Fixed agent&awel examples (#2256)

2025-07-31 15:47:05 +00:00 · 2025-01-09 20:01:36 +08:00 · 2025-01-09 20:01:36 +08:00 · 523ad323f1
commit 523ad323f1
parent d5213004d2
14 changed files with 156 additions and 334 deletions
--- a/dbgpt/rag/embedding/embeddings.py
+++ b/dbgpt/rag/embedding/embeddings.py
@ -803,9 +803,10 @@ class OllamaEmbeddings(BaseModel, Embeddings):
                "Please install ollama by command `pip install ollama"
            ) from e
        try:
-            return (
-                Client(self.api_url).embeddings(model=self.model_name, prompt=text)
-            )["embedding"]
+            embedding = Client(self.api_url).embeddings(
+                model=self.model_name, prompt=text
+            )
+            return list(embedding["embedding"])
        except ollama.ResponseError as e:
            raise ValueError(f"**Ollama Response Error, Please CheckErrorInfo.**: {e}")

@ -839,7 +840,7 @@ class OllamaEmbeddings(BaseModel, Embeddings):
            embedding = await AsyncClient(host=self.api_url).embeddings(
                model=self.model_name, prompt=text
            )
-            return embedding["embedding"]
+            return list(embedding["embedding"])
        except ollama.ResponseError as e:
            raise ValueError(f"**Ollama Response Error, Please CheckErrorInfo.**: {e}")

--- a/examples/main.py
+++ b/examples/main.py
@ -0,0 +1,32 @@
+# TODO add example run code here
+
+import asyncio
+
+# Agents examples
+from .agents.auto_plan_agent_dialogue_example import main as auto_plan_main
+from .agents.awel_layout_agents_chat_examples import main as awel_layout_main
+from .agents.custom_tool_agent_example import main as custom_tool_main
+from .agents.plugin_agent_dialogue_example import main as plugin_main
+from .agents.retrieve_summary_agent_dialogue_example import (
+    main as retrieve_summary_main,
+)
+from .agents.sandbox_code_agent_example import main as sandbox_code_main
+from .agents.single_agent_dialogue_example import main as single_agent_main
+from .agents.sql_agent_dialogue_example import main as sql_main
+
+if __name__ == "__main__":
+
+    # Run the examples
+
+    ## Agent examples
+    asyncio.run(auto_plan_main())
+    asyncio.run(awel_layout_main())
+    asyncio.run(custom_tool_main())
+    asyncio.run(retrieve_summary_main())
+    asyncio.run(plugin_main())
+    asyncio.run(sandbox_code_main())
+    asyncio.run(single_agent_main())
+    asyncio.run(sql_main())
+
+    ## awel examples
+    print("hello world!")
--- a/examples/agents/auto_plan_agent_dialogue_example.py
+++ b/examples/agents/auto_plan_agent_dialogue_example.py
@ -5,9 +5,9 @@
        Execute the following command in the terminal:
        Set env params.
        .. code-block:: shell
-
-            export OPENAI_API_KEY=sk-xx
-            export OPENAI_API_BASE=https://xx:80/v1
+            
+            export SILICONFLOW_API_KEY=sk-xx
+            export SILICONFLOW_API_BASE=https://xx:80/v1

        run example.
        ..code-block:: shell
@ -33,13 +33,14 @@ initialize_tracer(


 async def main():
-    from dbgpt.model.proxy import OpenAILLMClient
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

    agent_memory = AgentMemory()
-    from dbgpt.model.proxy.llms.tongyi import TongyiLLMClient

-    llm_client = TongyiLLMClient(
-        model_alias="qwen2-72b-instruct",
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
    )

    context: AgentContext = AgentContext(
--- a/examples/agents/awel_layout_agents_chat_examples.py
+++ b/examples/agents/awel_layout_agents_chat_examples.py
@ -6,14 +6,13 @@
        Set env params.
        .. code-block:: shell

