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Re-add sync bgl TS files to bgl.json script. #5613

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Re-add sync bgl TS files to bgl.json script. #5613

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104 changes: 103 additions & 1 deletion package-lock.json
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2 changes: 1 addition & 1 deletion packages/a2/bgl/_connector-template.bgl.json
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Expand Up @@ -53,7 +53,7 @@
},
"modules": {
"configurator": {
"code": "/**\n * @fileoverview Add a description for your module here.\n */\nimport { err, ok } from \"./a2/utils\";\nimport { createConfigurator } from \"./a2/connector-manager\";\nimport read from \"@read\";\nimport write from \"@write\";\nexport { invoke as default, describe };\nconst CONNECTOR_TITLE = \"{{ title }}\";\nconst { invoke, describe } = createConfigurator({\n title: CONNECTOR_TITLE,\n initialize: async () => {\n return { title: CONNECTOR_TITLE, configuration: {} };\n },\n});\n",
"code": "/**\n * @fileoverview Add a description for your module here.\n */\nimport { createConfigurator } from \"./a2/connector-manager\";\nexport { invoke as default, describe };\nconst CONNECTOR_TITLE = \"{{ title }}\";\nconst { invoke, describe } = createConfigurator({\n title: CONNECTOR_TITLE,\n initialize: async () => {\n return { title: CONNECTOR_TITLE, configuration: {} };\n },\n});\n",
"metadata": {
"title": "configurator",
"source": {
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44 changes: 22 additions & 22 deletions packages/a2/bgl/a2.bgl.json
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2 changes: 1 addition & 1 deletion packages/a2/bgl/audio-generator.bgl.json
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Expand Up @@ -51,7 +51,7 @@
},
"modules": {
"main": {
"code": "/**\n * @fileoverview Generates audio (tts) output using supplied context.\n */\nimport gemini, { defaultSafetySettings, } from \"./a2/gemini\";\nimport { err, ok, llm, toLLMContent, toLLMContentInline, toLLMContentStored, toTextConcat, joinContent, toText, defaultLLMContent, } from \"./a2/utils\";\nimport { Template } from \"./a2/template\";\nimport { ToolManager } from \"./a2/tool-manager\";\nimport {} from \"./a2/common\";\nimport { ArgumentNameGenerator } from \"./a2/introducer\";\nimport { executeStep, } from \"./a2/step-executor\";\nimport { ListExpander } from \"./a2/lists\";\nconst VoiceMap = {\n \"Male (English)\": \"en-US-male\",\n \"Female (English)\": \"en-US-female\",\n}; // Use 'as const' for stricter type inference\nconst VOICES = Object.keys(VoiceMap);\nexport { invoke as default, describe };\nasync function callAudioGen(prompt, voice) {\n let voiceParam = \"en-US-female\";\n if (voice in VoiceMap) {\n voiceParam = VoiceMap[voice];\n }\n const executionInputs = {};\n const encodedPrompt = btoa(unescape(encodeURIComponent(prompt)));\n executionInputs[\"text_to_speak\"] = {\n chunks: [\n {\n mimetype: \"text/plain\",\n data: encodedPrompt,\n },\n ],\n };\n executionInputs[\"voice_key\"] = {\n chunks: [\n {\n mimetype: \"text/plain\",\n data: btoa(voiceParam),\n },\n ],\n };\n const inputParameters = [\"text_to_speak\"];\n const body = {\n planStep: {\n stepName: \"GenerateAudio\",\n modelApi: \"tts\",\n inputParameters: inputParameters,\n systemPrompt: \"\",\n output: \"generated_speech\",\n },\n execution_inputs: executionInputs,\n };\n const response = await executeStep(body);\n if (!ok(response)) {\n return toLLMContent(\"TTS generation failed: \" + response.