| Name | llama-index-llms-openrouter JSON |
| Version |
0.2.1
JSON |
| download |
| home_page | None |
| Summary | llama-index llms openrouter integration |
| upload_time | 2024-10-08 22:33:39 |
| maintainer | None |
| docs_url | None |
| author | Your Name |
| requires_python | <4.0,>=3.8.1 |
| license | MIT |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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| coveralls test coverage |
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|
# LlamaIndex Llms Integration: Openrouter
## Installation
To install the required packages, run:
```bash
%pip install llama-index-llms-openrouter
!pip install llama-index
```
## Setup
### Initialize OpenRouter
You need to set either the environment variable `OPENROUTER_API_KEY` or pass your API key directly in the class constructor. Replace `<your-api-key>` with your actual API key:
```python
from llama_index.llms.openrouter import OpenRouter
from llama_index.core.llms import ChatMessage
llm = OpenRouter(
api_key="<your-api-key>",
max_tokens=256,
context_window=4096,
model="gryphe/mythomax-l2-13b",
)
```
## Generate Chat Responses
You can generate a chat response by sending a list of `ChatMessage` instances:
```python
message = ChatMessage(role="user", content="Tell me a joke")
resp = llm.chat([message])
print(resp)
```
### Streaming Responses
To stream responses, use the `stream_chat` method:
```python
message = ChatMessage(role="user", content="Tell me a story in 250 words")
resp = llm.stream_chat([message])
for r in resp:
print(r.delta, end="")
```
### Complete with Prompt
You can also generate completions with a prompt using the `complete` method:
```python
resp = llm.complete("Tell me a joke")
print(resp)
```
### Streaming Completion
To stream completions, use the `stream_complete` method:
```python
resp = llm.stream_complete("Tell me a story in 250 words")
for r in resp:
print(r.delta, end="")
```
## Model Configuration
To use a specific model, you can specify it during initialization. For example, to use Mistral's Mixtral model, you can set it like this:
```python
llm = OpenRouter(model="mistralai/mixtral-8x7b-instruct")
resp = llm.complete("Write a story about a dragon who can code in Rust")
print(resp)
```
### LLM Implementation example
https://docs.llamaindex.ai/en/stable/examples/llm/openrouter/
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"description": "# LlamaIndex Llms Integration: Openrouter\n\n## Installation\n\nTo install the required packages, run:\n\n```bash\n%pip install llama-index-llms-openrouter\n!pip install llama-index\n```\n\n## Setup\n\n### Initialize OpenRouter\n\nYou need to set either the environment variable `OPENROUTER_API_KEY` or pass your API key directly in the class constructor. Replace `<your-api-key>` with your actual API key:\n\n```python\nfrom llama_index.llms.openrouter import OpenRouter\nfrom llama_index.core.llms import ChatMessage\n\nllm = OpenRouter(\n api_key=\"<your-api-key>\",\n max_tokens=256,\n context_window=4096,\n model=\"gryphe/mythomax-l2-13b\",\n)\n```\n\n## Generate Chat Responses\n\nYou can generate a chat response by sending a list of `ChatMessage` instances:\n\n```python\nmessage = ChatMessage(role=\"user\", content=\"Tell me a joke\")\nresp = llm.chat([message])\nprint(resp)\n```\n\n### Streaming Responses\n\nTo stream responses, use the `stream_chat` method:\n\n```python\nmessage = ChatMessage(role=\"user\", content=\"Tell me a story in 250 words\")\nresp = llm.stream_chat([message])\nfor r in resp:\n print(r.delta, end=\"\")\n```\n\n### Complete with Prompt\n\nYou can also generate completions with a prompt using the `complete` method:\n\n```python\nresp = llm.complete(\"Tell me a joke\")\nprint(resp)\n```\n\n### Streaming Completion\n\nTo stream completions, use the `stream_complete` method:\n\n```python\nresp = llm.stream_complete(\"Tell me a story in 250 words\")\nfor r in resp:\n print(r.delta, end=\"\")\n```\n\n## Model Configuration\n\nTo use a specific model, you can specify it during initialization. For example, to use Mistral's Mixtral model, you can set it like this:\n\n```python\nllm = OpenRouter(model=\"mistralai/mixtral-8x7b-instruct\")\nresp = llm.complete(\"Write a story about a dragon who can code in Rust\")\nprint(resp)\n```\n\n### LLM Implementation example\n\nhttps://docs.llamaindex.ai/en/stable/examples/llm/openrouter/\n",
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