Merge branch 'main' of https://github.com/phidatahq/phidata

cookbook/agents/agent.py

@@ -118,7 +118,8 @@ def get_agent(
  "Make your report engaging, informative, and well-structured.",
  "Remember: you are writing for the New York Times, so the quality of the report is important.",
  ],
- expected_output=dedent("""\
+ expected_output=dedent(
+ """\
  An engaging, informative, and well-structured report in the following format:
  <report_format>
  ## Title
@@ -142,7 +143,8 @@ def get_agent(
  - [Reference 1](Link to Source)
  - [Reference 2](Link to Source)
  </report_format>
- """),
+ """
+ ),
  tools=[ExaTools(num_results=5, text_length_limit=1000)],
  # This setting tells the LLM to format messages in markdown
  markdown=True,
@@ -167,7 +169,8 @@ def get_agent(
  "When you share numbers, make sure to include the units (e.g., millions/billions) and currency.",
  "REMEMBER: This report is for a very important client, so the quality of the report is important.",
  ],
- expected_output=dedent("""\
+ expected_output=dedent(
+ """\
  <report_format>
  ## [Company Name]: Investment Report
 
@@ -203,7 +206,8 @@ def get_agent(
  {provide a recommendation on the stock along with a thorough reasoning}
 
  </report_format>
- """),
+ """
+ ),
  tools=[YFinanceTools(stock_price=True, company_info=True, analyst_recommendations=True, company_news=True)],
  # This setting tells the LLM to format messages in markdown
  markdown=True,
@@ -226,11 +230,13 @@ def get_agent(
  run_id=run_id,
  user_id=user_id,
  llm=OpenAIChat(model=llm_id),
- description=dedent("""\
+ description=dedent(
+ """\
  You are a powerful AI Agent called `Optimus Prime v7`.
  You have access to a set of tools and a team of AI Assistants at your disposal.
  Your goal is to assist the user in the best way possible.\
- """),
+ """
+ ),
  instructions=[
  "When the user sends a message, first **think** and determine if:\n"
  " - You can answer by using a tool available to you\n"
@@ -278,9 +284,11 @@ def get_agent(
  # This setting adds the current datetime to the instructions
  add_datetime_to_instructions=True,
  # Add an introductory Assistant message
- introduction=dedent("""\
+ introduction=dedent(
+ """\
  Hi, I'm Optimus Prime v7, your powerful AI Assistant. Send me on my mission boss :statue_of_liberty:\
- """),
+ """
+ ),
  debug_mode=debug_mode,
  )
  return agent

cookbook/assistants/research.py

@@ -19,7 +19,8 @@
  "Read the results carefully and prepare a NYT worthy article.",
  ],
  add_datetime_to_instructions=True,
- expected_output=dedent("""\
+ expected_output=dedent(
+ """\
  An engaging, informative, and well-structured article in the following format:
  <article_format>
  ## Engaging Article Title

cookbook/integrations/singlestore/ai_apps/assistants.py

@@ -176,7 +176,8 @@ def get_research_assistant(
  "Remember: you are writing for the New York Times, so the quality of the report is important.",
  ],
  add_datetime_to_instructions=True,
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ## Title
 
@@ -204,7 +205,8 @@ def get_research_assistant(
  - [Reference 2](Link to Source)
  - Report generated on: {Month Date, Year (hh:mm AM/PM)}
  </report_format>
- """),
+ """
+ ),
  markdown=True,
  debug_mode=debug_mode,
  # -*- Disable memory to save on tokens

cookbook/llm_os/assistant.py

@@ -118,7 +118,8 @@ def get_llm_os(
  "Make your report engaging, informative, and well-structured.",
  "Remember: you are writing for the New York Times, so the quality of the report is important.",
  ],
- expected_output=dedent("""\
+ expected_output=dedent(
+ """\
  An engaging, informative, and well-structured report in the following format:
  <report_format>
  ## Title
@@ -142,7 +143,8 @@ def get_llm_os(
  - [Reference 1](Link to Source)
  - [Reference 2](Link to Source)
  </report_format>
- """),
+ """
+ ),
  tools=[ExaTools(num_results=5, text_length_limit=1000)],
  # This setting tells the LLM to format messages in markdown
  markdown=True,
@@ -167,7 +169,8 @@ def get_llm_os(
  "When you share numbers, make sure to include the units (e.g., millions/billions) and currency.",
  "REMEMBER: This report is for a very important client, so the quality of the report is important.",
  ],
- expected_output=dedent("""\
+ expected_output=dedent(
+ """\
  <report_format>
  ## [Company Name]: Investment Report
 
