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docs(agent): Add agents development guide (#1673)

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This commit is contained in:
Fangyin Cheng
2024-06-28 09:56:29 +08:00
committed by GitHub
parent 1796969bac
commit 45a960f331
43 changed files with 4010 additions and 146 deletions
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25
dbgpt/agent/core/base_agent.py
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@@ -21,6 +21,7 @@ from .agent import Agent, AgentContext, AgentMessage, AgentReviewInfo
from .memory.agent_memory import AgentMemory
from .memory.gpts.base import GptsMessage
from .memory.gpts.gpts_memory import GptsMemory
from .profile.base import ProfileConfig
from .role import Role
logger = logging.getLogger(__name__)
@@ -170,6 +171,10 @@ class ConversableAgent(Role, Agent):
self.resource = target
elif isinstance(target, AgentMemory):
self.memory = target
elif isinstance(target, ProfileConfig):
self.profile = target
elif isinstance(target, type) and issubclass(target, Action):
self.actions.append(target())
return self
async def send(
@@ -228,13 +233,26 @@ class ConversableAgent(Role, Agent):
await self._a_process_received_message(message, sender)
if request_reply is False or request_reply is None:
return
if self.is_human:
# Not generating a reply for human agents now
return
if not self.is_human:
if (
self.consecutive_auto_reply_counter
<= self.not_null_agent_context.max_chat_round
):
# If reply count is less than the maximum chat round, generate a reply
reply = await self.generate_reply(
received_message=message, sender=sender, reviewer=reviewer
)
if reply is not None:
await self.send(reply, sender)
else:
logger.info(
f"Current round {self.consecutive_auto_reply_counter} "
f"exceeds the maximum chat round "
f"{self.not_null_agent_context.max_chat_round}!"
)
def prepare_act_param(self) -> Dict[str, Any]:
"""Prepare the parameters for the act method."""
@@ -381,7 +399,7 @@ class ConversableAgent(Role, Agent):
reply_message, sender, reviewer, request_reply=False
)
fail_reason = reason
await self.save_to_memory(
await self.write_memories(
question=question,
ai_message=ai_message,
action_output=act_out,
@@ -389,7 +407,7 @@ class ConversableAgent(Role, Agent):
check_fail_reason=fail_reason,
)
else:
await self.save_to_memory(
await self.write_memories(
question=question,
ai_message=ai_message,
action_output=act_out,
@@ -437,6 +455,7 @@ class ConversableAgent(Role, Agent):
llm_model=llm_model,
max_new_tokens=self.not_null_agent_context.max_new_tokens,
temperature=self.not_null_agent_context.temperature,
verbose=self.not_null_agent_context.verbose,
)
return response, llm_model
except LLMChatError as e: