Merge pull request #281 from MervinPraison/develop

Update praisonaiagents to version 0.0.31 and enhance agent functionality
2026-11-08 08:11:07 -10:00 · 2025-01-11 07:51:59 +00:00 · 2025-01-11 07:51:05 +00:00
11 changed files with 117 additions and 41 deletions
@@ -1,6 +1,6 @@
 FROM python:3.11-slim
 WORKDIR /app
 COPY . .
-RUN pip install flask praisonai==2.0.38 gunicorn markdown
+RUN pip install flask praisonai==2.0.39 gunicorn markdown
 EXPOSE 8080
 CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]
@@ -1,34 +1,62 @@
 from praisonaiagents.agents.agents import Agent, Task, PraisonAIAgents
 from praisonaiagents.tools import duckduckgo

-research_agent = Agent(
-    role="Research Analyst",
-    goal="Research and document key information about topics",
-    backstory="Expert at analyzing and storing information in memory",
-    llm="gpt-4o-mini",
-    tools=[duckduckgo]
-)
+# Test facts
+fact1 = "The capital city of Jujuha is Hahanu and its population is 102300"
+fact2 = "Three main ingredients in a classic proloder are eggs, sugar, and flour"
+fact3 = "The year the first Josinga was released is 2007"

-blog_agent = Agent(
-    role="Blog Writer",
-    goal="Write a blog post about the research",
-    backstory="Expert at writing blog posts",
+fact_agent = Agent(
+    name="Fact Agent",
+    instructions="You are a fact agent, you store and retrieve facts in memory",
    llm="gpt-4o-mini"
 )

+research_agent = Agent(
+    name="Research Agent",
+    instructions="You are a research analyst, you research and document key points about topics",
+    llm="gpt-4o-mini"
+)
+
+blog_agent = Agent(
+    name="Blog Agent",
+    instructions="You are a blog writer, you write a blog post about the research",
+    llm="gpt-4o-mini"
+)
+
+fact_task = Task(
+    description="Store the following facts in memory: " + fact1 + ", " + fact2 + ", " + fact3,
+    agent=fact_agent
+)
+
 research_task = Task(
-    description="Research and document key information about topics",
+    description="Research and document 2 key points about AI",
+    agent=research_agent
+)
+
+research_task2 = Task(
+    description="Research and document 2 key points about AI in healthcare",
+    agent=research_agent
+)
+
+research_task3 = Task(
+    description="Research and document 2 key points about AI in education",
+    agent=research_agent
+)
+
+research_task4 = Task(
+    description="Research and document 2 key points about AI in finance",
    agent=research_agent
 )

 blog_task = Task(
-    description="Write a blog post about the research",
+    description="Write a blog post about Jujuha",
    agent=blog_agent
 )

 agents = PraisonAIAgents(
-    agents=[research_agent, blog_agent],
-    tasks=[research_task, blog_task],
+    agents=[fact_agent, research_agent, blog_agent],
+    tasks=[fact_task, research_task, research_task2, research_task3, research_task4, blog_task],
    memory=True
 )   

@@ -381,7 +381,7 @@ Your Goal: {self.goal}
                    display_generating("", start_time),
                    console=self.console,
                    refresh_per_second=4,
-                    transient=False,  # Changed to False to preserve output
+                    transient=True,  # Changed to False to preserve output
                    vertical_overflow="ellipsis",
                    auto_refresh=True
                ) as live:
@@ -466,7 +466,15 @@ Your Goal: {self.goal}
                        display_text = next((item["text"] for item in prompt if item["type"] == "text"), "")
                    
                    if display_text and str(display_text).strip():
-                        display_instruction(f"Agent {self.name} is processing prompt: {display_text}", console=self.console)
+                        # Pass agent information to display_instruction
+                        agent_tools = [t.__name__ if hasattr(t, '__name__') else str(t) for t in self.tools]
+                        display_instruction(
+                            f"Agent {self.name} is processing prompt: {display_text}", 
+                            console=self.console,
+                            agent_name=self.name,
+                            agent_role=self.role,
+                            agent_tools=agent_tools
+                        )

