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conversational database AI SDK","maintainers":[{"name":"eddy.gu","email":"eddygudom@gmail.com"}],"readme":"# Telygent AI SDK\n\nClient-side SDK to connect your app to Telygent AI. The SDK stores conversation history in your Redis, executes database tools locally, and sends tool results to Telygent for AI reasoning.\n\n## Install\n\n```bash\nnpm install @telygent/ai-sdk\n```\n\n### Required dependencies\n\n```bash\nnpm install ioredis mongodb\n```\n\n## Usage\n\n```ts\nimport { TelygentClient, createRedisHistoryStore, createMongoAdapter, type ModelRegistry } from \"@telygent/ai-sdk\";\nimport { MongoClient } from \"mongodb\";\n\n// createRedisHistoryStore reuses a shared client per URL.\nconst historyStore = createRedisHistoryStore({\n  url: process.env.REDIS_URL as string,\n  ttlSeconds: 3600,\n});\n\nconst mongoClient = new MongoClient(process.env.MONGO_URI as string);\nawait mongoClient.connect();\nconst mongoDb = mongoClient.db(process.env.MONGO_DB_NAME as string);\n\nconst registry = {\n  Statute: {\n    collectionName: \"canadian_statutes\",\n    allowedFields: [\"title\", \"shortTitle\", \"year\", \"jurisdiction\", \"topics\", \"createdAt\"],\n    links: {\n      list: \"/laws/statutes\",\n      detail: \"/laws/statutes/{_id}\",\n      allowedQueryParams: [\"year\", \"jurisdiction\", \"topics\", \"createdAt\"],\n      queryParamMap: {\n        year: \"year\",\n        jurisdiction: \"jurisdiction\",\n        topics: \"topic\",\n        createdAt: { gte: \"fromDate\", lte: \"toDate\" },\n      },\n      allowedQueryValues: {\n        jurisdiction: [\"federal\", \"provincial\"],\n      },\n    },\n    fieldTypes: {\n      _id: \"objectId\",\n      createdAt: \"date\",\n    },\n    requiredFilters: [\n      { field: \"jurisdiction\", contextKey: \"jurisdiction\", type: \"string\" }\n    ],\n    instructions:\n      \"Use jurisdiction filters (federal or provincial) and default to the most recent 5 years when dates are missing.\",\n  },\n  CaseLaw: {\n    collectionName: \"canadian_cases\",\n    allowedFields: [\"title\", \"citation\", \"court\", \"decisionDate\", \"topics\", \"summary\"],\n    links: {\n      list: \"/laws/cases\",\n      detail: \"/laws/cases/{_id}\",\n      allowedQueryParams: [\"court\", \"decisionDate\", \"topics\"],\n      queryParamMap: {\n        court: \"court\",\n        decisionDate: { gte: \"fromDate\", lte: \"toDate\" },\n        topics: \"topic\",\n      },\n    },\n    fieldTypes: {\n      _id: \"objectId\",\n      decisionDate: \"date\",\n    },\n    customServices: [\n      {\n        name: \"case_search\",\n        description: \"Search Canadian case law by title, citation, or topic.\",\n        inputSchema: {\n          properties: {\n            query: { type: \"string\", optional: false, description: \"Title, citation, or keyword.\" },\n            court: { type: \"string\", optional: true, description: \"e.g., SCC, FCA, ONSC.\" },\n            year: { type: \"number\", optional: true, description: \"Decision year filter.\" },\n            limit: { type: \"number\", optional: true, description: \"Maximum results to return.\" }\n          }\n        }\n      },\n      {\n        name: \"case_summary\",\n        description: \"Fetch a short summary for a single case by citation.\",\n        inputSchema: {\n          properties: {\n            citation: { type: \"string\", optional: false, description: \"Case citation, e.g. 2018 SCC 10.\" }\n          }\n        }\n      }\n    ]\n  },\n} satisfies ModelRegistry;\n\n// Multiple custom services:\n// - Define each service in `customServices` with a unique name.\n// - The AI will call `custom_query` with `service: \"<name>\"` to select the handler.\n\n// If you don't have Redis yet, omit `historyStore` and the SDK will use empty history.\n\nconst dbAdapter = createMongoAdapter({\n  db: mongoDb,\n  registry,\n});\n\nconst client = new TelygentClient({\n  apiKey: process.env.TELYGENT_API_KEY as string,\n  aiName: \"Atlas\",\n  registry,\n  historyStore,\n  dbAdapter,\n  customServices: {\n    CaseLaw: {\n      case_search: async (input) => caseService.search(input),\n      case_summary: async (input) => caseService.summary(input),\n    },\n  },\n  log: false,\n});\n\nconst response = await client.query({\n  question: \"Show me federal statutes on privacy passed after 2018\",\n  conversationId: \"conv_123\",\n  userContext: {\n    userId: \"user_1\",\n    jurisdiction: \"federal\",\n  },\n  messageContext: \"Viewing document id: 3283823883\",\n});\n\nconsole.log(response.content);\n\nconst messages = await client.getConversationMessages(\"conv_123\");\nconsole.log(messages);\n```\n\n### Reload conversation history\n\n```ts\nimport { TelygentClient, createRedisHistoryStore, type ModelRegistry } from \"@telygent/ai-sdk\";\n\nconst historyStore = createRedisHistoryStore({\n  url: process.env.REDIS_URL as string,\n});\n\n// Requires Redis. If you don't pass a history store, this returns an empty list.