Add linter (will break as we have style issues)

.github/workflows/linter.yaml

@@ -0,0 +1,18 @@
+name: Lint
+on: push
+jobs:
+  flake8_py3:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Setup Python
+        uses: actions/setup-python@v1
+      - name: Checkout PyTorch
+        uses: actions/checkout@master
+      - name: Install flake8
+        run: pip install flake8 wemake-python-styleguide
+      - name: Run flake8
+        uses: suo/flake8-github-action@releases/v1
+        with:
+          checkName: 'flake8_py3'   # NOTE: this needs to be the same as the job name
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

examples/agents/biochemist.py

@@ -1,41 +1,45 @@
-import os
-from log10.anthropic import Anthropic
-from log10.llm import NoopLLM
-from log10.agents.camel import camel_agent
+"""Example of a biochemist agent using the camel agent framework."""
+
+import anthropic
+import openai
 from dotenv import load_dotenv
 
-from log10.openai import OpenAI
+from log10.agents.camel import camel_agent
+from log10.anthropic import Anthropic
+from log10.llm import NoopLLM
 from log10.load import log10
+from log10.openai import OpenAI
 
 load_dotenv()
 
-# Select one of OpenAI or Anthropic models
-# model = "noop"
-model = "gpt-3.5-turbo-16k"
-# model = "claude-1"
+# Select one of OpenAI or Anthropic models with "claude-1" or "gpt-3.5-turbo"
+model = 'gpt-3.5-turbo-16k'
 max_turns = 30
 
 llm = None
 summary_model = None
-if "claude" in model:
-    import anthropic
+if 'claude' in model:
     log10(anthropic)
-    summary_model = "claude-1-100k"
-    llm = Anthropic({"model": model})
-elif model == "noop":
+    summary_model = 'claude-1-100k'
+    llm = Anthropic({'model': model})
+elif model == 'noop':
     summary_model = model
     llm = NoopLLM()
 else:
-    import openai
     log10(openai)
-    summary_model = "gpt-3.5-turbo-16k"
-    llm = OpenAI({"model": model})
+    summary_model = 'gpt-3.5-turbo-16k'
+    llm = OpenAI({'model': model})
 
 # example calls from playground (select 1)
 camel_agent(
-    user_role="Poor PhD Student",
-    assistant_role="Experienced Computational Chemist",
-    task_prompt="Perform a molecular dynamics solution of a molecule: CN1CCC[C@H]1c2cccnc2. Design and conduct a 100 ns molecular dynamics simulation of the molecule CN1CCC[C@H]1c2cccnc2 in an explicit solvent environment using the CHARMM force field and analyze the conformational changes and hydrogen bonding patterns over time",
+    user_role='Poor PhD Student',
+    assistant_role='Experienced Computational Chemist',
+    task_prompt="""
+Perform a molecular dynamics solution of a molecule: CN1CCC[C@H]1c2cccnc2.
+Design and conduct a 100 ns molecular dynamics simulation of the molecule
+CN1CCC[C@H]1c2cccnc2 in an explicit solvent environment using the CHARMM
+force field and analyze the conformational changes and hydrogen bonding
+patterns over time""",
     summary_model=summary_model,
     max_turns=max_turns,
     llm=llm,

examples/agents/code_optimizer.py

@@ -1,44 +1,69 @@
-import os
+"""Code optimizer agent example."""
+# flake8: noqa
+
+import anthropic
+import openai
+
+from log10.agents.camel import camel_agent
 from log10.anthropic import Anthropic
+from log10.evals import compile
 from log10.llm import NoopLLM
 from log10.load import log10
-from log10.evals import compile
-from log10.agents.camel import camel_agent
 from log10.openai import OpenAI
 from log10.tools import code_extractor
 
