Build Powerful AI Workflows: Together AI + Klavis for Salesforce & Gmail Integration

pip install together klavis

import os
import json
import webbrowser
from together import Together
from klavis import Klavis
from klavis.types import McpServerName, ToolFormat

# Set your API keys
os.environ["TOGETHER_API_KEY"] = "YOUR_TOGETHER_API_KEY"
os.environ["KLAVIS_API_KEY"] = "YOUR_KLAVIS_API_KEY"

# Initialize clients
together_client = Together(api_key=os.getenv("TOGETHER_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))

# Create Salesforce MCP Server instance
salesforce_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.SALESFORCE,
    user_id="1234", 
    platform_name="TogetherAI" 
)

# Open OAuth URL for Salesforce authorization
webbrowser.open(salesforce_mcp_instance.oauth_url)
print(f"🔐 Opening OAuth authorization for Salesforce...")

# Create Gmail MCP Server instance
gmail_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.GMAIL,
    user_id="1234",
    platform_name="TogetherAI"
)

# Open OAuth URL for Gmail authorization
webbrowser.open(gmail_mcp_instance.oauth_url)
print(f"🔐 Opening OAuth authorization for Gmail...")

class Workflow:
    def __init__(self, together_client, klavis_client, mcp_server_urls, model="meta-llama/Llama-3.3-70B-Instruct-Turbo"):
        self.together = together_client
        self.klavis = klavis_client
        self.mcp_server_urls = mcp_server_urls
        self.model = model
    
    def process_request(self, user_message):
        # 1. Get available tools from all MCP servers
        all_tools = []
        tool_to_server = {}  # Maps tool names to their server URLs
        
        for server_url in self.mcp_server_urls:
            mcp_tools = self.klavis.mcp_server.list_tools(
                server_url=server_url,
                format=ToolFormat.OPENAI,
            )
            all_tools.extend(mcp_tools.tools)
            
            for tool in mcp_tools.tools:
                tool_to_server[tool["function"]["name"]] = server_url
        
        # 2. Initialize conversation with the AI
        messages = [
            {"role": "system", "content": "You are a helpful AI assistant with access to tools. Complete requested tasks step by step with the tools available. When all tasks are completed, end your response with 'Done'."},
            {"role": "user", "content": user_message}
        ]
        
        max_iterations = 10 
        iteration = 0
        
        # 3. Execute the workflow
        while iteration < max_iterations:
            iteration += 1
            
            # Call Together AI with all available tools
            response = self.together.chat.completions.create(
                model=self.model,
                messages=messages,
                tools=all_tools
            )
            
            assistant_message = response.choices[0].message
            messages.append(assistant_message)
                        
            # Handle tool calls
            if assistant_message.tool_calls:
                for tool_call in assistant_message.tool_calls:
                    tool_name = tool_call.function.name
                    tool_args = json.loads(tool_call.function.arguments)
                    
                    print(f"🛠️ Calling tool: {tool_name} with args: {tool_args}")
                    
                    # Execute the tool on the correct server
                    if tool_name in tool_to_server:
                        server_url = tool_to_server[tool_name]
                        
                        try:
                            tool_result = self.klavis.mcp_server.call_tools(
                                server_url=server_url,
                                tool_name=tool_name,
                                tool_args=tool_args,
                            )
                            print(f"✅ Tool {tool_name} executed successfully")
                        except Exception as e:
                            tool_result = f"Error executing tool {tool_name}: {str(e)}"
                            print(f"❌ Tool {tool_name} failed: {str(e)}")
                    
                    messages.append({
                        "role": "tool",
                        "tool_call_id": tool_call.id,
                        "content": str(tool_result)
                    })
                
                continue
            
            else:
                # Check if task is complete
                content = assistant_message.content or ""
                if "done" in content.lower():
                    print(f"✅ Task completed in {iteration} iterations")
                    return assistant_message.content
        
        return assistant_message.content

# Create the workflow instance
workflow = Workflow(
    together_client=together_client,
    klavis_client=klavis_client,
    mcp_server_urls=[salesforce_mcp_instance.server_url, gmail_mcp_instance.server_url],
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo"
)

# Execute a complex multi-step request
response = workflow.process_request("""
    1. List my Salesforce opportunities
    2. Update the Together AI opportunity's next step to "Meeting scheduled for 07/31/2025"
    3. Draft a professional follow-up email in Gmail for this next step
""")

print(response)

🛠️ Calling tool: salesforce_get_opportunities with args: {'fields': [], 'limit': 50}
✅ Tool salesforce_get_opportunities executed successfully
🛠️ Calling tool: salesforce_update_opportunity with args: {'next_step': 'Meeting schedule on 07/31/2025', 'opportunity_id': '006fJ0000080dpaQAA'}
✅ Tool salesforce_update_opportunity executed successfully
🛠️ Calling tool: gmail_draft_email with args: {'body': 'Next step: Meeting schedule on 07/31/2025', 'subject': 'Follow-up on Together AI Opportunity', 'to': ['together.ai@example.com']}
✅ Tool gmail_draft_email executed successfully
✅ Task completed in 6 iterations

A follow-up email for the next step has been drafted in your Gmail account with the subject "Follow-up on Together AI Opportunity" and the body "Next step: Meeting schedule on 07/31/2025".

Done