docs(agent): Add agents cookbook

dbgpt/agent/expand/code_assistant_agent.py

@@ -25,7 +25,17 @@
     "such as: True.\n"
     "        If it is determined to be a failure, return false and the reason, "
     "such as: False. There are no numbers in the execution results that answer the "
-    "computational goals of the mission."
+    "computational goals of the mission.\n"
+    "You can refer to the following examples:\n"
+    "user: Please understand the following task objectives and results and give your "
+    "judgment:\nTask goal: Calculate the result of 1 + 2 using Python code.\n"
+    "Execution Result: 3\n"
+    "assistant: True\n\n"
+    "user: Please understand the following task objectives and results and give your "
+    "judgment:\nTask goal: Calculate the result of 100 * 10 using Python code.\n"
+    "Execution Result: 'you can get the result by multiplying 100 by 10'\n"
+    "assistant: False. There are no numbers in the execution results that answer the "
+    "computational goals of the mission.\n"
 )
 
 

dbgpt/agent/resource/resource_db_api.py

@@ -1,7 +1,7 @@
 """Database resource client API."""
 import logging
 from contextlib import contextmanager
-from typing import Iterator, List, Optional, Union
+from typing import TYPE_CHECKING, Iterator, List, Optional, Union
 
 from .resource_api import AgentResource, ResourceClient, ResourceType
 
@@ -48,7 +48,8 @@ async def run_sql(self, db: str, sql: str):
 class SqliteLoadClient(ResourceDbClient):
     """SQLite resource client."""
 
-    from sqlalchemy.orm.session import Session
+    if TYPE_CHECKING:
+        from sqlalchemy.orm.session import Session
 
     def __init__(self):
         """Create a SQLite resource client."""
@@ -59,7 +60,7 @@ def get_data_type(self, resource: AgentResource) -> str:
         return "sqlite"
 
     @contextmanager
-    def connect(self, db) -> Iterator[Session]:
+    def connect(self, db) -> Iterator["Session"]:
         """Connect to the database."""
         from sqlalchemy import create_engine
         from sqlalchemy.orm import sessionmaker

dbgpt/agent/util/__init__.py

@@ -1 +1,4 @@
 """Utils for the agent module."""
+from .cmp import cmp_string_equal  # noqa: F401
+
+__ALL__ = ["cmp_string_equal"]

dbgpt/vis/__init__.py

@@ -1,5 +1,6 @@
 """GPT-Vis Module."""
 
+from .base import Vis  # noqa: F401
 from .client import vis_client  # noqa: F401
 from .tags.vis_agent_message import VisAgentMessages  # noqa: F401
 from .tags.vis_agent_plans import VisAgentPlans  # noqa: F401
@@ -9,6 +10,7 @@
 from .tags.vis_plugin import VisPlugin  # noqa: F401
 
 __ALL__ = [
+    "Vis",
     "vis_client",
     "VisAgentMessages",
     "VisAgentPlans",

docs/docs/agents/cookbook/calculator_with_agents.md

@@ -0,0 +1,91 @@
+# Calculator With Agents
+
+In this example, we will show you how to use an agent as your calculator.
+
+## Installations
+
+Install the required packages by running the following command:
+
+```bash
+pip install "dbgpt[agent]>=0.5.4rc0" -U
+pip install openai
+```
+
+## Code
+
+Create a new Python file and add the following code:
+
+```python
+import asyncio
+
+from dbgpt.agent import AgentContext, GptsMemory, LLMConfig, UserProxyAgent
+from dbgpt.agent.expand.code_assistant_agent import CodeAssistantAgent
+from dbgpt.model.proxy import OpenAILLMClient
+
+async def main():
+    llm_client = OpenAILLMClient(model_alias="gpt-3.5-turbo")
+    context: AgentContext = AgentContext(conv_id="test123")
+    default_memory: GptsMemory = GptsMemory()
+
+    # Create a code assistant agent
+    coder = (
+        await CodeAssistantAgent()
+        .bind(context)
+        .bind(LLMConfig(llm_client=llm_client))
+        .bind(default_memory)
+        .build()
+    )
+
+    # Create a user proxy agent
+    user_proxy = await UserProxyAgent().bind(context).bind(default_memory).build()
+
+    # Initiate a chat with the user proxy agent
+    await user_proxy.initiate_chat(
+        recipient=coder,
+        reviewer=user_proxy,
+        message="calculate the result of 321 * 123"  
+    )
+    # Obtain conversation history messages between agents
+    print(await default_memory.one_chat_completions("test123"))
+
+if __name__ == "__main__":
+    asyncio.run(main())
+```
+
+You will see the following output:
+
+````bash
+--------------------------------------------------------------------------------
+User (to Turing)-[]:
+
+"calculate the result of 321 * 123"
+
+--------------------------------------------------------------------------------
+un_stream ai response: ```python
+# Calculate the result of 321 * 123
+result = 321 * 123
+print(result)
+```
+
+>>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...
+execute_code was called without specifying a value for use_docker. Since the python docker package is not available, code will be run natively. Note: this fallback behavior is subject to change
+un_stream ai response: True
+
+--------------------------------------------------------------------------------
+Turing (to User)-[gpt-3.5-turbo]:
+
+"```python\n# Calculate the result of 321 * 123\nresult = 321 * 123\nprint(result)\n```"
+>>>>>>>>Turing Review info: 
+Pass(None)
+>>>>>>>>Turing Action report: 
+execution succeeded,
+
+39483
+
+
+--------------------------------------------------------------------------------
+```agent-plans
+[{"name": "calculate the result of 321 * 123", "num": 1, "status": "complete", "agent": "Human", "markdown": "```agent-messages\n[{\"sender\": \"CodeEngineer\", \"receiver\": \"Human\", \"model\": \"gpt-3.5-turbo\", \"markdown\": \"```vis-code\\n{\\\"exit_success\\\": true, \\\"language\\\": \\\"python\\\", \\\"code\\\": [[\\\"python\\\", \\\"# Calculate the result of 321 * 123\\\\nresult = 321 * 123\\\\nprint(result)\\\"]], \\\"log\\\": \\\"\\\\n39483\\\\n\\\"}\\n```\"}]\n```"}]
+```
+(dbgpt-agents-py3.11) (base) ➜  dbgpt-agents
+````