update streamlit docs and examples

Author: jeffkayne

README.md

@@ -82,7 +82,7 @@ user_feedback = trubrics.log_feedback(
 
 ## Collect user prompts & feedback from a Streamlit app
 
-To start collecting prompts & feedback from your [Streamlit](https://streamlit.io/) app, install the additional dependency:
+To start collecting user feedback from your [Streamlit](https://streamlit.io/) app, install the additional dependency:
 
 ```console
 pip install "trubrics[streamlit]"
@@ -94,34 +94,27 @@ and test this code snippet in your app:
 import streamlit as st
 from trubrics.integrations.streamlit import FeedbackCollector
 
-if "logged_prompt" not in st.session_state:
-    st.session_state.logged_prompt = None
-
 collector = FeedbackCollector(
     email=st.secrets.TRUBRICS_EMAIL,
     password=st.secrets.TRUBRICS_PASSWORD,
     project="default"
 )
 
-if st.button("Predict"):
-    st.session_state.logged_prompt = collector.log_prompt(
-        config_model={"model": "gpt-3.5-turbo"},
-        prompt="Tell me a joke",
-        generation="Why did the chicken cross the road? To get to the other side.",
-    )
-
-if st.session_state.logged_prompt:
-    st.write("A model generation...")
-    user_feedback = collector.st_feedback(
-        component="default",
-        feedback_type="thumbs",
-        open_feedback_label="[Optional] Provide additional feedback",
-        model=st.session_state.logged_prompt.config_model.model,
-        prompt_id=st.session_state.logged_prompt.id,
-        align="flex-start",
-    )
+user_feedback = collector.st_feedback(
+    component="default",
+    feedback_type="thumbs",
+    open_feedback_label="[Optional] Provide additional feedback",
+    model="gpt-3.5-turbo",
+    prompt_id=None,  # checkout collector.log_prompt() to log your user prompts
+)
+
+if user_feedback:
+    st.write("#### Raw feedback saved to Trubrics:")
+    st.write(user_feedback)
 ```
 
+For a full examples logging user prompts and feedback in Streamlit, see our [Streamlit integration docs](https://trubrics.github.io/trubrics-sdk/integrations/streamlit/).
+
 ## Collect user feedback from a React.js app
 
 To collect user feedback from a React application, check out [this example](https://github.com/trubrics/trubrics-sdk/tree/main/examples/react_js).

docs/assets/streamlit-example.png

@@ -11,13 +11,14 @@ pip install "trubrics[streamlit]"
 ## Streamlit Example Apps
 Once you have created an account with [Trubrics](https://trubrics.streamlit.app/), you can try our deployed example Streamlit apps that use the integration to save feedback:
 
-- [LLM Chat Completion](https://trubrics-llm-example-chatbot.streamlit.app/): A chatbot that queries OpenAI's API and allows users to leave feedback.
-- [LLM Completion](https://trubrics-llm-example.streamlit.app/): An LLM app that queries OpenAI's API and allows users to leave feedback on single text generations.
-- [Titanic](https://trubrics-titanic-example.streamlit.app/): An app that allows users to give feedback on a classifier that predicts whether passengers will survive the titanic.
+![](../assets/streamlit-example.png)
+
+- **LLM chat** - [deployed app](https://trubrics-llm-example-chatbot.streamlit.app/) | [code](https://github.com/trubrics/trubrics-sdk/blob/main/examples/streamlit/llm_chatbot.py) : A chatbot that queries OpenAI's API and allows users to leave feedback.
+- **LLM single answer** - [deployed app](https://trubrics-llm-example.streamlit.app/) | [code](https://github.com/trubrics/trubrics-sdk/blob/main/examples/streamlit/llm_app.py) : An LLM app that queries OpenAI's API and allows users to leave feedback on single text generations.
 
 The code for these apps can be viewed in the [trubrics-sdk](https://github.com/trubrics/trubrics-sdk/tree/main/examples), and may be run by cloning the repo and running:
 
-=== "LLM Chat Completion"
+=== "LLM chat"
     !!!tip OpenAI
         To run this app, you are required to have your own [OpenAI](https://platform.openai.com/overview) API key.
 
@@ -31,7 +32,7 @@ The code for these apps can be viewed in the [trubrics-sdk](https://github.com/t
     streamlit run examples/feedback/streamlit/llm_chatbot.py
     ```
 
-=== "LLM Completion"
+=== "LLM single answer"
     !!!tip OpenAI
         To run this app, you are required to have your own [OpenAI](https://platform.openai.com/overview) API key.
 
