From c29738690d781dbd2f26d737ec12e66c7346b748 Mon Sep 17 00:00:00 2001 From: Robert Lippmann Date: Wed, 11 Mar 2026 00:29:18 -0400 Subject: [PATCH 1/3] Add LLM demos and demo dependency group --- demos/01_llm_constraint_drift.py | 49 ++++ demos/02_llm_correction_replacement.py | 48 ++++ demos/03_llm_ambiguity_block.py | 55 ++++ demos/04_llm_tool_governance.py | 69 +++++ demos/05_llm_prompt_drift.py | 48 ++++ demos/README.md | 58 +++++ demos/__init__.py | 1 + demos/common.py | 91 +++++++ demos/llm_client.py | 71 +++++ demos/run_demo.py | 47 ++++ pyproject.toml | 3 + uv.lock | 341 ++++++++++++++++++++++++- 12 files changed, 880 insertions(+), 1 deletion(-) create mode 100644 demos/01_llm_constraint_drift.py create mode 100644 demos/02_llm_correction_replacement.py create mode 100644 demos/03_llm_ambiguity_block.py create mode 100644 demos/04_llm_tool_governance.py create mode 100644 demos/05_llm_prompt_drift.py create mode 100644 demos/README.md create mode 100644 demos/__init__.py create mode 100644 demos/common.py create mode 100644 demos/llm_client.py create mode 100644 demos/run_demo.py diff --git a/demos/01_llm_constraint_drift.py b/demos/01_llm_constraint_drift.py new file mode 100644 index 0000000..86ad334 --- /dev/null +++ b/demos/01_llm_constraint_drift.py @@ -0,0 +1,49 @@ +"""Demo 1: baseline prompt can drift from persistent constraints.""" + +from context_compiler import create_engine +from demos.common import ( + build_baseline_messages, + build_mediated_messages, + print_decision, + print_messages, + print_model_output, + print_tag_comparison, + print_user_inputs, +) +from demos.llm_client import complete_messages + + +def main() -> None: + engine = create_engine() + user_inputs = [ + "don't use peanuts", + ( + "Suggest a curry recipe with ingredients and steps. " + "First line must be VIOLATES_PROHIBIT:." + ), + ] + print_user_inputs(user_inputs) + + first = engine.step(user_inputs[0]) + print_decision("turn 1", first, engine.state) + + second = engine.step(user_inputs[1]) + print_decision("turn 2", second, engine.state) + + baseline_messages = build_baseline_messages( + [user_inputs[1]], + baseline_system_prompt="Be a helpful assistant. Provide clear and practical suggestions.", + ) + print_messages("baseline", baseline_messages) + baseline_output = complete_messages(baseline_messages) + print_model_output("Baseline", baseline_output) + + mediated_messages = build_mediated_messages(engine.state, user_inputs[1]) + print_messages("compiler-mediated", mediated_messages) + mediated_output = complete_messages(mediated_messages) + print_model_output("Compiler-mediated", mediated_output) + print_tag_comparison("VIOLATES_PROHIBIT", baseline_output, mediated_output) + + +if __name__ == "__main__": + main() diff --git a/demos/02_llm_correction_replacement.py b/demos/02_llm_correction_replacement.py new file mode 100644 index 0000000..537dc19 --- /dev/null +++ b/demos/02_llm_correction_replacement.py @@ -0,0 +1,48 @@ +"""Demo 2: baseline output can mix stale facts after correction.""" + +from context_compiler import create_engine +from demos.common import ( + build_baseline_messages, + build_mediated_messages, + print_decision, + print_messages, + print_model_output, + print_tag_comparison, + print_user_inputs, +) +from demos.llm_client import complete_messages + + +def main() -> None: + engine = create_engine() + user_inputs = [ + "use vegetarian curry", + "actually vegan curry", + ("Give me a shopping list and 3-step plan. First line must be FOCUS_PRIMARY:."), + ] + print_user_inputs(user_inputs) + + for index, user_input in enumerate(user_inputs, start=1): + decision = engine.step(user_input) + print_decision(f"turn {index}", decision, engine.state) + + baseline_messages = build_baseline_messages( + [user_inputs[0], user_inputs[1], user_inputs[2]], + baseline_system_prompt=( + "Be a