Formatting

cookbook/examples/streamlit/llm_os/app.py

@@ -1,4 +1,5 @@
 from typing import List
+
 import nest_asyncio
 import streamlit as st
 from agno.agent import Agent
@@ -15,7 +16,9 @@
     page_icon=":orange_heart:",
 )
 st.title("LLM OS")
-st.markdown("##### :orange_heart: built using [Agno](https://github.com/phidatahq/agno)")
+st.markdown(
+    "##### :orange_heart: built using [Agno](https://github.com/phidatahq/agno)"
+)
 
 
 def main() -> None:
@@ -40,7 +43,9 @@ def main() -> None:
     # Get calculator_enabled from session state if set
     calculator_enabled = st.session_state["calculator_enabled"]
     # Checkbox for enabling calculator
-    calculator = st.sidebar.checkbox("Calculator", value=calculator_enabled, help="Enable calculator.")
+    calculator = st.sidebar.checkbox(
+        "Calculator", value=calculator_enabled, help="Enable calculator."
+    )
     if calculator_enabled != calculator:
         st.session_state["calculator_enabled"] = calculator
         calculator_enabled = calculator
@@ -52,7 +57,9 @@ def main() -> None:
     # Get file_tools_enabled from session state if set
     file_tools_enabled = st.session_state["file_tools_enabled"]
     # Checkbox for enabling shell tools
-    file_tools = st.sidebar.checkbox("File Tools", value=file_tools_enabled, help="Enable file tools.")
+    file_tools = st.sidebar.checkbox(
+        "File Tools", value=file_tools_enabled, help="Enable file tools."
+    )
     if file_tools_enabled != file_tools:
         st.session_state["file_tools_enabled"] = file_tools
         file_tools_enabled = file_tools
@@ -64,7 +71,11 @@ def main() -> None:
     # Get ddg_search_enabled from session state if set
     ddg_search_enabled = st.session_state["ddg_search_enabled"]
     # Checkbox for enabling web search
-    ddg_search = st.sidebar.checkbox("Web Search", value=ddg_search_enabled, help="Enable web search using DuckDuckGo.")
+    ddg_search = st.sidebar.checkbox(
+        "Web Search",
+        value=ddg_search_enabled,
+        help="Enable web search using DuckDuckGo.",
+    )
     if ddg_search_enabled != ddg_search:
         st.session_state["ddg_search_enabled"] = ddg_search
         ddg_search_enabled = ddg_search
@@ -76,7 +87,9 @@ def main() -> None:
     # Get shell_tools_enabled from session state if set
     shell_tools_enabled = st.session_state["shell_tools_enabled"]
     # Checkbox for enabling shell tools
-    shell_tools = st.sidebar.checkbox("Shell Tools", value=shell_tools_enabled, help="Enable shell tools.")
+    shell_tools = st.sidebar.checkbox(
+        "Shell Tools", value=shell_tools_enabled, help="Enable shell tools."
+    )
     if shell_tools_enabled != shell_tools:
         st.session_state["shell_tools_enabled"] = shell_tools
         shell_tools_enabled = shell_tools
@@ -159,7 +172,9 @@ def main() -> None:
             st.session_state["llm_os"] = llm_os
         except RuntimeError as e:
             st.error(f"Database Error: {str(e)}")
-            st.info("Please make sure your PostgreSQL database is running at postgresql+psycopg://ai:ai@localhost:5532/ai")
+            st.info(
+                "Please make sure your PostgreSQL database is running at postgresql+psycopg://ai:ai@localhost:5532/ai"
+            )
             return
     else:
         llm_os = st.session_state["llm_os"]
@@ -177,11 +192,14 @@ def main() -> None:
     if llm_os.memory and not st.session_state["messages"]:
         logger.debug("Loading chat history")
         st.session_state["messages"] = [
-            {"role": message.role, "content": message.content} for message in llm_os.memory.messages
+            {"role": message.role, "content": message.content}
+            for message in llm_os.memory.messages
         ]
     elif not st.session_state["messages"]:
         logger.debug("No chat history found")
-        st.session_state["messages"] = [{"role": "agent", "content": "Ask me questions..."}]
+        st.session_state["messages"] = [
+            {"role": "agent", "content": "Ask me questions..."}
+        ]
 
