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@ -12,6 +12,7 @@ config_directory = os.path.expanduser("~/.config/fabric")
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env_file = os.path.join(config_directory, ".env")
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env_file = os.path.join(config_directory, ".env")
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class Standalone:
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class Standalone:
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def __init__(self, args, pattern="", env_file="~/.config/fabric/.env"):
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def __init__(self, args, pattern="", env_file="~/.config/fabric/.env"):
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""" Initialize the class with the provided arguments and environment file.
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""" Initialize the class with the provided arguments and environment file.
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@ -45,6 +46,7 @@ class Standalone:
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self.config_pattern_directory = config_directory
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self.config_pattern_directory = config_directory
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self.pattern = pattern
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self.pattern = pattern
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self.args = args
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self.args = args
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self.model = args.model
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def streamMessage(self, input_data: str):
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def streamMessage(self, input_data: str):
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""" Stream a message and handle exceptions.
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""" Stream a message and handle exceptions.
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@ -78,7 +80,7 @@ class Standalone:
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messages = [user_message]
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messages = [user_message]
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try:
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try:
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stream = self.client.chat.completions.create(
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stream = self.client.chat.completions.create(
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model="gpt-4-turbo-preview",
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model=self.model,
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messages=messages,
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messages=messages,
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temperature=0.0,
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temperature=0.0,
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top_p=1,
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top_p=1,
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@ -137,7 +139,7 @@ class Standalone:
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messages = [user_message]
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messages = [user_message]
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try:
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try:
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response = self.client.chat.completions.create(
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response = self.client.chat.completions.create(
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model="gpt-4-turbo-preview",
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model=self.model,
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messages=messages,
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messages=messages,
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temperature=0.0,
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temperature=0.0,
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top_p=1,
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top_p=1,
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@ -154,6 +156,25 @@ class Standalone:
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with open(self.args.output, "w") as f:
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with open(self.args.output, "w") as f:
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f.write(response.choices[0].message.content)
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f.write(response.choices[0].message.content)
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def fetch_available_models(self):
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headers = {
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"Authorization": f"Bearer { self.client.api_key }"
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}
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response = requests.get("https://api.openai.com/v1/models", headers=headers)
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if response.status_code == 200:
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models = response.json().get("data", [])
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# Filter only gpt models
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gpt_models = [model for model in models if model.get("id", "").startswith(("gpt"))]
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# Sort the models alphabetically by their ID
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sorted_gpt_models = sorted(gpt_models, key=lambda x: x.get("id"))
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for model in sorted_gpt_models:
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print(model.get("id"))
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else:
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print(f"Failed to fetch models: HTTP {response.status_code}")
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class Update:
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class Update:
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def __init__(self):
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def __init__(self):
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@ -274,7 +295,6 @@ class Update:
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else:
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else:
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print(f"Failed to fetch directory contents due to an HTTP error: {e}")
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print(f"Failed to fetch directory contents due to an HTTP error: {e}")
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class Setup:
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class Setup:
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def __init__(self):
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def __init__(self):
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""" Initialize the object.
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""" Initialize the object.
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