Updated to version 0.5

README.md

@@ -2,6 +2,28 @@
 
 ![Animated GIF](https://github.com/wunderwuzzi23/blog/raw/master/static/images/2023/yolo-shell-anim-gif.gif)
 
+# Update Yolo v0.5 - Support for Claude and other providers
+
+* Added Claude support. Can an API key from Anthropic, current model `claude-3-5-sonnet-20240620`. 
+* ai_model.py to abstract model usage and allow adding new providers more easily
+* Rewrote some logic to simplify and generalize support for various new APIs (like Ollama, Claude)
+
+# Update Yolo v0.4 - Support for Groq
+
+* Added groq support. You can get an API key at `https://console.groq.com` and set mode to for instance `llama3-8b-8192`. groq is lightning fast. 
+* Simplified and improved default `prompt.txt`, 
+* Note: Testing shows that model `gpt-4o` gives the best results.
+
+
+# Update Yolo v0.3 - Support for Azure OpenAI
+
+* Key changes are upgrades to the latest OpenAI libraries and support for Azure OpenAI. There is an `api` key in the `yolo.yaml` that can be set to `azure_openai` and then you can provide all the parameters accordingly in the yaml file as well (`api-version`, your `azure-endpoint`,...). The api key for azure is called `AZURE_OPENAI_API_KEY` by the way. It can be set via environment variable and config file.
+* It's now possible to change the color of the suggested command via config file
+* The "modify prompt" feature is now optional and can be toggled via config file.
+* Minor bug fixes (like copy to clipboard should work on macOS)
+
+Tested on macOS and Linux. Windows hopefully still works also.
+
 # Update Yolo v0.2 - Support for GPT-4 API
 
 This update introduces the `yolo.yaml` configuration file. In this file you can specify which OpenAI model you want to query, and other settings. The safety switch also moved into this configuration file.
@@ -9,16 +31,18 @@ This update introduces the `yolo.yaml` configuration file. In this file you can
 For now the default model is still `gpt-3.5-turbo`, but you can update to `gpt-4` if you have gotten access already!
 
 ```
-Yolo v0.2 - by @wunderwuzzi23
+Yolo v0.3 - by @wunderwuzzi23
 
 Usage: yolo [-a] list the current directory information
 Argument: -a: Prompt the user before running the command (only useful when safety is off)
 
 Current configuration per yolo.yaml:
-* Model        : gpt-3.5-turbo
+* API          : openai
+* Model        : gpt-4-turbo-preview
 * Temperature  : 0
 * Max. Tokens  : 500
-* Safety       : on
+* Safety       : True
+* Command Color: blue
 ```
 
 Happy Hacking!
@@ -41,7 +65,18 @@ yolo show me some funny unicode characters
 There are three ways to configure the key on Linux and macOS:
 - You can either `export OPENAI_API_KEY=<yourkey>`, or have a `.env` file in the same directory as `yolo.py` with `OPENAI_API_KEY="<yourkey>"` as a line
 - Create a file at `~/.openai.apikey` with the key in it
-- Add the key to the `yolo.yaml` configuration file
+- Set the key in the `yolo.yaml` configuration file
+
+### Azure OpenAI Key configuration
+There are three ways to configure the key on Linux and macOS:
+- You can either `export AZURE_OPENAI_API_KEY=<yourkey>`, or have a `.env` file in the same directory as `yolo.py` with `AZURE_OPENAI_API_KEY="<yourkey>"` as a line
+- Create a file at `~/.azureopenai.apikey` with the key in it
+- Set the key in the `yolo.yaml` configuration file
+
+### Groq Configuration
+- Grab an API key from `console.groq.com` 
+- You can either `export GROQ_API_KEY=<yourkey>`, or have a `.env` file in the same directory as `yolo.py` with `GROQ_API_KEY="<yourkey>"` as a line
+- Set `api` and `model` (e.g llama3-8b-8192) in `yolo.yaml` configuration file
 
 ## Aliases
 
@@ -74,6 +109,22 @@ You also have the option to:
 
 That's it basically.
 
+
+### PowerShell Command 
+
+If you want a PowerShell style command you can use something like this (check that the path is to yolo.py is correct) and you can add this function to your PowerShell profile. 
+
+```
+function Invoke-Yolo { 
+    param([Parameter(ValueFromRemainingArguments=$true)]$Commands)
+    $AllCommands = $Commands -join " "
+    $YoloPath = Join-Path -Path $env:USERPROFILE -ChildPath "\yolo-ai-cmdbot\yolo.py"
+    python.exe $YoloPath $AllCommands
+}
+```
+
+You can find the profile file with `$PROFILE` in a PowerShell Terminal. I might add a better installation in future.
+
 ## OpenAI API Key Configuration on Windows
 
 On Windows `export OPENAI_API_KEY=<yourkey>` will not work instead:
@@ -83,6 +134,8 @@ On Windows `export OPENAI_API_KEY=<yourkey>` will not work instead:
 
 Optionally (since v.0.2), the key can also be stored in `yolo.yaml`.
 
+If you want to use Azure, the the key is called `AZURE_OPENAI_API_KEY`.
+
 ## Running yolo on Windows 
 
 Windows is less tested, it does work though and will use PowerShell.
@@ -117,7 +170,7 @@ Since v.0.2 the safety switch setting moved to `yolo.yaml`, the old `~/.yolo-saf
 
 To have yolo run commands right away when they come back from ChatGPT change the `safety` in the `yolo.yaml` to `False`.
 
-If you still want to inspect the command that is executed when safety is off, add the `-s` argument, e.g `yolo -s delete the file test.txt`.
+If you still want to inspect the command that is executed when safety is off, add the `-a` argument, e.g `yolo -a delete the file test.txt`.
 