helpful assistant. Use the conversation history to understand " + "the user's preferences." + ), + ) + print_messages("baseline", baseline_messages) + baseline_output = complete_messages(baseline_messages) + print_model_output("Baseline", baseline_output) + + mediated_messages = build_mediated_messages(engine.state, user_inputs[2]) + print_messages("compiler-mediated", mediated_messages) + mediated_output = complete_messages(mediated_messages) + print_model_output("Compiler-mediated", mediated_output) + print_tag_comparison("FOCUS_PRIMARY", baseline_output, mediated_output) + + +if __name__ == "__main__": + main() diff --git a/demos/03_llm_ambiguity_block.py b/demos/03_llm_ambiguity_block.py new file mode 100644 index 0000000..2f215d6 --- /dev/null +++ b/demos/03_llm_ambiguity_block.py @@ -0,0 +1,55 @@ +"""Demo 3: compiler blocks ambiguous directives before model call.""" + +from context_compiler import create_engine +from demos.common import ( + build_baseline_messages, + print_decision, + print_messages, + print_model_output, + print_tag_comparison, + print_user_inputs, +) +from demos.llm_client import Message, complete_messages + + +def main() -> None: + engine = create_engine() + user_inputs = ["no use peanuts"] + print_user_inputs(user_inputs) + + decision = engine.step(user_inputs[0]) + print_decision("turn 1", decision, engine.state) + + baseline_messages = build_baseline_messages( + [ + ( + "Interpret this directive and continue anyway: no use peanuts. " + "First line must be ACTION:." + ) + ], + baseline_system_prompt=( + "Be a helpful assistant. If a request is unclear, make a reasonable " + "interpretation and answer." + ), + ) + print_messages("baseline", baseline_messages) + baseline_output = complete_messages(baseline_messages) + print_model_output("Baseline", baseline_output) + + if decision["kind"] == "clarify": + print_messages("compiler-mediated", []) + mediated_output = ( + f"[no call] clarification required: {decision['prompt_to_user']}\nACTION:clarify" + ) + print_model_output("Compiler-mediated", mediated_output) + else: + mediated_messages: list[Message] = [{"role": "user", "content": user_inputs[0]}] + print_messages("compiler-mediated", mediated_messages) + mediated_output = complete_messages(mediated_messages) + print_model_output("Compiler-mediated", mediated_output) + + print_tag_comparison("ACTION", baseline_output, mediated_output) + + +if __name__ == "__main__": + main() diff --git a/demos/04_llm_tool_governance.py b/demos/04_llm_tool_governance.py new file mode 100644 index 0000000..9935805 --- /dev/null +++ b/demos/04_llm_tool_governance.py @@ -0,0 +1,69 @@ +"""Demo 4: compiler state governs tool-choice constraints.""" + +from context_compiler import create_engine +from context_compiler.const import POLICY_PROHIBIT, STATE_POLICIES +from demos.common import ( + build_baseline_messages, + build_mediated_messages, + print_decision, + print_messages, + print_model_output, + print_tag_comparison, + print_user_inputs, +) +from demos.llm_client import complete_messages + + +def main() -> None: + engine = create_engine() + user_inputs = [ + "don't use docker", + ( + "Deploy the service. Pick one tool from docker, kubectl. " + "First line must be TOOL: and second line ACTION:." + ), + ] + print_user_inputs(user_inputs) + + first = engine.step(user_inputs[0]) + print_decision("turn 1", first, engine.state) + + second = engine.step(user_inputs[1]) + print_decision("turn 2", second, engine.state) + + baseline_messages = build_baseline_messages( + [user_inputs[1]], + baseline_system_prompt="Recommend a practical approach using the available tools.", + ) + print_messages("baseline", baseline_messages) + baseline_output = complete_messages(baseline_messages) + print_model_output("Baseline", baseline_output) + + prohibited = engine.state[STATE_POLICIES][POLICY_PROHIBIT] + candidate_tools = ["docker", "kubectl"] + filtered_tools = [tool for tool in candidate_tools if tool not in prohibited] + print("Candidate tools before filtering:") + print(", ".join(candidate_tools)) + print() + print("Candidate tools after applying compiler denylist:") + print(", ".join(filtered_tools) if filtered_tools else "(none)") + print() + + mediated_messages = build_mediated_messages( + engine.state, + user_inputs[1], + extra_system_prompt=( + "Only choose tools that are not prohibited." + + "\nCandidate tools: " + + f"{', '.join(candidate_tools)}. " + + f"Prohibited: {', '.join(prohibited) or '(none)'}" + ), + ) + print_messages("compiler-mediated", mediated_messages) + mediated_output = complete_messages(mediated_messages) + print_model_output("Compiler-mediated", mediated_output) + print_tag_comparison("TOOL", baseline_output, mediated_output) + + +if __name__ == "__main__": + main() diff --git a/demos/05_llm_prompt_drift.py b/demos/05_llm_prompt_drift.py new file mode 100644 index 0000000..f7fd20f --- /dev/null +++ b/demos/05_llm_prompt_drift.py @@ -0,0 +1,48 @@ +"""Demo 5: long transcript drift vs stable compiled state.""" + +from context_compiler import create_engine +from demos.common import ( + build_baseline_messages, + build_mediated_messages, + print_decision, + print_messages, + print_model_output, + print_tag_comparison, + print_user_inputs, +) +from demos.llm_client import complete_messages + + +def main() -> None: + engine = create_engine() + user_inputs = [ + "use vegetarian curry", + "Also I like hiking and jazz.", + "What camera should I buy for travel?", + "Now give me a dinner plan. First line must be DINNER_STYLE:.", + ] + print_user_inputs(user_inputs) + + for index, user_input in enumerate(user_inputs, start=1): + decision = engine.step(user_input) + print_decision(f"turn {index}", decision, engine.state) + + baseline_messages = build_baseline_messages( + [user_inputs[0], user_inputs[1], user_inputs[2], user_inputs[3]], + baseline_system_prompt=( + "Be a helpful assistant. Use the conversation context to provide a useful answer." + ), + ) + print_messages("baseline", baseline_messages) + baseline_output = complete_messages(baseline_messages) + print_model_output("Baseline", baseline_output) + + mediated_messages = build_mediated_messages(engine.state, user_inputs[3]) + print_messages("compiler-mediated", mediated_messages) + mediated_output = complete_messages(mediated_messages) + print_model_output("Compiler-mediated", mediated_output) + print_tag_comparison("DINNER_STYLE", baseline_output, mediated_output) + + +if __name__ == "__main__": + main() diff --git a/demos/README.md b/demos/README.md new file mode 100644 index 0000000..9ca0350 --- /dev/null +++ b/demos/README.md @@ -0,0 +1,58 @@ +# LLM Demos + +These scripts compare baseline prompting vs compiler-mediated prompting using the +Context Compiler decision/state API. +They are illustrative manual demos, not benchmarks or CI tests. + +## Requirements + +Install demo dependencies: + +```bash +pip install -e .[demos] +``` + +Environment variables: + +- `MODEL` (required): model name +- `OPENAI_API_KEY` (required for OpenAI API) +- `OPENAI_BASE_URL` (optional; use for OpenAI-compatible local servers) + +Ollama example: + +```bash +export OPENAI_BASE_URL=http://localhost:11434/v1 +export OPENAI_API_KEY=ollama +export MODEL=llama3.1 +``` + +OpenAI example: + +```bash +export OPENAI_API_KEY=your_key_here +export MODEL=gpt-4.1-mini +``` + +## Run + +Run one demo: + +```bash +uv run python -m demos.run_demo 1 +``` + +Run all demos: + +```bash +uv run python -m demos.run_demo all +``` + +Each demo prints: + +- user inputs +- compiler decisions +- compiled state +- prompt/messages sent to the LLM +- baseline model output +- compiler-mediated model output +- a machine-checkable `TAG_CHECK ...