feat: add Telnyx chat, embeddings, audio, and telecom integrations

packages/components/credentials/TelnyxApi.credential.ts

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+import { INodeParams, INodeCredential } from '../src/Interface'
+
+class TelnyxApi implements INodeCredential {
+    label: string
+    name: string
+    version: number
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Telnyx API'
+        this.name = 'telnyxApi'
+        this.version = 1.0
+        this.inputs = [
+            {
+                label: 'API Key',
+                name: 'apiKey',
+                type: 'password'
+            }
+        ]
+    }
+}
+
+module.exports = { credClass: TelnyxApi }

packages/components/nodes/chatmodels/ChatTelnyx/ChatTelnyx.ts

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+import { ChatOpenAI, ChatOpenAIFields } from '@langchain/openai'
+import { BaseCache } from '@langchain/core/caches'
+import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { secureFetch } from '../../../src/httpSecurity'
+
+const TELNYX_OPENAI_BASE = 'https://api.telnyx.com/v2/ai/openai'
+const TELNYX_CHAT_MODELS_URL = 'https://api.telnyx.com/v2/ai/openai/models'
+
+const fetchTelnyxModels = async (apiKey: string) => {
+    const response = await secureFetch(TELNYX_CHAT_MODELS_URL, {
+        headers: {
+            Authorization: `Bearer ${apiKey}`,
+            'Content-Type': 'application/json'
+        }
+    })
+
+    if (!response.ok) {
+        throw new Error(`Failed to fetch Telnyx models: ${response.status} ${response.statusText}`)
+    }
+
+    const json = await response.json()
+    return json.data || []
+}
+
+class ChatTelnyx_ChatModels implements INode {
+    label: string
+    name: string
+    version: number
+    type: string
+    icon: string
+    category: string
+    description: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Telnyx Chat'
+        this.name = 'chatTelnyx'
+        this.version = 1.1
+        this.type = 'ChatTelnyx'
+        this.icon = 'telnyx.png'
+        this.category = 'Chat Models'
+        this.description = 'Use Telnyx OpenAI-compatible chat completions as a native Flowise chat model'
+        this.baseClasses = [this.type, ...getBaseClasses(ChatOpenAI)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['telnyxApi'],
+            refresh: true
+        }
+        this.inputs = [
+            { label: 'Cache', name: 'cache', type: 'BaseCache', optional: true },
+            { label: 'Model Name', name: 'modelName', type: 'asyncOptions', loadMethod: 'listModels', default: 'openai/gpt-4o', refresh: true },
+            { label: 'Temperature', name: 'temperature', type: 'number', step: 0.1, default: 0.9, optional: true },
+            { label: 'Streaming', name: 'streaming', type: 'boolean', default: true, optional: true, additionalParams: true },
+            { label: 'Max Tokens', name: 'maxTokens', type: 'number', step: 1, optional: true, additionalParams: true },
+            { label: 'Top Probability', name: 'topP', type: 'number', step: 0.1, optional: true, additionalParams: true },
+            { label: 'Frequency Penalty', name: 'frequencyPenalty', type: 'number', step: 0.1, optional: true, additionalParams: true },
+            { label: 'Presence Penalty', name: 'presencePenalty', type: 'number', step: 0.1, optional: true, additionalParams: true },
+            { label: 'Timeout', name: 'timeout', type: 'number', step: 1, optional: true, additionalParams: true }
+        ]
+    }
+
+    //@ts-ignore
+    loadMethods = {
+        async listModels(nodeData: INodeData, options: ICommonObject): Promise<INodeOptionsValue[]> {
+            const credentialId = nodeData.credential || nodeData.inputs?.credentialId
+            if (!credentialId) {
+                return [{ label: 'Select a Telnyx API credential to load models', name: 'openai/gpt-4o' }]
+            }
+
+            try {
+                const credentialData = await getCredentialData(credentialId as string, options)
+                const apiKey = getCredentialParam('apiKey', credentialData, nodeData)
+                const models = await fetchTelnyxModels(apiKey)
+
+                return models
+                    .map((model: any) => ({
+                        label: model.id,
+                        name: model.id,
+                        description: [model.task, model.context_length ? `context ${model.context_length}` : '', model.tier || '']
+                            .filter(Boolean)
+                            .join(' • ')
+                    }))
+            } catch (error) {
+                console.warn('Falling back to static Telnyx chat model list:', error)
+                return [{ label: 'openai/gpt-4o', name: 'openai/gpt-4o' }]
+            }
+        }
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const temperature = nodeData.inputs?.temperature as string
+        const modelName = nodeData.inputs?.modelName as string
+        const maxTokens = nodeData.inputs?.maxTokens as string
+        const topP = nodeData.inputs?.topP as string
+        const frequencyPenalty = nodeData.inputs?.frequencyPenalty as string
+        const presencePenalty = nodeData.inputs?.presencePenalty as string
+        const timeout = nodeData.inputs?.timeout as string
+        const streaming = nodeData.inputs?.streaming as boolean
+        const cache = nodeData.inputs?.cache as BaseCache
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const apiKey = getCredentialParam('apiKey', credentialData, nodeData)
+
+        const parsedTemperature = temperature ? parseFloat(temperature) : 0.9
+        if (Number.isNaN(parsedTemperature)) {
+            throw new Error('Temperature must be a valid number')
+        }
+
+        const obj: ChatOpenAIFields = {
+            temperature: parsedTemperature,
+            modelName,
+            openAIApiKey: apiKey,
+            apiKey,
+            streaming: streaming ?? true,
+            configuration: {
+                baseURL: TELNYX_OPENAI_BASE
+            }
+        }
+
+        if (maxTokens) obj.maxTokens = parseInt(maxTokens, 10)
+        if (topP) obj.topP = parseFloat(topP)
+        if (frequencyPenalty) obj.frequencyPenalty = parseFloat(frequencyPenalty)
+        if (presencePenalty) obj.presencePenalty = parseFloat(presencePenalty)
+        if (timeout) obj.timeout = parseInt(timeout, 10)
+        if (cache) obj.cache = cache
+
+        return new ChatOpenAI(obj)
+    }
+}
+
+module.exports = { nodeClass: ChatTelnyx_ChatModels }

