Job analysis in flight

frontend/src/pages/JobAnalysisPage.tsx

@@ -39,6 +39,8 @@ import { useNavigate } from 'react-router-dom';
 import { BackstoryPageProps } from 'components/BackstoryTab';
 import { useAuth } from 'hooks/AuthContext';
 import { useSelectedCandidate } from 'hooks/GlobalContext';
+import { CandidateInfo } from 'components/CandidateInfo';
+import { ComingSoon } from 'components/ui/ComingSoon';
 
 // Main component
 const JobAnalysisPage: React.FC<BackstoryPageProps> = (props: BackstoryPageProps) => {
@@ -93,32 +95,14 @@ const JobAnalysisPage: React.FC<BackstoryPageProps> = (props: BackstoryPageProps
   }, [selectedCandidate, activeStep]);
 
   // Steps in our process
-  const steps = selectedCandidate === null ? [
+  const steps = [
-    { index: 0, label: 'Select Candidate', icon: <PersonIcon /> },
     { index: 1, label: 'Job Description', icon: <WorkIcon /> },
-    { index: 2, label: 'View Analysis', icon: <AssessmentIcon /> }
+    { index: 2, label: 'AI Analysis', icon: <WorkIcon /> },
-  ] : [
+    { index: 3, label: 'Generated Resume', icon: <AssessmentIcon /> }
-    { index: 1, label: 'Job Description', icon: <WorkIcon /> },
-    { index: 2, label: 'View Analysis', icon: <AssessmentIcon /> }
   ];
-
+  if (!selectedCandidate) {
-  // Mock handlers for our analysis APIs
+    steps.unshift({ index: 0, label: 'Select Candidate', icon: <PersonIcon /> })
-  const fetchRequirements = async (): Promise<string[]> => {
+  }
-    // Simulates extracting requirements from the job description
-    await new Promise(resolve => setTimeout(resolve, 2000));
-    
-    // This would normally parse the job description to extract requirements
-    const mockRequirements = [
-      "5+ years of React development experience",
-      "Strong TypeScript skills",
-      "Experience with RESTful APIs",
-      "Knowledge of state management solutions (Redux, Context API)",
-      "Experience with CI/CD pipelines",
-      "Cloud platform experience (AWS, Azure, GCP)"
-    ];
-    
-    return mockRequirements;
-  };
 
   const fetchMatchForRequirement = async (requirement: string): Promise<any> => {
     // Create different mock responses based on the requirement
@@ -245,10 +229,12 @@ const JobAnalysisPage: React.FC<BackstoryPageProps> = (props: BackstoryPageProps
       return;
     }
     
-    if (activeStep === 1 && (/*(extraInfo && !jobTitle) || */!jobDescription)) {
+    if (activeStep === 1) {
-      setError('Please provide both job title and description before continuing.');
+      if ((/*(extraInfo && !jobTitle) || */!jobDescription)) {
+        setError('Please provide job description before continuing.');
         return;
       }
+    }
     
     if (activeStep === 2) {
       setAnalysisStarted(true);
@@ -433,15 +419,19 @@ const JobAnalysisPage: React.FC<BackstoryPageProps> = (props: BackstoryPageProps
     <Box sx={{ mt: 3 }}>
       {selectedCandidate && (
         <JobMatchAnalysis
-          jobTitle={jobTitle}
+          job={{ title: jobTitle, description: jobDescription }}
-          candidateName={selectedCandidate.fullName}
+          candidate={selectedCandidate}
-          fetchRequirements={fetchRequirements}
-          fetchMatchForRequirement={fetchMatchForRequirement}
         />
       )}
     </Box>
   );
 
+  const renderResume = () => (
+    <Box sx={{ mt: 3 }}>
+      {selectedCandidate && <ComingSoon>Resume Builder</ComingSoon>}
+    </Box>
+  );
+
   // If no user is logged in, show message
   if (!user) {
     return (
@@ -464,6 +454,7 @@ const JobAnalysisPage: React.FC<BackstoryPageProps> = (props: BackstoryPageProps
         <Typography variant="h4" component="h1" gutterBottom>
           Candidate Analysis
         </Typography>
+        {selectedCandidate && <CandidateInfo variant="small" candidate={selectedCandidate} />}
         <Typography variant="subtitle1" color="text.secondary" gutterBottom>
           Match candidates to job requirements with AI-powered analysis
         </Typography>
@@ -496,6 +487,7 @@ const JobAnalysisPage: React.FC<BackstoryPageProps> = (props: BackstoryPageProps
       {activeStep === 0 && renderCandidateSelection()}
       {activeStep === 1 && renderJobDescription()}
       {activeStep === 2 && renderAnalysis()}
+      {activeStep === 3 && renderResume()}
       