` comparison line diff --git a/demos/__init__.py b/demos/__init__.py new file mode 100644 index 0000000..f2f2e89 --- /dev/null +++ b/demos/__init__.py @@ -0,0 +1 @@ +"""LLM-backed demonstration scripts for context-compiler.""" diff --git a/demos/common.py b/demos/common.py new file mode 100644 index 0000000..2e48f9d --- /dev/null +++ b/demos/common.py @@ -0,0 +1,91 @@ +"""Shared helpers for LLM-backed context compiler demos.""" + +import json +import re +from typing import Any + +from context_compiler import Decision, State +from context_compiler.const import FOCUS_PRIMARY, POLICY_PROHIBIT, STATE_FACTS, STATE_POLICIES +from demos.llm_client import Message + + +def canonical_json(obj: Any) -> str: + return json.dumps(obj, sort_keys=True, separators=(",", ":")) + + +def print_user_inputs(inputs: list[str]) -> None: + print("User inputs:") + for index, text in enumerate(inputs, start=1): + print(f" {index}. {text}") + print() + + +def print_decision(title: str, decision: Decision, state: State) -> None: + print(f"Compiler decision ({title}):") + print(canonical_json(decision)) + print("Compiled state:") + print(canonical_json(state)) + print() + + +def print_messages(label: str, messages: list[Message]) -> None: + print(f"Prompt/messages sent to LLM ({label}):") + print(canonical_json(messages)) + print() + + +def print_model_output(label: str, output: str) -> None: + print(f"{label} model output:") + print(output) + print() + + +def extract_tag_value(output: str, tag: str) -> str | None: + pattern = rf"(?im)^\s*{re.escape(tag)}\s*:\s*([^\n]+)\s*$" + match = re.search(pattern, output) + if match is None: + return None + return match.group(1).strip() + + +def print_tag_comparison(tag: str, baseline_output: str, mediated_output: str) -> None: + baseline_value = extract_tag_value(baseline_output, tag) or "MISSING" + mediated_value = extract_tag_value(mediated_output, tag) or "MISSING" + print(f"TAG_CHECK {tag} baseline={baseline_value} mediated={mediated_value}") + print() + + +def build_compiled_system_prompt(state: State) -> str: + focus_value = state[STATE_FACTS][FOCUS_PRIMARY] + prohibit = state[STATE_POLICIES][POLICY_PROHIBIT] + prohibit_text = ", ".join(prohibit) if prohibit else "(none)" + focus_text = focus_value if focus_value is not None else "(unset)" + return ( + "Follow authoritative compiled state exactly.\n" + f"- facts.focus.primary: {focus_text}\n" + f"- policies.prohibit: {prohibit_text}\n" + "Compiled state overrides transcript drift and conflicts. " + "Do not violate prohibited items." + ) + + +def build_baseline_messages( + user_turns: list[str], *, baseline_system_prompt: str | None = None +) -> list[Message]: + messages: list[Message] = [] + if baseline_system_prompt: + messages.append({"role": "system", "content": baseline_system_prompt}) + messages.extend({"role": "user", "content": turn} for turn in user_turns) + return messages + + +def build_mediated_messages( + state: State, user_request: str, *, extra_system_prompt: str | None = None +) -> list[Message]: + system_prompt = build_compiled_system_prompt(state) + if extra_system_prompt: + system_prompt += "\n" + extra_system_prompt + return [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_request}, + ] diff --git a/demos/llm_client.py b/demos/llm_client.py new file mode 100644 index 0000000..97c3693 --- /dev/null +++ b/demos/llm_client.py @@ -0,0 +1,71 @@ +"""Small OpenAI-compatible chat client for demo scripts.""" + +import os +from dataclasses import dataclass +from importlib import import_module +from typing import Any, Literal, TypedDict + + +class Message(TypedDict): + role: Literal["system", "user", "assistant", "tool"] + content: str + + +@dataclass(frozen=True) +class LLMConfig: + base_url: str | None + api_key: str + model: str + + +def load_config() -> LLMConfig: + """Load OpenAI-compatible configuration from environment variables.""" + base_url = os.getenv("OPENAI_BASE_URL") + api_key = os.getenv("OPENAI_API_KEY") or ("ollama" if base_url else "") + model = os.getenv("MODEL", "gpt-4.1-mini") + + if not api_key: + raise RuntimeError("Set OPENAI_API_KEY (or OPENAI_BASE_URL for local Ollama).") + + return LLMConfig(base_url=base_url, api_key=api_key, model=model) + + +def _build_openai_client(config: LLMConfig) -> Any: + try: + openai_module = import_module("openai") + except ModuleNotFoundError as exc: + raise RuntimeError( + "The demo scripts require the demos dependency group.