packages/components/nodes/chatmodels/ChatTelnyx/README.md

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+# Telnyx Chat Model
+
+Telnyx Chat Model integration for Flowise
+
+## 🌱 Env Variables
+
+| Variable        | Description                                           | Type   | Default |
+| --------------- | ----------------------------------------------------- | ------ | ------- |
+| TELNYX_API_KEY  | Default `credential.apiKey` for the Telnyx API        | String |         |
+
+## License
+
+Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).

packages/components/nodes/embeddings/TelnyxEmbedding/README.md

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+# Telnyx Embedding Model
+
+Telnyx Embedding Model integration for Flowise
+
+## 🌱 Env Variables
+
+| Variable        | Description                                           | Type   | Default |
+| --------------- | ----------------------------------------------------- | ------ | ------- |
+| TELNYX_API_KEY  | Default `credential.apiKey` for the Telnyx API        | String |         |
+
+## License
+
+Source code in this repository is made available under the [Apache License Version 2.0](https://github.com/FlowiseAI/Flowise/blob/master/LICENSE.md).

packages/components/nodes/embeddings/TelnyxEmbedding/TelnyxEmbedding.ts

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+import { ClientOptions, OpenAIEmbeddings, OpenAIEmbeddingsParams } from '@langchain/openai'
+import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
+import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
+import { secureFetch } from '../../../src/httpSecurity'
+
+const TELNYX_OPENAI_BASE = 'https://api.telnyx.com/v2/ai/openai'
+const TELNYX_EMBEDDINGS_MODELS_URL = 'https://api.telnyx.com/v2/ai/embeddings/models'
+
+const fetchTelnyxModels = async (apiKey: string) => {
+    const response = await secureFetch(TELNYX_EMBEDDINGS_MODELS_URL, {
+        headers: {
+            Authorization: `Bearer ${apiKey}`,
+            'Content-Type': 'application/json'
+        }
+    })
+
+    if (!response.ok) {
+        throw new Error(`Failed to fetch Telnyx models: ${response.status} ${response.statusText}`)
+    }
+
+    const json = await response.json()
+    return json.data || []
+}
+
+class TelnyxEmbedding_Embeddings implements INode {
+    label: string
+    name: string
+    version: number
+    type: string
+    icon: string
+    category: string
+    description: string
+    baseClasses: string[]
+    credential: INodeParams
+    inputs: INodeParams[]
+
+    constructor() {
+        this.label = 'Telnyx Embeddings'
+        this.name = 'telnyxEmbeddings'
+        this.version = 1.1
+        this.type = 'TelnyxEmbeddings'
+        this.icon = 'telnyx.png'
+        this.category = 'Embeddings'
+        this.description = 'Use Telnyx OpenAI-compatible embeddings as a native Flowise embeddings node'
+        this.baseClasses = [this.type, ...getBaseClasses(OpenAIEmbeddings)]
+        this.credential = {
+            label: 'Connect Credential',
+            name: 'credential',
+            type: 'credential',
+            credentialNames: ['telnyxApi'],
+            refresh: true
+        }
+        this.inputs = [
+            { label: 'Model Name', name: 'modelName', type: 'asyncOptions', loadMethod: 'listModels', default: 'text-embedding-3-small', refresh: true },
