py

@@ -0,0 +1,279 @@
+"""Skill extraction from CV text using LLM."""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List
+
+from LLM.llm_models import cv_analyzer_model  # Using CV-specific model (same as orchestrator)
+import json
+import re
+
+
+def _print_terminal_log(action: str, details: str = ""):
+    """Print formatted log to terminal."""
+    timestamp = __import__('datetime').datetime.now().strftime("%H:%M:%S")
+    if details:
+        print(f"[{timestamp}] [CV ANALYZER] {action} :: {details}")
+    else:
+        print(f"[{timestamp}] [CV ANALYZER] {action}")
+
+
+def extract_skills_from_cv_text(cv_text: str, log_callback=None) -> Dict[str, Any]:
+    """
+    Extract skills and relevant information from CV text using LLM.
+    
+    Args:
+        cv_text: The extracted text content from a CV
+    
+    Returns:
+        Dictionary containing extracted skills and candidate information
+    """
+    
+    prompt = f"""Analyze the following CV/Resume text and extract ALL relevant information in a structured format.
+
+CV TEXT:
+{cv_text}
+
+Please extract and organize the following information:
+
+1. TECHNICAL SKILLS: Programming languages, frameworks, tools, technologies
+2. SOFT SKILLS: Communication, leadership, teamwork, problem-solving, etc.
+3. PROFESSIONAL EXPERIENCE: Years of experience, job titles, companies
+4. EDUCATION: Degrees, certifications, institutions
+5. DOMAIN EXPERTISE: Industries, specific domains (e.g., Finance, Healthcare, AI/ML)
+
+Return your analysis in the following JSON-like structure:
+{{
+    "technical_skills": ["skill1", "skill2", ...],
+    "soft_skills": ["skill1", "skill2", ...],
+    "experience_years": <number or "unknown">,
+    "recent_roles": ["role1", "role2", ...],
+    "education": ["degree1", "degree2", ...],
+    "certifications": ["cert1", "cert2", ...],
+    "domain_expertise": ["domain1", "domain2", ...],
+    "summary": "A brief 2-3 sentence summary of the candidate's profile"
+}}
+
+Be thorough and extract as many relevant skills as possible. If information is not available, use empty arrays or "unknown"."""
+
+    try:
+        _print_terminal_log("Starting AI skill extraction from CV text")
+        
+        if log_callback:
+            log_callback("AI Skill Extraction", {"status": "Initializing LLM model..."})
+        
+        # Use the CV analyzer model (same provider as orchestrator - HF/Gemini)
+        model = cv_analyzer_model
+        
+        _print_terminal_log("LLM Initialized", f"Model ready, CV length: {len(cv_text)} chars")
+        
+        if log_callback:
+            log_callback("AI Analysis", {"status": "Sending CV to AI for analysis", "cv_length": len(cv_text)})
+        
+        messages = [
+            {
+                "role": "system",
+                "content": "You are an expert HR analyst specializing in CV/Resume analysis and skill extraction. Extract information accurately and comprehensively."
+            },
+            {
+                "role": "user",
+                "content": prompt
+            }
+        ]
+        
+        if log_callback:
+            log_callback("LLM Request", {"message_count": len(messages), "model": "cv_analyzer_model"})
+        
+        _print_terminal_log("Sending request to AI", "Waiting for skill extraction...")
+        
+        response = model.generate(messages=messages)
+        
+        # Handle ChatMessage object - convert to string
+        if hasattr(response, 'content'):
+            response_text = response.content
+        else:
+            response_text = str(response)
+        
+        _print_terminal_log("AI Response Received", f"Response length: {len(response_text) if response_text else 0} chars")
+        
+        if log_callback:
+            log_callback("AI Response Received", {"response_length": len(response_text) if response_text else 0})
+        
+        # Extract JSON from response (handle markdown code blocks)
+        
+        if log_callback:
+            log_callback("Parsing AI Response", {"status": "Extracting structured data from AI response"})
+        
+        json_match = re.search(r'\{[\s\S]*\}', response_text)
+        
+        if json_match:
+            if log_callback:
+                log_callback("JSON Extraction", {"status": "Found JSON in response, parsing..."})
+            
+            _print_terminal_log("Parsing JSON response", "Extracting structured skill data...")
+            
+            skills_data = json.loads(json_match.group())
+            
+            tech_count = len(skills_data.get("technical_skills", []))
+            soft_count = len(skills_data.get("soft_skills", []))
+            
+            _print_terminal_log("Skills Extracted Successfully", 
+                              f"Technical: {tech_count}, Soft: {soft_count}, Total: {tech_count + soft_count}")
+            
+            if log_callback:
+                log_callback("Skills Parsed Successfully", {
+                    "technical_skills": tech_count,
+                    "soft_skills": soft_count,
+                    "total_skills": tech_count + soft_count
+                })
+        else:
+            if log_callback:
+                log_callback("JSON Extraction Failed", {"status": "No JSON found, using fallback structure"})
+            # Fallback: return a basic structure with the raw response
+            skills_data = {
+                "technical_skills": [],
+                "soft_skills": [],
+                "experience_years": "unknown",
+                "recent_roles": [],
+                "education": [],
+                "certifications": [],
+                "domain_expertise": [],
+                "summary": response_text[:500]  # First 500 chars
+            }
+        
+        _print_terminal_log("✅ CV Analysis Complete", "All skills successfully extracted and structured")
+        
+        if log_callback:
+            log_callback("✅ Extraction Complete", {"status": "CV processing finished successfully"})
+        
+        return skills_data
+        
+    except Exception as e:
+        error_msg = str(e)
+        
+        _print_terminal_log(f"❌ ERROR: {type(e).__name__}", error_msg)
+        
+        if log_callback:
