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added support for same models convo

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tcsenpai 2024-10-06 20:57:44 +02:00
parent 5d865e90f0
commit 778c8e1b43
2 changed files with 16 additions and 28 deletions
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4
README.md
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@ -40,14 +40,18 @@ Please refer to [Ollama](https://ollama.com/download) to install Ollama on your
```
3. Set up your environment variables by creating a `.env` file in the project root:
```
OLLAMA_ENDPOINT=http://localhost:11434
MODEL_1=llama2
MODEL_2=mistral
INITIAL_PROMPT="Let's discuss the future of AI. What are your thoughts on its potential impact on society?"
```
Feel free to use the env.example file as a template.
**Note:** The INITIAL_PROMPT is the first message that will be sent and it will be send on behalf of the second AI to the first AI.
## Usage
### Command-line Interface

40
ai_conversation.py
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@ -12,7 +12,8 @@ class AIConversation:
self.messages_1 = [{"role": "system", "content": system_prompt_1}]
self.messages_2 = [{"role": "system", "content": system_prompt_2}]
self.client = ollama.Client(ollama_endpoint)
self.ollama_endpoint = ollama_endpoint
def start_conversation(self, initial_message, num_exchanges=0):
current_message = initial_message
color_1 = "cyan"
@ -29,12 +30,17 @@ class AIConversation:
try:
i = 0
active_ai = 0 # Starting with AI 1
while num_exchanges == 0 or i < num_exchanges:
if self.current_model == self.model_1:
if active_ai == 0:
name = "AI 1"
messages = self.messages_1
other_messages = self.messages_2
color = color_1
else:
name = "AI 2"
messages = self.messages_2
other_messages = self.messages_1
color = color_2
@ -45,7 +51,7 @@ class AIConversation:
response = self.client.chat(model=self.current_model, messages=messages)
response_content = response['message']['content']
model_name = f"{self.current_model.upper()}:"
model_name = f"{self.current_model.upper()} ({name}):"
formatted_response = f"{model_name}\n{response_content}\n"
print(colored(formatted_response, color))
@ -55,7 +61,8 @@ class AIConversation:
other_messages.append({"role": "user", "content": response_content})
current_message = response_content
self.current_model = self.model_2 if self.current_model == self.model_1 else self.model_1
self.current_model = self.model_2 if active_ai == 1 else self.model_1
active_ai = 1 if active_ai == 0 else 0
print(colored("---", "magenta"))
print()
@ -72,29 +79,6 @@ class AIConversation:
print(colored("Conversation ended.", "green"))
self.save_conversation_log(conversation_log)
def get_conversation_response(self, current_message):
if self.current_model == self.model_1:
messages = self.messages_1
other_messages = self.messages_2
else:
messages = self.messages_2
other_messages = self.messages_1
messages.append({"role": "user", "content": current_message})
other_messages.append({"role": "assistant", "content": current_message})
response = self.client.chat(model=self.current_model, messages=messages)
response_content = response['message']['content']
model_name = f"{self.current_model.upper()}:"
formatted_response = f"{model_name}\n{response_content}\n"
messages.append({"role": "assistant", "content": response_content})
other_messages.append({"role": "user", "content": response_content})
self.current_model = self.model_2 if self.current_model == self.model_1 else self.model_1
return formatted_response
def save_conversation_log(self, messages, filename=None):
if filename is None:
@ -102,7 +86,7 @@ class AIConversation:
filename = f"conversation_log_{timestamp}.txt"
log_content = f"Conversation Log - {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
log_content += f"Ollama Endpoint: {self.ollama_client.endpoint}\n"
log_content += f"Ollama Endpoint: {self.ollama_endpoint}\n"
log_content += f"Model 1: {self.model_1}\n"
log_content += f"Model 2: {self.model_2}\n"
log_content += f"System Prompt 1:\n{self.system_prompt_1}\n\n"