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request-body-generator.json
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| { | |
| "title": "Request Body Builder", | |
| "description": "Builds the POST body for a request", | |
| "version": "0.0.1", | |
| "nodes": [ | |
| { | |
| "type": "output", | |
| "id": "output", | |
| "configuration": { | |
| "schema": { | |
| "type": "object", | |
| "properties": { | |
| "json": { | |
| "type": "string", | |
| "title": "json", | |
| "examples": [] | |
| } | |
| }, | |
| "required": [] | |
| } | |
| }, | |
| "metadata": { | |
| "visual": { | |
| "x": 488, | |
| "y": 238 | |
| } | |
| } | |
| }, | |
| { | |
| "id": "text-2daa1e8a", | |
| "type": "text", | |
| "metadata": { | |
| "visual": { | |
| "x": 214, | |
| "y": -774 | |
| }, | |
| "title": "generate-json", | |
| "logLevel": "debug" | |
| }, | |
| "configuration": { | |
| "model": "gemini-1.5-pro-latest", | |
| "systemInstruction": "{ \"type\": \"object\", \"additionalProperties\": false, \"properties\": { \"input\": { \"description\": \"Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.\\n\", \"example\": \"The quick brown fox jumped over the lazy dog\", \"oneOf\": [ { \"type\": \"string\", \"title\": \"string\", \"description\": \"The string that will be turned into an embedding.\", \"default\": \"\", \"example\": \"This is a test.\" }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of strings that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"string\", \"default\": \"\", \"example\": \"['This is a test.']\" } }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of integers that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"integer\" }, \"example\": \"[1212, 318, 257, 1332, 13]\" }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of arrays containing integers that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"array\", \"minItems\": 1, \"items\": { \"type\": \"integer\" } }, \"example\": \"[[1212, 318, 257, 1332, 13]]\" } ], \"x-oaiExpandable\": true }, \"model\": { \"description\": \"ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.\\n\", \"example\": \"text-embedding-3-small\", \"anyOf\": [ { \"type\": \"string\" }, { \"type\": \"string\", \"enum\": [ \"text-embedding-ada-002\", \"text-embedding-3-small\", \"text-embedding-3-large\" ] } ], \"x-oaiTypeLabel\": \"string\" }, \"encoding_format\": { \"description\": \"The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).\", \"example\": \"float\", \"default\": \"float\", \"type\": \"string\", \"enum\": [\"float\", \"base64\"] }, \"dimensions\": { \"description\": \"The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.\\n\", \"type\": \"integer\", \"minimum\": 1 }, \"user\": { \"type\": \"string\", \"example\": \"user-1234\", \"description\": \"A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\\n\" } }, \"required\": [\"model\", \"input\"] }" | |
| } | |
| }, | |
| { | |
| "id": "validateJson-eefab6f5", | |
| "type": "validateJson", | |
| "metadata": { | |
| "visual": { | |
| "x": -36, | |
| "y": 109 | |
| }, | |
| "title": "validate-json", | |
| "logLevel": "debug" | |
| }, | |
| "configuration": { | |
| "schema": { | |
| "type": "object", | |
| "additionalProperties": false, | |
| "properties": { | |
| "input": { | |
| "description": "Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.\n", | |
| "oneOf": [ | |
| { | |
| "type": "string", | |
| "title": "string", | |
| "description": "The string that will be turned into an embedding.", | |
| "default": "" | |
| }, | |
| { | |
| "type": "array", | |
| "title": "array", | |
| "description": "The array of strings that will be turned into an embedding.", | |
| "minItems": 1, | |
| "maxItems": 2048, | |
| "items": { | |
| "type": "string", | |
| "default": "" | |
| } | |
| }, | |
| { | |
| "type": "array", | |
| "title": "array", | |
| "description": "The array of integers that will be turned into an embedding.", | |
| "minItems": 1, | |
| "maxItems": 2048, | |
| "items": { | |
| "type": "integer" | |
| } | |
| }, | |
| { | |
| "type": "array", | |
| "title": "array", | |
| "description": "The array of arrays containing integers that will be turned into an embedding.", | |
| "minItems": 1, | |
| "maxItems": 2048, | |
| "items": { | |
| "type": "array", | |
| "minItems": 1, | |
| "items": { | |
| "type": "integer" | |
| } | |
| } | |
| } | |
| ] | |
| }, | |
| "model": { | |
| "description": "ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.\n", | |
| "anyOf": [ | |
| { | |
| "type": "string" | |
| }, | |
| { | |
| "type": "string", | |
| "enum": [ | |
| "text-embedding-ada-002", | |
| "text-embedding-3-small", | |
| "text-embedding-3-large" | |
| ] | |
| } | |
| ] | |
| }, | |
| "encoding_format": { | |
| "description": "The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).", | |
| "default": "float", | |
| "type": "string", | |
| "enum": [ | |
| "float", | |
| "base64" | |
| ] | |
| }, | |
| "dimensions": { | |
| "description": "The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.\n", | |
| "type": "integer", | |
| "minimum": 1 | |
| }, | |
| "user": { | |
| "type": "string", | |
| "description": "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\n" | |
| } | |
| }, | |
| "required": [ | |
| "model", | |
| "input" | |
| ] | |
| } | |
| } | |
| }, | |
| { | |
| "id": "promptTemplate-47d4a7bf", | |
| "type": "promptTemplate", | |
| "metadata": { | |
| "visual": { | |
| "x": -332, | |
| "y": -729 | |
| }, | |
| "title": "create-schema-generation prompt", | |
| "logLevel": "debug" | |
| }, | |
| "configuration": { | |
| "template": "Consider the following JSON schema: \n\n```\n{{schema}}\n```\n\nThis JSON Schema represents the format I want you to follow to generate your answer.\n\nBased on all this information, generate a valid JSON object containing the information I requested.\n\nIf you don't have enough information and their isn't a default value, ask for it", | |
| "schema": "{ \"type\": \"object\", \"additionalProperties\": false, \"properties\": { \"input\": { \"description\": \"Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.\\n\", \"example\": \"The quick brown fox jumped over the lazy dog\", \"oneOf\": [ { \"type\": \"string\", \"title\": \"string\", \"description\": \"The string that will be turned into an embedding.\", \"default\": \"\", \"example\": \"This is a test.\" }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of strings that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"string\", \"default\": \"\", \"example\": \"['This is a test.']\" } }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of integers that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"integer\" }, \"example\": \"[1212, 318, 257, 1332, 13]\" }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of arrays containing integers that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"array\", \"minItems\": 1, \"items\": { \"type\": \"integer\" } }, \"example\": \"[[1212, 318, 257, 1332, 13]]\" } ], \"x-oaiExpandable\": true }, \"model\": { \"description\": \"ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.\\n\", \"example\": \"text-embedding-3-small\", \"anyOf\": [ { \"type\": \"string\" }, { \"type\": \"string\", \"enum\": [ \"text-embedding-ada-002\", \"text-embedding-3-small\", \"text-embedding-3-large\" ] } ], \"x-oaiTypeLabel\": \"string\" }, \"encoding_format\": { \"description\": \"The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).\", \"example\": \"float\", \"default\": \"float\", \"type\": \"string\", \"enum\": [\"float\", \"base64\"] }, \"dimensions\": { \"description\": \"The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.\\n\", \"type\": \"integer\", \"minimum\": 1 }, \"user\": { \"type\": \"string\", \"example\": \"user-1234\", \"description\": \"A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\\n\" } }, \"required\": [\"model\", \"input\"] }" | |
