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Published
1 month ago
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FlowiseAI
FlowiseAI
[BUG] ERR_HTTP_HEADERS_SENT
Describe the bug "Cannot set headers after they are sent to the client" is returned on 5-10th post request and denies further request to client
To Reproduce Steps to reproduce the behavior:
- Deploy on Railway
- Setup Conversational Retrieval QA Chain
- Remove text embeddings and document upload
- Ask 5-10 questions via node client
uncaughtException: Error [ERR_HTTP_HEADERS_SENT]: Cannot set headers after they are sent to the client
Jun 26 13:21:37at new NodeError (node:internal/errors:399:5)
Jun 26 13:21:37at ServerResponse.setHeader (node:_http_outgoing:645:11)
Jun 26 13:21:37at ServerResponse.header (/usr/local/lib/node_modules/flowise/node_modules/express/lib/response.js:794:10)
Jun 26 13:21:37at ServerResponse.send (/usr/local/lib/node_modules/flowise/node_modules/express/lib/response.js:174:12)
Jun 26 13:21:37at App.processPrediction (/usr/local/lib/node_modules/flowise/dist/index.js:567:36)
Jun 26 13:21:37at process.processTicksAndRejections (node:internal/process/task_queues:95:5)
Jun 26 13:21:37at async /usr/local/lib/node_modules/flowise/dist/index.js:290:13 {
Jun 26 13:21:37code: 'ERR_HTTP_HEADERS_SENT'
Jun 26 13:21:37}
Thanks in advance, any direction appreciated.
@chungyau97 Yes, thanks.
Chatflow Export:
{
"nodes": [
{
"width": 300,
"height": 331,
"id": "openAIEmbeddings_1",
"position": {
"x": 719.8090613945707,
"y": 875.480986998991
},
"type": "customNode",
"data": {
"id": "openAIEmbeddings_1",
"label": "OpenAI Embeddings",
"name": "openAIEmbeddings",
"type": "OpenAIEmbeddings",
"baseClasses": [
"OpenAIEmbeddings",
"Embeddings"
],
"category": "Embeddings",
"description": "OpenAI API to generate embeddings for a given text",
"inputParams": [
{
"label": "OpenAI Api Key",
"name": "openAIApiKey",
"type": "password",
"id": "openAIEmbeddings_1-input-openAIApiKey-password"
},
{
"label": "Strip New Lines",
"name": "stripNewLines",
"type": "boolean",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_1-input-stripNewLines-boolean"
},
{
"label": "Batch Size",
"name": "batchSize",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_1-input-batchSize-number"
},
{
"label": "Timeout",
"name": "timeout",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_1-input-timeout-number"
},
{
"label": "BasePath",
"name": "basepath",
"type": "string",
"optional": true,
"additionalParams": true,
"id": "openAIEmbeddings_1-input-basepath-string"
}
],
"inputAnchors": [],
"inputs": {
"stripNewLines": "",
"batchSize": "100",
"timeout": ""
},
"outputAnchors": [
{
"id": "openAIEmbeddings_1-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
"name": "openAIEmbeddings",
"label": "OpenAIEmbeddings",
"type": "OpenAIEmbeddings | Embeddings"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 719.8090613945707,
"y": 875.480986998991
},
"dragging": false
},
{
"width": 300,
"height": 525,
"id": "chatOpenAI_0",
"position": {
"x": 1201.5421033751813,
"y": -33.64814327538039
},
"type": "customNode",
"data": {
"id": "chatOpenAI_0",
"label": "ChatOpenAI",
"name": "chatOpenAI",
"type": "ChatOpenAI",
"baseClasses": [
"ChatOpenAI",
"BaseChatModel",
"BaseLanguageModel",
"BaseLangChain"
],
"category": "Chat Models",
"description": "Wrapper around OpenAI large language models that use the Chat endpoint",
"inputParams": [
{
"label": "OpenAI Api Key",
"name": "openAIApiKey",
"type": "password",
"id": "chatOpenAI_0-input-openAIApiKey-password"
},
{
"label": "Model Name",
"name": "modelName",
"type": "options",
"options": [
{
"label": "gpt-4",
"name": "gpt-4"
},
{
"label": "gpt-4-0314",
"name": "gpt-4-0314"
},
{
"label": "gpt-4-32k-0314",
"name": "gpt-4-32k-0314"
},
{
"label": "gpt-4-0613",
"name": "gpt-4-0613"
},
{
"label": "gpt-3.5-turbo",
"name": "gpt-3.5-turbo"
},
{
"label": "gpt-3.5-turbo-0301",
"name": "gpt-3.5-turbo-0301"
},
{
"label": "gpt-3.5-turbo-0613",
"name": "gpt-3.5-turbo-0613"
}
],
"default": "gpt-3.5-turbo",
"optional": true,
"id": "chatOpenAI_0-input-modelName-options"
},
{
"label": "Temperature",
"name": "temperature",
"type": "number",
"default": 0.9,
"optional": true,
"id": "chatOpenAI_0-input-temperature-number"
},
{
"label": "Max Tokens",
"name": "maxTokens",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-maxTokens-number"
},
{
"label": "Top Probability",
"name": "topP",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-topP-number"
},
{
"label": "Frequency Penalty",
