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For the complete documentation index for agents and LLMs, see llms.txt.

OpenAIChatGenerator

Complete chats using OpenAI's large language models (LLMs).

Key Features

  • Works with GPT-4, GPT-5, and o-series models via the OpenAI API.
  • Accepts ChatMessage objects as input and returns generated replies as ChatMessage objects.
  • Supports streaming responses via a callback function.
  • Supports tool calls for agentic workflows.
  • Supports customizable generation parameters via generation_kwargs.

Configuration

  1. Drag the OpenAIChatGenerator component onto the canvas from the Component Library.
  2. Click on the component to open the configuration panel.
  3. On the General tab:
    • Set the model name.
    • Set the OpenAI API key. Connect the platform to your OpenAI account on the Integrations page first. For details, see Use OpenAI Models.
  4. Go to the Advanced tab to configure api_base_url, timeout, max_retries, generation_kwargs, and http_client_kwargs.

Connections

OpenAIChatGenerator accepts a list of ChatMessage objects as input. Connect its messages input to the prompt output of ChatPromptBuilder.

It outputs replies as a list of ChatMessage objects. Connect its replies output through OutputAdapter to DeepsetAnswerBuilder or AnswerBuilder.

Source Code

To check this component's source code, open openai.py in the Haystack repository.

Usage Examples

Basic Configuration

  openai_chat_generator:
type: haystack.components.generators.chat.openai.OpenAIChatGenerator
init_parameters:
model: gpt-5-mini
generation_kwargs:
temperature: 0.7
max_tokens: 500

This is an example RAG pipeline with OpenAIChatGenerator and DeepsetAnswerBuilder connected through OutputAdapter:

components:
bm25_retriever:
type: haystack_integrations.components.retrievers.opensearch.bm25_retriever.OpenSearchBM25Retriever
init_parameters:
document_store:
type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore
init_parameters:
hosts:
- ${OPENSEARCH_HOST}
http_auth:
- ${OPENSEARCH_USER}
- ${OPENSEARCH_PASSWORD}
use_ssl: true
verify_certs: false
top_k: 20

query_embedder:
type: haystack.components.embedders.sentence_transformers_text_embedder.SentenceTransformersTextEmbedder
init_parameters:
model: intfloat/e5-base-v2

embedding_retriever:
type: haystack_integrations.components.retrievers.opensearch.embedding_retriever.OpenSearchEmbeddingRetriever
init_parameters:
document_store:
type: haystack_integrations.document_stores.opensearch.document_store.OpenSearchDocumentStore
init_parameters:
hosts:
- ${OPENSEARCH_HOST}
http_auth:
- ${OPENSEARCH_USER}
- ${OPENSEARCH_PASSWORD}
use_ssl: true
verify_certs: false
top_k: 20

document_joiner:
type: haystack.components.joiners.document_joiner.DocumentJoiner
init_parameters:
join_mode: concatenate

ranker:
type: haystack.components.rankers.transformers_similarity.TransformersSimilarityRanker
init_parameters:
model: intfloat/simlm-msmarco-reranker
top_k: 8

chat_prompt_builder:
type: haystack.components.builders.chat_prompt_builder.ChatPromptBuilder
init_parameters:
template:
- _content:
- text: "You are a helpful assistant answering questions based on the provided documents.\nIf the documents don't contain the answer, say so.\nDo not use your own knowledge.\n"
_role: system
- _content:
- text: "Documents:\n{% for document in documents %}\nDocument [{{ loop.index }}]:\n{{ document.content }}\n{% endfor %}\n\nQuestion: {{ query }}\n"
_role: user

openai_chat_generator:
type: haystack.components.generators.chat.openai.OpenAIChatGenerator
init_parameters:
model: gpt-5-mini
generation_kwargs:
temperature: 0.7
max_tokens: 500

output_adapter:
type: haystack.components.converters.output_adapter.OutputAdapter
init_parameters:
template: '{{ replies[0] }}'
output_type: List[str]

answer_builder:
type: haystack.components.builders.answer_builder.AnswerBuilder
init_parameters: {}

