Update groq agent

cookbook/playground/groq_agents.py

@@ -0,0 +1,84 @@
+"""Usage:
+1. Install libraries: `pip install groq duckduckgo-search yfinance pypdf sqlalchemy 'fastapi[standard]' youtube-transcript-api phidata`
+2. Run the script: `python cookbook/playground/groq_agents.py`
+"""
+
+from phi.agent import Agent
+from phi.model.groq import Groq
+from phi.playground import Playground, serve_playground_app
+from phi.storage.agent.sqlite import SqlAgentStorage
+from phi.tools.duckduckgo import DuckDuckGo
+from phi.tools.yfinance import YFinanceTools
+from phi.tools.youtube_tools import YouTubeTools
+
+xai_agent_storage: str = "tmp/groq_agents.db"
+common_instructions = [
+    "If the user about you or your skills, tell them your name and role.",
+]
+
+web_agent = Agent(
+    name="Web Agent",
+    role="Search the web for information",
+    agent_id="web-agent",
+    model=Groq(id="llama3-groq-70b-8192-tool-use-preview"),
+    tools=[DuckDuckGo()],
+    instructions=[
+        "Use the `duckduckgo_search` or `duckduckgo_news` tools to search the web for information.",
+        "Always include sources you used to generate the answer.",
+    ]
+    + common_instructions,
+    storage=SqlAgentStorage(table_name="web_agent", db_file=xai_agent_storage),
+    show_tool_calls=True,
+    add_history_to_messages=True,
+    num_history_responses=2,
+    add_name_to_instructions=True,
+    add_datetime_to_instructions=True,
+    markdown=True,
+)
+
+finance_agent = Agent(
+    name="Finance Agent",
+    role="Get financial data",
+    agent_id="finance-agent",
+    model=Groq(id="llama3-groq-70b-8192-tool-use-preview"),
+    tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True, company_news=True)],
+    description="You are an investment analyst that researches stocks and helps users make informed decisions.",
+    instructions=["Always use tables to display data"] + common_instructions,
+    storage=SqlAgentStorage(table_name="finance_agent", db_file=xai_agent_storage),
+    show_tool_calls=True,
+    add_history_to_messages=True,
+    num_history_responses=5,
+    add_name_to_instructions=True,
+    add_datetime_to_instructions=True,
+    markdown=True,
+)
+
+
+youtube_agent = Agent(
+    name="YouTube Agent",
+    role="Understand YouTube videos and answer questions",
+    agent_id="youtube-agent",
+    model=Groq(id="llama3-groq-70b-8192-tool-use-preview"),
+    tools=[YouTubeTools()],
+    description="You are a YouTube agent that has the special skill of understanding YouTube videos and answering questions about them.",
+    instructions=[
+        "Using a video URL, get the video data using the `get_youtube_video_data` tool and captions using the `get_youtube_video_data` tool.",
+        "Using the data and captions, answer the user's question in an engaging and thoughtful manner. Focus on the most important details.",
+        "If you cannot find the answer in the video, say so and ask the user to provide more details.",
+        "Keep your answers concise and engaging.",
+        "If the user just provides a URL, summarize the video and answer questions about it.",
+    ]
+    + common_instructions,
+    storage=SqlAgentStorage(table_name="youtube_agent", db_file=xai_agent_storage),
+    show_tool_calls=True,
+    add_history_to_messages=True,
+    num_history_responses=5,
+    add_name_to_instructions=True,
+    add_datetime_to_instructions=True,
+    markdown=True,
+)
+
+app = Playground(agents=[finance_agent, youtube_agent, web_agent]).get_app(use_async=False)
+
+if __name__ == "__main__":
+    serve_playground_app("groq_agents:app", reload=True)

cookbook/providers/groq/README.md

@@ -75,6 +75,14 @@ python cookbook/providers/groq/structured_output.py
 
 ### 7. Run Agent that uses storage
 
+Please run pgvector in a docker container using:
+
+```shell
+./cookbook/run_pgvector.sh
+```
+
+Then run the following:
+
 ```shell
 python cookbook/providers/groq/storage.py
 ```

cookbook/providers/groq/finance_agent.py

@@ -12,4 +12,6 @@
     markdown=True,
 )
 
-agent.print_response("Summarize and compare analyst recommendations and fundamentals for TSLA and NVDA. Show in tables.", stream=True)
+agent.print_response(
+    "Summarize and compare analyst recommendations and fundamentals for TSLA and NVDA. Show in tables.", stream=True
+)