code updated

.env

@@ -0,0 +1 @@
+cohere_api_key="CTx2vcy4vjHeGC77cGGQXrCCz4xZYxlnPyFWZqqe"

app.py

@@ -40,18 +40,17 @@ elif temperature=="High accuracy":
     temperature=0
 temperature=temperature/10
 
-# stream_handler = StreamHandler(st.empty())  
+ 
 
 if option=="GPT-4o":
     api_key=st.sidebar.text_input("API Key:",placeholder="Enter OpenAI API Key...")
     if api_key:
-        stream_handler = StreamHandler(st.empty())
-        model=ChatOpenAI(model="gpt-4o" , temperature=temperature , api_key=api_key , streaming=True, callbacks=[stream_handler])
+        
+        model=ChatOpenAI(model="gpt-4o" , temperature=temperature , api_key=api_key , streaming=True, callbacks=[StreamHandler(st.empty())])
 elif option=="Cohere":
     api_key= st.sidebar.text_input("API Key:",placeholder="Enter Cohere API Key...")
     if api_key:
-        stream_handler = StreamHandler(st.empty())    
-        model = ChatCohere(cohere_api_key=api_key,temperature=temperature ,  streaming=True, callbacks=[stream_handler])
+        model = ChatCohere(cohere_api_key=api_key,temperature=temperature ,  streaming=True, callbacks=[StreamHandler(st.empty())])
         #model = ChatCohere(cohere_api_key=api_key , temperature = temperature , model = "command-r-plus")
 # elif option=="Mixtral-8x7b":
 #     api_key=st.sidebar.text_input("API Key:",placeholder="Enter NVIDIA NIM API Key...")
@@ -67,7 +66,6 @@ elif option=="Cohere":
 #         model=HuggingFaceHub(repo_id="mistralai/Mixtral-8x22B-Instruct-v0.1",huggingfacehub_api_token=api_key ,model_kwargs={"temperature":temperature})
         
 
-
 if st.sidebar.toggle("Normal LinkedIn Post"):        
     url = st.sidebar.text_input("Enter URL:", placeholder="Enter URL here...")   
     if st.sidebar.button("Submit"):
@@ -93,31 +91,6 @@ if st.sidebar.toggle("Normal LinkedIn Post"):
 
 
 
-# paraphrase_text=st.text_area("Generated LinkedIn post",value=session_state.paraphrase, height=400)
-# import pyperclip
-# if st.button('Copy'):
-#     pyperclip.copy(paraphrase_text)
-#     st.success('Text copied successfully!')
-# from paraphrase_post import extract_data
-# # session_state.keywords , session_state.take_aways , session_state.highlights =extract_data(session_state.paraphrase , model) 
-# from paraphrase_post import generate_details
-# if st.sidebar.button("Show Details"):
-#     session_state.keywords =generate_details(session_state.paraphrase , model)   
-        # session_state.take_aways =generate_takeaways(session_state.paraphrase , model)
-        # session_state.highlights =generate_highlights(session_state.paraphrase , model) 
-        
-        # st.write("Keywords:")
-        # for i, statement in enumerate(session_state.keywords, start=1):
-        #     st.write(f"{i}. {statement}")
-    
-        # st.write("Take Aways:")
-        # for i, statement in enumerate(session_state.take_aways, start=1):
-        #     st.write(f"{i}. {statement}")
-
-        # st.write("Highlights:")
-        # for i, statement in enumerate(session_state.highlights, start=1):
-        #     st.write(f"{i}. {statement}")
-
 #------------------------------------------------------------Advance LinkedIn post code below-----------------------------------------------------------------
 
 
@@ -141,14 +114,14 @@ if st.sidebar.toggle("Advance LinkedIn Post"):
 
                                 if match:
                                     try:
-                                        session_state.advancepost =google_search(url ,model , google_api_key,search_engine_id)
-                                        # session_state.advancepost = advanced_post(all_links ,model ,session_state.paraphrase)
+                                        with st.spinner("Creating post ,please wait..."):
+                                            session_state.advancepost =google_search(url ,model , google_api_key,search_engine_id)
+                                       
                                     except (openai.AuthenticationError) as e:
                                         st.sidebar.error("Enter your valid API key")
                                 else:
                                     st.sidebar.error("Put a valid LinkedIn post url only")
-                                    # if len(docs)==0:
-                                #     st.sidebar.error("Please Check your both credentials carefully")
+                        
                     