 Let's go!
 

ai_model.py

@@ -0,0 +1,149 @@
+# MIT License
+# Copyright (c) 2023-2024 wunderwuzzi23
+# Greetings from Seattle! 
+
+from abc import ABC, abstractmethod
+from openai import OpenAI
+from groq import Groq
+from ollama import Client
+from openai import AzureOpenAI 
+from anthropic import Anthropic
+import os
+
+class AIModel(ABC):
+    @abstractmethod
+    def chat(self, model, messages):
+        pass
+
+    @abstractmethod
+    def moderate(self, message):
+        pass
+
+    @staticmethod
+    def get_model_client(config):
+        api_provider=config["api"]
+
+        if api_provider == "" or api_provider==None:
+            api_provider = "groq"
+        
+        if api_provider == "groq":
+            return GroqModel(api_key=os.environ.get("GROQ_API_KEY"))
+        
+        elif api_provider == "openai":
+            api_key = os.getenv("OPENAI_API_KEY")
+            if not api_key:  
+                api_key=config["openai_api_key"]       
+            if not api_key:  #If statement to avoid "invalid filepath" error
+                home_path = os.path.expanduser("~")   
+                api_key=open(os.path.join(home_path,".openai.apikey"), "r").readline().strip()
+                api_key = api_key
+
+            return OpenAIModel(api_key=api_key)
+        
+        elif api_provider == "azure":
+            api_key = os.getenv("AZURE_OPENAI_API_KEY")
+            if not api_key:  
+                api_key=config["azure_openai_api_key"]
+            if not api_key: 
+                home_path = os.path.expanduser("~")   
+                api_key=open(os.path.join(home_path,".azureopenai.apikey"), "r").readline().strip()
+
+            return AzureOpenAIModel(
+                    api_key=api_key,
+                    azure_endpoint=config["azure_endpoint"], 
+                    api_version=config["azure_api_version"])
+        
+        elif api_provider == "ollama":
+            ollama_api   = os.environ.get("OLLAMA_ENDPOINT", "http://localhost:11434")
+            #ollama_model = os.environ.get("OLLAMA_MODEL", "llama3-8b-8192")
+            return OllamaModel(ollama_api)
+
+        if api_provider == "anthropic":
+            api_key = os.getenv("ANTHROPIC_API_KEY")
+            if not api_key: 
+                api_key=config["anthropic_api_key"]
+            return AnthropicModel(api_key=api_key) 
+        else:
+            raise ValueError(f"Invalid AI model provider: {api_provider}")
+
+class GroqModel(AIModel):
+    def __init__(self, api_key):
+        self.client = Groq(api_key=api_key)
+
+    def chat(self, messages, model, temperature, max_tokens):
+        resp = self.client.chat.completions.create(model=model, 
+                                                   messages=messages, 
+                                                   temperature=temperature, 
+                                                   max_tokens=max_tokens)
+        return resp.choices[0].message.content
+    
+    def moderate(self, message):
+        pass
+
+class OpenAIModel(AIModel):
+    def __init__(self, api_key):
+        self.client = OpenAI(api_key=api_key)
+
+    def chat(self, messages, model, temperature, max_tokens):
+        resp = self.client.chat.completions.create(model=model, 
+                                                   messages=messages, 
+                                                   temperature=temperature,
+                                                   max_tokens=max_tokens)
+        
+        return resp.choices[0].message.content
+    
+    def moderate(self, message):
+        return self.client.moderations.create(input=message)
+
+class OllamaModel(AIModel):
+    def __init__(self, host):
+        self.client = Client(host=host)
+    
+    def chat(self, messages, model, temperature, max_tokens):
+        resp = self.client.chat(model=model, 
+                                messages=messages)
+        return resp["message"]["content"]
+    
+    def moderate(self, message):
+        pass
+
+
+class AzureOpenAIModel(AIModel):
+    def __init__(self, azure_endpoint, api_key, api_version):
+        self.client = AzureOpenAI(azure_endpoint=azure_endpoint, api_key=api_key, api_version=api_version)
+
+    def chat(self, messages, model, temperature, max_tokens):
+
+        resp = self.client.chat.completions.create(model=model, 
+                        messages=messages, 
+                        temperature=temperature, 
+                        max_tokens=max_tokens)
+        
+        return resp.choices[0].message.content
+    
+    def moderate(self, message):
+        return self.client.moderations.create(input=message)
+
+class AnthropicModel(AIModel):
+    def __init__(self, api_key):
+        self.client = Anthropic(api_key=api_key)
+
+    def chat(self, messages, model, temperature, max_tokens):
+        ## Anthropic requires the system prompt to be passed separately
+        ## Hence extracting system prompt role from the messages
+        ## and then passing the messages without the system role 
+        ## messages is not subscriptable, so we need to convert it to a list
+        system_prompt = next((m.get("content", "") for m in messages if m.get("role") == "system"), "")
+
+        # Remove system messages from the list
+        user_messages = [m for m in messages if m.get("role") != "system"]
+        resp = self.client.messages.create(model=model, 
+                                    system=system_prompt,
+                                    messages=user_messages,
+                                    temperature=temperature, 
+                                    max_tokens=max_tokens)
+        
+        return resp.content[0].text
+    
+    def moderate(self, message):
+        pass

install.bat

@@ -3,8 +3,9 @@ setlocal enabledelayedexpansion
 
 :: First check if `install.bat` (this) has needed files in same directory
 if not exist %~dp0\yolo.py ( echo `yolo.py` missing in %~dp0 cannot install & goto :choice_default_3 )
-if not exist %~dp0\yolo.prompt ( echo `yolo.prompt` missing in %~dp0 cannot install & goto :choice_default_3 ) 
+if not exist %~dp0\prompt.txt ( echo `prompt.txt` missing in %~dp0 cannot install & goto :choice_default_3 ) 
 if not exist %~dp0\yolo.yaml ( echo `yolo.yaml` missing in %~dp0 cannot install & goto :choice_default_3 ) 
+if not exist %~dp0\ai_model.py ( echo `ai_model.py` missing in %~dp0 cannot install & goto :choice_default_3 ) 
 
 
 :: Note: "~" or %HOME% is equivalent to "%HOMEDRIVE%%HOMEPATH%\" but the latter is set in VM environments (from what I can tell)
@@ -137,6 +138,7 @@ mkdir !TARGET_DIR!
 copy  %~dp0\yolo.py !TARGET_DIR!
 copy  %~dp0\prompt.txt !TARGET_DIR!
 copy  %~dp0\yolo.yaml !TARGET_DIR!
+copy  %~dp0\ai_model.py !TARGET_DIR!
 goto :EOF
 
 :: Create yolo.bat and input code linking to created directory
@@ -312,4 +314,6 @@ echo   -If you run PowerShell as administrator you can then run `setx OPENAI_API
 echo   -Go to `Start` and search `edit environment variables for your account` and manually create the variable with name `OPENAI_API_KEY` and value `[yourkey]`
 echo (4) Another option is to put the API key in the yolo.yaml configuration file (since v.0.2)
 echo.
+echo Yolo also supports Azure OpenAI, and many other LLMs now. Configure settings in yolo.yaml accordingly.
+echo.
 goto :EOF

install.sh

@@ -7,7 +7,7 @@ TARGET_FULLPATH=$TARGET_DIR/yolo.py
 mkdir -p $TARGET_DIR
 
 echo "- Copying files..."
-cp yolo.py yolo.prompt yolo.yaml $TARGET_DIR
+cp yolo.py prompt.txt yolo.yaml ai_model.py $TARGET_DIR
 chmod +x $TARGET_FULLPATH
 
 # Creates two aliases for use
@@ -34,9 +34,11 @@ fi
 echo
 echo "Done."
 echo
-echo "Make sure you have the OpenAI API key set via one of these options:" 
+echo "Make sure you have your LLM key (e.g. OpenAI API) set via one of these options:" 
 echo "  - environment variable"
-echo "  - .env or an ~/.openai.apikey file or in"
+echo "  - .env or in"
 echo "  - yolo.yaml"
 echo
+echo "Yolo also supports Azure OpenAI, Ollama, groq, Claude now. Change settings in yolo.yaml accordingly."
+echo
 echo "Have fun!"

prompt.txt

@@ -0,0 +1,26 @@
+You are Yolo, a natural language to {shell} command translation engine for {os}. You are an expert in {shell} on {os} and translate the question at the end to valid command line syntax.
+
+Rules:
+* No code style markdown output, ever.
+* Construct valid {shell} command to solve the question
+* Leverage help and man pages to ensure valid syntax and an optimal solution
+* Be concise, think step by step, and show just final commands in plain text
+* Only show a single answer, but you can always chain commands together 
+* Create valid syntax of {shell} on {os}, include comments if useful
+* If python or python3 is installed you can use it to solve problems
+* Even if there is a lack of details, find the most logical solution by going about it step by step
+* Do not return multiple solutions
+* Do not show html, styled, colored formatting 
+* Do not create invalid syntax or cause syntax errors
+* Do not add unnecessary text in the response 
+* Do not add notes or intro sentences 
+* Do not show multiple distinct solutions to the question
+* Do not add explanations on what the commands do
+* Do not return what the question was 
+* Do not repeat or paraphrase the question in your response 
+* Do not rush to a conclusion
+* Never start a response with ```
+
+Follow above rules. There are no exceptions to these rules. 
+
+Question: 