       <Box sx={{ display: 'flex', flexDirection: 'row', pt: 2 }}>
         <Button

frontend/src/types/types.ts

@@ -1,6 +1,6 @@
 // Generated TypeScript types from Pydantic models
 // Source: src/backend/models.py
-// Generated on: 2025-06-03T18:51:32.304683
+// Generated on: 2025-06-03T23:59:28.355326
 // DO NOT EDIT MANUALLY - This file is auto-generated
 
 // ============================
@@ -13,13 +13,13 @@ export type ActivityType = "login" | "search" | "view_job" | "apply_job" | "mess
 
 export type ApplicationStatus = "applied" | "reviewing" | "interview" | "offer" | "rejected" | "accepted" | "withdrawn";
 
-export type ChatContextType = "job_search" | "candidate_chat" | "interview_prep" | "resume_review" | "general" | "generate_persona" | "generate_profile" | "generate_image" | "rag_search";
+export type ChatContextType = "job_search" | "job_requirements" | "candidate_chat" | "interview_prep" | "resume_review" | "general" | "generate_persona" | "generate_profile" | "generate_image" | "rag_search";
 
 export type ChatMessageType = "error" | "generating" | "info" | "preparing" | "processing" | "heartbeat" | "response" | "searching" | "rag_result" | "system" | "thinking" | "tooling" | "user";
 
 export type ChatSenderType = "user" | "assistant" | "system";
 
-export type ChatStatusType = "initializing" | "streaming" | "done" | "error";
+export type ChatStatusType = "initializing" | "streaming" | "status" | "done" | "error";
 
 export type ColorBlindMode = "protanopia" | "deuteranopia" | "tritanopia" | "none";
 
@@ -272,7 +272,7 @@ export interface Certification {
 }
 
 export interface ChatContext {
-  type: "job_search" | "candidate_chat" | "interview_prep" | "resume_review" | "general" | "generate_persona" | "generate_profile" | "generate_image" | "rag_search";
+  type: "job_search" | "job_requirements" | "candidate_chat" | "interview_prep" | "resume_review" | "general" | "generate_persona" | "generate_profile" | "generate_image" | "rag_search";
   relatedEntityId?: string;
   relatedEntityType?: "job" | "candidate" | "employer";
   additionalContext?: Record<string, any>;
@@ -282,10 +282,10 @@ export interface ChatMessage {
   id?: string;
   sessionId: string;
   senderId?: string;
-  status: "initializing" | "streaming" | "done" | "error";
+  status: "initializing" | "streaming" | "status" | "done" | "error";
   type: "error" | "generating" | "info" | "preparing" | "processing" | "heartbeat" | "response" | "searching" | "rag_result" | "system" | "thinking" | "tooling" | "user";
   sender: "user" | "assistant" | "system";
-  timestamp: Date;
+  timestamp?: Date;
   tunables?: Tunables;
   content: string;
   metadata?: ChatMessageMetaData;
@@ -295,16 +295,16 @@ export interface ChatMessageBase {
   id?: string;
   sessionId: string;
   senderId?: string;
-  status: "initializing" | "streaming" | "done" | "error";
+  status: "initializing" | "streaming" | "status" | "done" | "error";
   type: "error" | "generating" | "info" | "preparing" | "processing" | "heartbeat" | "response" | "searching" | "rag_result" | "system" | "thinking" | "tooling" | "user";
   sender: "user" | "assistant" | "system";
-  timestamp: Date;
+  timestamp?: Date;
   tunables?: Tunables;
   content: string;
 }
 
 export interface ChatMessageMetaData {
-  model: "qwen2.5";
+  model: "qwen2.5" | "flux-schnell";
   temperature: number;
   maxTokens: number;
   topP: number;
@@ -326,10 +326,10 @@ export interface ChatMessageRagSearch {
   id?: string;
   sessionId: string;
   senderId?: string;
-  status: "done";
+  status: "initializing" | "streaming" | "status" | "done" | "error";
-  type: "rag_result";
+  type: "error" | "generating" | "info" | "preparing" | "processing" | "heartbeat" | "response" | "searching" | "rag_result" | "system" | "thinking" | "tooling" | "user";
-  sender: "user";
+  sender: "user" | "assistant" | "system";
-  timestamp: Date;
+  timestamp?: Date;
   tunables?: Tunables;
   content: string;
   dimensions: number;
@@ -339,10 +339,10 @@ export interface ChatMessageUser {
   id?: string;
   sessionId: string;
   senderId?: string;
-  status: "done";
+  status: "initializing" | "streaming" | "status" | "done" | "error";
-  type: "user";
+  type: "error" | "generating" | "info" | "preparing" | "processing" | "heartbeat" | "response" | "searching" | "rag_result" | "system" | "thinking" | "tooling" | "user";
-  sender: "user";
+  sender: "user" | "assistant" | "system";
-  timestamp: Date;
+  timestamp?: Date;
   tunables?: Tunables;
   content: string;
 }
@@ -857,6 +857,233 @@ export interface WorkExperience {
   achievements?: Array<string>;
 }
 