@@ -203,7 +206,8 @@ def get_llm_os(
  {provide a recommendation on the stock along with a thorough reasoning}
 
  </report_format>
- """),
+ """
+ ),
  tools=[YFinanceTools(stock_price=True, company_info=True, analyst_recommendations=True, company_news=True)],
  # This setting tells the LLM to format messages in markdown
  markdown=True,
@@ -226,11 +230,13 @@ def get_llm_os(
  run_id=run_id,
  user_id=user_id,
  llm=OpenAIChat(model=llm_id),
- description=dedent("""\
+ description=dedent(
+ """\
  You are the most advanced AI system in the world called `LLM-OS`.
  You have access to a set of tools and a team of AI Assistants at your disposal.
  Your goal is to assist the user in the best way possible.\
- """),
+ """
+ ),
  instructions=[
  "When the user sends a message, first **think** and determine if:\n"
  " - You can answer by using a tool available to you\n"
@@ -278,11 +284,13 @@ def get_llm_os(
  # This setting adds the current datetime to the instructions
  add_datetime_to_instructions=True,
  # Add an introductory Assistant message
- introduction=dedent("""\
+ introduction=dedent(
+ """\
  Hi, I'm your LLM OS.
  I have access to a set of tools and AI Assistants to assist you.
  Let's solve some problems together!\
- """),
+ """
+ ),
  debug_mode=debug_mode,
  )
  return llm_os

cookbook/llms/groq/ai_apps/assistants.py

@@ -90,7 +90,8 @@ def get_rag_research_assistant(
  "Remember: you are writing for the New York Times, so the quality of the report is important.",
  ],
  add_datetime_to_instructions=True,
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ## [Title]
 
@@ -119,7 +120,8 @@ def get_rag_research_assistant(
 
  Report generated on: {Month Date, Year (hh:mm AM/PM)}
  </report_format>
- """),
+ """
+ ),
  markdown=True,
  debug_mode=debug_mode,
  )

cookbook/llms/groq/investment_researcher/assistants.py

@@ -22,7 +22,8 @@ def get_invstment_research_assistant(
  ],
  markdown=True,
  add_datetime_to_instructions=True,
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ## [Company Name]: Investment Report
 
@@ -63,6 +64,7 @@ def get_invstment_research_assistant(
 
  Report generated on: {Month Date, Year (hh:mm AM/PM)}
  </report_format>
- """),
+ """
+ ),
  debug_mode=debug_mode,
  )

cookbook/llms/groq/news_articles/assistants.py

@@ -22,7 +22,8 @@ def get_article_summarizer(
  "REMEMBER: you are writing for the New York Times, so the quality of the report is important.",
  "Make sure your report is properly formatted and follows the <report_format> provided below.",
  ],
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  **Overview:**\n
  {overview of the article}
@@ -33,7 +34,8 @@ def get_article_summarizer(
  **Key Takeaways:**\n
  {provide key takeaways from the article}
  </report_format>
- """),
+ """
+ ),
  # This setting tells the LLM to format messages in markdown
  markdown=True,
  add_datetime_to_instructions=True,
@@ -59,7 +61,8 @@ def get_article_writer(
  "Give the section relevant titles and provide details/facts/processes in each section."
  "REMEMBER: you are writing for the New York Times, so the quality of the article is important.",
  ],
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <article_format>
  ## Engaging Article Title
 
@@ -81,7 +84,8 @@ def get_article_writer(
  - [Title](url)
  - [Title](url)
  </article_format>
- """),
+ """
+ ),
  # This setting tells the LLM to format messages in markdown
  markdown=True,
  add_datetime_to_instructions=True,

cookbook/llms/groq/research/assistant.py

@@ -20,7 +20,8 @@ def get_research_assistant(
  "Your report should follow the format provided below."
  "Remember: you are writing for the New York Times, so the quality of the report is important.",
  ],
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ## Title
 
