Merge pull request #14 from ServiceNow/rename-nodes

Rename Collective to Team and move from Task to Node.

examples/chat.py

@@ -1,27 +1,27 @@
 import sys
 
-from tapeagents.collective import CollectiveAgent, CollectiveTape
+from tapeagents.team import TeamAgent, TeamTape
 from tapeagents.develop import Develop
 from tapeagents.llms import LLAMA, LLM
 from tapeagents.rendering import PrettyRenderer
 
 
 def try_chat(llm: LLM, develop: bool):
     # equilavent of https://microsoft.github.io/autogen/docs/tutorial/introduction
-    comedy_duo = CollectiveAgent.create_chat_initiator(
+    comedy_duo = TeamAgent.create_chat_initiator(
         name="Joe",
         llm=llm,
         system_prompt="Your name is Joe and you are a part of a duo of comedians.",
-        collective_manager=CollectiveAgent.create(
+        teammate=TeamAgent.create(
             name="Cathy", llm=llm, system_prompt="Your name is Cathy and you are a part of a duo of comedians."
         ),
         max_turns=3,
         init_message="Hey Cathy, tell me a joke",
     )
     if develop:
-        Develop(comedy_duo, CollectiveTape(context=None, steps=[]), PrettyRenderer()).launch()
+        Develop(comedy_duo, TeamTape(context=None, steps=[]), PrettyRenderer()).launch()
     else:
-        for event in comedy_duo.run(CollectiveTape(context=None, steps=[])):
+        for event in comedy_duo.run(TeamTape(context=None, steps=[])):
             print(event.model_dump_json(indent=2))
 
 

examples/code_chat.py

@@ -3,7 +3,7 @@
 import sys
 
 from tapeagents.autogen_prompts import AUTOGEN_ASSISTANT_SYSTEM_MESSAGE
-from tapeagents.collective import CollectiveAgent, CollectiveTape
+from tapeagents.team import TeamAgent, TeamTape
 from tapeagents.container_executor import ContainerExecutor
 from tapeagents.develop import Develop
 from tapeagents.environment import CodeExecutionEnvironment
@@ -16,11 +16,11 @@
 
 def try_chat(llm: LLM, develop: bool):
     # equilavent of https://microsoft.github.io/autogen/docs/tutorial/introduction
-    org = CollectiveAgent.create_chat_initiator(
+    org = TeamAgent.create_chat_initiator(
         name="UserProxy",
         llm=llm,
         system_prompt="",
-        collective_manager=CollectiveAgent.create(
+        teammate=TeamAgent.create(
             name="Assistant",
             system_prompt=AUTOGEN_ASSISTANT_SYSTEM_MESSAGE,
             llm=llm,
@@ -29,7 +29,7 @@ def try_chat(llm: LLM, develop: bool):
         init_message="compute 5 fibonacci numbers",
         execute_code=True,
     )
-    start_tape = CollectiveTape(context=None, steps=[])
+    start_tape = TeamTape(context=None, steps=[])
     now = f"{datetime.datetime.now():%Y%m%d%H%M%S}"
     env = CodeExecutionEnvironment(ContainerExecutor(work_dir=f"outputs/chat_code/{now}"))
     if develop:

examples/data_science.py

@@ -4,7 +4,7 @@
 
 from tapeagents.agent import Agent
 from tapeagents.autogen_prompts import AUTOGEN_ASSISTANT_SYSTEM_MESSAGE
-from tapeagents.collective import CollectiveAgent, CollectiveTape
+from tapeagents.team import TeamAgent, TeamTape
 from tapeagents.container_executor import ContainerExecutor
 from tapeagents.core import Action, FinalStep, Observation, Tape
 from tapeagents.environment import CodeExecutionEnvironment, Environment
@@ -19,33 +19,33 @@
 
