Update app.py

app.py

@@ -50,6 +50,8 @@ class ZhipuAILLM(LLM):
     api_key: str
     model: str = "chatglm3-6b"
     temperature: float = 0.1
+    # Declare client as a field to avoid Pydantic validation error
+    client: Optional[ZhipuAI] = None
 
     def __init__(self, api_key: str, **kwargs: Any):
         # Pass api_key to parent class
@@ -57,14 +59,16 @@ class ZhipuAILLM(LLM):
         self.model = kwargs.get("model", self.model)
         self.temperature = kwargs.get("temperature", self.temperature)
         # Initialize client after setting attributes
-        self._client = ZhipuAI(api_key=self.api_key)
+        self.client = ZhipuAI(api_key=self.api_key)
 
     @property
     def _llm_type(self) -> str:
         return "zhipuai"
 
     def _call(self, prompt: str, stop: Optional[List[str]] = None, **kwargs: Any) -> str:
-        response = self._client.chat.completions.create(
+        if self.client is None:
+            raise ValueError("ZhipuAI client not initialized")
+        response = self.client.chat.completions.create(
             model=self.model,
             messages=[{"role": "user", "content": prompt}],
             temperature=self.temperature
@@ -182,22 +186,19 @@ def initialize_system(pdf_path):
     return qa_chain
 
 # Initialize on startup
+qa_chain = None
 try:
     qa_chain = initialize_system("Henry_Linkedin_Profile.pdf")
+    print("System initialized successfully")
 except Exception as e:
     print(f"Error initializing system: {e}")
     # Create a dummy chain to allow the app to run
-    from langchain.chains import LLMChain
-    from langchain.llms import OpenAI  # This is just a placeholder
+    # Instead of using OpenAI, we'll create a simple dummy chain
+    class DummyChain:
+        def __call__(self, inputs):
+            return {"result": f"System initialization failed: {str(e)}"}
     
-    # Create a fallback chain that returns an error message
-    qa_chain = LLMChain(
-        llm=OpenAI(temperature=0), 
-        prompt=PromptTemplate(
-            template="Error: {error}", 
-            input_variables=["error"]
-        )
-    )
+    qa_chain = DummyChain()
 
 # Chat function
 def chat(message, history):