| name | foundry-config-setup |
| description | Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded project_endpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment. |
| license | MIT |
| compatibility | Works with any model that supports tool use. |
| metadata | {"author":"agent-framework-samples","version":"1.0"} |
Usage
Some samples (notably those under 01-get-started) hardcode the Foundry
project endpoint and model directly in the FoundryChatClient constructor
using placeholder values, for example:
client = FoundryChatClient(
project_endpoint="https://your-project.services.ai.azure.com",
model="gpt-4o",
credential=AzureCliCredential(),
)
These placeholder values are not real and the sample cannot run as written.
The validation environment provides the real values through environment
variables, so the sample must read them from the environment instead.
When you detect a hardcoded/placeholder project_endpoint (or model) that
is causing the sample to fail with missing or invalid setup:
- Replace the hardcoded
project_endpoint value with a read from the
FOUNDRY_PROJECT_ENDPOINT environment variable.
- Replace the hardcoded
model value with a read from the FOUNDRY_MODEL
environment variable.
- Ensure
import os is present at the top of the file.
The corrected constructor should look like:
import os
client = FoundryChatClient(
project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
model=os.environ["FOUNDRY_MODEL"],
credential=AzureCliCredential(),
)
These samples are intentionally written with hardcoded placeholders, so this
is expected setup—not a defect in the sample. After applying the change,
re-run the sample and report the result as a success if it now runs.