pylintrc

@@ -1,499 +0,0 @@
-[MASTER]
-
-# A comma-separated list of package or module names from where C extensions may
-# be loaded. Extensions are loading into the active Python interpreter and may
-# run arbitrary code.
-extension-pkg-whitelist=
-
-# Specify a score threshold to be exceeded before program exits with error.
-fail-under=10.0
-
-# Add files or directories to the blacklist. They should be base names, not
-# paths.
-ignore=CVS
-
-# Add files or directories matching the regex patterns to the blacklist. The
-# regex matches against base names, not paths.
-ignore-patterns=
-
-# Python code to execute, usually for sys.path manipulation such as
-# pygtk.require().
-#init-hook=
-
-# Use multiple processes to speed up Pylint. Specifying 0 will auto-detect the
-# number of processors available to use.
-jobs=1
-
-# Control the amount of potential inferred values when inferring a single
-# object. This can help the performance when dealing with large functions or
-# complex, nested conditions.
-limit-inference-results=100
-
-# List of plugins (as comma separated values of python module names) to load,
-# usually to register additional checkers.
-load-plugins=
-
-# Pickle collected data for later comparisons.
-persistent=yes
-
-# When enabled, pylint would attempt to guess common misconfiguration and emit
-# user-friendly hints instead of false-positive error messages.
-suggestion-mode=yes
-
-# Allow loading of arbitrary C extensions. Extensions are imported into the
-# active Python interpreter and may run arbitrary code.
-unsafe-load-any-extension=no
-
-
-[MESSAGES CONTROL]
-
-# Only show warnings with the listed confidence levels. Leave empty to show
-# all. Valid levels: HIGH, INFERENCE, INFERENCE_FAILURE, UNDEFINED.
-confidence=
-
-# Enable the message, report, category or checker with the given id(s). You can
-# either give multiple identifier separated by comma (,) or put this option
-# multiple time (only on the command line, not in the configuration file where
-# it should appear only once). See also the "--disable" option for examples.
-enable=c-extension-no-member
-
-
-[REPORTS]
-
-# Python expression which should return a score less than or equal to 10. You
-# have access to the variables 'error', 'warning', 'refactor', and 'convention'
-# which contain the number of messages in each category, as well as 'statement'
-# which is the total number of statements analyzed. This score is used by the
-# global evaluation report (RP0004).
-evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10)
-
-# Template used to display messages. This is a python new-style format string
-# used to format the message information. See doc for all details.
-#msg-template=
-
-# Set the output format. Available formats are text, parseable, colorized, json
-# and msvs (visual studio). You can also give a reporter class, e.g.
-# mypackage.mymodule.MyReporterClass.
-output-format=text
-
-# Tells whether to display a full report or only the messages.
-reports=no
-
-# Activate the evaluation score.
-score=yes
-
-
-[REFACTORING]
-
-# Maximum number of nested blocks for function / method body
-max-nested-blocks=5
-
-# Complete name of functions that never returns. When checking for
-# inconsistent-return-statements if a never returning function is called then
-# it will be considered as an explicit return statement and no message will be
-# printed.
-never-returning-functions=sys.exit
-
-
-[LOGGING]
-
-# The type of string formatting that logging methods do. `old` means using %
-# formatting, `new` is for `{}` formatting.
-logging-format-style=old
-
-# Logging modules to check that the string format arguments are in logging
-# function parameter format.
-logging-modules=logging
-
-
-[SPELLING]
-
-# Limits count of emitted suggestions for spelling mistakes.
-max-spelling-suggestions=4
-
-# Spelling dictionary name. Available dictionaries: none. To make it work,
-# install the python-enchant package.
-spelling-dict=
-
-# List of comma separated words that should not be checked.
-spelling-ignore-words=
-
-# A path to a file that contains the private dictionary; one word per line.
-spelling-private-dict-file=
-
-# Tells whether to store unknown words to the private dictionary (see the
-# --spelling-private-dict-file option) instead of raising a message.
-spelling-store-unknown-words=no
-
-
-[MISCELLANEOUS]
-
-# List of note tags to take in consideration, separated by a comma.
-notes=FIXME,
-      XXX,
-      TODO
-
-# Regular expression of note tags to take in consideration.
-#notes-rgx=
-
-
-[TYPECHECK]
-
-# List of decorators that produce context managers, such as
-# contextlib.contextmanager. Add to this list to register other decorators that
-# produce valid context managers.
-contextmanager-decorators=contextlib.contextmanager
-
-# List of members which are set dynamically and missed by pylint inference
-# system, and so shouldn't trigger E1101 when accessed. Python regular
-# expressions are accepted.
-generated-members=
-
-# Tells whether missing members accessed in mixin class should be ignored. A
-# mixin class is detected if its name ends with "mixin" (case insensitive).
-ignore-mixin-members=yes
-
-# Tells whether to warn about missing members when the owner of the attribute
-# is inferred to be None.
-ignore-none=yes
-
-# This flag controls whether pylint should warn about no-member and similar
-# checks whenever an opaque object is returned when inferring. The inference
-# can return multiple potential results while evaluating a Python object, but
-# some branches might not be evaluated, which results in partial inference. In
-# that case, it might be useful to still emit no-member and other checks for
-# the rest of the inferred objects.
-ignore-on-opaque-inference=yes
-
-# List of class names for which member attributes should not be checked (useful
-# for classes with dynamically set attributes). This supports the use of
-# qualified names.
-ignored-classes=optparse.Values,thread._local,_thread._local
-
-# List of module names for which member attributes should not be checked
-# (useful for modules/projects where namespaces are manipulated during runtime
-# and thus existing member attributes cannot be deduced by static analysis). It
-# supports qualified module names, as well as Unix pattern matching.
-ignored-modules=
-
-# Show a hint with possible names when a member name was not found. The aspect
-# of finding the hint is based on edit distance.
-missing-member-hint=yes
-
-# The minimum edit distance a name should have in order to be considered a
-# similar match for a missing member name.
-missing-member-hint-distance=1
-
-# The total number of similar names that should be taken in consideration when
-# showing a hint for a missing member.
-missing-member-max-choices=1
-
-# List of decorators that change the signature of a decorated function.
-signature-mutators=
-
-
-[VARIABLES]
-
-# List of additional names supposed to be defined in builtins. Remember that
-# you should avoid defining new builtins when possible.
-additional-builtins=
-
-# Tells whether unused global variables should be treated as a violation.
-allow-global-unused-variables=yes
-
-# List of strings which can identify a callback function by name. A callback
-# name must start or end with one of those strings.
-callbacks=cb_,
-          _cb
-
-# A regular expression matching the name of dummy variables (i.e. expected to
-# not be used).
-dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_
-
-# Argument names that match this expression will be ignored. Default to name
-# with leading underscore.
-ignored-argument-names=_.*|^ignored_|^unused_
-
-# Tells whether we should check for unused import in __init__ files.
-init-import=no
-
-# List of qualified module names which can have objects that can redefine
-# builtins.
-redefining-builtins-modules=six.moves,past.builtins,future.builtins,builtins,io
-
-
-[FORMAT]
-
-# Expected format of line ending, e.g. empty (any line ending), LF or CRLF.
-expected-line-ending-format=
-
-# Regexp for a line that is allowed to be longer than the limit.
-ignore-long-lines=^\s*(# )?<?https?://\S+>?$
-
-# Number of spaces of indent required inside a hanging or continued line.
-indent-after-paren=4
-
-# String used as indentation unit. This is usually "    " (4 spaces) or "\t" (1
-# tab).
-indent-string='    '
-
-# Maximum number of characters on a single line.
-max-line-length=100
-
-# Maximum number of lines in a module.
-max-module-lines=1000
-
-# Allow the body of a class to be on the same line as the declaration if body
-# contains single statement.
-single-line-class-stmt=no
-
-# Allow the body of an if to be on the same line as the test if there is no
-# else.
-single-line-if-stmt=no
-
-
-[SIMILARITIES]
-
-# Ignore comments when computing similarities.
-ignore-comments=yes
-
-# Ignore docstrings when computing similarities.
-ignore-docstrings=yes
-
-# Ignore imports when computing similarities.
-ignore-imports=no
-
-# Minimum lines number of a similarity.
-min-similarity-lines=4
-
-
-[BASIC]
-
-# Naming style matching correct argument names.
-argument-naming-style=snake_case
-
-# Regular expression matching correct argument names. Overrides argument-
-# naming-style.
-#argument-rgx=
-
-# Naming style matching correct attribute names.
-attr-naming-style=snake_case
-
-# Regular expression matching correct attribute names. Overrides attr-naming-
-# style.
-#attr-rgx=
-
-# Bad variable names which should always be refused, separated by a comma.
-bad-names=foo,
-          bar,
-          baz,
-          toto,
-          tutu,
-          tata
-
-# Bad variable names regexes, separated by a comma. If names match any regex,
-# they will always be refused
-bad-names-rgxs=
-
-# Naming style matching correct class attribute names.
-class-attribute-naming-style=any
-
-# Regular expression matching correct class attribute names. Overrides class-
-# attribute-naming-style.
-#class-attribute-rgx=
-
-# Naming style matching correct class names.
-class-naming-style=PascalCase
-
-# Regular expression matching correct class names. Overrides class-naming-
-# style.
-#class-rgx=
-
-# Naming style matching correct constant names.
-const-naming-style=UPPER_CASE
-
-# Regular expression matching correct constant names. Overrides const-naming-
-# style.
-#const-rgx=
-
-# Minimum line length for functions/classes that require docstrings, shorter
-# ones are exempt.
-docstring-min-length=-1
-
-# Naming style matching correct function names.
-function-naming-style=snake_case
-
-# Regular expression matching correct function names. Overrides function-
-# naming-style.
-#function-rgx=
-
-# Good variable names which should always be accepted, separated by a comma.
-good-names=i,
-           j,
-           k,
-           ex,
-           Run,
-           _
-
-# Good variable names regexes, separated by a comma. If names match any regex,
-# they will always be accepted
-good-names-rgxs=
-
-# Include a hint for the correct naming format with invalid-name.
-include-naming-hint=no
-
-# Naming style matching correct inline iteration names.
-inlinevar-naming-style=any
-
-# Regular expression matching correct inline iteration names. Overrides
-# inlinevar-naming-style.
-#inlinevar-rgx=
-
-# Naming style matching correct method names.
-method-naming-style=snake_case
-
-# Regular expression matching correct method names. Overrides method-naming-
-# style.
-#method-rgx=
-
-# Naming style matching correct module names.
-module-naming-style=snake_case
-
-# Regular expression matching correct module names. Overrides module-naming-
-# style.
-#module-rgx=
-
-# Colon-delimited sets of names that determine each other's naming style when
-# the name regexes allow several styles.
-name-group=
-
-# Regular expression which should only match function or class names that do
-# not require a docstring.
-no-docstring-rgx=^_
-
-# List of decorators that produce properties, such as abc.abstractproperty. Add
-# to this list to register other decorators that produce valid properties.
-# These decorators are taken in consideration only for invalid-name.
-property-classes=abc.abstractproperty
-
-# Naming style matching correct variable names.
-variable-naming-style=snake_case
-
-# Regular expression matching correct variable names. Overrides variable-
-# naming-style.
-#variable-rgx=
-
-
-[STRING]
-
-# This flag controls whether inconsistent-quotes generates a warning when the
-# character used as a quote delimiter is used inconsistently within a module.
-check-quote-consistency=no
-
-# This flag controls whether the implicit-str-concat should generate a warning
-# on implicit string concatenation in sequences defined over several lines.
-check-str-concat-over-line-jumps=no
-
-
-[IMPORTS]
-
-# List of modules that can be imported at any level, not just the top level
-# one.
-allow-any-import-level=
-
-# Allow wildcard imports from modules that define __all__.
-allow-wildcard-with-all=no
-
-# Analyse import fallback blocks. This can be used to support both Python 2 and
-# 3 compatible code, which means that the block might have code that exists
-# only in one or another interpreter, leading to false positives when analysed.
-analyse-fallback-blocks=no
-
-# Deprecated modules which should not be used, separated by a comma.
-deprecated-modules=optparse,tkinter.tix
-
-# Create a graph of external dependencies in the given file (report RP0402 must
-# not be disabled).
-ext-import-graph=
-
-# Create a graph of every (i.e. internal and external) dependencies in the
-# given file (report RP0402 must not be disabled).
-import-graph=
-
-# Create a graph of internal dependencies in the given file (report RP0402 must
-# not be disabled).
-int-import-graph=
-
-# Force import order to recognize a module as part of the standard
-# compatibility libraries.
-known-standard-library=
-
-# Force import order to recognize a module as part of a third party library.
-known-third-party=enchant
-
-# Couples of modules and preferred modules, separated by a comma.
-preferred-modules=
-
-
-[CLASSES]
-
-# List of method names used to declare (i.e. assign) instance attributes.
-defining-attr-methods=__init__,
-                      __new__,
-                      setUp,
-                      __post_init__
-
-# List of member names, which should be excluded from the protected access
-# warning.
-exclude-protected=_asdict,
-                  _fields,
-                  _replace,
-                  _source,
-                  _make
-
-# List of valid names for the first argument in a class method.
-valid-classmethod-first-arg=cls
-
-# List of valid names for the first argument in a metaclass class method.
-valid-metaclass-classmethod-first-arg=cls
-
-
-[DESIGN]
-
-# Maximum number of arguments for function / method.
-max-args=5
-
-# Maximum number of attributes for a class (see R0902).
-max-attributes=7
-
-# Maximum number of boolean expressions in an if statement (see R0916).
-max-bool-expr=5
-
-# Maximum number of branch for function / method body.
-max-branches=12
-
-# Maximum number of locals for function / method body.
-max-locals=15
-
-# Maximum number of parents for a class (see R0901).
-max-parents=7
-
-# Maximum number of public methods for a class (see R0904).
-max-public-methods=20
-
-# Maximum number of return / yield for function / method body.
-max-returns=6
-
-# Maximum number of statements in function / method body.
-max-statements=50
-
-# Minimum number of public methods for a class (see R0903).
-min-public-methods=2
-
-
-[EXCEPTIONS]
-
-# Exceptions that will emit a warning when being caught. Defaults to
-# "BaseException, Exception".
-overgeneral-exceptions=BaseException,
-                       Exception