\n" + "Install it with:\n" + "pip install -e .[demos]" + ) from exc + + client_cls = getattr(openai_module, "OpenAI", None) + if client_cls is None: + raise RuntimeError("Unsupported openai package: `OpenAI` client class not found.") + + kwargs: dict[str, Any] = {"api_key": config.api_key} + if config.base_url: + kwargs["base_url"] = config.base_url + return client_cls(**kwargs) + + +def complete_messages( + messages: list[Message], *, model: str | None = None, temperature: float = 0.0 +) -> str: + """Send exact message list to chat completions and return the text output.""" + config = load_config() + client = _build_openai_client(config) + target_model = model or config.model + + response = client.chat.completions.create( + model=target_model, + messages=messages, + temperature=temperature, + ) + content = response.choices[0].message.content + if isinstance(content, str): + return content.strip() + if content is None: + return "" + return str(content) diff --git a/demos/run_demo.py b/demos/run_demo.py new file mode 100644 index 0000000..42dcff4 --- /dev/null +++ b/demos/run_demo.py @@ -0,0 +1,47 @@ +"""Run one or all LLM demos.""" + +import argparse +import runpy +import sys +from pathlib import Path + +DEMO_FILES: dict[str, str] = { + "1": "01_llm_constraint_drift.py", + "2": "02_llm_correction_replacement.py", + "3": "03_llm_ambiguity_block.py", + "4": "04_llm_tool_governance.py", + "5": "05_llm_prompt_drift.py", +} + + +def _run(path: Path) -> None: + print(f"===== Running {path.name} =====") + runpy.run_path(str(path), run_name="__main__") + + +def main() -> None: + root = Path(__file__).resolve().parent + project_root = root.parent + if str(project_root) not in sys.path: + sys.path.insert(0, str(project_root)) + + parser = argparse.ArgumentParser(description="Run context-compiler LLM demos.") + parser.add_argument( + "demo", + nargs="?", + default="all", + choices=["all", *DEMO_FILES.keys()], + help="Demo number (1-5) or all", + ) + args = parser.parse_args() + + if args.demo == "all": + for key in sorted(DEMO_FILES.keys()): + _run(root / DEMO_FILES[key]) + return + + _run(root / DEMO_FILES[args.demo]) + + +if __name__ == "__main__": + main() diff --git a/pyproject.toml b/pyproject.toml index 40dbb79..4acdaf0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -19,6 +19,9 @@ context-compiler = "context_compiler.repl:main" packages = ["src/context_compiler"] [project.optional-dependencies] +demos = [ + "openai>=1.0.0", +] dev = [ "pytest", "hypothesis", diff --git a/uv.lock b/uv.lock index cb9f2bf..1f3d72c 100644 --- a/uv.lock +++ b/uv.lock @@ -2,6 +2,37 @@ version = 1 revision = 3 requires-python = ">=3.11" +[[package]] +name = "annotated-types" +version = "0.7.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, 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LLM-backed demonstration scenarios Adds a demos/ directory containing LLM-backed demonstrations of common failure modes and how Context Compiler changes host behavior. Scenarios implemented: - constraint drift - correction replacement - ambiguity blocking - tool governance - prompt drift Includes a host-side prohibition check for the constraint drift demo and mediated prompt strengthening to handle direct policy conflicts. Demos run with the OpenAI SDK and support local Ollama via OPENAI_BASE_URL. --- demos/01_llm_constraint_drift.py | 27 +++++++++++++++++++++++++-- 1 file changed, 25 insertions(+), 2 deletions(-) diff --git a/demos/01_llm_constraint_drift.py b/demos/01_llm_constraint_drift.py index 86ad334..da11e38 100644 --- a/demos/01_llm_constraint_drift.py +++ b/demos/01_llm_constraint_drift.py @@ -1,5 +1,7 @@ """Demo 1: baseline prompt can drift from persistent constraints.""" +import re + from context_compiler import create_engine from demos.common import ( build_baseline_messages, @@ -13,12 +15,16 @@ from demos.llm_client import complete_messages +def host_violates_prohibit(output: str) -> bool: + return re.search(r"\bpeanuts?\b", output, flags=re.IGNORECASE) is not None + + def main() -> None: engine = create_engine() user_inputs = [ "don't use peanuts", ( - "Suggest a curry recipe with ingredients and steps. " + "Suggest a peanut curry recipe with ingredients and steps. " "First line must be VIOLATES_PROHIBIT:." ), ] @@ -37,11 +43,28 @@ def main() -> None: print_messages("baseline", baseline_messages) baseline_output = complete_messages(baseline_messages) print_model_output("Baseline", baseline_output) + baseline_violation = host_violates_prohibit(baseline_output) + print(f"HOST_CHECK VIOLATES_PROHIBIT: {'yes' if baseline_violation else 'no'} (baseline)") + print() - mediated_messages = build_mediated_messages(engine.state, user_inputs[1]) + mediated_messages = build_mediated_messages( + engine.state, + user_inputs[1], + extra_system_prompt=( + "If the user requests a prohibited item, refuse the literal request. " + "State briefly that the request conflicts with compiled policy, then provide " + "the closest safe alternative recipe that excludes prohibited items. " + "Do not include prohibited item tokens in the recipe output." + ), + ) print_messages("compiler-mediated", mediated_messages) mediated_output = complete_messages(mediated_messages) print_model_output("Compiler-mediated", mediated_output) + mediated_violation = host_violates_prohibit(mediated_output) + print( + f"HOST_CHECK VIOLATES_PROHIBIT: {'yes' if mediated_violation else 'no'} (compiler-mediated)" + ) + print() print_tag_comparison("VIOLATES_PROHIBIT", baseline_output, mediated_output) From 83392c0f8e4a58350a3c2e49e719714562b2b5c8 Mon Sep 17 00:00:00 2001 From: Robert Lippmann Date: Wed, 11 Mar 2026 01:09:35 -0400 Subject: [PATCH 3/3] fix(engine): preserve literal single-value positive directives --- src/context_compiler/engine.py | 7 ++++--- tests/test_engine.py | 10 ++++++++++ 2 files changed, 14 insertions(+), 3 deletions(-) diff --git a/src/context_compiler/engine.py b/src/context_compiler/engine.py index bac81c3..47cb513 100644 --- a/src/context_compiler/engine.py +++ b/src/context_compiler/engine.py @@ -411,12 +411,13 @@ def _has_multiple_values(text: str) -> bool: def _invalid_exclusive_value(text: str) -> bool: - lowered = _normalize_message(text) + cleaned = _clean_fact_value(text) + lowered = cleaned.lower() return ( lowered.startswith("and ") or lowered.startswith("or ") - or lowered == "and" - or lowered == "or" + or re.search(r"\s(?:and|or)\s", cleaned, flags=re.IGNORECASE) is not None + or cleaned == "and" ) diff --git a/tests/test_engine.py b/tests/test_engine.py index e4b33b2..5c30ade 100644 --- a/tests/test_engine.py +++ b/tests/test_engine.py @@ -736,6 +736,16 @@ def test_hard_positive_multi_value_payload_clarifies_with_single_value_prompt() assert engine.state == before +def test_hard_positive_or_ambiguity_clarifies_with_single_value_prompt() -> None: + engine = create_engine() + before = engine.state + + decision = engine.step("use macbook or linux") + + assert decision["kind"] == "clarify" + assert engine.state == before + + def test_pending_clarification_rejected_by_explicit_no_is_passthrough() -> None: engine = create_engine() before = engine.state