$error);\n }\n if (!response.executionOutputs) {\n return toLLMContent(\"TTS returned no audio\");\n }\n let returnVal;\n for (let value of Object.values(response.executionOutputs)) {\n const mimetype = value.chunks[0].mimetype;\n if (mimetype.startsWith(\"audio\")) {\n if (mimetype.endsWith(\"/storedData\")) {\n returnVal = toLLMContentStored(mimetype.replace(\"/storedData\", \"\"), value.chunks[0].data);\n }\n else {\n returnVal = toLLMContentInline(mimetype, value.chunks[0].data);\n }\n }\n }\n if (!returnVal) {\n return toLLMContent(\"Error: No audio returned from backend\");\n }\n console.log(returnVal);\n return returnVal;\n}\nasync function invoke({ context, text, voice, ...params }) {\n context ??= [];\n let instructionText = \"\";\n if (text) {\n instructionText = toText(text).trim();\n }\n const template = new Template(toLLMContent(instructionText));\n const toolManager = new ToolManager(new ArgumentNameGenerator());\n const substituting = await template.substitute(params, async ({ path: url, instance }) => toolManager.addTool(url, instance));\n if (!ok(substituting)) {\n return substituting;\n }\n console.log(\"context\");\n console.log(context);\n console.log(\"instruction\");\n console.log(text);\n console.log(\"substituting\");\n console.log(substituting);\n const results = await new ListExpander(substituting, context).map(async (itemInstruction, itemContext) => {\n const combinedInstruction = toTextConcat(joinContent(toText(itemInstruction), itemContext, false));\n if (!combinedInstruction) {\n return toLLMContent(\"Please provide the text to be converted to speech.\");\n }\n console.log(\"PROMPT: \", combinedInstruction);\n return callAudioGen(combinedInstruction, voice);\n });\n if (!ok(results))\n return results;\n return { context: results };\n}\nasync function describe({ inputs: { text } }) {\n const template = new Template(text);\n return {\n inputSchema: {\n type: \"object\",\n properties: {\n context: {\n type: \"array\",\n items: { type: \"object\", behavior: [\"llm-content\"] },\n title: \"Context in\",\n behavior: [\"main-port\"],\n },\n text: {\n type: \"object\",\n behavior: [\"llm-content\", \"config\", \"hint-preview\"],\n title: \"Text\",\n description: \"Construct the inputs to be spoken with text-to-speech. Use @ to reference previous step outputs.\",\n default: defaultLLMContent(),\n },\n voice: {\n type: \"string\",\n behavior: [\"hint-text\", \"config\"],\n title: \"Voice\",\n icon: \"voice-selection\",\n enum: VOICES,\n description: \"The voice you'd like to generate with\",\n default: \"Female (English)\",\n },\n ...template.schemas(),\n },\n behavior: [\"at-wireable\"],\n ...template.requireds(),\n },\n outputSchema: {\n type: \"object\",\n properties: {\n context: {\n type: \"array\",\n items: { type: \"object\", behavior: [\"llm-content\"] },\n title: \"Context out\",\n behavior: [\"hint-audio\", \"main-port\"],\n },\n },\n additionalProperties: false,\n },\n title: \"Make Speech\",\n metadata: {\n icon: \"generative-audio\",\n tags: [\"quick-access\", \"generative\"],\n order: 3,\n },\n };\n}\n",
"code": "/**\n * @fileoverview Generates audio (tts) output using supplied context.\n */\nimport { ok, toLLMContent, toLLMContentInline, toLLMContentStored, toTextConcat, joinContent, toText, defaultLLMContent, } from \"./a2/utils\";\nimport { Template } from \"./a2/template\";\nimport { ToolManager } from \"./a2/tool-manager\";\nimport { ArgumentNameGenerator } from \"./a2/introducer\";\nimport { executeStep, } from \"./a2/step-executor\";\nimport { ListExpander } from \"./a2/lists\";\nconst VoiceMap = {\n \"Male (English)\": \"en-US-male\",\n \"Female (English)\": \"en-US-female\",\n}; // Use 'as const' for stricter type inference\nconst VOICES = Object.keys(VoiceMap);\nexport { invoke as default, describe };\nasync function callAudioGen(prompt, voice) {\n let voiceParam = \"en-US-female\";\n if (voice in VoiceMap) {\n voiceParam = VoiceMap[voice];\n }\n const executionInputs = {};\n const encodedPrompt = btoa(unescape(encodeURIComponent(prompt)));\n