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DeepSeek ACTION

Create Chat Completion

Creates a chat completion using the DeepSeek API. See the documentation
  • Action
  • Writes data
  • API key
  • SDK
  • MCP

IMPLEMENTATION

Call this tool

Connect a user's DeepSeek account once, then configure and run Create Chat Completion from your backend or agent.

import { PipedreamClient } from "@pipedream/sdk"

const pd = new PipedreamClient({
  projectId: process.env.PIPEDREAM_PROJECT_ID!,
  clientId: process.env.PIPEDREAM_CLIENT_ID!,
  clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
  projectEnvironment: "production",
})

const result = await pd.actions.run({
  id: "deepseek-create-chat-completion",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    deepseek: { authProvisionId: "apn_xxxxxxx" },
    messages: ["Messages"],
    frequencyPenalty: "Frequency Penalty",
  },
})

console.log(result)

SCHEMA

Inputs

Pipedream supplies the connected account. Your application provides the operation-specific values below. Dynamic inputs are resolved against that user's account.

Create Chat Completion inputs
Property Type Description
messages Messages string[]
The messages for the chat conversation as JSON strings. Each message should be a JSON string like '{"role": "user", "content": "Hello!"}'. See the documentation for further details.
Required
frequencyPenalty Frequency Penalty string
Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
Optional
maxTokens Max Tokens integer
Integer between 1 and 8192. The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length. If max_tokens is not specified, the default value 4096 is used.
Optional
presencePenalty Presence Penalty string
Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
Optional
responseFormatType Response Format Type string
The format that the model must output. Setting to JSON Object enables JSON Output, which guarantees the message the model generates is valid JSON.
Optional
stop Stop Sequences string[]
Up to 16 sequences where the API will stop generating further tokens.
Optional
stream Stream boolean
If set, partial message deltas will be sent. Tokens will be sent as data-only server-sent events (SSE) as they become available, with the stream terminated by a data: [DONE] message.
Optional
streamIncludeUsage Stream Include Usage string
If set, an additional chunk will be streamed before the data: [DONE] message. The usage field on this chunk shows the token usage statistics for the entire request, and the choices field will always be an empty array. All other chunks will also include a usage field, but with a null value.
Optional
temperature Temperature string
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or Top P but not both.
Optional
topP Top P string
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or Temperature but not both.
Optional
tools Tools string[]
A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
Optional
toolChoice Tool Choice string
Controls which (if any) tool is called by the model. See the documentation for further details.
Optional
logprobs Log Probs boolean
Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.
Optional
topLogprobs Top Log Probabilities string
An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.
Optional

REFERENCE

Tool details

Behavior hints are published with the component in the Pipedream registry and surface as MCP tool annotations, so an agent can reason about a tool before it calls it.

Registry key
deepseek-create-chat-completion
Version
0.0.2
App
DeepSeek
Authentication
API key
Read-only
No
Destructive
No
Open world
Yes