refactor agent class to openssa.agent.dana.DANA

examples/FinanceBench/Makefile

@@ -4,33 +4,33 @@ agent-solve:
 agent-solve-w-knowledge:
 	@poetry run python htp_oodar_agent.py ${id} --knowledge
 
-agent-solve-w-prog-space:
-	@poetry run python htp_oodar_agent.py ${id} --prog-space
+agent-solve-w-prog-store:
+	@poetry run python htp_oodar_agent.py ${id} --prog-store
 
-agent-solve-w-knowledge-and-prog-space:
-	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-space
+agent-solve-w-knowledge-and-prog-store:
+	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-store
 
 agent-solve-w-llama3:
 	@poetry run python htp_oodar_agent.py ${id} --llama3
 
 agent-solve-w-knowledge-w-llama3:
 	@poetry run python htp_oodar_agent.py ${id} --knowledge --llama3
 
-agent-solve-w-prog-space-w-llama3:
-	@poetry run python htp_oodar_agent.py ${id} --prog-space --llama3
+agent-solve-w-prog-store-w-llama3:
+	@poetry run python htp_oodar_agent.py ${id} --prog-store --llama3
 
-agent-solve-w-knowledge-and-prog-space-w-llama3:
-	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-space --llama3
+agent-solve-w-knowledge-and-prog-store-w-llama3:
+	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-store --llama3
 
 agent-solve-all-combos:
 	@poetry run python htp_oodar_agent.py ${id}
 	@poetry run python htp_oodar_agent.py ${id} --knowledge
-	@poetry run python htp_oodar_agent.py ${id} --prog-space
-	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-space
+	@poetry run python htp_oodar_agent.py ${id} --prog-store
+	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-store
 	@poetry run python htp_oodar_agent.py ${id} --llama3
 	@poetry run python htp_oodar_agent.py ${id} --knowledge --llama3
-	@poetry run python htp_oodar_agent.py ${id} --prog-space --llama3
-	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-space --llama3
+	@poetry run python htp_oodar_agent.py ${id} --prog-store --llama3
+	@poetry run python htp_oodar_agent.py ${id} --knowledge --prog-store --llama3
 
 
 openai-assist:

examples/FinanceBench/data_and_knowledge.py

@@ -190,15 +190,15 @@ class Category(StrEnum):
     EXPERT_KNOWLEDGE: str = f.read()
 
 
-EXPERT_PROGRAM_SPACE_FILE_PATH: Path = Path(__file__).parent / 'expert-program-space.yml'
-with open(file=EXPERT_PROGRAM_SPACE_FILE_PATH,
+EXPERT_PROGRAMS_FILE_PATH: Path = Path(__file__).parent / 'expert-programs.yml'
+with open(file=EXPERT_PROGRAMS_FILE_PATH,
           buffering=-1,
           encoding='utf-8',
           errors='strict',
           newline=None,
           closefd=True,
           opener=None) as f:
-    EXPERT_PROGRAM_SPACE: dict[ExpertPlanId, HTPDict] = yaml.safe_load(stream=f)
+    EXPERT_PROGRAMS: dict[ExpertPlanId, HTPDict] = yaml.safe_load(stream=f)
 
 EXPERT_HTP_COMPANY_KEY: str = 'COMPANY'
 EXPERT_HTP_PERIOD_KEY: str = 'PERIOD'

examples/FinanceBench/htp_oodar_agent.py

@@ -1,13 +1,13 @@
 from argparse import ArgumentParser
 from functools import cache
 
-from openssa import Agent, ProgramSpace, HTP, HTPlanner, FileResource, LMConfig
+from openssa import DANA, ProgramStore, HTP, HTPlanner, FileResource, LMConfig
 from openssa.core.util.lm.huggingface import HuggingFaceLM
 from openssa.core.util.lm.openai import OpenAILM, default_llama_index_openai_lm
 
 # pylint: disable=wrong-import-order,wrong-import-position
 from data_and_knowledge import (DocName, FbId, Answer, Doc, FB_ID_COL_NAME, DOC_NAMES_BY_FB_ID, QS_BY_FB_ID,
-                                EXPERT_KNOWLEDGE, EXPERT_PROGRAM_SPACE, EXPERT_HTP_COMPANY_KEY, EXPERT_HTP_PERIOD_KEY)
+                                EXPERT_KNOWLEDGE, EXPERT_PROGRAMS, EXPERT_HTP_COMPANY_KEY, EXPERT_HTP_PERIOD_KEY)
 from util import QAFunc, enable_batch_qa_and_eval, log_qa_and_update_output_file
 
 
@@ -17,33 +17,33 @@ def get_main_lm(use_llama3: bool = False):
 
 
 @cache
-def get_or_create_expert_program_space(use_llama3: bool = False) -> ProgramSpace:
-    program_space = ProgramSpace(lm=get_main_lm(use_llama3=use_llama3))
+def get_or_create_expert_program_store(use_llama3: bool = False) -> ProgramStore:
+    program_store = ProgramStore(lm=get_main_lm(use_llama3=use_llama3))
 
-    for program_name, htp_dict in EXPERT_PROGRAM_SPACE.items():
+    for program_name, htp_dict in EXPERT_PROGRAMS.items():
         htp = HTP.from_dict(htp_dict)
-        program_space.add_or_update_program(name=program_name, description=htp.task.ask, program=htp)
+        program_store.add_or_update_program(name=program_name, description=htp.task.ask, program=htp)
 
-    return program_space
+    return program_store
 
 
 @cache
-def get_or_create_agent(doc_name: DocName, expert_knowledge: bool = False, expert_program_space: bool = False,
+def get_or_create_agent(doc_name: DocName, expert_knowledge: bool = False, expert_programs: bool = False,
                         max_depth=3, max_subtasks_per_decomp=6,
                         use_llama3: bool = False,
-                        llama_index_openai_lm_name: str = LMConfig.OPENAI_DEFAULT_MODEL) -> Agent:
+                        llama_index_openai_lm_name: str = LMConfig.OPENAI_DEFAULT_MODEL) -> DANA:
     # pylint: disable=too-many-arguments
-    return Agent(knowledge={EXPERT_KNOWLEDGE} if expert_knowledge else None,
+    return DANA(knowledge={EXPERT_KNOWLEDGE} if expert_knowledge else None,
 
-                 program_space=(get_or_create_expert_program_space(use_llama3=use_llama3)
-                                if expert_program_space
-                                else ProgramSpace()),
+                program_store=(get_or_create_expert_program_store(use_llama3=use_llama3)
+                               if expert_programs
+                               else ProgramStore()),
 
-                 programmer=HTPlanner(lm=get_main_lm(use_llama3=use_llama3),
-                                      max_depth=max_depth, max_subtasks_per_decomp=max_subtasks_per_decomp),
+                programmer=HTPlanner(lm=get_main_lm(use_llama3=use_llama3),
+                                     max_depth=max_depth, max_subtasks_per_decomp=max_subtasks_per_decomp),
 
-                 resources={FileResource(path=Doc(name=doc_name).dir_path,
-                                         lm=default_llama_index_openai_lm(llama_index_openai_lm_name))})
+                resources={FileResource(path=Doc(name=doc_name).dir_path,
+                                        lm=default_llama_index_openai_lm(llama_index_openai_lm_name))})
 
 
 @cache
@@ -69,16 +69,16 @@ def solve_with_knowledge(fb_id: FbId) -> Answer:
 
 @enable_batch_qa_and_eval(output_name='HTP-OODAR-wProgSpace')
 @log_qa_and_update_output_file(output_name='HTP-OODAR-wProgSpace')
-def solve_with_program_space(fb_id: FbId) -> Answer:
-    return get_or_create_agent(doc_name=DOC_NAMES_BY_FB_ID[fb_id], expert_program_space=True).solve(
+def solve_with_program_store(fb_id: FbId) -> Answer:
+    return get_or_create_agent(doc_name=DOC_NAMES_BY_FB_ID[fb_id], expert_programs=True).solve(
         problem=QS_BY_FB_ID[fb_id],
         adaptations_from_known_programs=get_or_create_adaptations(doc_name=DOC_NAMES_BY_FB_ID[fb_id]))
 
 
 @enable_batch_qa_and_eval(output_name='HTP-OODAR-wKnowledge-wProgSpace')
 @log_qa_and_update_output_file(output_name='HTP-OODAR-wKnowledge-wProgSpace')
-def solve_with_knowledge_and_program_space(fb_id: FbId) -> Answer:
-    return get_or_create_agent(DOC_NAMES_BY_FB_ID[fb_id], expert_knowledge=True, expert_program_space=True).solve(
+def solve_with_knowledge_and_program_store(fb_id: FbId) -> Answer:
+    return get_or_create_agent(DOC_NAMES_BY_FB_ID[fb_id], expert_knowledge=True, expert_programs=True).solve(
         problem=QS_BY_FB_ID[fb_id],
         adaptations_from_known_programs=get_or_create_adaptations(doc_name=DOC_NAMES_BY_FB_ID[fb_id]))
 