+            log_callback("❌ AI Extraction Error", {"error": error_msg, "type": type(e).__name__})
+        
+        # Return error information
+        return {
+            "error": error_msg,
+            "technical_skills": [],
+            "soft_skills": [],
+            "experience_years": "unknown",
+            "recent_roles": [],
+            "education": [],
+            "certifications": [],
+            "domain_expertise": [],
+            "summary": f"Failed to extract skills: {error_msg}"
+        }
+
+
+def format_skills_for_display(skills_data: Dict[str, Any]) -> str:
+    """
+    Format extracted skills data into HTML for display in Gradio.
+    
+    Args:
+        skills_data: Dictionary containing extracted skills
+    
+    Returns:
+        HTML string for display
+    """
+    
+    if "error" in skills_data:
+        return f"""
+        <div style="padding: 20px; background: var(--bg-card); border: 1px solid var(--arc-red); border-radius: 4px;">
+            <h3 style="color: var(--arc-red); margin-top: 0;">⚠️ Error Extracting Skills</h3>
+            <p style="color: var(--text-dim);">{skills_data.get('summary', 'Unknown error')}</p>
+        </div>
+        """
+    
+    html_parts = [
+        '<div style="padding: 24px; background: var(--bg-card); border: 1px solid var(--border-bright); border-radius: 4px; margin-top: 20px;">',
+        '<h2 style="color: var(--arc-orange); margin-top: 0; display: flex; align-items: center; gap: 12px;">',
+        '<span style="font-size: 32px;">📄</span> CV ANALYSIS COMPLETE',
+        '</h2>',
+    ]
+    
+    # Summary
+    if skills_data.get("summary"):
+        html_parts.append(f'<div style="background: var(--bg-panel); padding: 16px; border-left: 4px solid var(--arc-cyan); margin-bottom: 24px;">')
+        html_parts.append(f'<p style="color: var(--text-main); margin: 0; line-height: 1.6;">{skills_data["summary"]}</p>')
+        html_parts.append('</div>')
+    
+    # Technical Skills
+    if skills_data.get("technical_skills"):
+        html_parts.append('<div style="margin-bottom: 20px;">')
+        html_parts.append('<h3 style="color: var(--arc-yellow); margin-bottom: 12px;">💻 TECHNICAL SKILLS</h3>')
+        html_parts.append('<div style="display: flex; flex-wrap: wrap; gap: 8px;">')
+        for skill in skills_data["technical_skills"]:
+            html_parts.append(
+                f'<span style="background: var(--bg-panel); border: 1px solid var(--border-dim); '
+                f'padding: 6px 12px; border-radius: 4px; color: var(--arc-green); font-weight: 600; '
+                f'font-size: 13px;">{skill}</span>'
+            )
+        html_parts.append('</div></div>')
+    
+    # Soft Skills
+    if skills_data.get("soft_skills"):
+        html_parts.append('<div style="margin-bottom: 20px;">')
+        html_parts.append('<h3 style="color: var(--arc-yellow); margin-bottom: 12px;">🤝 SOFT SKILLS</h3>')
+        html_parts.append('<div style="display: flex; flex-wrap: wrap; gap: 8px;">')
+        for skill in skills_data["soft_skills"]:
+            html_parts.append(
+                f'<span style="background: var(--bg-panel); border: 1px solid var(--border-dim); '
+                f'padding: 6px 12px; border-radius: 4px; color: var(--arc-cyan); font-weight: 600; '
+                f'font-size: 13px;">{skill}</span>'
+            )
+        html_parts.append('</div></div>')
+    
+    # Experience & Roles
+    if skills_data.get("experience_years") or skills_data.get("recent_roles"):
+        html_parts.append('<div style="margin-bottom: 20px;">')
+        html_parts.append('<h3 style="color: var(--arc-yellow); margin-bottom: 12px;">💼 EXPERIENCE</h3>')
+        if skills_data.get("experience_years"):
+            html_parts.append(f'<p style="color: var(--text-main); margin: 8px 0;"><strong>Years:</strong> {skills_data["experience_years"]}</p>')
+        if skills_data.get("recent_roles"):
+            html_parts.append('<p style="color: var(--text-main); margin: 8px 0;"><strong>Recent Roles:</strong></p>')
+            html_parts.append('<ul style="color: var(--text-dim); margin-top: 4px;">')
+            for role in skills_data["recent_roles"]:
+                html_parts.append(f'<li>{role}</li>')
+            html_parts.append('</ul>')
+        html_parts.append('</div>')
+    
+    # Education
+    if skills_data.get("education") or skills_data.get("certifications"):
+        html_parts.append('<div style="margin-bottom: 20px;">')
+        html_parts.append('<h3 style="color: var(--arc-yellow); margin-bottom: 12px;">🎓 EDUCATION & CERTIFICATIONS</h3>')
+        if skills_data.get("education"):
+            html_parts.append('<p style="color: var(--text-main); margin: 8px 0;"><strong>Education:</strong></p>')
+            html_parts.append('<ul style="color: var(--text-dim); margin-top: 4px;">')
+            for edu in skills_data["education"]:
+                html_parts.append(f'<li>{edu}</li>')
+            html_parts.append('</ul>')
+        if skills_data.get("certifications"):
+            html_parts.append('<p style="color: var(--text-main); margin: 8px 0;"><strong>Certifications:</strong></p>')
+            html_parts.append('<ul style="color: var(--text-dim); margin-top: 4px;">')
+            for cert in skills_data["certifications"]:
+                html_parts.append(f'<li>{cert}</li>')
+            html_parts.append('</ul>')
+        html_parts.append('</div>')
+    
+    # Domain Expertise
+    if skills_data.get("domain_expertise"):
+        html_parts.append('<div style="margin-bottom: 20px;">')
+        html_parts.append('<h3 style="color: var(--arc-yellow); margin-bottom: 12px;">🎯 DOMAIN EXPERTISE</h3>')
+        html_parts.append('<div style="display: flex; flex-wrap: wrap; gap: 8px;">')
+        for domain in skills_data["domain_expertise"]:
+            html_parts.append(
+                f'<span style="background: var(--bg-panel); border: 1px solid var(--border-dim); '
+                f'padding: 6px 12px; border-radius: 4px; color: var(--arc-orange); font-weight: 600; '
+                f'font-size: 13px;">{domain}</span>'
+            )
+        html_parts.append('</div></div>')
+    
+    html_parts.append('</div>')
+    
+    return ''.join(html_parts)
+

