From 57a40de2315cd0ea9beca21b7124a54a46e747da Mon Sep 17 00:00:00 2001
From: Joschka Braun <joschka.braun@gmail.com>
Date: Mon, 4 Dec 2023 11:43:00 -0500
Subject: [PATCH] feat: add eval functions to readme

---
 README.md                                     | 35 ++++++++++++++++++-
 .../tracing_and_evaluating_openai_endpoint.py |  2 +-
 pyproject.toml                                |  2 +-
 3 files changed, 36 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index f3d4aa57..161e00ea 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,4 @@
-# parea-sdk
+# Parea Python SDK
 
 <div align="center">
 
@@ -26,6 +26,39 @@ or install with `Poetry`
 poetry add parea-ai
 ```
 
+## Evaluating Your LLM App
+
+You can evaluate any step of your LLM app by wrapping it with a decorator, called `trace`, and specifying the evaluation function(s).
+The scores associated with the traces will be logged to the Parea [dashboard](https://app.parea.ai/logs) and/or in a local CSV file if you don't have a Parea API key.
+
+Evaluation functions receive an argument `log` (of type [Log](parea/schemas/models.py)) and should return a 
+float between 0 (bad) and 1 (good) inclusive. You don't need to start from scratch, there are pre-defined evaluation functions for [general purpose](parea/evals/general.py), 
+[chat](parea/evals/chat.py), [RAG](parea/evals/rag.py), and [summarization](parea/evals/summary.py) apps :)
+
+You can define evaluation functions locally or use the ones you have deployed to Parea's [Test Hub](https://app.parea.ai/test-hub).
+If you choose the latter option, the evaluation happens asynchronously and non-blocking.
+
+A fully locally working cookbook can be found [here](parea/cookbook/tracing_and_evaluating_openai_endpoint.py). 
+Alternatively, you can add the following code to your codebase to get started: 
+
+```python
+import os
+from parea import init, InMemoryCache
+from parea.schemas.models import Log
+from parea.utils.trace_utils import trace
+
+init(api_key=os.getenv("PAREA_API_KEY"), cache=InMemoryCache())  # use InMemoryCache if you don't have a Parea API key
+
+
+def locally_defined_eval_function(log: Log) -> float:
+  ...
+
+
+@trace(eval_func_names=['deployed_eval_function_name'], eval_funcs=[locally_defined_eval_function])
+def function_to_evaluate(*args, **kwargs) -> ...:
+  ...
+```
+
 ## Debugging Chains & Agents
 
 You can iterate on your chains & agents much faster by using a local cache. This will allow you to make changes to your
diff --git a/parea/cookbook/tracing_and_evaluating_openai_endpoint.py b/parea/cookbook/tracing_and_evaluating_openai_endpoint.py
index f9cd3377..831085f7 100644
--- a/parea/cookbook/tracing_and_evaluating_openai_endpoint.py
+++ b/parea/cookbook/tracing_and_evaluating_openai_endpoint.py
@@ -20,7 +20,7 @@
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
 
-use_cache = True
+use_cache = True  # by using the in memory cache, you don't need a Parea API key
 cache = InMemoryCache() if use_cache else None
 init(api_key=os.getenv("PAREA_API_KEY"), cache=cache)
 
diff --git a/pyproject.toml b/pyproject.toml
index 1f9f1f3d..799f4e8d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -6,7 +6,7 @@ build-backend = "poetry.core.masonry.api"
 [tool.poetry]
 name = "parea-ai"
 packages = [{ include = "parea" }]
-version = "0.2.20"
+version = "0.2.21"
 description = "Parea python sdk"
 readme = "README.md"
 authors = ["joel-parea-ai <joel@parea.ai>"]