first commit

.gitignore

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+chat.json
+.git.old/
+
+# Byte-compiled / optimized / DLL files
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+*$py.class
+
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+.Python
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+.installed.cfg
+*.egg
+MANIFEST
+
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+
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+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

README.md

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+# Ploppie
+
+A high-level, stupid-simple Pythonic LiteLLM abstraction layer for implementing simple chat workflows, with tools. Supports vision and audio models. Includes facilities for easy (de)serialization of chat histories. 
+
+So stupid that I couldn't come up with a better name.
+
+## Installation
+
+```bash
+pip install ploppie
+```
+
+## Usage
+
+### Simple chat
+```python
+from ploppie import Chat
+
+chat = Chat()
+
+response = chat.system("You are a helpful assistant.") \
+    .user("What is the capital of France?") \
+    .ready()
+
+print(response)
+```
+
+### Chat with tools
+```python
+from ploppie import Chat
+
+chat = Chat()
+
+@chat.tool("Perform mathematical calculations")
+def calculate(expression: "str: The expression to calculate"):
+    return eval(expression)
+
+print(chat.send("What is 2502 * 2502, and 2858 - 28592? Please tell me the results."))
+```
+
+### Chat with vision
+```python
+from ploppie import Chat
+from ploppie.messages import Image
+
+chat = Chat()
+
+response = chat.system("You are a helpful assistant.") \
+    .user(Image(file_handle=open("beautiful_landscape.png", "rb"))) \
+    .ready()
+
+print(response)
+```

SCOPE.md

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+Ploppie is a high-level, stupid-simple Pythonic LiteLLM abstraction layer for implementing simple chat workflows, with tools. No more messing around with dictionaries and JSON, no more OpenAI-specific APIs. Just plain Python.
+
+Supports vision, audio, and any other LiteLLM features.
+
+# Vanilla LiteLLM Example
+
+```python
+from litellm import completion
+
+# Define a system prompt
+system_prompt = "You are a helpful assistant that can perform calculations."
+
+# Define a tool for basic math
+def calculate(expression):
+    try:
+        return str(eval(expression))
+    except:
+        return "Invalid expression"
+
+# Example conversation
+messages = [
+    {"role": "system", "content": system_prompt},
+    {"role": "user", "content": "What is 25 * 4?"}
+]
+
+# Get completion from LiteLLM
+response = completion(
+    model="gpt-4o-mini",
+    messages=messages,
+    functions=[{
+        "name": "calculate",
+        "description": "Perform basic mathematical calculations",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "expression": {
+                    "type": "string",
+                    "description": "The mathematical expression to evaluate"
+                }
+            },
+            "required": ["expression"]
+        }
+    }]
+)
+
+# Print the response
+print(response.choices[0].message)
+```
+
+# Ploppie Example
+```python
+from ploppie import Chat, Tool, System
+
+chat = Chat(model="gpt-4o-mini")
+
+@chat.tool(description="Perform basic mathematical calculations.")
+def calculate(
+    expression: "str: The result of the calculation as a string, or 'Invalid expression' if evaluation fails") -> str:
+    try:
+        return str(eval(expression))
+    except:
+        return "Invalid expression"
+
+chat.system("You are a helpful assistant that can perform calculations.")\
+    .user("What is 25 * 4?")\
+    .ready()
+
+print(_)
+```
+
+# Vision Example
+
+```python
+from ploppie import Chat, System, User, Assistant
+
+chat = Chat(model="gpt-4o-mini")
+
+a = chat.system("Identify the objects in the image.") \
+    .user(Image(content=open("path/to/image.jpg", "rb"))) \
+    .ready()  # Signals chat is ready for interaction
+
+print(a)
+```

TODO.md

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+- [ ] Streaming support
+- [ ] JSON mode
+- [x] Image and file support

examples/chat_test.py

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+from ploppie import Chat
+from ploppie.messages import System
+from ploppie.messages.files import Image
+
+import os
+import re
+from datetime import datetime
+
+if __name__ == "__main__":
+    chat = Chat(model="gpt-4o-mini")
+
+    @chat.dynamic()
+    def dynamic_message():
+        return System("The current time is " + datetime.now().strftime("%H:%M:%S"))
+
+    @chat.tool("Perform mathematical calculations")
+    def calculate(expression: "str: The expression to calculate"):
+        print(f"Calculating {expression}")
+
+        try:
+            return eval(expression)
+        except Exception as e:
+            return f"I'm sorry, I can't calculate that. ({e})"
+
+    while True:
+        input_ = input("<You> ")
+
+        # Parse the input for a file path
+
+        inputs = [input_]
+
+        file_path_match = re.search(r'(?:^|\s)([\'"]?)([a-zA-Z0-9_\-./\\]+\.(png|jpg|jpeg|gif|webp))\1(?:\s|$)', input_)
+        if file_path_match:
+            file_path = file_path_match.group(2)
+
+            if os.path.exists(file_path):
+                print(f"* Found image: {file_path}")
+                image = Image(open(file_path, 'rb'))
+                inputs.append(image)
+            else:
+                chat.system(f"File not found: {file_path} - please inform the user")
+                print(f"* File not found: {file_path}")
+
+        responses = chat.send(inputs)
+
+        for response in responses:
+            print(f"<Ploppie> {response}")

examples/json_test.py

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+from ploppie import Chat
+import random
+
+if __name__ == "__main__":
+    # You can pass any standard LiteLLM parameters to the Chat object
+    chat = Chat(model="gpt-4o-mini", response_format={"type": "json_object"})
+
+    response = chat.system("Take any input and convert it to a sensible JSON object.") \
+        .user("Make a JSON object that represents a cat.") \
+        .ready()
+
+    print(response)

examples/save_test.py

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+import json
+import os
+from ploppie import Chat
+
+if __name__ == "__main__":
+    chat = Chat(model="gpt-4o-mini")
+
+    @chat.tool("Perform mathematical calculations")
+    def calculate(expression: "str: The expression to calculate"):
+        return eval(expression)
+
+    if os.path.exists("chat.json"):
+        with open("chat.json", "r") as f:
+            chat.from_dict(json.load(f))
+
+    while True:
+        input_ = input("<You> ")
+        responses = chat.send(input_)
+
+        for response in responses:
+            print(f"<Ploppie> {response}")
+
+        with open("chat.json", "w") as f:
+            json.dump(chat.to_dict(), f)