@@ -50,7 +51,8 @@ def get_research_assistant(
  - [Reference 1](Link to Source)
  - [Reference 2](Link to Source)
  </report_format>
- """),
+ """
+ ),
  # This setting tells the LLM to format messages in markdown
  markdown=True,
  add_datetime_to_instructions=True,

cookbook/llms/groq/video_summary/assistant.py

@@ -22,7 +22,8 @@ def get_chunk_summarizer(
  "REMEMBER: you are writing for the New York Times, so the quality of the report is important.",
  "Make sure your report is properly formatted and follows the <report_format> provided below.",
  ],
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ### Overview
  {give an overview of the video}
@@ -35,7 +36,8 @@ def get_chunk_summarizer(
  ### Takeaways
  {provide key takeaways from the video}
  </report_format>
- """),
+ """
+ ),
  # This setting tells the LLM to format messages in markdown
  markdown=True,
  add_datetime_to_instructions=True,
@@ -65,7 +67,8 @@ def get_video_summarizer(
  "Give the section relevant titles and provide details/facts/processes in each section."
  "REMEMBER: you are writing for the New York Times, so the quality of the report is important.",
  ],
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ## Video Title with Link
  {this is the markdown link to the video}
@@ -85,7 +88,8 @@ def get_video_summarizer(
 
  Report generated on: {Month Date, Year (hh:mm AM/PM)}
  </report_format>
- """),
+ """
+ ),
  # This setting tells the LLM to format messages in markdown
  markdown=True,
  add_datetime_to_instructions=True,

cookbook/llms/ollama/tools/assistant.py

@@ -51,9 +51,11 @@ def get_function_calling_assistant(
  debug_mode=debug_mode,
  )
  assistant.add_introduction(
- dedent("""\
+ dedent(
+ """\
  Hi, I'm a local AI Assistant that uses function calling to answer questions.\n
  Select the tools from the sidebar and ask me questions.
- """)
+ """
+ )
  )
  return assistant

cookbook/llms/ollama/video_summary/assistant.py

@@ -20,7 +20,8 @@ def get_chunk_summarizer(
  "REMEMBER: you are writing for the New York Times, so the quality of the report is important.",
  "Make sure your report is properly formatted and follows the <report_format> provided below.",
  ],
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ### Overview
  {give an overview of the video}
@@ -33,7 +34,8 @@ def get_chunk_summarizer(
  ### Takeaways
  {provide key takeaways from the video}
  </report_format>
- """),
+ """
+ ),
  # This setting tells the LLM to format messages in markdown
  markdown=True,
  add_datetime_to_instructions=True,
@@ -61,7 +63,8 @@ def get_video_summarizer(
  "Give the section relevant titles and provide details/facts/processes in each section."
  "REMEMBER: you are writing for the New York Times, so the quality of the report is important.",
  ],
- add_to_system_prompt=dedent("""
+ add_to_system_prompt=dedent(
+ """
  <report_format>
  ## [video_title](video_link)
  {provide a markdown link to the video}
@@ -81,7 +84,8 @@ def get_video_summarizer(
 
  Report generated on: {Month Date, Year (hh:mm AM/PM)}
  </report_format>
- """),
+ """
+ ),
  # This setting tells the LLM to format messages in markdown
  markdown=True,
  add_datetime_to_instructions=True,

cookbook/workflows/news_article.py

@@ -48,7 +48,8 @@ class NewsArticle(BaseModel):
  "Ignore articles that you cannot read or understand.",
  "REMEMBER: you are writing for the New York Times, so the quality of the article is important.",
  ],
- expected_output=dedent("""\
+ expected_output=dedent(
+ """\
  An engaging, informative, and well-structured article in the following format:
  <article_format>
  ## Engaging Article Title
@@ -71,7 +72,8 @@ class NewsArticle(BaseModel):
  - [Title](url)
  - [Title](url)
  </article_format>
- """),
+ """
+ ),
 )
 
 news_article = Workflow(