requirements.txt

@@ -1,7 +1,10 @@
-openai==0.27
+ollama==0.2.1
-termcolor==2.2.0
+openai==1.35.7
-colorama==0.4.4
+termcolor==2.4.0
-python-dotenv==1.0.0
+colorama==0.4.6
-distro==1.7.0
+python-dotenv==1.0.1
-PyYAML==5.4.1
+distro==1.9.0
-pyperclip==1.8.2
+PyYAML==6.0.1
+pyperclip==1.9.0
+groq==0.9.0
+anthropic==0.30.0

yolo.prompt

@@ -1,31 +0,0 @@
-Act as a natural language to {shell} command translation engine on {os}.
-
-You are an expert in {shell} on {os} and translate the question at the end to valid syntax.
-
-Follow these rules:
-Construct valid {shell} command that solve the question
-Leverage help and man pages to ensure valid syntax and an optimal solution
-Be concise 
-Just show the commands 
-Return only plaintext 
-Only show a single answer, but you can always chain commands together 
-Think step by step
-Only create valid syntax (you can use comments if it makes sense)
-If python is installed you can use it to solve problems
-if python3 is installed you can use it to solve problems
-Even if there is a lack of details, attempt to find the most logical solution by going about it step by step
-Do not return multiple solutions
-Do not show html, styled, colored formatting 
-Do not creating invalid syntax 
-Do not add unnecessary text in the response 
-Do not add notes or intro sentences 
-Do not show multiple distinct solutions to the question
-Do not add explanations on what the commands do
-Do not return what the question was 
-Do not repeat or paraphrase the question in your response 
-Do not cause syntax errors
-Do not rush to a conclusion
-
-Follow all of the above rules. This is important you MUST follow the above rules. There are no exceptions to these rules. You must always follow them. No exceptions.
-
-Question: 

yolo.py

@@ -1,385 +1,198 @@
-"""
+#!/usr/bin/env python3
-AI Chatbot to generate shell commands.
 
-This script allows the user to ask their question in plain English and translates
+# MIT License
-that question into a command that can be run in the shell. The functionalities
+# Copyright (c) 2023-2024 wunderwuzzi23
-include leveraging OpenAI's GPT models to generate command, verifying newly generated
+# Greetings from Seattle! 
-commands, checking commands for any unsafe attributes, and allowing the user to
-execute or modify the generated command.
 
-This program is an implementation of an AI model used to assist users in
-generating Unix/shell commands or other scripts, based on their natural language
-input. The objective is to aid those users who might not remember the exact syntax
-of every command or script they frequently use.
-
-Sources:
-— https://github.com/wunderwuzzi23/yolo-ai-cmdbot
-"""
 import os
 import platform
-import subprocess
+from ai_model import AIModel, GroqModel, OpenAIModel, OllamaModel, AnthropicModel, AzureOpenAIModel
 import sys
-
+import subprocess
-import argparse
+import dotenv 
 import distro
-import dotenv
-import openai
-import pyperclip
 import yaml
-
+import pyperclip
 from termcolor import colored
 from colorama import init
 
-CONFIG_FILE = "yolo.yaml"
+def read_config():
-PROMPT_FILE = "yolo.prompt"
+  ## Find the executing directory (e.g. in case an alias is set)
+  ## So we can find the config file
+  yolo_path = os.path.abspath(__file__)
+  prompt_path = os.path.dirname(yolo_path)
 
-def read_yaml_config() -> any:
+  config_file = os.path.join(prompt_path, "yolo.yaml")
-    """
+  with open(config_file, 'r') as file:
-    Read the configuration file from the executing directory.
+    return yaml.safe_load(file)
 
