explain LLM API key setup

Author: allenanie

README.md

@@ -260,7 +260,7 @@ The table evaluates the frameworks in the following aspects:
 We provide a comparison to validate our implementation of TextGrad in Trace:
 
 <p align="center">
-    <img src="https://github.com/microsoft/Trace/blob/main/docs/images/compare_to_textgrad3.png" alt="drawing" width="100%"/>
+    <img src="https://github.com/microsoft/Trace/blob/main/docs/images/compare_to_textgrad3.png?raw=True" alt="drawing" width="100%"/>
 </p>
 
 To produce this table, we ran the TextGrad pip-installed repo on 2024-10-30, and we also include the numbers reported in the TextGrad paper.
@@ -269,6 +269,31 @@ The LLM APIs are called around the same time to ensure a fair comparison. TextGr
 You can also easily implement your own optimizer that works directly with `TraceGraph` (more tutorials on how to work
 with TraceGraph coming soon).
 
+## LLM API Setup
+
+Currently we rely on AutoGen for LLM caching and API-Key management. 
+AutoGen relies on `OAI_CONFIG_LIST`, which is a file you put in your working directory. It has the format of:
+
+```json lines
+[
+    {
+        "model": "gpt-4",
+        "api_key": "<your OpenAI API key here>"
+    },
+      {
+        "model": "claude-sonnet-3.5-latest",
+        "api_key": "<your Anthropic API key here>"
+    }
+]
+```
+You switch between different LLM models by changing the `model` field in this configuration file.
+
+You can also set an `os.environ` variable `OAI_CONFIG_LIST` to point to the location of this file or directly set a JSON string as the value of this variable.
+
+For convenience, we also provide a method that directly grabs the API key from the environment variable `OPENAI_API_KEY` or `ANTHROPIC_API_KEY`.
+However, doing so, we specify the model version you use, which is `gpt-4o` for OpenAI and `claude-sonnet-3.5-latest` for Anthropic.
+
+
 ## Citation
 
 If you use this code in your research please cite the following [publication](https://arxiv.org/abs/2406.16218):