microsoft/TypeAgent
Publicmirrored fromhttps://github.com/microsoft/TypeAgentAvailable
python/nprData/prompts.py
141lines · modecode
| 1 | # Copyright (c) Microsoft Corporation and Henry Lucco. |
| 2 | # Licensed under the MIT License. |
| 3 | |
| 4 | typeagent_entity_extraction_system = """ |
| 5 | You are a service that extracts all entities and actions from a conversation passage into a JSON object of type KnowledgeResponsea according to the following TypeScript definitions: |
| 6 | export type Quantity = { |
| 7 | amount: number; |
| 8 | units: string; |
| 9 | }; |
| 10 | |
| 11 | export type Value = string | number | boolean | Quantity; |
| 12 | |
| 13 | export type Facet = { |
| 14 | name: string; |
| 15 | // Very concise values. |
| 16 | value: Value; |
| 17 | }; |
| 18 | |
| 19 | // Specific, tangible people, places, institutions or things only |
| 20 | export type ConcreteEntity = { |
| 21 | // the name of the entity or thing such as "Bach", "Great Gatsby", "frog" or "piano" |
| 22 | name: string; |
| 23 | // the types of the entity such as "speaker", "person", "artist", "animal", "object", "instrument", "school", "room", "museum", "food" etc. |
| 24 | // An entity can have multiple types; entity types should be single words |
| 25 | type: string[]; |
| 26 | // A specific, inherent, defining, or non-immediate facet of the entity such as "blue", "old", "famous", "sister", "aunt_of", "weight: 4 kg" |
| 27 | // trivial actions or state changes are not facets |
| 28 | // facets are concise "properties" |
| 29 | facets?: Facet[]; |
| 30 | }; |
| 31 | |
| 32 | export type ActionParam = { |
| 33 | name: string; |
| 34 | value: Value; |
| 35 | }; |
| 36 | |
| 37 | export type VerbTense = "past" | "present" | "future"; |
| 38 | |
| 39 | export type Action = { |
| 40 | // Each verb is typically a word not a phrase; parse the verb phrase and put the object into the objectEntityName field |
| 41 | verbs: string[]; |
| 42 | verbTense: VerbTense; |
| 43 | // the subject of "mary ate pie" is mary |
| 44 | subjectEntityName: string | "none"; |
| 45 | // the object of the verb for example the object of "mary ate pie" is pie |
| 46 | objectEntityName: string | "none"; |
| 47 | // the indirect object of "mary gave the pie to mom" is mom |
| 48 | indirectObjectEntityName: string | "none"; |
| 49 | params?: (string | ActionParam)[]; |
| 50 | // If the action implies this additional facet or property of the subjectEntity, such as hobbies, activities, interests, personality |
| 51 | subjectEntityFacet?: Facet | undefined; |
| 52 | }; |
| 53 | |
| 54 | // Detailed and comprehensive knowledge response |
| 55 | export type KnowledgeResponse = { |
| 56 | entities: ConcreteEntity[]; |
| 57 | // The 'subjectEntityName' and 'objectEntityName' must correspond to the 'name' of an entity listed in the 'entities' array. |
| 58 | actions: Action[]; |
| 59 | // Detailed, descriptive topics and keywords. Each topic is a string; topics don't have object structure like entities and actions. |
| 60 | topics: string[]; |
| 61 | }; |
| 62 | The following is the conversation passage: |
| 63 | """ |
| 64 | |
| 65 | def typeagent_entity_extraction_user(passage: str): |
| 66 | return f""" |
| 67 | {passage} |
| 68 | The following is a comprehensive set of entities, actions, and topics extracted from the conversation passage above, expressed as a JSON object of type KnowledgeResponse with 2 spaces of indentation and no properties with the value undefined: |
| 69 | """ |
| 70 | |
| 71 | def typeagent_entity_extraction_system_full(passage: str): |
| 72 | return """ |
| 73 | You are a service that extracts all entities and actions from a conversation passage into a JSON object of type KnowledgeResponsea according to the following TypeScript definitions: |
| 74 | export type Quantity = { |
| 75 | amount: number; |
| 76 | units: string; |
| 77 | }; |
| 78 | |
| 79 | export type Value = string | number | boolean | Quantity; |
| 80 | |
| 81 | export type Facet = { |
| 82 | name: string; |
| 83 | // Very concise values. |
| 84 | value: Value; |
| 85 | }; |
| 86 | |
| 87 | // Specific, tangible people, places, institutions or things only |
| 88 | export type ConcreteEntity = { |
| 89 | // the name of the entity or thing such as "Bach", "Great Gatsby", "frog" or "piano" |
| 90 | name: string; |
| 91 | // the types of the entity such as "speaker", "person", "artist", "animal", "object", "instrument", "school", "room", "museum", "food" etc. |
| 92 | // An entity can have multiple types; entity types should be single words |
| 93 | type: string[]; |
| 94 | // A specific, inherent, defining, or non-immediate facet of the entity such as "blue", "old", "famous", "sister", "aunt_of", "weight: 4 kg" |
| 95 | // trivial actions or state changes are not facets |
| 96 | // facets are concise "properties" |
| 97 | facets?: Facet[]; |
| 98 | }; |
| 99 | |
| 100 | export type ActionParam = { |
| 101 | name: string; |
| 102 | value: Value; |
| 103 | }; |
| 104 | |
| 105 | export type VerbTense = "past" | "present" | "future"; |
| 106 | |
| 107 | export type Action = { |
| 108 | // Each verb is typically a word not a phrase; parse the verb phrase and put the object into the objectEntityName field |
| 109 | verbs: string[]; |
| 110 | verbTense: VerbTense; |
| 111 | // the subject of "mary ate pie" is mary |
| 112 | subjectEntityName: string | "none"; |
| 113 | // the object of the verb for example the object of "mary ate pie" is pie |
| 114 | objectEntityName: string | "none"; |
| 115 | // the indirect object of "mary gave the pie to mom" is mom |
| 116 | indirectObjectEntityName: string | "none"; |
| 117 | params?: (string | ActionParam)[]; |
| 118 | // If the action implies this additional facet or property of the subjectEntity, such as hobbies, activities, interests, personality |
| 119 | subjectEntityFacet?: Facet | undefined; |
| 120 | }; |
| 121 | |
| 122 | // Detailed and comprehensive knowledge response |
| 123 | export type KnowledgeResponse = { |
| 124 | entities: ConcreteEntity[]; |
| 125 | // The 'subjectEntityName' and 'objectEntityName' must correspond to the 'name' of an entity listed in the 'entities' array. |
| 126 | actions: Action[]; |
| 127 | // Detailed, descriptive topics and keywords. Each topic is a string; topics don't have object structure like entities and actions. |
| 128 | topics: string[]; |
| 129 | }; |
| 130 | The following is the conversation passage: |
| 131 | """ + f""" |
| 132 | {passage} |
| 133 | The following is a comprehensive set of entities, actions, and topics extracted from the conversation passage above, expressed as a JSON object of type KnowledgeResponse with 2 spaces of indentation and no properties with the value undefined: |
| 134 | """ |
| 135 | |
| 136 | def generic_chunk_prompt(content: str): |
| 137 | return f""" |
| 138 | You are a service that generates a chunk of text from a conversation passage. The conversation passage is the following: |
| 139 | {content} |
| 140 | Generate a chunk of text that summarizes the conversation passage. |
| 141 | """ |