├── .gitignore
├── LICENSE
├── Pipfile
├── Pipfile.lock
├── README.md
├── codex_params.toml
├── logo.png
├── modes.toml
├── mouse.gif
├── requirements.txt
└── streamlit_app.py
/.gitignore:
--------------------------------------------------------------------------------
1 | # Streamlit runtime information
2 | .streamlit
3 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
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/Pipfile:
--------------------------------------------------------------------------------
1 | [[source]]
2 | url = "https://pypi.org/simple"
3 | verify_ssl = true
4 | name = "pypi"
5 |
6 | [packages]
7 |
8 | streamlit = "*"
9 | transformers = "*"
10 | openai = "*"
11 | yfinance = "*"
12 | plotly = "*"
13 | streamlit-ace = "*"
14 | polyfuzz = "*"
15 |
16 |
17 |
18 | [dev-packages]
19 | black = "*" # Pretty formatting of Python code
20 | pynvim = "*" # Allows nvim users to use black formatting
21 |
22 | [pipenv]
23 | allow_prereleases = true
24 |
--------------------------------------------------------------------------------
/Pipfile.lock:
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1601 | "sha256:0b5d6f9aed3153487252d00a18e53f19b7f52a1651bc1d0c4b5844bc286dfa52",
1602 | "sha256:0d2f5c3f7057530afd7b739ed42eb04f1011203bc5e4663e1e1d01bb50f813e3",
1603 | "sha256:11772be1eb1748e0e197a40ffb82fb8fd0d6914cd147d841d9703e2bef24d288",
1604 | "sha256:1333b3ce73269f986b1fa4d5d395643810074dc2de5b9d262eb258daf37dc98f",
1605 | "sha256:16f81025bb3556eccb0681d7946e2b35ff254f9f888cff7d2120e8826330315c",
1606 | "sha256:1a171eaac36a08964d023eeff740b18a415f79aeb212169080c170ec42dd5184",
1607 | "sha256:1d6301f5288e9bdca65fab3de6b7de17362c5016d6bf8ee4ba4cbe833b2eda0f",
1608 | "sha256:1e031899cb2bc92c0cf4d45389eff5b078d1936860a1be3aa8c94fa25fb46ed8",
1609 | "sha256:1f8c0ae0a0de4e19fddaaff036f508db175f6f03db318c80bbc239a1def62d02",
1610 | "sha256:2245441445099411b528379dee83e56eadf449db924648e5feb9b747473f42e3",
1611 | "sha256:22709d701e7037e64dae2a04855021b62efd64a66c3ceed99dfd684bfef09e38",
1612 | "sha256:24c89346734a4e4d60ecf9b27cac4c1fee3431a413f7aa00be7c4d7bbacc2c4d",
1613 | "sha256:25716aa70a0d153cd844fe861d4f3315a6ccafce22b39d8aadbf7fcadff2b633",
1614 | "sha256:2dacb3dae6b8cc579637a7b72f008bff50a94cde5e36e432352f4ca57b9e54c4",
1615 | "sha256:34316bf693b1d2d29c087ee7e4bb10cdfa39da5f9c50fa15b07489b4ab93a1b5",
1616 | "sha256:36b2d700a27e168fa96272b42d28c7ac3ff72030c67b32f37c05616ebd22a202",
1617 | "sha256:37978254d9d00cda01acc1997513f786b6b971e57b778fbe7c20e30ae81a97f3",
1618 | "sha256:38289f1690a7e27aacd049e420769b996826f3728756859420eeee21cc857118",
1619 | "sha256:385ccf6d011b97768a640e9d4de25412204fbe8d6b9ae39ff115d4ff03f6fe5d",
1620 | "sha256:3c7ea86b9ca83e30fa4d4cd0eaf01db3ebcc7b2726a25990966627e39577d729",
1621 | "sha256:49810f907dfe6de8da5da7d2b238d343e6add62f01a15d03e2195afc180059ed",
1622 | "sha256:519c0b3a6fbb68afaa0febf0d28f6c4b0a1074aefc484802ecb9709faf181607",
1623 | "sha256:51f02ca184518702975b56affde6c573ebad4e411599005ce4468b1014b4786c",
1624 | "sha256:552a39987ac6655dad4bf6f17dd2b55c7b0c6e949d933b8846d2e312ee80005a",
