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feat: implement YAML-based configuration, .env support, and customizable prompt templates for AI analysis

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This commit is contained in:
haopengzhan
2026-08-22 10:17:38 -07:00
parent 7ec91f384f
commit 0de312edbd
30 changed files with 895 additions and 211 deletions
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internal/analyzer/analyzer.go
+5 -2
View File
@@ -9,6 +9,9 @@ import (
)
type AnalysisOutput struct {
AIScore float64 `json:"ai_score"`
IsQualified bool `json:"is_qualified"`
Summary string `json:"summary"`
MatchedHighlights []string `json:"matched_highlights"`
MissingHighlights []string `json:"missing_highlights"`
TailoringSuggestions []string `json:"tailoring_suggestions"`
@@ -25,12 +28,12 @@ func NewAnalyzer(cfg *config.Config) (LLMAnalyzer, error) {
if cfg.GeminiAPIKey == "" {
return nil, fmt.Errorf("GEMINI_API_KEY is required for provider 'gemini'")
}
return NewGeminiAnalyzer(cfg.GeminiAPIKey), nil
return NewGeminiAnalyzer(cfg.GeminiAPIKey, cfg.SystemPrompt, cfg.UserPrompt), nil
case "deepseek":
if cfg.DeepSeekAPIKey == "" {
return nil, fmt.Errorf("DEEPSEEK_API_KEY is required for provider 'deepseek'")
}
return NewDeepSeekAnalyzer(cfg.DeepSeekAPIKey, cfg.DeepSeekBaseURL), nil
return NewDeepSeekAnalyzer(cfg.DeepSeekAPIKey, cfg.DeepSeekBaseURL, cfg.SystemPrompt, cfg.UserPrompt), nil
case "mock":
return NewMockAnalyzer(), nil
default:
internal/analyzer/analyzer_test.go
+50
View File
@@ -0,0 +1,50 @@
package analyzer
import (
"context"
"testing"
)
func TestCleanJSONResponse(t *testing.T) {
cases := []struct {
input string
expected string
}{
{
input: "```json\n{\"ai_score\": 90}\n```",
expected: "{\"ai_score\": 90}",
},
{
input: "```\n{\"ai_score\": 85}\n```",
expected: "{\"ai_score\": 85}",
},
{
input: "{\"ai_score\": 95}",
expected: "{\"ai_score\": 95}",
},
}
for _, c := range cases {
out := cleanJSONResponse(c.input)
if out != c.expected {
t.Errorf("cleanJSONResponse(%q) = %q, expected %q", c.input, out, c.expected)
}
}
}
func TestMockAnalyzer(t *testing.T) {
mock := NewMockAnalyzer()
res, err := mock.AnalyzeJD(context.Background(), "Senior AI Infrastructure Engineer", "Building GKE and K8s runtimes.")
if err != nil {
t.Fatalf("unexpected error: %v", err)
}
if res.AIScore <= 0 {
t.Errorf("expected positive AI score, got %f", res.AIScore)
}
if !res.IsQualified {
t.Errorf("expected IsQualified=true, got false")
}
if len(res.MatchedHighlights) == 0 {
t.Errorf("expected matched highlights to not be empty")
}
}
internal/analyzer/deepseek.go
+50 -19
View File
@@ -12,38 +12,48 @@ import (
)
type DeepSeekAnalyzer struct {
apiKey string
baseURL string
client *http.Client
apiKey string
baseURL string
systemPrompt string
userPromptTemplate string
client *http.Client
}
func NewDeepSeekAnalyzer(apiKey, baseURL string) *DeepSeekAnalyzer {
func NewDeepSeekAnalyzer(apiKey, baseURL, systemPrompt, userPromptTemplate string) *DeepSeekAnalyzer {
if baseURL == "" {
baseURL = "https://api.deepseek.com"
}
return &DeepSeekAnalyzer{
apiKey: apiKey,
baseURL: strings.TrimRight(baseURL, "/"),
client: &http.Client{Timeout: 30 * time.Second},
apiKey: apiKey,
baseURL: strings.TrimRight(baseURL, "/"),
systemPrompt: systemPrompt,
userPromptTemplate: userPromptTemplate,
client: &http.Client{Timeout: 30 * time.Second},
}
}
func (d *DeepSeekAnalyzer) AnalyzeJD(ctx context.Context, jobTitle, rawContent string) (*AnalysisOutput, error) {
prompt := fmt.Sprintf(`You are an expert technical resume screener. Analyze the following job description for the title "%s".
