OPENAICHAT

Overview

The OPENAICHAT workflow application lets you interact with AI chat models from multiple providers, including OpenAI, Mistral AI, Google Gemini, and Anthropic Claude.

How it works

• The application allows you to interact with completion models.

• Application logs are available. These can be specified by setting the value of the OpenAIChatLogLevel parameter in the web.config file to 0 to deactivate logs, 1 for error logs, 2 for information logs, or 3 for debug logs; the default value is 0.

Supported providers

Provider	API format	Default URL
OpenAI	Native	https://api.openai.com/v1/chat/completions
Mistral AI	OpenAI-compatible	https://api.mistral.ai/v1/chat/completions
Google Gemini	OpenAI-compatible	https://generativelanguage.googleapis.com/v1beta/openai/chat/completions
Anthropic Claude	Native	https://api.anthropic.com/v1/messages

The provider is automatically detected from the API URL, but it can be explicitly set using the PROVIDER parameter (see the Optional parameters table below).

OpenAI-compatible providers

The OPENAICHAT application automatically detects and supports OpenAI-compatible providers based on the API URL. For providers that use the OpenAI-compatible API format (Mistral AI, Google Gemini), you can set the URL parameter (or the provider's API URL setting in the web.config file) to the provider's endpoint.

For Anthropic Claude, which uses a different native API, either set URL to an Anthropic endpoint (auto-detected), or set PROVIDER = anthropic explicitly.

Provider API configuration settings

Setting	Description
OpenAIApiKey	OpenAI API key
OpenAIChatApiUrl	OpenAI API endpoint
MistralApiKey	Mistral AI API key (required for Mistral)
MistralChatApiUrl	Mistral AI API endpoint Default: https://api.mistral.ai/v1/chat/completions
GeminiApiKey	Google Gemini API key (required for Gemini)
GeminiChatApiUrl	Google Gemini API endpoint Default: https://generativelanguage.googleapis.com/v1beta/openai/chat/completions Note: This is a beta endpoint that may change when GA.
AnthropicApiKey	Anthropic API key (required for Anthropic)
AnthropicChatApiUrl	Anthropic API endpoint Default: https://api.anthropic.com/v1/messages

Each provider requires its own API key. There is no cross-provider fallback.

Provider auto-detection

URL pattern	Detected provider
Contains api.anthropic.com	Anthropic
Contains generativelanguage.googleapis.com	Gemini
Contains api.mistral.ai	Mistral
Default	OpenAI

Compatible providers

Provider	Type
Azure OpenAI	Cloud
Ollama	Self-hosted
vLLM	Self-hosted
LocalAI	Self-hosted
LM Studio	Self-hosted
Together AI	Cloud
Groq	Cloud
Mistral AI	Cloud
OpenRouter	Cloud

• Do not use MAX_COMPLETION_TOKENS and REASONING_EFFORT with non-OpenAI providers unless you know the provider supports these parameters.

• Use MAX_TOKENS for token limits when using non-OpenAI providers.

• Some providers may ignore unsupported parameters, while others may return an error.

Required parameters

Parameter	Type	Direction	Description
MODEL	TEXT	IN	ID of the model to use You can find available models at the following link: https://platform.openai.com/docs/models/; the endpoint used by default is /v1/chat/completions.

You can use either of the following configurations: with system/user messages, with a message number, or with a JSON message array.

With system/user messages

Parameter	Type	Direction	Description
SYSTEM_MESSAGE	TEXT	IN	The system message content
USER_MESSAGE	TEXT	IN	The user message content

With a message number

Parameter	Type	Direction	Description
MESSAGE_ROLEx	TEXT	IN	The type of the message, where x corresponds to the message number; the value should be assistant, system, or user
MESSAGE_CONTENTx	TEXT	IN	The user message content, where x corresponds to the message number

With a JSON message array

Parameter	Type	Direction	Description
MESSAGE_JSON	TEXT	IN	The JSON array message object; the structure should match the following: [ { "role": "assistant/system/user", "content": "First message content" }, { "role": "assistant/system/user", "content": "Second message content" } ]