1625 | "sha256:596f5ae2eeddb79b595583c2e0285312b2783b0ec759930c272dbf02f851ff75",
1626 | "sha256:6014038f52b4b2ac1fa41a58d439a8a00f015b5c0735a0cd4b09afe344c94899",
1627 | "sha256:61ebbcd208d78658b09e19c78920f1ad38936a0aa0f9c459c46c197d11c580a0",
1628 | "sha256:6213713ac743b190ecbf3f316d6e41d099e774812d470422b3a0f137ea635832",
1629 | "sha256:637e27ea1ebe4a561db75a880ac659ff439dec7f55588212e71700bb1ddd5af9",
1630 | "sha256:6aa427c55a0abec450bca10b64446331b5ca8f79b648531138f357569705bc4a",
1631 | "sha256:6ca45359d7a21644793de0e29de497ef7f1ae7268e346c4faf87b421fea364e6",
1632 | "sha256:6db1b52c6f2c04fafc8da17ea506608e6be7086715dab498570c3e55e4f8fbd1",
1633 | "sha256:752e7ddfb743344d447367baa85bccd3629c2c3940f70506eb5f01abce98ee68",
1634 | "sha256:760c54ad1b8a9b81951030a7e8e7c3ec0964c1cb9fee585a03ff53d9e531bb8e",
1635 | "sha256:768632fd8172ae03852e3245f11c8a425d95f65ff444ce46b3e673ae5b057b74",
1636 | "sha256:7a0b9f6a1a15d494b35f25ed07abda03209fa76c33564c09c9e81d34f4b919d7",
1637 | "sha256:7e070d3aef50ac3856f2ef5ec7214798453da878bb5e5a16c16a61edf1817cc3",
1638 | "sha256:7e12949e5071c20ec49ef00c75121ed2b076972132fc1913ddf5f76cae8d10b4",
1639 | "sha256:7e26eac9e52e8ce86f915fd33380f1b6896a2b51994e40bb094841e5003429b4",
1640 | "sha256:85ffd6b1cb0dfb037ede50ff3bef80d9bf7fa60515d192403af6745524524f3b",
1641 | "sha256:8618d9213a863c468a865e9d2ec50221015f7abf52221bc927152ef26c484b4c",
1642 | "sha256:8acef4d8a4353f6678fd1035422a937c2170de58a2b29f7da045d5249e934101",
1643 | "sha256:8d2f355a951f60f0843f2368b39970e4667517e54e86b1508e76f92b44811a8a",
1644 | "sha256:90b6840b6448203228a9d8464a7a0d99aa8fa9f027ef95fe230579abaf8a6ee1",
1645 | "sha256:9187500d83fd0cef4669385cbb0961e227a41c0c9bc39219044e35810793edf7",
1646 | "sha256:93c20777a72cae8620203ac11c4010365706062aa13aaedd1a21bb07adbb9d5d",
1647 | "sha256:93cce7d422a0093cfb3606beae38a8e47a25232eea0f292c878af580a9dc7605",
1648 | "sha256:94c623c331a48a5ccc7d25271399aff29729fa202c737ae3b4b28b89d2b0976d",
1649 | "sha256:97f32dc03a8054a4c4a5ab5d761ed4861e828b2c200febd4e46857069a483916",
1650 | "sha256:9a2bf98ac92f58777c0fafc772bf0493e67fcf677302e0c0a630ee517a43b949",
1651 | "sha256:a602bdc8607c99eb5b391592d58c92618dcd1537fdd87df1813f03fed49957a6",
1652 | "sha256:a9d24b03daf7415f78abc2d25a208f234e2c585e5e6f92f0204d2ab7b9ab48e3",
1653 | "sha256:abfcb0ef78df0ee9df4ea81f03beea41849340ce33a4c4bd4dbb99e23ec781b6",
1654 | "sha256:b013f759cd69cb0a62de954d6d2096d648bc210034b79b1881406b07ed0a83f9",
1655 | "sha256:b02e3e72665cd02afafb933453b0c9f6c59ff6e3708bd28d0d8580450e7e88af",
1656 | "sha256:b52cc45e71657bc4743a5606d9023459de929b2a198d545868e11898ba1c3f59",
1657 | "sha256:ba37f11e1d020969e8a779c06b4af866ffb6b854d7229db63c5fdddfceaa917f",
1658 | "sha256:bb804c7d0bfbd7e3f33924ff49757de9106c44e27979e2492819c16972ec0da2",
1659 | "sha256:bf594cc7cc9d528338d66674c10a5b25e3cde7dd75c3e96784df8f371d77a298",
1660 | "sha256:c38baee6bdb7fe1b110b6b3aaa555e6e872d322206b7245aa39572d3fc991ee4",
1661 | "sha256:c73d2166e4b210b73d1429c4f1ca97cea9cc090e5302df2a7a0a96ce55373f1c",
1662 | "sha256:c9099bf89078675c372339011ccfc9ec310310bf6c292b413c013eb90ffdcafc",
1663 | "sha256:cf0db26a1f76aa6b3aa314a74b8facd586b7a5457d05b64f8082a62c9c49582a",
1664 | "sha256:d19a34f8a3429bd536996ad53597b805c10352a8561d8382e05830df389d2b43",
1665 | "sha256:da80047524eac2acf7c04c18ac7a7da05a9136241f642dd2ed94269ef0d0a45a",
1666 | "sha256:de2923886b5d3214be951bc2ce3f6b8ac0d6dfd4a0d0e2a4d2e5523d8046fdfb",
1667 | "sha256:defa0652696ff0ba48c8aff5a1fac1eef1ca6ac9c660b047fc8e7623c4eb5093",
1668 | "sha256:e54a1eb9fd38f2779e973d2f8958fd575b532fe26013405d1afb9ee2374e7ab8",
1669 | "sha256:e5c31d70a478b0ca22a9d2d76d520ae996214019d39ed7dd93af872c7f301e52",
1670 | "sha256:ebaeb93f90c0903233b11ce913a7cb8f6ee069158406e056f884854c737d2442",
1671 | "sha256:ecfe51abf7f045e0b9cdde71ca9e153d11238679ef7b5da6c82093874adf3338",
1672 | "sha256:f99112aed4fb7cee00c7f77e8b964a9b10f69488cdff626ffd797d02e2e4484f",
1673 | "sha256:fd914db437ec25bfa410f8aa0aa2f3ba87cdfc04d9919d608d02330947afaeab"
1674 | ],
1675 | "version": "==2022.1.18"
1676 | },
1677 | "tomli": {
1678 | "hashes": [
1679 | "sha256:05b6166bff487dc068d322585c7ea4ef78deed501cc124060e0f238e89a9231f",
1680 | "sha256:e3069e4be3ead9668e21cb9b074cd948f7b3113fd9c8bba083f48247aab8b11c"
1681 | ],
1682 | "markers": "python_version >= '3.6'",
1683 | "version": "==1.2.3"
1684 | },
1685 | "typing-extensions": {
1686 | "hashes": [
1687 | "sha256:4ca091dea149f945ec56afb48dae714f21e8692ef22a395223bcd328961b6a0e",
1688 | "sha256:7f001e5ac290a0c0401508864c7ec868be4e701886d5b573a9528ed3973d9d3b"
1689 | ],
1690 | "markers": "python_version >= '3.6'",
1691 | "version": "==4.0.1"
1692 | }
1693 | }
1694 | }
1695 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 |
2 | [](https://share.streamlit.io/streamlit/example-app-streamlit-codex/main)
3 |
4 | 
5 |
6 | A Streamlit app that builds Streamlit apps!
7 |
8 |
9 | ### How to use our Codex app
10 |
11 | Here are a few sample apps to get you started:
12 |
13 | 
14 |
15 |
16 | The text prompt is where the magic starts.
17 |
18 | First, explain to Codex what app you’d like to create. For example, create a web app that shows Google stocks in a particular date range. When done, generate the code by clicking on the Execute button:
19 |
20 | 
21 |
22 | Next, tweak the settings and edit the Codex output. Once Codex generates the code, you’ll see a second prompt. Review the code and edit it if you spot any issues:
23 |
24 | 
25 |
26 | Happy with your prompt? It’s time to generate the code to launch your Streamlit app! I’ve used the Python exec function and this code snippet:
27 |
28 |
29 | ```
30 | button3 = st.button("🎈 Execute Code")
31 | if button3:
32 | exec(output_code)Le
33 | ```
34 |
35 | That’s it. Sit back, relax, and watch your app launch!
36 |
37 | 
38 |
39 | )
40 |
41 |
42 |
--------------------------------------------------------------------------------
/codex_params.toml:
--------------------------------------------------------------------------------
1 | [ codex_params.max_tokens ]
2 |
3 | input_type = "slider"
4 | default_value = 16
5 |
6 | input_params.min_value = 16
7 | input_params.max_value = 1000
8 | input_params.help = "The maximum number of tokens to generate in the completion."
9 |
10 |
11 | [ codex_params.temperature ]
12 |
13 | input_type = "slider"
14 | default_value = 1.0
15 |
16 | input_params.min_value = 0.0
17 | input_params.max_value = 1.0
18 | input_params.help = "Higher values means the model will take more risks."
19 |
20 |
21 | [ codex_params.frequency_penalty ]
22 |
23 | input_type = "slider"
24 | default_value = 0.0
25 |
26 | input_params.min_value = -2.0
27 | input_params.max_value = 2.0
28 | input_params.help = "Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim."
29 |
30 |
31 | [ codex_params.presence_penalty ]
32 |
33 | input_type = "slider"
34 | default_value = 0.0
35 |
36 | input_params.min_value = -2.0
37 | input_params.max_value = 2.0
38 | input_params.help = "Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics."
39 |
40 |
41 | [ codex_params.stop ]
42 |
43 | input_type = "multiselect"
44 | default_value = []
45 |
46 | input_params.options = ['#', '###', '"""']
47 | input_params.help = "Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence."
48 |
49 |
50 | [ codex_params.best_of ]
51 |
52 | input_type = "number_input"
53 | default_value = 1
54 |
55 | input_params.min_value = 1
56 | input_params.max_value = 5
57 | input_params.help = 'Generates best_of completions server-side and returns the "best" (the one with the lowest log probability per token).'
58 |
59 |
--------------------------------------------------------------------------------
/logo.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/streamlit/example-app-streamlit-codex/93e0f90c5ed671830f666da90d5ebf2212e7e0e4/logo.png
--------------------------------------------------------------------------------
/modes.toml:
--------------------------------------------------------------------------------
1 | #####################################################################
2 | # These are some sample modes for the Codex app. #
3 | # Each mode consists of a snippet of code with some CODEX settings. #
4 | #####################################################################
5 |
6 | ######################################
7 | # An app to show Google Stock prices #
8 | ######################################
9 |
10 | [modes.google_stock]
11 |
12 | title = "💸 Google Stocks App"
13 |
14 | input_code = """
15 | # An app to show Google stocks.
16 |
17 | \"\"\"
18 | App which shows price for Google Stock from 09/11/2019 to 09/15/2021
19 | \"\"\"
20 |
21 | import streamlit as st
22 | import yfinance as yf
23 | """
24 |
25 | codex_args.temperature=0.0
26 | codex_args.max_tokens=500
27 | codex_args.frequency_penalty=0.0
28 | codex_args.presence_penalty=0
29 | codex_args.best_of=2
30 |
31 |
32 | # Uncommment to get an an "execute" button
33 | output_controls.execute_button = "🎈 Execute Code"
34 |
35 |
36 | #######################################
37 | # An app to interactively blur images #
38 | #######################################
39 |
40 | [modes.blur_image]
41 |
42 | title = "🙈 Blur Image"
43 |
44 | input_code = """
45 | \"\"\"
46 | 1. Ask the user to upload an image.
47 | 2. Blur that image with a Guassian blur
48 | \"\"\"
49 |
50 | import streamlit as st
51 | from PIL import Image, ImageFilter
52 | """
53 |
54 | codex_args.temperature=0.0
55 | codex_args.max_tokens=500
56 | codex_args.frequency_penalty=0.0
57 | codex_args.presence_penalty=0
58 | codex_args.best_of=2
59 |
60 | # Uncommment to get an an "execute" button
61 | output_controls.execute_button = "🎈 Execute Code"
62 |
63 |
64 | ###############################################
65 | # An app to generate firstname-lastname pairs #
66 | ###############################################
67 |
68 | [modes.name_generator]
69 |
70 | title = "👶 Name Generator app"
71 |
72 | input_code = """
73 | \"\"\"
74 | 1. Create and display a list of first names in Streamlit
75 | 2. Create and display a list of last names in Streamlit
76 | 3. Combine them randomly into a list of 10 full names in Streamlit
77 | 4. plot the first names' length and last names' length in 2 plotly bar charts.
78 | \"\"\"
79 | """
80 |
81 | codex_args.temperature=0.0
82 | codex_args.max_tokens=1000
83 | codex_args.frequency_penalty=0.0
84 | codex_args.presence_penalty=0
85 | codex_args.best_of=2
86 |
87 | # Uncommment to get an an "execute" button
88 | output_controls.execute_button = "🎈 Execute Code"
89 |
90 |
91 | #########################################
92 | # An app to generate Python docstrings. #
93 | #########################################
94 |
95 | [modes.docstring_generator]
96 |
97 | title = "💎 Python docstring generator"
98 |
99 | input_code = """
100 | \"\"\"
101 | # Python 3.8
102 |
103 | def randomly_split_dataset(folder, filename, split_ratio=[0.8, 0.2]):
104 | df = pd.read_json(folder + filename, lines=True)
105 | train_name, test_name = "train.jsonl", "test.jsonl"
106 | df_train, df_test = train_test_split(df, test_size=split_ratio[1], random_state=42)
107 | df_train.to_json(folder + train_name, orient='records', lines=True)
108 | df_test.to_json(folder + test_name, orient='records', lines=True)
109 | randomly_split_dataset('finetune_data/', 'dataset.jsonl')
110 |
111 | # An elaborate, high quality Python docstring generator for the above function:
112 |
113 | \"\"\"
114 | """
115 |
116 | codex_args.temperature=0.0
117 | codex_args.max_tokens=150
118 | codex_args.frequency_penalty=0.0
119 | codex_args.presence_penalty=0
120 | codex_args.stop=["#", '"""']
121 | codex_args.best_of=2
122 |
123 | # Uncommment to get a download button
124 | output_controls.download_button = "📥 Download Python docstring"
125 |
126 |
127 | ###########################################
128 | # An app to convert javacript into Python #
129 | ###########################################
130 |
131 | [modes.javascript_to_python]
132 | title = "☕️ JavaScript to Python"
133 |
134 | input_code = """
135 | \"\"\"
136 |
137 | #JavaScript to Python:
138 | JavaScript:
139 | dogs = ["bill", "joe", "carl"]
140 | car = []
141 | dogs.forEach((dog) {
142 | car.push(dog);
143 | });
144 |
145 | Python:
146 |
147 | \"\"\"
148 | """
149 |
150 | codex_args.temperature=0.0
151 | codex_args.max_tokens=64
152 | codex_args.frequency_penalty=0.0
153 | codex_args.presence_penalty=0
154 | codex_args.stop=["#"]
155 |
156 | # Uncommment to get a download button
157 | output_controls.download_button = "📥 Download JavaScript to Python"
158 |
159 |
160 | ###########################################
161 | # An app to fix a bug in some Python code #
162 | ###########################################
163 |
164 | [modes.fix_bugs]
165 |
166 | title = "🐛 Fix bugs in Python"
167 |
168 | input_code = """
169 | \"\"\"
170 |
171 | ##### Fix bugs in the below function
172 |
173 | ### Buggy Python
174 | import Random
175 | a = random.randint(1,12)
176 | b = random.randint(1,12)
177 | for i in range(10):
178 | question = "What is "+a+" x "+b+"? "
179 | answer = input(question)
180 | if answer = a*b
181 | print (Well done!)
182 | else:
183 | print("No.")
184 |
185 | ### Fixed Python
186 |
187 | \"\"\"
188 | """
189 |
190 | codex_args.temperature=0.0
191 | codex_args.max_tokens=182
192 | codex_args.frequency_penalty=0.0
193 | codex_args.presence_penalty=0
194 | codex_args.stop=["###", "#"]
195 |
196 | # Uncommment to get a download button
197 | output_controls.download_button = "📥 Download fixed Python code "
198 |
199 |
200 | ########################################
201 | # An app let you do whatever you want. #
202 | ########################################
203 |
204 | [modes.blank]
205 |
206 | title = "🤷 Blank"
207 |
208 | input_code = """
209 | \"\"\"
210 | \"\"\"
211 |
212 | import streamlit as st
213 | """
214 |
215 | codex_args.temperature=0.5
216 | codex_args.max_tokens=500
217 | codex_args.frequency_penalty=0.05
218 | codex_args.presence_penalty=0
219 | codex_args.best_of=2
220 |
221 |
222 | # Uncommment to get an an "execute" button
223 | output_controls.execute_button = "🎈 Execute Code"
224 |
225 |
--------------------------------------------------------------------------------
/mouse.gif:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/streamlit/example-app-streamlit-codex/93e0f90c5ed671830f666da90d5ebf2212e7e0e4/mouse.gif
--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | streamlit
2 | openai
3 | yfinance
4 | plotly
5 | click==8
6 |
--------------------------------------------------------------------------------
/streamlit_app.py:
--------------------------------------------------------------------------------
1 | import streamlit as st
2 | from streamlit_ace import st_ace
3 | import toml
4 | import openai
5 |
6 |
7 | @st.experimental_memo(suppress_st_warning=True) # type: ignore
8 | def complete_code(input_code: str, codex_args: dict) -> str:
9 | """Call OpenAI Codex to convert input code into output code."""