Provide a structured JSON output with 3 fields:
- "matched_highlights": list of 3-5 core technical skills/requirements matched (e.g. ["Go (Golang)", "Microservices", "REST APIs"]).
- "missing_highlights": list of 1-3 missing skills, experience gaps, or extra requirements (e.g. ["10+ yrs experience", "Kubernetes administration"]).
- "tailoring_suggestions": list of 2-3 specific action points for tailoring a resume to this JD.
func (d *DeepSeekAnalyzer) buildUserPrompt(jobTitle, rawContent string) string {
if d.userPromptTemplate == "" {
return fmt.Sprintf("Analyze the following job description for candidate Pengzhan Hao.\n\nJob Title: %s\n\nJob Description:\n%s\n\nProvide the structured evaluation adhering to the JSON schema.", jobTitle, rawContent)
}
res := strings.ReplaceAll(d.userPromptTemplate, "{{.JobTitle}}", jobTitle)
res = strings.ReplaceAll(res, "{{.JobContent}}", rawContent)
return res
}
Job Title: %s
Job Content:
%s`, jobTitle, jobTitle, rawContent)
func (d *DeepSeekAnalyzer) AnalyzeJD(ctx context.Context, jobTitle, rawContent string) (*AnalysisOutput, error) {
sysPrompt := d.systemPrompt
if sysPrompt == "" {
sysPrompt = "You are an expert technical resume screener. You MUST respond with a valid JSON object matching {\"ai_score\": 80.0, \"is_qualified\": true, \"summary\": \"...\", \"matched_highlights\": [...], \"missing_highlights\": [...], \"tailoring_suggestions\": [...]}."
}
userPrompt := d.buildUserPrompt(jobTitle, rawContent)
reqBody := map[string]interface{}{
"model": "deepseek-chat",
"messages": []map[string]string{
{"role": "system", "content": "You are a professional hiring assistant. You MUST respond ONLY with valid JSON matching {\"matched_highlights\": [...], \"missing_highlights\": [...], \"tailoring_suggestions\": [...]}."},
{"role": "user", "content": prompt},
{"role": "system", "content": sysPrompt},
{"role": "user", "content": userPrompt},
},
"response_format": map[string]string{
"type": "json_object",
@@ -99,7 +109,28 @@ Job Content:
var output AnalysisOutput
if err := json.Unmarshal([]byte(rawJSON), &output); err != nil {
return nil, fmt.Errorf("failed to parse DeepSeek JSON output: %w", err)
return nil, fmt.Errorf("failed to parse DeepSeek JSON output: %w (content: %s)", err, rawJSON)
}
// Sanitize output bounds
if output.AIScore < 0 {
output.AIScore = 0
} else if output.AIScore > 100 {
output.AIScore = 100
}
if output.AIScore >= 60.0 {
output.IsQualified = true
}
if output.MatchedHighlights == nil {
output.MatchedHighlights = []string{}
}
if output.MissingHighlights == nil {
output.MissingHighlights = []string{}
}
if output.TailoringSuggestions == nil {
output.TailoringSuggestions = []string{}
}
return &output, nil
internal/analyzer/gemini.go
+36 -17
View File
@@ -7,40 +7,49 @@ import (
"fmt"
"io"
"net/http"
"strings"
"time"
)
type GeminiAnalyzer struct {
apiKey string
client *http.Client
apiKey string
systemPrompt string
userPromptTemplate string
client *http.Client
}
func NewGeminiAnalyzer(apiKey string) *GeminiAnalyzer {
func NewGeminiAnalyzer(apiKey, systemPrompt, userPromptTemplate string) *GeminiAnalyzer {
return &GeminiAnalyzer{
apiKey: apiKey,
