some more updates

app.py

@@ -9,11 +9,10 @@ import requests as re
 import json
 import streamlit as st
 
-##### start Def part
+##### Start Func Def part 
 ## Call selected LLM, get word def and return
-def call_llm(lmodel: str, lword: str) -> str:
-    ltoken = os.getenv('HF_TOKEN')
-    sysmsg = 'You are an English language expert. you are precise in your output. Users will ask you a word and in your response you will include the word meaning, synonyms, antonyms, and word usage examples. Format your output in different sections to make it easy to read'
+def call_llm(lmodel: str, lword: str, sysmsg: str, ltoken: str) -> str:
+    #ltoken = os.getenv('HF_TOKEN')
     usermsg = lword
     messages = [
         { "role": "system", "content": sysmsg },
@@ -35,86 +34,67 @@ def call_llm(lmodel: str, lword: str) -> str:
     return(completion.choices[0].message.content)   
 
 ## Call Dictionary API and get word def
-def call_dict_api(lword: str) -> str:
-    return 'helo'
-
-##### end Def part
+def call_dict_api(lword: str) -> dict:
+    dict_url = 'https://api.dictionaryapi.dev/api/v2/entries/en/'
+    api_url = dict_url + lword
+    response = re.get(url=api_url)
+    rjson = response.json()
+    if type(rjson) == dict:
+        return rjson
+    elif type(rjson) == list:
+        return rjson[0]
+    else:
+        return dict()
+
+##### End Func Def part
+
+sysmsg = '''You are an English language expert. You are precise in your output. 
+User will ask you a word and in your response you will include the word meaning, synonyms, antonyms, and word usage examples. 
+Format your output in different sections to make it easy to understand.'''
 
 lmodel = 'meta-llama/Llama-3.2-3B-Instruct'
+ltoken = os.getenv('HF_TOKEN')
+llm_out = ''
+api_out = dict()
+
+st.set_page_config(page_title='Simple Dictionary', page_icon=':blue_book:', layout="wide")
 
 st.title('A simple dictionary')
 lword = st.text_input(label='Enter word')
 lmodel = st.selectbox('Choose Language Model:',
                        index=0,
                        options=['meta-llama/Llama-3.2-3B-Instruct', 'Qwen/Qwen2.5-1.5B-Instruct', 'microsoft/Phi-3.5-mini-instruct']
-)
+                    )
+sys_prmpt = st.text_area(label='Sytem Prompt:', value=sysmsg)
 chk1 = st.checkbox(label='Use Language model to get word definition', value=True)
 chk2 = st.checkbox(label='Use Dictionary API call to get word definition', value=True)
 
 btn_submit = st.button(label='Submit')
-st.write(os.environ)
-col1, col2 = st.columns(2, border=True)
-## when setting hf token in terminal remember to set witout ''
-ltoken = os.getenv('HF_TOKEN')
-print(ltoken)
-#st.write(ltoken)
-
-#lmodel = 'cardiffnlp/twitter-roberta-base-sentiment-latest'    #Text classification
-# lmodel = 'meta-llama/Llama-3.2-3B-Instruct'            #Text Generation
-# lmodel = 'microsoft/phi-4'               #Not Working for inference API, model too large
-# lmodel = 'PowerInfer/SmallThinker-3B-Preview'  #Time out for this shit
-lmodel = 'Qwen/Qwen2.5-1.5B-Instruct'   #Working But output is in a strange format
-# lmodel = 'mistralai/Mistral-Small-24B-Instruct-2501'   #Not Working
-# lmodel = 'microsoft/Phi-3.5-mini-instruct'   #working
 
-# client = InferenceClient(
-#     model= lmodel,
-#     token= ltoken
-# )
-
-# #loutput = client.text_classification("Today is a great day")
-# #print('output=',loutput)
-
-
-# completion = client.chat.completions.create(
-#     model= lmodel,
-#     messages= messages,
-#     temperature=0.5,
-#     max_tokens=2048,
-#     top_p=0.7
-#     #stream=False
-# )
-
-# print('Chat output : ')
-# print(completion.choices[0].message.content)
-sample_out = '''
-Tolerate
-Definition: To accept or allow something that one does not like or approve of, especially in a mild or passive way.
-Synonyms: Accept, endure, put up with, overlook, tolerate
-Antonyms: Disapprove, reject, condemn, despise
-Usage examples:
-1. The new law was difficult to tolerate.
-2. I have to tolerate my boss's constant interruptions.
-3. He was tolerant of her eccentricities.
-4. We had to tolerate the long wait at the airport.
-5. She tolerated his frequent late arrivals.
-6. We have to tolerate the noise from the construction site.
-7. He tolerated the criticism as a necessary part of his job.
-8. She tolerated the small talk at the meeting.
-9. We have to tolerate the inconvenience of the traffic.
-10. He tolerated the long hours at work.
-
-In these examples, "tolerate" is used to describe the acceptance or allowance of something that is not liked or approved of, often in a mild or passive manner.
-'''
-#### Dict API call
-# dict_url = 'https://api.dictionaryapi.dev/api/v2/entries/en/'
-# lword = 'Tolerate'
-# api_url = dict_url + lword
-# print(api_url)
-# response = re.get(url=api_url)
-# print(response.status_code)
-# rjson = response.json()
-# print(rjson)
-# st.write(rjson)
+##st.write(os.environ)
 
+if btn_submit:
+    if chk1:
+        llm_out = call_llm(lmodel, lword, sys_prmpt, ltoken)
+    if chk2:
+        api_out = call_dict_api(lword)
 
+col1, col2 = st.columns(2, border=True)
+with col1:
+    st.subheader(':green[LLM Output]')
+    if chk1:
+        st.write(llm_out)
+    else:
+        st.write('LLM Call option not selected')
+
+with col2:
+    st.subheader(':orange[API Call]')
+    if chk2:
+        st.write(api_out)
+    else:
+        st.write('API Call option not selected')
+
+st.divider()
+st.write('*:blue[Developed By: Rashid Javed]*')
+st.write('Dictionary API Call courtesy of ')
+st.page_link('https://dictionaryapi.dev/', label='https://dictionaryapi.dev/')