fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.
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import requests
import os
from openai import OpenAI
import asyncio
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import pyperclip
import sys
import platform
from dotenv import load_dotenv
import zipfile
import tempfile
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import re
import shutil
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current_directory = os.path.dirname(os.path.realpath(__file__))
config_directory = os.path.expanduser("~/.config/fabric")
env_file = os.path.join(config_directory, ".env")
class Standalone:
def __init__(self, args, pattern="", env_file="~/.config/fabric/.env"):
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""" Initialize the class with the provided arguments and environment file.
Args:
args: The arguments for initialization.
pattern: The pattern to be used (default is an empty string).
env_file: The path to the environment file (default is "~/.config/fabric/.env").
Returns:
None
Raises:
KeyError: If the "OPENAI_API_KEY" is not found in the environment variables.
FileNotFoundError: If no API key is found in the environment variables.
"""
# Expand the tilde to the full path
env_file = os.path.expanduser(env_file)
load_dotenv(env_file)
try:
apikey = os.environ["OPENAI_API_KEY"]
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self.client = OpenAI()
self.client.api_key = apikey
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except FileNotFoundError:
print("No API key found. Use the --apikey option to set the key")
sys.exit()
self.local = False
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self.config_pattern_directory = config_directory
self.pattern = pattern
self.args = args
self.model = args.model
self.claude = False
sorted_gpt_models, ollamaList, claudeList = self.fetch_available_models()
self.local = self.model.strip() in ollamaList
self.claude = self.model.strip() in claudeList
async def localChat(self, messages):
from ollama import AsyncClient
response = await AsyncClient().chat(model=self.model, messages=messages)
print(response['message']['content'])
async def localStream(self, messages):
from ollama import AsyncClient
async for part in await AsyncClient().chat(model=self.model, messages=messages, stream=True):
print(part['message']['content'], end='', flush=True)
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async def claudeStream(self, system, user):
from anthropic import AsyncAnthropic
self.claudeApiKey = os.environ["CLAUDE_API_KEY"]
Streamingclient = AsyncAnthropic(api_key=self.claudeApiKey)
async with Streamingclient.messages.stream(
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max_tokens=4096,
system=system,
messages=[user],
model=self.model, temperature=0.0, top_p=1.0
) as stream:
async for text in stream.text_stream:
print(text, end="", flush=True)
print()
message = await stream.get_final_message()
async def claudeChat(self, system, user):
from anthropic import Anthropic
self.claudeApiKey = os.environ["CLAUDE_API_KEY"]
client = Anthropic(api_key=self.claudeApiKey)
message = client.messages.create(
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max_tokens=4096,
system=system,
messages=[user],
model=self.model,
temperature=0.0, top_p=1.0
)
print(message.content[0].text)
def streamMessage(self, input_data: str, context=""):
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""" Stream a message and handle exceptions.
Args:
input_data (str): The input data for the message.
Returns:
None: If the pattern is not found.
Raises:
FileNotFoundError: If the pattern file is not found.
"""
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wisdomFilePath = os.path.join(
config_directory, f"patterns/{self.pattern}/system.md"
)
user_message = {"role": "user", "content": f"{input_data}"}
wisdom_File = os.path.join(current_directory, wisdomFilePath)
system = ""
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buffer = ""
if self.pattern:
try:
with open(wisdom_File, "r") as f:
if context:
system = context + '\n\n' + f.read()
else:
system = f.read()
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system_message = {"role": "system", "content": system}
messages = [system_message, user_message]
except FileNotFoundError:
print("pattern not found")
return
else:
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if context:
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messages = [
{"role": "system", "content": context}, user_message]
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else:
messages = [user_message]
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try:
if self.local:
asyncio.run(self.localStream(messages))
elif self.claude:
from anthropic import AsyncAnthropic
asyncio.run(self.claudeStream(system, user_message))
else:
stream = self.client.chat.completions.create(
model=self.model,
messages=messages,
temperature=0.0,
top_p=1,
frequency_penalty=0.1,
presence_penalty=0.1,
stream=True,
)
for chunk in stream:
if chunk.choices[0].delta.content is not None:
char = chunk.choices[0].delta.content
buffer += char
if char not in ["\n", " "]:
print(char, end="")
elif char == " ":
print(" ", end="") # Explicitly handle spaces
elif char == "\n":
print() # Handle newlines
sys.stdout.flush()
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except Exception as e:
if "All connection attempts failed" in str(e):
print(
"Error: cannot connect to llama2. If you have not already, please visit https://ollama.com for installation instructions")
if "CLAUDE_API_KEY" in str(e):
print(
"Error: CLAUDE_API_KEY not found in environment variables. Please run --setup and add the key")
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if "overloaded_error" in str(e):
print(
"Error: Fabric is working fine, but claude is overloaded. Please try again later.")
else:
print(f"Error: {e}")
print(e)
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if self.args.copy:
pyperclip.copy(buffer)
if self.args.output:
with open(self.args.output, "w") as f:
f.write(buffer)
def sendMessage(self, input_data: str, context=""):
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""" Send a message using the input data and generate a response.
Args:
input_data (str): The input data to be sent as a message.
Returns:
None
Raises:
FileNotFoundError: If the specified pattern file is not found.
"""
wisdomFilePath = os.path.join(
config_directory, f"patterns/{self.pattern}/system.md"
)
user_message = {"role": "user", "content": f"{input_data}"}
wisdom_File = os.path.join(current_directory, wisdomFilePath)
system = ""
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if self.pattern:
try:
with open(wisdom_File, "r") as f:
if context:
system = context + '\n\n' + f.read()
else:
system = f.read()
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system_message = {"role": "system", "content": system}
messages = [system_message, user_message]
except FileNotFoundError:
print("pattern not found")
return
else:
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if context:
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messages = [
{'role': 'system', 'content': context}, user_message]
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else:
messages = [user_message]
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try:
if self.local:
asyncio.run(self.localChat(messages))
elif self.claude:
asyncio.run(self.claudeChat(system, user_message))
else:
response = self.client.chat.completions.create(
model=self.model,
messages=messages,
temperature=0.0,
top_p=1,
frequency_penalty=0.1,
presence_penalty=0.1,
)
print(response.choices[0].message.content)
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except Exception as e:
if "All connection attempts failed" in str(e):
print(
"Error: cannot connect to llama2. If you have not already, please visit https://ollama.com for installation instructions")
if "CLAUDE_API_KEY" in str(e):
print(
"Error: CLAUDE_API_KEY not found in environment variables. Please run --setup and add the key")
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if "overloaded_error" in str(e):
print(
"Error: Fabric is working fine, but claude is overloaded. Please try again later.")
if "Attempted to call a sync iterator on an async stream" in str(e):
print("Error: There is a problem connecting fabric with your local ollama installation. Please visit https://ollama.com for installation instructions. It is possible that you have chosen the wrong model. Please run fabric --listmodels to see the available models and choose the right one with fabric --model <model> or fabric --changeDefaultModel. If this does not work. Restart your computer (always a good idea) and try again. If you are still having problems, please visit https://ollama.com for installation instructions.")
else:
print(f"Error: {e}")
print(e)
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if self.args.copy:
pyperclip.copy(response.choices[0].message.content)
if self.args.output:
with open(self.args.output, "w") as f:
f.write(response.choices[0].message.content)
def fetch_available_models(self):
gptlist = []
fullOllamaList = []
claudeList = ['claude-3-opus-20240229']
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headers = {
"Authorization": f"Bearer {self.client.api_key}"
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}
response = requests.get(
"https://api.openai.com/v1/models", headers=headers)
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if response.status_code == 200:
models = response.json().get("data", [])
# Filter only gpt models
gpt_models = [model for model in models if model.get(
"id", "").startswith(("gpt"))]
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# Sort the models alphabetically by their ID
sorted_gpt_models = sorted(
gpt_models, key=lambda x: x.get("id"))
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for model in sorted_gpt_models:
gptlist.append(model.get("id"))
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else:
print(f"Failed to fetch models: HTTP {response.status_code}")
sys.exit()
import ollama
try:
default_modelollamaList = ollama.list()['models']
for model in default_modelollamaList:
fullOllamaList.append(model['name'].rstrip(":latest"))
except:
fullOllamaList = []
return gptlist, fullOllamaList, claudeList
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def get_cli_input(self):
""" aided by ChatGPT; uses platform library
accepts either piped input or console input
from either Windows or Linux
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Args:
none
Returns:
string from either user or pipe
"""
system = platform.system()
if system == 'Windows':
if not sys.stdin.isatty(): # Check if input is being piped
return sys.stdin.read().strip() # Read piped input
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else:
# Prompt user for input from console
return input("Enter Question: ")
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else:
return sys.stdin.read()
class Update:
def __init__(self):
"""Initialize the object with default values."""
self.repo_zip_url = "https://github.com/danielmiessler/fabric/archive/refs/heads/main.zip"
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self.config_directory = os.path.expanduser("~/.config/fabric")
self.pattern_directory = os.path.join(
self.config_directory, "patterns")
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os.makedirs(self.pattern_directory, exist_ok=True)
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print("Updating patterns...")
self.update_patterns() # Start the update process immediately
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def update_patterns(self):
"""Update the patterns by downloading the zip from GitHub and extracting it."""
with tempfile.TemporaryDirectory() as temp_dir:
zip_path = os.path.join(temp_dir, "repo.zip")
self.download_zip(self.repo_zip_url, zip_path)
extracted_folder_path = self.extract_zip(zip_path, temp_dir)
# The patterns folder will be inside "fabric-main" after extraction
patterns_source_path = os.path.join(
extracted_folder_path, "fabric-main", "patterns")
if os.path.exists(patterns_source_path):
# If the patterns directory already exists, remove it before copying over the new one
if os.path.exists(self.pattern_directory):
shutil.rmtree(self.pattern_directory)
shutil.copytree(patterns_source_path, self.pattern_directory)
print("Patterns updated successfully.")
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else:
print("Patterns folder not found in the downloaded zip.")
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def download_zip(self, url, save_path):
"""Download the zip file from the specified URL."""
response = requests.get(url)
response.raise_for_status() # Check if the download was successful
with open(save_path, 'wb') as f:
f.write(response.content)
print("Downloaded zip file successfully.")
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def extract_zip(self, zip_path, extract_to):
"""Extract the zip file to the specified directory."""
with zipfile.ZipFile(zip_path, 'r') as zip_ref:
zip_ref.extractall(extract_to)
print("Extracted zip file successfully.")
return extract_to # Return the path to the extracted contents
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class Alias:
def __init__(self):
self.config_files = []
home_directory = os.path.expanduser("~")
self.patterns = os.path.join(home_directory, ".config/fabric/patterns")
if os.path.exists(os.path.join(home_directory, ".bashrc")):
self.config_files.append(os.path.join(home_directory, ".bashrc"))
if os.path.exists(os.path.join(home_directory, ".zshrc")):
self.config_files.append(os.path.join(home_directory, ".zshrc"))
if os.path.exists(os.path.join(home_directory, ".bash_profile")):
self.config_files.append(os.path.join(
home_directory, ".bash_profile"))
self.remove_all_patterns()
self.add_patterns()
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print('Aliases added successfully. Please restart your terminal to use them.')
def add(self, name, alias):
for file in self.config_files:
with open(file, "a") as f:
f.write(f"alias {name}='{alias}'\n")
def remove(self, pattern):
for file in self.config_files:
# Read the whole file first
with open(file, "r") as f:
wholeFile = f.read()
# Determine if the line to be removed is in the file
target_line = f"alias {pattern}='fabric --pattern {pattern}'\n"
if target_line in wholeFile:
# If the line exists, replace it with nothing (remove it)
wholeFile = wholeFile.replace(target_line, "")
# Write the modified content back to the file
with open(file, "w") as f:
f.write(wholeFile)
def remove_all_patterns(self):
allPatterns = os.listdir(self.patterns)
for pattern in allPatterns:
self.remove(pattern)
def find_line(self, name):
for file in self.config_files:
with open(file, "r") as f:
lines = f.readlines()
for line in lines:
if line.strip("\n") == f"alias ${name}='{alias}'":
return line
def add_patterns(self):
allPatterns = os.listdir(self.patterns)
for pattern in allPatterns:
self.add(pattern, f"fabric --pattern {pattern}")
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class Setup:
def __init__(self):
""" Initialize the object.
Raises:
OSError: If there is an error in creating the pattern directory.