                response = self._chat_completion(messages, temperature=temperature, tools=tools if tools else None)
                if not response:
@@ -525,7 +533,7 @@ Your Goal: {self.goal}
                    self.chat_history.append({"role": "user", "content": original_prompt})
                    self.chat_history.append({"role": "assistant", "content": response_text})
                    if self.verbose:
-                        logging.info(f"Agent {self.name} final response: {response_text}")
+                        logging.debug(f"Agent {self.name} final response: {response_text}")
                    display_interaction(original_prompt, response_text, markdown=self.markdown, generation_time=time.time() - start_time, console=self.console)
                    return response_text

@@ -630,6 +638,22 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                            item["text"] += "\nReturn ONLY a valid JSON object. No other text or explanation."
                            break

+            # Display instruction with agent info if verbose
+            if self.verbose:
+                display_text = prompt
+                if isinstance(prompt, list):
+                    display_text = next((item["text"] for item in prompt if item["type"] == "text"), "")
+                
+                if display_text and str(display_text).strip():
+                    agent_tools = [t.__name__ if hasattr(t, '__name__') else str(t) for t in self.tools]
+                    await adisplay_instruction(
+                        f"Agent {self.name} is processing prompt: {display_text}",
+                        console=self.console,
+                        agent_name=self.name,
+                        agent_role=self.role,
+                        agent_tools=agent_tools
+                    )
+
            # Format tools if provided
            formatted_tools = []
            if tools:
@@ -116,10 +116,10 @@ def display_interaction(message, response, markdown=True, generation_time=None,
        console.print(Text(f"Response generated in {generation_time:.1f}s", style="dim"))

    if markdown:
-        console.print(Panel.fit(Markdown(message), title="Message", border_style="cyan"))
+        console.print(Panel.fit(Markdown(message), title="Task", border_style="cyan"))
        console.print(Panel.fit(Markdown(response), title="Response", border_style="cyan"))
    else:
-        console.print(Panel.fit(Text(message, style="bold green"), title="Message", border_style="cyan"))
+        console.print(Panel.fit(Text(message, style="bold green"), title="Task", border_style="cyan"))
        console.print(Panel.fit(Text(response, style="bold blue"), title="Response", border_style="cyan"))

 def display_self_reflection(message: str, console=None):
@@ -135,7 +135,7 @@ def display_self_reflection(message: str, console=None):
    
    console.print(Panel.fit(Text(message, style="bold yellow"), title="Self Reflection", border_style="magenta"))

-def display_instruction(message: str, console=None):
+def display_instruction(message: str, console=None, agent_name: str = None, agent_role: str = None, agent_tools: List[str] = None):
    if not message or not message.strip():
        return
    if console is None:
@@ -146,7 +146,19 @@ def display_instruction(message: str, console=None):
    if 'instruction' in sync_display_callbacks:
        sync_display_callbacks['instruction'](message=message)
    
-    console.print(Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))
+    # Display agent info if available
+    if agent_name:
+        agent_info = f"[bold #FF9B9B]👤 Agent:[/] [#FFE5E5]{agent_name}[/]"
+        if agent_role:
+            agent_info += f"\n[bold #B4B4B3]Role:[/] [#FFE5E5]{agent_role}[/]"
+        if agent_tools:
+            tools_str = ", ".join(f"[italic #B4D4FF]{tool}[/]" for tool in agent_tools)
+            agent_info += f"\n[bold #86A789]Tools:[/] {tools_str}"
+        console.print(Panel(agent_info, border_style="#D2E3C8", title="[bold]Agent Info[/]", title_align="left", padding=(1, 2)))
+    
+    # Only print if log level is DEBUG
+    if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
+        console.print(Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))

 def display_tool_call(message: str, console=None):
    if not message or not message.strip():
@@ -222,10 +234,10 @@ async def adisplay_interaction(message, response, markdown=True, generation_time
        console.print(Text(f"Response generated in {generation_time:.1f}s", style="dim"))

