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The claude-cli backend passed the extraction schema via --system-prompt with
only the raw file dump in the user turn, assuming a replacement system prompt
is the model's sole authority. Claude Code >= ~2.1 (verified on 2.1.197) does
not honour that: it still layers in the local coding-agent context
(CLAUDE.md/AGENTS.md in cwd, skills, MCP) and, given a user turn that is just a
file with no request, replies conversationally ("I see the file, but there's no
actual request attached"). That prose parses to zero nodes/edges, so
_response_is_hollow flags it as truncation and the adaptive-retry path bisects
the chunk indefinitely (94 -> 47 -> 23 -> ...), never converging and never
writing graph.json.
Move the full extraction schema plus an explicit imperative into the user turn
and drop --system-prompt, so the CLI emits the JSON object directly. The
<untrusted_source> prompt-injection guardrails are carried verbatim; model
override, --add-dir image handling, timeout, and token accounting are untouched.
156 lines
6.0 KiB
Python
156 lines
6.0 KiB
Python
"""Tests for `_parse_llm_json` robustness and the `_call_claude_cli`
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subprocess argv shape introduced in the hollow-response fix.
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These tests cover:
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- The four parser failure modes described in PR #1062
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- Extraction instructions delivered in the user turn (Claude Code >= 2.1)
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- The GRAPHIFY_CLAUDE_CLI_MODEL env-var passthrough
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"""
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from __future__ import annotations
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import json
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from unittest.mock import patch
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import pytest
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from graphify import llm
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# ---------- _parse_llm_json: the four canonical failure modes ----------
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def test_preamble_then_fence_is_parsed():
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"""Claude often prefixes the JSON with a short preamble before the
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```json fence. The original parser only stripped fences at offset 0,
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so any preamble caused json.loads to fail and the chunk to be
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dropped as a hollow response. The robust parser handles fences
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anywhere in the text."""
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raw = (
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"Here are the extracted entities:\n\n"
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'```json\n{"nodes": [{"id": "a"}], "edges": []}\n```'
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)
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result = llm._parse_llm_json(raw)
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assert result["nodes"] == [{"id": "a"}]
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assert result["edges"] == []
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def test_prose_wrapped_json_without_fence_is_parsed():
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"""Some models return prose around bare JSON with no markdown fence.
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The balanced-brace fallback extracts the first complete object."""
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raw = (
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'The extracted graph is {"nodes": [{"id": "b"}], "edges": []}. '
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"Hope this helps!"
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)
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result = llm._parse_llm_json(raw)
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assert result["nodes"] == [{"id": "b"}]
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def test_raw_json_still_works():
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"""Regression: clean JSON input (the original happy path) must keep
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parsing exactly as before."""
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raw = '{"nodes": [], "edges": [], "hyperedges": []}'
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result = llm._parse_llm_json(raw)
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assert result == {"nodes": [], "edges": [], "hyperedges": []}
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def test_total_refusal_returns_empty_fragment():
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"""When the model refuses or returns unrelated prose, the parser
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must degrade gracefully — return the empty fragment so the hollow
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detector takes over, never raise."""
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raw = "I cannot extract structured data from this content."
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result = llm._parse_llm_json(raw)
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assert result == {"nodes": [], "edges": [], "hyperedges": []}
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# ---------- _parse_llm_json: secondary cases worth pinning ----------
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def test_fence_with_uppercase_language_tag():
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raw = '```JSON\n{"nodes": [{"id": "x"}], "edges": []}\n```'
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result = llm._parse_llm_json(raw)
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assert result["nodes"] == [{"id": "x"}]
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def test_fence_without_closing_backticks():
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"""Truncated response: the model started the fence but ran out of
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tokens before closing it. We should still recover the JSON body."""
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raw = '```json\n{"nodes": [{"id": "y"}], "edges": []}'
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result = llm._parse_llm_json(raw)
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assert result["nodes"] == [{"id": "y"}]
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def test_empty_response_returns_empty_fragment():
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assert llm._parse_llm_json("") == {"nodes": [], "edges": [], "hyperedges": []}
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# ---------- _call_claude_cli: argv shape ----------
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def _make_envelope(result_obj: dict) -> str:
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return json.dumps({
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"type": "result",
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"subtype": "success",
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"is_error": False,
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"result": json.dumps(result_obj),
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"usage": {"input_tokens": 1, "output_tokens": 1,
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"cache_creation_input_tokens": 0, "cache_read_input_tokens": 0},
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"modelUsage": {"claude-opus-4-7": {}},
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"stop_reason": "end_turn",
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})
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@patch("shutil.which", return_value="/usr/local/bin/claude")
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@patch("subprocess.run")
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def test_instructions_ride_in_user_turn_not_system_prompt(mock_run, _which):
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"""Extraction instructions must be delivered in the user turn, not via
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--system-prompt.
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History: the original hollow-response cause was --append-system-prompt
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layering graphify's prompt on top of Claude Code's default agent prompt;
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the first fix switched to --system-prompt (replace). But newer Claude Code
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CLIs (>= ~2.1) don't treat --system-prompt as the sole authority — they
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keep the coding-agent context and reply conversationally to a bare file
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dump, which parses to zero nodes and gets bisected forever. The instructions
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now ride in the user turn (stdin) and neither system-prompt flag is used."""
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mock_run.return_value.returncode = 0
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mock_run.return_value.stdout = _make_envelope({"nodes": [], "edges": [], "hyperedges": []})
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mock_run.return_value.stderr = ""
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llm._call_claude_cli("payload")
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argv = mock_run.call_args.args[0]
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assert "--system-prompt" not in argv, (
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f"--system-prompt is ignored by Claude Code >= 2.1; argv: {argv}"
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)
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assert "--append-system-prompt" not in argv
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sent = mock_run.call_args.kwargs["input"]
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assert "graphify semantic extraction agent" in sent
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assert "output ONLY the JSON object" in sent
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assert "payload" in sent
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@patch("shutil.which", return_value="/usr/local/bin/claude")
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@patch("subprocess.run")
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def test_model_env_var_adds_model_flag(mock_run, _which, monkeypatch):
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"""GRAPHIFY_CLAUDE_CLI_MODEL must be forwarded to claude -p --model."""
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monkeypatch.setenv("GRAPHIFY_CLAUDE_CLI_MODEL", "haiku")
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mock_run.return_value.returncode = 0
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mock_run.return_value.stdout = _make_envelope({"nodes": [], "edges": [], "hyperedges": []})
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mock_run.return_value.stderr = ""
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llm._call_claude_cli("payload")
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argv = mock_run.call_args.args[0]
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assert "--model" in argv
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assert argv[argv.index("--model") + 1] == "haiku"
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@patch("shutil.which", return_value="/usr/local/bin/claude")
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@patch("subprocess.run")
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def test_no_model_flag_when_env_var_unset(mock_run, _which, monkeypatch):
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"""Default behaviour: when the env var is not set, --model is not
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added so claude-cli's own default kicks in."""
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monkeypatch.delenv("GRAPHIFY_CLAUDE_CLI_MODEL", raising=False)
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mock_run.return_value.returncode = 0
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mock_run.return_value.stdout = _make_envelope({"nodes": [], "edges": [], "hyperedges": []})
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mock_run.return_value.stderr = ""
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llm._call_claude_cli("payload")
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argv = mock_run.call_args.args[0]
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assert "--model" not in argv
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