feat(agent): Release agent SDK (#1396)

examples/agents/auto_plan_agent_dialogue_example.py

@@ -16,27 +16,23 @@
 
 
 import asyncio
-import os
 
-from dbgpt.agent.agents.agent import AgentContext
-from dbgpt.agent.agents.expand.code_assistant_agent import CodeAssistantAgent
-from dbgpt.agent.agents.llm.llm import LLMConfig
-from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
-from dbgpt.agent.memory.gpts_memory import GptsMemory
-from dbgpt.agent.resource.resource_api import AgentResource, ResourceType
-from dbgpt.agent.resource.resource_loader import ResourceLoader
-from dbgpt.agent.resource.resource_plugin_api import PluginFileLoadClient
-from dbgpt.core.interface.llm import ModelMetadata
-from dbgpt.serve.agent.team.plan.team_auto_plan import AutoPlanChatManager
+from dbgpt.agent import (
+    AgentContext,
+    GptsMemory,
+    LLMConfig,
+    ResourceLoader,
+    UserProxyAgent,
+)
+from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent
+from dbgpt.agent.plan import AutoPlanChatManager
 
 
 async def main():
-    from dbgpt.model import OpenAILLMClient
+    from dbgpt.model.proxy import OpenAILLMClient
 
-    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
-    context: AgentContext = AgentContext(
-        conv_id="test456", team_mode=Team, gpts_app_name="代码分析助手"
-    )
+    llm_client = OpenAILLMClient(model_alias="gpt-4")
+    context: AgentContext = AgentContext(conv_id="test456", gpts_app_name="代码分析助手")
 
     default_memory = GptsMemory()
 
@@ -62,7 +58,7 @@ async def main():
 
     user_proxy = await UserProxyAgent().bind(context).bind(default_memory).build()
 
-    await user_proxy.a_initiate_chat(
+    await user_proxy.initiate_chat(
         recipient=manager,
         reviewer=user_proxy,
         message="Obtain simple information about issues in the repository 'eosphoros-ai/DB-GPT' in the past three days and analyze the data. Create a Markdown table grouped by day and status.",
@@ -70,7 +66,7 @@ async def main():
         # message="find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.",
     )
 
-    print(await default_memory.one_chat_competions("test456"))
+    print(await default_memory.one_chat_completions("test456"))
 
 
 if __name__ == "__main__":

examples/agents/awel_layout_agents_chat_examples.py

@@ -11,31 +11,32 @@
 
         run example.
         ..code-block:: shell
-            python examples/agents/auto_plan_agent_dialogue_example.py
+            python examples/agents/awel_layout_agents_chat_examples.py
 """
 
 import asyncio
 import os
 
-from dbgpt.agent.agents.agent import AgentContext
-from dbgpt.agent.agents.expand.plugin_assistant_agent import PluginAssistantAgent
-from dbgpt.agent.agents.expand.summary_assistant_agent import SummaryAssistantAgent
-from dbgpt.agent.agents.llm.llm import LLMConfig
-from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
-from dbgpt.agent.memory.gpts_memory import GptsMemory
-from dbgpt.agent.resource.resource_api import AgentResource, ResourceType
-from dbgpt.agent.resource.resource_loader import ResourceLoader
-from dbgpt.agent.resource.resource_plugin_api import PluginFileLoadClient
-from dbgpt.core.interface.llm import ModelMetadata
-from dbgpt.serve.agent.team.layout.team_awel_layout import AwelLayoutChatManager
+from dbgpt.agent import (
+    AgentContext,
+    AgentResource,
+    GptsMemory,
+    LLMConfig,
+    ResourceLoader,
+    ResourceType,
+    UserProxyAgent,
+)
+from dbgpt.agent.expand.plugin_assistant_agent import PluginAssistantAgent
+from dbgpt.agent.expand.summary_assistant_agent import SummaryAssistantAgent
+from dbgpt.agent.plan import WrappedAWELLayoutManager
+from dbgpt.agent.resource import PluginFileLoadClient
+from dbgpt.configs.model_config import ROOT_PATH
 
-current_dir = os.getcwd()
-parent_dir = os.path.dirname(current_dir)
-test_plugin_dir = os.path.join(parent_dir, "test_files/plugins")
+test_plugin_dir = os.path.join(ROOT_PATH, "examples/test_files/plugins")
 
 
 async def main():
-    from dbgpt.model import OpenAILLMClient
+    from dbgpt.model.proxy import OpenAILLMClient
 
     llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
     context: AgentContext = AgentContext(conv_id="test456", gpts_app_name="信息析助手")
@@ -44,7 +45,7 @@ async def main():
 
     resource_loader = ResourceLoader()
     plugin_file_loader = PluginFileLoadClient()
-    resource_loader.register_resesource_api(plugin_file_loader)
+    resource_loader.register_resource_api(plugin_file_loader)
 
     plugin_resource = AgentResource(
         type=ResourceType.Plugin,
@@ -52,7 +53,7 @@ async def main():
         value=test_plugin_dir,
     )
 