    if markdown:
-        console.print(Panel.fit(Markdown(message), title="Message", border_style="cyan"))
+        console.print(Panel.fit(Markdown(message), title="Task", border_style="cyan"))
        console.print(Panel.fit(Markdown(response), title="Response", border_style="cyan"))
    else:
-        console.print(Panel.fit(Text(message, style="bold green"), title="Message", border_style="cyan"))
+        console.print(Panel.fit(Text(message, style="bold green"), title="Task", border_style="cyan"))
        console.print(Panel.fit(Text(response, style="bold blue"), title="Response", border_style="cyan"))

 async def adisplay_self_reflection(message: str, console=None):
@@ -241,7 +253,7 @@ async def adisplay_self_reflection(message: str, console=None):
    
    console.print(Panel.fit(Text(message, style="bold yellow"), title="Self Reflection", border_style="magenta"))

-async def adisplay_instruction(message: str, console=None):
+async def adisplay_instruction(message: str, console=None, agent_name: str = None, agent_role: str = None, agent_tools: List[str] = None):
    """Async version of display_instruction."""
    if not message or not message.strip():
        return
@@ -252,7 +264,19 @@ async def adisplay_instruction(message: str, console=None):
    if 'instruction' in async_display_callbacks:
        await async_display_callbacks['instruction'](message=message)
    
-    console.print(Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))
+    # Display agent info if available
+    if agent_name:
+        agent_info = f"[bold #FF9B9B]👤 Agent:[/] [#FFE5E5]{agent_name}[/]"
+        if agent_role:
+            agent_info += f"\n[bold #B4B4B3]Role:[/] [#FFE5E5]{agent_role}[/]"
+        if agent_tools:
+            tools_str = ", ".join(f"[italic #B4D4FF]{tool}[/]" for tool in agent_tools)
+            agent_info += f"\n[bold #86A789]Tools:[/] {tools_str}"
+        console.print(Panel(agent_info, border_style="#D2E3C8", title="[bold]Agent Info[/]", title_align="left", padding=(1, 2)))
+    
+    # Only print if log level is DEBUG
+    if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
+        console.print(Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))

 async def adisplay_tool_call(message: str, console=None):
    """Async version of display_tool_call."""
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"

 [project]
 name = "praisonaiagents"
-version = "0.0.30"
+version = "0.0.31"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 authors = [
    { name="Mervin Praison" }
@@ -990,7 +990,7 @@ wheels = [

 [[package]]
 name = "praisonaiagents"
-version = "0.0.30"
+version = "0.0.31"
 source = { editable = "." }
 dependencies = [
    { name = "openai" },
@@ -110,7 +110,7 @@ Loads environment variables from .env file or system and sets them.</p>
            file.write(&#34;FROM python:3.11-slim\n&#34;)
            file.write(&#34;WORKDIR /app\n&#34;)
            file.write(&#34;COPY . .\n&#34;)
-            file.write(&#34;RUN pip install flask praisonai==2.0.38 gunicorn markdown\n&#34;)
+            file.write(&#34;RUN pip install flask praisonai==2.0.39 gunicorn markdown\n&#34;)
            file.write(&#34;EXPOSE 8080\n&#34;)
            file.write(&#39;CMD [&#34;gunicorn&#34;, &#34;-b&#34;, &#34;0.0.0.0:8080&#34;, &#34;api:app&#34;]\n&#39;)
            
@@ -3,7 +3,7 @@ class Praisonai < Formula
  
    desc "AI tools for various AI applications"
    homepage "https://github.com/MervinPraison/PraisonAI"
-    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/2.0.38.tar.gz"
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/2.0.39.tar.gz"
    sha256 "1828fb9227d10f991522c3f24f061943a254b667196b40b1a3e4a54a8d30ce32"  # Replace with actual SHA256 checksum
    license "MIT"
  
@@ -56,7 +56,7 @@ class CloudDeployer:
            file.write("FROM python:3.11-slim\n")
            file.write("WORKDIR /app\n")
            file.write("COPY . .\n")
-            file.write("RUN pip install flask praisonai==2.0.38 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.0.39 gunicorn markdown\n")
            file.write("EXPOSE 8080\n")
            file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
            
