Update PraisonAI to version 2.0.42 and praisonaiagents to version 0.0.32

- Updated the PraisonAI package version from 2.0.41 to 2.0.42 in Dockerfile, pyproject.toml, and related files. - Adjusted installation command in Dockerfile and deploy scripts to reflect the new version. - Updated the praisonaiagents package version from 0.0.31 to 0.0.32 in relevant files. - Enhanced the prompt chaining implementation in agents/prompt_chaining.py for improved task management and workflow execution. - Added new documentation on agentic prompt chaining to guide users in creating complex workflows. - Updated dependencies in uv.lock for compatibility with the new versions.
MervinPraison · Jan 12, 2025 · 0a4e476 · 0a4e476
1 parent 315ac71
commit 0a4e476
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diff --git a/Dockerfile b/Dockerfile
@@ -1,6 +1,6 @@
 FROM python:3.11-slim
 WORKDIR /app
 COPY . .
-RUN pip install flask praisonai==2.0.41 gunicorn markdown
+RUN pip install flask praisonai==2.0.42 gunicorn markdown
 EXPOSE 8080
 CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]
diff --git a/agents/praisonaiagents/process/process.py b/agents/praisonaiagents/process/process.py
@@ -130,22 +130,28 @@ async def aworkflow(self) -> AsyncGenerator[str, None]:
 
             # Determine next task based on result
             next_task = None
-            if current_task.result:
+            if current_task and current_task.result:
                 if current_task.task_type in ["decision", "loop"]:
                     result = current_task.result.raw.lower()
                     # Check conditions
                     for condition, tasks in current_task.condition.items():
-                        if condition.lower() in result and tasks:
-                            next_task_name = tasks[0]
+                        if condition.lower() in result:
+                            # Handle both list and direct string values
+                            task_value = tasks[0] if isinstance(tasks, list) else tasks
+                            if not task_value or task_value == "exit":  # If empty or explicit exit
+                                logging.info("Workflow exit condition met, ending workflow")
+                                current_task = None
+                                break
+                            next_task_name = task_value
                             next_task = next((t for t in self.tasks.values() if t.name == next_task_name), None)
                             # For loops, allow revisiting the same task
                             if next_task and next_task.id == current_task.id:
                                 visited_tasks.discard(current_task.id)
                             break
 
-                if not next_task and current_task.next_tasks:
-                    next_task_name = current_task.next_tasks[0]
-                    next_task = next((t for t in self.tasks.values() if t.name == next_task_name), None)
+            if not next_task and current_task and current_task.next_tasks:
+                next_task_name = current_task.next_tasks[0]
+                next_task = next((t for t in self.tasks.values() if t.name == next_task_name), None)
 
             current_task = next_task
             if not current_task:
@@ -391,22 +397,28 @@ def workflow(self):
 
             # Determine next task based on result
             next_task = None
-            if current_task.result:
+            if current_task and current_task.result:
                 if current_task.task_type in ["decision", "loop"]:
                     result = current_task.result.raw.lower()
                     # Check conditions
                     for condition, tasks in current_task.condition.items():
-                        if condition.lower() in result and tasks:
-                            next_task_name = tasks[0]
+                        if condition.lower() in result:
+                            # Handle both list and direct string values
+                            task_value = tasks[0] if isinstance(tasks, list) else tasks
+                            if not task_value or task_value == "exit":  # If empty or explicit exit
+                                logging.info("Workflow exit condition met, ending workflow")
+                                current_task = None
+                                break
+                            next_task_name = task_value
                             next_task = next((t for t in self.tasks.values() if t.name == next_task_name), None)
                             # For loops, allow revisiting the same task
                             if next_task and next_task.id == current_task.id:
                                 visited_tasks.discard(current_task.id)
                             break
 