connections:
- sender: bm25_retriever.documents
receiver: document_joiner.documents
- sender: query_embedder.embedding
receiver: embedding_retriever.query_embedding
- sender: embedding_retriever.documents
receiver: document_joiner.documents
- sender: document_joiner.documents
receiver: ranker.documents
- sender: ranker.documents
receiver: chat_prompt_builder.documents
- sender: ranker.documents
receiver: answer_builder.documents
- sender: chat_prompt_builder.prompt
receiver: openai_chat_generator.messages
- sender: openai_chat_generator.replies
receiver: output_adapter.replies
- sender: output_adapter.output
receiver: answer_builder.replies

max_runs_per_component: 100

inputs:
query:
- bm25_retriever.query
- query_embedder.text
- ranker.query
- chat_prompt_builder.query
- answer_builder.query
filters:
- bm25_retriever.filters
- embedding_retriever.filters

outputs:
documents: ranker.documents
answers: answer_builder.answers

metadata: {}

Parameters

Inputs

ParameterTypeDescription
messagesList[ChatMessage]A list of ChatMessage instances representing the input messages.
streaming_callbackOptional[StreamingCallbackT]A callback function called when a new token is received from the stream.
generation_kwargsOptional[Dict[str, Any]]Additional keyword arguments for text generation. These parameters override the parameters in pipeline configuration. For supported parameters, see OpenAI documentation.
toolsOptional[Union[List[Tool], Toolset]]A list of tools or a Toolset for which the model can prepare calls. If set, it overrides the tools parameter set during component initialization.
tools_strictOptional[bool]Whether to enable strict schema adherence for tool calls. If set, it overrides the tools_strict parameter in pipeline configuration.

Outputs

ParameterTypeDescription
repliesList[ChatMessage]A list containing the generated responses as ChatMessage instances.

Init Parameters

These are the parameters you can configure in Pipeline Builder:

ParameterTypeDefaultDescription
api_keySecretSecret.from_env_var('OPENAI_API_KEY')The OpenAI API key. Set it on the Integrations page.
modelstrgpt-5-miniThe name of the model to use.
streaming_callbackOptional[StreamingCallbackT]NoneA callback function called when a new token is received from the stream.
api_base_urlOptional[str]NoneAn optional base URL.
organizationOptional[str]NoneYour organization ID. See production best practices.
generation_kwargsOptional[Dict[str, Any]]NoneOther parameters to use for the model, sent directly to the OpenAI endpoint. See OpenAI documentation for more details.
timeoutOptional[float]30.0Timeout for OpenAI client calls. If not set, it defaults to the OPENAI_TIMEOUT environment variable or 30 seconds.
max_retriesOptional[int]fiveMaximum number of retries to contact OpenAI after an internal error. If not set, it defaults to the OPENAI_MAX_RETRIES environment variable or five.
toolsOptional[Union[List[Tool], Toolset]]NoneA list of tools or a Toolset for which the model can prepare calls.
tools_strictbooleanFalseWhether to enable strict schema adherence for tool calls. If set to True, the model follows exactly the schema provided in the parameters field of the tool definition, but this may increase latency.
http_client_kwargsOptional[Dict[str, Any]]NoneA dictionary of keyword arguments to configure a custom httpx.Client or httpx.AsyncClient. For more information, see the HTTPX documentation.

Run Method Parameters

These are the parameters you can configure for the component's run() method. This means you can pass these parameters at query time through the API, in Playground, or when running a job. For details, see Modify Pipeline Parameters at Query Time.

ParameterTypeDefaultDescription
messagesList[ChatMessage]A list of ChatMessage instances representing the input messages.
streaming_callbackOptional[StreamingCallbackT]NoneA callback function called when a new token is received from the stream.
generation_kwargsOptional[Dict[str, Any]]NoneAdditional keyword arguments for text generation. These parameters override the parameters in pipeline configuration. For supported parameters, see OpenAI documentation.
toolsOptional[Union[List[Tool], Toolset]]NoneA list of tools or a Toolset for which the model can prepare calls. If set, it overrides the tools parameter in pipeline configuration.
tools_strictOptional[bool]NoneWhether to enable strict schema adherence for tool calls. If set, it overrides the tools_strict parameter in pipeline configuration.