dspy.Predict

dspy.Predict(signature, callbacks=None, **config)

Bases: Module, Parameter

Source code in dspy/predict/predict.py

def __init__(self, signature, callbacks=None, **config):
    self.stage = random.randbytes(8).hex()
    self.signature = ensure_signature(signature)
    self.config = config
    self.callbacks = callbacks or []
    self.reset()

Functions

__call__(**kwargs)

Source code in dspy/predict/predict.py

@with_callbacks
def __call__(self, **kwargs):
    return self.forward(**kwargs)

dump_state()

Source code in dspy/predict/predict.py

def dump_state(self):
    state_keys = ["lm", "traces", "train"]
    state = {k: getattr(self, k) for k in state_keys}

    state["demos"] = []
    for demo in self.demos:
        demo = demo.copy()

        for field in demo:
            # FIXME: Saving BaseModels as strings in examples doesn't matter because you never re-access as an object
            # It does matter for images
            if isinstance(demo[field], Image):
                demo[field] = demo[field].model_dump()
            elif isinstance(demo[field], BaseModel):
                demo[field] = demo[field].model_dump_json()

        state["demos"].append(demo)

    state["signature"] = self.signature.dump_state()
    return state

forward(**kwargs)

Source code in dspy/predict/predict.py

def forward(self, **kwargs):
    import dspy

    # Extract the three privileged keyword arguments.
    assert "new_signature" not in kwargs, "new_signature is no longer a valid keyword argument."
    signature = ensure_signature(kwargs.pop("signature", self.signature))
    demos = kwargs.pop("demos", self.demos)
    config = dict(**self.config, **kwargs.pop("config", {}))

    # Get the right LM to use.
    lm = kwargs.pop("lm", self.lm) or dspy.settings.lm
    assert isinstance(lm, dspy.LM), "No LM is loaded."

    # If temperature is 0.0 but its n > 1, set temperature to 0.7.
    temperature = config.get("temperature")
    temperature = lm.kwargs["temperature"] if temperature is None else temperature
    num_generations = config.get("n") or lm.kwargs.get("n") or lm.kwargs.get("num_generations") or 1

    if (temperature is None or temperature <= 0.15) and num_generations > 1:
        config["temperature"] = 0.7

    if not all(k in kwargs for k in signature.input_fields):
        present = [k for k in signature.input_fields if k in kwargs]
        missing = [k for k in signature.input_fields if k not in kwargs]
        print(f"WARNING: Not all input fields were provided to module. Present: {present}. Missing: {missing}.")

    import dspy
    adapter = dspy.settings.adapter or dspy.ChatAdapter()
    completions = adapter(lm, lm_kwargs=config, signature=signature, demos=demos, inputs=kwargs)

    pred = Prediction.from_completions(completions, signature=signature)

    if kwargs.pop("_trace", True) and dspy.settings.trace is not None:
        trace = dspy.settings.trace
        trace.append((self, {**kwargs}, pred))

    return pred

get_config()

Source code in dspy/predict/predict.py

def get_config(self):
    return self.config

load_state(state)

Load the saved state of a Predict object.

Parameters:

Name	Type	Description	Default
state	dict	The saved state of a Predict object.	required

Returns:

Name	Type	Description
self		Returns self to allow method chaining

Source code in dspy/predict/predict.py

def load_state(self, state):
    """Load the saved state of a `Predict` object.

    Args:
        state (dict): The saved state of a `Predict` object.

    Returns:
        self: Returns self to allow method chaining
    """
    excluded_keys = ["signature", "extended_signature"]
    for name, value in state.items():
        # `excluded_keys` are fields that go through special handling.
        if name not in excluded_keys:
            setattr(self, name, value)

    # FIXME: Images are getting special treatment, but all basemodels initialized from json should be converted back to objects
    for demo in self.demos:
        for field in demo:
            if isinstance(demo[field], dict) and "url" in demo[field]:
                url = demo[field]["url"]
                if not isinstance(url, str):
                    raise ValueError(f"Image URL must be a string, got {type(url)}")
                demo[field] = Image(url=url)

    self.signature = self.signature.load_state(state["signature"])

    if "extended_signature" in state: # legacy, up to and including 2.5, for CoT.
        raise NotImplementedError("Loading extended_signature is no longer supported in DSPy 2.6+")

    return self

reset()

Source code in dspy/predict/predict.py

def reset(self):
    self.lm = None
    self.traces = []
    self.train = []
    self.demos = []

update_config(**kwargs)

Source code in dspy/predict/predict.py

def update_config(self, **kwargs):
    self.config = {**self.config, **kwargs}