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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,22 +1,26 @@ | ||
| { | ||
| "name": "@digdir/assistant-lib", | ||
| "private": true, | ||
| "version": "1.0.0", | ||
| "description": "Core assistant library", | ||
| "main": "dist/src/index.js", | ||
| "license": "MIT", | ||
| "dependencies": { | ||
| "@azure/openai": "^1.0.0-beta.11", | ||
| "@instructor-ai/instructor": "^0.0.7", | ||
| "@supabase/supabase-js": "^2.39.7", | ||
| "axios": "^1.6.7", | ||
| "dataclass": "^2.1.1", | ||
| "js-yaml": "^4.1.0", | ||
| "lodash": "^4.17.21", | ||
| "openai": "^4.28.0", | ||
| "remeda": "^1.44.1", | ||
| "typesense": "^1.7.2", | ||
| "zod": "^3.22.4", | ||
| "zod-to-json-schema": "^3.22.4" | ||
| } | ||
| "name": "@digdir/assistant-lib", | ||
| "private": true, | ||
| "version": "1.0.0", | ||
| "description": "Core assistant library", | ||
| "main": "dist/src/index.js", | ||
| "license": "MIT", | ||
| "scripts": { | ||
| "codestyle:check": "prettier src/ --check", | ||
| "codestyle:fix": "prettier src/ --write" | ||
| }, | ||
| "dependencies": { | ||
| "@azure/openai": "^1.0.0-beta.11", | ||
| "@instructor-ai/instructor": "^0.0.7", | ||
| "@supabase/supabase-js": "^2.39.7", | ||
| "axios": "^1.6.7", | ||
| "dataclass": "^2.1.1", | ||
| "js-yaml": "^4.1.0", | ||
| "lodash": "^4.17.21", | ||
| "openai": "^4.28.0", | ||
| "remeda": "^1.44.1", | ||
| "typesense": "^1.7.2", | ||
| "zod": "^3.22.4", | ||
| "zod-to-json-schema": "^3.22.4" | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,34 +1,35 @@ | ||
| import { envVar } from '../general'; | ||
|
|
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| import { envVar } from "../general"; | ||
|
|
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| type TypesenseNodeConfig = { | ||
| host: string; | ||
| port: number; | ||
| protocol: string; | ||
| host: string; | ||
| port: number; | ||
| protocol: string; | ||
| }; | ||
|
|
||
| type TypesenseServiceConfig = { | ||
| nodes: TypesenseNodeConfig[] | ||
| connectionTimeoutSec: number; | ||
| apiKey: string; | ||
| docsCollection: string; | ||
| docsSearchPhraseCollection: string; | ||
| nodes: TypesenseNodeConfig[]; | ||
| connectionTimeoutSec: number; | ||
| apiKey: string; | ||
| docsCollection: string; | ||
| docsSearchPhraseCollection: string; | ||
| }; | ||
|
|
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|
|
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| export function typesenseConfig(): TypesenseServiceConfig { | ||
|
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|
|
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| const cfg: TypesenseServiceConfig = { | ||
| nodes: [{ | ||
| host: envVar("TYPESENSE_API_HOST"), | ||
| port: 443, protocol: "https" | ||
| }], | ||
| apiKey: envVar("TYPESENSE_API_KEY"), | ||
| docsCollection: envVar("TYPESENSE_DOCS_COLLECTION"), | ||
| docsSearchPhraseCollection: envVar("TYPESENSE_DOCS_SEARCH_PHRASE_COLLECTION"), | ||
| connectionTimeoutSec: 2 | ||
| } | ||
|
|
||
| return cfg; | ||
| } | ||
| const cfg: TypesenseServiceConfig = { | ||
| nodes: [ | ||
| { | ||
| host: envVar("TYPESENSE_API_HOST"), | ||
| port: 443, | ||
| protocol: "https", | ||
| }, | ||
| ], | ||
| apiKey: envVar("TYPESENSE_API_KEY"), | ||
| docsCollection: envVar("TYPESENSE_DOCS_COLLECTION"), | ||
| docsSearchPhraseCollection: envVar( | ||
| "TYPESENSE_DOCS_SEARCH_PHRASE_COLLECTION", | ||
| ), | ||
| connectionTimeoutSec: 2, | ||
| }; | ||
|
|
||
| return cfg; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,75 +1,84 @@ | ||
| import Instructor from '@instructor-ai/instructor'; | ||
| import { z } from 'zod'; | ||
| import Instructor from "@instructor-ai/instructor"; | ||
| import { z } from "zod"; | ||
| import { | ||
| // azure_client, | ||
| openaiClient | ||
| } from '../llm'; | ||
| import { scopedEnvVar } from '../general'; | ||
| // azure_client, | ||
| openaiClient, | ||
| } from "../llm"; | ||
| import { scopedEnvVar } from "../general"; | ||
|
|
||
| const stage_name = 'DOCS_QA_EXTRACT'; | ||
| const stage_name = "DOCS_QA_EXTRACT"; | ||
| const envVar = scopedEnvVar(stage_name); | ||
|
|
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| // const azureClient = azure_client(); | ||
| const openaiClientInstance = Instructor({ | ||
| client: openaiClient() as any, | ||
| mode: "FUNCTIONS", | ||