+// ============================
+// Default Objects
+// ============================
+
+// These objects contain the default values from your Pydantic models
+// Use them to initialize objects with sensible defaults:
+// const message: ChatMessage = { ...DefaultChatMessage, sessionId: '123', content: 'Hello' };
+
+/**
+ * Default values for BaseUser
+ * Fields with defaults: isAdmin
+ */
+export const DefaultBaseUser: Partial<BaseUser> = {
+  isAdmin: False
+};
+
+/**
+ * Default values for BaseUserWithType
+ * Fields with defaults: isAdmin
+ */
+export const DefaultBaseUserWithType: Partial<BaseUserWithType> = {
+  isAdmin: False
+};
+
+/**
+ * Default values for Candidate
+ * Fields with defaults: isAdmin, userType, ragContentSize
+ */
+export const DefaultCandidate: Partial<Candidate> = {
+  isAdmin: False,
+  userType: "candidate",
+  ragContentSize: 0
+};
+
+/**
+ * Default values for CandidateAI
+ * Fields with defaults: isAdmin, userType, ragContentSize, isAI
+ */
+export const DefaultCandidateAI: Partial<CandidateAI> = {
+  isAdmin: False,
+  userType: "candidate",
+  ragContentSize: 0,
+  isAI: True
+};
+
+/**
+ * Default values for ChatContext
+ * Fields with defaults: additionalContext
+ */
+export const DefaultChatContext: Partial<ChatContext> = {
+  additionalContext: {}
+};
+
+/**
+ * Default values for ChatMessage
+ * Fields with defaults: status, type, sender, content
+ */
+export const DefaultChatMessage: Partial<ChatMessage> = {
+  status: "initializing",
+  type: "preparing",
+  sender: "system",
+  content: ""
+};
+
+/**
+ * Default values for ChatMessageBase
+ * Fields with defaults: status, type, sender, content
+ */
+export const DefaultChatMessageBase: Partial<ChatMessageBase> = {
+  status: "initializing",
+  type: "preparing",
+  sender: "system",
+  content: ""
+};
+
+/**
+ * Default values for ChatMessageMetaData
+ * Fields with defaults: model, temperature, maxTokens, topP, evalCount, evalDuration, promptEvalCount, promptEvalDuration
+ */
+export const DefaultChatMessageMetaData: Partial<ChatMessageMetaData> = {
+  model: "qwen2.5",
+  temperature: 0.7,
+  maxTokens: 8092,
+  topP: 1,
+  evalCount: 0,
+  evalDuration: 0,
+  promptEvalCount: 0,
+  promptEvalDuration: 0
+};
+
+/**
+ * Default values for ChatMessageRagSearch
+ * Fields with defaults: status, type, sender, content, dimensions
+ */
+export const DefaultChatMessageRagSearch: Partial<ChatMessageRagSearch> = {
+  status: "done",
+  type: "rag_result",
+  sender: "user",
+  content: "",
+  dimensions: 3
+};
+
+/**
+ * Default values for ChatMessageUser
+ * Fields with defaults: status, type, sender, content
+ */
+export const DefaultChatMessageUser: Partial<ChatMessageUser> = {
+  status: "done",
+  type: "user",
+  sender: "user",
+  content: ""
+};
+
+/**
+ * Default values for ChatOptions
+ * Fields with defaults: seed, temperature
+ */
+export const DefaultChatOptions: Partial<ChatOptions> = {
+  seed: 8911,
+  temperature: 0.7
+};
+
+/**
+ * Default values for ChatSession
+ * Fields with defaults: isArchived
+ */
+export const DefaultChatSession: Partial<ChatSession> = {
+  isArchived: False
+};
+
+/**
+ * Default values for ChromaDBGetResponse
+ * Fields with defaults: ids, embeddings, documents, metadatas, distances, name, size, dimensions, query
+ */
+export const DefaultChromaDBGetResponse: Partial<ChromaDBGetResponse> = {
+  ids: [],
+  embeddings: [],
+  documents: [],
+  metadatas: [],
+  distances: [],
+  name: "",
+  size: 0,
+  dimensions: 3,
+  query: ""
+};
+
+/**
+ * Default values for Document
+ * Fields with defaults: includeInRAG, ragChunks
+ */
+export const DefaultDocument: Partial<Document> = {
+  includeInRAG: True,
+  ragChunks: 0
+};
+
+/**
+ * Default values for Employer
+ * Fields with defaults: isAdmin, userType
+ */
+export const DefaultEmployer: Partial<Employer> = {
+  isAdmin: False,
+  userType: "employer"
+};
+
+/**
+ * Default values for Job
+ * Fields with defaults: views, applicationCount
+ */
+export const DefaultJob: Partial<Job> = {
+  views: 0,
+  applicationCount: 0
+};
+
+/**
+ * Default values for LLMMessage
+ * Fields with defaults: role, content, toolCalls
+ */
+export const DefaultLLMMessage: Partial<LLMMessage> = {
+  role: "",
+  content: "",
+  toolCalls: {}
+};
+
+/**
+ * Default values for MFAVerifyRequest
+ * Fields with defaults: rememberDevice
+ */
+export const DefaultMFAVerifyRequest: Partial<MFAVerifyRequest> = {
+  rememberDevice: False
+};
+
+/**
+ * Default values for PaginatedRequest
+ * Fields with defaults: page, limit
+ */
+export const DefaultPaginatedRequest: Partial<PaginatedRequest> = {
+  page: 1,
+  limit: 20
+};
+
+/**
+ * Default values for RagEntry
+ * Fields with defaults: description, enabled
+ */
+export const DefaultRagEntry: Partial<RagEntry> = {
+  description: "",
+  enabled: True
+};
+
+/**
+ * Default values for SearchQuery
+ * Fields with defaults: page, limit
+ */
+export const DefaultSearchQuery: Partial<SearchQuery> = {
+  page: 1,
+  limit: 20
+};
+
+/**
+ * Default values for Tunables
+ * Fields with defaults: enableRAG, enableTools, enableContext
+ */
+export const DefaultTunables: Partial<Tunables> = {
+  enableRAG: True,
+  enableTools: True,
+  enableContext: True
+};
 // ============================
 // Date Conversion Functions
 // ============================
@@ -1017,7 +1244,7 @@ export function convertChatMessageFromApi(data: any): ChatMessage {
   return {
     ...data,
     // Convert timestamp from ISO string to Date
-    timestamp: new Date(data.timestamp),
+    timestamp: data.timestamp ? new Date(data.timestamp) : undefined,
   };
 }
 /**
@@ -1030,7 +1257,7 @@ export function convertChatMessageBaseFromApi(data: any): ChatMessageBase {
   return {
     ...data,
     // Convert timestamp from ISO string to Date
-    timestamp: new Date(data.timestamp),
+    timestamp: data.timestamp ? new Date(data.timestamp) : undefined,
   };
 }
 /**
@@ -1043,7 +1270,7 @@ export function convertChatMessageRagSearchFromApi(data: any): ChatMessageRagSea
   return {
     ...data,
     // Convert timestamp from ISO string to Date
-    timestamp: new Date(data.timestamp),
+    timestamp: data.timestamp ? new Date(data.timestamp) : undefined,
   };
 }
 /**
@@ -1056,7 +1283,7 @@ export function convertChatMessageUserFromApi(data: any): ChatMessageUser {
   return {
     ...data,
     // Convert timestamp from ISO string to Date
-    timestamp: new Date(data.timestamp),
+    timestamp: data.timestamp ? new Date(data.timestamp) : undefined,
   };
 }
 /**

