base openai_assistant

docs/mkdocs.yml

@@ -1,8 +1,8 @@
 docs_dir: '.'  # replace with the correct path if your documentation files are not in the same directory as mkdocs.yml
 site_name: Swarms
 site_url: https://docs.swarms.world
 site_author: Swarms
 site_description: The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework
 repo_name: kyegomez/swarms
 repo_url: https://github.com/kyegomez/swarms
 edit_uri: https://github.com/kyegomez/swarms/tree/main/docs
@@ -13,9 +13,9 @@
   - search
   - git-authors
   - mkdocs-jupyter:
         kernel_name: python3
         execute: false
         include_source: True
         include_requirejs: true
   - mkdocstrings:
       default_handler: python
@@ -137,10 +137,10 @@
   - pymdownx.tilde
 nav:
   - Home:
     - Overview: "index.md"
     # - The Vision: "swarms/framework/vision.md"
     # - Docker Setup: "swarms/install/docker_setup.md"
     - Our Goal; The Ultimate Multi-Agent LLM Framework for Developers: "swarms/concept/vision.md"
     - Swarm Ecosystem: "swarms/concept/swarm_ecosystem.md"
     - Onboarding: 
       - Installation: "swarms/install/install.md"
@@ -149,7 +149,7 @@
       - Swarms CLI: "swarms/cli/main.md"
       # - Swarms + Docker: 
       - Swarms Framework Architecture: "swarms/concept/framework_architecture.md"
     # - Prelimary:
       # - 80/20 Rule For Agents: "swarms/prompting/8020.md"
       - Managing Prompts in Production: "swarms/prompts/main.md"
     - Agents:
@@ -157,6 +157,7 @@
       # - Build Custom Agents: "swarms/structs/diy_your_own_agent.md"
       - Agent Architecture: "swarms/framework/agents_explained.md"
       - Complete Agent API: "swarms/structs/agent.md"
+      - OpenAI Assistant: "swarms/agents/openai_assistant.md"
       - Create and Run Agents from YAML: "swarms/agents/create_agents_yaml.md"
       - Integrating External Agents from Griptape, Langchain, etc: "swarms/agents/external_party_agents.md"
       - Tools:
@@ -250,7 +251,7 @@
       - Edit Agents: "swarms_platform/agents/edit_agent.md"
     - Telemetry API:
       - PUT: "swarms_platform/telemetry/index.md"
     # - Tools API:
     #   - Overview: "swarms_platform/tools_api.md"
     #   - Add Tools: "swarms_platform/fetch_tools.md"
   - Guides:

docs/swarms/agents/openai_assistant.md

@@ -0,0 +1,135 @@
+# OpenAI Assistant
+
+The OpenAI Assistant class provides a wrapper around OpenAI's Assistants API, integrating it with the swarms framework.
+
+## Overview
+
+The `OpenAIAssistant` class allows you to create and interact with OpenAI Assistants, providing a simple interface for:
+
+- Creating assistants with specific roles and capabilities
+- Adding custom functions that the assistant can call
+- Managing conversation threads
+- Handling tool calls and function execution
+- Getting responses from the assistant
+
+## Insstallation
+
+```bash
+pip install swarms
+```
+## Basic Usage
+
+```python
+
+from swarms import OpenAIAssistant
+
+#Create an assistant
+assistant = OpenAIAssistant(
+    name="Math Tutor",
+    instructions="You are a helpful math tutor.",
+    model="gpt-4o",
+    tools=[{"type": "code_interpreter"}]
+)
+
+#Run a Task
+response = assistant.run("Solve the equation: 3x + 11 = 14")
+print(response)
+
+# Continue the conversation in the same thread
+follow_up = assistant.run("Now explain how you solved it")
+print(follow_up)
+```
+
+## Function Calling
+
+The assistant supports custom function integration:
+
+```python
+
+def get_weather(location: str, unit: str = "celsius") -> str:
+    # Mock weather function
+    return f"The weather in {location} is 22 degrees {unit}"
+
+# Add function to assistant
+assistant.add_function(
+    description="Get the current weather in a location",
+    parameters={
+        "type": "object",
+        "properties": {
+            "location": {
+                "type": "string",
+                "description": "City name"
+            },
+            "unit": {
+                "type": "string",
+                "enum": ["celsius", "fahrenheit"],
+                "default": "celsius"
+            }
+        },
+        "required": ["location"]
+    }
+)
+```
+
+## API Reference
+
+### Constructor
+
+```python
+OpenAIAssistant(
+    name: str,
+    instructions: Optional[str] = None,
+    model: str = "gpt-4o",
+    tools: Optional[List[Dict[str, Any]]] = None,
+    file_ids: Optional[List[str]] = None,
+    metadata: Optional[Dict[str, Any]] = None,
+    functions: Optional[List[Dict[str, Any]]] = None,
+)
+```
+
+### Methods
+
+#### run(task: str) -> str
+Sends a task to the assistant and returns its response. The conversation thread is maintained between calls.
+
+#### add_function(func: Callable, description: str, parameters: Dict[str, Any]) -> None
+Adds a callable function that the assistant can use during conversations.
+
+#### add_message(content: str, file_ids: Optional[List[str]] = None) -> None
+Adds a message to the current conversation thread.
+
+## Error Handling
+
+The assistant implements robust error handling:
+- Retries on rate limits
+- Graceful handling of API errors
+- Clear error messages for debugging
+- Status monitoring for runs and completions
+
+## Best Practices
+
+1. Thread Management
+   - Use the same assistant instance for related conversations
+   - Create new instances for unrelated tasks
+   - Monitor thread status during long-running operations
+
+2. Function Integration
+   - Keep functions simple and focused
+   - Provide clear descriptions and parameter schemas
+   - Handle errors gracefully in custom functions
+   - Test functions independently before integration
+
+3. Performance
+   - Reuse assistant instances when possible
+   - Monitor and handle rate limits appropriately
+   - Use appropriate polling intervals for status checks
+   - Consider implementing timeouts for long-running operations
+
+## References
+
+- [OpenAI Assistants API Documentation](https://platform.openai.com/docs/assistants/overview)
+- [OpenAI Function Calling Guide](https://platform.openai.com/docs/guides/function-calling)
+- [OpenAI Rate Limits](https://platform.openai.com/docs/guides/rate-limits)
+
+
+

docs/swarms/structs/async_workflow.md

@@ -203,4 +203,64 @@ await workflow.add(tasks=[task_1, task_2])
 # Running the workflow
 results = await workflow.run()
 print(results)  # Output: ["Task 1 Completed", "Task 2 Completed"]
-```
+```
+
+# Async Workflow
+
+The AsyncWorkflow allows multiple agents to process tasks concurrently using Python's asyncio framework.
+
+## Usage Example
+
+```python
+import asyncio
+from swarms import Agent, AsyncWorkflow
+from swarm_models import OpenAIChat
+
+# Initialize model
+model = OpenAIChat(
+    openai_api_key="your-api-key",
+    model_name="gpt-4",
+    temperature=0.7
+)
+
+# Create agents
+agents = [
+    Agent(
+        agent_name=f"Analysis-Agent-{i}",
+        llm=model,
+        max_loops=1,
+        dashboard=False,
+        verbose=True,
+    )
+    for i in range(3)
+]
+
+# Initialize workflow
+workflow = AsyncWorkflow(
+    name="Analysis-Workflow",
+    agents=agents,
+    max_workers=3,
+    verbose=True
+)
+
+# Run workflow
+async def main():
+    task = "Analyze the potential impact of AI on healthcare"
+    results = await workflow.run(task)
+    for i, result in enumerate(results):
+        print(f"Agent {i} result: {result}")
+
+# Execute
+asyncio.run(main())
+```
+
+## Parameters
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `name` | str | "AsyncWorkflow" | Name of the workflow |
+| `agents` | List[Agent] | None | List of agents to execute tasks |
+| `max_workers` | int | 5 | Maximum number of concurrent workers |
+| `dashboard` | bool | False | Enable/disable dashboard |
+| `autosave` | bool | False | Enable/disable autosaving results |
+| `verbose` | bool | False | Enable/disable verbose logging |