Dedalus Runner
Response object returned by the
DedalusRunner for non-streaming tool execution runs.Show Properties
Show Properties
Final text output from the conversation after all tool executions complete
Total number of steps (LLM calls) used during the run
List of tool names that were called during the run
Full conversation history including system prompts, user messages, assistant responses, and tool calls/results. Useful for debugging, logging, or continuing conversations.
Optional list of detected intents (when
return_intent=true)Alias for
final_output (legacy compatibility)Alias for
final_output (legacy compatibility)Show Methods
Show Methods
Returns a copy of the full conversation history (
messages) for use in follow-up runs. Enables multi-turn conversations by passing the result to subsequent runner.run() calls.Example
from dedalus_labs import Dedalus, DedalusRunner
client = Dedalus(api_key="YOUR_API_KEY")
runner = DedalusRunner(client)
def get_weather(location: str) -> str:
"""Get the current weather for a location."""
return f"The weather in {location} is sunny and 72°F"
result = runner.run(
input="What's the weather like in San Francisco?",
tools=[get_weather],
model="openai/gpt-5-nano",
max_steps=5
)
# Access result properties
print(result.final_output) # "The weather in San Francisco is sunny and 72°F"
print(result.steps_used) # e.g., 2
print(result.tools_called) # ["get_weather"]
print(result.tool_results) # [{"name": "get_weather", "result": "The weather...", "step": 1}]
Accessing Message History
import json
# Print the full conversation history
for msg in result.messages:
role = msg.get("role")
content = msg.get("content", "")
if role == "user":
print(f"User: {content}")
elif role == "assistant":
if msg.get("tool_calls"):
tools = [tc["function"]["name"] for tc in msg["tool_calls"]]
print(f"Assistant: [calling {', '.join(tools)}]")
else:
print(f"Assistant: {content}")
elif role == "tool":
print(f"Tool Result: {content[:100]}...")
# Store message history to JSON for logging/debugging
with open("conversation_log.json", "w") as f:
json.dump(result.messages, f, indent=2)
# Continue the conversation with message history
follow_up = runner.run(
messages=result.to_input_list(), # Pass previous conversation
input="What about New York?", # Add new user message
tools=[get_weather],
model="openai/gpt-5-nano"
)
Example Response
{
"final_output": "The weather in San Francisco is sunny and 72°F",
"tool_results": [
{
"name": "get_weather",
"result": "The weather in San Francisco is sunny and 72°F",
"step": 1
}
],
"steps_used": 2,
"tools_called": ["get_weather"],
"messages": [
{ "role": "user", "content": "What's the weather like in San Francisco?" },
{
"role": "assistant",
"tool_calls": [
{
"id": "call_abc123",
"type": "function",
"function": {
"name": "get_weather",
"arguments": "{\"location\": \"San Francisco\"}"
}
}
]
},
{
"role": "tool",
"tool_call_id": "call_abc123",
"content": "The weather in San Francisco is sunny and 72°F"
},
{
"role": "assistant",
"content": "The weather in San Francisco is sunny and 72°F"
}
],
"intents": null
}
Chat Completions
The complete response object for non-streaming chat completions.
Show Properties
Show Properties
Unique identifier for the chat completion
Object type, always
chat.completionUnix timestamp (seconds) when the completion was created
The model used for completion (e.g.,
openai/gpt-5-nano)List of completion choices
Show Choice Properties
Show Choice Properties
Index of this choice
Why the generation stopped:
stop, length, tool_calls, content_filterLog probability information for tokens
System fingerprint for reproducibility
Example
{
"id": "chatcmpl-abc123",
"object": "chat.completion",
"created": 1677652288,
"model": "openai/gpt-5-nano",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! I'm doing well, thank you for asking."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 13,
"completion_tokens": 12,
"total_tokens": 25
}
}
Streamed response chunks for streaming completions (
stream=true).Show Properties
Show Properties
Unique identifier for the chat completion
Object type, always
chat.completion.chunkUnix timestamp when the chunk was created
The model being used
List of chunk choices
Show Choice Properties
Show Choice Properties
Index of this choice
Reason for completion (only in final chunk):
stop, length, tool_calls, content_filter, or nullExample
{
"id": "chatcmpl-abc123",
"object": "chat.completion.chunk",
"created": 1677652288,
"model": "openai/gpt-5-nano",
"choices": [
{
"index": 0,
"delta": {
"content": "Hello"
},
"finish_reason": null
}
]
}
Embeddings
Response object for embedding creation requests.
Show Properties
Show Properties
Object type, always
listThe model used to generate embeddings
Example
{
"object": "list",
"data": [
{
"object": "embedding",
"embedding": [0.0023064255, -0.009327292, -0.0028842222],
"index": 0
}
],
"model": "openai/text-embedding-3-small",
"usage": {
"prompt_tokens": 8,
"total_tokens": 8
}
}
Models
Response object for listing available models. Includes rich metadata about capabilities and routing.
Show Properties
Show Properties
Object type, always
listList of model objects
Show Model Properties
Show Model Properties
Model identifier with provider prefix (e.g.,
openai/gpt-4o, anthropic/claude-opus-4-5)Provider name:
openai, anthropic, google, xai, deepseek, mistral, etc.ISO 8601 timestamp when the model was created
Human-readable display name (optional)
Model description (optional)
Model capabilities
Show Capabilities
Show Capabilities
Supports text generation via chat completions
Supports image input / multimodal
Can generate images
Supports audio input/output
Supports tool/function calling
Supports structured JSON output
Supports streaming responses
Supports extended reasoning (e.g., o1, o3, Claude thinking)
Maximum input context window in tokens
Maximum output tokens
Example
{
"object": "list",
"data": [
{
"id": "openai/gpt-4o",
"provider": "openai",
"created_at": "1970-01-01T00:00:00Z",
"display_name": null,
"description": null,
"capabilities": {
"text": true,
"vision": null,
"image_generation": null,
"audio": null,
"tools": null,
"structured_output": null,
"streaming": null,
"thinking": null,
"input_token_limit": null,
"output_token_limit": null
},
"provider_info": {
"status": "enabled",
"upstream_api": "openai/chat/completions"
}
},
{
"id": "openai/o1",
"provider": "openai",
"created_at": "1970-01-01T00:00:00Z",
"capabilities": {
"text": true,
"thinking": true
},
"provider_info": {
"status": "enabled",
"upstream_api": "openai/chat/completions"
}
},
{
"id": "anthropic/claude-opus-4-5",
"provider": "anthropic",
"created_at": "1970-01-01T00:00:00Z",
"capabilities": {
"text": true,
"vision": true,
"tools": true
},
"provider_info": {
"status": "enabled",
"upstream_api": "anthropic/messages"
}
}
]
}
Images
Response object for image generation requests.
Show Properties
Show Properties
Unix timestamp when the images were generated
Example
{
"created": 1677652288,
"data": [
{
"url": "https://images.example.com/abc123.png",
"revised_prompt": "A cute baby sea otter floating on its back in calm blue water"
}
]
}
Audio
Response object for audio transcription requests.
Show Properties
Show Properties
The transcribed text from the audio file
Example
{
"text": "Hello, this is a test of audio transcription."
}
Response object for audio translation requests (always translates to English).
Show Properties
Show Properties
The translated text from the audio file (in English)
Example
{
"text": "Hello, this is a test of audio translation."
}
Errors
All endpoints may return errors with this structure.
Show Properties
Show Properties
Error information object
Example
{
"error": {
"message": "Invalid API key provided",
"type": "authentication_error",
"code": "invalid_api_key"
}
}