src/backend/generate_types.py

@@ -138,10 +138,14 @@ def is_date_type(python_type: Any) -> bool:
     
     return False
 
-def get_default_enum_value(field_info: Any, debug: bool = False) -> Optional[Any]:
+def get_field_default_value(field_info: Any, debug: bool = False) -> tuple[bool, Any]:
-    """Extract the specific enum value from a field's default, if it exists"""
+    """Extract the default value from a field, if it exists
+    
+    Returns:
+        tuple: (has_default, default_value)
+    """
     if not hasattr(field_info, 'default'):
-        return None
+        return False, None
     
     default_val = field_info.default
     
@@ -152,7 +156,7 @@ def get_default_enum_value(field_info: Any, debug: bool = False) -> Optional[Any
     if default_val is ... or default_val is None:
         if debug:
             print(f"         └─ Default is undefined marker")
-        return None
+        return False, None
     
     # Check for Pydantic's internal "PydanticUndefined" or similar markers
     default_str = str(default_val)
@@ -173,17 +177,72 @@ def get_default_enum_value(field_info: Any, debug: bool = False) -> Optional[Any
     if is_undefined_marker:
         if debug:
             print(f"         └─ Default is undefined marker pattern")
-        return None
+        return False, None
     
-    # Check if it's an enum instance
+    # We have a real default value
+    if debug:
+        print(f"         └─ Has real default value: {repr(default_val)}")
+    return True, default_val
+
+def convert_default_to_typescript(default_val: Any, debug: bool = False) -> str:
+    """Convert a Python default value to TypeScript literal"""
+    if debug:
+        print(f"         🔄 Converting default: {repr(default_val)} (type: {type(default_val)})")
+    
+    # Handle None
+    if default_val is None:
+        return "undefined"
+    
+    # Handle Enum instances
     if isinstance(default_val, Enum):
-        if debug:
+        return f'"{default_val.value}"'
-            print(f"         └─ Default is enum instance: {default_val.value}")
-        return default_val
     
+    # Handle basic types
+    if isinstance(default_val, str):
+        # Escape quotes and special characters
+        escaped = default_val.replace('\\', '\\\\').replace('"', '\\"')
+        return f'"{escaped}"'
+    elif isinstance(default_val, (int, float)):
+        return str(default_val)
+    elif isinstance(default_val, bool):
+        return "true" if default_val else "false"
+    elif isinstance(default_val, list):
+        if not default_val:  # Empty list
+            return "[]"
+        # For non-empty lists, convert each item
+        items = [convert_default_to_typescript(item, debug) for item in default_val]
+        return f"[{', '.join(items)}]"
+    elif isinstance(default_val, dict):
+        if not default_val:  # Empty dict
+            return "{}"
+        # For non-empty dicts, convert each key-value pair
+        items = []
+        for key, value in default_val.items():
+            key_str = f'"{key}"' if isinstance(key, str) else str(key)
+            value_str = convert_default_to_typescript(value, debug)
+            items.append(f"{key_str}: {value_str}")
+        return f"{{{', '.join(items)}}}"
+    elif isinstance(default_val, datetime):
+        # Convert datetime to ISO string, then wrap in new Date()
+        iso_string = default_val.isoformat()
+        return f'new Date("{iso_string}")'
+    
+    # For other types, try to convert to string
     if debug:
-        print(f"         └─ Default is not an enum instance")
+        print(f"         ⚠️  Unknown default type, converting to string: {type(default_val)}")
-    return None
+    
+    # Try to convert to a reasonable TypeScript representation
+    try:
+        if hasattr(default_val, '__dict__'):
+            # It's an object, try to serialize its properties
+            return "{}"  # Fallback to empty object for complex types
+        else:
+            # Try string conversion
+            str_val = str(default_val)
+            escaped = str_val.replace('\\', '\\\\').replace('"', '\\"')
+            return f'"{escaped}"'
+    except:
+        return "undefined"
 
 def python_type_to_typescript(python_type: Any, field_info: Any = None, debug: bool = False) -> str:
     """Convert a Python type to TypeScript type string, considering field defaults"""
@@ -198,13 +257,9 @@ def python_type_to_typescript(python_type: Any, field_info: Any = None, debug: b
     if debug and original_type != python_type:
         print(f"    🔄 Unwrapped: {original_type} -> {python_type}")
     
-    # Check if this field has a specific enum default value
+    # REMOVED: The problematic enum default checking that returns only the default value
-    if field_info:
+    # This was causing the issue where enum fields would only show the default value
-        default_enum = get_default_enum_value(field_info, debug)
+    # instead of all possible enum values
-        if default_enum is not None:
-            if debug:
-                print(f"    🎯 Field has specific enum default: {default_enum.value}")
-            return f'"{default_enum.value}"'
     
     # Handle None/null
     if python_type is type(None):
@@ -268,9 +323,12 @@ def python_type_to_typescript(python_type: Any, field_info: Any = None, debug: b
                     literal_values.append(str(arg))
             return " | ".join(literal_values)
     
-    # Handle Enum types
+    # Handle Enum types - THIS IS THE CORRECT BEHAVIOR
+    # Return all possible enum values, not just the default
     if isinstance(python_type, type) and issubclass(python_type, Enum):
         enum_values = [f'"{v.value}"' for v in python_type]
+        if debug:
+            print(f"    🎯 Enum type detected: {python_type.__name__} with values: {enum_values}")
         return " | ".join(enum_values)
     
     # Handle individual enum instances
@@ -375,18 +433,12 @@ def is_field_optional(field_info: Any, field_type: Any, debug: bool = False) ->
                 print(f"         └─ RESULT: Required (default is undefined marker)")
             return False
         
-        # Special case: if field has a specific default value (like enum), it's required
+        # FIXED: Fields with actual default values (including enums) should be REQUIRED
-        # because it will always have a value, just not optional for the consumer
-        if isinstance(default_val, Enum):
-            if debug:
-                print(f"         └─ RESULT: Required (has specific enum default: {default_val.value})")
-            return False
-            
-        # FIXED: Fields with actual default values (like [], "", 0) should be REQUIRED
         # because they will always have a value (either provided or the default)
+        # This applies to enum fields with defaults as well
         if debug:
             print(f"         └─ RESULT: Required (has actual default value - field will always have a value)")
-        return False  # Changed from True to False
+        return False
     else:
         if debug:
             print(f"         └─ No default attribute found")
@@ -420,6 +472,7 @@ def process_pydantic_model(model_class, debug: bool = False) -> Dict[str, Any]:
     interface_name = model_class.__name__
     properties = []
     date_fields = []  # Track date fields for conversion functions
+    default_fields = []  # Track fields with default values for default object generation
     
     if debug:
         print(f"  🔍 Processing model: {interface_name}")
@@ -445,6 +498,17 @@ def process_pydantic_model(model_class, debug: bool = False) -> Dict[str, Any]:
             if debug:
                 print(f"       Raw type: {field_type}")
             
