Etash Guha commited on
Commit
229e7eb
1 Parent(s): 0f38260

some small changes

Browse files
Files changed (1) hide show
  1. app.py +4 -5
app.py CHANGED
@@ -16,14 +16,13 @@ if 'response_content' not in st.session_state:
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  chat_col = st.container()
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  chat_col.title("CodeLATS")
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- description = """This demo is an implementation of Language Agent Tree Search (LATS) (https://arxiv.org/abs/2310.04406) built specifically for generating code in the form of python functions. It achieves :green[**state-of-the-art**] results on HumanEval with a :green[**94.4% pass@1 rate**] on GPT-4.
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- Listed below is an example programming problem (https://leetcode.com/problems/longest-valid-parentheses/description/) to get started with.
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  ```python
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- Given a string containing just the characters '(' and ')', return the length of the longest valid (well-formed) parentheses substring
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  ```
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- :red[**NOTE:**] On average a call for a HumanEval or Leetcode question will cost around 5-30 cents on GPT-4, using the default parameters. This value may change depending on problem difficulty and parameters.
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  """
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  chat_col.markdown(description)
@@ -32,7 +31,7 @@ sidebar = st.sidebar
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  runtime_container = st.container()
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  # Parameters Section
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- sidebar.title("**A Lapis Labs Project** (https://lapis.rocks/)")
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  parameters_section = sidebar.expander("Parameters", expanded=False)
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  tree_width = parameters_section.number_input("Tree Width", min_value=1, max_value=5, value=1)
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  tree_depth = parameters_section.number_input("Tree Depth", min_value=1, max_value=8, value=3)
 
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  chat_col = st.container()
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  chat_col.title("CodeLATS")
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+ description = """This demo is an implementation of Language Agent Tree Search (LATS) (https://arxiv.org/abs/2310.04406) with Samba-1 in the backend. Thank you to the original authors of demo on which this is based from [Lapis Labs](https://lapis.rocks/)
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+ Listed below is an example programming problem (https://leetcode.com/problems/median-of-two-sorted-arrays/description/) to get started with.
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  ```python
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+ Given two sorted arrays `nums1` and `nums2` of size `m` and `n` respectively, return **the median** of the two sorted arrays. The overall run time complexity should be `O(log (m+n))`. **Example 1:** **Input:** nums1 = \[1,3\], nums2 = \[2\] **Output:** 2.00000 **Explanation:** merged array = \[1,2,3\] and median is 2. **Example 2:** **Input:** nums1 = \[1,2\], nums2 = \[3,4\] **Output:** 2.50000 **Explanation:** merged array = \[1,2,3,4\] and median is (2 + 3) / 2 = 2.5. **Constraints:** * `nums1.length == m` * `nums2.length == n` * `0 <= m <= 1000` * `0 <= n <= 1000` * `1 <= m + n <= 2000` * `-106 <= nums1[i], nums2[i] <= 106`
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  ```
 
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  """
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  chat_col.markdown(description)
 
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  runtime_container = st.container()
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  # Parameters Section
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+ sidebar.title("From SambaNova Systems")
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  parameters_section = sidebar.expander("Parameters", expanded=False)
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  tree_width = parameters_section.number_input("Tree Width", min_value=1, max_value=5, value=1)
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  tree_depth = parameters_section.number_input("Tree Depth", min_value=1, max_value=8, value=3)