-            export OPENAI_API_KEY=sk-xx
-            export OPENAI_API_BASE=https://xx:80/v1
+            export SILICONFLOW_API_KEY=sk-xx
+            export SILICONFLOW_API_BASE=https://xx:80/v1

        run example.
        ..code-block:: shell
            python examples/agents/awel_layout_agents_chat_examples.py
 """
-
 import asyncio
 import os

@ -34,15 +33,16 @@ initialize_tracer("/tmp/agent_trace.jsonl", create_system_app=True)


 async def main():
-    from dbgpt.model.proxy import OpenAILLMClient

    agent_memory = AgentMemory()
    agent_memory.gpts_memory.init(conv_id="test456")
    try:
-        from dbgpt.model.proxy.llms.tongyi import TongyiLLMClient
+        from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

-        llm_client = TongyiLLMClient(
-            model_alias="qwen2-72b-instruct",
+        llm_client = SiliconFlowLLMClient(
+            model_alias=os.getenv(
+                "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+            ),
        )

        context: AgentContext = AgentContext(conv_id="test456", gpts_app_name="信息析助手")
--- a/examples/agents/custom_tool_agent_example.py
+++ b/examples/agents/custom_tool_agent_example.py
@ -44,12 +44,17 @@ def count_directory_files(path: Annotated[str, Doc("The directory path")]) -> in


 async def main():
-    from dbgpt.model.proxy import OpenAILLMClient
-
-    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
-    context: AgentContext = AgentContext(conv_id="test456")
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
+    )
    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="test456")
+
+    context: AgentContext = AgentContext(conv_id="test456", gpts_app_name="工具助手")

    tools = ToolPack([simple_calculator, count_directory_files])

@ -77,7 +82,7 @@ async def main():
    )

    # dbgpt-vis message infos
-    print(await agent_memory.gpts_memory.one_chat_completions("test456"))
+    print(await agent_memory.gpts_memory.app_link_chat_message("test456"))


 if __name__ == "__main__":
--- a/examples/agents/plugin_agent_dialogue_example.py
+++ b/examples/agents/plugin_agent_dialogue_example.py
@ -6,8 +6,8 @@
        Set env params.
        .. code-block:: shell

-            export OPENAI_API_KEY=sk-xx
-            export OPENAI_API_BASE=https://xx:80/v1
+            export SILICONFLOW_API_KEY=sk-xx
+            export SILICONFLOW_API_BASE=https://xx:80/v1

        run example.
        ..code-block:: shell
@ -20,19 +20,24 @@ import os
 from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
 from dbgpt.agent.expand.tool_assistant_agent import ToolAssistantAgent
 from dbgpt.agent.resource import AutoGPTPluginToolPack
+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.proxy import OpenAILLMClient
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

-    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
-    context: AgentContext = AgentContext(conv_id="test456")
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
+    )

    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="test456")
+
+    context: AgentContext = AgentContext(conv_id="test456", gpts_app_name="插件对话助手")

    tools = AutoGPTPluginToolPack(test_plugin_dir)

@ -54,7 +59,7 @@ async def main():
    )

    # dbgpt-vis message infos
-    print(await agent_memory.gpts_memory.one_chat_completions("test456"))
+    print(await agent_memory.gpts_memory.app_link_chat_message("test456"))


 if __name__ == "__main__":
--- a/examples/agents/retrieve_summary_agent_dialogue_example.py
+++ b/examples/agents/retrieve_summary_agent_dialogue_example.py
@ -6,8 +6,8 @@
        Set env params.
        .. code-block:: shell

-            export OPENAI_API_KEY=sk-xx
-            export OPENAI_API_BASE=https://xx:80/v1
+            export SILICONFLOW_API_KEY=sk-xx
+            export SILICONFLOW_API_BASE=https://xx:80/v1

        run example.
        ..code-block:: shell
@ -18,20 +18,27 @@ import asyncio
 import os

 from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
-from dbgpt.agent.expand.retrieve_summary_assistant_agent import (
-    RetrieveSummaryAssistantAgent,
-)
+from dbgpt.agent.expand.summary_assistant_agent import SummaryAssistantAgent
 from dbgpt.configs.model_config import ROOT_PATH


-async def summary_example_with_success():
-    from dbgpt.model.proxy import OpenAILLMClient
+async def main():
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient
+
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
+    )
+    context: AgentContext = AgentContext(
+        conv_id="retrieve_summarize", gpts_app_name="Summary Assistant"
+    )

-    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo-16k")
-    context: AgentContext = AgentContext(conv_id="retrieve_summarize")
    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="retrieve_summarize")
+
    summarizer = (
-        await RetrieveSummaryAssistantAgent()
+        await SummaryAssistantAgent()
        .bind(context)
        .bind(LLMConfig(llm_client=llm_client))
        .bind(agent_memory)
@ -47,6 +54,7 @@ async def summary_example_with_success():
        "https://en.wikipedia.org/wiki/Chernobyl_disaster",
    ]

+    # TODO add a tool to load the pdf and internet files
    await user_proxy.initiate_chat(
        recipient=summarizer,
        reviewer=user_proxy,
@ -55,11 +63,8 @@ async def summary_example_with_success():
    )

    # dbgpt-vis message infos
-    print(await agent_memory.gpts_memory.one_chat_completions("retrieve_summarize"))
+    print(await agent_memory.gpts_memory.app_link_chat_message("retrieve_summarize"))


 if __name__ == "__main__":
-    asyncio.run(summary_example_with_success())
-    print(
-        "\033[92m=======================The Summary Assistant with Successful Results Ended==================\n\n\033[91m"
-    )
+    asyncio.run(main())
--- a/examples/agents/sandbox_code_agent_example.py
+++ b/examples/agents/sandbox_code_agent_example.py
@ -10,9 +10,9 @@ You can limit the memory and file system resources available to the code executi
 environment. The code execution environment is isolated from the host system,
 preventing access to the internet and other external resources.
 """
-
 import asyncio
 import logging
+import os
 from typing import Optional, Tuple

 from dbgpt.agent import (
@ -270,11 +270,28 @@ class SandboxCodeAssistantAgent(ConversableAgent):


 async def main():
-    from dbgpt.model.proxy import OpenAILLMClient
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

-    llm_client = OpenAILLMClient(model_alias="gpt-4o-mini")
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
+    )
    context: AgentContext = AgentContext(conv_id="test123")
-    agent_memory = AgentMemory(HybridMemory[AgentMemoryFragment].from_chroma())
+
+    # TODO Embedding and Rerank model refactor
+    from dbgpt.rag.embedding import OpenAPIEmbeddings
+
+    silicon_embeddings = OpenAPIEmbeddings(
+        api_url=os.getenv("SILICONFLOW_API_BASE") + "/embeddings",
+        api_key=os.getenv("SILICONFLOW_API_KEY"),
+        model_name="BAAI/bge-large-zh-v1.5",
+    )
+    agent_memory = AgentMemory(
+        HybridMemory[AgentMemoryFragment].from_chroma(
+            embeddings=silicon_embeddings,
+        )
+    )
    agent_memory.gpts_memory.init("test123")

    coder = (
--- a/examples/agents/single_agent_dialogue_example.py
+++ b/examples/agents/single_agent_dialogue_example.py
@ -17,28 +17,21 @@
 import asyncio
 import os

-from dbgpt.agent import (
-    AgentContext,
-    AgentMemory,
-    AgentMemoryFragment,
-    HybridMemory,
-    LLMConfig,
-    UserProxyAgent,
-)
+from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
 from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent


 async def main():
-    from dbgpt.model.proxy import OpenAILLMClient
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

-    # llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
-    from dbgpt.model.proxy.llms.tongyi import TongyiLLMClient
-
-    llm_client = TongyiLLMClient(
-        model_alias="qwen2-72b-instruct",
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
    )