@@ -101,16 +101,16 @@ def solve_with_knowledge_with_llama3(fb_id: FbId) -> Answer:
 
 @enable_batch_qa_and_eval(output_name='HTP-OODAR-wProgSpace-wLlama3')
 @log_qa_and_update_output_file(output_name='HTP-OODAR-wProgSpace-wLlama3')
-def solve_with_program_space_with_llama3(fb_id: FbId) -> Answer:
-    return get_or_create_agent(doc_name=DOC_NAMES_BY_FB_ID[fb_id], expert_program_space=True, use_llama3=True).solve(
+def solve_with_program_store_with_llama3(fb_id: FbId) -> Answer:
+    return get_or_create_agent(doc_name=DOC_NAMES_BY_FB_ID[fb_id], expert_programs=True, use_llama3=True).solve(
         problem=QS_BY_FB_ID[fb_id],
         adaptations_from_known_programs=get_or_create_adaptations(doc_name=DOC_NAMES_BY_FB_ID[fb_id]))
 
 
 @enable_batch_qa_and_eval(output_name='HTP-OODAR-wKnowledge-wProgSpace-wLlama3')
 @log_qa_and_update_output_file(output_name='HTP-OODAR-wKnowledge-wProgSpace-wLlama3')
-def solve_with_knowledge_and_program_space_with_llama3(fb_id: FbId) -> Answer:
-    return get_or_create_agent(DOC_NAMES_BY_FB_ID[fb_id], expert_knowledge=True, expert_program_space=True, use_llama3=True).solve(  # noqa: E501
+def solve_with_knowledge_and_program_store_with_llama3(fb_id: FbId) -> Answer:
+    return get_or_create_agent(DOC_NAMES_BY_FB_ID[fb_id], expert_knowledge=True, expert_programs=True, use_llama3=True).solve(  # noqa: E501
         problem=QS_BY_FB_ID[fb_id],
         adaptations_from_known_programs=get_or_create_adaptations(doc_name=DOC_NAMES_BY_FB_ID[fb_id]))
 
@@ -119,22 +119,22 @@ def solve_with_knowledge_and_program_space_with_llama3(fb_id: FbId) -> Answer:
     arg_parser = ArgumentParser()
     arg_parser.add_argument('fb_id')
     arg_parser.add_argument('--knowledge', action='store_true')
-    arg_parser.add_argument('--prog-space', action='store_true')
+    arg_parser.add_argument('--prog-store', action='store_true')
     arg_parser.add_argument('--llama3', action='store_true')
     args = arg_parser.parse_args()
 
-    match (args.knowledge, args.prog_space, args.llama3):
+    match (args.knowledge, args.prog_store, args.llama3):
         case (False, False, False):
             solve_func: QAFunc = solve
 
         case (True, False, False):
             solve_func: QAFunc = solve_with_knowledge
 
         case (False, True, False):
-            solve_func: QAFunc = solve_with_program_space
+            solve_func: QAFunc = solve_with_program_store
 
         case (True, True, False):
-            solve_func: QAFunc = solve_with_knowledge_and_program_space
+            solve_func: QAFunc = solve_with_knowledge_and_program_store
 
         case (False, False, True):
             solve_func: QAFunc = solve_with_llama3
@@ -143,10 +143,10 @@ def solve_with_knowledge_and_program_space_with_llama3(fb_id: FbId) -> Answer:
             solve_func: QAFunc = solve_with_knowledge_with_llama3
 
         case (False, True, True):
-            solve_func: QAFunc = solve_with_program_space_with_llama3
+            solve_func: QAFunc = solve_with_program_store_with_llama3
 
         case (True, True, True):
-            solve_func: QAFunc = solve_with_knowledge_and_program_space_with_llama3
+            solve_func: QAFunc = solve_with_knowledge_and_program_store_with_llama3
 
     solve_func(fb_id
                if (fb_id := args.fb_id).startswith(FB_ID_COL_NAME)

