hangshuo652
bc1d56d1a4
P0.6: gcov infrastructure P1: extract_structure output expansion (11 new feature fields) P2: Confusion group rule engine (8 pairs + contradiction + backtrack) P3: 4-factor confidence calculation + quality gate update P4: 33+2 COBOL program type test samples (22 files, 7 categories) P5: parametrized/ test data generation engine P6: japanese_data.py lookup tables P7-10: Type-specific test suites (~159 parametrized tests) P11: Full classification pipeline (classify_program) + orchestrator integration P12: Documentation (module-interfaces, test-plan v3.0, coverage-matrix) Architecture decisions: - classification_pipeline/ merged to hina/pipeline/ - parametrized/ as independent module - japanese_data.py as root-level file - hina/__all__ only exports classify_program() Co-Authored-By: Claude <noreply@anthropic.com>
18 lines
613 B
Python
18 lines
613 B
Python
import json, os, sys
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sys.path.insert(0, ".")
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os.environ["LLM_API_KEY"] = "sk-ca4961087c7f4aefa8ed0fc6f3d02329"
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os.environ["LLM_API_BASE"] = "https://api.deepseek.com/v1"
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from agents.llm import LLMClient
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import time
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c = LLMClient(model="deepseek-chat", timeout=30)
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t0 = time.time()
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r = c.call([
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{"role":"system","content":"Parse this COBOL COPYBOOK into JSON: {\"fields\":[{\"name\":\"...\",\"level\":N,\"pic\":\"...\",\"usage\":\"DISPLAY|COMP-3\",\"length\":N}]}"},
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{"role":"user","content": open("uploads/ec17bf32/copybook.cpy").read()}
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])
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print(f"LLM call OK ({time.time()-t0:.1f}s)")
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print(r[:500])
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