warhawkmonk commited on
Commit
0e80dd6
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1 Parent(s): 9741000

Update app.py

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Files changed (1) hide show
  1. app.py +52 -2
app.py CHANGED
@@ -213,7 +213,7 @@ with open("/home/user/app/DataBase/datetimeRecords.json","r") as read:
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  dateTimeRecord=json.load(read)
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  with column2:
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  st.header("HISTORY")
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- tab1,tab2,tab3,tab4=st.tabs(["CHAT HISTORY","IMAGES","PROMPT IMPROVEMENT","LOGIN"])
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  with tab1:
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@@ -270,7 +270,57 @@ with column2:
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  image = prompts_[-1].crop((0, 0, size, size))
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  image.putalpha(mask)
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  st.image(image)
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  with tab2:
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  if "current_image" in dictionary and len(dictionary['current_image']):
 
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  dateTimeRecord=json.load(read)
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  with column2:
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  st.header("HISTORY")
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+ tab1,tab2,tab3,tab4=st.tabs(["CHAT HISTORY","FREE API","IMAGES","PROMPT IMPROVEMENT","LOGIN"])
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  with tab1:
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  image = prompts_[-1].crop((0, 0, size, size))
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  image.putalpha(mask)
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  st.image(image)
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+
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+ with tab5:
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+ st.write("ADD PINECONE API KEY TO GET FREE LLM API")
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+ random_val = """
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+ def prompt_limmiter(prompt):
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+
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+ import requests
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+ from sentence_transformers import SentenceTransformer
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+ from pinecone import Pinecone, ServerlessSpec
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+ Gen_api = "https://8417-201-238-124-65.ngrok-free.app/api/llm-response"
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+ api_key = "xxxxxxxxxxxxxxxxxxxxxx----pine cone api key---xxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
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+ pc = Pinecone(api_key=api_key)
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+ model = SentenceTransformer("all-mpnet-base-v2")
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+ try:
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+ index_name = "quickstart"
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+ pc.create_index(
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+ name=index_name,
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+ dimension=768,
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+ metric="cosine",
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+ spec=ServerlessSpec(
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+ cloud="aws",
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+ region="us-east-1"
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+ )
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+ )
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+ except:
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+ pass
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+ index = pc.Index(index_name)
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+ index.upsert(
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+ vectors=[
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+ {
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+ "id": "lorum",
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+ "values": [float(i) for i in list(model.encode("lorum"))],
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+ "metadata": {"string":str(prompt)}
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+
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+ }
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+ ]
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+ )
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+
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+ gen_api_response = requests.post(url = Gen_api,json={"api_key": api_key},verify=False)
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+
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+ if gen_api_response.json().get("status"):
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+ response = index.query(
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+ vector=[float(i) for i in model.encode(str(prompt))],
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+ top_k=1,
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+ include_metadata=True,
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+ )
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+
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+ return response['matches'][0]['metadata']['string']
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+ """
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+ with st.container(height=600):
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+ st.code(random_val,language="python")
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  with tab2:
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  if "current_image" in dictionary and len(dictionary['current_image']):