-    context: AgentContext = AgentContext(conv_id="test123")
+    context: AgentContext = AgentContext(conv_id="test123", gpts_app_name="代码助手")
+
    agent_memory = AgentMemory()
    agent_memory.gpts_memory.init(conv_id="test123")
    try:
--- a/examples/agents/single_summary_agent_dialogue_example.py
+++ b/examples/agents/single_summary_agent_dialogue_example.py
@ -15,18 +15,25 @@
 """

 import asyncio
+import os

 from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
 from dbgpt.agent.expand.summary_assistant_agent import SummaryAssistantAgent


 async def summary_example_with_success():
-    from dbgpt.model.proxy import OpenAILLMClient
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

-    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
+    )
    context: AgentContext = AgentContext(conv_id="summarize")

    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="summarize")
+
    summarizer = (
        await SummaryAssistantAgent()
        .bind(context)
@ -71,16 +78,22 @@ async def summary_example_with_success():
    )

    # dbgpt-vis message infos
-    print(await agent_memory.gpts_memory.one_chat_completions("summarize"))
+    print(await agent_memory.gpts_memory.app_link_chat_message("summarize"))


 async def summary_example_with_faliure():
-    from dbgpt.model.proxy import OpenAILLMClient
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

-    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
+    )
    context: AgentContext = AgentContext(conv_id="summarize")

    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="summarize")
+
    summarizer = (
        await SummaryAssistantAgent()
        .bind(context)
@ -92,7 +105,6 @@ async def summary_example_with_faliure():
    user_proxy = await UserProxyAgent().bind(agent_memory).bind(context).build()

    # Test the failure example
-
    await user_proxy.initiate_chat(
        recipient=summarizer,
        reviewer=user_proxy,
@ -110,7 +122,7 @@ async def summary_example_with_faliure():
            """,
    )

-    print(await agent_memory.gpts_memory.one_chat_completions("summarize"))
+    print(await agent_memory.gpts_memory.app_link_chat_message("summarize"))


 if __name__ == "__main__":
--- a/examples/agents/sql_agent_dialogue_example.py
+++ b/examples/agents/sql_agent_dialogue_example.py
@ -20,24 +20,28 @@ import os
 from dbgpt.agent import AgentContext, AgentMemory, LLMConfig, UserProxyAgent
 from dbgpt.agent.expand.data_scientist_agent import DataScientistAgent
 from dbgpt.agent.resource import SQLiteDBResource
+from dbgpt.configs.model_config import ROOT_PATH
 from dbgpt.util.tracer import initialize_tracer

-current_dir = os.getcwd()
-parent_dir = os.path.dirname(current_dir)
-test_plugin_dir = os.path.join(parent_dir, "test_files")
+test_plugin_dir = os.path.join(ROOT_PATH, "test_files")

 initialize_tracer("/tmp/agent_trace.jsonl", create_system_app=True)


 async def main():
-    from dbgpt.model.proxy import OpenAILLMClient
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient

-    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
+    llm_client = SiliconFlowLLMClient(
+        model_alias=os.getenv(
+            "SILICONFLOW_MODEL_VERSION", "Qwen/Qwen2.5-Coder-32B-Instruct"
+        ),
+    )
    context: AgentContext = AgentContext(conv_id="test456")
+
    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="test456")

    sqlite_resource = SQLiteDBResource("SQLite Database", f"{test_plugin_dir}/dbgpt.db")
-
    user_proxy = await UserProxyAgent().bind(agent_memory).bind(context).build()

    sql_boy = (
@ -56,7 +60,7 @@ async def main():
    )

    ## dbgpt-vis message infos
-    print(await agent_memory.gpts_memory.one_chat_completions("test456"))
+    print(await agent_memory.gpts_memory.app_link_chat_message("test456"))


 if __name__ == "__main__":
--- a/examples/awel/simple_rag_summary_example.py
+++ b/examples/awel/simple_rag_summary_example.py
@ -31,7 +31,7 @@ from typing import Dict
 from dbgpt._private.pydantic import BaseModel, Field
 from dbgpt.core.awel import DAG, HttpTrigger, MapOperator
 from dbgpt.model.proxy import OpenAILLMClient
-from dbgpt.rag.knowledge import KnowledgeType
+from dbgpt.rag.knowledge.base import KnowledgeType
 from dbgpt.rag.operators import KnowledgeOperator, SummaryAssemblerOperator


--- a/examples/notebook/agent_auto_plan_dialogue_example.ipynb
+++ b/examples/notebook/agent_auto_plan_dialogue_example.ipynb
@ -1,118 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2024-04-10T04:38:14.228948Z",
-     "start_time": "2024-04-10T04:38:14.224972Z"
-    }
-   },
-   "source": [
-    "import nest_asyncio\n",
-    "from dbgpt.agent import (\n",
-    "    AgentContext,\n",
-    "    GptsMemory,\n",
-    "    LLMConfig,\n",
-    "    ResourceLoader,\n",
-    "    UserProxyAgent,\n",
-    ")\n",
-    "from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent\n",
-    "from dbgpt.agent.plan import AutoPlanChatManager\n",
-    "from dbgpt.model.proxy import OpenAILLMClient\n",
-    "\n",
-    "nest_asyncio.apply()"
-   ],
-   "execution_count": 7,
-   "outputs": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "is_executing": true
-   },
-   "source": [
-    "# Set your api key and api base url\n",
-    "# os.environ[\"OPENAI_API_KEY\"] = \"Your API\"\n",
-    "# os.environ[\"OPENAI_API_BASE\"] = \"https://api.openai.com/v1\""
-   ],
-   "outputs": []
-  },
-  {
-   "cell_type": "code",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2024-04-10T04:19:47.838081Z",
-     "start_time": "2024-04-10T04:17:54.465616Z"
-    }
-   },
-   "source": [
-    "llm_client = OpenAILLMClient(model_alias=\"gpt-4\")\n",
-    "context: AgentContext = AgentContext(conv_id=\"test456\", gpts_app_name=\"代码分析助手\")\n",
-    "\n",
-    "default_memory = GptsMemory()\n",
-    "\n",
-    "resource_loader = ResourceLoader()\n",
-    "\n",
-    "coder = (\n",
-    "    await CodeAssistantAgent()\n",
-    "    .bind(context)\n",
-    "    .bind(LLMConfig(llm_client=llm_client))\n",
-    "    .bind(default_memory)\n",
-    "    .bind(resource_loader)\n",
-    "    .build()\n",
-    ")\n",
-    "\n",
-    "manager = (\n",
-    "    await AutoPlanChatManager()\n",
-    "    .bind(context)\n",
-    "    .bind(default_memory)\n",
-    "    .bind(LLMConfig(llm_client=llm_client))\n",
-    "    .build()\n",
-    ")\n",
-    "manager.hire([coder])\n",
-    "\n",
-    "user_proxy = await UserProxyAgent().bind(context).bind(default_memory).build()\n",
-    "\n",
-    "\n",
-    "await user_proxy.initiate_chat(\n",
-    "    recipient=manager,\n",
-    "    reviewer=user_proxy,\n",
-    "    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.\",\n",
-    "    # message=\"Find papers on gpt-4 in the past three weeks on arxiv, and organize their titles, authors, and links into a markdown table\",\n",
-    "    # message=\"find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.\",\n",
-    ")"
-   ],
-   "execution_count": 4,
-   "outputs": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "dbgpt_env",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.13"
-  },
-  "orig_nbformat": 4,
-  "vscode": {
-   "interpreter": {
-    "hash": "f8b6b0e04f284afd2fbb5e4163e7d03bbdc845eaeb6e8c78fae04fce6b51dae6"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
--- a/examples/notebook/agent_awel_layout_dialogue_example.ipynb
+++ b/examples/notebook/agent_awel_layout_dialogue_example.ipynb
@ -1,135 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "id": "6de2e0bb",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2024-04-10T04:37:21.832993Z",
-     "start_time": "2024-04-10T04:37:21.828221Z"
-    }
-   },
-   "source": [
-    "import os\n",
-    "import nest_asyncio\n",
-    "from dbgpt.agent import (\n",