                             else:
                                 st.sidebar.error("Please enter Search Engine ID")
@@ -159,7 +132,7 @@ if st.sidebar.toggle("Advance LinkedIn Post"):
         else:
             st.sidebar.error("Please enter url")
 
-    advance_post=st.text_area("Advance LinkedIn post",value=session_state.advancepost, height=400) 
+    advance_post=st.write(session_state.advancepost) 
 
 
 
@@ -170,9 +143,6 @@ if st.sidebar.toggle("Message"):
     if st.sidebar.button("Generate Post"):
         if content:
             if api_key:
-                # with st.container(height=500):
-                    # stream_handler = StreamHandler(st.empty())    
-                    # model = ChatCohere(cohere_api_key=api_key,temperature=temperature ,  streaming=True, callbacks=[stream_handler])
                     post_from_content(model ,content)
                     
                 

paraphrase_post.py

@@ -70,43 +70,3 @@ def generate_details(post_data,model):
     keywords=chain.invoke({"data":post_data})
     return keywords
 
-
-
-
-
-# # Below function extract the details such as keywords  , Take aways , highlights and questions 
-# def extract_data(post_data ,model):
-#     keywords = ResponseSchema(name="Keywords",
-#                         description="These are the keywords extracted from LinkedIn post",type="list")
-
-#     # Take_aways = ResponseSchema(name="Take Aways",
-#     #                             description="These are the take aways extracted from LinkedIn post", type= "list")
-#     # Highlights=ResponseSchema(name="Highlights",
-#     #                             description="These are the highlights extracted from LinkedIn post", type= "list")
-    
-    
-#     response_schema = [
-#         keywords,
-#         # Take_aways,
-#         # Highlights
-
-#     ]
-#     output_parser = StructuredOutputParser.from_response_schemas(response_schema)
-#     format_instructions = output_parser.get_format_instructions()
-
-#     template = """
-#         You are a helpful keywords extractor from the post of LinkedIn Bot. Your task is to extract relevant keywords in descending order of their scores in a list, means high relevant should  be on the top .
-#         From the following text message, extract the following information:
-
-#         text message: {content}
-#         {format_instructions}
-#         """
-    
-#     prompt_template = ChatPromptTemplate.from_template(template)
-#     messages = prompt_template.format_messages(content=post_data, format_instructions=format_instructions)
-#     response = model(messages)
-#     output_dict=  output_parser.parse(response.content)
-#     keywords=output_dict['Keywords'][:3]
-#     # take_aways=output_dict['Take Aways'][:3]
-#     # highlights=output_dict['Highlights'][:3]
-#     return  keywords 

streaming_response.py

@@ -11,26 +11,3 @@ class StreamHandler(BaseCallbackHandler):
         self.container.markdown(self.text)
 
 
-# with st.sidebar:
-#     openai_api_key = st.text_input("OpenAI API Key", type="password")
-
-# if "messages" not in st.session_state:
-#     st.session_state["messages"] = [ChatMessage(role="assistant", content="How can I help you?")]
-
-# for msg in st.session_state.messages:
-#     st.chat_message(msg.role).write(msg.content)
-
-# if prompt := st.chat_input():
-#     st.session_state.messages.append(ChatMessage(role="user", content=prompt))
-#     st.chat_message("user").write(prompt)
-
-#     if not openai_api_key:
-#         st.info("Please add your OpenAI API key to continue.")
-#         st.stop()
-
-#     with st.chat_message("assistant"):
-#         stream_handler = StreamHandler(st.empty())
-#         # llm = ChatOpenAI(openai_api_key=openai_api_key, streaming=True, callbacks=[stream_handler])
-#         llm = ChatCohere(openai_api_key=openai_api_key, streaming=True, callbacks=[stream_handler])
-#         response = llm.invoke(st.session_state.messages)
-#         st.session_state.messages.append(ChatMessage(role="assistant", content=response.content))