     # Display chat history first (all previous messages)
     for message in st.session_state["messages"]:
@@ -219,7 +237,9 @@ def main() -> None:
             st.session_state["url_scrape_key"] = 0
 
         input_url = st.sidebar.text_input(
-            "Add URL to Knowledge Base", type="default", key=st.session_state["url_scrape_key"]
+            "Add URL to Knowledge Base",
+            type="default",
+            key=st.session_state["url_scrape_key"],
         )
         add_url_button = st.sidebar.button("Add URL")
         if add_url_button:
@@ -240,7 +260,9 @@ def main() -> None:
             st.session_state["file_uploader_key"] = 100
 
         uploaded_file = st.sidebar.file_uploader(
-            "Add a PDF :page_facing_up:", type="pdf", key=st.session_state["file_uploader_key"]
+            "Add a PDF :page_facing_up:",
+            type="pdf",
+            key=st.session_state["file_uploader_key"],
         )
         if uploaded_file is not None:
             alert = st.sidebar.info("Processing PDF...", icon="🧠")
@@ -264,10 +286,14 @@ def main() -> None:
     if llm_os.team and len(llm_os.team) > 0:
         for team_member in llm_os.team:
             if team_member.memory and len(team_member.memory.messages) > 0:
-                with st.status(f"{team_member.name} Memory", expanded=False, state="complete"):
+                with st.status(
+                    f"{team_member.name} Memory", expanded=False, state="complete"
+                ):
                     with st.container():
                         _team_member_memory_container = st.empty()
-                        _team_member_memory_container.json(team_member.memory.get_messages())
+                        _team_member_memory_container.json(
+                            team_member.memory.get_messages()
+                        )
 
     # Remove the run history section entirely
     if st.sidebar.button("New Run"):
@@ -280,7 +306,9 @@ def restart_agent():
     for key in ["llm_os", "messages"]:  # Removed "llm_os_run_id"
         st.session_state.pop(key, None)
     st.session_state["url_scrape_key"] = st.session_state.get("url_scrape_key", 0) + 1
-    st.session_state["file_uploader_key"] = st.session_state.get("file_uploader_key", 100) + 1
+    st.session_state["file_uploader_key"] = (
+        st.session_state.get("file_uploader_key", 100) + 1
+    )
     st.rerun()
 
 

cookbook/examples/streamlit/llm_os/os_agent.py

@@ -1,24 +1,24 @@
+import os
 from pathlib import Path
-from typing import Optional, List
 from textwrap import dedent
+from typing import List, Optional
 
 from agno.agent import Agent
+from agno.embedder.openai import OpenAIEmbedder
+from agno.knowledge import AgentKnowledge
 from agno.models.openai import OpenAIChat
+from agno.storage.agent.postgres import PostgresAgentStorage
 from agno.tools import Toolkit
 from agno.tools.calculator import CalculatorTools
+from agno.tools.duckdb import DuckDbTools
 from agno.tools.duckduckgo import DuckDuckGoTools
 from agno.tools.exa import ExaTools
 from agno.tools.file import FileTools
+from agno.tools.python import PythonTools
 from agno.tools.shell import ShellTools
 from agno.tools.yfinance import YFinanceTools
-from agno.tools.duckdb import DuckDbTools
-from agno.tools.python import PythonTools
-from agno.knowledge import AgentKnowledge
-from agno.storage.agent.postgres import PostgresAgentStorage
-from agno.vectordb.qdrant import Qdrant
-from agno.embedder.openai import OpenAIEmbedder
 from agno.utils.log import logger
-import os
+from agno.vectordb.qdrant import Qdrant
 from dotenv import load_dotenv
 
 load_dotenv()
@@ -75,21 +75,26 @@ def get_llm_os(
 
     if data_analyst:
         data_analyst_agent: Agent = Agent(
-    tools=[DuckDbTools()],
-    show_tool_calls=True,
-    instructions="Use this file for Movies data: https://phidata-public.s3.amazonaws.com/demo_data/IMDB-Movie-Data.csv",
-
-)
+            tools=[DuckDbTools()],
+            show_tool_calls=True,
+            instructions="Use this file for Movies data: https://phidata-public.s3.amazonaws.com/demo_data/IMDB-Movie-Data.csv",
+        )
         team.append(data_analyst_agent)
         extra_instructions.append(
             "To answer questions about my favorite movies, delegate the task to the `Data Analyst`."
         )
 