@@ -1,6 +1,6 @@
 [project]
 name = "PraisonAI"
-version = "2.0.38"
+version = "2.0.39"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human–agent collaboration."
 readme = "README.md"
 license = ""
@@ -12,7 +12,7 @@ dependencies = [
    "rich>=13.7",
    "markdown>=3.5",
    "pyparsing>=3.0.0",
-    "praisonaiagents>=0.0.30",
+    "praisonaiagents>=0.0.31",
    "python-dotenv>=0.19.0",
    "instructor>=1.3.3",
    "PyYAML>=6.0",
@@ -84,7 +84,7 @@ autogen = ["pyautogen>=0.2.19", "praisonai-tools>=0.0.7", "crewai"]

 [tool.poetry]
 name = "PraisonAI"
-version = "2.0.38"
+version = "2.0.39"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human–agent collaboration."
 authors = ["Mervin Praison"]
 license = ""
@@ -102,7 +102,7 @@ python = ">=3.10,<3.13"
 rich = ">=13.7"
 markdown = ">=3.5"
 pyparsing = ">=3.0.0"
-praisonaiagents = ">=0.0.30"
+praisonaiagents = ">=0.0.31"
 python-dotenv = ">=0.19.0"
 instructor = ">=1.3.3"
 PyYAML = ">=6.0"
@@ -3060,7 +3060,7 @@ wheels = [

 [[package]]
 name = "praisonai"
-version = "2.0.38"
+version = "2.0.39"
 source = { editable = "." }
 dependencies = [
    { name = "instructor" },
@@ -3197,7 +3197,7 @@ requires-dist = [
    { name = "plotly", marker = "extra == 'realtime'", specifier = ">=5.24.0" },
    { name = "praisonai-tools", marker = "extra == 'autogen'", specifier = ">=0.0.7" },
    { name = "praisonai-tools", marker = "extra == 'crewai'", specifier = ">=0.0.7" },
-    { name = "praisonaiagents", specifier = ">=0.0.30" },
+    { name = "praisonaiagents", specifier = ">=0.0.31" },
    { name = "pyautogen", marker = "extra == 'autogen'", specifier = ">=0.2.19" },
    { name = "pydantic", marker = "extra == 'chat'", specifier = "<=2.10.1" },
    { name = "pydantic", marker = "extra == 'code'", specifier = "<=2.10.1" },
@@ -3250,16 +3250,16 @@ wheels = [

 [[package]]
 name = "praisonaiagents"
-version = "0.0.30"
+version = "0.0.31"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "openai" },
    { name = "pydantic" },
    { name = "rich" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/21/d2/0974b47b7e38052facc68538c3d616569185588f5bc28f44fa02a960ea19/praisonaiagents-0.0.30.tar.gz", hash = "sha256:28997d411da9a0c0a912f1be5f2cde84d9a40d302efdec09040f447344b9ba53", size = 68012 }
+sdist = { url = "https://files.pythonhosted.org/packages/e6/33/3dbf92fd64ee405b9382e79f688cef390ff9164d72ead030f4246fb9d2d1/praisonaiagents-0.0.31.tar.gz", hash = "sha256:9c372c51c741a0365c1186b087b3a72f4371e6ae2c203fa072b7a89a400e2560", size = 68508 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/b5/ce/a3c6f27a14db93ffcf4c079a718b190fd46fb5dc9cf7e6755f356ac921ce/praisonaiagents-0.0.30-py3-none-any.whl", hash = "sha256:d19ab553026bee839a311f554d78fdcecdb670bae6014e3dbde91914817fb7ac", size = 84981 },
+    { url = "https://files.pythonhosted.org/packages/91/7e/6eea88722770bd5f2691d8a0669cc46746961db969ea58d1380ce9e31648/praisonaiagents-0.0.31-py3-none-any.whl", hash = "sha256:41445ca9ab38d26f01df0873837bf8436e7013020474808312eff06894f2ce8e", size = 85455 },
 ]

 [[package]]