-    This function determines the execution folder (which may vary if an alias is set) in order to
+def get_system_prompt(shell):
-    find the configuration file. It reads the file and returns its content in a Python data
+  ## Find the executing directory (e.g. in case an alias is set)
-    structure.
+  ## So we can find the prompt.txt file
+  yolo_path = os.path.abspath(__file__)
+  prompt_path = os.path.dirname(yolo_path)
 
-    Returns:
+  ## Load the prompt and prep it
-        The content of the configuration file. Could be dictionary, list, etc. depending on
+  prompt_file = os.path.join(prompt_path, "prompt.txt")
-        the YAML file structure.
+  system_prompt = open(prompt_file,"r").read()
-    """
+  system_prompt = system_prompt.replace("{shell}", shell)
-    yolo_path = os.path.abspath(__file__)
+  system_prompt = system_prompt.replace("{os}", get_os_friendly_name())
-    prompt_path = os.path.dirname(yolo_path)
 
-    config_file = os.path.join(prompt_path, CONFIG_FILE)
+  return system_prompt
-    with open(config_file, 'r') as file:
-        return yaml.safe_load(file)
 
-def set_openai_api_key(config):
+def ensure_prompt_is_question(prompt):
-    """
+  if prompt[-1:] != "?" and prompt[-1:] != ".":
-    Set the OpenAI API key by attempting several methods.
+    prompt+="?"
+  return prompt
 
-    This function first tries to grab the OpenAI API key from environment variables,
+def print_usage(config):
-    if not found, it then looks for the key in the `.openai.apikey` in the home directory,
+  print("Yolo v0.5 - by @wunderwuzzi23 (June 29, 2024)")
-    and lastly, it will look in the provided config dictionary. It sets the `openai.api_key`
+  print()
-    with the retrieved key.
+  print("Usage: yolo [-a] list the current directory information")
+  print("Argument: -a: Prompt the user before running the command (only useful when safety is off)")
+  print()
 
-    Parameters:
+  print("Current configuration per yolo.yaml:")
-        config (dict): A dictionary containing configuration values.
+  print("* API          : " + str(config["api"]))
-                       It may contain `openai_api_key` as one of the keys.
+  print("* Model        : " + str(config["model"]))
-    """
+  print("* Temperature  : " + str(config["temperature"]))
-    dotenv.load_dotenv()
+  print("* Max. Tokens  : " + str(config["max_tokens"]))
-
+  print("* Safety       : " + str(bool(config["safety"])))
-    # Method 1: Read API key from environment variable
+  print("* Command Color: " + str(config["suggested_command_color"]))
-    # The user can set their OpenAI API key by creating a ".env" file in the same
-    # directory as this script or by exporting it to their environment variables.
-    # The file or environment variable should contain the line `OPENAI_API_KEY="<yourkey>"`.
-    config["openai_api_key"] = os.getenv("OPENAI_API_KEY")
-
-    # Method 2: Read API key from a file in the home directory
-    # The user can also place a file named ".openai.apikey" in their home directory,
-    # which includes the API key in raw format. This method might be deprecated in future versions.
-    if not openai.api_key:  # Check this to avoid potential "invalid filepath" error.
-        home_path = os.path.expanduser("~")
-        openai.api_key_path = os.path.join(home_path, ".openai.apikey")
-
-    # Method 3: Read API key from the provided config dictionary
-    # The final method to set the API key is by providing it in the 'config' dictionary under the
-    # key 'openai_api_key'. For instance, in a `yolo.yaml` config file, it would appear as
-    # `openai_apikey: <yourkey>`.
-    if not openai.api_key:
-        openai.api_key = config["openai_api_key"]
-
-def print_config(config):
-    """
-    Print config information.
-
-    Given an input configuration dictionary, this function prints out the
-    current configurations per yolo.yaml. This includes details on "model",
-    "temperature", "max_tokens", "safety", and "shell".
-
-    Parameters
-    ----------
-    config : dict
-        A dictionary containing the various configuration parameters. It should have
-        the following keys: "model", "temperature", "max_tokens", "safety", "shell".
-    """
-    print("Current configuration per yolo.yaml:")
-    print("— Model        : " + str(config["model"]))
-    print("— Temperature  : " + str(config["temperature"]))
-    print("— Max. Tokens  : " + str(config["max_tokens"]))
-    print("— Safety       : " + str(bool(config["safety"])))
-    print("— Shell        : " + str(config["shell"]))
 
 def get_os_friendly_name():
-    """
+  os_name = platform.system()
-    Returns a friendly name of the user's operating system.
-
-    The function retrieves the current system platform name using the `platform.system()` function.
-    For Linux, it appends the distribution name retrieved from `distro.name(pretty=True)` to give a
-    more descriptive representation. For Darwin (Apple's macOS), it appends "macOS" to "Darwin" to
-    make the output clearer to the user.
-
-    Returns
-    -------
-    str
-        A friendly name for the user's operating system. It will be one of the following:
-
-        - "Linux/<distribution name>"
-        - "Darwin/macOS"
-        - The system string returned by `platform.system()` if it's not Linux or Darwin.
-    """
-    os_name = platform.system()
-
-    if os_name == "Linux":
-        os_name = "Linux/" + distro.name(pretty=True)
-    elif os_name == "Darwin":
-        os_name = "Darwin/macOS"
 
+  if os_name == "Linux":
+    return "Linux/"+distro.name(pretty=True)
+  elif os_name == "Windows":
+    return os_name
+  elif os_name == "Darwin":
+    return "Darwin/macOS"
+  else:
     return os_name
 
-def get_full_prompt(user_prompt, shell):
+def chat_completion(client, query, config, shell):
-    """
+  if query == "":
-    Constructs a full prompt string by appending the user's prompt to a predefined prompt template
+      print ("No user prompt specified.")
-    located in the PROMPT_FILE file.
+      sys.exit(-1)
+ 
+  system_prompt = get_system_prompt(shell)
 
