Python: fix anthropic code interpreter tool repr (#2244)

* fix anthropic code interpreter tool repr

* fixes

* added skills and sample

* test fix

* add new sample to readme

* fixes tests
This commit is contained in:
Eduard van Valkenburg
2025-11-17 11:06:10 +01:00
committed by GitHub
Unverified
parent 45dba6b825
commit fcc3f1b6c0
4 changed files with 148 additions and 18 deletions
@@ -8,6 +8,7 @@ This folder contains examples demonstrating how to use Anthropic's Claude models
|------|-------------|
| [`anthropic_basic.py`](anthropic_basic.py) | Demonstrates how to setup a simple agent using the AnthropicClient, with both streaming and non-streaming responses. |
| [`anthropic_advanced.py`](anthropic_advanced.py) | Shows advanced usage of the AnthropicClient, including hosted tools and `thinking`. |
| [`anthropic_skills.py`](anthropic_skills.py) | Illustrates how to use Anthropic-managed Skills with an agent, including the Code Interpreter tool and file generation and saving. |
## Environment Variables
@@ -0,0 +1,88 @@
# Copyright (c) Microsoft. All rights reserved.
import asyncio
import logging
from pathlib import Path
from agent_framework import HostedCodeInterpreterTool, HostedFileContent
from agent_framework.anthropic import AnthropicClient
logger = logging.getLogger(__name__)
"""
Anthropic Skills Agent Example
This sample demonstrates using Anthropic with:
- Listing and using Anthropic-managed Skills.
- One approach to add additional beta flags.
You can also set additonal_chat_options with "additional_beta_flags" per request.
- Creating an agent with the Code Interpreter tool and a Skill.
- Catching and downloading generated files from the agent.
"""
async def main() -> None:
"""Example of streaming response (get results as they are generated)."""
client = AnthropicClient(additional_beta_flags=["skills-2025-10-02"])
# List Anthropic-managed Skills
skills = await client.anthropic_client.beta.skills.list(source="anthropic", betas=["skills-2025-10-02"])
for skill in skills.data:
print(f"{skill.source}: {skill.id} (version: {skill.latest_version})")
# Create a agent with the pptx skill enabled
# Skills also need the code interpreter tool to function
agent = client.create_agent(
name="DocsAgent",
instructions="You are a helpful agent for creating powerpoint presentations.",
tools=HostedCodeInterpreterTool(),
max_tokens=20000,
additional_chat_options={
"thinking": {"type": "enabled", "budget_tokens": 10000},
"container": {"skills": [{"type": "anthropic", "skill_id": "pptx", "version": "latest"}]},
},
)
print(
"The agent output will use the following colors:\n"
"\033[0mUser: (default)\033[0m\n"
"\033[0mAgent: (default)\033[0m\n"
"\033[32mAgent Reasoning: (green)\033[0m\n"
"\033[34mUsage: (blue)\033[0m\n"
)
query = "Create a presentation about renewable energy with 5 slides"
print(f"User: {query}")
print("Agent: ", end="", flush=True)
files: list[HostedFileContent] = []
async for chunk in agent.run_stream(query):
for content in chunk.contents:
match content.type:
case "text":
print(content.text, end="", flush=True)
case "text_reasoning":
print(f"\033[32m{content.text}\033[0m", end="", flush=True)
case "usage":
print(f"\n\033[34m[Usage so far: {content.details}]\033[0m\n", end="", flush=True)
case "hosted_file":
# Catch generated files
files.append(content)
case _:
logger.debug("Unhandled content type: %s", content.type)
pass
print("\n")
if files:
# Save to a new file (will be in the folder where you are running this script)
# When running this sample multiple times, the files will be overritten
# Since I'm using the pptx skill, the files will be PowerPoint presentations
print("Generated files:")
for idx, file in enumerate(files):
file_content = await client.anthropic_client.beta.files.download(
file_id=file.file_id, betas=["files-api-2025-04-14"]
)
with open(Path(__file__).parent / f"renewable_energy-{idx}.pptx", "wb") as f:
await file_content.write_to_file(f.name)
print(f"File {idx}: renewable_energy-{idx}.pptx saved to disk.")
if __name__ == "__main__":
asyncio.run(main())