Merge master into fix/all-except-first-drops-an-agent

Resolved conversation.py:1364 in favour of _index_after_first_message().
master had reached [1:] on both methods (kyegomez#2079 for the dict variant, kyegomez#2133 for
the string one), which is the opposite fixed guess to the [2:] this PR was
opened against. Both are wrong for one of the two history shapes.

Author: ayaangazali

example.py

@@ -1,6 +1,6 @@
 from dotenv import load_dotenv
 
-from swarms import Agent
+from swarms.structs.agent import Agent
 
 load_dotenv()
 
@@ -25,7 +25,7 @@
     max_loops=1,
     top_p=None,
     temperature=None,
-    reasoning_effort="medium",
+    reasoning_effort=None,
     persistent_memory=False,
 )
 

examples/multi_agent/concurrent_examples/concurrent_mix.py

@@ -18,15 +18,12 @@
     corporate law and ensure that all hiring practices are in compliance with 
     state and federal regulations.
     """,
-    model_name="claude-sonnet-4-20250514",
+    model_name="claude-sonnet-5",
     max_loops=1,
     autosave=False,
     dashboard=False,
     verbose=True,
-    output_type="str",
-    artifacts_on=True,
-    artifacts_output_path="delaware_ccorp_hiring_description.md",
-    artifacts_file_extension=".md",
+    temperature=None,
 )
 
 indian_foreign_agent = Agent(
@@ -45,15 +42,12 @@
     implications of hiring foreign nationals and the requirements for obtaining 
     necessary visas and work permits.
     """,
-    model_name="claude-sonnet-4-20250514",
+    model_name="claude-sonnet-5",
     max_loops=1,
     autosave=False,
     dashboard=False,
     verbose=True,
-    output_type="str",
-    artifacts_on=True,
-    artifacts_output_path="indian_foreign_hiring_description.md",
-    artifacts_file_extension=".md",
+    temperature=None,
 )
 
 # List of agents and corresponding tasks

examples/multi_agent/hierarchical_swarm/hierarchical_swarm_plan_panel_example.py

@@ -0,0 +1,39 @@
+from swarms import Agent, HierarchicalSwarm
+
+
+def main() -> None:
+    """Run a director with two specialized workers.
+
+    Returns:
+        None.
+    """
+    researcher = Agent(
+        agent_name="Researcher",
+        agent_description="Finds relevant facts and key considerations.",
+        system_prompt="Research the assigned topic and return concise facts.",
+        model_name="gpt-5.4",
+        max_loops=1,
+    )
+    writer = Agent(
+        agent_name="Writer",
+        agent_description="Turns research into a clear final explanation.",
+        system_prompt="Write a concise explanation for a general audience.",
+        model_name="gpt-5.4",
+        max_loops=1,
+    )
+
+    swarm = HierarchicalSwarm(
+        name="ResearchWritingSwarm",
+        description="Researches a topic and explains the findings.",
+        agents=[researcher, writer],
+        max_loops=1,
+    )
+
+    result = swarm.run(
+        "Explain three practical benefits of multi-agent systems."
+    )
+    print(result)
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "14.0.2"
+version = "15.0.0"
 description = "Swarms - TGSC"
 license = "Apache-2.0"
 authors = ["Kye Gomez <kye@swarms.world>"]
@@ -99,8 +99,6 @@ pytest = "*"
 
 [tool.pytest.ini_options]
 testpaths = ["tests"]
-# Without this, pytest-asyncio's strict default silently skips every bare
-# `async def test_`, reporting it as a failure that never ran.
 asyncio_mode = "auto"
 markers = [
     "remote: tests that hit a real remote MCP server over the network",
@@ -109,12 +107,6 @@ markers = [
 [tool.ruff]
 line-length = 70
 
