ai-prompter

Name: ai-prompter
Author: lfnovo

27stars4forks

How to install ai-prompter?

lfnovo/ai-prompter

$git clone https://github.com/lfnovo/ai-prompter

Installs into the current project.

Summary

Stop hardcoding prompts. Start building maintainable, reusable AI prompt templates.

Files · 1

View on GitHub

README.md

1	# AI Prompter: Professional Prompt Management Made Simple
2
3	Stop hardcoding prompts. Start building maintainable, reusable AI prompt templates.
4
5	AI Prompter is a powerful Python library that transforms how you manage AI prompts. Using familiar Jinja2 templating, you can create dynamic, reusable prompts that scale with your applications - whether you're building chatbots, content generators, or complex AI workflows.
6
7	## Why AI Prompter?
8
9	- 🎯 Template-Driven: Write prompts once, reuse everywhere with dynamic variables
10	- 📁 Organized: Keep prompts in separate files, organized and version-controlled
11	- 🔧 Flexible: Works with any LLM provider - OpenAI, Anthropic, local models
12	- ⚡ LangChain Ready: Seamless integration with LangChain workflows
13	- 🏗️ Structured Output: Built-in support for JSON, Pydantic models, and custom parsers
14	- 🎨 Modular: Include and compose templates for complex prompt engineering
15
16	## Quick Start
17
18	### Installation
19
20	```bash
21	pip install ai-prompter
22
23	# For LangChain integration
24	pip install ai-prompter[langchain]
25	```
26
27	### 30-Second Example
28
29	```python
30	from ai_prompter import Prompter
31
32	# Create a simple prompt template
33	prompter = Prompter(template_text="""
34	You are a {{ role }} expert. Help the user with their {{ task_type }} question.
35
36	User Question: {{ question }}
37
38	Please provide a {{ tone }} and detailed response.
39	""")
40
41	# Use it with different scenarios
42	response = prompter.render({
43	"role": "Python programming",
44	"task_type": "debugging",
45	"question": "Why is my list comprehension not working?",
46	"tone": "friendly"
47	})
48
49	print(response)
50	# Output: You are a Python programming expert. Help the user with their debugging question...
51	```
52
53	### File-Based Templates (Recommended)
54
55	Create a `prompts/` folder in your project and save templates as `.jinja` files:
56
57	```jinja
58	<!-- prompts/code_review.jinja -->
59	You are an experienced {{ language }} developer conducting a code review.
60
61	Code to review:
62	```{{ language }}
63	{{ code }}
64	```
65
66	Focus on:
67	{% for focus_area in focus_areas %}
68	- {{ focus_area }}
69	{% endfor %}
70
71	Provide specific, actionable feedback with examples.
72	```
73
74	```python
75	from ai_prompter import Prompter
76
77	# Load the template by name (finds prompts/code_review.jinja automatically)
78	reviewer = Prompter(prompt_template="code_review")
79
80	prompt = reviewer.render({
81	"language": "python",
82	"code": "def calculate(x, y): return x + y",
83	"focus_areas": ["error handling", "documentation", "performance"]
84	})
85	```
86
87	## Features
88
89	- Define prompts as Jinja templates.
90	- Load default templates from `src/ai_prompter/prompts`.
91	- Override templates via `PROMPTS_PATH` environment variable.
92	- Automatic project root detection for prompt templates.
93	- Render prompts with arbitrary data or Pydantic models.
94	- Export to LangChain `ChatPromptTemplate`.
95	- Automatic output parser integration for structured outputs.
96
97	## Installation & Setup
98
99	### Basic Installation
100
101	```bash
102	# Install from PyPI
103	pip install ai-prompter
104
105	# Or using uv (recommended for Python projects)
106	uv add ai-prompter
107	```
108
109	### With LangChain Integration
110
111	```bash
112	pip install ai-prompter[langchain]
113	# or
114	uv add ai-prompter[langchain]
115	```
116
117	### Development Installation
118
119	```bash
120	git clone https://github.com/lfnovo/ai-prompter
121	cd ai-prompter
122	uv sync # installs with all dev dependencies
123	```
124
125	## Configuration
126
127	Configure a custom template path by creating a `.env` file in the project root:
128
129	```dotenv
130	PROMPTS_PATH=path/to/custom/templates
131	```
132
133	## Usage
134
135	### Basic Usage
136
137	```python
138	from ai_prompter import Prompter
139
140	# Initialize with a template name
141	prompter = Prompter('my_template')
142
143	# Render a prompt with variables
144	prompt = prompter.render({'variable': 'value'})
145	print(prompt)
146	```
147
148	### Custom Prompt Directory
149
150	You can specify a custom directory for your prompt templates using the `prompt_dir` parameter:
151
152	```python
153	prompter = Prompter(template_text='Hello {{ name }}!', prompt_dir='/path/to/your/prompts')
154	```
155
156	### Using Environment Variable for Prompt Path
157
158	Se

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ai-prompter

27stars4forks

View on GitHub

How to install ai-prompter?

lfnovo/ai-prompter

$git clone https://github.com/lfnovo/ai-prompter

Installs into the current project.

Summary

Stop hardcoding prompts. Start building maintainable, reusable AI prompt templates.

Files · 1

View on GitHub

README.md

1	# AI Prompter: Professional Prompt Management Made Simple
2
3	Stop hardcoding prompts. Start building maintainable, reusable AI prompt templates.
4
5	AI Prompter is a powerful Python library that transforms how you manage AI prompts. Using familiar Jinja2 templating, you can create dynamic, reusable prompts that scale with your applications - whether you're building chatbots, content generators, or complex AI workflows.
6
7	## Why AI Prompter?
8
9	- 🎯 Template-Driven: Write prompts once, reuse everywhere with dynamic variables
10	- 📁 Organized: Keep prompts in separate files, organized and version-controlled
11	- 🔧 Flexible: Works with any LLM provider - OpenAI, Anthropic, local models
12	- ⚡ LangChain Ready: Seamless integration with LangChain workflows
13	- 🏗️ Structured Output: Built-in support for JSON, Pydantic models, and custom parsers
14	- 🎨 Modular: Include and compose templates for complex prompt engineering
15
16	## Quick Start
17
18	### Installation
19
20	```bash
21	pip install ai-prompter
22
23	# For LangChain integration
24	pip install ai-prompter[langchain]
25	```
26
27	### 30-Second Example
28
29	```python
30	from ai_prompter import Prompter
31
32	# Create a simple prompt template
33	prompter = Prompter(template_text="""
34	You are a {{ role }} expert. Help the user with their {{ task_type }} question.
35
36	User Question: {{ question }}
37
38	Please provide a {{ tone }} and detailed response.
39	""")
40
41	# Use it with different scenarios
42	response = prompter.render({
43	"role": "Python programming",
44	"task_type": "debugging",
45	"question": "Why is my list comprehension not working?",
46	"tone": "friendly"
47	})
48
49	print(response)
50	# Output: You are a Python programming expert. Help the user with their debugging question...
51	```
52
53	### File-Based Templates (Recommended)
54
55	Create a `prompts/` folder in your project and save templates as `.jinja` files:
56
57	```jinja
58	<!-- prompts/code_review.jinja -->
59	You are an experienced {{ language }} developer conducting a code review.
60
61	Code to review:
62	```{{ language }}
63	{{ code }}
64	```
65
66	Focus on:
67	{% for focus_area in focus_areas %}
68	- {{ focus_area }}
69	{% endfor %}
70
71	Provide specific, actionable feedback with examples.
72	```
73
74	```python
75	from ai_prompter import Prompter
76
77	# Load the template by name (finds prompts/code_review.jinja automatically)
78	reviewer = Prompter(prompt_template="code_review")
79
80	prompt = reviewer.render({
81	"language": "python",
82	"code": "def calculate(x, y): return x + y",
83	"focus_areas": ["error handling", "documentation", "performance"]
84	})
85	```
86
87	## Features
88
89	- Define prompts as Jinja templates.
90	- Load default templates from `src/ai_prompter/prompts`.
91	- Override templates via `PROMPTS_PATH` environment variable.
92	- Automatic project root detection for prompt templates.
93	- Render prompts with arbitrary data or Pydantic models.
94	- Export to LangChain `ChatPromptTemplate`.
95	- Automatic output parser integration for structured outputs.
96
97	## Installation & Setup
98
99	### Basic Installation
100
101	```bash
102	# Install from PyPI
103	pip install ai-prompter
104
105	# Or using uv (recommended for Python projects)
106	uv add ai-prompter
107	```
108
109	### With LangChain Integration
110
111	```bash
112	pip install ai-prompter[langchain]
113	# or
114	uv add ai-prompter[langchain]
115	```
116
117	### Development Installation
118
119	```bash
120	git clone https://github.com/lfnovo/ai-prompter
121	cd ai-prompter
122	uv sync # installs with all dev dependencies
123	```
124
125	## Configuration
126
127	Configure a custom template path by creating a `.env` file in the project root:
128
129	```dotenv
130	PROMPTS_PATH=path/to/custom/templates
131	```
132
133	## Usage
134
135	### Basic Usage
136
137	```python
138	from ai_prompter import Prompter
139
140	# Initialize with a template name
141	prompter = Prompter('my_template')
142
143	# Render a prompt with variables
144	prompt = prompter.render({'variable': 'value'})
145	print(prompt)
146	```
147
148	### Custom Prompt Directory
149
150	You can specify a custom directory for your prompt templates using the `prompt_dir` parameter:
151
152	```python
153	prompter = Prompter(template_text='Hello {{ name }}!', prompt_dir='/path/to/your/prompts')
154	```
155
156	### Using Environment Variable for Prompt Path
157
158	Se

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6 picks

Type