executionInputs[\"text_to_speak\"] = {\n chunks: [\n {\n mimetype: \"text/plain\",\n data: encodedPrompt,\n },\n ],\n };\n executionInputs[\"voice_key\"] = {\n chunks: [\n {\n mimetype: \"text/plain\",\n data: btoa(voiceParam),\n },\n ],\n };\n const inputParameters = [\"text_to_speak\"];\n const body = {\n planStep: {\n stepName: \"GenerateAudio\",\n modelApi: \"tts\",\n inputParameters: inputParameters,\n systemPrompt: \"\",\n output: \"generated_speech\",\n },\n execution_inputs: executionInputs,\n };\n const response = await executeStep(body);\n if (!ok(response)) {\n return toLLMContent(\"TTS generation failed: \" + response.$error);\n }\n if (!response.executionOutputs) {\n return toLLMContent(\"TTS returned no audio\");\n }\n let returnVal;\n for (let value of Object.values(response.executionOutputs)) {\n const mimetype = value.chunks[0].mimetype;\n if (mimetype.startsWith(\"audio\")) {\n if (mimetype.endsWith(\"/storedData\")) {\n returnVal = toLLMContentStored(mimetype.replace(\"/storedData\", \"\"), value.chunks[0].data);\n }\n else {\n returnVal = toLLMContentInline(mimetype, value.chunks[0].data);\n }\n }\n }\n if (!returnVal) {\n return toLLMContent(\"Error: No audio returned from backend\");\n }\n console.log(returnVal);\n return returnVal;\n}\nasync function invoke({ context, text, voice, ...params }) {\n context ??= [];\n let instructionText = \"\";\n if (text) {\n instructionText = toText(text).trim();\n }\n const template = new Template(toLLMContent(instructionText));\n const toolManager = new ToolManager(new ArgumentNameGenerator());\n const substituting = await template.substitute(params, async ({ path: url, instance }) => toolManager.addTool(url, instance));\n if (!ok(substituting)) {\n return substituting;\n }\n console.log(\"context\");\n console.log(context);\n console.log(\"instruction\");\n console.log(text);\n console.log(\"substituting\");\n console.log(substituting);\n const results = await new ListExpander(substituting, context).map(async (itemInstruction, itemContext) => {\n const combinedInstruction = toTextConcat(joinContent(toText(itemInstruction), itemContext, false));\n if (!combinedInstruction) {\n return toLLMContent(\"Please provide the text to be converted to speech.\");\n }\n console.log(\"PROMPT: \", combinedInstruction);\n return callAudioGen(combinedInstruction, voice);\n });\n if (!ok(results))\n return results;\n return { context: results };\n}\nasync function describe({ inputs: { text } }) {\n const template = new Template(text);\n return {\n inputSchema: {\n type: \"object\",\n properties: {\n context: {\n type: \"array\",\n items: { type: \"object\", behavior: [\"llm-content\"] },\n title: \"Context in\",\n behavior: [\"main-port\"],\n },\n text: {\n type: \"object\",\n behavior: [\"llm-content\", \"config\", \"hint-preview\"],\n title: \"Text\",\n description: \"Construct the inputs to be spoken with text-to-speech. Use @ to reference previous step outputs.\",\n default: defaultLLMContent(),\n },\n voice: {\n type: \"string\",\n behavior: [\"hint-text\", \"config\"],\n title: \"Voice\",\n icon: \"voice-selection\",\n enum: VOICES,\n description: \"The voice you'd like to generate with\",\n default: \"Female (English)\",\n },\n ...template.schemas(),\n },\n behavior: [\"at-wireable\"],\n ...template.requireds(),\n },\n outputSchema: {\n type: \"object\",\n properties: {\n context: {\n type: \"array\",\n items: { type: \"object\", behavior: [\"llm-content\"] },\n title: \"Context out\",\n behavior: [\"hint-audio\", \"main-port\"],\n },\n },\n additionalProperties: false,\n },\n title: \"Make Speech\",\n metadata: {\n icon: \"generative-audio\",\n tags: [\"quick-access\", \"generative\"],\n order: 3,\n },\n };\n}\n",
"metadata": {
"title": "main",
"source": {
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