mirror of
https://github.com/tiennm99/serena.git
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Dominik Jain
6707cd9b7e
The repository is licensed per component. SolidLSP (src/solidlsp,
test/solidlsp, test/resources) remains MIT-licensed and independently
reusable; the Serena application (src/serena, src/interprompt, scripts,
test/serena, docs) is licensed under GPL-3.0-or-later starting with the v2
licensing transition. The change is not retroactive: all releases and
commits up to v1.7.0 / 74c38a65 (tag mit-final) remain available under MIT.
Since MIT is GPL-compatible, a distribution combining both (such as the
serena-agent package) is as a whole subject to GPL-3.0-or-later, while the
SolidLSP files themselves stay MIT and can be extracted and used separately
under MIT terms. The distribution metadata therefore declares
GPL-3.0-or-later, with both license texts shipped alongside it.
Serena originally began under the GPL (v2) and was switched to MIT in
May 2025 following community requests. We consider that change a mistake;
the substantial changes in v2 make this the appropriate time to revert it.
We want the best version of Serena to remain free.
Changes:
* LICENSE is now the licensing overview; canonical license texts live in
LICENSES/ (MIT.txt is the previous LICENSE verbatim, GPL-3.0-or-later.txt
is the unmodified FSF text)
* pyproject.toml declares the PEP 639 license expression
"GPL-3.0-or-later" and bundles LICENSE and LICENSES/* as license files;
the deprecated MIT classifier is dropped and flake.nix declares gpl3Plus;
README has per-component license badges and a License section
* SPDX-License-Identifier headers in all Python sources under src/ and
scripts/, added by the new idempotent scripts/add_spdx_headers.py, which
gen_prompt_factory.py also uses to keep the header on the generated
module; existing third-party notices are preserved
* CLA.md: Contributor License Agreement (contributor retains copyright;
grants a perpetual, irrevocable license including relicensing under any
terms, incl. proprietary/commercial; patent grant; authority
representations), to be enforced repository-wide via cla-assistant.io
* CONTRIBUTING.md, PR template and a new docs page explain the licensing
boundary and the CLA workflow
64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
"""Generates a GraphML file of the memory reference structure for a given project."""
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# SPDX-License-Identifier: GPL-3.0-or-later
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import argparse
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import xml.etree.ElementTree as ET
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from serena.config.serena_config import SerenaConfig
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from serena.memories.memory_reference_analysis import iter_referenced_names_in_content
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def main() -> None:
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parser = argparse.ArgumentParser(description="Generate a GraphML graph of memory references for a Serena project.")
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parser.add_argument("project", help="Name (or root path) of the registered project.")
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parser.add_argument("-o", "--output", default="memory_graph.graphml", help="Output file path (default: memory_graph.graphml).")
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args = parser.parse_args()
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# load project and its memory manager
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serena_config = SerenaConfig.from_config_file()
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project = serena_config.get_project(args.project)
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if project is None:
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raise SystemExit(f"Project '{args.project}' not found in Serena configuration.")
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mm = project.memory_manager
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# gather all project memory names
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memories_list = mm.list_project_memories()
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all_names = memories_list.get_full_list()
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# collect references by reading each memory's content
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edges: list[tuple[str, str]] = []
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node_names: set[str] = set(all_names)
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for name in all_names:
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content = mm.load_memory(name)
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for referenced in iter_referenced_names_in_content(content):
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edges.append((name, referenced))
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node_names.add(referenced)
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# build GraphML
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ns = "http://graphml.graphdrawing.org/xmlns"
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y_ns = "http://www.yworks.com/xml/graphml"
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graphml = ET.Element("graphml", xmlns=ns)
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graphml.set("xmlns:y", y_ns)
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ET.SubElement(graphml, "key", id="d0", **{"for": "node", "yfiles.type": "nodegraphics"})
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graph = ET.SubElement(graphml, "graph", id="memory_references", edgedefault="directed")
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for node_name in sorted(node_names):
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node = ET.SubElement(graph, "node", id=node_name)
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data = ET.SubElement(node, "data", key="d0")
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shape_node = ET.SubElement(data, "y:ShapeNode")
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label = ET.SubElement(shape_node, "y:NodeLabel")
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label.text = node_name
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for i, (source, target) in enumerate(edges):
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ET.SubElement(graph, "edge", id=f"e{i}", source=source, target=target)
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tree = ET.ElementTree(graphml)
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ET.indent(tree)
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tree.write(args.output, xml_declaration=True, encoding="utf-8")
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print(f"Wrote {len(node_names)} nodes and {len(edges)} edges to {args.output}")
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if __name__ == "__main__":
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main()
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