-                if not next_task and current_task.next_tasks:
-                    next_task_name = current_task.next_tasks[0]
-                    next_task = next((t for t in self.tasks.values() if t.name == next_task_name), None)
+            if not next_task and current_task and current_task.next_tasks:
+                next_task_name = current_task.next_tasks[0]
+                next_task = next((t for t in self.tasks.values() if t.name == next_task_name), None)
 
             current_task = next_task
             if not current_task:

diff --git a/agents/prompt_chaining.py b/agents/prompt_chaining.py
@@ -10,82 +10,72 @@ def get_time_check():
     print(f"Time check: {current_time} is {result}")
     return result
 
-def create_prompt_chain():
-    # Create agents for each step in the chain
-    agent1 = Agent(
-        name="Time Checker",
-        role="Time checker",
-        goal="Check if the time is even or odd",
-        instructions="Check if the time is even or odd",
-        tools=[get_time_check]
-    )
+# Create agents for each step in the chain
+agent1 = Agent(
+    name="Time Checker",
+    role="Time checker",
+    goal="Check if the time is even or odd",
+    instructions="Check if the time is even or odd",
+    tools=[get_time_check]
+)
 
-    agent2 = Agent(
-        name="Advanced Analyzer",
-        role="Advanced data analyzer",
-        goal="Perform in-depth analysis of processed data",
-        instructions="Analyze the processed data in detail"
-    )
+agent2 = Agent(
+    name="Advanced Analyzer",
+    role="Advanced data analyzer",
+    goal="Perform in-depth analysis of processed data",
+    instructions="Analyze the processed data in detail"
+)
 
-    agent3 = Agent(
-        name="Final Processor",
-        role="Final data processor",
-        goal="Generate final output based on analysis",
-        instructions="Create final output based on analyzed data"
-    )
+agent3 = Agent(
+    name="Final Processor",
+    role="Final data processor",
+    goal="Generate final output based on analysis",
+    instructions="Create final output based on analyzed data"
+)
 
-    # Create tasks for each step
-    initial_task = Task(
-        name="time_check",
-        description="Getting time check and checking if it is even or odd",
-        expected_output="Getting time check and checking if it is even or odd",
-        agent=agent1,
-        is_start=True,  # Mark as the starting task
-        task_type="decision",  # This task will make a decision
-        next_tasks=["advanced_analysis"],  # Next task if condition passes
-        condition={
-            "even": ["advanced_analysis"],  # If passes, go to advanced analysis
-            "odd": ["final_processing"]  # If fails, exit the chain
-        }
-    )
+# Create tasks for each step
+initial_task = Task(
+    name="time_check",
+    description="Getting time check and checking if it is even or odd",
+    expected_output="Getting time check and checking if it is even or odd",
+    agent=agent1,
+    is_start=True,  # Mark as the starting task
+    task_type="decision",  # This task will make a decision
+    next_tasks=["advanced_analysis"],  # Next task if condition passes
+    condition={
+        "even": ["advanced_analysis"],  # If passes, go to advanced analysis
+        "odd": ""  # If fails, exit the chain
+    }
+)
 
-    analysis_task = Task(
-        name="advanced_analysis",
-        description="Perform advanced analysis on the processed data",
-        expected_output="Analyzed data ready for final processing",
-        agent=agent2,
-        next_tasks=["final_processing"]
-    )
+analysis_task = Task(
+    name="advanced_analysis",
+    description="Perform advanced analysis on the processed data",
+    expected_output="Analyzed data ready for final processing",
+    agent=agent2,
+    next_tasks=["final_processing"]
+)
 
-    final_task = Task(
-        name="final_processing",
-        description="Generate final output",
-        expected_output="Final processed result",
-        agent=agent3
-    )
+final_task = Task(
+    name="final_processing",
+    description="Generate final output",
+    expected_output="Final processed result",
+    agent=agent3
+)
 
-    # Create the workflow manager
-    workflow = PraisonAIAgents(
-        agents=[agent1, agent2, agent3],
-        tasks=[initial_task, analysis_task, final_task],
-        process="workflow",  # Use workflow process type
-        verbose=True
-    )
+# Create the workflow manager
+workflow = PraisonAIAgents(
+    agents=[agent1, agent2, agent3],
+    tasks=[initial_task, analysis_task, final_task],
+    process="workflow",  # Use workflow process type
+    verbose=True
+)
 