@@ -45,24 +46,18 @@ The code for these apps can be viewed in the [trubrics-sdk](https://github.com/t
     streamlit run examples/feedback/streamlit/llm_app.py
     ```
 
-=== "Titanic"
-
-    ```
-    pip install scikit-learn==1.1.0
-    ```
+## Add the FeedbackCollector to your App
 
-    ```console
-    streamlit run examples/feedback/streamlit/titanic_app.py
-    ```
+Here is a complete example to log user prompts and feedback from a simple streamlit application:
 
-## Add the FeedbackCollector to your App
-To get started, you can add this code snippet directly to your streamlit app:
-```py
+```py title="examples/streamlit/basic_app.py"
 import streamlit as st
 from trubrics.integrations.streamlit import FeedbackCollector
 
 if "logged_prompt" not in st.session_state:
     st.session_state.logged_prompt = None
+if "feedback_key" not in st.session_state:
+    st.session_state.feedback_key = 0
 
 # 1. authenticate with trubrics
 collector = FeedbackCollector(
@@ -71,24 +66,34 @@ collector = FeedbackCollector(
     project="default"
 )
 
-if st.button("Predict"):
+if st.button("Refresh"):
+    st.session_state.feedback_key += 1
+    st.session_state.logged_prompt = None
+    st.experimental_rerun()
+
+prompt = "Tell me a joke"
+generation = "Why did the chicken cross the road? To get to the other side."
+st.write(f"#### :orange[Example user prompt: {prompt}]")
+
+
+if st.button("Generate response"):
     # 2. log a user prompt & model response
     st.session_state.logged_prompt = collector.log_prompt(
         config_model={"model": "gpt-3.5-turbo"},
-        prompt="Tell me a joke",
-        generation="Why did the chicken cross the road? To get to the other side.",
+        prompt=prompt,
+        generation=generation,
     )
 
 if st.session_state.logged_prompt:
-    st.write("A model generation...")
-
+    st.write(f"#### :blue[Example model generation: {generation}]")
     # 3. log some user feedback
     user_feedback = collector.st_feedback(
         component="default",
         feedback_type="thumbs",
         open_feedback_label="[Optional] Provide additional feedback",
         model=st.session_state.logged_prompt.config_model.model,
         prompt_id=st.session_state.logged_prompt.id,
+        key=st.session_state.feedback_key,
         align="flex-start",
     )
 ```

docs/integrations/streamlit.md

@@ -4,23 +4,39 @@
 
 if "logged_prompt" not in st.session_state:
     st.session_state.logged_prompt = None
+if "feedback_key" not in st.session_state:
+    st.session_state.feedback_key = 0
 
+# 1. authenticate with trubrics
 collector = FeedbackCollector(email=st.secrets.TRUBRICS_EMAIL, password=st.secrets.TRUBRICS_PASSWORD, project="default")
 
-if st.button("Predict"):
+if st.button("Refresh"):
+    st.session_state.feedback_key += 1
+    st.session_state.logged_prompt = None
+    st.experimental_rerun()
+
+prompt = "Tell me a joke"
+generation = "Why did the chicken cross the road? To get to the other side."
+st.write(f"#### :orange[Example user prompt: {prompt}]")
+
+
+if st.button("Generate response"):
+    # 2. log a user prompt & model response
     st.session_state.logged_prompt = collector.log_prompt(
         config_model={"model": "gpt-3.5-turbo"},
-        prompt="Tell me a joke",
-        generation="Why did the chicken cross the road? To get to the other side.",
+        prompt=prompt,
+        generation=generation,
     )
 
 if st.session_state.logged_prompt:
-    st.write("A model generation...")
+    st.write(f"#### :blue[Example model generation: {generation}]")
+    # 3. log some user feedback
     user_feedback = collector.st_feedback(
         component="default",
         feedback_type="thumbs",
         open_feedback_label="[Optional] Provide additional feedback",
         model=st.session_state.logged_prompt.config_model.model,
         prompt_id=st.session_state.logged_prompt.id,
+        key=st.session_state.feedback_key,
         align="flex-start",
     )

examples/streamlit/basic_app.py

@@ -0,0 +1,17 @@
+import streamlit as st
+
+from trubrics.integrations.streamlit import FeedbackCollector
+
+collector = FeedbackCollector(email=st.secrets.TRUBRICS_EMAIL, password=st.secrets.TRUBRICS_PASSWORD, project="default")
+
+user_feedback = collector.st_feedback(
+    component="default",
+    feedback_type="thumbs",
+    open_feedback_label="[Optional] Provide additional feedback",
+    model="gpt-3.5-turbo",
+    prompt_id=None,  # checkout collector.log_prompt() to log your user prompts
+)
+
+if user_feedback:
+    st.write("#### Raw feedback saved to Trubrics:")
+    st.write(user_feedback)