Optional parameters

Parameters	Type	Direction	Description
PROVIDER	TEXT	IN	Force provider selection; if not set, the provider is auto-detected from the URL Possible values: openai, mistral, gemini, or anthropic
API_KEY	TEXT	IN	API key By default, this value comes from the OpenAIApiKey parameter in the web.config file.
URL	TEXT	IN	API endpoint; this value comes from the OpenAIChatApiUrl parameter in the web.config file, if it's been defined
TEMPERATURE	NUMERIC	IN	Sampling temperature, between 0 and 1 Default: 1 Higher values (e.g. 0.8) will make the output more random, while lower values (e.g. 0.2) will make it more focused and deterministic.
TOP_P	NUMERIC	IN	An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass Default: 1 📌 Example: A value of 0.1 means only the tokens comprising the top 10% probability mass are considered.
FREQUENCY_PENALTY	NUMERIC	IN	Number between -2.0 and 2.0 Default: 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.
MAX_TOKENS	NUMERIC	IN	Maximum number of tokens that can be generated in the chat completion Default: 4096 for Anthropic only; undefined for other providers ✏️ Note: For reasoning models (o1, o3, GPT-5 series), use MAX_COMPLETION_TOKENS instead. If both MAX_TOKENS and MAX_COMPLETION_TOKENS are specified, MAX_COMPLETION_TOKENS takes precedence.
MAX_COMPLETION_TOKENS	NUMERIC	IN	Maximum number of tokens to generate in the completion This parameter is required for reasoning models (o1, o3, GPT-5 series) and takes precedence over MAX_TOKENS when both are specified. For reasoning models, this value includes both reasoning tokens and visible completion tokens.
REASONING_EFFORT	TEXT	IN	Controls the effort level for reasoning models; only applicable to reasoning models (o1, o3, GPT-5 series) Values: low, medium, or high ⚠️ Important: Do not use this parameter with non-reasoning models (e.g. GPT-4o, GPT-4-turbo) as this will cause an API error.
PRESENCE_PENALTY	NUMERIC	IN	Number between -2.0 and 2.0 Default: 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.
RESPONSE_FORMAT	TEXT	IN	Format of the response: json_object, text, or json_schema When the value is json_object, the system prompt should contain the JSON keyword. When the value is json_schema, the expected schema must be provided in the RESPONSE_FORMAT_JSON_SCHEMA parameter.
RESPONSE_FORMAT_JSON_SCHEMA	TEXT	IN	The JSON schema that will be used by the model to respond. See the RESPONSE_FORMAT_JSON_SCHEMA section below for an example.
APP_RESPONSE_IGNORE_ERROR	TEXT	IN	Specifies (Y or N) if error should be ignored Default: N ✏️ Note: In case of error, if the parameter has Y as its value, the error will be ignored and defined OUT parameters (APP_RESPONSE_STATUS or APP_RESPONSE_CONTENT) will be mapped. Otherwise, an exception will be thrown.
TOOLS	TEXT	IN	List of tools available to the model, formatted in JSON and compliant with OpenAI's format: https://platform.openai.com/docs/api-reference/chat/create#chat-create-tools; see the TOOLS section below for an example
TOOL_CHOICE_REQUIRED	TEXT	IN	Specifies whether the model must necessarily choose a tool Values: Y or N (default)
PARALLEL_TOOL	TEXT	IN	Specifies whether the model can choose multiple tools Values: Y (default) or N
MESSAGE_HISTORY	TEXT	INOUT	The message history in JSON format The reference structure follows OpenAI's documentation for the messages object: https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages.
SELECTED_TOOLS	TEXT	OUT	The list of selected tool names, separated by commas
SELECTED_TOOLS_PARAM	TEXT	OUT	A JSON array representing the list of selected tools along with their parameters; see the SELECTED_TOOLS_PARAMS section below for an example output
SELECTED_TOOLS_COUNT	NUMERIC	OUT	The number of selected tools
RESULT	TEXT	OUT	Chat result call
RESULT_CONTENT	TEXT	OUT	Content of the assistant message
RESULT_TOTAL_TOKENS	NUMERIC	OUT	Total of tokens used for generation
RESULT_COMPLETION_TOKENS	NUMERIC	OUT	Total of tokens used for generation
RESULT_PROMPT_TOKENS	NUMERIC	OUT	Total of token used for the prompt
RESULT_REASONING_TOKENS	NUMERIC	OUT	Number of tokens used for internal reasoning by reasoning models (o1, o3, GPT-5 series) These tokens are not visible in the response but count toward usage and billing. Returns 0 for non-reasoning models.
RESULT_CACHED_TOKENS	NUMERIC	OUT	Number of prompt tokens that were served from cache Cached tokens are billed at a reduced rate. This is useful for understanding cost optimization from prompt caching.
APP_RESPONSE_STATUS	TEXT	OUT	Response status code
APP_RESPONSE_CONTENT	TEXT	OUT	Response payload or error message
USER_AUDIO	FILE	IN	Local audio file sent as audio input WorkflowGen converts the file to base64 before sending the request. Supported by OpenAI (audio-capable models only), Mistral, and Gemini.
USER_DOCUMENT_URL	TEXT	IN	URL of a document to analyze Best used with the optional USER_DOCUMENT_NAME parameter. Supported by Mistral and Anthropic (PDF URLs only for Anthropic).
USER_FILE_ID	TEXT	IN	File identifier returned by the provider's Files API Use this when the file has already been uploaded outside OPENAICHAT. Supported by OpenAI, Mistral, and Anthropic.
USER_FILE	FILE	IN	Local file sent inline in the chat request as base64 file content No pre-upload step is required. Supported by OpenAI and Anthropic. Anthropic currently accepts PDF and plain text files only in this flow.

