| Name | par-ai-core JSON |
| Version |
0.1.10
JSON |
| download |
| home_page | None |
| Summary | PAR AI Core |
| upload_time | 2025-01-08 15:09:25 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT License Copyright (c) 2024 Paul Robello Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
ai
anthropic
langchain
llamacpp
ollama
openai
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Par AI Core
[](https://pypi.org/project/par_ai_core/)
[](https://pypi.org/project/par_ai_core/)
[](https://codecov.io/gh/paulrobello/par_ai_core)
## Description
Par AI Core is a Python library that provides a set of tools, helpers, and wrappers built on top of LangChain.
It is designed to accelerate the development of AI-powered applications by offering a streamlined and efficient way
to interact with various Large Language Models (LLMs) and related services. This library serves as the foundation
for my AI projects, encapsulating common functionalities and best practices for LLM integration.
[](https://buymeacoffee.com/probello3)
## Technology
- Python
- LangChain
## Prerequisites
- Python 3.10 or higher
- UV package manager
- API keys for chosen AI provider (except for Ollama and LlamaCpp)
- See (Environment Variables)[#environment-variables] below for provider-specific variables
## Features
* **Simplified LLM Configuration:** Easily configure and manage different LLM providers (OpenAI, Anthropic, etc.) and models through a unified interface.
* **Asynchronous and Synchronous Support:** Supports both asynchronous and synchronous calls to LLMs.
* **Context Management:** Tools for gathering relevant files as context for LLM prompts.
* **Output Formatting:** Utilities for displaying LLM outputs in various formats (JSON, CSV, tables).
* **Cost Tracking:** Optional integration to display the cost of LLM calls.
* **Tool Call Handling:** Support for handling tool calls within LLM interactions.
## Documentation
[Library Documentation](https://htmlpreview.github.io/?https://github.com/paulrobello/par_ai_core/blob/main/src/par_ai_core/docs/index.html)
## Installation
```shell
uv add par_ai_core
```
## Update
```shell
uv add par_ai_core -U
```
## Environment Variables
### Create a .env file in the root of your project with the following content adjusted for your needs
```shell
# AI API KEYS
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GROQ_API_KEY=
XAI_API_KEY=
GOOGLE_API_KEY=
MISTRAL_API_KEY=
GITHUB_TOKEN=
AWS_PROFILE=
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
# Search
GOOGLE_CSE_ID=
GOOGLE_CSE_API_KEY=
SERPER_API_KEY=
SERPER_API_KEY_GOOGLE=
TAVILY_API_KEY=
JINA_API_KEY=
BRAVE_API_KEY=
REDDIT_CLIENT_ID=
REDDIT_CLIENT_SECRET=
# Misc API
WEATHERAPI_KEY=
GITHUB_PERSONAL_ACCESS_TOKEN=
### Tracing (optional)
LANGCHAIN_TRACING_V2=false
LANGCHAIN_ENDPOINT=https://api.smith.langchain.com
LANGCHAIN_API_KEY=
LANGCHAIN_PROJECT=par_ai
# PARAI Related (Not all providers / models support all vars)
PARAI_AI_PROVIDER=
PARAI_MODEL=
PARAI_AI_BASE_URL=
PARAI_TEMPERATURE=
PARAI_TIMEOUT=
PARAI_NUM_CTX=
PARAI_NUM_REDICT=
PARAI_REPEAT_LAST_N=
PARAI_REPEAT_PENALTY=
PARAI_MIROSTAT=
PARAI_MIROSTAT_ETA=
PARAI_MIROSTAT_TAU=
PARAI_TFS_Z=
PARAI_TOP_K=
PARAI_TOP_P=
PARAI_SEED=
```
### AI API KEYS
* ANTHROPIC_API_KEY is required for Anthropic. Get a key from https://console.anthropic.com/
* OPENAI_API_KEY is required for OpenAI. Get a key from https://platform.openai.com/account/api-keys
* GITHUB_TOKEN is required for GitHub Models. Get a free key from https://github.com/marketplace/models
* GOOGLE_API_KEY is required for Google Models. Get a free key from https://console.cloud.google.com
* XAI_API_KEY is required for XAI. Get a free key from https://x.ai/api
* GROQ_API_KEY is required for Groq. Get a free key from https://console.groq.com/
* MISTRAL_API_KEY is required for Mistral. Get a free key from https://console.mistral.ai/
* AWS_PROFILE or AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are used for Bedrock authentication. The environment must
already be authenticated with AWS.
* No key required to use with Ollama or LlamaCpp.
### Search
* TAVILY_API_KEY is required for Tavily AI search. Get a free key from https://tavily.com/. Tavily is much better than
* JINA_API_KEY is required for Jina search. Get a free key from https://jina.ai
* BRAVE_API_KEY is required for Brave search. Get a free key from https://brave.com/search/api/
* SERPER_API_KEY is required for Serper search. Get a free key from https://serper.dev
* SERPER_API_KEY_GOOGLE is required for Google Serper search. Get a free key from https://serpapi.com/
* GOOGLE_CSE_ID and GOOGLE_CSE_API_KEY are required for Google search.
* REDDIT_CLIENT_ID and REDDIT_CLIENT_SECRET are needed for Reddit search. Get a free key
from https://www.reddit.com/prefs/apps/
### Misc API
* GITHUB_PERSONAL_ACCESS_TOKEN is required for GitHub related tools. Get a free key
from https://github.com/settings/tokens
* WEATHERAPI_KEY is required for weather. Get a free key from https://www.weatherapi.com/
* LANGCHAIN_API_KEY is required for Langchain / Langsmith tracing. Get a free key
from https://smith.langchain.com/settings
### PARAI Related
* PARAI_AI_PROVIDER is one of Ollama|OpenAI|Groq|XAI|Anthropic|Google|Bedrock|Github|LlamaCpp
* PARAI_MODEL is the model to use with the selected provider
* PARAI_AI_BASE_URL can be used to override the base url used to call a provider
* PARAI_TEMPERATURE sets model temperature. Range depends on provider usually 0.0 to 1.0
* PARAI_TIMEOUT length of time to wait in seconds for ai response
* PARAI_NUM_CTX sets the context window size. Max size varies by model
* Other PARAI related params are to tweak model responses not all are supported / used by all providers
### Open AI Compatible Providers
If a specify provider is not listed but has an OpenAI compatible endpoint you can use the following combo of vars:
* PARAI_AI_PROVIDER=OpenAI
* PARAI_MODEL=Your selected model
* PARAI_AI_BASE_URL=The providers OpenAI endpoint URL
## Example
```python
"""Basic LLM example using Par AI Core."""
import sys
from dotenv import load_dotenv
from par_ai_core.llm_config import LlmConfig, llm_run_manager
from par_ai_core.llm_providers import (
LlmProvider,
is_provider_api_key_set,
provider_light_models,
)
from par_ai_core.par_logging import console_out
from par_ai_core.pricing_lookup import PricingDisplay
from par_ai_core.provider_cb_info import get_parai_callback
def main() -> None:
"""
Use OpenAI lightweight model to answer a question from the command line.
This function performs the following steps:
1. Checks if OpenAI API key is set
2. Validates that a prompt is provided as a command-line argument
3. Configures an OpenAI chat model
4. Invokes the model with a system and user message
5. Prints the model's response
Requires:
- OPENAI_API_KEY environment variable to be set
- A prompt provided as the first command-line argument
"""
load_dotenv()
# Validate OpenAI API key is available
if not is_provider_api_key_set(LlmProvider.OPENAI):
console_out.print("OpenAI API key not set. Please set the OPENAI_API_KEY environment variable.")
return
# Ensure a prompt is provided via command-line argument
if len(sys.argv) < 2:
console_out.print("Please provide a prompt as 1st command line argument.")
return
# Configure the LLM using OpenAI's lightweight model
llm_config = LlmConfig(provider=LlmProvider.OPENAI, model_name=provider_light_models[LlmProvider.OPENAI])
chat_model = llm_config.build_chat_model()
# Use context manager to handle callbacks for pricing and tool calls
with get_parai_callback(show_pricing=PricingDisplay.DETAILS, show_tool_calls=True, show_end=False):
# Prepare messages with a system context and user prompt
messages: list[dict[str, str]] = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": sys.argv[1]},
]
# Invoke the chat model and get the result
result = chat_model.invoke(messages, config=llm_run_manager.get_runnable_config(chat_model.name or ""))
# Print the model's response
console_out.print(result.content)
if __name__ == "__main__":
main()
```
## Whats New
- Version 0.1.10:
- Add format param to LlmConfig for Ollama output format
- Fixed bug with util function has_stdin_content
- Version 0.1.9:
- Added Mistral support
- Fix dotenv loading bug
- Version 0.1.8:
- Added time display utils
- Made LlmConfig.from_json more robust
- Version 0.1.7:
- Fix documentation issues
- Version 0.1.6:
- Pricing for Deepseek
- Updated Docs
- Version 0.1.5:
- Initial release
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Author
Paul Robello - probello@gmail.com
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"description": "# Par AI Core\n\n[](https://pypi.org/project/par_ai_core/)\n[](https://pypi.org/project/par_ai_core/) \n\n \n\n[](https://codecov.io/gh/paulrobello/par_ai_core)\n\n## Description\nPar AI Core is a Python library that provides a set of tools, helpers, and wrappers built on top of LangChain. \nIt is designed to accelerate the development of AI-powered applications by offering a streamlined and efficient way \nto interact with various Large Language Models (LLMs) and related services. This library serves as the foundation \nfor my AI projects, encapsulating common functionalities and best practices for LLM integration.\n\n[](https://buymeacoffee.com/probello3)\n\n## Technology\n- Python\n- LangChain\n\n## Prerequisites\n\n- Python 3.10 or higher\n- UV package manager\n- API keys for chosen AI provider (except for Ollama and LlamaCpp)\n - See (Environment Variables)[#environment-variables] below for provider-specific variables\n\n## Features\n\n* **Simplified LLM Configuration:** Easily configure and manage different LLM providers (OpenAI, Anthropic, etc.) and models through a unified interface.\n* **Asynchronous and Synchronous Support:** Supports both asynchronous and synchronous calls to LLMs.\n* **Context Management:** Tools for gathering relevant files as context for LLM prompts.\n* **Output Formatting:** Utilities for displaying LLM outputs in various formats (JSON, CSV, tables).\n* **Cost Tracking:** Optional integration to display the cost of LLM calls.\n* **Tool Call Handling:** Support for handling tool calls within LLM interactions.\n\n## Documentation\n[Library Documentation](https://htmlpreview.github.io/?https://github.com/paulrobello/par_ai_core/blob/main/src/par_ai_core/docs/index.html)\n\n## Installation\n```shell\nuv add par_ai_core\n```\n\n## Update\n```shell\nuv add par_ai_core -U\n```\n\n## Environment Variables\n\n### Create a .env file in the root of your project with the following content adjusted for your needs\n\n```shell\n# AI API KEYS\nOPENAI_API_KEY=\nANTHROPIC_API_KEY=\nGROQ_API_KEY=\nXAI_API_KEY=\nGOOGLE_API_KEY=\nMISTRAL_API_KEY=\nGITHUB_TOKEN=\nAWS_PROFILE=\nAWS_ACCESS_KEY_ID=\nAWS_SECRET_ACCESS_KEY=\n\n# Search\nGOOGLE_CSE_ID=\nGOOGLE_CSE_API_KEY=\nSERPER_API_KEY=\nSERPER_API_KEY_GOOGLE=\nTAVILY_API_KEY=\nJINA_API_KEY=\nBRAVE_API_KEY=\nREDDIT_CLIENT_ID=\nREDDIT_CLIENT_SECRET=\n\n# Misc API\nWEATHERAPI_KEY=\nGITHUB_PERSONAL_ACCESS_TOKEN=\n\n### Tracing (optional)\nLANGCHAIN_TRACING_V2=false\nLANGCHAIN_ENDPOINT=https://api.smith.langchain.com\nLANGCHAIN_API_KEY=\nLANGCHAIN_PROJECT=par_ai\n\n# PARAI Related (Not all providers / models support all vars)\nPARAI_AI_PROVIDER=\nPARAI_MODEL=\nPARAI_AI_BASE_URL=\nPARAI_TEMPERATURE=\nPARAI_TIMEOUT=\nPARAI_NUM_CTX=\nPARAI_NUM_REDICT=\nPARAI_REPEAT_LAST_N=\nPARAI_REPEAT_PENALTY=\nPARAI_MIROSTAT=\nPARAI_MIROSTAT_ETA=\nPARAI_MIROSTAT_TAU=\nPARAI_TFS_Z=\nPARAI_TOP_K=\nPARAI_TOP_P=\nPARAI_SEED=\n```\n\n### AI API KEYS\n\n* ANTHROPIC_API_KEY is required for Anthropic. Get a key from https://console.anthropic.com/\n* OPENAI_API_KEY is required for OpenAI. Get a key from https://platform.openai.com/account/api-keys\n* GITHUB_TOKEN is required for GitHub Models. Get a free key from https://github.com/marketplace/models\n* GOOGLE_API_KEY is required for Google Models. Get a free key from https://console.cloud.google.com\n* XAI_API_KEY is required for XAI. Get a free key from https://x.ai/api\n* GROQ_API_KEY is required for Groq. Get a free key from https://console.groq.com/\n* MISTRAL_API_KEY is required for Mistral. Get a free key from https://console.mistral.ai/\n* AWS_PROFILE or AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY are used for Bedrock authentication. The environment must\n already be authenticated with AWS.\n* No key required to use with Ollama or LlamaCpp.\n\n### Search\n\n* TAVILY_API_KEY is required for Tavily AI search. Get a free key from https://tavily.com/. Tavily is much better than\n* JINA_API_KEY is required for Jina search. Get a free key from https://jina.ai\n* BRAVE_API_KEY is required for Brave search. Get a free key from https://brave.com/search/api/\n* SERPER_API_KEY is required for Serper search. Get a free key from https://serper.dev\n* SERPER_API_KEY_GOOGLE is required for Google Serper search. Get a free key from https://serpapi.com/\n* GOOGLE_CSE_ID and GOOGLE_CSE_API_KEY are required for Google search.\n* REDDIT_CLIENT_ID and REDDIT_CLIENT_SECRET are needed for Reddit search. Get a free key\n from https://www.reddit.com/prefs/apps/\n\n### Misc API\n\n* GITHUB_PERSONAL_ACCESS_TOKEN is required for GitHub related tools. Get a free key\n from https://github.com/settings/tokens\n* WEATHERAPI_KEY is required for weather. Get a free key from https://www.weatherapi.com/\n* LANGCHAIN_API_KEY is required for Langchain / Langsmith tracing. Get a free key\n from https://smith.langchain.com/settings\n\n### PARAI Related\n* PARAI_AI_PROVIDER is one of Ollama|OpenAI|Groq|XAI|Anthropic|Google|Bedrock|Github|LlamaCpp\n* PARAI_MODEL is the model to use with the selected provider\n* PARAI_AI_BASE_URL can be used to override the base url used to call a provider\n* PARAI_TEMPERATURE sets model temperature. Range depends on provider usually 0.0 to 1.0\n* PARAI_TIMEOUT length of time to wait in seconds for ai response\n* PARAI_NUM_CTX sets the context window size. Max size varies by model\n* Other PARAI related params are to tweak model responses not all are supported / used by all providers\n\n### Open AI Compatible Providers\n\nIf a specify provider is not listed but has an OpenAI compatible endpoint you can use the following combo of vars:\n* PARAI_AI_PROVIDER=OpenAI\n* PARAI_MODEL=Your selected model\n* PARAI_AI_BASE_URL=The providers OpenAI endpoint URL\n\n## Example\n\n```python\n\"\"\"Basic LLM example using Par AI Core.\"\"\"\n\nimport sys\n\nfrom dotenv import load_dotenv\n\nfrom par_ai_core.llm_config import LlmConfig, llm_run_manager\nfrom par_ai_core.llm_providers import (\n LlmProvider,\n is_provider_api_key_set,\n provider_light_models,\n)\nfrom par_ai_core.par_logging import console_out\nfrom par_ai_core.pricing_lookup import PricingDisplay\nfrom par_ai_core.provider_cb_info import get_parai_callback\n\n\ndef main() -> None:\n \"\"\"\n Use OpenAI lightweight model to answer a question from the command line.\n\n This function performs the following steps:\n 1. Checks if OpenAI API key is set\n 2. Validates that a prompt is provided as a command-line argument\n 3. Configures an OpenAI chat model\n 4. Invokes the model with a system and user message\n 5. Prints the model's response\n\n Requires:\n - OPENAI_API_KEY environment variable to be set\n - A prompt provided as the first command-line argument\n \"\"\"\n \n load_dotenv()\n\n # Validate OpenAI API key is available\n if not is_provider_api_key_set(LlmProvider.OPENAI):\n console_out.print(\"OpenAI API key not set. Please set the OPENAI_API_KEY environment variable.\")\n return\n\n # Ensure a prompt is provided via command-line argument\n if len(sys.argv) < 2:\n console_out.print(\"Please provide a prompt as 1st command line argument.\")\n return\n\n # Configure the LLM using OpenAI's lightweight model\n llm_config = LlmConfig(provider=LlmProvider.OPENAI, model_name=provider_light_models[LlmProvider.OPENAI])\n chat_model = llm_config.build_chat_model()\n\n # Use context manager to handle callbacks for pricing and tool calls\n with get_parai_callback(show_pricing=PricingDisplay.DETAILS, show_tool_calls=True, show_end=False):\n # Prepare messages with a system context and user prompt\n messages: list[dict[str, str]] = [\n {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n {\"role\": \"user\", \"content\": sys.argv[1]},\n ]\n\n # Invoke the chat model and get the result\n result = chat_model.invoke(messages, config=llm_run_manager.get_runnable_config(chat_model.name or \"\"))\n\n # Print the model's response\n console_out.print(result.content)\n\n\nif __name__ == \"__main__\":\n main()\n```\n\n## Whats New\n- Version 0.1.10:\n - Add format param to LlmConfig for Ollama output format\n - Fixed bug with util function has_stdin_content\n- Version 0.1.9:\n - Added Mistral support\n - Fix dotenv loading bug\n- Version 0.1.8:\n - Added time display utils\n - Made LlmConfig.from_json more robust\n- Version 0.1.7:\n - Fix documentation issues\n- Version 0.1.6:\n - Pricing for Deepseek\n - Updated Docs\n- Version 0.1.5:\n - Initial release\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Author\n\nPaul Robello - probello@gmail.com\n",
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