Upload 3 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+allbook.book filter=lfs diff=lfs merge=lfs -text

Dockerfile

@@ -0,0 +1,8 @@
+FROM python:3.9
+RUN useradd -ms /bin/bash myuser
+WORKDIR /code
+COPY . .
+RUN pip install llama-index flask requests chromadb llama-index-embeddings-huggingface-api llama-index-vector-stores-chroma
+RUN chown -R myuser:myuser /code
+USER myuser
+CMD ["python", "app.py"]

allbook.book

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f43cb55656b6e5c510c478656d38bda6c769b9e6483410373789d50bf2fe15d
+size 16263962

app.py

@@ -0,0 +1,76 @@
+from typing import Dict
+from llama_index.core import StorageContext , VectorStoreIndex
+from llama_index.core.base.base_retriever import BaseRetriever
+from llama_index.core.schema import TextNode , NodeRelationship
+from llama_index.embeddings.huggingface_api import HuggingFaceInferenceAPIEmbedding
+from json import loads
+from chromadb import EphemeralClient
+from llama_index.vector_stores.chroma import ChromaVectorStore
+import requests
+import nest_asyncio
+import os
+import pickle
+import flask
+app = flask.Flask(__name__)
+
+nest_asyncio.apply()
+class AIBook:
+  embed_model:HuggingFaceInferenceAPIEmbedding
+  index:VectorStoreIndex
+  retriever:BaseRetriever
+  def __init__(self,token=os.environ["hf_api"],srcnum=2):
+    self.embed_model = HuggingFaceInferenceAPIEmbedding(model_name="BAAI/bge-large-en-v1.5",token=token)
+    self.index = VectorStoreIndex(nodes=pickle.load(open('allbook.book', 'rb')),embed_model=self.embed_model,storage_context=StorageContext.from_defaults(vector_store=ChromaVectorStore(chroma_collection= EphemeralClient().get_or_create_collection("jainbook"))))
+    self.retriever = self.index.as_retriever(similarity_top_k=srcnum,vector_store_query_mode="default")
+  def changeToken(self,token:str):
+    if self.embed_model.token != token:
+      self.embed_model = HuggingFaceInferenceAPIEmbedding(model_name="BAAI/bge-large-en-v1.5",token=token)
+  def changesrcnum(self,srcnum:int):
+    self.retriever = self.index.as_retriever(similarity_top_k=srcnum,vector_store_query_mode="default")
+  def retrieve(self,query:str):
+    return self.retriever.retrieve(query)
+  
+  @classmethod
+  def nodes_to_guj(cls,nodes:list[TextNode])->list[str]:
+    return [node.node.relationships[NodeRelationship("1")].metadata["maintext"] for node in nodes]
+  @classmethod
+  def nodes_to_eng(cls,nodes:list[TextNode])->list[str]:
+    return [node.node.text for node in nodes]
+  @classmethod
+  def nodes_to_page_with_bookname(cls,nodes:list[TextNode])->list[Dict]:
+    return [{"page":int(node.node.relationships[NodeRelationship("1")].metadata["page"]),"bookname":node.node.relationships[NodeRelationship("1")].metadata["book"]} for node in nodes]
+  @classmethod
+  def translate_to_eng(cls,text:str)->str:
+    return "".join([i[0] for i in requests.get(f"https://translate.googleapis.com/translate_a/single?client=gtx&sl=gu&tl=en&dt=t&q={text}").json()[0]])
+
+book = AIBook()
+@app.route("/")
+def function():
+  question = flask.request.args.get("question")
+  if question is None:
+    return """Please provide a question as 'https://shethjenil-apiofbookai.hf.space?question=પ્રભુ છે કે નહિ'<br>Change Token as https://shethjenil-apiofbookai.hf.space/changeToken?token=hf_<b>rgPNhjnXpLSodIphwjmRvPbvrovNYnQavj</b><br>Change srcnum as https://shethjenil-apiofbookai.hf.space/changesrcnum?srcnum=2<br><br><form action="/insert_node" method="post" enctype="multipart/form-data"><input type="file" name="file" accept=".book"><input type="submit" value="Upload Book File"></form>"""
+  if question == "":
+    return ""
+  return "\n\n".join(AIBook.nodes_to_guj(book.retrieve(AIBook.translate_to_eng(question))))
+
+@app.route("/changeToken")
+def function2():
+  book.changeToken(flask.request.args.get("token"))
+  return "Token changed"
+@app.route("/changesrcnum")
+def function3():
+  book.changesrcnum(int(flask.request.args.get("srcnum")))
+  return "srcnum changed"
+@app.route("/insert_nodes",methods=["POST"])
+def function4():
+  if 'file' not in flask.request.files:
+    return "Error"
+  file = flask.request.files['file']
+  if file.filename.endswith(".book"):
+    book.index.insert(pickle.load(file))
+    return "inserted" + file.filename
+  else:
+    return "not inserted because file is not a book"
+
+if __name__ == '__main__':
+    app.run("0.0.0.0",7860)