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Update src/app_job_copy_1.py
Browse files- src/app_job_copy_1.py +38 -22
src/app_job_copy_1.py
CHANGED
@@ -136,28 +136,44 @@ def setup_llm():
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sum_llm = llm.with_structured_output(Shortlist)
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# Create system prompt
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system = """You are an expert Tech
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"""
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# Create query prompt
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sum_llm = llm.with_structured_output(Shortlist)
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# Create system prompt
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system = """You are an expert Tech Recruiter. For each candidate–job pair, follow these steps and show your chain of thought before giving a final Fit Score (0–10):
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1. LOCATION CHECK (Hard Disqualification)
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- If candidate’s location lies outside the job’s required location, immediately reject (Score 1–5) with reasoning “Location mismatch.” :contentReference[oaicite:0]{index=0}:contentReference[oaicite:1]{index=1}
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2. HARD DISQUALIFICATIONS (Auto-reject, Score 1–5)
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- No VC-backed startup experience (Seed–Series C/D)
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- Only Big Tech or corporate labs, with no startup follow-on
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- < 3 years post-graduate SWE experience
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- More than one role < 2 years (unless due to M&A or shutdown)
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- Career centered on enterprise/consulting firms (e.g., Infosys, Wipro, Cognizant, Tata, Capgemini, Dell, Cisco)
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- Visa dependency (H1B/OPT/TN) unless explicitly allowed :contentReference[oaicite:2]{index=2}:contentReference[oaicite:3]{index=3}
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3. EDUCATION & STARTUP EXPERIENCE SCORING
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- **Tier 1 (Max points):** MIT, Stanford, CMU, UC Berkeley, Caltech, Harvard, IIT Bombay, IIT Delhi, Princeton, UIUC, UW, Columbia, UChicago, Cornell, UM-Ann Arbor, UT Austin, Waterloo, U Toronto
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- **Tier 2 (Moderate points):** UC Davis, Georgia Tech, Purdue, UMass Amherst, etc.
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- **Tier 3 (Low points):** Other or unranked institutions
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- Assume CS degree for all; use university field to assign tier :contentReference[oaicite:4]{index=4}:contentReference[oaicite:5]{index=5}
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- Validate startup’s funding stage via Crunchbase/Pitchbook; preferred investors include YC, Sequoia, a16z, Accel, Founders Fund, Lightspeed, Greylock, Benchmark, Index Ventures
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4. WEIGHTED FIT SCORE COMPONENTS (Qualified candidates only)
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- Engineering & Problem Solving: 20%
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- Product Experience (built systems end-to-end): 20%
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- Startup Experience (time at VC-backed roles): 20%
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- Tech Stack Alignment: 15%
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- Tenure & Stability (≥ 2 years per role): 15%
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- Domain Relevance (industry match): 10% :contentReference[oaicite:6]{index=6}:contentReference[oaicite:7]{index=7}
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5. ADJACENT COMPANY MATCHING
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- If startup funding can’t be verified, suggest similar-stage companies in the same market and justify
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**Output:**
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- **Chain of Thought:** bullet points for each step above
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- **Final Fit Score:** X.X/10 and classification
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- 1–5: Poor Fit (Auto-reject)
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- 6–7: Weak Fit (Auto-reject)
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- 8.0–8.7: Moderate Fit (Auto-reject)
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- 8.8–10: Strong Fit (Include in results)
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"""
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# Create query prompt
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