examples/FinanceBench/make.bat

@@ -6,13 +6,13 @@
 SET TARGET=%1
 
 IF "%TARGET%"=="agent-solve" GOTO agent-solve
-IF "%TARGET%"=="agent-solve-w-prog-space" GOTO agent-solve-w-prog-space
+IF "%TARGET%"=="agent-solve-w-prog-store" GOTO agent-solve-w-prog-store
 IF "%TARGET%"=="agent-solve-w-knowledge" GOTO agent-solve-w-knowledge
-IF "%TARGET%"=="agent-solve-w-knowledge-and-prog-space" GOTO agent-solve-w-knowledge-and-prog-space
+IF "%TARGET%"=="agent-solve-w-knowledge-and-prog-store" GOTO agent-solve-w-knowledge-and-prog-store
 IF "%TARGET%"=="agent-solve-w-llama3" GOTO agent-solve-w-llama3
-IF "%TARGET%"=="agent-solve-w-prog-space-w-llama3" GOTO agent-solve-w-prog-space-w-llama3
+IF "%TARGET%"=="agent-solve-w-prog-store-w-llama3" GOTO agent-solve-w-prog-store-w-llama3
 IF "%TARGET%"=="agent-solve-w-knowledge-w-llama3" GOTO agent-solve-w-knowledge-w-llama3
-IF "%TARGET%"=="agent-solve-w-knowledge-and-prog-space-w-llama3" GOTO agent-solve-w-knowledge-and-prog-space-w-llama3
+IF "%TARGET%"=="agent-solve-w-knowledge-and-prog-store-w-llama3" GOTO agent-solve-w-knowledge-and-prog-store-w-llama3
 
 IF "%TARGET%"=="openai-assist" GOTO openai-assist
 
@@ -37,12 +37,12 @@ IF "%TARGET%"=="streamlit-run" GOTO streamlit-run
   poetry run python htp_oodar_agent.py %2 --knowledge
   GOTO end
 
-:agent-solve-w-prog-space
-  poetry run python htp_oodar_agent.py %2 --prog-space
+:agent-solve-w-prog-store
+  poetry run python htp_oodar_agent.py %2 --prog-store
   GOTO end
 
-:agent-solve-w-knowledge-and-prog-space
-  poetry run python htp_oodar_agent.py %2 --knowledge --prog-space
+:agent-solve-w-knowledge-and-prog-store
+  poetry run python htp_oodar_agent.py %2 --knowledge --prog-store
   GOTO end
 
 :agent-solve-w-llama3
@@ -53,12 +53,12 @@ IF "%TARGET%"=="streamlit-run" GOTO streamlit-run
   poetry run python htp_oodar_agent.py %2 --knowledge --llama3
   GOTO end
 
-:agent-solve-w-prog-space-w-llama3
-  poetry run python htp_oodar_agent.py %2 --prog-space --llama3
+:agent-solve-w-prog-store-w-llama3
+  poetry run python htp_oodar_agent.py %2 --prog-store --llama3
   GOTO end
 
-:agent-solve-w-knowledge-and-prog-space-w-llama3
-  poetry run python htp_oodar_agent.py %2 --knowledge --prog-space --llama3
+:agent-solve-w-knowledge-and-prog-store-w-llama3
+  poetry run python htp_oodar_agent.py %2 --knowledge --prog-store --llama3
   GOTO end
 
 

examples/FinanceBench/streamlit-main.py

@@ -4,12 +4,12 @@
 from loguru import logger
 import streamlit as st
 
-from data_and_knowledge import DocName, Doc, DOC_NAMES, ExpertPlanId as TaskId, EXPERT_PROGRAM_SPACE
+from data_and_knowledge import DocName, Doc, DOC_NAMES, ExpertPlanId as TaskId, EXPERT_PROGRAMS
 from htp_oodar_agent import get_or_create_agent, get_or_create_adaptations
 from rag_default import get_or_create_file_resource
 
 
-TASK_IDS: list[TaskId] = list(EXPERT_PROGRAM_SPACE)
+TASK_IDS: list[TaskId] = list(EXPERT_PROGRAMS)
 TASK_IDS.insert(0, '')
 
 DOC_NAMES: list[DocName] = sorted(set(DOC_NAMES)
@@ -38,7 +38,7 @@
 
 @cache
 def task_statement_template(task_id: TaskId, /) -> str:
-    return EXPERT_PROGRAM_SPACE[task_id]['task']
+    return EXPERT_PROGRAMS[task_id]['task']
 