-    tool_enginer = (
+    tool_engineer = (
         await PluginAssistantAgent()
         .bind(context)
         .bind(LLMConfig(llm_client=llm_client))
@@ -70,17 +71,17 @@ async def main():
     )
 
     manager = (
-        await AwelLayoutChatManager()
+        await WrappedAWELLayoutManager()
         .bind(context)
         .bind(default_memory)
         .bind(LLMConfig(llm_client=llm_client))
         .build()
     )
-    manager.hire([tool_enginer, summarizer])
+    manager.hire([tool_engineer, summarizer])
 
     user_proxy = await UserProxyAgent().bind(context).bind(default_memory).build()
 
-    await user_proxy.a_initiate_chat(
+    await user_proxy.initiate_chat(
         recipient=manager,
         reviewer=user_proxy,
         message="查询成都今天天气",
@@ -89,7 +90,7 @@ async def main():
         # message="find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.",
     )
 
-    print(await default_memory.one_chat_competions("test456"))
+    print(await default_memory.one_chat_completions("test456"))
 
 
 if __name__ == "__main__":

examples/agents/plugin_agent_dialogue_example.py

@@ -11,22 +11,23 @@
 
         run example.
         ..code-block:: shell
-            python examples/agents/single_agent_dialogue_example.py
+            python examples/agents/plugin_agent_dialogue_example.py
 """
 
 import asyncio
 import os
 
-from dbgpt.agent.actions.plugin_action import PluginAction
-from dbgpt.agent.agents.agent import AgentContext
-from dbgpt.agent.agents.expand.plugin_assistant_agent import PluginAssistantAgent
-from dbgpt.agent.agents.llm.llm import LLMConfig
-from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
-from dbgpt.agent.memory.gpts_memory import GptsMemory
-from dbgpt.agent.resource.resource_api import AgentResource, ResourceType
-from dbgpt.agent.resource.resource_loader import ResourceLoader
-from dbgpt.agent.resource.resource_plugin_api import PluginFileLoadClient
-from dbgpt.core.interface.llm import ModelMetadata
+from dbgpt.agent import (
+    AgentContext,
+    AgentResource,
+    GptsMemory,
+    LLMConfig,
+    ResourceLoader,
+    ResourceType,
+    UserProxyAgent,
+)
+from dbgpt.agent.expand.plugin_assistant_agent import PluginAssistantAgent
+from dbgpt.agent.resource import PluginFileLoadClient
 
 current_dir = os.getcwd()
 parent_dir = os.path.dirname(current_dir)
@@ -34,7 +35,7 @@ test_plugin_dir = os.path.join(parent_dir, "test_files/plugins")
 
 
 async def main():
-    from dbgpt.model import OpenAILLMClient
+    from dbgpt.model.proxy import OpenAILLMClient
 
     llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
     context: AgentContext = AgentContext(conv_id="test456")
@@ -49,11 +50,11 @@ async def main():
 
     resource_loader = ResourceLoader()
     plugin_file_loader = PluginFileLoadClient()
-    resource_loader.register_resesource_api(plugin_file_loader)
+    resource_loader.register_resource_api(plugin_file_loader)
 
     user_proxy = await UserProxyAgent().bind(default_memory).bind(context).build()
 
-    tool_enginer = (
+    tool_engineer = (
         await PluginAssistantAgent()
         .bind(context)
         .bind(LLMConfig(llm_client=llm_client))
@@ -63,14 +64,14 @@ async def main():
         .build()
     )
 
-    await user_proxy.a_initiate_chat(
-        recipient=tool_enginer,
+    await user_proxy.initiate_chat(
+        recipient=tool_engineer,
         reviewer=user_proxy,
         message="查询今天成都的天气",
     )
 