+            # Check for default values
+            has_default, default_value = get_field_default_value(field_info, debug)
+            if has_default:
+                ts_default = convert_default_to_typescript(default_value, debug)
+                default_fields.append({
+                    'name': ts_name,
+                    'value': ts_default
+                })
+                if debug:
+                    print(f"       🎯 Default value: {repr(default_value)} -> {ts_default}")
+            
             # Check if this is a date field
             is_date = is_date_type(field_type)
             if debug:
@@ -461,7 +525,7 @@ def process_pydantic_model(model_class, debug: bool = False) -> Dict[str, Any]:
             elif debug and ('date' in str(field_type).lower() or 'time' in str(field_type).lower()):
                 print(f"       ⚠️  Field {ts_name} contains 'date'/'time' but not detected as date type: {field_type}")
             
-            # Pass field_info to the type converter for default enum handling
+            # Pass field_info to the type converter (but now it won't override enum types)
             ts_type = python_type_to_typescript(field_type, field_info, debug)
             
             # Check if optional
@@ -497,6 +561,17 @@ def process_pydantic_model(model_class, debug: bool = False) -> Dict[str, Any]:
             if debug:
                 print(f"       Raw type: {field_type}")
             
+            # Check for default values
+            has_default, default_value = get_field_default_value(field_info, debug)
+            if has_default:
+                ts_default = convert_default_to_typescript(default_value, debug)
+                default_fields.append({
+                    'name': ts_name,
+                    'value': ts_default
+                })
+                if debug:
+                    print(f"       🎯 Default value: {repr(default_value)} -> {ts_default}")
+            
             # Check if this is a date field
             is_date = is_date_type(field_type)
             if debug:
@@ -513,7 +588,7 @@ def process_pydantic_model(model_class, debug: bool = False) -> Dict[str, Any]:
             elif debug and ('date' in str(field_type).lower() or 'time' in str(field_type).lower()):
                 print(f"       ⚠️  Field {ts_name} contains 'date'/'time' but not detected as date type: {field_type}")
             
-            # Pass field_info to the type converter for default enum handling
+            # Pass field_info to the type converter (but now it won't override enum types)
             ts_type = python_type_to_typescript(field_type, field_info, debug)
             
             # For Pydantic v1, check required and default
@@ -534,7 +609,8 @@ def process_pydantic_model(model_class, debug: bool = False) -> Dict[str, Any]:
     return {
         'name': interface_name,
         'properties': properties,
-        'date_fields': date_fields
+        'date_fields': date_fields,
+        'default_fields': default_fields
     }
 
 def process_enum(enum_class) -> Dict[str, Any]:
@@ -548,6 +624,159 @@ def process_enum(enum_class) -> Dict[str, Any]:
         'values': " | ".join(values)
     }
 