 
 @cache
@@ -142,7 +142,7 @@ def task_statement(task_id: TaskId, doc_name: DocName) -> str:
             logger.level('DEBUG')
 
             agent = get_or_create_agent(doc_name=st.session_state.doc_name,
-                                        expert_knowledge=True, expert_program_space=True,
+                                        expert_knowledge=True, expert_programs=True,
                                         max_depth=3, max_subtasks_per_decomp=6,
                                         llama_index_openai_lm_name='gpt-4o-mini')
 

examples/japanese-easy-demo/main.py

@@ -1,14 +1,14 @@
 from pathlib import Path
 from dotenv import load_dotenv
-from openssa import Agent, FileResource
+from openssa import DANA, FileResource
 
 load_dotenv()
 
 LOCAL_CACHE_DOCS_DIR_PATH: Path = Path(__file__).parent / '.data'
 
 
-def get_or_create_agent() -> Agent:
-    return Agent(
+def get_or_create_agent() -> DANA:
+    return DANA(
         resources={FileResource(path=LOCAL_CACHE_DOCS_DIR_PATH)}
     )
 

examples/semiconductor/agent.py

@@ -3,27 +3,27 @@
 from argparse import ArgumentParser
 from functools import cache
 
-from openssa import Agent, ProgramSpace, HTP, HTPlanner, OpenAILM
+from openssa import DANA, ProgramStore, HTP, HTPlanner, OpenAILM
 
 # pylint: disable=wrong-import-order
-from data_and_knowledge import EXPERT_PROGRAM_SPACE
+from data_and_knowledge import EXPERT_PROGRAMS
 from semikong_lm import SemiKongLM
 
 
 @cache
-def get_or_create_agent(use_semikong_lm: bool = True, max_depth=2, max_subtasks_per_decomp=4) -> Agent:
+def get_or_create_agent(use_semikong_lm: bool = True, max_depth=2, max_subtasks_per_decomp=4) -> DANA:
     lm = (SemiKongLM if use_semikong_lm else OpenAILM).from_defaults()
 
-    program_space = ProgramSpace(lm=lm)
-    if EXPERT_PROGRAM_SPACE:
-        for program_name, htp_dict in EXPERT_PROGRAM_SPACE.items():
+    program_store = ProgramStore(lm=lm)
+    if EXPERT_PROGRAMS:
+        for program_name, htp_dict in EXPERT_PROGRAMS.items():
             htp = HTP.from_dict(htp_dict)
-            program_space.add_or_update_program(name=program_name, description=htp.task.ask, program=htp)
+            program_store.add_or_update_program(name=program_name, description=htp.task.ask, program=htp)
 
-    return Agent(knowledge={},
-                 program_space=program_space,
-                 programmer=HTPlanner(lm=lm, max_depth=max_depth, max_subtasks_per_decomp=max_subtasks_per_decomp),
-                 resources={})
+    return DANA(knowledge={},
+                program_store=program_store,
+                programmer=HTPlanner(lm=lm, max_depth=max_depth, max_subtasks_per_decomp=max_subtasks_per_decomp),
+                resources={})
 
 
 if __name__ == '__main__':

examples/semiconductor/data_and_knowledge.py

@@ -13,12 +13,12 @@
 load_dotenv()
 
 
-EXPERT_PROGRAM_SPACE_FILE_PATH: Path = Path(__file__).parent / 'expert-program-space.yml'
-with open(file=EXPERT_PROGRAM_SPACE_FILE_PATH,
+EXPERT_PROGRAMS_FILE_PATH: Path = Path(__file__).parent / 'expert-program-store.yml'
+with open(file=EXPERT_PROGRAMS_FILE_PATH,
           buffering=-1,
           encoding='utf-8',
           errors='strict',
           newline=None,
           closefd=True,
           opener=None) as f:
-    EXPERT_PROGRAM_SPACE: dict[str, HTPDict] = yaml.safe_load(stream=f)
+    EXPERT_PROGRAMS: dict[str, HTPDict] = yaml.safe_load(stream=f)

openssa/__init__.py

@@ -11,9 +11,9 @@
 from pathlib import Path
 import tomllib
 
-from .core.agent.agent import Agent
+from .core.agent.dana import DANA
 
-from .core.program_space import ProgramSpace
+from .core.program_store import ProgramStore
 from .core.programming.hierarchical.plan import HTP
 from .core.programming.hierarchical.planner import HTPlanner