agentset init

Author: luancazarine

components/agentset/actions/create-injest-job/create-injest-job.mjs

@@ -0,0 +1,36 @@
+import agentset from "../../agentset.app.mjs";
+import { axios } from "@pipedream/platform";
+
+export default {
+  key: "agentset-create-ingest-job",
+  name: "Create Ingest Job",
+  description: "Create an ingest job for the authenticated organization. [See the documentation](https://docs.agentset.ai/api-reference/endpoint/ingest-jobs/create)",
+  version: "0.0.{{ts}}",
+  type: "action",
+  props: {
+    agentset,
+    namespaceId: {
+      propDefinition: [
+        agentset,
+        "namespaceId",
+      ],
+    },
+    payloadType: {
+      propDefinition: [
+        agentset,
+        "payloadType",
+      ],
+    },
+    payload: {
+      propDefinition: [
+        agentset,
+        "payload",
+      ],
+    },
+  },
+  async run({ $ }) {
+    const response = await this.agentset.createIngestJob(this.namespaceId, this.payloadType, this.payload);
+    $.export("$summary", `Ingest job created successfully: ID ${response.id}`);
+    return response;
+  },
+};

components/agentset/actions/create-namespace/create-namespace.mjs

@@ -0,0 +1,88 @@
+import agentset from "../../agentset.app.mjs";
+import { axios } from "@pipedream/platform";
+
+export default {
+  key: "agentset-create-namespace",
+  name: "Create Namespace",
+  description: "Creates a namespace for the authenticated organization. [See the documentation](https://docs.agentset.ai/api-reference/endpoint/namespaces/create)",
+  version: "0.0.{{ts}}",
+  type: "action",
+  props: {
+    agentset,
+    name: {
+      type: "string",
+      label: "Name",
+      description: "The name of the namespace to create",
+    },
+    slug: {
+      type: "string",
+      label: "Slug",
+      description: "A unique slug for the namespace",
+    },
+    embeddingConfigProvider: {
+      type: "string",
+      label: "Embedding Config Provider",
+      description: "Provider for the embedding config",
+      options: [
+        "OPENAI",
+      ],
+    },
+    embeddingConfigModel: {
+      type: "string",
+      label: "Embedding Config Model",
+      description: "The model for the embedding config",
+      options: [
+        "text-embedding-3-small",
+        "text-embedding-3-large",
+      ],
+    },
+    embeddingConfigApiKey: {
+      type: "string",
+      label: "Embedding Config API Key",
+      description: "API key for the embedding config provider",
+      secret: true,
+    },
+    vectorStoreConfigProvider: {
+      type: "string",
+      label: "Vector Store Config Provider",
+      description: "Provider for the vector store config",
+      options: [
+        "PINECONE",
+      ],
+    },
+    vectorStoreConfigApiKey: {
+      type: "string",
+      label: "Vector Store Config API Key",
+      description: "API key for the vector store",
+      secret: true,
+    },
+    vectorStoreConfigIndexHost: {
+      type: "string",
+      label: "Vector Store Config Index Host",
+      description: "URL of the Pinecone index host",
+    },
+  },
+  async run({ $ }) {
+    const response = await this.agentset._makeRequest({
+      method: "POST",
+      path: "/namespace",
+      data: {
+        name: this.name,
+        slug: this.slug,
+        embeddingConfig: {
+          provider: this.embeddingConfigProvider,
+          model: this.embeddingConfigModel,
+          apiKey: this.embeddingConfigApiKey,
+        },
+        vectorStoreConfig: {
+          provider: this.vectorStoreConfigProvider,
+          apiKey: this.vectorStoreConfigApiKey,
+          indexHost: this.vectorStoreConfigIndexHost,
+        },
+      },
+    });
+
+    $.export("$summary", `Successfully created namespace ${response.name}`);
+    return response;
+  },
+};

components/agentset/actions/search-namespace/search-namespace.mjs

@@ -0,0 +1,80 @@
+import agentset from "../../agentset.app.mjs";
+import { axios } from "@pipedream/platform";
+
+export default {
+  key: "agentset-search-namespace",
+  name: "Agentset Search Namespace",
+  description: "Complete retrieval pipeline for RAG with semantic search, filtering, and reranking. [See the documentation](https://docs.agentset.ai/api-reference/endpoint/search)",
+  version: "0.0.{{ts}}",
+  type: "action",
+  props: {
+    agentset,
+    namespaceId: {
+      propDefinition: [
+        agentset,
+        "namespaceId",
+      ],
+    },
+    query: {
+      type: "string",
+      label: "Query",
+      description: "The query for semantic search",
+    },
+    topK: {
+      type: "integer",
+      label: "Top K",
+      description: "Number of top documents to return",
+      optional: true,
+    },
+    rerank: {
+      type: "boolean",
+      label: "Rerank",
+      description: "Rerank documents based on query",
+      optional: true,
+    },
+    rerankLimit: {
+      type: "integer",
+      label: "Rerank Limit",
+      description: "Limit for reranking documents",
+      optional: true,
+    },
+    filter: {
+      type: "string",
+      label: "Filter",
+      description: "Filter to apply to search results",
+      optional: true,
+    },
+    minScore: {
+      type: "number",
+      label: "Minimum Score",
+      description: "Minimum score threshold for results",
+      optional: true,
+    },
+    includeRelationship: {
+      type: "boolean",
+      label: "Include Relationship",
+      description: "Include relationship data in results",
+      optional: true,
+    },
+    includeMetadata: {
+      type: "boolean",
+      label: "Include Metadata",
+      description: "Include metadata in results",
+      optional: true,
+    },
+  },
+  async run({ $ }) {
+    const response = await this.agentset.searchNamespace(this.namespaceId, this.query, {
+      topK: this.topK,
+      rerank: this.rerank,
+      rerankLimit: this.rerankLimit,
+      filter: this.filter,
+      minScore: this.minScore,
+      includeRelationships: this.includeRelationship,
+      includeMetadata: this.includeMetadata,
+    });
+
+    $.export("$summary", `Successfully completed the search for query: "${this.query}"`);
+    return response;
+  },
+};