 def make_world(llm: LLM | None = None, env: Environment | None = None) -> tuple[Agent, Tape, Environment]:
     llm = llm or LiteLLM(model_name="gpt-4o", parameters={"timeout": 15.0})
-    coder = CollectiveAgent.create(
+    coder = TeamAgent.create(
         name="SoftwareEngineer",
         system_prompt=(
             AUTOGEN_ASSISTANT_SYSTEM_MESSAGE + "Only say TERMINATE when your code was successfully executed."
         ),
         llm=llm,
     )
-    code_executor = CollectiveAgent.create(
+    code_executor = TeamAgent.create(
         name="CodeExecutor",
         llm=llm,
         execute_code=True,
     )
-    team = CollectiveAgent.create_collective_manager(
+    team = TeamAgent.create_team_manager(
         name="GroupChatManager",
         subagents=[coder, code_executor],
         max_calls=15,
         llm=llm,
     )
-    org = CollectiveAgent.create_chat_initiator(
+    org = TeamAgent.create_chat_initiator(
         name="UserProxy",
         init_message=(
             "Make a plot comparing the stocks of ServiceNow and Salesforce"
             " since beginning of 2024. Save it to a PNG file."
         ),
-        collective_manager=team,
+        teammate=team,
     )
-    start_tape = CollectiveTape(context=None, steps=[])
+    start_tape = TeamTape(context=None, steps=[])
     now = f"{datetime.datetime.now():%Y%m%d%H%M%S}"
     env = env or CodeExecutionEnvironment(ContainerExecutor(work_dir=f"outputs/data_science/{now}"))
     return org, start_tape, env

examples/multi_chat.py

@@ -3,7 +3,7 @@
 import sys
 
 from tapeagents.autogen_prompts import AUTOGEN_ASSISTANT_SYSTEM_MESSAGE
-from tapeagents.collective import CollectiveAgent, CollectiveTape
+from tapeagents.team import TeamAgent, TeamTape
 from tapeagents.container_executor import ContainerExecutor
 from tapeagents.core import FinalStep
 from tapeagents.develop import Develop
@@ -18,33 +18,33 @@
 
 def try_chat(develop: bool):
     llm = LiteLLM(model_name="gpt-4o", parameters={"timeout": 15.0}, use_cache=True)
-    product_manager = CollectiveAgent.create(
+    product_manager = TeamAgent.create(
         name="ProductManager",
         system_prompt="Creative in software product ideas.",
         llm=llm,
     )
-    coder = CollectiveAgent.create(
+    coder = TeamAgent.create(
         name="SoftwareEngineer",
         system_prompt=AUTOGEN_ASSISTANT_SYSTEM_MESSAGE,
         llm=llm,
     )
-    code_executor = CollectiveAgent.create(
+    code_executor = TeamAgent.create(
         name="CodeExecutor",
         llm=llm,
         execute_code=True,
     )
-    team = CollectiveAgent.create_collective_manager(
+    team = TeamAgent.create_team_manager(
         name="GroupChatManager",
         subagents=[product_manager, coder, code_executor],
         max_calls=15,
         llm=llm,
     )
-    org = CollectiveAgent.create_chat_initiator(
+    org = TeamAgent.create_chat_initiator(
         name="UserProxy",
         init_message="Find a latest paper about gpt-4 on arxiv and find its potential applications in software.",
-        collective_manager=team,
+        teammate=team,
     )
-    start_tape = CollectiveTape(context=None, steps=[])
+    start_tape = TeamTape(context=None, steps=[])
     now = f"{datetime.datetime.now():%Y%m%d%H%M%S}"
     env = CodeExecutionEnvironment(ContainerExecutor(work_dir=f"outputs/multi_chat_code/{now}"))
     if develop:

examples/tape_improver.py

@@ -5,7 +5,7 @@
 
 from tapeagents.agent import Agent
 from tapeagents.chain import Chain
-from tapeagents.collective import CollectiveTape
+from tapeagents.team import TeamTape
 from tapeagents.core import (
     Action,
     AgentStep,
@@ -113,7 +113,7 @@ class StepParsingError(Action):
     error: str
 
 
-CodeImproverTape = Tape[CollectiveTape, SelectAgent | SelectStep | RewriteStep | FinalStep | Call | Respond]
+CodeImproverTape = Tape[TeamTape, SelectAgent | SelectStep | RewriteStep | FinalStep | Call | Respond]
 
 
 def improver_tape_view(tape: Tape) -> str:
@@ -186,7 +186,7 @@ def generate_steps(self, tape: Any, llm_stream: LLMStream):
 def make_world(llm: LLM | None = None) -> tuple[Agent, Tape, Tape]:
     res_dir = f"{pathlib.Path(__file__).parent.resolve()}/res"
     with open(f"{res_dir}/bad_tape.json", "r") as f:
-        bad_tape = CollectiveTape.model_validate(json.load(f))
+        bad_tape = TeamTape.model_validate(json.load(f))
     improver_tape = CodeImproverTape(context=bad_tape, steps=[])
 
     llm = llm or LiteLLM(