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character, {{character}}, knows about. + + Here are a few rules: + 1. A character knows about all events that they do. + 2. If a character is in a certain room/location, that character knows about all other events that happens in the room. This includes other characters leaving or exiting the location, the locations of objects in that location, and whether somebody moves an object to another place. + 3. If a character leaves a location, and is NOT in that location, they no longer know about any events that happen within that location. However, they can re-enter the location. + + Story: {{story}} + What events does {{character}} know about? Only output the events according to the above rules, do not provide an explanation. [/INST]""" # noqa + +@outlines.prompt +def simulation(events: list, name: str, question: str) -> None: + """[INST] {% for event in events %} + {{event}} + {% endfor %} + You are {{name}}. + Based on the above information, answer the following question: + {{question}} + You must choose one of the above choices, do not say there is not enough information. Answer with a single word, do not output anything else. [/INST]""" # noqa +``` + +### JSON Structured Generation + +Outlines guarantees that the LLM will return a valid JSON object, which we can specify as a Pydantic model. + +We will need two Pydantic models for SimToM, one for each prompt: + +```python +from pydantic import BaseModel, Field +from typing import List + + +class PerspectiveTaking(BaseModel): + """This is for the first prompt.""" + character: str = Field(description="The character we extract the events for.") + events: List[str] = Field(description="All events that the character knows about.") + + +class Simulation(BaseModel): + """This is for the second prompt.""" + answer: str +``` + +### Calling an LLM + +Let's try SimToM with an example from the ToMI dataset: + +```python +story = """ +1 Aria entered the front_yard. +2 Aiden entered the front_yard. +3 The grapefruit is in the green_bucket. +4 Aria moved the grapefruit to the blue_container. +5 Aiden exited the front_yard. +6 Noah entered the playroom. +""" +question = "7 Where was the grapefruit at the beginning?" +character = "Aria" +``` + +We load `Mistral-7B-Instruct-v0.3`, create the prompt using the template we defined earlier, and generate a structured response. As a reminder, the goal of the first call is to get all the events a character, `Aria`, knows about. + +```python +# Load an LLM from Hugging Face +MODEL_NAME = "mistral-community/Mistral-7B-Instruct-v0.3" +model = outlines.models.transformers(MODEL_NAME, device="cuda") + +perspective_prompt = perspective_taking(story=story, character=character) + +# Call Mistral 7B with the first prompt +generator = outlines.generate.json(model, PerspectiveTaking) +perspective = generator(perspective_prompt) + +print(perspective.model_dump()) +# {'character': 'Aria', 'events': ['1 Aria entered the front_yard.', '3 The grapefruit is in the green_bucket.', '4 Aria moved the grapefruit to the blue_container.']} +``` + +Not bad! We will now generate the second prompt with those events. + +```python +sim_prompt = simulation(events=perspective.events, name=character, question=question) + +# Call Mistral 7B with the second prompt +generator = outlines.generate.json(model, Simulation) +result = generator(sim_prompt) + +print(result.model_dump()) +# {'answer': 'green_bucket'} +``` + +And this is it! SimToM could be useful in agentic workflows, where agents must act based on what they know, not all available information. One caveat of SimToM is that the perspective-taking step can sometimes remove important information, leading to wrong results. As the authors note in their paper, it can still be a simple and effective baseline for evaluating LLMs on Theory of Mind reasoning tasks. From cbe82a2e07a46a1382fa8a3e5a50c1733529e46c Mon Sep 17 00:00:00 2001 From: Kostas Stathoulopoulos Date: Sun, 23 Jun 2024 14:50:19 +0100 Subject: [PATCH 2/3] Add recipe to the index --- docs/cookbook/index.md | 1 + docs/cookbook/simtom.md | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/cookbook/index.md b/docs/cookbook/index.md index 6abe1416c..5e84cabab 100644 --- a/docs/cookbook/index.md +++ b/docs/cookbook/index.md @@ -5,3 +5,4 @@ - [Dating Profile](dating_profiles.md): Build dating profiles from descriptions using prompt templating and JSON-structured generation. - [Chain Of Density](chain_of_density.md): Summarize documents using chain of density prompting and JSON-structured generation. - [Playing Chess](models_playing_chess.md): Make Mistral-7B play chess against itself using regex-structured generation. +- [SimToM](simtom.md): Improve LLMs' Theory of Mind capabilities with perspective-taking prompting and JSON-structured generation. diff --git a/docs/cookbook/simtom.md b/docs/cookbook/simtom.md index 44c7c1473..aa96005b4 100644 --- a/docs/cookbook/simtom.md +++ b/docs/cookbook/simtom.md @@ -126,4 +126,4 @@ print(result.model_dump()) # {'answer': 'green_bucket'} ``` -And this is it! SimToM could be useful in agentic workflows, where agents must act based on what they know, not all available information. One caveat of SimToM is that the perspective-taking step can sometimes remove important information, leading to wrong results. As the authors note in their paper, it can still be a simple and effective baseline for evaluating LLMs on Theory of Mind reasoning tasks. +And this is it! SimToM could be useful in agentic workflows, where agents must act based on what they know, not all available information. One caveat of SimToM is that the perspective-taking step may remove important information, leading to wrong results. As the authors note in their paper, it can feature as a simple and effective baseline for evaluating LLMs on Theory of Mind reasoning tasks. From cc5e6bce612633aaf476b46756e69769c5895f35 Mon Sep 17 00:00:00 2001 From: Kostas Stathoulopoulos Date: Sun, 23 Jun 2024 14:53:59 +0100 Subject: [PATCH 3/3] Add simtom to the mkdocs config --- mkdocs.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/mkdocs.yml b/mkdocs.yml index 2cdbb88a7..12e79fd75 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -105,6 +105,7 @@ nav: - Generate synthetic data: cookbook/dating_profiles.md - Summarize a document: cookbook/chain_of_density.md - Playing chess: cookbook/models_playing_chess.md + - Perspective-taking prompting: cookbook/simtom.md - Run on the cloud: - BentoML: cookbook/deploy-using-bentoml.md - Cerebrium: cookbook/deploy-using-cerebrium.md