+def generate_default_objects(interfaces: List[Dict[str, Any]]) -> str:
+    """Generate TypeScript default objects for models with default values"""
+    default_objects = []
+    
+    for interface in interfaces:
+        interface_name = interface['name']
+        default_fields = interface.get('default_fields', [])
+        
+        if not default_fields:
+            continue  # Skip interfaces without default values
+        
+        object_name = f"Default{interface_name}"
+        
+        # Generate default object
+        obj_lines = [
+            f"/**",
+            f" * Default values for {interface_name}",
+            f" * Fields with defaults: {', '.join([f['name'] for f in default_fields])}",
+            f" */",
+            f"export const {object_name}: Partial<{interface_name}> = {{"
+        ]
+        
+        # Add default field values
+        for i, default_field in enumerate(default_fields):
+            field_name = default_field['name']
+            field_value = default_field['value']
+            
+            # Add comma for all but the last field
+            comma = "," if i < len(default_fields) - 1 else ""
+            obj_lines.append(f"  {field_name}: {field_value}{comma}")
+        
+        obj_lines.append("};")
+        obj_lines.append("")  # Empty line after each object
+        
+        default_objects.append('\n'.join(obj_lines))
+    
+    if not default_objects:
+        return ""
+    
+    # Generate the default objects section
+    result = [
+        "// ============================",
+        "// Default Objects", 
+        "// ============================",
+        "",
+        "// These objects contain the default values from your Pydantic models",
+        "// Use them to initialize objects with sensible defaults:",
+        "// const message: ChatMessage = { ...DefaultChatMessage, sessionId: '123', content: 'Hello' };",
+        "",
+    ]
+    
+    result.extend(default_objects)
+    
+    return '\n'.join(result)
+    """Generate TypeScript conversion functions for models with date fields"""
+    conversion_functions = []
+    
+    for interface in interfaces:
+        interface_name = interface['name']
+        date_fields = interface.get('date_fields', [])
+        
+        if not date_fields:
+            continue  # Skip interfaces without date fields
+        
+        function_name = f"convert{interface_name}FromApi"
+        
+        # Generate function
+        func_lines = [
+            f"/**",
+            f" * Convert {interface_name} from API response, parsing date fields",
+            f" * Date fields: {', '.join([f['name'] for f in date_fields])}",
+            f" */",
+            f"export function {function_name}(data: any): {interface_name} {{",
+            f"  if (!data) return data;",
+            f"  ",
+            f"  return {{",
+            f"    ...data,"
+        ]
+        
+        # Add date field conversions with validation
+        for date_field in date_fields:
+            field_name = date_field['name']
+            is_optional = date_field['optional']
+            
+            # Add a comment for clarity
+            func_lines.append(f"    // Convert {field_name} from ISO string to Date")
+            
+            if is_optional:
+                func_lines.append(f"    {field_name}: data.{field_name} ? new Date(data.{field_name}) : undefined,")
+            else:
+                func_lines.append(f"    {field_name}: new Date(data.{field_name}),")
+        
+        func_lines.extend([
+            f"  }};",
+            f"}}"
+        ])
+        
+        conversion_functions.append('\n'.join(func_lines))
+    
+    if not conversion_functions:
+        return ""
+    
+    # Generate the conversion functions section
+    result = [
+        "// ============================",
+        "// Date Conversion Functions", 
+        "// ============================",
+        "",
+        "// These functions convert API responses to properly typed objects",
+        "// with Date objects instead of ISO date strings",
+        "",
+    ]
+    
+    result.extend(conversion_functions)
+    result.append("")
+    
+    # Generate a generic converter function
+    models_with_dates = [interface['name'] for interface in interfaces if interface.get('date_fields')]
+    
+    if models_with_dates:
+        result.extend([
+            "/**",
+            " * Generic converter that automatically selects the right conversion function",
+            " * based on the model type",
+            " */",
+            "export function convertFromApi<T>(data: any, modelType: string): T {",
+            "  if (!data) return data;",
+            "  ",
+            "  switch (modelType) {"
+        ])
+        
+        for model_name in models_with_dates:
+            result.append(f"    case '{model_name}':")
+            result.append(f"      return convert{model_name}FromApi(data) as T;")
+        
+        result.extend([
+            "    default:",
+            "      return data as T;",
+            "  }",
+            "}",
+            "",
+            "/**",
+            " * Convert array of items using the appropriate converter",
+            " */", 
+            "export function convertArrayFromApi<T>(data: any[], modelType: string): T[] {",
+            "  if (!data || !Array.isArray(data)) return data;",
+            "  return data.map(item => convertFromApi<T>(item, modelType));",
+            "}",
+            ""
+        ])
+    
+    return '\n'.join(result)
+
 def generate_conversion_functions(interfaces: List[Dict[str, Any]]) -> str:
     """Generate TypeScript conversion functions for models with date fields"""
     conversion_functions = []
@@ -706,8 +935,10 @@ def generate_typescript_interfaces(source_file: str, debug: bool = False):
             continue
     
     total_date_fields = sum(len(interface.get('date_fields', [])) for interface in interfaces)
+    total_default_fields = sum(len(interface.get('default_fields', [])) for interface in interfaces)
     print(f"\n📊 Found {len(interfaces)} interfaces and {len(enums)} enums")
     print(f"🗓️  Found {total_date_fields} date fields across all models")
+    print(f"🎯 Found {total_default_fields} fields with default values across all models")
     
     # Generate TypeScript content
     ts_content = f"""// Generated TypeScript types from Pydantic models
@@ -741,6 +972,11 @@ def generate_typescript_interfaces(source_file: str, debug: bool = False):
             
             ts_content += "}\n\n"
     
+    # Add default objects
+    default_objects = generate_default_objects(interfaces)
+    if default_objects:
+        ts_content += default_objects
+    
     # Add conversion functions
     conversion_functions = generate_conversion_functions(interfaces)
     if conversion_functions:
@@ -780,7 +1016,7 @@ def compile_typescript(ts_file: str) -> bool:
 def main():
     """Main function with command line argument parsing"""
     parser = argparse.ArgumentParser(
-        description='Generate TypeScript types from Pydantic models with date conversion functions and proper enum default handling',
+        description='Generate TypeScript types from Pydantic models with date conversion functions, default objects, and proper enum handling',
         formatter_class=argparse.RawDescriptionHelpFormatter,
         epilog="""
 Examples:
@@ -795,8 +1031,12 @@ Generated conversion functions can be used like:
   const candidate = convertCandidateFromApi(apiResponse);
   const jobs = convertArrayFromApi<Job>(apiResponse, 'Job');
 
-Enum defaults are now properly handled:
+Generated default objects can be used like:
-  status: ChatStatusType = ChatStatusType.DONE  ->  status: "done"
+  const message: ChatMessage = { ...DefaultChatMessage, sessionId: '123', content: 'Hello' };
+  const overrideMessage: ChatMessage = { ...DefaultChatMessage, status: 'error' };
+
+Enum fields now properly support all enum values:
+  status: ChatStatusType = ChatStatusType.DONE  ->  status: "pending" | "processing" | "done" | "error"
         """
     )
     