client: &http.Client{Timeout: 30 * time.Second},
apiKey: apiKey,
systemPrompt: systemPrompt,
userPromptTemplate: userPromptTemplate,
client: &http.Client{Timeout: 30 * time.Second},
}
}
func (g *GeminiAnalyzer) buildUserPrompt(jobTitle, rawContent string) string {
if g.userPromptTemplate == "" {
return fmt.Sprintf("Analyze the following job description for candidate Pengzhan Hao.\n\nJob Title: %s\n\nJob Content:\n%s\n\nRespond with structured JSON.", jobTitle, rawContent)
}
res := strings.ReplaceAll(g.userPromptTemplate, "{{.JobTitle}}", jobTitle)
res = strings.ReplaceAll(res, "{{.JobContent}}", rawContent)
return res
}
func (g *GeminiAnalyzer) AnalyzeJD(ctx context.Context, jobTitle, rawContent string) (*AnalysisOutput, error) {
prompt := fmt.Sprintf(`You are an expert technical resume screener. Analyze the following job description for the title "%s".
Provide a structured JSON output with 3 fields:
- "matched_highlights": list of 3-5 core technical skills/requirements matched (e.g. ["Go (Golang)", "Microservices", "REST APIs"]).
- "missing_highlights": list of 1-3 missing skills, experience gaps, or extra requirements (e.g. ["10+ yrs experience", "Kubernetes administration"]).
- "tailoring_suggestions": list of 2-3 specific action points for tailoring a resume to this JD.
sysPrompt := g.systemPrompt
if sysPrompt == "" {
sysPrompt = "You are an expert technical resume screener. Respond STRICTLY with valid JSON matching {\"ai_score\": 85.0, \"is_qualified\": true, \"summary\": \"...\", \"matched_highlights\": [...], \"missing_highlights\": [...], \"tailoring_suggestions\": [...]}."
}
Job Title: %s
Job Content:
%s
Respond STRICTLY with valid JSON matching the format:
{"matched_highlights": [...], "missing_highlights": [...], "tailoring_suggestions": [...]}`, jobTitle, jobTitle, rawContent)
userPrompt := g.buildUserPrompt(jobTitle, rawContent)
fullPrompt := fmt.Sprintf("%s\n\n%s", sysPrompt, userPrompt)
reqBody := map[string]interface{}{
"contents": []map[string]interface{}{
{
"parts": []map[string]string{
{"text": prompt},
{"text": fullPrompt},
},
},
},
@@ -102,5 +111,15 @@ Respond STRICTLY with valid JSON matching the format:
return nil, fmt.Errorf("failed to parse Gemini JSON output: %w", err)
}
if output.AIScore < 0 {
output.AIScore = 0
} else if output.AIScore > 100 {
output.AIScore = 100
}
if output.AIScore >= 60.0 {
output.IsQualified = true
}
return &output, nil
}
internal/analyzer/mock.go
+5 -3
View File
@@ -10,11 +10,13 @@ func NewMockAnalyzer() *MockAnalyzer {
return &MockAnalyzer{}
}
// AnalyzeJD returns empty slices for mock provider so no fake mock text is injected into side panel during debug
func (m *MockAnalyzer) AnalyzeJD(ctx context.Context, jobTitle, rawContent string) (*AnalysisOutput, error) {
return &AnalysisOutput{
MatchedHighlights: []string{},
AIScore: 75.0,
IsQualified: true,
Summary: "Mock analysis: relevant systems and distributed infrastructure role.",
MatchedHighlights: []string{"Golang", "Distributed Systems", "Kubernetes"},
MissingHighlights: []string{},
TailoringSuggestions: []string{},
TailoringSuggestions: []string{"Highlight Google GKE runtime experience."},
}, nil
}