mirror of
https://github.com/camel-ai/owl.git
synced 2026-03-22 05:57:17 +08:00
update readme
This commit is contained in:
20
README.md
20
README.md
@@ -154,6 +154,21 @@ Run the following demo case:
|
||||
python owl/run.py
|
||||
```
|
||||
|
||||
## Running with Different Models
|
||||
|
||||
OWL supports various LLM backends. You can use the following scripts to run with different models:
|
||||
|
||||
```bash
|
||||
# Run with Qwen model
|
||||
python owl/run_qwen.py
|
||||
|
||||
# Run with Deepseek model
|
||||
python owl/run_deepseek.py
|
||||
|
||||
# Run with other OpenAI-compatible models
|
||||
python owl/run_openai_compatiable_model.py
|
||||
```
|
||||
|
||||
For a simpler version that only requires an LLM API key, you can try our minimal example:
|
||||
|
||||
```bash
|
||||
@@ -169,7 +184,7 @@ question = "Task description here."
|
||||
society = construct_society(question)
|
||||
answer, chat_history, token_count = run_society(society)
|
||||
|
||||
logger.success(f"Answer: {answer}")
|
||||
print(f"Answer: {answer}")
|
||||
```
|
||||
|
||||
For uploading files, simply provide the file path along with your question:
|
||||
@@ -180,8 +195,7 @@ question = "What is in the given DOCX file? Here is the file path: tmp/example.d
|
||||
|
||||
society = construct_society(question)
|
||||
answer, chat_history, token_count = run_society(society)
|
||||
|
||||
logger.success(f"Answer: {answer}")
|
||||
print(f"Answer: {answer}")
|
||||
```
|
||||
|
||||
OWL will then automatically invoke document-related tools to process the file and extract the answer.
|
||||
|
||||
20
README_zh.md
20
README_zh.md
@@ -154,6 +154,21 @@ python owl/run.py
|
||||
python owl/run_mini.py
|
||||
```
|
||||
|
||||
## 使用不同的模型
|
||||
|
||||
OWL 支持多种 LLM 后端。您可以使用以下脚本来运行不同的模型:
|
||||
|
||||
```bash
|
||||
# 使用 Qwen 模型运行
|
||||
python owl/run_qwen.py
|
||||
|
||||
# 使用 Deepseek 模型运行
|
||||
python owl/run_deepseek.py
|
||||
|
||||
# 使用其他 OpenAI 兼容模型运行
|
||||
python owl/run_openai_compatiable_model.py
|
||||
```
|
||||
|
||||
你可以通过修改 `run.py` 脚本来运行自己的任务:
|
||||
|
||||
```python
|
||||
@@ -163,7 +178,7 @@ question = "Task description here."
|
||||
society = construct_society(question)
|
||||
answer, chat_history, token_count = run_society(society)
|
||||
|
||||
logger.success(f"Answer: {answer}")
|
||||
print(f"Answer: {answer}")
|
||||
```
|
||||
|
||||
上传文件时,只需提供文件路径和问题:
|
||||
@@ -175,12 +190,11 @@ question = "给定的 DOCX 文件中有什么内容?文件路径如下:tmp/e
|
||||
society = construct_society(question)
|
||||
answer, chat_history, token_count = run_society(society)
|
||||
|
||||
logger.success(f"答案:{answer}")
|
||||
print(f"答案:{answer}")
|
||||
```
|
||||
|
||||
OWL 将自动调用与文档相关的工具来处理文件并提取答案。
|
||||
|
||||
|
||||
OWL 将自动调用与文档相关的工具来处理文件并提取答案。
|
||||
|
||||
你可以尝试以下示例任务:
|
||||
|
||||
Reference in New Issue
Block a user