Docs Connect Components Processors openai_chat_completion openai_chat_completion Beta Available in: Cloud, Self-Managed License: This component requires an enterprise license. You can either upgrade to an Enterprise Edition license, or generate a trial license key that's valid for 30 days. Generates responses to messages in a chat conversation, using the OpenAI API and external tools. Introduced in version 4.32.0. Common Advanced # Common configuration fields, showing default values label: "" openai_chat_completion: server_address: https://api.openai.com/v1 api_key: "" # No default (required) model: gpt-4o # No default (required) prompt: "" # No default (optional) system_prompt: "" # No default (optional) image: 'root = this.image.decode("base64") # decode base64 encoded image' # No default (optional) max_tokens: 0 # No default (optional) temperature: 0 # No default (optional) user: "" # No default (optional) response_format: text json_schema: name: "" # No default (required) schema: "" # No default (required) tools: [] # No default (required) # All configuration fields, showing default values label: "" openai_chat_completion: server_address: https://api.openai.com/v1 api_key: "" # No default (required) model: gpt-4o # No default (required) prompt: "" # No default (optional) system_prompt: "" # No default (optional) image: 'root = this.image.decode("base64") # decode base64 encoded image' # No default (optional) max_tokens: 0 # No default (optional) temperature: 0 # No default (optional) user: "" # No default (optional) response_format: text json_schema: name: "" # No default (required) description: "" # No default (optional) schema: "" # No default (required) schema_registry: url: "" # No default (required) name_prefix: schema_registry_id_ subject: "" # No default (required) refresh_interval: "" # No default (optional) tls: skip_cert_verify: false enable_renegotiation: false root_cas: "" # No default (optional) root_cas_file: "" # No default (optional) client_certs: [] # Optional oauth: enabled: false consumer_key: "" # No default (optional) consumer_secret: "" # No default (optional) access_token: "" # No default (optional) access_token_secret: "" # No default (optional) basic_auth: enabled: false username: "" # No default (optional) password: "" # No default (optional) jwt: enabled: false private_key_file: "" # No default (optional) signing_method: "" # No default (optional) claims: {} # Optional headers: {} # Optional top_p: 0 # No default (optional) frequency_penalty: 0 # No default (optional) presence_penalty: 0 # No default (optional) seed: 0 # No default (optional) stop: [] # No default (optional) tools: [] # No default (required) This processor sends user prompts to the OpenAI API, and the specified large language model (LLM) generates responses using all available context, including supplementary data provided by external tools. By default, the processor submits the entire payload of each message as a string, unless you use the prompt configuration field to customize it. To learn more about chat completion, see the OpenAI API documentation, and Examples. Fields server_address The OpenAI API endpoint to which the processor sends requests. Update the default value to use a different OpenAI-compatible service. Type: string Default: "https://api.openai.com/v1" api_key The API secret key for OpenAI API. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string model The name of the OpenAI model to use. Type: string # Examples model: gpt-4o model: gpt-4o-mini model: gpt-4 model: gpt4-turbo prompt The user prompt for which a response is generated. By default, the processor sends the entire payload as a string unless customized using this field. Type: string system_prompt The system prompt to submit along with the user prompt. This field supports interpolation functions. Type: string image An optional image to submit along with the prompt. The result of the Bloblang mapping must be a byte array. Type: string # Examples image: 'root = this.image.decode("base64")' # Decode base64 encoded image Requires version 4.38.0 or newer max_tokens The maximum number of tokens to generate for chat completion. Type: int temperature Choose a sampling temperature between 0 and 2: Higher values, such as 0.8 make the output more random. Lower values, such as 0.2 make the output more focused and deterministic. Redpanda recommends adding a value for this field or top_p, but not both. Type: float user A unique identifier that represents the end-user generating the prompt. This value can help OpenAI monitor and detect platform abuse. This field supports interpolation functions. Type: string response_format Specify the configured model’s output format. If you choose the json_schema option, you must also configure a json_schema or schema_registry. Type: string Default: text Options: text, json, json_schema