| Name | llama-index-agent-llm-compiler JSON |
| Version |
0.3.0
JSON |
| download |
| home_page | None |
| Summary | llama-index agent llm compiler integration |
| upload_time | 2024-11-18 01:36:40 |
| maintainer | jerryjliu |
| docs_url | None |
| author | Your Name |
| requires_python | <4.0,>=3.9 |
| license | MIT |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# LlamaIndex Agent Integration: LLM Compiler
This Agent integration implements the [LLMCompiler agent paper](https://github.com/SqueezeAILab/LLMCompiler).
A lot of code came from the source repo, we repurposed with LlamaIndex abstractions. All credits
to the original authors for a great work!
A full notebook guide can be found [here](https://github.com/run-llama/llama_index/blob/main/docs/docs/examples/agent/llm_compiler.ipynb).
## Usage
First install the package:
```bash
pip install llama-index-agent-llm-compiler
```
```python
# setup pack arguments
from llama_index.core.agent import AgentRunner
from llama_index.agent.llm_compiler.step import LLMCompilerAgentWorker
agent_worker = LLMCompilerAgentWorker.from_tools(
tools, llm=llm, verbose=True, callback_manager=callback_manager
)
agent = AgentRunner(agent_worker, callback_manager=callback_manager)
# start using the agent
response = agent.chat("What is (121 * 3) + 42?")
```
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"description": "# LlamaIndex Agent Integration: LLM Compiler\n\nThis Agent integration implements the [LLMCompiler agent paper](https://github.com/SqueezeAILab/LLMCompiler).\n\nA lot of code came from the source repo, we repurposed with LlamaIndex abstractions. All credits\nto the original authors for a great work!\n\nA full notebook guide can be found [here](https://github.com/run-llama/llama_index/blob/main/docs/docs/examples/agent/llm_compiler.ipynb).\n\n## Usage\n\nFirst install the package:\n\n```bash\npip install llama-index-agent-llm-compiler\n```\n\n```python\n# setup pack arguments\n\nfrom llama_index.core.agent import AgentRunner\nfrom llama_index.agent.llm_compiler.step import LLMCompilerAgentWorker\n\nagent_worker = LLMCompilerAgentWorker.from_tools(\n tools, llm=llm, verbose=True, callback_manager=callback_manager\n)\nagent = AgentRunner(agent_worker, callback_manager=callback_manager)\n\n# start using the agent\nresponse = agent.chat(\"What is (121 * 3) + 42?\")\n```\n",
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