uv.lock

@@ -441,7 +441,11 @@ dependencies = [
     { name = "elevenlabs" },
     { name = "fastmcp" },
     { name = "gradio" },
+    { name = "pdfplumber" },
     { name = "pydantic" },
+    { name = "pypdf" },
+    { name = "python-docx" },
+    { name = "python-multipart" },
     { name = "repr" },
     { name = "smolagents", extra = ["mcp", "openai"] },
     { name = "supabase" },
@@ -454,7 +458,11 @@ requires-dist = [
     { name = "elevenlabs", specifier = ">=2.24.0" },
     { name = "fastmcp", specifier = ">=2.13.1" },
     { name = "gradio", specifier = "==6.0.0.dev1" },
+    { name = "pdfplumber", specifier = ">=0.11.0" },
     { name = "pydantic", specifier = ">=2.0.0" },
+    { name = "pypdf", specifier = ">=4.0.0" },
+    { name = "python-docx", specifier = ">=1.0.0" },
+    { name = "python-multipart", specifier = ">=0.0.6" },
     { name = "repr", specifier = ">=0.3.1" },
     { name = "smolagents", extras = ["mcp", "openai"] },
     { name = "supabase", specifier = ">=2.0.0" },
@@ -1421,6 +1429,33 @@ wheels = [
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 ]
 
+[[package]]
+name = "pdfminer-six"
+version = "20251107"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "charset-normalizer" },
+    { name = "cryptography" },
+]
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+]
+
+[[package]]
+name = "pdfplumber"
+version = "0.11.8"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pdfminer-six" },
+    { name = "pillow" },
+    { name = "pypdfium2" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/09/d8/cb9fda4261ce389656bec0bb0bdde905df109ad97f7ae387747ded070e8c/pdfplumber-0.11.8.tar.gz", hash = "sha256:db29b04bc8bb62f39dd444533bcf2e0ba33584bd24f5a54644f3ba30f4f22d31", size = 102724, upload-time = "2025-11-08T20:52:01.955Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/12/28/3958ed81a9be317610ab73df32f1968076751d651c84dff1bcb45b7c6c0e/pdfplumber-0.11.8-py3-none-any.whl", hash = "sha256:7dda117b8ed21bca9c8e7d7808fee2439f93c8bd6ea45989bfb1aead6dc3cad3", size = 60043, upload-time = "2025-11-08T20:52:00.652Z" },
+]
+
 [[package]]
 name = "pillow"
 version = "11.3.0"
@@ -1726,6 +1761,35 @@ crypto = [
     { name = "cryptography" },
 ]
 
+[[package]]
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+version = "6.3.0"
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+]
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+[[package]]
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