| } | |
| }, | |
| { | |
| "id": "input-a15bcc81", | |
| "type": "input", | |
| "metadata": { | |
| "visual": { | |
| "x": -203, | |
| "y": -430 | |
| }, | |
| "title": "prompt-input", | |
| "logLevel": "debug" | |
| } | |
| }, | |
| { | |
| "id": "input-f44b216d", | |
| "type": "input", | |
| "metadata": { | |
| "visual": { | |
| "x": -534, | |
| "y": -167 | |
| } | |
| }, | |
| "configuration": { | |
| "schema": { | |
| "properties": { | |
| "theSchema": { | |
| "type": "string", | |
| "title": "The Schema", | |
| "examples": [ | |
| "{\n \"type\":\"object\",\n \"additionalProperties\":false,\n \"properties\":{\n \"input\":{\n \"description\":\"Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.\\n\",\n \"oneOf\":[\n {\n \"type\":\"string\",\n \"title\":\"string\",\n \"description\":\"The string that will be turned into an embedding.\",\n \"default\":\"\"\n },\n {\n \"type\":\"array\",\n \"title\":\"array\",\n \"description\":\"The array of strings that will be turned into an embedding.\",\n \"minItems\":1,\n \"maxItems\":2048,\n \"items\":{\n \"type\":\"string\",\n \"default\":\"\"\n }\n },\n {\n \"type\":\"array\",\n \"title\":\"array\",\n \"description\":\"The array of integers that will be turned into an embedding.\",\n \"minItems\":1,\n \"maxItems\":2048,\n \"items\":{\n \"type\":\"integer\"\n }\n },\n {\n \"type\":\"array\",\n \"title\":\"array\",\n \"description\":\"The array of arrays containing integers that will be turned into an embedding.\",\n \"minItems\":1,\n \"maxItems\":2048,\n \"items\":{\n \"type\":\"array\",\n \"minItems\":1,\n \"items\":{\n \"type\":\"integer\"\n }\n }\n }\n ]\n },\n \"model\":{\n \"description\":\"ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.\\n\",\n \"anyOf\":[\n {\n \"type\":\"string\"\n },\n {\n \"type\":\"string\",\n \"enum\":[\n \"text-embedding-ada-002\",\n \"text-embedding-3-small\",\n \"text-embedding-3-large\"\n ]\n }\n ]\n },\n \"encoding_format\":{\n \"description\":\"The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).\",\n \"default\":\"float\",\n \"type\":\"string\",\n \"enum\":[\n \"float\",\n \"base64\"\n ]\n },\n \"dimensions\":{\n \"description\":\"The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.\\n\",\n \"type\":\"integer\",\n \"minimum\":1\n },\n \"user\":{\n \"type\":\"string\",\n \"description\":\"A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\\n\"\n }\n },\n \"required\":[\n \"model\",\n \"input\"\n ]\n}" | |
| ], | |
| "default": "{ \"type\": \"object\", \"additionalProperties\": false, \"properties\": { \"input\": { \"description\": \"Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.\\n\", \"example\": \"The quick brown fox jumped over the lazy dog\", \"oneOf\": [ { \"type\": \"string\", \"title\": \"string\", \"description\": \"The string that will be turned into an embedding.\", \"default\": \"\", \"example\": \"This is a test.\" }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of strings that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"string\", \"default\": \"\", \"example\": \"['This is a test.']\" } }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of integers that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"integer\" }, \"example\": \"[1212, 318, 257, 1332, 13]\" }, { \"type\": \"array\", \"title\": \"array\", \"description\": \"The array of arrays containing integers that will be turned into an embedding.\", \"minItems\": 1, \"maxItems\": 2048, \"items\": { \"type\": \"array\", \"minItems\": 1, \"items\": { \"type\": \"integer\" } }, \"example\": \"[[1212, 318, 257, 1332, 13]]\" } ], \"x-oaiExpandable\": true }, \"model\": { \"description\": \"ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.