refactor: Update code to use prompt.content instead of prompt.prompt Fix installation library path

Author: unclecode

README.md

@@ -22,8 +22,14 @@ pip install git+https://github.com/unclecode/promptuner.git
 
 ### Usage
 
-Here's a basic example of how to use promptuner:
+Here's a basic example of how to use promptuner. First make sure to set your Anthropic Api Key in the environment variable `ANTHROPIC_API_KEY`.
+```
+export ANTHROPIC_API_KEY=YOUR_ANTHROPIC_API_KEY
+```
+
+I use Claude only for generating the prompt, which I found better than other models, however you may try other models as well. Specially the recent ones like `Llama3.1-70b` or `Llama3.1-405b`.
 
+1. Create the Prompt
 ```python
 from promptuner import Prompt
 from promptuner.decorators import *
@@ -50,9 +56,14 @@ prompt.train()
 
 # Print the generated prompt template
 print("Generated Prompt Template:")
-print(prompt.prompt)
-prompt.save("data/email_analysis_prompt.json")
+print(prompt.content)
+prompt.save("email_analysis_prompt.json")
+```
+
+2. Use the Prompt
+You may simply use the generated prompt, replace the generate variables with the actual values and pass the prompt to your favorite model. Another way is to use the `promptuner` library to execute the prompt for you.
 
+```python
 # Sample email content
 EMAIL_CONTENT = """
 From: [email protected]
@@ -71,10 +82,34 @@ John Doe
 Project Manager
 """
 
+prompt Prompt.load("email_analysis_prompt.json")
 # Define class labels
 CLASS_LABELS = "Work-related, Personal, Spam, Urgent, Newsletter, Other"
 
-# Use the prompt to analyze the email
+# First Method: Use the generated prompt directly
+new_prompt = prompt.content.replace("{{EMAIL_CONTENT}}", EMAIL_CONTENT)
+new_prompt = prompt.content.replace("{{CLASS_LABELS}}", CLASS_LABELS)
+from openai import OpenAI
+client = OpenAI()
+
+completion = client.chat.completions.create(
+  model="gpt-4o",
+  messages=[
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": new_prompt}
+  ]
+)
+
+answer = completion.choices[0].message
+tag = "analysis"
+pattern = f"<{tag}>(.*?)</{tag}>"
+match = re.search(pattern, answer, re.DOTALL)
+if match:
+    result = match.group(1).strip()
+print("\nEmail Analysis Results:")
+print(result)
+
+# Second Method: Use the promptuner library to execute the prompt
 response = prompt(
     variable_values={
         "EMAIL_CONTENT": EMAIL_CONTENT,
@@ -94,7 +129,9 @@ print("\nTags:")
 for tag, content in response['tags'].items():
     if tag != "analysis":
         print(f"<{tag}>\n{content}\n</{tag}>")
+
 ```
+
 For more examples check the `docs/examples` folder.
 
 ## Stay Tuned

promptuner/__init__.py

@@ -16,7 +16,7 @@ def __init__(self, task: str, variables: List[str] = None, metaprompt: str = "de
         self.task = task
         self.variables = variables or []
         self.decorators = []
-        self.prompt = None
+        self.content = None
         self.token_count = None
         self.model_name = model_name or MODEL_NAME
         self.answer_tag = kwargs.get("answer_tag", "result")
@@ -29,8 +29,12 @@ def __init__(self, task: str, variables: List[str] = None, metaprompt: str = "de
 
         # Load metaprompt
         __location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))
+        # Load metaprompt
+        package_dir = os.path.dirname(os.path.abspath(__file__))
+        metaprompts_dir = os.path.join(package_dir, "metaprompts")
+        metaprompt_file = os.path.join(metaprompts_dir, f"{metaprompt}.md")
         try:
-            with open(os.path.join(__location__, "metaprompts", f"{metaprompt}.md"), "r") as file:
+            with open(metaprompt_file, "r") as file:
                 self.metaprompt = file.read()
         except FileNotFoundError:
             raise ValueError(f"Metaprompt file '{metaprompt}.md' not found")
@@ -78,16 +82,16 @@ def train(self,  **kwargs):
         remove_empty_tags = lambda x: re.sub(r"<(\w+)></\1>$", "", x)
 
         between_tags = extract_between_tags("Instructions", metaprompt_response)[0]
-        self.prompt = remove_empty_tags(between_tags).strip()
+        self.content = remove_empty_tags(between_tags).strip()
 
         pattern = r"{(.*)}"
-        self.variables = list(set(re.findall(pattern, self.prompt)))
+        self.variables = list(set(re.findall(pattern, self.content)))
 
     def run(self, variable_values: Dict[str, str], model_name: str = None, api_key: str = None, **kwargs) -> Union[str, Dict]:
         return self(variable_values, model_name, api_key, **kwargs)
 
     def __call__(self, variable_values: Dict[str, str], model_name: str = None, api_key: str = None, **kwargs) -> Union[str, Dict]:
-        if not self.prompt:
+        if not self.content:
             raise ValueError("Prompt hasn't been trained yet. Call the train() method first.")
 
         prompt = self.replace_variables(variable_values)
@@ -113,7 +117,7 @@ def __call__(self, variable_values: Dict[str, str], model_name: str = None, api_
         return {"answer": content, "tags": tags_contnet, "raw": response.choices[0].message.content}
 
     def replace_variables(self, variable_values: Dict[str, str]) -> str:
-        prompt_with_variables = self.prompt
+        prompt_with_variables = self.content
         for variable, value in variable_values.items():
             if variable not in self.variables:
                 continue
@@ -122,14 +126,14 @@ def replace_variables(self, variable_values: Dict[str, str]) -> str:
 
     def save(self, path: str):
         with open(path, "w") as file:
-            json.dump({"task": self.task, "prompt": self.prompt, "variables": self.variables}, file)
+            json.dump({"task": self.task, "prompt": self.content, "variables": self.variables}, file)
 
     @staticmethod
     def load(path: str) -> "Prompt":
         with open(path, "r") as file:
             data = json.load(file)
             prompt = Prompt(data["task"])
-            prompt.prompt = data["prompt"]
+            prompt.content = data["prompt"]
             prompt.variables = data["variables"]
             return prompt
 

promptuner/docs/examples/email_classifier.py

@@ -37,7 +37,7 @@
 
     # Print the generated prompt template
     print("Generated Prompt Template:")
-    print(prompt.prompt)
+    print(prompt.content)
     prompt.save("data/email_analysis_prompt.json")
 
     # Sample email content
@@ -90,4 +90,4 @@
     # Optionally, load the saved prompt
     # loaded_prompt = Prompt.load("data/email_analysis_prompt.json")
     # print("\nLoaded Prompt Template:")
-    # print(loaded_prompt.prompt)
+    # print(loaded_prompt.content)

promptuner/docs/examples/knowledge_graph.py

@@ -32,7 +32,7 @@
 
     # Print the generated prompt template
     print("Generated Prompt Template:")
-    print(prompt.prompt)
+    print(prompt.content)
     prompt.save("data/knowledge_graph_prompt.json")
 
     # Sample passage

promptuner/docs/examples/summarizer.py

@@ -18,7 +18,7 @@
 
     # Print the generated prompt template
     print("Generated Prompt Template:")
-    print(prompt.prompt)
+    print(prompt.content)
 
     # Load a sample passage
     SAMPLE_PASSAGE = """
@@ -54,4 +54,4 @@
     # Optionally, load the saved prompt
     # loaded_prompt = Prompt.load("data/saved_prompt.json")
     # print("\nLoaded Prompt Template:")
-    # print(loaded_prompt.prompt)
+    # print(loaded_prompt.content)

promptuner/docs/quickstart.py

@@ -18,7 +18,7 @@
 # Create prompt
 promptuner = promptuner()
 prompt = promptuner(TASK, variables)
-print(prompt.prompt)    
+print(prompt.content)    
 
 # Execute prompt    
 print(prompt.replace_variables({"PASSAGE": SAMPLE_PASSAGE}))
@@ -32,4 +32,4 @@
 # Test saving and loading prompt
 prompt.save(__current__ / "prompt.json")
 prompt = Prompt.load(__current__ / "prompt.json")
-print(prompt.prompt)
+print(prompt.content)

server/api.py

@@ -48,7 +48,7 @@ async def generate_prompt(request: PromptRequest):
         # Train the prompt
         prompt.train()
 
-        return PromptResponse(prompt=prompt.prompt, token_count=prompt.token_count)
+        return PromptResponse(prompt=prompt.content, token_count=prompt.token_count)
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
 

setup.py

@@ -31,6 +31,9 @@
     ],
     packages=find_packages(),
     include_package_data=True,
+    package_data={
+        'promptuner': ['metaprompts/*.md'],
+    },
     install_requires=required,
     entry_points={
         "console_scripts": [