@@ -833,12 +1073,12 @@ Enum defaults are now properly handled:
     parser.add_argument(
         '--version', '-v',
         action='version',
-        version='TypeScript Generator 3.1 (with Enum Default Handling)'
+        version='TypeScript Generator 3.3 (with Default Objects and Fixed Enum Handling)'
     )
     
     args = parser.parse_args()
     
-    print("🚀 Enhanced TypeScript Type Generator with Enum Default Handling")
+    print("🚀 Enhanced TypeScript Type Generator with Default Objects and Fixed Enum Handling")
     print("=" * 60)
     print(f"📁 Source file: {args.source}")
     print(f"📁 Output file: {args.output}")
@@ -883,27 +1123,37 @@ Enum defaults are now properly handled:
         
         # Count conversion functions and provide detailed feedback
         conversion_count = ts_content.count('export function convert') - ts_content.count('convertFromApi') - ts_content.count('convertArrayFromApi')
-        enum_specific_count = ts_content.count(': "') - ts_content.count('export type')
+        default_objects_count = ts_content.count('export const Default')
+        enum_union_count = ts_content.count(' | ')
         
         if conversion_count > 0:
             print(f"🗓️  Generated {conversion_count} date conversion functions")
-        if enum_specific_count > 0:
+        if default_objects_count > 0:
-            print(f"🎯 Generated {enum_specific_count} specific enum default types")
+            print(f"🎯 Generated {default_objects_count} default objects")
+        if enum_union_count > 0:
+            print(f"🔗 Generated {enum_union_count} union types (including proper enum types)")
             
         if args.debug:
             # Show which models have date conversion
             models_with_dates = []
+            models_with_defaults = []
             for line in ts_content.split('\n'):
                 if line.startswith('export function convert') and 'FromApi' in line and 'convertFromApi' not in line:
                     model_name = line.split('convert')[1].split('FromApi')[0]
                     models_with_dates.append(model_name)
+                elif line.startswith('export const Default'):
+                    model_name = line.split('export const Default')[1].split(':')[0]
+                    models_with_defaults.append(model_name)
+            
             if models_with_dates:
                 print(f"   Models with date conversion: {', '.join(models_with_dates)}")
+            if models_with_defaults:
+                print(f"   Models with default objects: {', '.join(models_with_defaults)}")
                     
         # Provide troubleshooting info if debug mode
         if args.debug:
             print(f"\n🐛 Debug mode was enabled. If you see incorrect type conversions:")
-            print(f"   1. Check the debug output above for '🎯 Field has specific enum default' lines")
+            print(f"   1. Look for '🎯 Enum type detected' lines to verify enum handling")
             print(f"   2. Look for '📅 Date type check' lines for date handling")
             print(f"   3. Look for '⚠️' warnings about fallback types") 
             print(f"   4. Verify your Pydantic model field types and defaults are correct")
@@ -924,18 +1174,23 @@ Enum defaults are now properly handled:
         print(f"✅ File size: {file_size} characters")
         if conversion_count > 0:
             print(f"✅ Date conversion functions: {conversion_count}")
-        if enum_specific_count > 0:
+        if default_objects_count > 0:
-            print(f"✅ Specific enum default types: {enum_specific_count}")
+            print(f"✅ Default objects: {default_objects_count}")
+        if enum_union_count > 0:
+            print(f"✅ Union types (proper enum support): {enum_union_count}")
         if not args.skip_test:
             print("✅ Model validation passed")
         if not args.skip_compile:
             print("✅ TypeScript syntax validated")
         
         print(f"\n💡 Usage in your TypeScript project:")
-        print(f"   import {{ Candidate, Employer, Job, convertCandidateFromApi }} from './{Path(args.output).stem}';")
+        print(f"   import {{ ChatMessage, ChatStatusType, DefaultChatMessage, convertChatMessageFromApi }} from './{Path(args.output).stem}';")
+        print(f"   const message: ChatMessage = {{ ...DefaultChatMessage, sessionId: '123', content: 'Hello' }};")
         if conversion_count > 0:
-            print(f"   const candidate = convertCandidateFromApi(apiResponse);")
+            print(f"   const message = convertChatMessageFromApi(apiResponse);")
-            print(f"   const jobs = convertArrayFromApi<Job>(apiResponse, 'Job');")
+            print(f"   const messages = convertArrayFromApi<ChatMessage>(apiResponse, 'ChatMessage');")
+        if default_objects_count > 0:
+            print(f"   const overrideMessage: ChatMessage = {{ ...DefaultChatMessage, status: 'error' }};")
             
         return True
         

src/backend/models.py

@@ -97,6 +97,7 @@ class ChatStatusType(str, Enum):
 
 class ChatContextType(str, Enum):
     JOB_SEARCH = "job_search"
+    JOB_REQUIREMENTS = "job_requirements"
     CANDIDATE_CHAT = "candidate_chat"
     INTERVIEW_PREP = "interview_prep"
     RESUME_REVIEW = "resume_review"