✨ feat(pyproject): add psycopg dependency for PostgreSQL support

- 在依赖项中添加psycopg[binary]以支持PostgreSQL
- 提高项目与PostgreSQL的兼容性和灵活性

✨ feat(test2): create pdf_agent CLI application

- 添加pdf_agent函数以实现PDF代理功能
- 允许用户通过命令行界面与代理交互

pyproject.toml

@@ -14,6 +14,7 @@ dependencies = [
     "numpy>=2.2.4",
     "openai>=1.69.0",
     "pandas>=2.2.3",
+    "psycopg[binary]>=3.2.6",
     "pypdf>=5.4.0",
     "python-dotenv>=1.1.0",
     "sqlalchemy>=2.0.40",

test2.py

@@ -0,0 +1,48 @@
+import typer
+from typing import Optional, List
+from agno.agent import Agent
+from agno.storage.sqlite import SqliteStorage
+from agno.storage.postgres import PostgresStorage
+storage =SqliteStorage(table_name="agent_sessions", db_file="tmp/agent_storage.db")
+# db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
+# storage = PostgresStorage(table_name="pdf_agent", db_url=db_url)
+
+def pdf_agent(new: bool = False, user: str = "user"):
+    session_id: Optional[str] = None
+
+    if not new:
+        existing_sessions: List[str] = storage.get_all_session_ids(user)
+        if len(existing_sessions) > 0:
+            session_id = existing_sessions[0]
+
+    agent = Agent(
+        session_id=session_id,
+        user_id=user,
+        #knowledge=knowledge_base,
+        storage=storage,
+        # Show tool calls in the response
+        show_tool_calls=True,
+        # Enable the agent to read the chat history
+        read_chat_history=True,
+        # We can also automatically add the chat history to the messages sent to the model
+        # But giving the model the chat history is not always useful, so we give it a tool instead
+        # to only use when needed.
+        # add_history_to_messages=True,
+        # Number of historical responses to add to the messages.
+        # num_history_responses=3,
+    )
+    if session_id is None:
+        session_id = agent.session_id
+        print(f"Started Session: {session_id}\n")
+    else:
+        print(f"Continuing Session: {session_id}\n")
+
+    # Runs the agent as a cli app
+    agent.cli_app(markdown=True)
+
+
+if __name__ == "__main__":
+    # Load the knowledge base: Comment after first run
+    #knowledge_base.load(upsert=True)
+
+    typer.run(pdf_agent)

uv.lock

@@ -39,6 +39,7 @@ dependencies = [
     { name = "numpy" },
     { name = "openai" },
     { name = "pandas" },
+    { name = "psycopg", extra = ["binary"] },
     { name = "pypdf" },
     { name = "python-dotenv" },
     { name = "sqlalchemy" },
@@ -56,6 +57,7 @@ requires-dist = [
     { name = "numpy", specifier = ">=2.2.4" },
     { name = "openai", specifier = ">=1.69.0" },
     { name = "pandas", specifier = ">=2.2.3" },
+    { name = "psycopg", extras = ["binary"], specifier = ">=3.2.6" },
     { name = "pypdf", specifier = ">=5.4.0" },
     { name = "python-dotenv", specifier = ">=1.1.0" },
     { name = "sqlalchemy", specifier = ">=2.0.40" },
@@ -1300,6 +1302,53 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/50/1b/6921afe68c74868b4c9fa424dad3be35b095e16687989ebbb50ce4fceb7c/psutil-7.0.0-cp37-abi3-win_amd64.whl", hash = "sha256:4cf3d4eb1aa9b348dec30105c55cd9b7d4629285735a102beb4441e38db90553", size = 244885 },
 ]
 
+[[package]]
+name = "psycopg"
+version = "3.2.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
+    { name = "tzdata", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/67/97/eea08f74f1c6dd2a02ee81b4ebfe5b558beb468ebbd11031adbf58d31be0/psycopg-3.2.6.tar.gz", hash = "sha256:16fa094efa2698f260f2af74f3710f781e4a6f226efe9d1fd0c37f384639ed8a", size = 156322 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d7/7d/0ba52deff71f65df8ec8038adad86ba09368c945424a9bd8145d679a2c6a/psycopg-3.2.6-py3-none-any.whl", hash = "sha256:f3ff5488525890abb0566c429146add66b329e20d6d4835662b920cbbf90ac58", size = 199077 },
+]
+
+[package.optional-dependencies]
+binary = [
+    { name = "psycopg-binary", marker = "implementation_name != 'pypy'" },
+]
+
+[[package]]
+name = "psycopg-binary"
+version = "3.2.6"
+source = { registry = "https://pypi.org/simple" }
+wheels = [
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+]
+
 [[package]]
 name = "ptyprocess"
 version = "0.7.0"

数据库优化工程师.py

@@ -15,7 +15,7 @@ from typing import Optional
 from dataclasses import dataclass
 from dotenv import load_dotenv
 
-from agno.agent import Agent
+from agno.agent import Agent, AgentMemory
 from agno.models.deepseek import DeepSeek
 from agno.knowledge.pdf import PDFKnowledgeBase
 from agno.vectordb.lancedb import LanceDb, SearchType
@@ -25,8 +25,9 @@ from agno.tools.mcp import MCPTools
 from mcp.client.stdio import stdio_client
 from mcp import ClientSession, StdioServerParameters
 from agno.knowledge.website import WebsiteKnowledgeBase
+from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.memory.db.sqlite import SqliteMemoryDb
 
- 
 
 async def main():
     load_dotenv()
@@ -94,13 +95,31 @@ async def main():
     ):
         agent = Agent(
             model=DeepSeek(id="deepseek-chat"),
+            storage=SqliteAgentStorage(
+                table_name="agent_sessions", db_file="tmp/agent_storage.db"
+            ),
+            memory=AgentMemory(
+                db=SqliteMemoryDb(
+                    table_name="agent_memory", db_file="tmp/agent_storage.db"
+                ),
+                create_user_memories=True,
+                create_session_summary=True,
+            ),
+            # Set add_history_to_messages=true to add the previous chat history to the messages sent to the Model.
+            #add_history_to_messages=True,
+            # Number of historical responses to add to the messages.
+            #num_history_responses=3,
             markdown=True,
             knowledge=knowledge_base,
             search_knowledge=True,
             show_tool_calls=True,
             tools=[postgres_tools, searxng_tools],
+            session_id="1",
+            # Enable the agent to read the chat history
+            read_chat_history=True,
         )
-        await agent.aprint_response("帮我分析一下aq.public数据库,并给出优化建议", stream=True)
+        await agent.aprint_response("我现在想要记录用户对智能体和课程的使用权限及使用情况，需要如何设计表结构", stream=True)
+        # await agent.aprint_response("帮我分析一下aq.public数据库,并给出优化建议", stream=True)
         # await agent.aprint_response("阅读下 https://www.lucidchart.com/blog/database-design-best-practices 这篇文章", stream=True)