-    "    AgentContext,\n",
-    "    AgentResource,\n",
-    "    GptsMemory,\n",
-    "    LLMConfig,\n",
-    "    ResourceLoader,\n",
-    "    ResourceType,\n",
-    "    UserProxyAgent,\n",
-    ")\n",
-    "from dbgpt.agent.expand.plugin_assistant_agent import PluginAssistantAgent\n",
-    "from dbgpt.agent.expand.summary_assistant_agent import SummaryAssistantAgent\n",
-    "from dbgpt.agent.plan import WrappedAWELLayoutManager\n",
-    "from dbgpt.agent.resource import PluginFileLoadClient\n",
-    "from dbgpt.configs.model_config import ROOT_PATH\n",
-    "from dbgpt.model.proxy import OpenAILLMClient\n",
-    "\n",
-    "nest_asyncio.apply()\n",
-    "test_plugin_dir = os.path.join(ROOT_PATH, \"examples/test_files/plugins\")"
-   ],
-   "execution_count": 11,
-   "outputs": []
-  },
-  {
-   "cell_type": "code",
-   "id": "437b9c40",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2024-04-10T04:37:27.592117Z",
-     "start_time": "2024-04-10T04:37:23.569538Z"
-    }
-   },
-   "source": [
-    "# os.environ['OPENAI_API_KEY']=\"sk-x\"\n",
-    "# os.environ['OPENAI_API_BASE']=\"https://proxy_url/v1\"\n",
-    "# os.environ['SEARCH_ENGINE']=\"baidu\"\n",
-    "# os.environ['BAIDU_COOKIE']=\"\"\"your baidu cookie\"\"\"\n",
-    "\n",
-    "llm_client = OpenAILLMClient(model_alias=\"gpt-3.5-turbo\")\n",
-    "context: AgentContext = AgentContext(conv_id=\"test456\", gpts_app_name=\"信息析助手\")\n",
-    "\n",
-    "default_memory = GptsMemory()\n",
-    "\n",
-    "resource_loader = ResourceLoader()\n",
-    "plugin_file_loader = PluginFileLoadClient()\n",
-    "resource_loader.register_resource_api(plugin_file_loader)\n",
-    "\n",
-    "plugin_resource = AgentResource(\n",
-    "    type=ResourceType.Plugin,\n",
-    "    name=\"test\",\n",
-    "    value=test_plugin_dir,\n",
-    ")\n",
-    "\n",
-    "tool_engineer = (\n",
-    "    await PluginAssistantAgent()\n",
-    "    .bind(context)\n",
-    "    .bind(LLMConfig(llm_client=llm_client))\n",
-    "    .bind(default_memory)\n",
-    "    .bind([plugin_resource])\n",
-    "    .bind(resource_loader)\n",
-    "    .build()\n",
-    ")\n",
-    "summarizer = (\n",
-    "    await SummaryAssistantAgent()\n",
-    "    .bind(context)\n",
-    "    .bind(default_memory)\n",
-    "    .bind(LLMConfig(llm_client=llm_client))\n",
-    "    .build()\n",
-    ")\n",
-    "\n",
-    "manager = (\n",
-    "    await WrappedAWELLayoutManager()\n",
-    "    .bind(context)\n",
-    "    .bind(default_memory)\n",
-    "    .bind(LLMConfig(llm_client=llm_client))\n",
-    "    .build()\n",
-    ")\n",
-    "manager.hire([tool_engineer, summarizer])\n",
-    "\n",
-    "user_proxy = await UserProxyAgent().bind(context).bind(default_memory).build()\n",
-    "\n",
-    "await user_proxy.initiate_chat(\n",
-    "    recipient=manager,\n",
-    "    reviewer=user_proxy,\n",
-    "    message=\"查询成都今天天气\",\n",
-    "    # message=\"查询今天的最新热点财经新闻\",\n",
-    ")"
-   ],
-   "execution_count": 12,
-   "outputs": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7ded4107",
-   "metadata": {},
-   "source": [],
-   "outputs": []
-  }
- ],
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-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
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-   "file_extension": ".py",
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-   "nbconvert_exporter": "python",
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