update to v0.3 - add anthropic, rework params, rename class

.gitignore

@@ -4,3 +4,4 @@ autochat/__pycache__/
 build/
 dist/
 .DS_Store
+draft

README.md

@@ -1,8 +1,8 @@
 # AutoChat
 
-AutoChat is an assistant interface to OpenAI and alternative providers, to simplify the process of creating interactive agents.
+AutoChat is an assistant library, that supports OpenAI/Anthropic, to simplify the process of creating interactive agents.
 
-- **ChatGPT Class**: Conversation wrapper to store instruction, context and messages histories.
+- **Autochat Class**: Conversation wrapper to store instruction, context and messages histories.
 - **Message Class**: Message wrapper to handle format/parsing automatically.
 - **Function Calls**: Capability to handle function calls within the conversation, allowing complex interactions and responses.
 - **Template System**: A straightforward text-based template system for defining the behavior of the chatbot, making it easy to customize its responses and actions.
@@ -20,14 +20,45 @@ Please note that this package requires Python 3.6 or later.
 ## Simple Example
 
 ```python
-> from autochat import ChatGPT
-> chat = ChatGPT(instruction="You are a parot")
+> from autochat import Autochat
+> chat = Autochat(instruction="You are a parot")
 > chat.ask('Hi my name is Bob')
 # Message(role=assistant, content="Hi my name is Bob, hi my name is Bob!")
 > chat.ask('Can you tell me my name?')
 # Message(role=assistant, content="Your name is Bob, your name is Bob!")
 ```
 
+## Function Calls Handling
+
+The library supports function calls, handling the back-and-forth between the system and the assistant.
+
+```python
+from autochat import Autochat, Message
+import json
+
+def label_item(category: str, from_response: Message):
+    # TODO: Implement function
+    raise NotImplementedError()
+
+with open("./examples/function_label.json") as f:
+    FUNCTION_LABEL_ITEM = json.load(f)
+
+classifierGPT = Autochat.from_template("./examples/classify_template.txt")
+classifierGPT.add_function(label_item, FUNCTION_LABEL_ITEM)
+
+text = "The new iPhone is out"
+for message in classifierGPT.run_conversation(text):
+    print(message.to_markdown())
+
+# > ## assistant
+# > It's about \"Technology\" since it's about a new iPhone.
+# > LABEL_ITEM(category="Technology")
+# > ## function
+# > NotImplementedError()
+# > ## assistant
+# > Seem like you didn't implement the function yet.
+```
+
 ## Template System
 
 We provide a simple template system for defining the behavior of the chatbot, using markdown-like syntax.
@@ -52,52 +83,31 @@ Your name is Bob, your name is Bob!
 You can then load the template file using the `from_template` method:
 
 ```python
-parrotGPT = ChatGPT.from_template("./parrot_template.txt")
+parrotGPT = Autochat.from_template("./parrot_template.txt")
 ```
 
-The template system also supports function calls. Check out the [examples/classify.py](examples/classify.py) for a complete example.
-
-## Function Calls Handling
+The template system also supports function calls. Check out the [examples/demo_label.py](examples/demo_label.py) for a complete example.
 
-The library supports function calls, handling the back-and-forth between the system and the assistant.
-
-```python
-from autochat import ChatGPT, Message
-import json
+## Use different API providers (only anthropic and openai are supported for now)
 
-def label_item(category: str, from_response: Message):
-    # TODO: Implement function
-    raise NotImplementedError()
+Default provider is openai.
 
-with open("./examples/function_label.json") as f:
-    FUNCTION_LABEL_ITEM = json.load(f)
+Anthropic:
 
-classifierGPT = ChatGPT.from_template("./examples/classify_template.txt")
-classifierGPT.add_function(label_item, FUNCTION_LABEL_ITEM)
-
-text = "The new iPhone is out"
-for message in classifierGPT.run_conversation(text):
-    print(message.to_markdown())
-
-# > ## assistant
-# > It's about \"Technology\" since it's about a new iPhone.
-# > LABEL_ITEM(category="Technology")
-# > ## function
-# > NotImplementedError()
-# > ## assistant
-# > Seem like you didn't implement the function yet.
+```python
+chat = Autochat(provider="anthropic")
 ```
 
 ## Environment Variables
 
-The `AUTOCHAT_DEFAULT_MODEL` environment variable specifies the model to use. If not set, it defaults to "gpt-4-turbo".
+The `AUTOCHAT_MODEL` environment variable specifies the model to use. If not set, it defaults to "gpt-4-turbo".
 
 ```bash
 export AUTOCHAT_MODEL="gpt-4-turbo"
 export OPENAI_API_KEY=<your-key>
 ```
 
-Use `AUTOCHAT_HOST` to use alternative provider that are openai compatible (openpipe, llama_cpp, ...)
+Use `AUTOCHAT_HOST` to use alternative provider (openai, anthropic, openpipe, llama_cpp, ...)
 
 ## Support