     ## dbgpt-vis message infos
-    print(await default_memory.one_chat_competions("test456"))
+    print(await default_memory.one_chat_completions("test456"))
 
 
 if __name__ == "__main__":

examples/agents/retrieve_summary_agent_dialogue_example.py

@@ -17,50 +17,50 @@
 import asyncio
 import os
 
-from dbgpt.agent.agents.agent import AgentContext
-from dbgpt.agent.agents.expand.retrieve_summary_assistant_agent import (
+from dbgpt.agent import AgentContext, GptsMemory, LLMConfig, UserProxyAgent
+from dbgpt.agent.expand.retrieve_summary_assistant_agent import (
     RetrieveSummaryAssistantAgent,
 )
-from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
-from dbgpt.agent.memory.gpts_memory import GptsMemory
-from dbgpt.core.interface.llm import ModelMetadata
+from dbgpt.configs.model_config import ROOT_PATH
 
 
-def summary_example_with_success():
+async def summary_example_with_success():
     from dbgpt.model.proxy import OpenAILLMClient
 
-    llm_client = OpenAILLMClient()
-    context: AgentContext = AgentContext(
-        conv_id="retrieve_summarize", llm_provider=llm_client
-    )
-    context.llm_models = [ModelMetadata(model="gpt-3.5-turbo-16k")]
+    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo-16k")
+    context: AgentContext = AgentContext(conv_id="retrieve_summarize")
 
     default_memory = GptsMemory()
-    summarizer = RetrieveSummaryAssistantAgent(
-        memory=default_memory, agent_context=context
+    summarizer = (
+        await RetrieveSummaryAssistantAgent()
+        .bind(context)
+        .bind(LLMConfig(llm_client=llm_client))
+        .bind(default_memory)
+        .build()
     )
 
     user_proxy = UserProxyAgent(memory=default_memory, agent_context=context)
 
-    asyncio.run(
-        user_proxy.a_initiate_chat(
-            recipient=summarizer,
-            reviewer=user_proxy,
-            message="""I want to summarize advantages of Nuclear Power. 
-            You can refer the following file pathes and URLs: ['/home/ubuntu/DB-GPT/examples/Nuclear_power.pdf', 'https://en.wikipedia.org/wiki/Modern_Family', '/home/ubuntu/DB-GPT/examples/Taylor_Swift.pdf', 'https://en.wikipedia.org/wiki/Chernobyl_disaster']
-            """,
-        )
+    paths_urls = [
+        os.path.join(ROOT_PATH, "examples/agents/example_files/Nuclear_power.pdf"),
+        os.path.join(ROOT_PATH, "examples/agents/example_files/Taylor_Swift.pdf"),
+        "https://en.wikipedia.org/wiki/Modern_Family",
+        "https://en.wikipedia.org/wiki/Chernobyl_disaster",
+    ]
+
+    await user_proxy.initiate_chat(
+        recipient=summarizer,
+        reviewer=user_proxy,
+        message=f"I want to summarize advantages of Nuclear Power. You can refer the "
+        f"following file paths and URLs: {paths_urls}",
     )
 
-    ## dbgpt-vis message infos
-    print(asyncio.run(default_memory.one_plan_chat_competions("retrieve_summarize")))
+    # dbgpt-vis message infos
+    print(await default_memory.one_chat_completions("retrieve_summarize"))
 
 
 if __name__ == "__main__":
-    print(
-        "\033[92m=======================Start The Summary Assistant with Successful Results==================\033[0m"
-    )
-    summary_example_with_success()
+    asyncio.run(summary_example_with_success())
     print(
         "\033[92m=======================The Summary Assistant with Successful Results Ended==================\n\n\033[91m"
     )

examples/agents/single_agent_dialogue_example.py

@@ -15,17 +15,13 @@
 """
 
 import asyncio
-import os
 
-from dbgpt.agent.agents.agent import AgentContext
-from dbgpt.agent.agents.expand.code_assistant_agent import CodeAssistantAgent
-from dbgpt.agent.agents.llm.llm import LLMConfig
-from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
-from dbgpt.agent.memory.gpts_memory import GptsMemory
+from dbgpt.agent import AgentContext, GptsMemory, LLMConfig, UserProxyAgent
+from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent
 
 
 async def main():
-    from dbgpt.model import OpenAILLMClient
+    from dbgpt.model.proxy import OpenAILLMClient
 
     llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
     context: AgentContext = AgentContext(conv_id="test123")
@@ -41,14 +37,14 @@ async def main():
 
     user_proxy = await UserProxyAgent().bind(context).bind(default_memory).build()
 
