Merge pull request #52 from barnett-yuxiang/main

Update .gitignore, README, and configuration files

.gitignore

@@ -5,8 +5,18 @@
 venv/
 
 # codecontests datasets
+# https://huggingface.co/datasets/talrid/CodeContests_valid_and_test_AlphaCodium/blob/main/codecontests_valid_and_test_processed_alpha_codium.zip
 valid_and_test_processed/
 
 # Python cache files
 **/__pycache__/
+
+# Cache files generated during documentation builds
 docs/.cache/
+
+# IDEA project-specific settings and configuration files
+.idea/
+
+alpha_codium/settings/.secrets.toml
+dataset_output.json
+example.log

README.md

@@ -41,9 +41,14 @@ Many of the principles and best practices we acquired in this work, we believe,
 
 ## Installation
 
-(1) setup a virtual environment and run: `pip install -r requirements.txt`
+(1) setup a virtual environment：
+```bash
+python3 -m venv venv
+source ./venv/bin/activate
+```
+and run: `pip install -r requirements.txt`.
 
-(2) Duplicate the file `alpha_codium/settings/.secrets_template.toml`, rename it as `.secrets.toml`, and fill in your OpenAI API key:
+(2) Duplicate the file `alpha_codium/settings/.secrets_template.toml`, rename it as `alpha_codium/settings/.secrets.toml`, and fill in your OpenAI API key:
 ```
 [openai]
 key = "..."
@@ -87,7 +92,7 @@ to solve the entire dataset with AlphaCodium, from the root folder run:
 ```
 python -m alpha_codium.solve_dataset \
 --dataset_name /path/to/dataset \
---split_name test
+--split_name test \
 --database_solution_path /path/to/output/dir/dataset_output.json
 ```
 
@@ -101,9 +106,9 @@ python -m alpha_codium.solve_dataset \
 
 Once you generate a solution for the entire dataset (valid or test), you can evaluate it by running:
 ```
-python -m alpha_codium.evaluate_dataset\
---dataset_name /path/to/dataset\
---split_name test\
+python -m alpha_codium.evaluate_dataset \
+--dataset_name /path/to/dataset \
+--split_name test \
 --database_solution_path /path/to/output/dir/dataset_output.json
 ```
 

alpha_codium/settings/configuration.toml

@@ -1,7 +1,8 @@
 [config]
 model="gpt-4-0125-preview"
-#model="gpt-4-0613"
-#model = "gpt-3.5-turbo-16k"
+# model="gpt-4o-2024-05-13"
+# model="gpt-4-0613"
+# model="gpt-3.5-turbo-16k"
 frequency_penalty=0.1
 ai_timeout=90 # seconds
 fallback_models =[]
@@ -60,5 +61,5 @@ trace_depth=4
 [code_contests_tester]
 stop_on_first_failure = false
 timeout = 3
-path_to_python_bin = "/usr/bin/python3.9"
-path_to_python_lib = ["/usr/lib", "/usr/lib/python3.9"]
+path_to_python_bin = "./venv/bin/python3.9"
+path_to_python_lib = ["./venv/lib", "./venv/lib/python3.9"]