add qwq as default ollama model (#133)

Signed-off-by: ChengZi <chen.zhang@zilliz.com>

Author: zc277584121

README.md

@@ -5,7 +5,7 @@
   <a href="https://discord.gg/mKc3R95yE5"><img height="20" src="https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white" alt="discord"/></a>
 
 
-DeepSearcher combines reasoning LLMs (OpenAI o1, o3-mini, DeepSeek, Grok 3, Claude 3.7 Sonnet, etc.) and Vector Databases (Milvus, Zilliz Cloud etc.) to perform search, evaluation, and reasoning based on private data, providing highly accurate answer and comprehensive report. This project is suitable for enterprise knowledge management, intelligent Q&A systems, and information retrieval scenarios.
+DeepSearcher combines reasoning LLMs (OpenAI o1, o3-mini, DeepSeek, Grok 3, Claude 3.7 Sonnet, QwQ, etc.) and Vector Databases (Milvus, Zilliz Cloud etc.) to perform search, evaluation, and reasoning based on private data, providing highly accurate answer and comprehensive report. This project is suitable for enterprise knowledge management, intelligent Q&A systems, and information retrieval scenarios.
 
 ![Architecture](./assets/pic/deep-searcher-arch.png)
 
@@ -135,7 +135,7 @@ result = query("Write a report about xxx.") # Your question here
   <p> <a href="https://ollama.ai/download">Download</a> and install Ollama onto the available supported platforms (including Windows Subsystem for Linux).</p>
   <p> View a list of available models via the <a href="https://ollama.ai/library">model library</a>.</p>
   <p> Fetch available LLM models via <code>ollama pull &lt;name-of-model&gt;</code></p>
-  <p> Example: <code>ollama pull qwen2.5:3b</code></p>
+  <p> Example: <code>ollama pull qwq</code></p>
   <p> To chat directly with a model from the command line, use <code>ollama run &lt;name-of-model&gt;</code>.</p>
   <p> By default, Ollama has a REST API for running and managing models on <a href="http://localhost:11434">http://localhost:11434</a>.</p>
 </details>

config.yaml

@@ -38,7 +38,7 @@ provide_settings:
 
 #    provider: "Ollama"
 #    config:
-#      model: "qwen2.5:3b"
+#      model: "qwq"
 ##      base_url: ""
 
   embedding:

deepsearcher/llm/ollama.py

@@ -4,7 +4,7 @@
 
 
 class Ollama(BaseLLM):
-    def __init__(self, model: str = "qwen2.5:3b", **kwargs):
+    def __init__(self, model: str = "qwq", **kwargs):
         from ollama import Client
 
         self.model = model

evaluation/eval_config.yaml

@@ -38,7 +38,7 @@ provide_settings:
 
 #    provider: "Ollama"
 #    config:
-#      model: "qwen2.5:3b"
+#      model: "qwq"
 ##      base_url: ""
 
   embedding: