DSPy is a framework for programming—rather than prompting—language models. DSPy enables you to build interpretable and modular LLM-powered agents using Python functions, structured modules, and declarative signatures, making it easy to compose, debug, and reliably deploy language model applications.
With DSPy in Aptlystar, you can:
- Run custom predictions: Connect your DSPy HTTP server and invoke prediction endpoints for a variety of natural language tasks.
- Chain of Thought and ReAct reasoning: Leverage advanced DSPy modules for step-by-step reasoning, multi-turn dialogs, and action-observation loops.
- Integrate with your workflows: Automate LLM predictions and reasoning as part of any Aptlystar automation or agent routine.
- Provide custom endpoints and context: Flexibly call your own DSPy-powered APIs with custom authentication, endpoints, input fields, and context.
These features let your Aptlystar agents access modular, interpretable LLM-based programs for tasks like question answering, document analysis, decision support, and more—where you remain in control of the model, data, and logic.
Usage Instructions
Integrate with your DSPy programs over HTTP for LLM-powered predictions. Supports Predict, Chain of Thought, and ReAct agents. DSPy is the framework for programming—not prompting—language models.
Tools
dspy_predict
Run a prediction using a DSPy program HTTP endpoint
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
baseUrl | string | Yes | Base URL of the DSPy server (e.g., https://your-dspy-server.com\) |
apiKey | string | No | API key for authentication (if required by your server) |
endpoint | string | No | API endpoint path (defaults to /predict) |
input | string | Yes | The input text to send to the DSPy program |
inputField | string | No | Name of the input field expected by the DSPy program (defaults to "text") |
context | string | No | Additional context to provide to the DSPy program |
additionalInputs | json | No | Additional key-value pairs to include in the request body |
Output
| Parameter | Type | Description |
|---|---|---|
answer | string | The main output/answer from the DSPy program |
reasoning | string | The reasoning or rationale behind the answer (if available) |
status | string | Response status from the DSPy server (success or error) |
rawOutput | json | The complete raw output from the DSPy program (result.toDict()) |
dspy_chain_of_thought
Run a Chain of Thought prediction using a DSPy ChainOfThought program HTTP endpoint
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
baseUrl | string | Yes | Base URL of the DSPy server (e.g., https://your-dspy-server.com\) |
apiKey | string | No | API key for authentication (if required by your server) |
endpoint | string | No | API endpoint path (defaults to /predict) |
question | string | Yes | The question to answer using chain of thought reasoning |
context | string | No | Additional context to provide for answering the question |
Output
| Parameter | Type | Description |
|---|---|---|
answer | string | The answer generated through chain of thought reasoning |
reasoning | string | The step-by-step reasoning that led to the answer |
status | string | Response status from the DSPy server (success or error) |
rawOutput | json | The complete raw output from the DSPy program (result.toDict()) |
dspy_react
Run a ReAct agent using a DSPy ReAct program HTTP endpoint for multi-step reasoning and action
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
baseUrl | string | Yes | Base URL of the DSPy server (e.g., https://your-dspy-server.com\) |
apiKey | string | No | API key for authentication (if required by your server) |
endpoint | string | No | API endpoint path (defaults to /predict) |
task | string | Yes | The task or question for the ReAct agent to work on |
context | string | No | Additional context to provide for the task |
maxIterations | number | No | Maximum number of reasoning iterations (defaults to server setting) |
Output
| Parameter | Type | Description |
|---|---|---|
answer | string | The final answer or result from the ReAct agent |
reasoning | string | The overall reasoning summary from the agent |
trajectory | array | The step-by-step trajectory of thoughts, actions, and observations |
↳ thought | string | The reasoning thought at this step |
↳ toolName | string | The name of the tool/action called |
↳ toolArgs | json | Arguments passed to the tool |
↳ observation | string | The observation/result from the tool execution |
status | string | Response status from the DSPy server (success or error) |
rawOutput | json | The complete raw output from the DSPy program (result.toDict()) |