update with code fix

README.md

@@ -63,8 +63,10 @@ Below is a simple workflow to help you quickly connect the pipeline.
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
+import re
+import json
 
-MODEL_PATH = "THUDM/GLM-Z1-Rumination-32B-0414"
+MODEL_PATH = "THUDM/GLM-4-Z1-Rumination-32B-0414"
 
 tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
 model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto")
@@ -75,6 +77,7 @@ generate_kwargs = {
     "temperature": 0.95,
     "top_p": 0.7,
     "do_sample": True,
+    "max_new_tokens": 16384
 }
 
 def get_assistant():
@@ -84,16 +87,17 @@ def get_assistant():
         add_generation_prompt=True,
         return_dict=True,
     ).to(model.device)
-    out = model.generate(input_ids=input["input_ids"], **generate_kwargs)
+    out = model.generate(input_ids=inputs["input_ids"], **generate_kwargs)
     return tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True).strip()
 
 def get_observation(function_name, args):
-    if fucntion_name == "search":
+    content = None
+    if function_name == "search":
         mock_search_res = [
             {"title": "t1", "url":"url1", "snippet": "snippet_content_1"},
             {"title": "t2", "url":"url2", "snippet": "snippet_content_2"}
         ]
-        content = "\n\n".join([f"【{i}†{res['title']}†{res['url']}\n{res['snippet']}】"] for i, res in mock_search_res)
+        content = "\n\n".join([f"【{i}†{res['title']}†{res['url']}\n{res['snippet']}】"] for i, res in enumerate(mock_search_res))
     elif function_name == "click":
         mock_click_res = "main content"
         content = mock_click_res
@@ -102,6 +106,7 @@ def get_observation(function_name, args):
         content = mock_open_res
     else:
         raise ValueError("unspport function name!")
+    return content
         
 def get_func_name_args(llm_text):
     function_call = re.sub(r'.*?</think>', '', llm_text, flags=re.DOTALL)