-    The function finds the absolute path of the currently executing file, and based on this path,
+  response = client.chat(
-    identifies the directory of PROMPT_FILE. It reads this file, replaces placeholders {shell}
+    model=config["model"],
-    and {os} in the text file with a passed shell parameter and the friendly name of the operating
+    messages=[
-    system respectively. The user prompt is then appended to this pre-prompt. If the resulting
+        {"role": "system", "content": system_prompt},
-    prompt does not end with a question mark or a period, a question mark is added at last.
+        {"role": "user", "content": query}
-
+    ],
-    Parameters
+    temperature=config["temperature"],
-    ----------
+    max_tokens=config["max_tokens"])
-    user_prompt : str
+ 
-        The prompt supplied by the user to be appended to the pre-prompt.
+  return response
-    shell : str
-        The shell information to be inserted in the place of {shell} placeholder in PROMPT_FILE.
-
-    Returns
-    -------
-    str
-        The full prompt, constructed from the template prompt in PROMPT_FILE,
-        user-provided shell info, the OS name, and the user-supplied prompt string.
-    """
-    yolo_path = os.path.abspath(__file__)
-    prompt_path = os.path.dirname(yolo_path)
-
-    ## Load the prompt and prep it
-    prompt_file = os.path.join(prompt_path, PROMPT_FILE)
-    pre_prompt = open(prompt_file,"r").read()
-    pre_prompt = pre_prompt.replace("{shell}", shell)
-    pre_prompt = pre_prompt.replace("{os}", get_os_friendly_name())
-    prompt = pre_prompt + user_prompt
-
-    # Be nice and make it a question.
-    if prompt[-1:] != "?" and prompt[-1:] != ".":
-        prompt+="?"
-
-    return prompt
-
-def call_open_ai(config, query):
-    """
-    Do we have a prompt from the user?
-    """
-    if query == "":
-        print ("No user prompt specified.")
-        sys.exit(-1)
-
-    # Load the correct prompt based on shell and OS and append the user's prompt.
-    prompt = get_full_prompt(query, config["shell"])
-
-    # Make the first line also the system prompt
-    system_prompt = prompt[1]
-    #print(prompt)
-
-    # Call the ChatGPT API
-    response = openai.ChatCompletion.create(
-        model=config["model"],
-        messages=[
-            {"role": "system", "content": system_prompt},
-            {"role": "user", "content": prompt}
-        ],
-        temperature=config["temperature"],
-        max_tokens=config["max_tokens"],
-    )
-
-    return response.choices[0].message.content.strip()
 
 def check_for_issue(response):
-    """
+  prefixes = ("sorry", "i'm sorry", "the question is not clear", "i'm", "i am")
-    Checks the given response for any issues and raise an error when detected.
+  if response.lower().startswith(prefixes):
-
+    print(colored("There was an issue: "+response, 'red'))
-    The function checks if the supplied text response begins with any of a set of predefined
+    sys.exit(-1)
-    prefixes, which indicate a problem with the response. If such a prefix is found, an error
-    message is printed to the console in red, and the program exits with a -1 status code.
-
-    Parameters
-    ----------
-    response : str
-        A response text string that needs to be examined for any issues.
-    """
-    prefixes = ("sorry", "i'm sorry", "the question is not clear", "i'm", "i am")
-    if response.lower().startswith(prefixes):
-        print(colored("There was an issue: "+response, 'red'))
-        sys.exit(-1)
 
 def check_for_markdown(response):
-    """
+  if response.count("```",2):
-    Checks for the presence of markdown formatting (specifically, code snippet markdown) in the
+    print(colored("The proposed command contains markdown, so I did not execute the response directly: \n", 'red')+response)
-    provided response.
+    sys.exit(-1)
-
-    This function considers the presence of markdown formatting (specifically, code block
-    formatting marked by ```) in the `response` as an "odd corner case". If such a case is
-    detected, it prints an error message in red, along with the markdown-contained response, and
-    then terminates the program with a -1 status code.
-
-    Parameters
-    ----------
-    response : str
-        A response text string that needs to be examined for markdown formatting.
-    """
-    if response.count("```",2):
-        print(colored(
-            "The proposed command contains markdown, response not executed directly: \n", 'red'
-        ) + response)
-        sys.exit(-1)
 
 def missing_posix_display():
-    """
+  return 'DISPLAY' not in os.environ or not os.environ["DISPLAY"]
-    Checks if the DISPLAY environment variable is set in a POSIX-compliant shell.
 
-    This function runs a shell subprocess that outputs the value of the DISPLAY environment
+def prompt_user_for_action(config, ask_flag, response):
-    variable. It then checks if this value is unset (i.e., equals a newline 'b'\\n'') in the
+  print("Command: " + colored(response, config["suggested_command_color"], attrs=['bold']))
-    current shell environment. If the DISPLAY variable is unset, the function returns `True`
+  
-    indicating a "missing" display; otherwise, it returns `False`.
+  modify_snippet = ""
+  if bool(config["modify"]) == True:
+    modify_snippet = " [m]odify"
+    
+  copy_to_clipboard_snippet = " [c]opy to clipboard"
+  if os.name == "posix" and missing_posix_display():
+    if get_os_friendly_name() != "Darwin/macOS":
+      copy_to_clipboard_snippet = ""
 
-    Returns
+  if bool(config["safety"]) == True or ask_flag == True:
-    -------
+    prompt_text = f"Execute command? [Y]es [n]o{modify_snippet}{copy_to_clipboard_snippet} ==> "
-    bool
+    print(prompt_text, end = '')
-        `True` if the DISPLAY environment variable is unset or empty, `False` otherwise.
+    user_input = input()
-    """
+    return user_input 
-    display = subprocess.check_output("echo $DISPLAY", shell=True)
+  
-
+  if bool(config["safety"]) == False:
-    return display == b'\n'
+     return "Y"
-
-def prompt_user_input(config, response):
-    """
-    Print the command proposal in blue and prompt the user for next action based on the safety
-    configuration.
-
-    The user is given options to execute, modify, or copy the command to clipboard if the safety
-    configuration is enabled (config["safety"] = True). If the safety configuration is off
-    (config["safety"] = False), the function automatically assumes an execution action ('Y' for
-    Yes). In a POSIX-compliant shell with no display available (checked using
-    `missing_posix_display()`), the 'copy to clipboard' option is omitted.
-
-    Parameters
-    ----------
-    config : dict
-        The system configurations dictionary which contains a "safety" key
-        to determine user prompt options.
-    response : str
-        The proposed command which is to be printed and may be executed by the user.
-    """
-    print("Command: " + colored(response, 'blue'))
-
-    if config["safety"]:
-        prompt_text = "Execute command? [Y]es [n]o [m]odify [c]opy to clipboard ==> "
-
-        if os.name == "posix" and missing_posix_display():
-            prompt_text =  "Execute command? [Y]es [n]o [m]odify ==> "
-
-        print(prompt_text, end = '')
-
-        user_input = input()
-    else:
-        user_input = "Y"
-
-    return user_input
-
-def evaluate_input(config, user_input, command):
-    """
-    Evaluate the user input to either execute, modify, or copy the command.
-
-    Based on the user's response, this function takes action:
-    - If the user response is 'Y' or blank, the given command gets executed in the shell.
-    - If the user response is 'M', user can modify the command and the modified command is executed
-      recursively.
-    - If the user response is 'C', the command is copied to the clipboard.
-
-    Parameters
-    ----------
-    config : dict
-        The system configurations dictionary. It should contain a "shell" key specifying the shell
-        environment.
-    user_input : str
-        The user response which determines the course of action. It can be 'Y', 'n', 'm', 'c',
-        or '' (empty string).
-    command : str
-        The command which is either executed, modified, or copied to clipboard.
-    """
-    if user_input.upper() == "Y" or user_input == "":
-        if config["shell"] == "powershell.exe":
-            subprocess.run([config["shell"], "/c", command], shell=False, check=True)
-        else:
-            # Unix: /bin/bash /bin/zsh: uses -c both Ubuntu and macOS should work, others might not
-            subprocess.run([config["shell"], "-c", command], shell=False, check=True)
-
-    if user_input.upper() == "M":
-        print("Modify prompt: ", end = '')
-        modded_query = input()
-        modded_response = call_open_ai(config, modded_query)
-        check_for_issue(modded_response)
-        check_for_markdown(modded_response)
-        modded_user_input = prompt_user_input(config, modded_response)
-        print()
-        evaluate_input(config, modded_user_input, modded_response)
-
-    if user_input.upper() == "C":
-        if os.name == "posix" and missing_posix_display():
-            return
-        pyperclip.copy(command)
-        print("Copied command to clipboard.")
 