| debug: envVar('DEBUG_INSTRUCTOR') | ||
| client: openaiClient() as any, | ||
| mode: "FUNCTIONS", | ||
| debug: envVar("DEBUG_INSTRUCTOR"), | ||
| }); | ||
|
|
||
| const QueryRelaxationSchema = z.object({ | ||
| searchQueries: z.array(z.string()) | ||
| searchQueries: z.array(z.string()), | ||
| }); | ||
|
|
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| export type QueryRelaxation = z.infer<typeof QueryRelaxationSchema> | null; | ||
|
|
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| export async function queryRelaxation(user_input: string): Promise<QueryRelaxation> { | ||
| let query_result: QueryRelaxation | null = null; | ||
| export async function queryRelaxation( | ||
| user_input: string, | ||
| ): Promise<QueryRelaxation> { | ||
| let query_result: QueryRelaxation | null = null; | ||
|
|
||
| const prompt = `You have access to a search API that returns relevant documentation. | ||
| const prompt = `You have access to a search API that returns relevant documentation. | ||
| Your task is to generate an array of up to 7 search queries that are relevant to this question. | ||
| Use a variation of related keywords and synonyms for the queries, trying to be as general as possible. | ||
| Include as many queries as you can think of, including and excluding terms. | ||
| For example, include queries like ['keyword_1 keyword_2', 'keyword_1', 'keyword_2']. | ||
| Be creative. The more queries you include, the more likely you are to find relevant results.` | ||
| Be creative. The more queries you include, the more likely you are to find relevant results.`; | ||
|
|
||
| if (envVar('USE_AZURE_OPENAI_API', false) == true) { | ||
| // query_result = await azureClient.chat.completions.create({ | ||
| // model: envVar('AZURE_OPENAI_DEPLOYMENT'), | ||
| // response_model: { schema: SearchQueriesSchema, name: "GeneratedSearchQueries" }, | ||
| // temperature: 0.1, | ||
| // max_retries: 0, | ||
| // messages: [ | ||
| // { | ||
| // role: "system", | ||
| // content: prompt }, | ||
| // { role: "user", content: "[User query]\n" + user_input }, | ||
| // ] | ||
| // }); | ||
| } else { | ||
| console.log(`${stage_name} model name: ${envVar('OPENAI_API_MODEL_NAME', "")}`); | ||
| query_result = await openaiClientInstance.chat.completions.create({ | ||
| model: envVar('OPENAI_API_MODEL_NAME'), | ||
| response_model: { schema: QueryRelaxationSchema, name: "QueryRelaxation" }, | ||
| temperature: 0.1, | ||
| max_retries: 0, | ||
| messages: [ | ||
| { | ||
| role: "system", | ||
| content: prompt | ||
| }, | ||
| { role: "user", content: "[User query]\n" + user_input }, | ||
| ] | ||
| }); | ||
| } | ||
| if (envVar("USE_AZURE_OPENAI_API", false) == true) { | ||
| // query_result = await azureClient.chat.completions.create({ | ||
| // model: envVar('AZURE_OPENAI_DEPLOYMENT'), | ||
| // response_model: { schema: SearchQueriesSchema, name: "GeneratedSearchQueries" }, | ||
| // temperature: 0.1, | ||
| // max_retries: 0, | ||
| // messages: [ | ||
| // { | ||
| // role: "system", | ||
| // content: prompt }, | ||
| // { role: "user", content: "[User query]\n" + user_input }, | ||
| // ] | ||
| // }); | ||
| } else { | ||
| console.log( | ||
| `${stage_name} model name: ${envVar("OPENAI_API_MODEL_NAME", "")}`, | ||
| ); | ||
| query_result = await openaiClientInstance.chat.completions.create({ | ||
| model: envVar("OPENAI_API_MODEL_NAME"), | ||
| response_model: { | ||
| schema: QueryRelaxationSchema, | ||
| name: "QueryRelaxation", | ||
| }, | ||
| temperature: 0.1, | ||
| max_retries: 0, | ||
| messages: [ | ||
| { | ||
| role: "system", | ||
| content: prompt, | ||
| }, | ||
| { role: "user", content: "[User query]\n" + user_input }, | ||
| ], | ||
| }); | ||
| } | ||
|
|
||
| if (!query_result) { | ||
| return null | ||
| } | ||
| if (!query_result) { | ||
| return null; | ||
| } | ||
|
|
||
| for (let i = 0; i < query_result.searchQueries.length; i++) { | ||
| query_result.searchQueries[i] = query_result.searchQueries[i].replace("GitHub", "").trim(); | ||
| } | ||
| for (let i = 0; i < query_result.searchQueries.length; i++) { | ||
| query_result.searchQueries[i] = query_result.searchQueries[i] | ||
| .replace("GitHub", "") | ||
| .trim(); | ||
| } | ||
|
|
||
| return query_result; | ||
| } | ||
| return query_result; | ||
| } |
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