(self, profile: Profile, memory: Memory, practice: dict[str, Any], step: int)
| 14 | self.llm = llm or LLMClient() |
| 15 | |
| 16 | def simulate_practice(self, profile: Profile, memory: Memory, practice: dict[str, Any], step: int) -> dict[str, Any]: |
| 17 | true_concept = normalize_concept(practice["know_name"]) |
| 18 | short_memory = memory.retrieve_short() |
| 19 | long_memory = memory.retrieve_long(current_concept=true_concept, time_step=step) |
| 20 | options = self._concept_options(memory, true_concept, seed=step + memory.student_id) |
| 21 | |
| 22 | system_prompt = profile.build_prompt() + "\nThe information above is your # profile #." |
| 23 | user_prompt = self._build_action_prompt(practice, short_memory, long_memory, options) |
| 24 | response = self.llm.call([ |
| 25 | {"role": "system", "content": system_prompt}, |
| 26 | {"role": "user", "content": user_prompt}, |
| 27 | ]) |
| 28 | parsed = self._parse_tasks(response) |
| 29 | |
| 30 | task_scores = self._score_tasks(practice, parsed) |
| 31 | corrective = memory.reflect_corrective(practice, parsed) |
| 32 | reflection = self.llm.call([ |
| 33 | {"role": "system", "content": system_prompt}, |
| 34 | {"role": "user", "content": Memory.reflection_instruction(corrective)}, |
| 35 | ]) |
| 36 | |
| 37 | record = [practice.get("exer_content", ""), true_concept, int(practice.get("score", 0)), 1] |
| 38 | if memory is not None: |
| 39 | memory.reinforce(record) |
| 40 | memory.update_practiced_knowledge(true_concept) |
| 41 | memory.write_long_summary(reflection) |
| 42 | memory.forget(step) |
| 43 | |
| 44 | return { |
| 45 | "exercise_id": practice.get("exer_id"), |
| 46 | "true_score": int(practice.get("score", 0)), |
| 47 | "true_concept": true_concept, |
| 48 | "concept_options": options, |
| 49 | "prompt": user_prompt, |
| 50 | "raw_response": response, |
| 51 | "parsed_response": parsed, |
| 52 | "task_scores": task_scores, |
| 53 | "reflection": reflection, |
| 54 | } |
| 55 | |
| 56 | def _concept_options(self, memory: Memory, true_concept: str, seed: int) -> list[str]: |
| 57 | distractors = memory.relation_graph.sample_distractors(true_concept, k=2, seed=seed) |
no test coverage detected