+def eval_user_intent_and_execute(client, config, user_input, command, shell, ask_flag):
+  if user_input.upper() not in ["", "Y", "C", "M"]:
+    print("No action taken.")
+    return
+  
+  if user_input.upper() == "Y" or user_input == "":
+    if shell == "powershell.exe":
+      subprocess.run([shell, "/c", command], shell=False)  
+    else: 
+      # Unix: /bin/bash /bin/zsh: uses -c both Ubuntu and macOS should work, others might not
+      subprocess.run([shell, "-c", command], shell=False)
+  
+  if bool(config["modify"]) and user_input.upper() == "M":
+    print("Modify prompt: ", end = '')
+    modded_query = input()
+    modded_response = chat_completion(client, modded_query, config, shell)
+    check_for_issue(modded_response)
+    check_for_markdown(modded_response)
+    user_intent = prompt_user_for_action(config, ask_flag, modded_response)
+    print()
+    eval_user_intent_and_execute(client, config, user_intent, modded_response, shell, ask_flag)
+  
+  if user_input.upper() == "C":
+      if os.name == "posix" and missing_posix_display():
+        if get_os_friendly_name() != "Darwin/macOS":
+          return
+      pyperclip.copy(command) 
+      print("Copied command to clipboard.")
 
 def main():
-    """
+  init()  #Enable color output on Windows using colorama
-    Defined starting point of source code.
+  dotenv.load_dotenv()
-    """
-    parser = argparse.ArgumentParser(
-        description='AI bot that translates your question to a command.'
-    )
-    parser.add_argument('text', nargs='+',
-                        help='A sequence of strings')
-    parser.add_argument("-s", "--safety", action='store_true',
-                        help='Enable safety mode (only useful when safety is off)')
-    parser.add_argument("-c", "--config", action='store_true',
-                        help='Print current configuration')
-    args = parser.parse_args()
 
-    # Load configuration
+  config = read_config()
-    config = read_yaml_config()
+  client = AIModel.get_model_client(config)
-    set_openai_api_key(config)
 
-    # Process parameters
+  # Unix based SHELL (/bin/bash, /bin/zsh), otherwise assuming it's Windows
-    user_prompt = " ".join(args.text)
+  shell = os.environ.get("SHELL", "powershell.exe") 
 
-    if args.safety:
+  command_start_idx  = 1     # Question starts at which argv index?
-        config["safety"] = args.safety
+  ask_flag = False           # safety switch -a command line argument
+  yolo = ""                  # user's answer to safety switch (-a) question y/n
 
-    # Unix based SHELL (/bin/bash, /bin/zsh), otherwise assuming it's Windows
+  # Parse arguments and make sure we have at least a single word
-    config["shell"] = os.environ.get("SHELL", "powershell.exe")
+  if len(sys.argv) < 2:
+    print_usage(config)
+    sys.exit(-1)
 
-    if args.config:
+  # Safety switch via argument -a (local override of global setting)
-        print_config(config)
+  # Force Y/n questions before running the command
+  if sys.argv[1] == "-a":
+    ask_flag = True
+    command_start_idx = 2
 
-    # Enable color output on Windows using colorama
+  # To allow easy/natural use we don't require the input to be a single string.
-    init()
+  # User can just type yolo what is my name? without having to put the question between ''
+  arguments = sys.argv[command_start_idx:]
+  user_prompt = " ".join(arguments)
 
-    res_command = call_open_ai(config, user_prompt)
+  ## core prompting loop logic
-    check_for_issue(res_command)
+  result = chat_completion(client, user_prompt, config, shell) 
-    check_for_markdown(res_command)
+  check_for_issue(result)
-    user_input = prompt_user_input(config, res_command)
+  check_for_markdown(result)
-    print()
+
-    evaluate_input(config, user_input, res_command)
+  users_intent = prompt_user_for_action(config, ask_flag, result)
+  print()
+  eval_user_intent_and_execute(client, config, users_intent, result, shell, ask_flag)
 
 if __name__ == "__main__":
-    main()
+  main()
+  

yolo.yaml

@@ -1,9 +1,22 @@
-model: gpt-3.5-turbo  # If you have access to gpt-4 API already, you can update this.
+api: openai   # openai, azure, groq, ollama, anthropic         
+model: gpt-4o # if azure this is the deployment name
+              # other options: gpt-4o, llama3-8b-8192, or claude-3-5-sonnet-20240620
+
+# Azure specific (only needed if api: azure-openai)
+azure_endpoint: https://<name>.openai.azure.com
+azure_api_version: 2024-02-15-preview
+
+# Completion parameters
 temperature: 0
 max_tokens: 500
 
-# Safety: If set to False, commands returned from the AI will be run *without* prompting the user.
+safety: True                  # Safety: If set to False, commands from LLM run *without* prompting the user.
-safety: True
+modify: False                 # Enable prompt modify feature
+suggested_command_color: blue # Suggested Command Color
 
-# Open AI API Key (optional): The key can aso be provided via environment variable (OPENAI_API_KEY), .env, or ~/.openai.apikey file
+# API Keys (optional): Preferred to use environment variables 
-openai_api_key:
+# OPENAI_API_KEY, AZURE_OPENAI_API_KEY, ANTHROPIC_API_KEY or GROQ_API_KEY (.env file is also supported)
+azure_openai_api_key: 
+openai_api_key:
+groq_api_key:
+anthropic_api_key: