adding a simplified code generator

CodeGenerator.py

@@ -0,0 +1,10 @@
+import os
+
+from flows.flow_verse import load_class
+repository_id = "martinjosifoski/OpenAIChatAtomicFlow"
+OpenAIChatAtomicFlow = load_class(repository_id, "OpenAIChatAtomicFlow")
+
+
+class CodeGenerator(OpenAIChatAtomicFlow):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)

CodeGenerator.yaml

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+name: "CodeGenerator"
+verbose: True
+description: "A simple demonstration flow that outputs python code"
+
+model_name: "gpt-4"
+generation_parameters:
+  n: 1
+  max_tokens: 3000
+  temperature: 0.3
+
+  model_kwargs:
+    top_p: 0.2
+    frequency_penalty: 0
+    presence_penalty: 0
+
+system_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    Your goal is to provide executable Python code that solves a problem described by the user.
+    The user will provide you with an output format that you will strictly follow.
+  input_variables: []
+  template_format: jinja2
+
+human_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: "{{query}}"
+  input_variables:
+    - "query"
+  template_format: jinja2
+
+query_message_prompt_template:
+  _target_: langchain.PromptTemplate
+  template: |2-
+    # Problem statement
+    {{problem_description}}
+
+    Return Python code that solves the problem. Reply in the following format:
+    ```python
+    {{code_placeholder}}
+    ```
+  input_variables:
+    - "problem_description"
+  partial_variables:
+    code_placeholder: "{{python_code}}"
+  template_format: jinja2
+
+input_data_transformations: []
+input_keys:
+  - "problem_description"
+
+output_data_transformations:
+  - _target_: flows.data_transformations.RegexFirstOccurrenceExtractor
+    regex: '(?<=```python)([\s\S]*?)(?=```)'
+    regex_fallback: '(?<=```)([\s\S]*?)(?=```)'
+    input_key: "raw_response"
+    output_key: "code"
+    strip: True
+    assert_unique: True
+    verbose: True
+output_keys:
+  - "code"