✨ 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
✨ feat(agent): 增加智能体存储和记忆功能
2025-03-31 03:38:50 +08:00 · 2025-03-31 03:06:38 +08:00
4 changed files with 120 additions and 3 deletions
--- a/pyproject.toml
+++ b/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",
--- a/test2.py
+++ b/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)
--- a/uv.lock
+++ b/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 = [
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 ]

+[[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 = [
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+]
+
+[package.optional-dependencies]
+binary = [
+    { name = "psycopg-binary", marker = "implementation_name != 'pypy'" },
+]
+
+[[package]]
+name = "psycopg-binary"
+version = "3.2.6"
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+]
+
 [[package]]
 name = "ptyprocess"
 version = "0.7.0"
--- a/数据库优化工程师.py
+++ b/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)