     if python_agent_enable:
-        python_agent: Agent = Agent(tools=[PythonTools(base_dir=Path("tmp/python"))], show_tool_calls=True , instructions="To write and run Python code, delegate the task to the `Python Agent`.")
+        python_agent: Agent = Agent(
+            tools=[PythonTools(base_dir=Path("tmp/python"))],
+            show_tool_calls=True,
+            instructions="To write and run Python code, delegate the task to the `Python Agent`.",
+        )
 
         team.append(python_agent)
-        extra_instructions.append("To write and run Python code, delegate the task to the `Python Agent`.")
+        extra_instructions.append(
+            "To write and run Python code, delegate the task to the `Python Agent`."
+        )
     if research_agent_enable:
         research_agent = Agent(
             name="Research Agent",
@@ -239,9 +244,8 @@ def get_llm_os(
             "Carefully read the information you have gathered and provide a clear and concise answer to the user.",
             "Do not use phrases like 'based on my knowledge' or 'depending on the information'.",
             "You can delegate tasks to an AI Agent in your team depending of their role and the tools available to them.",
-             extra_instructions,
+            extra_instructions,
         ],
-
         storage=PostgresAgentStorage(db_url=db_url, table_name="llm_os_runs"),
         # Define the knowledge base
         knowledge=AgentKnowledge(

cookbook/models/google/gemini/storage_and_memory.py

@@ -1,10 +1,10 @@
 """Run `pip install duckduckgo-search pgvector google.generativeai` to install dependencies."""
 
 from agno.agent import Agent
+from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
 from agno.memory import AgentMemory
 from agno.memory.db.postgres import PgMemoryDb
 from agno.models.google import Gemini
-from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
 from agno.storage.agent.postgres import PostgresAgentStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 from agno.vectordb.pgvector import PgVector

libs/agno/agno/models/google/gemini.py

@@ -6,29 +6,34 @@
 from pathlib import Path
 from typing import Any, Callable, Dict, Iterator, List, Optional, Union
 
-from agno.media import Image, Audio, Video
-from agno.models.base import Model, Metrics
+from agno.media import Audio, Image, Video
+from agno.models.base import Metrics, Model
 from agno.models.message import Message
 from agno.models.response import ModelResponse
-from agno.tools.function import Function
 from agno.tools import Toolkit
+from agno.tools.function import Function
 from agno.utils.log import logger
 
 try:
     import google.generativeai as genai
     from google.ai.generativelanguage_v1beta.types import (
-        Part,
         FunctionCall as GeminiFunctionCall,
+    )
+    from google.ai.generativelanguage_v1beta.types import (
         FunctionResponse as GeminiFunctionResponse,
     )
-    from google.generativeai import GenerativeModel
-    from google.generativeai.types.generation_types import GenerateContentResponse
-    from google.generativeai.types.content_types import FunctionDeclaration, Tool as GeminiTool
-    from google.generativeai.types import file_types
+    from google.ai.generativelanguage_v1beta.types import (
+        Part,
+    )
     from google.ai.generativelanguage_v1beta.types.generative_service import (
         GenerateContentResponse as ResultGenerateContentResponse,
     )
     from google.api_core.exceptions import PermissionDenied
+    from google.generativeai import GenerativeModel
+    from google.generativeai.types import file_types
+    from google.generativeai.types.content_types import FunctionDeclaration
+    from google.generativeai.types.content_types import Tool as GeminiTool
+    from google.generativeai.types.generation_types import GenerateContentResponse
     from google.protobuf.struct_pb2 import Struct
 except (ModuleNotFoundError, ImportError):
     raise ImportError("`google-generativeai` not installed. Please install it using `pip install google-generativeai`")
@@ -186,11 +191,7 @@ def _format_messages(messages: List[Message]) -> List[Dict[str, Any]]:
 
         # Add role to the message for the model
         role = (
-            "model"
-            if message.role in ["system", "developer"]
-            else "user"
-            if message.role == "tool"
-            else message.role
+            "model" if message.role in ["system", "developer"] else "user" if message.role == "tool" else message.role
         )
         message_for_model["role"] = role
 
@@ -425,7 +426,6 @@ def request_kwargs(self) -> Dict[str, Any]:
             request_params["tools"] = [GeminiTool(function_declarations=self.function_declarations)]
         return request_params
 
-
     def add_tool(
         self,
         tool: Union[Toolkit, Callable, Dict, Function],