gram-ai 0.3.2
Python Client SDK Generated by Speakeasy.
Requires Python: >=3.9

# gram-ai

Developer-friendly Python SDK to interact with Gram toolsets. 
Gram allows you to use your agentic tools in a variety of different frameworks and protocols. 
Gram tools can be used with pretty much any model that supports function calling via a chat completions or responses style API.

## SDK Installation

> [!NOTE]
> **Python version upgrade policy**
>
> Once a Python version reaches its [official end of life date](https://devguide.python.org/versions/), a 3-month grace period is provided for users to upgrade. Following this grace period, the minimum python version supported in the SDK will be updated.

The SDK can be installed with either *pip* or *poetry* package managers.

### PIP

*PIP* is the default package installer for Python, enabling easy installation and management of packages from PyPI via the command line.

```bash
pip install gram-ai
```

### Poetry

*Poetry* is a modern tool that simplifies dependency management and package publishing by using a single `pyproject.toml` file to handle project metadata and dependencies.

```bash
poetry add gram-ai
```

## OpenAI Agents SDK

```python
import asyncio
import os
from agents import Agent, Runner, set_default_openai_key
from gram_ai.openai_agents import GramOpenAIAgents

key = os.getenv("GRAM_API_KEY")

gram = GramOpenAIAgents(
    api_key=key,
)

set_default_openai_key(os.getenv("OPENAI_API_KEY"))

agent = Agent(
    name="Assistant",
    tools=gram.tools(
        project="default",
        toolset="default",
        environment="default",
    ),
)


async def main():
    result = await Runner.run(
        agent,
        "Can you tell me what tools you have available?",
    )
    print(result.final_output)


if __name__ == "__main__":
    asyncio.run(main()) 
```

## LangChain

```python
import asyncio
import os
from langchain import hub
from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor, create_openai_functions_agent
from gram_ai.langchain import GramLangchain

key = os.getenv("GRAM_API_KEY")

gram = GramLangchain(api_key=key)

llm = ChatOpenAI(
    model="gpt-4",
    temperature=0,
    openai_api_key=os.getenv("OPENAI_API_KEY")
)

tools = gram.tools(
    project="default",
    toolset="default",
    environment="default",
)

prompt = hub.pull("hwchase17/openai-functions-agent")

agent = create_openai_functions_agent(llm=llm, tools=tools, prompt=prompt)

agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=False)

async def main():
    response = await agent_executor.ainvoke({
        "input": "Can you tell me what tools you have available?"
    })
    print(response)

if __name__ == "__main__":
    asyncio.run(main())
```

## OpenAI Function Calling

```python
import os
from openai import OpenAI
from gram_ai.openai import OpenAIAdapter

key = os.getenv("GRAM_API_KEY")

gram = OpenAIAdapter(api_key=key)
openai_client = OpenAI(api_key=openai_api_key)
openai_tools = gram.tools(project="default", toolset="gtm", environment="default")

response = openai_client.chat.completions.create(
    model="gpt-4o",
    prompt: "Can you tell me what tools you have available?"
    tools=openai_tools_data.tools,
    tool_choice="auto",
)
```

## Vanilla Function Calling

```python
import os
from gram_ai.function_calling import GramFunctionCalling

key = os.getenv("GRAM_API_KEY")

# vanilla client that matches the function calling interface for direct use with model provider APIs
gram = GramFunctionCalling(api_key=key)

tools = gram.tools(
    project="default",
    toolset="default",
    environment="default",
)

# exposes name, description, parameters, and an execute and aexecute (async) function
print(tools[0].name)
print(tools[0].description)
print(tools[0].parameters)
print(tools[0].execute)
print(tools[0].aexecute)
```

## Passing in User Defined Environment Variables

If preferred, it's possible to pass in user defined environment variables into tools calls rather than using hosted gram environments.

```python
import asyncio
import os
from agents import Agent, Runner, set_default_openai_key
from gram_ai.openai_agents import GramOpenAIAgents

key = os.getenv("GRAM_API_KEY")

gram = GramOpenAIAgents(
    api_key=key,
    environment_variables= {
        "MY_TOOL_TOKEN": "VALUE"
    }
)

set_default_openai_key(os.getenv("OPENAI_API_KEY"))

agent = Agent(
    name="Assistant",
    tools=gram.tools(
        project="default",
        toolset="default",
    ),
)


async def main():
    result = await Runner.run(
        agent,
        "Can you tell me what tools you have available?",
    )
    print(result.final_output)


if __name__ == "__main__":
    asyncio.run(main()) 
```

## MCP

Gram also instantly allows you to expose and use any toolset as a hosted MCP server.

```json
{
    "mcpServers": {
      "GramTest": {
        "command": "npx",
        "args": [
          "mcp-remote",
          "https://app.getgram.ai/mcp/default/default/default",
          "--allow-http",
          "--header",
          "Authorization:${GRAM_KEY}"
        ],
        "env": {
          "GRAM_KEY": "Bearer <your-key-here>"
        }
      }
    }
  }
```

You also have the option to add a unique slug to these servers and make them publicly available to pass your own credentials.

```json
{
    "mcpServers": {
      "GramSlack": {
        "command": "npx",
        "args": [
          "mcp-remote",
          "https://app.getgram.ai/mcp/speakeasy-team-default",
          "--allow-http",
          "--header",
          "MCP-SPEAKEASY_YOUR_TOOLSET_CRED:${VALUE}"
        ]
      }
    }
  }
```