(no commit message)

README.md

@@ -1,2 +0,0 @@
-# nested_repo
-

auto_classes.json

@@ -0,0 +1,5 @@
+{
+  "AutoConfig": "program.config.AgentWRetreiverConfig",
+  "AutoProgram": "program.program.AgentWRetreiver",
+  "AutoRetriever": "program.retriever.ExampleRetriever"
+}

config.json

@@ -0,0 +1,15 @@
+{
+  "model": null,
+  "num_fetch": 1,
+  "lm": "openai/gpt-4o-mini",
+  "embedder": "openai/text-embedding-3-small",
+  "clients": {
+    "mit": [
+      "csail",
+      "mit-media-lab"
+    ],
+    "berkeley": [
+      "bear"
+    ]
+  }
+}

program.json

@@ -0,0 +1,9 @@
+{
+  "metadata": {
+    "dependency_versions": {
+      "python": "3.13",
+      "dspy": "3.1.2",
+      "cloudpickle": "3.1"
+    }
+  }
+}

program/compile.py

@@ -0,0 +1,13 @@
+import sys
+
+from .config import AgentWRetreiverConfig
+from .program import AgentWRetreiver
+from .retriever import ExampleRetriever
+
+if __name__ == "__main__":
+    username = sys.argv[1]  # ← first arg after script name (username)
+    config = AgentWRetreiverConfig(num_fetch=1)
+    retriever = ExampleRetriever(config, needed_param="hi")
+    agent = AgentWRetreiver(config, retriever=retriever)
+    repo_path = f"{username}/nested_repo"
+    agent.push_to_hub(repo_path, with_code=True)

program/config.py

@@ -0,0 +1,10 @@
+from pydantic import Field
+
+from modaic import PrecompiledConfig
+
+
+class AgentWRetreiverConfig(PrecompiledConfig):
+    num_fetch: int
+    lm: str = "openai/gpt-4o-mini"
+    embedder: str = "openai/text-embedding-3-small"
+    clients: dict = Field(default_factory=lambda: {"mit": ["csail", "mit-media-lab"], "berkeley": ["bear"]})

program/program.py

@@ -0,0 +1,18 @@
+from modaic import PrecompiledProgram
+
+from .config import AgentWRetreiverConfig
+from .retriever import ExampleRetriever
+from .tools.google.google_search import search_google  # noqa: F401
+from .utils.used import random_util  # noqa: F401
+
+
+class AgentWRetreiver(PrecompiledProgram):
+    config: AgentWRetreiverConfig
+
+    def __init__(self, config: AgentWRetreiverConfig, retriever: ExampleRetriever, **kwargs):
+        super().__init__(config, retriever=retriever, **kwargs)
+        self.lm = self.config.lm
+        self.clients = self.config.clients
+
+    def forward(self, query: str) -> str:
+        return self.retriever.retrieve(query)

program/retriever.py

@@ -0,0 +1,17 @@
+from modaic import Retriever
+
+from .config import AgentWRetreiverConfig
+from .tools.jira.jira_api_tools import call_jira_api  # noqa: F401
+from .utils.used import random_util  # noqa: F401
+
+
+class ExampleRetriever(Retriever):
+    config: AgentWRetreiverConfig
+
+    def __init__(self, config: AgentWRetreiverConfig, needed_param: str, **kwargs):
+        super().__init__(config, **kwargs)
+        self.embedder_name = config.embedder
+        self.needed_param = needed_param
+
+    def retrieve(self, query: str) -> str:
+        return f"Retrieved {self.config.num_fetch} results for {query}"

program/tools/google/google_search.py

@@ -0,0 +1,2 @@
+def search_google() -> str:
+    return "search_google"

program/tools/jira/jira_api_tools.py

@@ -0,0 +1,2 @@
+def call_jira_api() -> str:
+    return "call_jira_api"

program/utils/second_degree_import.py

@@ -0,0 +1,2 @@
+def import_me_too() -> str:
+    return "import_me_too"

program/utils/used.py

@@ -0,0 +1,5 @@
+from .second_degree_import import import_me_too  # noqa: F401
+
+
+def random_util() -> str:
+    return "random_util"

pyproject.toml

@@ -0,0 +1,10 @@
+[project]
+name = "nested_repo"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = ["dspy", "modaic"]
+
+[tool.uv.sources]
+modaic = { workspace = true }