-    return workflow
+# Run the workflow
+results = workflow.start()
 
-def main():
-    # Create and run the prompt chain
-    workflow = create_prompt_chain()
-
-    # Run the workflow
-    results = workflow.start()
-
-    # Print results
-    print("\nWorkflow Results:")
-    for task_id, result in results["task_results"].items():
-        if result:
-            print(f"Task {task_id}: {result.raw}")
-
-if __name__ == "__main__":
-    main()
+# Print results
+print("\nWorkflow Results:")
+for task_id, result in results["task_results"].items():
+    if result:
+        print(f"Task {task_id}: {result.raw}")
diff --git a/agents/pyproject.toml b/agents/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "0.0.31"
+version = "0.0.32"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 authors = [
     { name="Mervin Praison" }

diff --git a/agents/uv.lock b/agents/uv.lock
diff --git a/cookbooks/general/prompt_chaining.py b/cookbooks/general/prompt_chaining.py
@@ -0,0 +1,81 @@
+from praisonaiagents.agent import Agent
+from praisonaiagents.task import Task
+from praisonaiagents.agents import PraisonAIAgents
+from typing import List, Dict
+import time
+
+def get_time_check():
+    current_time = int(time.time())
+    result = "even" if current_time % 2 == 0 else "odd"
+    print(f"Time check: {current_time} is {result}")
+    return result
+
+# Create agents for each step in the chain
+agent1 = Agent(
+    name="Time Checker",
+    role="Time checker",
+    goal="Check if the time is even or odd",
+    instructions="Check if the time is even or odd",
+    tools=[get_time_check]
+)
+
+agent2 = Agent(
+    name="Advanced Analyzer",
+    role="Advanced data analyzer",
+    goal="Perform in-depth analysis of processed data",
+    instructions="Analyze the processed data in detail"
+)
+
+agent3 = Agent(
+    name="Final Processor",
+    role="Final data processor",
+    goal="Generate final output based on analysis",
+    instructions="Create final output based on analyzed data"
+)
+
+# Create tasks for each step
+initial_task = Task(
+    name="time_check",
+    description="Getting time check and checking if it is even or odd",
+    expected_output="Getting time check and checking if it is even or odd",
+    agent=agent1,
+    is_start=True,  # Mark as the starting task
+    task_type="decision",  # This task will make a decision
+    next_tasks=["advanced_analysis"],  # Next task if condition passes
+    condition={
+        "even": ["advanced_analysis"],  # If passes, go to advanced analysis
+        "odd": ""  # If fails, exit the chain
+    }
+)
+
+analysis_task = Task(
+    name="advanced_analysis",
+    description="Perform advanced analysis on the processed data",
+    expected_output="Analyzed data ready for final processing",
+    agent=agent2,
+    next_tasks=["final_processing"]
+)
+
+final_task = Task(
+    name="final_processing",
+    description="Generate final output",
+    expected_output="Final processed result",
+    agent=agent3
+)
+
+# Create the workflow manager
+workflow = PraisonAIAgents(
+    agents=[agent1, agent2, agent3],
+    tasks=[initial_task, analysis_task, final_task],
+    process="workflow",  # Use workflow process type
+    verbose=True
+)
+
+# Run the workflow
+results = workflow.start()
+
+# Print results
+print("\nWorkflow Results:")
+for task_id, result in results["task_results"].items():
+    if result:
+        print(f"Task {task_id}: {result.raw}")
diff --git a/docs/api/praisonai/deploy.html b/docs/api/praisonai/deploy.html
@@ -110,7 +110,7 @@ <h2 id="raises">Raises</h2>
             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==2.0.41 gunicorn markdown\n&#34;)
+            file.write(&#34;RUN pip install flask praisonai==2.0.42 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;)