Resume template activate

app/api/v1/routes.py

@@ -5,63 +5,14 @@
 from concurrent.futures import ProcessPoolExecutor
 import asyncio
 import logging
-import json
 from app.services.stack_service import generate_techstack
 from app.services.gpt_service import generate_aboutme, resume_update
-from app.services.github_service import get_github_profile_and_repos
 from app.config.settings import settings
 
 
 
 router = APIRouter()
 
-# 이력서 생성 api
-@router.post("/api/ai/resumes", response_model=ResumeResponse)
-async def generate_resume(request: ResumeRequest):
-    logging.basicConfig(level=logging.INFO)
-
-    # 각 레포지토리 요약을 멀티프로세싱으로 처리
-    with ProcessPoolExecutor() as executor:
-        loop = asyncio.get_event_loop()
-        tasks = [
-            loop.run_in_executor(executor, process_repository, repo_url, request.githubID, request.githubName, request.requirements)
-            for repo_url in request.selectedRepo
-        ]
-        try:
-            # 실패 시 예외를 발생시키고 에러 메시지를 리턴
-            project_summaries = await asyncio.gather(*tasks)
-
-        except Exception as e:
-            logging.error(f"Error processing repositories: {e}")
-            return {"error": f"Error processing repositories: {str(e)}"}
-
-    # # aboutme techstack 생성
-    # aboutme_techstack = create_aboutme_techstack(project_summaries)
-
-
-    # 레포 이름
-    repo_name = "/".join(str(request.selectedRepo[0]).rstrip('/').split('/')[-2:])
-
-
-    # techstack 생성
-    techstack = generate_techstack(settings.gh_token, repo_name)
-    aboutme = generate_aboutme(settings.openai_api_key)
-
-    print(aboutme)
-
-
-    # 최종 이력서 응답 생성
-    resume_response = ResumeResponse(
-        projects=project_summaries,
-        techStack=techstack,
-        aboutMe=aboutme
-        # aboutMe=aboutme_techstack.aboutMe
-    )
-    return resume_response
-
-
-
-
 @router.put("/api/ai/resumes", response_model=ResumeResponseDto)
 async def update_resume(request: UpdateRequestDto):
     try:
@@ -89,4 +40,42 @@ async def update_resume(request: UpdateRequestDto):
 
     except Exception as e:
         print(f"Error in update_resume: {e}")
-        raise HTTPException(status_code=500, detail="An error occurred while updating the resume.")
+        raise HTTPException(status_code=500, detail="An error occurred while updating the resume.")
+
+
+# 이력서 생성 api
+@router.post("/api/ai/resumes", response_model=ResumeResponse)
+async def generate_resume(request: ResumeRequest):
+    logging.basicConfig(level=logging.INFO)
+
+    # 각 레포지토리 요약을 멀티프로세싱으로 처리
+    with ProcessPoolExecutor() as executor:
+        loop = asyncio.get_event_loop()
+        tasks = [
+            loop.run_in_executor(executor, process_repository, request.template, repo_url, request.githubID, request.githubName, request.requirements)
+            for repo_url in request.selectedRepo
+        ]
+        try:
+            # 실패 시 예외를 발생시키고 에러 메시지를 리턴
+            project_data = await asyncio.gather(*tasks)
+
+        except Exception as e:
+            logging.error(f"Error processing repositories: {e}")
+            return {"error": f"Error processing repositories: {str(e)}"}
+
+    # 레포 이름
+    repo_name = "/".join(str(request.selectedRepo[0]).rstrip('/').split('/')[-2:])
+
+    # 공동생성 부분
+    techStack = generate_techstack(settings.gh_token, repo_name)
+    aboutMe = generate_aboutme(settings.openai_api_key)
+
+    resume_response = ResumeResponse(
+        template=request.template,
+        techStack=techStack,
+        aboutMe=aboutMe,
+        projects=project_data
+    )
+    print(resume_response)
+
+    return resume_response

