further updates

.gitignore

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+/test.py

app.py

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+"""
+30-01-2025
+Rashid Javed
+A simple dictionary to get word meaning, synonyms, antonyms
+"""
+from huggingface_hub import InferenceClient
+import os
+import requests as re
+import json
+import streamlit as st
+
+##### start 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'
+    usermsg = lword
+    messages = [
+        { "role": "system", "content": sysmsg },
+        { "role": "user", "content": usermsg }
+    ]    
+    client = InferenceClient(
+                    model= lmodel,
+                    token= ltoken 
+    )    
+
+    completion = client.chat.completions.create(
+        model= lmodel,
+        messages= messages,
+        temperature=0.5,
+        max_tokens=2048,
+        top_p=0.7,
+        stream=False
+    ) 
+    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
+
+lmodel = 'meta-llama/Llama-3.2-3B-Instruct'
+
+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']
+)
+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)
+
+

requirements.txt

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+huggingface_hub
+requests