\n\nconst client = new TelygentClient({\n  apiKey: process.env.TELYGENT_API_KEY as string,\n  aiName: \"Atlas\",\n  historyStore,\n});\n\nconst messages = await client.getConversationMessages(\"conv_123\");\nconsole.log(messages);\n```\n\n## Redis\n\nUse a single shared Redis client for history. Creating a new client per request can exhaust the Redis\n`maxclients` limit and cause errors. The SDK provides `createRedisHistoryStore` to reuse a shared\nclient per URL, or you can pass your own client if you already manage one.\n\n```ts\nimport Redis from \"ioredis\";\nimport { createRedisHistoryStore } from \"@telygent/ai-sdk\";\n\nconst redisClient = new Redis(process.env.REDIS_URL as string);\nconst historyStore = createRedisHistoryStore({ client: redisClient });\n```\n\n## Notes\n\n- Conversation history lives in your Redis and is sent to Telygent each request.\n- Database queries are executed locally through the adapter you provide.\n- Registry is static and versioned by hash after initial sync.\n- Use `requiredFilters` to inject fixed constraints into queries.\n- Custom services are optional and let the AI call your own per-model lookup handlers.\n- Use `getConversationMessages` to reload message history from Redis.\n- `messageContext` can be passed per request to enrich AI reasoning context; it is sent to AI for that turn but not stored as conversation history.\n- `messageContext` is currently limited to 600 characters; longer values are truncated before sending to AI.\n\n## Streaming (SSE)\n\nUse in an Express route to stream events to the browser:\n\n```ts\napp.post(\"/stream\", async (req, res) => {\n  res.setHeader(\"Content-Type\", \"text/event-stream\");\n  res.setHeader(\"Cache-Control\", \"no-cache\");\n  res.setHeader(\"Connection\", \"keep-alive\");\n\n  await client.queryStream(req.body, (event) => {\n    res.write(`data: ${JSON.stringify(event)}\\n\\n`);\n    if (event.phase === \"final\" || event.phase === \"error\") {\n      res.end();\n    }\n  });\n});\n```\n\nUse streaming when you want step-by-step updates (planning, tool execution, response). The stream emits\nJSON events with a `phase` field:\n\n- `thinking`: progress updates\n- `final`: final response payload\n- `error`: terminal error\n\n```ts\nconst response = await client.queryStream(\n  {\n    question: \"Show me recent transactions\",\n    conversationId: \"conv_123\",\n    userContext: { userId: \"user_1\" },\n    messageContext: \"Viewing transaction detail (transactionId: txn_123)\",\n  },\n  (event) => {\n    if (event.phase === \"thinking\") {\n      console.log(\"step:\", event.content);\n      return;\n    }\n    if (event.phase === \"final\") {\n      console.log(\"final:\", event.content);\n    }\n  }\n);\n\nconsole.log(\"answer:\", response.content);\n```\n\nNotes:\n- Streaming does not replace the existing `query()` method. Use either one.\n- Only `phase: \"final\"` messages are stored in Redis history.\n\n## Express middleware\n\n```ts\nimport express from \"express\";\nimport { attachAiClient, createRedisHistoryStore, createMongoAdapter } from \"@telygent/ai-sdk\";\n\nconst app = express();\napp.use(express.json());\n\nconst historyStore = createRedisHistoryStore({\n  url: process.env.REDIS_URL as string,\n});\n\napp.use(\n  attachAiClient({\n    apiKey: process.env.TELYGENT_API_KEY as string,\n    registry,\n    historyStore,\n    dbAdapter: createMongoAdapter({ db: mongoDb, registry }),\n  })\n);\n\napp.post(\"/ask\", async (req, res) => {\n  const { question, conversationId, userContext } = req.body;\n  const response = await req.aiClient!.query({ question, conversationId, userContext });\n  res.json(response);\n});\n```\n\n## Mongo History Store\n\nIf you want users to resume conversations from your application database, use MongoDB as the history store.\n\n```ts\nimport { createMongoHistoryStore } from \"@telygent/ai-sdk\";\n\nconst historyStore = createMongoHistoryStore({\n  db: mongoDb,\n  collectionName: \"telygent_conversations\", // optional\n});\n```\n\nRecommended Mongo index:\n\n```js\ndb.telygent_conversations.createIndex({ conversationId: 1, timestamp: 1 });\n```\n\nYou can use either Redis or Mongo for `historyStore`.\n","readmeFilename":"README.md"}