"name": "frequencyPenalty",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-frequencyPenalty-number"
},
{
"label": "Presence Penalty",
"name": "presencePenalty",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-presencePenalty-number"
},
{
"label": "Timeout",
"name": "timeout",
"type": "number",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-timeout-number"
},
{
"label": "BasePath",
"name": "basepath",
"type": "string",
"optional": true,
"additionalParams": true,
"id": "chatOpenAI_0-input-basepath-string"
}
],
"inputAnchors": [],
"inputs": {
"modelName": "gpt-3.5-turbo-0613",
"temperature": "0.9",
"maxTokens": "",
"topP": "",
"frequencyPenalty": "",
"presencePenalty": "",
"timeout": ""
},
"outputAnchors": [
{
"id": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain",
"name": "chatOpenAI",
"label": "ChatOpenAI",
"type": "ChatOpenAI | BaseChatModel | BaseLanguageModel | BaseLangChain"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 1201.5421033751813,
"y": -33.64814327538039
},
"dragging": false
},
{
"width": 300,
"height": 430,
"id": "conversationalRetrievalQAChain_0",
"position": {
"x": 1627.1855024401737,
"y": 394.42287890442145
},
"type": "customNode",
"data": {
"id": "conversationalRetrievalQAChain_0",
"label": "Conversational Retrieval QA Chain",
"name": "conversationalRetrievalQAChain",
"type": "ConversationalRetrievalQAChain",
"baseClasses": [
"ConversationalRetrievalQAChain",
"BaseChain",
"BaseLangChain"
],
"category": "Chains",
"description": "Document QA - built on RetrievalQAChain to provide a chat history component",
"inputParams": [
{
"label": "Return Source Documents",
"name": "returnSourceDocuments",
"type": "boolean",
"optional": true,
"id": "conversationalRetrievalQAChain_0-input-returnSourceDocuments-boolean"
},
{
"label": "System Message",
"name": "systemMessagePrompt",
"type": "string",
"rows": 4,
"additionalParams": true,
"optional": true,
"placeholder": "I want you to act as a document that I am having a conversation with. Your name is \"AI Assistant\". You will provide me with answers from the given info. If the answer is not included, say exactly \"Hmm, I am not sure.\" and stop after that. Refuse to answer any question not about the info. Never break character.",
"id": "conversationalRetrievalQAChain_0-input-systemMessagePrompt-string"
},
{
"label": "Chain Option",
"name": "chainOption",
"type": "options",
"options": [
{
"label": "MapReduceDocumentsChain",
"name": "map_reduce",
"description": "Suitable for QA tasks over larger documents and can run the preprocessing step in parallel, reducing the running time"
},
{
"label": "RefineDocumentsChain",
"name": "refine",
"description": "Suitable for QA tasks over a large number of documents."
},
{
"label": "StuffDocumentsChain",
"name": "stuff",
"description": "Suitable for QA tasks over a small number of documents."
}
],
"additionalParams": true,
"optional": true,
"id": "conversationalRetrievalQAChain_0-input-chainOption-options"
}
],
"inputAnchors": [
{
"label": "Language Model",
"name": "model",
"type": "BaseLanguageModel",
"id": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel"
},
{
"label": "Vector Store Retriever",
"name": "vectorStoreRetriever",
"type": "BaseRetriever",
"id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever"
}
],
"inputs": {
"model": "{{chatOpenAI_0.data.instance}}",
"vectorStoreRetriever": "{{pineconeExistingIndex_0.data.instance}}",
"chainOption": "stuff",
"systemMessagePrompt": "I want you to act as a document that I am having a conversation with. Your name is \"Onli.AI\". You will provide me with thorough answers from the given info. If the answer is not included, search for an answer and return it, and make a note that you searched outside of the given info. Never break character.",
"returnSourceDocuments": false
},
"outputAnchors": [
{
"id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain|BaseLangChain",
"name": "conversationalRetrievalQAChain",
"label": "ConversationalRetrievalQAChain",
"type": "ConversationalRetrievalQAChain | BaseChain | BaseLangChain"
}
],
"outputs": {},
"selected": false
},
"selected": false,
"positionAbsolute": {
"x": 1627.1855024401737,
"y": 394.42287890442145
},
"dragging": false
},
{
"width": 300,
"height": 605,
"id": "pineconeExistingIndex_0",
"position": {
"x": 1203.6567389964905,
"y": 619.6430879053763
},
"type": "customNode",
"data": {
"id": "pineconeExistingIndex_0",
"label": "Pinecone Load Existing Index",
"name": "pineconeExistingIndex",
"type": "Pinecone",
"baseClasses": [
"Pinecone",
"VectorStoreRetriever",
"BaseRetriever"
],
"category": "Vector Stores",
"description": "Load existing index from Pinecone (i.e: Document has been upserted)",
"inputParams": [
{
"label": "Pinecone Api Key",
"name": "pineconeApiKey",
"type": "password",
"id": "pineconeExistingIndex_0-input-pineconeApiKey-password"
},
{
"label": "Pinecone Environment",
"name": "pineconeEnv",
"type": "string",
"id": "pineconeExistingIndex_0-input-pineconeEnv-string"
},
{
"label": "Pinecone Index",
"name": "pineconeIndex",
"type": "string",
"id": "pineconeExistingIndex_0-input-pineconeIndex-string"
},
{
"label": "Pinecone Namespace",
"name": "pineconeNamespace",
"type": "string",
"placeholder": "my-first-namespace",
"additionalParams": true,
"optional": true,
"id": "pineconeExistingIndex_0-input-pineconeNamespace-string"
},
{
"label": "Pinecone Metadata Filter",
"name": "pineconeMetadataFilter",
"type": "json",
"optional": true,
"additionalParams": true,
"id": "pineconeExistingIndex_0-input-pineconeMetadataFilter-json"
},
{
"label": "Top K",
"name": "topK",
"description": "Number of top results to fetch. Default to 4",
"placeholder": "4",
"type": "number",
"additionalParams": true,
"optional": true,
"id": "pineconeExistingIndex_0-input-topK-number"
}
],
"inputAnchors": [
{
"label": "Embeddings",
"name": "embeddings",
"type": "Embeddings",
"id": "pineconeExistingIndex_0-input-embeddings-Embeddings"
}
],
"inputs": {
"embeddings": "{{openAIEmbeddings_1.data.instance}}",
"pineconeEnv": "asia-southeast1-gcp-free",
"pineconeIndex": "ian-dev",
"pineconeNamespace": "trainingpdf-1017am-062623",
"pineconeMetadataFilter": "",
"topK": "10"
},
"outputAnchors": [
{
"name": "output",
"label": "Output",
"type": "options",
"options": [
{
"id": "pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever",
"name": "retriever",
"label": "Pinecone Retriever",
"type": "Pinecone | VectorStoreRetriever | BaseRetriever"
},
{
"id": "pineconeExistingIndex_0-output-vectorStore-Pinecone|VectorStore",
"name": "vectorStore",
"label": "Pinecone Vector Store",
"type": "Pinecone | VectorStore"
}
],
"default": "retriever"
}
],
"outputs": {
"output": "retriever"
},
"selected": false
},
"positionAbsolute": {
"x": 1203.6567389964905,
"y": 619.6430879053763
},
"selected": false,
"dragging": false
}
],
"edges": [
{
"source": "chatOpenAI_0",
"sourceHandle": "chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain",
"target": "conversationalRetrievalQAChain_0",
"targetHandle": "conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"type": "buttonedge",
"id": "chatOpenAI_0-chatOpenAI_0-output-chatOpenAI-ChatOpenAI|BaseChatModel|BaseLanguageModel|BaseLangChain-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-model-BaseLanguageModel",
"data": {
"label": ""
}
},
{
"source": "openAIEmbeddings_1",
"sourceHandle": "openAIEmbeddings_1-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings",
"target": "pineconeExistingIndex_0",
"targetHandle": "pineconeExistingIndex_0-input-embeddings-Embeddings",
"type": "buttonedge",
"id": "openAIEmbeddings_1-openAIEmbeddings_1-output-openAIEmbeddings-OpenAIEmbeddings|Embeddings-pineconeExistingIndex_0-pineconeExistingIndex_0-input-embeddings-Embeddings",
"data": {
"label": ""
}
},
{
"source": "pineconeExistingIndex_0",
"sourceHandle": "pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever",
"target": "conversationalRetrievalQAChain_0",
"targetHandle": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
"type": "buttonedge",
"id": "pineconeExistingIndex_0-pineconeExistingIndex_0-output-retriever-Pinecone|VectorStoreRetriever|BaseRetriever-conversationalRetrievalQAChain_0-conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever",
"data": {
"label": ""
}
}
]
}
This is the chatflow from what I'm using with my nextjs app currently. But I'm not sure it reflects what is actually there.
Here is a screenshot of the general flow just in case.
I faced the same issue, upon debugging I realised that the authentication headers in my query flow on Flowise had changed without my intervention. Surprisingly, this didn't occur in the upsert flow. I changed the header key value pair and the issue was resolved. But still no idea how this happened. If you're using authentication headers while sending API request, make sure the client has the same headers as you have on Flowise.
@ianmcfall I'm not able to replicate your error after sending 12+ requests but I'm running it locally.
@chungyau97 @acerock6 Thanks for the help. I realized that the issue is coming from how I set my headers in my nextjs app. They're actually being set twice. 🤦