json_schema The JSON schema used by the model when generating responses in json_schema format. To learn more about supported JSON schema features, see the OpenAI documentation. Type: object json_schema.name The name of the JSON schema to use. Type: string json_schema.description An optional description, which helps the model understand the schema’s purpose. Type: string json_schema.schema The JSON schema for the model to use when generating the output. Type: string schema_registry The schema registry to dynamically load schemas for model responses in json_schema format. Schemas must be in JSON format. To learn more about supported JSON schema features, see the OpenAI documentation. Type: object schema_registry.url The base URL of the schema registry service. Type: string schema_registry.name_prefix A prefix to add to the schema registry name. To form the complete schema registry name, the schema ID is appended as a suffix. Type: string Default: schema_registry_id_ schema_registry.subject The subject name used to fetch the schema from the schema registry. Type: string schema_registry.refresh_interval How frequently to poll the schema registry for updates. If not specified, the schema does not refresh automatically. Type: string schema_registry.tls Specify custom TLS settings to override system defaults. Type: object schema_registry.tls.skip_cert_verify Whether to skip server-side certificate verification. Type: bool Default: false schema_registry.tls.enable_renegotiation Whether to allow the remote server to request renegotiation. Enable this option if you’re seeing the error message local error: tls: no renegotiation. Type: bool Default: false Requires version 3.45.0 or newer schema_registry.tls.root_cas Specify a certificate authority to use (optional). This is a string that represents a certificate chain from the parent trusted root certificate, through possible intermediate signing certificates, to the host certificate. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string Default: "" # Examples root_cas: |- -----BEGIN CERTIFICATE----- ... -----END CERTIFICATE----- schema_registry.tls.root_cas_file Specify the path to a root certificate authority file (optional). This is a file, often with a .pem extension, that contains a certificate chain from the parent trusted root certificate, through possible intermediate signing certificates, to the host certificate.certificate. Type: string Default: "" # Examples root_cas_file: ./root_cas.pem schema_registry.tls.client_certs A list of client certificates to use. For each certificate, specify values for either the cert and key fields, or cert_file and key_file fields. Type: array Default: [] # Examples client_certs: - cert: foo key: bar client_certs: - cert_file: ./example.pem key_file: ./example.key schema_registry.tls.client_certs[].cert The plain text certificate to use. Type: string Default: "" schema_registry.tls.client_certs[].key The plain text certificate key to use. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string Default: "" schema_registry.tls.client_certs[].cert_file The path to the certificate to use. Type: string Default: "" schema_registry.tls.client_certs[].key_file The path of a certificate key to use. Type: string Default: "" schema_registry.tls.client_certs[].password The plain text password for when the private key is password encrypted in PKCS#1 or PKCS#8 format. The obsolete pbeWithMD5AndDES-CBC algorithm is not supported for the PKCS#8 format. The pbeWithMD5AndDES-CBC algorithm does not authenticate ciphertext, and is vulnerable to padding oracle attacks which may allow an attacker to recover the plain text password. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string Default: "" # Examples password: foo password: ${KEY_PASSWORD} schema_registry.oauth Configure OAuth version 1.0 to give this component authorized access to your schema registry. Type: object schema_registry.oauth.enabled Whether to use OAuth version 1 in requests to the schema registry. Type: bool Default: false schema_registry.oauth.consumer_key The value used to identify this component or client to your schema registry. Type: string Default: "" schema_registry.oauth.consumer_secret The secret used to establish ownership of the consumer key. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string Default: "" schema_registry.oauth.access_token The value this component can use to gain access to the data in the schema registry. Type: string Default: "" schema_registry.oauth.access_token_secret The secret that establishes ownership of the oauth.access_token. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string Default: "" schema_registry.basic_auth Configure basic authentication for requests from this component to your schema registry. Type: object schema_registry.basic_auth.enabled Whether to use basic authentication in requests. Type: bool Default: false schema_registry.basic_auth.username The username of the account credentials to authenticate as. Type: string Default: "" schema_registry.basic_auth.password The password of the account credentials to authenticate with. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string Default: "" schema_registry.jwt (beta) Configure JSON Web Token (JWT) authentication for the secure transmission of data from your schema registry to this component. Type: object schema_registry.jwt.enabled Whether to use JWT authentication in requests. Type: bool Default: false schema_registry.jwt.private_key_file A file in PEM format, encoded using PKCS1 or PKCS8 as private key. Type: string Default: "" schema_registry.jwt.signing_method The method used to sign the token, such as RS256, RS384, RS512, or EdDSA. Type: string Default: "" schema_registry.jwt.claims Values used to pass the identity of the authenticated entity to the service provider. In this case, between this component and the schema registry. Type: object Default: {} schema_registry.jwt.headers The key/value pairs that identify the type of token and signing algorithm (optional). Type: object Default: {} top_p An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. For example, a top_p of 0.1 means only the tokens comprising the top 10% probability mass are sampled. Redpanda recommends adding a value for this field or temperature, but not both. Type: float frequency_penalty Specify a number between -2.0 and 2.0. Positive values penalize new tokens based on the frequency of their appearance in the text so far. This decreases the model’s likelihood to repeat the same line verbatim. Type: float presence_penalty Specify a number between -2.0 and 2.0. Positive values penalize new tokens if they have appeared in the text so far. This increases the model’s likelihood to talk about new topics. Type: float seed When set to a specific number, Redpanda Connect attempts to generate consistent responses for requests that use the same prompt, seed, and parameters. Type: int # Examples seed: 42 stop Specify up to four stop sequences to use. When the model encounters a stop pattern, it stops generating text and returns the final response. Type: array tools External tools the model can invoke, such as functions, APIs, or web browsing. You can build a series of processors that include definitions of these tools, and the specified model can choose when to invoke them to help answer a prompt. For more information, see Examples. If you don’t want to use external tools, enter an empty array tools:[]. Type: array tools[].name The name of the external tool you want to use. Type: string tools[].description A description of what the tool does. The model uses this to decide when to invoke the tool. Type: string tools[].parameters The parameters the model needs to invoke the tool. Type: object tools[].parameters.required The parameters you must define. Type: array Default: [] tools[].parameters.properties The required inputs to invoke the tool. Type: object tools[].parameters.properties.<name>.type The data type of the parameter. Type: string tools[].parameters.properties.<name>.description A description of the parameter. Type: string tools[].parameters.properties.<name>.enum Defines this parameter as an enumeration and specifies the set of values the model is allowed to use. Type: array Default: [] tools[].processors The pipeline to execute when the model invokes the external tool. Type: array Examples Analyze an image and generate a description Make calls to external tools This configuration fetches image URLs from the stdin input, and uses the GPT-4o LLM to describe the images. input: stdin: scanner: lines: {} pipeline: processors: - http: verb: GET url: "${!content().string()}" - openai_chat_completion: model: gpt-4o api_key: "${OPENAI_API_KEY}" prompt: "Describe the following image" image: "root = content()" output: stdout: codec: lines: lines In this configuration, the GPT-4o model executes a number of processors, which make a tool call to retrieve weather data for a specific city. input: generate: count: 1 mapping: | root = "What is the weather like in Chicago?" pipeline: processors: - openai_chat_completion: model: gpt-4o api_key: "${OPENAI_API_KEY}" prompt: "${!content().string()}" tools: - name: GetWeather description: "Retrieve the weather for a specific city" parameters: required: ["city"] properties: city: type: string description: the city to look up the weather for processors: - http: verb: GET url: 'https://wttr.in/${!this.city}?T' headers: User-Agent: curl/8.11.1 # Returns a text string from the weather website output: stdout: {} Back to top × Simple online edits For simple changes, such as fixing a typo, you can edit the content directly on GitHub. 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