-# Library code under swarms/ is held to the full rule set. Example scripts,
-# test helpers and one-off scripts are not: an availability probe imports a
-# package to see whether it is installed (F401), a demo loads dotenv before
-# importing (E402), and a teaching example catches everything so it can print
-# a friendly message (E722). Enforcing those there produces churn without
-# making the library safer.
 [tool.ruff.lint.per-file-ignores]
 "examples/**" = ["E402", "E721", "E722", "F401", "F402"]
 "tests/**" = ["E402", "E721", "E722", "F401", "F402"]

requirements.txt

@@ -11,7 +11,7 @@ networkx
 httpx
 requests
 litellm==1.76.1
-mcp>=1.28.1,<2.0.0
+mcp>=1.28.1,<3.0.0
 schedule
 opentelemetry-sdk
 opentelemetry-exporter-otlp-proto-http

swarms/__init__.py

@@ -7,10 +7,42 @@
 bootup()
 
 from swarms.agents import *  # noqa: E402, F403
-from swarms.artifacts import *  # noqa: E402, F403
 from swarms.prompts import *  # noqa: E402, F403
 from swarms.schemas import *  # noqa: E402, F403
 from swarms.structs import *  # noqa: E402, F403
 from swarms.telemetry import *  # noqa: E402, F403
 from swarms.tools import *  # noqa: E402, F403
 from swarms.utils import *  # noqa: E402, F403
+
+
+def __getattr__(name: str) -> str:
+    """Resolve ``swarms.__version__`` on first access.
+
+    The version comes from the installed distribution's metadata rather
+    than a literal here, so it cannot drift from ``pyproject.toml``.
+    Resolving it lazily keeps the dist-info scan off the import path for
+    the majority of programs, which never read it.
+    """
+    if name == "__version__":
+        from importlib.metadata import (
+            PackageNotFoundError,
+            version,
+        )
+
+        try:
+            resolved = version("swarms")
+        except PackageNotFoundError:
+            # A source checkout with no installed distribution.
+            resolved = "unknown"
+
+        globals()["__version__"] = resolved
+        return resolved
+
+    raise AttributeError(
+        f"module {__name__!r} has no attribute {name!r}"
+    )
+
+
+def __dir__() -> list:
+    """Advertise ``__version__`` before anything has accessed it."""
+    return sorted(set(globals()) | {"__version__"})

swarms/agents/autonomous_loop.py

@@ -145,6 +145,42 @@ def _map_batch_results(
             formatter=format_data_structure,
         )
 
+    def _maybe_compress_context(self) -> bool:
+        """Compress the conversation when it nears the context limit.
+
+        ``ContextCompressor`` measures and compacts
+        ``agent.short_memory``, but the request body actually sent to
+        the model is ``self._transcript`` — so after a compaction the
+        transcript is rebuilt around the summary. Compressing only the
+        mirror would leave the payload growing unbounded, which is the
+        failure the compressor exists to prevent.
+
+        Returns:
+            bool: True when a compression ran and the transcript was
+            re-seeded. The caller must then restore whatever immediate
+            instruction the model needs (e.g. the prompt for the
+            subtask in flight).
+        """
+        compressor = getattr(self.agent, "_context_compressor", None)
+        if compressor is None:
+            return False
+        summary = compressor.maybe_compress(self.agent)
+        if summary is None:
+            return False
+
+        # compact() already re-seeded short_memory with the summary,
+        # so the transcript copy must not be mirrored back a second
+        # time.
+        self._transcript = Transcript()
+        self._say_user(
+            "[Compressed Memory Summary]\n"
+            "Earlier turns were compressed to stay within the "
+            "context window. Progress so far:\n\n"
+            f"{summary}",
+            mirror=False,
+        )
+        return True
+
     def _run_autonomous_loop(
         self,
         task: Optional[Union[str, Any]] = None,
@@ -674,6 +710,16 @@ def _run_autonomous_loop(
                 ):
                     subtask_iterations += 1
 
+                    # Between iterations every recorded tool call has
+                    # been answered, so this is the one point the
+                    # transcript can be replaced without orphaning a
+                    # tool_call id.
+                    if self._maybe_compress_context():
+                        # The rebuilt transcript holds only the
+                        # summary; restore the instruction for the
+                        # subtask in flight.
+                        self._say_user(execution_prompt)
+
                     try:
                         response = self.agent.call_llm(
                             task=None,