app/api/v1/routes2.py

@@ -0,0 +1,63 @@
+from fastapi import APIRouter, HTTPException
+from app.dto.resume_dto import ResumeRequest, ResumeResponse, BasicDto, freedom_dto, gitfolio_dto, star_dto
+from app.dto.resume_modify_dto import UpdateRequestDto,ResumeResponseDto
+from app.services.api_service import process_repository, create_repo_start_end_date
+from concurrent.futures import ProcessPoolExecutor
+import asyncio
+import logging
+import json
+from app.services.stack_service import generate_techstack
+from app.services.gpt_service import generate_aboutme, resume_update, generate_project_title, generate_role_and_task
+from app.services.github_service import get_github_profile_and_repos
+from app.config.settings import settings
+
+
+
+router = APIRouter()
+# 기존 코드 백업용
+# 이력서 생성 api
+@router.post("/api/ai/resumes", response_model=ResumeResponse)
+async def generate_resume(request: ResumeRequest):
+    logging.basicConfig(level=logging.INFO)
+
+    # 각 레포지토리 요약을 멀티프로세싱으로 처리
+    with ProcessPoolExecutor() as executor:
+        loop = asyncio.get_event_loop()
+        tasks = [
+            loop.run_in_executor(executor, process_repository, repo_url, request.githubID, request.githubName, request.requirements)
+            for repo_url in request.selectedRepo
+        ]
+        try:
+            # 실패 시 예외를 발생시키고 에러 메시지를 리턴
+            project_summaries = await asyncio.gather(*tasks)
+
+        except Exception as e:
+            logging.error(f"Error processing repositories: {e}")
+            return {"error": f"Error processing repositories: {str(e)}"}
+
+    # 레포 이름
+    repo_name = "/".join(str(request.selectedRepo[0]).rstrip('/').split('/')[-2:])
+
+    # techstack 생성
+    techstack = generate_techstack(settings.gh_token, repo_name)
+    aboutme = generate_aboutme(settings.openai_api_key)
+
+    # # 선택적 구성 생성   
+    # role_and_task = generate_role_and_task(settings.openai_api_key)
+    # trouble_shooting = generate_trouble_shooting(settings.openai_api_key)
+    # star = generate_star_summary(settings.openai_api_key)
+
+
+    print("==========") 
+    print(aboutme)
+
+    # 최종 이력서 응답 생성
+    resume_response = ResumeResponse(
+        template=request.template,
+        project_summaries=project_summaries,
+    )
+    print("==================")
+    print(resume_response)
+
+    return resume_response
+    # return JSONResponse(content=resume_response.dict())

app/config/settings.py

@@ -1,7 +1,7 @@
 from typing import List
 from pydantic_settings import BaseSettings
 from app.config.constant import GPT_MODEL, MAX_TOTAL_TOKENS, PROMPT_TOKEN_RESERVE, MAX_OUTPUT_TOKENS, MAX_CONTENT_TOKENS, DEFAULT_DATA, CODE_DATA, PR_DATA, COMMIT_DATA, PROJECT_DATA, REPO_DIRECTORY, FILE_EXTENSIONS
-from app.prompts.resume_prompt import CODE_SUMMARY_PROMPT, PR_SUMMARY_PROMPT, COMMIT_DIFF_SUMMARY_PROMPT, FINAL_SUMMARY_PROMPT, FINAL_PROJECT_PROMPT, SIMPLIFY_PROJECT_PROMPT, ABOUTME_TECHSTACK_PROMPT, ABOUTME_PROMPT, RESUME_UPDATE_PROMPT, PROJECT_TITLE_PROMPT
+from app.prompts.resume_prompt import CODE_SUMMARY_PROMPT, PR_SUMMARY_PROMPT, COMMIT_DIFF_SUMMARY_PROMPT, FINAL_SUMMARY_PROMPT, FINAL_PROJECT_PROMPT, SIMPLIFY_PROJECT_PROMPT, ABOUTME_TECHSTACK_PROMPT, ABOUTME_PROMPT, RESUME_UPDATE_PROMPT, PROJECT_TITLE_PROMPT, ROLE_AND_TASK_PROMPT, TROUBLE_SHOOTING_PROMPT, STAR_PROMPT
 class Settings(BaseSettings):
     # API 키
     openai_api_key: str
@@ -40,6 +40,9 @@ class Settings(BaseSettings):
     aboutme_prompt: str = ABOUTME_PROMPT
     resume_update_prompt: str = RESUME_UPDATE_PROMPT
     project_title_prompt: str = PROJECT_TITLE_PROMPT
+    role_and_task_prompt:str = ROLE_AND_TASK_PROMPT
+    trouble_shooting_prompt:str = TROUBLE_SHOOTING_PROMPT
+    star_prompt:str = STAR_PROMPT
 
     class Config:
         env_file = ".env"

app/dto/resume_dto.py

@@ -1,5 +1,7 @@
 from pydantic import BaseModel, HttpUrl
-from typing import List
+from typing import List, Union
+from app.dto.resume_modify_dto import StarDto, TroubleShootingDto
+
 
 # 요청 데이터 모델
 class ResumeRequest(BaseModel):
@@ -8,16 +10,22 @@ class ResumeRequest(BaseModel):
     personalRepo: HttpUrl
     selectedRepo: List[HttpUrl]
     requirements: str
+    template: str
 
-# 응답 데이터 모델 - 프로젝트 정보
+# 응답 데이터 모델 - 프로젝트 정보(공통DTO)
 class Project(BaseModel):
     projectName: str
     projectStartedAt: str  # YYYY-MM-DD 형식
     projectEndedAt: str  # YYYY-MM-DD 형식
     skillSet: str
-    projectDescription: str
+    roleAndTask: List[str] # BASIC 템플릿에서 사용  
     repoLink: HttpUrl
 
+class StarProject(Project):
+    star: StarDto
+class GitfolioProject(Project):
+    troubleShooting: TroubleShootingDto
+
 # gpt 프로젝트 요약문, json형태
 class GptProject(BaseModel):
     projectName: str
@@ -31,7 +39,7 @@ class GptAboutmeTechstack(BaseModel):
 
 # 응답 데이터 모델 - 전체 이력서
 class ResumeResponse(BaseModel):
-    projects: List[Project]
+    template: str
     techStack: List[str]
     aboutMe: str
-
+    projects: List[Union[Project, StarProject, GitfolioProject]]

app/dto/resume_modify_dto.py

@@ -57,4 +57,19 @@ class UpdateRequestDto(BaseModel):
     resumeInfo: ResumeResponseDto
 
 class ProjectTitleDto(BaseModel):
-    projectTitle: str
+    projectTitle: str
+
+class RoleAndTaskDto(BaseModel):
+    roleAndTask: List[str]
+
+class TroubleShootingDto(BaseModel):
+    problem: str
+    hypothesis: str
+    tring: str
+    result: str
+
+class StarDto(BaseModel):
+    situation: str
+    task: str
+    action: str
+    result: str

app/prompts/resume_prompt.py

@@ -23,6 +23,7 @@
 )
 
 FINAL_PROJECT_PROMPT = (
+    "Do not use code blocks (```), but markdown formatting such as bold or lists is allowed. Provide plain text instead of code blocks."
     "Write concisely and clearly, highlighting your unique strengths rather than common development details."
 )
 
@@ -61,15 +62,48 @@
         "3. Use metaphorical or creative expressions to enhance engagement, avoiding direct repetition of the input text.\n"
         "4. Ensure each point reflects the provided company values and GitHub data."
 )
-
+# 이력서 재생성
 RESUME_UPDATE_PROMPT = (
+    "Do not use code blocks (```), but markdown formatting such as bold or lists is allowed. Provide plain text instead of code blocks."
         "Update the provided `selected_text` based on the user's request. "
         "Modify only the specified text, and ensure the updated text aligns with the tone and style of the surrounding context. "
         "Return only the modified text without altering the structure or other parts of the resume."
 )
-
+# 프로젝트 이름 생성
 PROJECT_TITLE_PROMPT = (
+
     "Return the best project title as plain text. "
     "Do not include any additional explanation, formatting, or context. "
     "Only provide the title itself."
+)
+# 맡은 업무 생성
+ROLE_AND_TASK_PROMPT = (
+    "Do not use code blocks (```), but markdown formatting such as bold or lists is allowed. Provide plain text instead of code blocks."
+    "Create a summary of the main roles and responsibilities based on the provided data. "
+    "Use bullet points to list the key actions and tasks performed. Each point should:\n"
+    "- Begin with an action verb.\n"
+    "- Be concise and specific.\n"
+    "- Clearly reflect the user's contributions and achievements.\n\n"
+    "- Follow this pattern:"
+    "- Performed [specific action] to achieve [specific result], improving/enhancing [specific metric] by [quantifiable amount].  "    
+    "- Identified [specific issue] and implemented [specific action], resulting in a performance improvement of [quantifiable amount]."  
+    "- Utilized [specific tool or library] to develop/implement [specific functionality or feature]. " 
+    "For example:\n"
+    "- Designed and implemented Redis caching to improve API response times by 30%.\n"
+    "- Refactored MongoDB queries to reduce average query time by 55.4%.\n"
+    "- Developed an event-driven architecture using Kafka for real-time notifications."
+)
+# 트러블슈팅 생성
+TROUBLE_SHOOTING_PROMPT = (
+    "Do not use code blocks (```), but markdown formatting such as bold or lists is allowed. Provide plain text instead of code blocks."
+)
+
+# star기법 기반 생성
+STAR_PROMPT = (
+    "Do not use code blocks (```), but markdown formatting such as bold or lists is allowed. Provide plain text instead of code blocks."
+        "The output should be generated in the following format:\n\n"
+        "- **Situation**: [Background and goals of the project]\n"
+        "- **Task**: [Challenges or problems addressed]\n"
+        "- **Action**: [Specific actions taken to solve the problem]\n"
+        "- **Result**: [Outcomes and improvements, including measurable metrics if possible]"
 )