Multimodal input

OPENAICHAT supports multimodal user input through USER_AUDIO, USER_DOCUMENT_URL, USER_FILE_ID, and USER_FILE.

Use these parameters together with USER_MESSAGE to tell the model what to do with the attached audio, document, or file.

Provider support

Provider	USER_AUDIO	USER_DOCUMENT_URL	USER_FILE_ID	USER_FILE
OpenAI	Yes, with audio-capable models	No	Yes	Yes
Mistral	Yes	Yes	Yes	No
Gemini (OpenAI-compatible endpoint)	Yes	No	No	No
Anthropic	No	Yes, for PDF document URLs	Yes	Yes, for PDF and plain text files

Indexed variants

These parameters also support indexed variants when a single user message must contain multiple content blocks.

📌 Examples

• USER_AUDIO1, USER_AUDIO2

• USER_DOCUMENT_URL1, USER_DOCUMENT_URL2

• USER_FILE_ID1, USER_FILE_ID2

• USER_FILE1, USER_FILE2

Use USER_DOCUMENT_NAME1, USER_DOCUMENT_NAME2, and so on with the matching USER_DOCUMENT_URL index.

• When indexed multimodal parameters are used, the non-indexed versions of USER_AUDIO, USER_DOCUMENT_URL, USER_FILE_ID, and USER_FILE are ignored.

• If USER_MESSAGE1 is not provided, the non-indexed USER_MESSAGE can still be included as the first text block.

• If the selected provider does not support one of these content types, OPENAICHAT skips that content and writes an informational log entry (if application logging is enabled).

Provider-specific considerations

Parameter availability by provider

Parameter	OpenAI	Mistral	Gemini	Anthropic
MODEL	Yes	Yes	Yes	Yes
SYSTEM_MESSAGE	Yes	Yes	Yes	Yes
USER_MESSAGE	Yes	Yes	Yes	Yes
TEMPERATURE	0-2	0-2	0-1	0-1
TOP_P	Yes	Yes	Yes	No
MAX_TOKENS	Yes	Yes	Yes	Required
TOOLS	Yes	Yes	Yes	Yes
RESPONSE_FORMAT	Yes	Yes	Yes	Yes
DEVELOPER_MESSAGE	o1+ only	No	No	No
MAX_COMPLETION_TOKENS	o1+ only	No	No	No
REASONING_EFFORT	o1/o3	No	Mapped	Mapped
FREQUENCY_PENALTY	Yes	Yes	No	No
PRESENCE_PENALTY	Yes	Yes	No	No
PARALLEL_TOOL	Yes	Yes	Yes	Yes

• Parameters not supported by a provider are silently ignored.

• TEMPERATURE values above 1.0 are capped at 1.0 for Gemini and Anthropic (Mistral supports 0-2).

• REASONING_EFFORT is mapped to provider-specific thinking/reasoning configurations.

• MAX_TOKENS is required for Anthropic (not optional).

• When REASONING_EFFORT is used with Anthropic, TEMPERATURE and TOP_P are ignored (API requirement).

TOP_P is not sent for Anthropic because Claude 4.5 models don't allow both temperature and top_p together.

OpenAI reasoning models

OpenAI offers reasoning models (o1, o3, GPT-5 series) that use internal reasoning before generating a response. These models have specific parameter requirements:

Parameters

Parameter	Description
MAX_COMPLETION_TOKENS (required for reasoning models)	Specifies the maximum tokens for the completion, including both reasoning tokens and visible output tokens
REASONING_EFFORT (optional)	Controls the depth of reasoning: low, medium, or high Higher values use more reasoning tokens but may produce better results.

• Use MAX_COMPLETION_TOKENS instead of MAX_TOKENS for reasoning models. The MAX_TOKENS parameter is deprecated for these models.

• Do not use REASONING_EFFORT with non-reasoning models (e.g., GPT-4o, GPT-4-turbo). These models don't support this parameter and the API will return an error.

• When using REASONING_EFFORT, always set MAX_COMPLETION_TOKENS. If REASONING_EFFORT is specified without MAX_COMPLETION_TOKENS, no token limit is sent to the API (the API will use its default limits). This is intentional because reasoning models reject the MAX_TOKENS parameter.

• Reasoning tokens are not visible in the response content but are included in the token usage count and billing.

Output parameters

Parameter	Description
RESULT_REASONING_TOKENS	Number of tokens used for internal reasoning Only populated for reasoning models; returns 0 for other models.
RESULT_CACHED_TOKENS	Number of prompt tokens served from cache (applies to all models with prompt caching)

Example of reasoning model use

MODEL = gpt-5-mini
USER_MESSAGE = "Solve this math problem: If a train travels 120 km in 2 hours, what is its average speed?"
MAX_COMPLETION_TOKENS = 500
REASONING_EFFORT = medium

Output

RESULT_CONTENT = "Average speed = distance ÷ time = 120 km ÷ 2 h = 60 km/h."
RESULT_TOTAL_TOKENS = 124
RESULT_COMPLETION_TOKENS = 95
RESULT_PROMPT_TOKENS = 29
RESULT_REASONING_TOKENS = 64
RESULT_CACHED_TOKENS = 0

JSON schema use case

Using a JSON schema as a response format enforces the application to respond in a structured manner that aligns with the schema.

You can directly extract the returned values to populate specific data; simply specify the name of the property to extract as the parameter name and set the target data in OUT.

Examples

TOOLS

[
    {
        "name": "GET_STOCK_INFORMATION",
        "description": "Get stock information about a product. If the product is not found, return an error. If the stock is less than 10, return a warning and a purchase order should be done.",      
        "parameters": {
            "type": "object",
            "properties": {
                "product_name": {
                    "type": "string",
                    "description": "The product name"
                },
                "serial_number": {
                    "type": "string",
                    "description": "The product serial number"
                }
            },
            "additionalProperties": false,
            "required": ["serial_number"]
        }
    },
    {
        "name": "PURCHASE_ORDER",
        "description": "Make a purchase order for a product.",    
        "parameters": {
            "type": "object",
            "properties": {
                "product_name": {
                    "type": "string",
                    "description": "The product name"
                },
                "serial_number": {
                    "type": "string",
                    "description": "The product serial number"
                },
                "quantity": {
                    "type": "number",
                    "description": "The quantity of the product to purchase"
                }
            },
            "additionalProperties": false,
            "required": ["serial_number", "quantity"]
        }
    }
]

SELECTED_TOOLS_PARAMS

[
    {
        "name": "GET_STOCK_INFORMATION",
        "id": "call_Vuc2Ga8jP7vUksxG9C0fwpY8",
        "parameters": {
            "product_name": "vis",
            "serial_number": "V45645"
        }
        
    },
    {
        "name": "GET_STOCK_INFORMATION",
        "id": "call_nq3SCVUk0FjAHCeqOZGNXpC8",
        "parameters": {
            "product_name": "boulons",
            "serial_number": "b456"
        }
    }
]

RESPONSE_FORMAT_JSON_SCHEMA

{
  "name": "schema",
  "schema": {
    "$schema": "http://json-schema.org/draft-04/schema#",
    "type": "object",
    "properties": {
      "advice": {
        "type": "string"
      },
      "next_action": {
        "type": "string",
        "enum": ["expert","sales","support","logistics",null]
      },
      "confidence_level": {
        "type": "number"
      }
    },
    "required": ["advice", "next_action","confidence_level"]
  }
}

Resolution priority (strict, no cross-provider fallback)

The application resolves provider, URL, and API key in the following order:

Provider resolution

1. PROVIDER parameter (if set and valid)

2. Auto-detect from URL parameter (if set)

3. Default: OpenAI

Provider detection only uses the URL parameter, not configuration values.

URL resolution (based on resolved provider)

1. URL parameter (if set)

2. Provider-specific configuration URL:

   • OpenAI → OpenAIChatApiUrl

   • Mistral → MistralChatApiUrl

   • Gemini → GeminiChatApiUrl

   • Anthropic → AnthropicChatApiUrl

3. Hardcoded default URL for provider

No cross-provider fallback. Each provider uses only its own configuration URL.

API key resolution (based on resolved provider)

1. API_KEY parameter (if set)

2. Provider-specific configuration key:

   • OpenAI → OpenAIApiKey

   • Mistral → MistralApiKey

   • Gemini → GeminiApiKey

   • Anthropic → AnthropicApiKey

No cross-provider fallback. Each provider uses only its own configuration key.

Common scenarios

Scenario	Provider	URL	API key
All defaults (nothing set)	OpenAI	OpenAIChatApiUrl or default	OpenAIApiKey
PROVIDER=anthropic	Anthropic	AnthropicChatApiUrl or default	AnthropicApiKey
PROVIDER=mistral	Mistral	MistralChatApiUrl or default	MistralApiKey
PROVIDER=gemini	Gemini	GeminiChatApiUrl or default	GeminiApiKey
URL=https://api.mistral.ai/...	Mistral (auto)	URL parameter	MistralApiKey
URL=https://api.anthropic.com/...	Anthropic (auto)	URL parameter	AnthropicApiKey

How to use each provider

Provider	Required configuration
OpenAI	Nothing (default) or set OpenAIApiKey in configuration
Mistral	Set PROVIDER=mistral OR URL param, AND MistralApiKey in configuration or API_KEY parameter
Gemini	Set PROVIDER=gemini OR URL param, AND GeminiApiKey in configuration or API_KEY parameter
Anthropic	Set PROVIDER=anthropic OR URL parameter, AND AnthropicApiKey in configuration or API_KEY parameter

Common examples

These examples work across all four providers, using parameters fully compatible with all of them.

Basic chat

MODEL = gpt-4o / mistral-large-latest / gemini-2.0-flash / claude-sonnet-4-5-20250929
SYSTEM_MESSAGE = "You are a helpful assistant."
USER_MESSAGE = "Explain quantum computing in simple terms."
MAX_TOKENS = 500
TEMPERATURE = 0.7

Multi-turn conversation with MESSAGE_HISTORY

MODEL = [any provider model]
MESSAGE_HISTORY = [previous conversation JSON]
USER_MESSAGE = "Continue from where we left off."
MAX_TOKENS = 500

Tool/function calling

MODEL = [any provider model]
USER_MESSAGE = "What's the weather in Paris?"
TOOLS = [{"name": "get_weather", "description": "Get weather info", "parameters": {...}}]
MAX_TOKENS = 500

Provider-specific examples

OpenAI-specific examples

Reasoning models (o1/o3/GPT-5 series)

MODEL = o3-mini
USER_MESSAGE = "Solve this complex math problem..."
MAX_COMPLETION_TOKENS = 2000
REASONING_EFFORT = high

Output includes: RESULT_REASONING_TOKENS

Developer message (o1+ models)

MODEL = o1
DEVELOPER_MESSAGE = "You are a code reviewer. Be strict."
USER_MESSAGE = "Review this code..."
MAX_COMPLETION_TOKENS = 1000

Mistral AI-specific examples

Using Mistral endpoint

URL = https://api.mistral.ai/v1/chat/completions
MODEL = mistral-large-latest
USER_MESSAGE = "Translate to French: Hello world"
MAX_TOKENS = 200

With explicit provider

PROVIDER = mistral
MODEL = mistral-large-latest
USER_MESSAGE = "Translate to French: Hello world"
MAX_TOKENS = 200

FREQUENCY_PENALTY and PRESENCE_PENALTY are supported.

Google Gemini-specific examples

Gemini's OpenAI-compatible endpoint does NOT support FREQUENCY_PENALTY and PRESENCE_PENALTY. These parameters are ignored.

Using Gemini OpenAI-compatible endpoint

URL = https://generativelanguage.googleapis.com/v1beta/openai/chat/completions
MODEL = gemini-2.0-flash
USER_MESSAGE = "Analyze this image"
USER_IMAGE_URL = https://example.com/image.jpg
MAX_TOKENS = 500

With explicit provider

PROVIDER = gemini
MODEL = gemini-2.0-flash
USER_MESSAGE = "Explain this concept"
MAX_TOKENS = 500

FREQUENCY_PENALTY and PRESENCE_PENALTY are supported.

Anthropic Claude-specific examples

Basic Claude usage

PROVIDER = anthropic
MODEL = claude-sonnet-4-5-20250929
SYSTEM_MESSAGE = "You are a helpful assistant."
USER_MESSAGE = "Explain machine learning."
MAX_TOKENS = 1000

Extended thinking (Claude)

PROVIDER = anthropic
MODEL = claude-sonnet-4-5-20250929
USER_MESSAGE = "Solve this complex reasoning problem..."
MAX_TOKENS = 2000
REASONING_EFFORT = high

Maps to Claude's thinking.budget_tokens parameter:

• low → 1,024 tokens

• medium → 8,192 tokens

• high → 24,576 tokens

Claude with Vision

PROVIDER = anthropic
MODEL = claude-sonnet-4-5-20250929
USER_MESSAGE = "Describe this image"
USER_IMAGE = [attached image file]
MAX_TOKENS = 500