\\n\", \"example\": \"text-embedding-3-small\", \"anyOf\": [ { \"type\": \"string\" }, { \"type\": \"string\", \"enum\": [ \"text-embedding-ada-002\", \"text-embedding-3-small\", \"text-embedding-3-large\" ] } ], \"x-oaiTypeLabel\": \"string\" }, \"encoding_format\": { \"description\": \"The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).\", \"example\": \"float\", \"default\": \"float\", \"type\": \"string\", \"enum\": [\"float\", \"base64\"] }, \"dimensions\": { \"description\": \"The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.\\n\", \"type\": \"integer\", \"minimum\": 1 }, \"user\": { \"type\": \"string\", \"example\": \"user-1234\", \"description\": \"A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\\n\" } }, \"required\": [\"model\", \"input\"] }" | |
| } | |
| }, | |
| "required": [], | |
| "type": "object" | |
| } | |
| } | |
| }, | |
| { | |
| "id": "runJavascript-b70ca9b3", | |
| "type": "runJavascript", | |
| "metadata": { | |
| "visual": { | |
| "x": 296, | |
| "y": -135 | |
| }, | |
| "title": "make-input-schema-from-error", | |
| "logLevel": "debug" | |
| }, | |
| "configuration": { | |
| "name": "run", | |
| "code": "function run(args) {\n console.log(args)\n if (\"$error\" in args) {\n \n return { \n //\"schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"additional\": {\n \"type\": \"string\",\n \"title\": \"Additional Data\",\n \"description\": args.$error.inputs.json || args.$error.error.message,\n \"examples\": []\n }\n },\n \"required\": []\n }\n // }\n }\n return;\n}" | |
| } | |
| }, | |
| { | |
| "id": "input-9dfbdaed", | |
| "type": "input", | |
| "metadata": { | |
| "visual": { | |
| "x": 649, | |
| "y": -113 | |
| }, | |
| "title": "additional-data-input", | |
| "logLevel": "debug" | |
| } | |
| }, | |
| { | |
| "id": "promptTemplate-df5c15c1", | |
| "type": "promptTemplate", | |
| "configuration": { | |
| "template": "{{text}}\n\nThe following data will override conflicting statements\n\n{{additional}}" | |
| }, | |
| "metadata": { | |
| "visual": { | |
| "x": 690, | |
| "y": -428 | |
| }, | |
| "title": "ammend-prompt-with-new-data", | |
| "logLevel": "debug" | |
| } | |
| } | |
| ], | |
| "edges": [ | |
| { | |
| "from": "text-2daa1e8a", | |
| "to": "validateJson-eefab6f5", | |
| "out": "text", | |
| "in": "json" | |
| }, | |
| { | |
| "from": "validateJson-eefab6f5", | |
| "to": "output", | |
| "out": "json", | |
| "in": "text" | |
| }, | |
| { | |
| "from": "promptTemplate-47d4a7bf", | |
| "to": "text-2daa1e8a", | |
| "out": "prompt", | |
| "in": "systemInstruction", | |
| "constant": true | |
| }, | |
| { | |
| "from": "input-a15bcc81", | |
| "to": "text-2daa1e8a", | |
| "out": "text", | |
| "in": "text" | |
| }, | |
| { | |
| "from": "input-f44b216d", | |
| "to": "promptTemplate-47d4a7bf", | |
| "out": "theSchema", | |
| "in": "schema" | |
| }, | |
| { | |
| "from": "input-f44b216d", | |
| "to": "validateJson-eefab6f5", | |
| "out": "theSchema", | |
| "in": "schema" | |
| }, | |
| { | |
| "from": "validateJson-eefab6f5", | |
| "to": "runJavascript-b70ca9b3", | |
| "out": "$error", | |
| "in": "$error" | |
| }, | |
| { | |
| "from": "input-a15bcc81", | |
| "to": "runJavascript-b70ca9b3", | |
| "out": "text", | |
| "in": "text" | |
| }, | |
| { | |
| "from": "runJavascript-b70ca9b3", | |
| "to": "input-9dfbdaed", | |
| "out": "result", | |
| "in": "schema" | |
| }, | |
| { | |
| "from": "input-a15bcc81", | |
| "to": "promptTemplate-df5c15c1", | |
| "out": "text", | |
| "in": "text" | |
| }, | |
| { | |
| "from": "input-9dfbdaed", | |
| "to": "promptTemplate-df5c15c1", | |
| "out": "additional", | |
| "in": "additional" | |
| }, | |
| { | |
| "from": "promptTemplate-df5c15c1", | |
| "to": "text-2daa1e8a", | |
| "out": "prompt", | |
| "in": "text" | |
| } | |
| ] | |
| } |
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