+            { label: 'Strip New Lines', name: 'stripNewLines', type: 'boolean', optional: true, additionalParams: true },
+            { label: 'Batch Size', name: 'batchSize', type: 'number', optional: true, additionalParams: true },
+            { label: 'Timeout', name: 'timeout', type: 'number', optional: true, additionalParams: true },
+            { label: 'Dimensions', name: 'dimensions', type: 'number', optional: true, additionalParams: true },
+            { label: 'Encoding Format', name: 'encodingFormat', type: 'options', options: [{ label: 'float', name: 'float' }, { label: 'base64', name: 'base64' }], optional: true, additionalParams: true }
+        ]
+    }
+
+    //@ts-ignore
+    loadMethods = {
+        async listModels(nodeData: INodeData, options: ICommonObject): Promise<INodeOptionsValue[]> {
+            const credentialId = nodeData.credential || nodeData.inputs?.credentialId
+            if (!credentialId) {
+                return [{ label: 'Select a Telnyx API credential to load models', name: 'text-embedding-3-small' }]
+            }
+
+            try {
+                const credentialData = await getCredentialData(credentialId as string, options)
+                const apiKey = getCredentialParam('apiKey', credentialData, nodeData)
+                const models = await fetchTelnyxModels(apiKey)
+
+                return models
+                    .map((model: any) => ({
+                        label: model.id,
+                        name: model.id,
+                        description: [model.task, model.context_length ? `context ${model.context_length}` : '', model.tier || '']
+                            .filter(Boolean)
+                            .join(' • ')
+                    }))
+            } catch (error) {
+                console.warn('Falling back to static Telnyx embeddings model list:', error)
+                return [{ label: 'text-embedding-3-small', name: 'text-embedding-3-small' }]
+            }
+        }
+    }
+
+    async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
+        const stripNewLines = nodeData.inputs?.stripNewLines as boolean
+        const batchSize = nodeData.inputs?.batchSize as string
+        const timeout = nodeData.inputs?.timeout as string
+        const modelName = nodeData.inputs?.modelName as string
+        const dimensions = nodeData.inputs?.dimensions as string
+        const encodingFormat = nodeData.inputs?.encodingFormat as 'float' | 'base64' | undefined
+
+        const credentialData = await getCredentialData(nodeData.credential ?? '', options)
+        const apiKey = getCredentialParam('apiKey', credentialData, nodeData)
+
+        const obj: Partial<OpenAIEmbeddingsParams> & { openAIApiKey?: string; configuration?: ClientOptions } = {
+            openAIApiKey: apiKey,
+            modelName,
+            configuration: {
+                baseURL: TELNYX_OPENAI_BASE
+            }
+        }
+
+        if (stripNewLines) obj.stripNewLines = stripNewLines
+        if (batchSize) obj.batchSize = parseInt(batchSize, 10)
+        if (timeout) obj.timeout = parseInt(timeout, 10)
+        if (dimensions) obj.dimensions = parseInt(dimensions, 10)
+        if (encodingFormat) obj.encodingFormat = encodingFormat
+
+        return new OpenAIEmbeddings(obj)
+    }
+}
+
+module.exports = { nodeClass: TelnyxEmbedding_Embeddings }