AI Resume Builder

# app/resume.py — JSON resume + rewrite diff + approve-before-export # pip install fastapi pydantic openai from enum import Enum from pydantic import BaseModel, Field, EmailStr from openai import OpenAI client = OpenAI() REWRITE_SYSTEM = ( "You rewrite resume JSON for a job description. " "You MUST NOT invent employers, titles, dates, degrees, or metrics. " "You MAY rephrase existing bullets and regroup listed skills. " "If the JD asks for a skill not in the resume, omit it or flag in warnings[]; never add it as a fact." ) class WorkItem(BaseModel): company: str position: str start: str end: str | None = None highlights: list[str] = Field(default_factory=list) class ResumeJSON(BaseModel): basics: dict work: list[WorkItem] education: list[dict] = Field(default_factory=list) skills: list[str] = Field(default_factory=list) class RewriteOut(BaseModel): resume: ResumeJSON warnings: list[str] = Field(default_factory=list) changelog: list[str] = Field(default_factory=list) class Status(str, Enum): draft = "draft" pending_review = "pending_review" approved = "approved" def fact_guard(original: ResumeJSON, proposed: ResumeJSON) -> list[str]: """Deterministic checks — do not delegate employment truth to the LLM.""" errors = [] orig_cos = {(w.company.lower(), w.position.lower()) for w in original.work} for w in proposed.work: key = (w.company.lower(), w.position.lower()) if key not in orig_cos and w.company.lower() not in {c[0] for c in orig_cos}: errors.append(f"new_employer_not_allowed:{w.company}") orig_edu = json.dumps(original.education, sort_keys=True) if json.dumps(proposed.education, sort_keys=True) != orig_edu: errors.append("education_mutation_not_allowed") return errors @app.post("/v1/resumes/{rid}/rewrite") def rewrite(rid: str, jd: str, user=Depends(current_user)): row = db.get_resume(rid, owner=user.id) original = ResumeJSON.model_validate(row.json_body) resp = client.chat.completions.create( model=os.environ.get("CHAT_MODEL", "gpt-4.1-mini"), messages=[ {"role": "system", "content": REWRITE_SYSTEM}, {"role": "user", "content": wrap_data("resume_json", original.model_dump_json())}, {"role": "user", "content": wrap_data("job_description", jd[:12_000])}, ], response_format={"type": "json_object"}, temperature=0.3, max_tokens=2_500, ) proposed_raw = RewriteOut.model_validate_json(resp.choices[0].message.content) errors = fact_guard(original, proposed_raw.resume) if errors: raise HTTPException(422, {"code": "factuality_violation", "errors": errors}) pid = db.save_proposal(rid, proposed_raw.model_dump(), status=Status.pending_review) return {"proposal_id": pid, "warnings": proposed_raw.warnings, "changelog": proposed_raw.changelog} @app.post("/v1/resumes/{rid}/approve") def approve(rid: str, proposal_id: str, user=Depends(current_user)): db.apply_proposal(rid, proposal_id, reviewer=user.id) # copies JSON; sets status=approved return {"status": Status.approved} @app.get("/v1/resumes/{rid}/export") def export_pdf(rid: str, user=Depends(current_user)): row = db.get_resume(rid, owner=user.id) if row.status != Status.approved: raise HTTPException(409, "export_requires_approval") pdf = render_pdf(row.json_body) # WeasyPrint/reportlab — no LLM here return StreamingResponse(pdf, media_type="application/pdf")