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README.md

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-# simple_repo
-

auto_classes.json

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+{
+  "AutoConfig": "program.ExampleConfig",
+  "AutoProgram": "program.ExampleProgram"
+}

config.json

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+{
+  "model": null,
+  "output_type": "str",
+  "lm": "openai/gpt-4o",
+  "number": 1
+}

program.json

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+{
+  "predictor": {
+    "traces": [],
+    "train": [],
+    "demos": [],
+    "signature": {
+      "instructions": "Given the fields `question`, `context`, produce the fields `answer`.",
+      "fields": [
+        {
+          "prefix": "Question:",
+          "description": "${question}"
+        },
+        {
+          "prefix": "Context:",
+          "description": "${context}"
+        },
+        {
+          "prefix": "Answer:",
+          "description": "Answer to the question, based on the passage"
+        }
+      ]
+    },
+    "lm": {
+      "model": "openai/gpt-4o",
+      "model_type": "chat",
+      "cache": true,
+      "num_retries": 3,
+      "finetuning_model": null,
+      "launch_kwargs": {},
+      "train_kwargs": {},
+      "temperature": null,
+      "max_tokens": null
+    }
+  },
+  "metadata": {
+    "dependency_versions": {
+      "python": "3.11",
+      "dspy": "3.1.2",
+      "cloudpickle": "3.1"
+    }
+  }
+}

program.py

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+import sys
+from typing import Literal
+
+import dspy
+from modaic import PrecompiledConfig, PrecompiledProgram
+
+
+class Summarize(dspy.Signature):
+    question = dspy.InputField()
+    context = dspy.InputField()
+    answer = dspy.OutputField(desc="Answer to the question, based on the passage")
+
+
+class ExampleConfig(PrecompiledConfig):
+    output_type: Literal["bool", "str"]
+    lm: str = "openai/gpt-4o"
+    number: int = 1
+
+
+class ExampleProgram(PrecompiledProgram):
+    config: ExampleConfig
+
+    def __init__(self, config: ExampleConfig, runtime_param: str, **kwargs):
+        super().__init__(config, **kwargs)
+        self.predictor = dspy.Predict(Summarize)
+        self.predictor.lm = dspy.LM(self.config.lm)
+        self.runtime_param = runtime_param
+
+    def forward(self, question: str, context: str) -> str:
+        return self.predictor(question=question, context=context)
+
+
+if __name__ == "__main__":
+    username = sys.argv[1]  # ← first arg after script name (username)
+    program = ExampleProgram(ExampleConfig(output_type="str"), runtime_param="hi")
+    repo_path = f"{username}/simple_repo"
+    program.push_to_hub(repo_path, with_code=True)

pyproject.toml

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+[project]
+name = "simple_repo"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = ["dspy", "modaic", "praw"]
+
+[tool.uv.sources]
+modaic = { workspace = true }
+