eagle0504 commited on
Commit
d4a32ac
Β·
1 Parent(s): 258745c

button added

Browse files
Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -59,7 +59,7 @@ special_threshold = st.sidebar.number_input(
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  st.sidebar.success(
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  "The 'distances' score indicates the proximity of your question to our database questions (lower is better). The 'ai_judge' ranks the similarity between user's question and database answers independently (higher is better)."
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  )
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- submit_button = st.sidebar.button("Submit", type="primary")
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  clear_button = st.sidebar.button("Clear Conversation", key="clear")
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  if clear_button:
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  st.session_state.messages = []
@@ -103,11 +103,11 @@ collection = client.create_collection(combined_string)
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  # Embed and store the first N supports for this demo
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  if submit_button:
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  with st.spinner("Loading, please be patient with us ... πŸ™"):
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- L = len(dataset["train"]["questions"][0:20])
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  begin_t = time.time()
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  collection.add(
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  ids=[str(i) for i in range(0, L)], # IDs are just strings
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- documents=dataset["train"]["questions"][0:20], # Enter questions here
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  metadatas=[{"type": "support"} for _ in range(0, L)],
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  )
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  end_t = time.time()
@@ -132,8 +132,8 @@ if prompt := st.chat_input(initial_input):
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  ref = pd.DataFrame(
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  {
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  "idx": idx,
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- "questions": [dataset["train"]["questions"][0:20][i] for i in idx],
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- "answers": [dataset["train"]["answers"][0:20][i] for i in idx],
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  "distances": results["distances"][0],
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  }
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  )
 
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  st.sidebar.success(
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  "The 'distances' score indicates the proximity of your question to our database questions (lower is better). The 'ai_judge' ranks the similarity between user's question and database answers independently (higher is better)."
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  )
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+ submit_button = st.button("Submit", type="primary")
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  clear_button = st.sidebar.button("Clear Conversation", key="clear")
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  if clear_button:
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  st.session_state.messages = []
 
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  # Embed and store the first N supports for this demo
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  if submit_button:
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  with st.spinner("Loading, please be patient with us ... πŸ™"):
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+ L = len(dataset["train"]["questions"])
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  begin_t = time.time()
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  collection.add(
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  ids=[str(i) for i in range(0, L)], # IDs are just strings
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+ documents=dataset["train"]["questions"], # Enter questions here
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  metadatas=[{"type": "support"} for _ in range(0, L)],
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  )
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  end_t = time.time()
 
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  ref = pd.DataFrame(
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  {
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  "idx": idx,
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+ "questions": [dataset["train"]["questions"][i] for i in idx],
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+ "answers": [dataset["train"]["answers"][i] for i in idx],
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  "distances": results["distances"][0],
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  }
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  )