move advanced options to utils.py

app.py

@@ -21,6 +21,7 @@ from utils import (
     authenticate,
     delete_uploaded_file,
     generate_response,
+    handle_advanced_options,
     logger,
     save_uploaded_file,
     update_chain,
@@ -108,55 +109,7 @@ with st.sidebar:
 
     # Advanced Options
     if ENABLE_ADVANCED_OPTIONS:
-        advanced_options = st.checkbox(
-            "Advanced Options", help="Caution! This may break things!"
-        )
-        if advanced_options:
-            with st.form("advanced_options"):
-                temperature = st.slider(
-                    "temperature",
-                    min_value=0.0,
-                    max_value=1.0,
-                    value=TEMPERATURE,
-                    help="Controls the randomness of the language model output",
-                )
-                col1, col2 = st.columns(2)
-                fetch_k = col1.number_input(
-                    "k_fetch",
-                    min_value=1,
-                    max_value=100,
-                    value=FETCH_K,
-                    help="The number of documents to pull from the vector database",
-                )
-                k = col2.number_input(
-                    "k",
-                    min_value=1,
-                    max_value=100,
-                    value=K,
-                    help="The number of most similar documents returned from the vector store",
-                )
-                chunk_size = col1.number_input(
-                    "chunk_size",
-                    min_value=1,
-                    max_value=100000,
-                    value=CHUNK_SIZE,
-                    help="The size at which the text is divided into smaller chunks before being embedded",
-                )
-                max_tokens = col2.number_input(
-                    "max_tokens",
-                    min_value=1,
-                    max_value=4069,
-                    value=MAX_TOKENS,
-                    help="Limits the documents returned from database based on tokens",
-                )
-                applied = st.form_submit_button("Apply")
-                if applied:
-                    st.session_state["k"] = k
-                    st.session_state["fetch_k"] = fetch_k
-                    st.session_state["chunk_size"] = chunk_size
-                    st.session_state["temperature"] = temperature
-                    st.session_state["max_tokens"] = max_tokens
-                    update_chain()
+        handle_advanced_options()
 
 
 # the chain can only be initialized after authentication is OK

constants.py

@@ -22,6 +22,12 @@ The keys are neither exposed nor made visible or stored permanently in any way.\
 Feel free to check out [the code base]({REPO_URL}) to validate how things work.
 """
 
+USAGE_HELP = f"""
+These are the accumulated OpenAI API usage metrics.\n
+The app uses '{MODEL}' for chat and 'text-embedding-ada-002' for embeddings.\n
+Learn more about OpenAI's pricing [here](https://openai.com/pricing#language-models)
+"""
+
 OPENAI_HELP = """
 You can sign-up for OpenAI's API [here](https://openai.com/blog/openai-api).\n
 Once you are logged in, you find the API keys [here](https://platform.openai.com/account/api-keys)
@@ -32,9 +38,3 @@ You can create an ActiveLoops account (including 500GB of free database storage)
 Once you are logged in, you find the API token [here](https://app.activeloop.ai/profile/gustavz/apitoken).\n
 The organisation name is your username, or you can create new organisations [here](https://app.activeloop.ai/organization/new/create)
 """
-
-USAGE_HELP = f"""
-These are the accumulated OpenAI API usage metrics.\n
-The app uses '{MODEL}' for chat and 'text-embedding-ada-002' for embeddings.\n
-Learn more about OpenAI's pricing [here](https://openai.com/pricing#language-models)
-"""

utils.py

@@ -110,6 +110,63 @@ def authenticate(openai_api_key, activeloop_token, activeloop_org_name):
     logger.info("Authentification successful!")
 
 
+def handle_advanced_options():
+    # Input Form that takes advanced options and rebuilds chain with them
+    advanced_options = st.checkbox(
+        "Advanced Options", help="Caution! This may break things!"
+    )
+    if advanced_options:
+        with st.form("advanced_options"):
+            temperature = st.slider(
+                "temperature",
+                min_value=0.0,
+                max_value=1.0,
+                value=TEMPERATURE,
+                help="Controls the randomness of the language model output",
+            )
+            col1, col2 = st.columns(2)
+            fetch_k = col1.number_input(
+                "k_fetch",
+                min_value=1,
+                max_value=100,
+                value=FETCH_K,
+                help="The number of documents to pull from the vector database",
+            )
+            k = col2.number_input(
+                "k",
+                min_value=1,
+                max_value=100,
+                value=K,
+                help="The number of most similar documents to build the context from",
+            )
+            chunk_size = col1.number_input(
+                "chunk_size",
+                min_value=1,
+                max_value=100000,
+                value=CHUNK_SIZE,
+                help=(
+                    "The size at which the text is divided into smaller chunks "
+                    "before being embedded.\n\nChanging this parameter makes re-embedding "
+                    "and re-uploading the data to the database necessary "
+                ),
+            )
+            max_tokens = col2.number_input(
+                "max_tokens",
+                min_value=1,
+                max_value=4069,
+                value=MAX_TOKENS,
+                help="Limits the documents returned from database based on number of tokens",
+            )
+            applied = st.form_submit_button("Apply")
+            if applied:
+                st.session_state["k"] = k
+                st.session_state["fetch_k"] = fetch_k
+                st.session_state["chunk_size"] = chunk_size
+                st.session_state["temperature"] = temperature
+                st.session_state["max_tokens"] = max_tokens
+                update_chain()
+
+
 def save_uploaded_file(uploaded_file):
     # streamlit uploaded files need to be stored locally
     # before embedded and uploaded to the hub