10 | # Load your API key from an environment variable or secret management service
11 | openai.api_key = st.secrets["OPENAI_API_KEY"]
12 |
13 | # Display a funny mouse moving animation.
14 | mouse_gif = st.columns(3)[1].image("mouse.gif")
15 |
16 | # Complete the code
17 | try:
18 | response = openai.Completion.create(
19 | engine="davinci-codex",
20 | prompt=input_code,
21 | echo=True,
22 | **codex_args,
23 | )
24 | return response["choices"][0]["text"]
25 | finally:
26 | mouse_gif.empty()
27 |
28 |
29 | def rows_of_three(width_ratio=7):
30 | """A generator of containers aranged in rows of three."""
31 | while True:
32 | for col in st.columns([width_ratio, 1, width_ratio, 1, width_ratio])[::2]:
33 | yield col
34 |
35 |
36 | def main():
37 | """Execution starts here."""
38 | # Header
39 | title = "Streamlit App Builder"
40 | st.set_page_config(page_title=title, page_icon="✨") # type: ignore
41 | # st.image("logoNew.png")
42 | st.image("logo.png")
43 |
44 | # These two TOML files describe possible modes and codex parameters, respectively.
45 | codex_params = toml.load("codex_params.toml")["codex_params"]
46 | modes = list(toml.load("modes.toml")["modes"].values())
47 |
48 | def reset_state():
49 | """Reset the state to mode defaults."""
50 | defaults = {key: input["default_value"] for key, input in codex_params.items()}
51 | st.session_state.update(defaults)
52 | st.session_state.update(st.session_state.mode["codex_args"])
53 | st.session_state.execute_code = False
54 | st.session_state.output_code = ""
55 | st.session_state.state_initialized = True
56 |
57 | # Let the user select an input mode
58 | get_title = lambda mode: mode["title"]
59 | mode = st.selectbox(
60 | "Code sample", modes, format_func=get_title, on_change=reset_state, key="mode"
61 | )
62 | if not st.session_state.get("state_initialized"):
63 | reset_state()
64 |
65 | # Let the user set the input code.
66 | input_code = st_ace(value=mode["input_code"], language="python", auto_update=True)
67 |
68 | # Draw a grid of inputs.
69 | codex_args = {}
70 | with st.form("Codex settings"):
71 | st.caption("Codex settings")
72 | for (key, input), container in zip(codex_params.items(), rows_of_three()):
73 | widget_func = getattr(container, input["input_type"])
74 | codex_args[key] = widget_func(label=key, key=key, **input["input_params"])
75 |
76 | # Empty lists cannot be passed in as codex_args. This only applies to "stop".
77 | if len(codex_args["stop"]) == 0:
78 | del codex_args["stop"]
79 |
80 | # Clicking the button Unchecks the "execute_code" checkbox.
81 | def uncheck_execute_code():
82 | st.session_state.execute_code = False
83 |
84 | if st.form_submit_button("Generate Code", on_click=uncheck_execute_code):
85 | st.session_state.output_code = complete_code(input_code, codex_args)
86 |
87 | output_code = st.session_state.get("output_code", "")
88 | output_code = st_ace(value=output_code, language="python", auto_update=True)
89 |
90 | # The "output_controls" dict defines any final output controls.
91 | output_controls = mode.get("output_controls", {})
92 |
93 | # If "execute_button" is defined, then display it.
94 | if "execute_button" in output_controls:
95 | if st.checkbox(output_controls["execute_button"], key="execute_code"):
96 | exec(output_code, globals())
97 |
98 | # If "download_button" is defined, then display it.
99 | if "download_button" in output_controls:
100 | st.download_button(output_controls["download_button"], output_code)
101 |
102 | st.caption(
103 | "Created with [Streamlit](https://streamlit.io/) and "
104 | "[OpenAI Codex](https://openai.com/blog/openai-codex/). "
105 | "Get your own [Codex API key](https://openai.com/blog/api-no-waitlist/)!"
106 | )
107 |
108 |
109 | if __name__ == "__main__":
110 | main()
111 |
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