-# Select one of OpenAI or Anthropic models
-model = "gpt-3.5-turbo-16k"
-# model = "claude-1"
-# model = "noop"
+# Select one of OpenAI or Anthropic models with "claude-1" or "gpt-3.5-turbo"
+model = 'gpt-3.5-turbo-16k'
 max_turns = 10
 
 llm = None
 summary_model = None
 extraction_model = None
-if "claude" in model:
-    import anthropic
+if 'claude' in model:
     log10(anthropic)
-    summary_model = "claude-1-100k"
-    extraction_model = "claude-1-100k"
-    llm = Anthropic({"model": model})
-elif model == "noop":
+    summary_model = 'claude-1-100k'
+    extraction_model = 'claude-1-100k'
+    llm = Anthropic({'model': model})
+elif model == 'noop':
     summary_model = model
     extraction_model = model
     llm = NoopLLM()
 else:
-    import openai
     log10(openai)
-    summary_model = "gpt-3.5-turbo-16k"
-    extraction_model = "gpt-4"
-    llm = OpenAI({"model": model})
-
+    summary_model = 'gpt-3.5-turbo-16k'
+    extraction_model = 'gpt-4'
+    llm = OpenAI({'model': model})
 
 # example calls from playground (select 1)
 user_messages, assistant_messages = camel_agent(
-    user_role="C developer",
-    assistant_role="Cybersecurity expert",
-    task_prompt='Correct the following code.\n\n#include <stdio.h>\n#include <string.h>\n\nint main() {\n    char password[8];\n    int granted = 0;\n\n    printf("Enter password: ");\n    scanf("%s", password);\n\n    if (strcmp(password, "password") == 0) {\n        granted = 1;\n    }\n\n    if (granted) {\n        printf("Access granted.\\n");\n    } else {\n        printf("Access denied.\\n");\n    }\n\n    return 0;\n}',
+    user_role='C developer',
+    assistant_role='Cybersecurity expert',
+    # noqa: WPS323 WPS342
+    task_prompt="""
+Correct the following code.
+
+#include <stdio.h>
+#include <string.h>
+
+int main() {
+    char password[8];
+    int granted = 0;
+
+    printf("Enter password: ");
+    scanf("%s", password);
+    if (strcmp(password, "password") == 0) {
+        granted = 1;
+    }
+
+    if (granted) {
+        printf("Access granted.\\n");
+    } else {
+        printf("Access denied.\\n");
+    }
+
+    return 0;
+}
+""",
     summary_model=summary_model,
     max_turns=max_turns,
     llm=llm,
@@ -47,13 +72,13 @@
 full_response = assistant_messages[-1].content
 
 # Next extract just the C code
-code = code_extractor(full_response, "C", extraction_model, llm=llm)
-print(f"Extracted code\n###\n{code}")
+code = code_extractor(full_response, 'C', extraction_model, llm=llm)
+print(f'Extracted code\n###\n{code}')
 
 # Evaluate if the code compiles
 result = compile(code)
 if result is True:
-    print("Compilation successful")
+    print('Compilation successful')
 else:
-    print("Compilation failed with error:")
+    print('Compilation failed with error:')
     print(result[1])

examples/agents/coder.py

@@ -1,41 +1,41 @@
-import os
+"""Agent that can code in Python and trade stocks."""
+
+import anthropic
+import openai
+from dotenv import load_dotenv
+
+from log10.agents.camel import camel_agent
 from log10.anthropic import Anthropic
 from log10.llm import NoopLLM
 from log10.load import log10
-from log10.agents.camel import camel_agent
-from dotenv import load_dotenv
-
 from log10.openai import OpenAI
 
 load_dotenv()
 
-# Select one of OpenAI or Anthropic models
-model = "gpt-3.5-turbo-16k"
-# model = "claude-1"
-# model = "noop"
+
+# Select one of OpenAI or Anthropic models with "claude-1" or "gpt-3.5-turbo"
+model = 'gpt-3.5-turbo-16k'
 max_turns = 30
 
 llm = None
 summary_model = None
-if "claude" in model:
-    import anthropic
+if 'claude' in model:
     log10(anthropic)
-    summary_model = "claude-1-100k"
-    llm = Anthropic({"model": model})
-elif model == "noop":
+    summary_model = 'claude-1-100k'
+    llm = Anthropic({'model': model})
+elif model == 'noop':
     summary_model = model
     llm = NoopLLM()
 else:
-    import openai
     log10(openai)
-    summary_model = "gpt-3.5-turbo-16k"
-    llm = OpenAI({"model": model})
+    summary_model = 'gpt-3.5-turbo-16k'
+    llm = OpenAI({'model': model})
 
 # example calls from playground (select 1)
 camel_agent(
-    user_role="Stock Trader",
-    assistant_role="Python Programmer",
-    task_prompt="Develop a trading bot for the stock market",
+    user_role='Stock Trader',
+    assistant_role='Python Programmer',
+    task_prompt='Develop a trading bot for the stock market',
     summary_model=summary_model,
     max_turns=max_turns,
     llm=llm,

examples/agents/cybersecurity_expert.py

@@ -1,40 +1,43 @@
-import os
+
+
+from dotenv import load_dotenv
+
+from log10.agents.camel import camel_agent
 from log10.anthropic import Anthropic
 from log10.llm import NoopLLM
 from log10.load import log10
-from log10.agents.camel import camel_agent
-from dotenv import load_dotenv
-
 from log10.openai import OpenAI
 
 load_dotenv()
 
 # Select one of OpenAI or Anthropic models
-model = "gpt-3.5-turbo-16k"
+model = 'gpt-3.5-turbo-16k'
 # model = "claude-1"
 # model = "noop"
 max_turns = 30
 
 llm = None
 summary_model = None
-if "claude" in model:
+if 'claude' in model:
     import anthropic
+
     log10(anthropic)
-    summary_model = "claude-1-100k"
-    llm = Anthropic({"model": model})
-elif model == "noop":
+    summary_model = 'claude-1-100k'
+    llm = Anthropic({'model': model})
+elif model == 'noop':
     summary_model = model
     llm = NoopLLM()
 else:
     import openai
+
     log10(openai)
-    summary_model = "gpt-3.5-turbo-16k"
-    llm = OpenAI({"model": model})
+    summary_model = 'gpt-3.5-turbo-16k'
+    llm = OpenAI({'model': model})
 
 # example calls from playground (select 1)
 camel_agent(
-    user_role="C developer",
-    assistant_role="Cybersecurity expert",
+    user_role='C developer',
+    assistant_role='Cybersecurity expert',
     task_prompt='Correct the following code.\n\n#include <stdio.h>\n#include <string.h>\n\nint main() {\n    char password[8];\n    int granted = 0;\n\n    printf("Enter password: ");\n    scanf("%s", password);\n\n    if (strcmp(password, "password") == 0) {\n        granted = 1;\n    }\n\n    if (granted) {\n        printf("Access granted.\\n");\n    } else {\n        printf("Access denied.\\n");\n    }\n\n    return 0;\n}',
     summary_model=summary_model,
     max_turns=max_turns,

examples/agents/email_generator.py

@@ -1,41 +1,44 @@
 import os
+
+from dotenv import load_dotenv
+
+from log10.agents.camel import camel_agent
 from log10.anthropic import Anthropic
 from log10.llm import NoopLLM
 from log10.load import log10
-from log10.agents.camel import camel_agent
-from dotenv import load_dotenv
-
 from log10.openai import OpenAI
 
 load_dotenv()
 
 # Select one of OpenAI or Anthropic models
-model = "gpt-3.5-turbo-16k"
+model = 'gpt-3.5-turbo-16k'
 # model = "claude-1"
 # model = "noop"
 max_turns = 30
 
 llm = None
 summary_model = None
-if "claude" in model:
+if 'claude' in model:
     import anthropic
+
     log10(anthropic)
-    summary_model = "claude-1-100k"
-    llm = Anthropic({"model": model})
-elif model == "noop":
+    summary_model = 'claude-1-100k'
+    llm = Anthropic({'model': model})
+elif model == 'noop':
     summary_model = model
     llm = NoopLLM()
 else:
     import openai
+
     log10(openai)
-    summary_model = "gpt-3.5-turbo-16k"
-    llm = OpenAI({"model": model})
+    summary_model = 'gpt-3.5-turbo-16k'
+    llm = OpenAI({'model': model})
 
 # example calls from playground (select 1)
 camel_agent(
-    user_role="Sales email copyeditor",
-    assistant_role="Sales email copywriter",
-    task_prompt="Write a sales email to Pfizer about a new healthcare CRM",
+    user_role='Sales email copyeditor',
+    assistant_role='Sales email copywriter',
+    task_prompt='Write a sales email to Pfizer about a new healthcare CRM',
     summary_model=summary_model,
     max_turns=max_turns,
     llm=llm,