v1.0

docs/static/redirect.js

+window.onload = function() {
+    if (window.location.pathname == '/' || window.location.pathname == "") {
+      window.location.href = '/docs/overview';
+    }
+};
\ No newline at end of file

docs/versions.json

+[
+]

examples/__main__.py

+# 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!")

examples/agents/auto_plan_agent_dialogue_example.py

+"""Agents: auto plan agents example?
+
+Examples:
+
+    Execute the following command in the terminal:
+    Set env params.
+    .. code-block:: shell
+
+        export SILICONFLOW_API_KEY=sk-xx
+        export SILICONFLOW_API_BASE=https://xx:80/v1
+
+    run example.
+    ..code-block:: shell
+        python examples/agents/auto_plan_agent_dialogue_example.py
+"""
+
+import asyncio
+import os
+
+from dbgpt.agent import (
+    AgentContext,
+    AgentMemory,
+    AutoPlanChatManager,
+    LLMConfig,
+    UserProxyAgent,
+)
+from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent
+from dbgpt.util.tracer import initialize_tracer
+
+initialize_tracer(
+    "/tmp/agent_auto_plan_agent_dialogue_example_trace.jsonl", create_system_app=True
+)
+
+
+async def main():
+    from dbgpt.model.proxy.llms.siliconflow import SiliconFlowLLMClient
+
+    agent_memory = AgentMemory()
+
+    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="代码分析助手", max_new_tokens=2048
+    )
+    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="test456")
+    try:
+        coder = (
+            await CodeAssistantAgent()
+            .bind(context)
+            .bind(LLMConfig(llm_client=llm_client))
+            .bind(agent_memory)
+            .build()
+        )
+
+        manager = (
+            await AutoPlanChatManager()
+            .bind(context)
+            .bind(agent_memory)
+            .bind(LLMConfig(llm_client=llm_client))
+            .build()
+        )
+        manager.hire([coder])
+
+        user_proxy = await UserProxyAgent().bind(context).bind(agent_memory).build()
+
+        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.",
+            # message="Find papers on gpt-4 in the past three weeks on arxiv, and organize their titles, authors, and links into a markdown table",
+            # message="find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.",
+        )
+    finally:
+        agent_memory.gpts_memory.clear(conv_id="test456")
+
+
+if __name__ == "__main__":
+    ## dbgpt-vis message infos
+    asyncio.run(main())

examples/agents/awel_layout_agents_chat_examples.py

+"""Agents: auto plan agents example?
+
+Examples:
+
+    Execute the following command in the terminal:
+    Set env params.
+    .. code-block:: shell
+
+        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
+
+from dbgpt.agent import (
+    AgentContext,
+    AgentMemory,
+    LLMConfig,
+    UserProxyAgent,
+    WrappedAWELLayoutManager,
+)
+from dbgpt.agent.expand.resources.search_tool import baidu_search
+from dbgpt.agent.expand.summary_assistant_agent import SummaryAssistantAgent
+from dbgpt.agent.expand.tool_assistant_agent import ToolAssistantAgent
+from dbgpt.agent.resource import ToolPack
+from dbgpt.util.tracer import initialize_tracer
+
+initialize_tracer("/tmp/agent_trace.jsonl", create_system_app=True)
+
+
+async def main():
+    agent_memory = AgentMemory()
+    agent_memory.gpts_memory.init(conv_id="test456")
+    try:
+        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="test456", gpts_app_name="信息析助手"
+        )
+
+        tools = ToolPack([baidu_search])
+        tool_engineer = (
+            await ToolAssistantAgent()
+            .bind(context)
+            .bind(LLMConfig(llm_client=llm_client))
+            .bind(agent_memory)
+            .bind(tools)
+            .build()
+        )
+        summarizer = (
+            await SummaryAssistantAgent()
+            .bind(context)
+            .bind(agent_memory)
+            .bind(LLMConfig(llm_client=llm_client))
+            .build()
+        )
+
+        manager = (
+            await WrappedAWELLayoutManager()
+            .bind(context)
+            .bind(agent_memory)
+            .bind(LLMConfig(llm_client=llm_client))
+            .build()
+        )
+        manager.hire([tool_engineer, summarizer])
+
+        user_proxy = await UserProxyAgent().bind(context).bind(agent_memory).build()
+
+        await user_proxy.initiate_chat(
+            recipient=manager,
+            reviewer=user_proxy,
+            message="查询北京今天天气",
+            # message="查询今天的最新热点财经新闻",
+            # message="Find papers on gpt-4 in the past three weeks on arxiv, and organize their titles, authors, and links into a markdown table",
+            # message="find papers on LLM applications from arxiv in the last month, create a markdown table of different domains.",
+        )
+
+    finally:
+        agent_memory.gpts_memory.clear(conv_id="test456")
+
+
+if __name__ == "__main__":
+    ## dbgpt-vis message infos
+    asyncio.run(main())