Update app.py

app.py

@@ -47,7 +47,7 @@ class Chatbot:
         # Initialize an OpenAIEmbeddings model to compute embeddings of the chunks
         embeddings = OpenAIEmbeddings()
 
-        # Build a knowledge base using FAISS from the chunks and their embeddings
+        # Build a knowledge base using Chroma from the chunks and their embeddings
         knowledge_base = Chroma.from_documents(chunks, embeddings)
 
         # Return the resulting knowledge base
@@ -151,37 +151,6 @@ class Chatbot:
         return history
 
 
-    def extract_excel_data(self,file_path):
-        # Read the Excel file
-        df = pd.read_excel(file_path)
-
-        # Flatten the data to a single list
-        data_list = []
-        for _, row in df.iterrows():
-            data_list.extend(row.tolist())
-
-        return data_list
-
-    def comparing_chemicals(self,excel_file_path,chemicals):
-        chemistry_capability = self.extract_excel_data(excel_file_path.name)
-        response = openai.Completion.create(
-        engine="text-davinci-003",
-        prompt= f"""Analyse the following text delimited by triple backticks to return the comman chemicals.
-                  text : ```{chemicals}  {chemistry_capability}```.
-                  result should be in bullet points format.
-                 """,
-        max_tokens=100,
-        n=1,
-        stop=None,
-        temperature=0,
-        top_p=1.0,
-        frequency_penalty=0.0,
-        presence_penalty=0.0
-        )
-
-        result = response.choices[0].text.strip()
-        return result
-
     def clear_function(self,state):
       state.clear()
       # state = gr.State(self.get_empty_state())