"""
self.config_directory = os.path.expanduser("~/.config/fabric")
self.pattern_directory = os.path.join(
self.config_directory, "patterns")
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os.makedirs(self.pattern_directory, exist_ok=True)
self.env_file = os.path.join(self.config_directory, ".env")
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self.gptlist = []
self.fullOllamaList = []
self.claudeList = ['claude-3-opus-20240229']
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load_dotenv(self.env_file)
try:
openaiapikey = os.environ["OPENAI_API_KEY"]
self.openaiapi_key = openaiapikey
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except:
pass
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try:
self.fetch_available_models()
except:
pass
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def fetch_available_models(self):
headers = {
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"Authorization": f"Bearer {self.openaiapi_key}"
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}
response = requests.get(
"https://api.openai.com/v1/models", headers=headers)
if response.status_code == 200:
models = response.json().get("data", [])
# Filter only gpt models
gpt_models = [model for model in models if model.get(
"id", "").startswith(("gpt"))]
# Sort the models alphabetically by their ID
sorted_gpt_models = sorted(
gpt_models, key=lambda x: x.get("id"))
for model in sorted_gpt_models:
self.gptlist.append(model.get("id"))
else:
print(f"Failed to fetch models: HTTP {response.status_code}")
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sys.exit()
import ollama
try:
default_modelollamaList = ollama.list()['models']
for model in default_modelollamaList:
self.fullOllamaList.append(model['name'].rstrip(":latest"))
except:
self.fullOllamaList = []
allmodels = self.gptlist + self.fullOllamaList + self.claudeList
return allmodels
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def api_key(self, api_key):
""" Set the OpenAI API key in the environment file.
Args:
api_key (str): The API key to be set.
Returns:
None
Raises:
OSError: If the environment file does not exist or cannot be accessed.
"""
api_key = api_key.strip()
if not os.path.exists(self.env_file) and api_key:
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with open(self.env_file, "w") as f:
f.write(f"OPENAI_API_KEY={api_key}")
print(f"OpenAI API key set to {api_key}")
elif api_key:
# erase the line OPENAI_API_KEY=key and write the new key
with open(self.env_file, "r") as f:
lines = f.readlines()
with open(self.env_file, "w") as f:
for line in lines:
if "OPENAI_API_KEY" not in line:
f.write(line)
f.write(f"OPENAI_API_KEY={api_key}")
def claude_key(self, claude_key):
""" Set the Claude API key in the environment file.
Args:
claude_key (str): The API key to be set.
Returns:
None
Raises:
OSError: If the environment file does not exist or cannot be accessed.
"""
claude_key = claude_key.strip()
if os.path.exists(self.env_file) and claude_key:
with open(self.env_file, "r") as f:
lines = f.readlines()
with open(self.env_file, "w") as f:
for line in lines:
if "CLAUDE_API_KEY" not in line:
f.write(line)
f.write(f"CLAUDE_API_KEY={claude_key}")
elif claude_key:
with open(self.env_file, "w") as f:
f.write(f"CLAUDE_API_KEY={claude_key}")
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def update_fabric_command(self, line, model):
fabric_command_regex = re.compile(
r"(alias.*fabric --pattern\s+\S+.*?)( --model.*)?'")
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match = fabric_command_regex.search(line)
if match:
base_command = match.group(1)
# Provide a default value for current_flag
current_flag = match.group(2) if match.group(2) else ""
new_flag = ""
new_flag = f" --model {model}"
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# Update the command if the new flag is different or to remove an existing flag.
# Ensure to add the closing quote that was part of the original regex
return f"{base_command}{new_flag}'\n"
else:
return line # Return the line unmodified if no match is found.
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def update_fabric_alias(self, line, model):
fabric_alias_regex = re.compile(
r"(alias fabric='[^']+?)( --model.*)?'")
match = fabric_alias_regex.search(line)
if match:
base_command, current_flag = match.groups()
new_flag = f" --model {model}"
# Update the alias if the new flag is different or to remove an existing flag.
return f"{base_command}{new_flag}'\n"
else:
return line # Return the line unmodified if no match is found.
def clear_alias(self, line):
fabric_command_regex = re.compile(
r"(alias fabric='[^']+?)( --model.*)?'")
match = fabric_command_regex.search(line)
if match:
base_command = match.group(1)
return f"{base_command}'\n"
else:
return line # Return the line unmodified if no match is found.
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def clear_env_line(self, line):
fabric_command_regex = re.compile(
r"(alias.*fabric --pattern\s+\S+.*?)( --model.*)?'")
match = fabric_command_regex.search(line)
if match:
base_command = match.group(1)
return f"{base_command}'\n"
else:
return line # Return the line unmodified if no match is found.
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def pattern(self, line):
fabric_command_regex = re.compile(
r"(alias fabric='[^']+?)( --model.*)?'")
match = fabric_command_regex.search(line)
if match:
base_command = match.group(1)
return f"{base_command}'\n"
else:
return line # Return the line unmodified if no match is found.
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def clean_env(self):
"""Clear the DEFAULT_MODEL from the environment file.
Returns:
None
"""
user_home = os.path.expanduser("~")
sh_config = None
# Check for shell configuration files
if os.path.exists(os.path.join(user_home, ".bashrc")):
sh_config = os.path.join(user_home, ".bashrc")
elif os.path.exists(os.path.join(user_home, ".zshrc")):
sh_config = os.path.join(user_home, ".zshrc")
else:
print("No environment file found.")
if sh_config:
with open(sh_config, "r") as f:
lines = f.readlines()
with open(sh_config, "w") as f:
for line in lines:
modified_line = line
# Update existing fabric commands
if "fabric --pattern" in line:
modified_line = self.clear_env_line(
modified_line)
elif "fabric=" in line:
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modified_line = self.clear_alias(
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modified_line)
f.write(modified_line)
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self.remove_duplicates(env_file)
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else:
print("No shell configuration file found.")
def default_model(self, model):
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"""Set the default model in the environment file.
Args:
model (str): The model to be set.
"""
model = model.strip()
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if model:
# Write or update the DEFAULT_MODEL in env_file
allModels = self.claudeList + self.fullOllamaList + self.gptlist
if model not in allModels:
print(
f"Error: {model} is not a valid model. Please run fabric --listmodels to see the available models.")
sys.exit()
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# Compile regular expressions outside of the loop for efficiency
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user_home = os.path.expanduser("~")
sh_config = None
# Check for shell configuration files
if os.path.exists(os.path.join(user_home, ".bashrc")):
sh_config = os.path.join(user_home, ".bashrc")
elif os.path.exists(os.path.join(user_home, ".zshrc")):
sh_config = os.path.join(user_home, ".zshrc")
if sh_config:
with open(sh_config, "r") as f:
lines = f.readlines()
with open(sh_config, "w") as f:
for line in lines:
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modified_line = line
# Update existing fabric commands
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if "fabric --pattern" in line:
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modified_line = self.update_fabric_command(
modified_line, model)
elif "fabric=" in line:
modified_line = self.update_fabric_alias(
modified_line, model)
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f.write(modified_line)
print(f"""Default model changed to {
model}. Please restart your terminal to use it.""")
else:
print("No shell configuration file found.")
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def remove_duplicates(filename):
unique_lines = set()
with open(filename, 'r') as file:
lines = file.readlines()
with open(filename, 'w') as file:
for line in lines:
if line not in unique_lines:
file.write(line)
unique_lines.add(line)
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def patterns(self):
""" Method to update patterns and exit the system.
Returns:
None
"""
Update()
def run(self):
""" Execute the Fabric program.
This method prompts the user for their OpenAI API key, sets the API key in the Fabric object, and then calls the patterns method.
Returns:
None
"""
print("Welcome to Fabric. Let's get started.")
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apikey = input(
"Please enter your OpenAI API key. If you do not have one or if you have already entered it, press enter.\n")
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self.api_key(apikey.strip())
print("Please enter your claude API key. If you do not have one, or if you have already entered it, press enter.\n")
claudekey = input()
self.claude_key(claudekey.strip())
model = input(
"Please enter your default model. Press enter to choose the default gpt-4-turbo-preview\n")
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self.patterns()
self.default_model(model)
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class Transcribe:
def youtube(video_id):
"""
This method gets the transciption
of a YouTube video designated with the video_id
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Input:
the video id specifing a YouTube video
an example url for a video: https://www.youtube.com/watch?v=vF-MQmVxnCs&t=306s
the video id is vF-MQmVxnCs&t=306s
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Output:
a transcript for the video
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Raises:
an exception and prints error
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"""
try:
transcript_list = YouTubeTranscriptApi.get_transcript(video_id)
transcript = ""
for segment in transcript_list:
transcript += segment['text'] + " "
return transcript.strip()
except Exception as e:
print("Error:", e)
return None
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class AgentSetup:
def apiKeys(self):
"""Method to set the API keys in the environment file.
Returns:
None
"""
print("Welcome to Fabric. Let's get started.")
browserless = input("Please enter your Browserless API key\n")
serper = input("Please enter your Serper API key\n")
# Entries to be added
browserless_entry = f"BROWSERLESS_API_KEY={browserless}"
serper_entry = f"SERPER_API_KEY={serper}"
# Check and write to the file
with open(env_file, "r+") as f:
content = f.read()
# Determine if the file ends with a newline
if content.endswith('\n'):
# If it ends with a newline, we directly write the new entries
f.write(f"{browserless_entry}\n{serper_entry}\n")
else:
# If it does not end with a newline, add one before the new entries
f.write(f"\n{browserless_entry}\n{serper_entry}\n")