-    await user_proxy.a_initiate_chat(
+    await user_proxy.initiate_chat(
         recipient=coder,
         reviewer=user_proxy,
         message="式计算下321 * 123等于多少",  # 用python代码的方式计算下321 * 123等于多少
         # message="download data from https://raw.githubusercontent.com/uwdata/draco/master/data/cars.csv and plot a visualization that tells us about the relationship between weight and horsepower. Save the plot to a file. Print the fields in a dataset before visualizing it.",
     )
     ## dbgpt-vis message infos
-    print(await default_memory.one_chat_competions("test123"))
+    print(await default_memory.one_chat_completions("test123"))
 
 
 if __name__ == "__main__":

examples/agents/single_summary_agent_dialogue_example.py

@@ -15,17 +15,13 @@
 """
 
 import asyncio
-import os
 
-from dbgpt.agent.agents.agent import AgentContext
-from dbgpt.agent.agents.expand.summary_assistant_agent import SummaryAssistantAgent
-from dbgpt.agent.agents.llm.llm import LLMConfig
-from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
-from dbgpt.agent.memory.gpts_memory import GptsMemory
+from dbgpt.agent import AgentContext, GptsMemory, LLMConfig, UserProxyAgent
+from dbgpt.agent.expand.summary_assistant_agent import SummaryAssistantAgent
 
 
 async def summary_example_with_success():
-    from dbgpt.model import OpenAILLMClient
+    from dbgpt.model.proxy import OpenAILLMClient
 
     llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
     context: AgentContext = AgentContext(conv_id="summarize")
@@ -42,7 +38,7 @@ async def summary_example_with_success():
 
     user_proxy = await UserProxyAgent().bind(default_memory).bind(context).build()
 
-    await user_proxy.a_initiate_chat(
+    await user_proxy.initiate_chat(
         recipient=summarizer,
         reviewer=user_proxy,
         message="""I want to summarize advantages of Nuclear Power according to the following content.
@@ -76,11 +72,11 @@ async def summary_example_with_success():
     )
 
     ## dbgpt-vis message infos
-    print(await default_memory.one_chat_competions("summarize"))
+    print(await default_memory.one_chat_completions("summarize"))
 
 
 async def summary_example_with_faliure():
-    from dbgpt.model import OpenAILLMClient
+    from dbgpt.model.proxy import OpenAILLMClient
 
     llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
     context: AgentContext = AgentContext(conv_id="summarize")
@@ -99,7 +95,7 @@ async def summary_example_with_faliure():
 
     # Test the failure example
 
-    await user_proxy.a_initiate_chat(
+    await user_proxy.initiate_chat(
         recipient=summarizer,
         reviewer=user_proxy,
         message="""I want to summarize advantages of Nuclear Power according to the following content.
@@ -116,7 +112,7 @@ async def summary_example_with_faliure():
             """,
     )
 
-    print(await default_memory.one_chat_competions("summarize"))
+    print(await default_memory.one_chat_completions("summarize"))
 
 
 if __name__ == "__main__":

examples/agents/sql_agent_dialogue_example.py

@@ -17,14 +17,17 @@
 import asyncio
 import os
 
-from dbgpt.agent.agents.agent import AgentContext
-from dbgpt.agent.agents.expand.data_scientist_agent import DataScientistAgent
-from dbgpt.agent.agents.llm.llm import LLMConfig
-from dbgpt.agent.agents.user_proxy_agent import UserProxyAgent
-from dbgpt.agent.memory.gpts_memory import GptsMemory
-from dbgpt.agent.resource.resource_api import AgentResource, ResourceType
-from dbgpt.agent.resource.resource_db_api import SqliteLoadClient
-from dbgpt.agent.resource.resource_loader import ResourceLoader
+from dbgpt.agent import (
+    AgentContext,
+    AgentResource,
+    GptsMemory,
+    LLMConfig,
+    ResourceLoader,
+    ResourceType,
+    UserProxyAgent,
+)
+from dbgpt.agent.expand.data_scientist_agent import DataScientistAgent
+from dbgpt.agent.resource import SqliteLoadClient
 
 current_dir = os.getcwd()
 parent_dir = os.path.dirname(current_dir)
@@ -47,7 +50,7 @@ async def main():
 
     resource_loader = ResourceLoader()
     sqlite_file_loader = SqliteLoadClient()
-    resource_loader.register_resesource_api(sqlite_file_loader)
+    resource_loader.register_resource_api(sqlite_file_loader)
 
     user_proxy = await UserProxyAgent().bind(default_memory).bind(context).build()
 
@@ -61,14 +64,14 @@ async def main():
         .build()
     )
 
-    await user_proxy.a_initiate_chat(
+    await user_proxy.initiate_chat(
         recipient=sql_boy,
         reviewer=user_proxy,
         message="当前库有那些表",
     )
 
     ## dbgpt-vis message infos
-    print(await default_memory.one_chat_competions("test456"))
+    print(await default_memory.one_chat_completions("test456"))
 
 
 if __name__ == "__main__":