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+FROM python:3.11.0
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY ./data  /code/data
+COPY ./chainlit.md /code/chainlit.md
+COPY ./.env /code/.env
+COPY ./app.py /code/app.py
+COPY ./.chainlit /code/.chainlit
+
+CMD ["chainlit", "run","-w","app.py", "--port", "8080"]
+
+

LICENSE

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README.md

@@ -1,13 +1,2 @@
----
-title: VaccineBot
-emoji: 🐨
-colorFrom: yellow
-colorTo: gray
-sdk: streamlit
-sdk_version: 1.38.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# vaccinebot
+Khop bot

app.py

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+import chainlit as cl
+from dotenv import load_dotenv
+load_dotenv()
+import warnings
+import google.generativeai as genai
+import os
+from pathlib import Path as p
+from langchain.prompts import PromptTemplate
+from langchain.chains.question_answering import load_qa_chain
+from langchain_community.document_loaders import PyPDFLoader
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import Chroma
+from langchain_google_genai import ChatGoogleGenerativeAI
+warnings.filterwarnings("ignore")
+# restart python kernal if issues with langchain import.
+
+genai.configure(api_key=os.environ.get("google_api_key"))
+"""### In Context Information Retreival
+"""
+model = ChatGoogleGenerativeAI(model="gemini-pro", temperature = 0.5)
+
+"""### Extract text from the PDF"""
+
+pdf_loader = PyPDFLoader(r'data/data.pdf')
+
+pages = pdf_loader.load_and_split()
+
+prompt_template = """Your name is खोप_Bot, a knowledgeable and helpful medical assistant specializing in Immunization information. User can ask you any information related to Immunization in Nepal. Your goal is to provide accurate, clear, and supportive answers to vaccine-related questions. Replace other country name with Nepal.You'll be presented with a context and a question. Carefully examine the context to extract any relevant information that can help you answer the question precisely.Answer maynot always be in context, In that case answer relevent to the context\n\n
+                    Context: \n {context}?\n
+                    Question: \n {question} \n
+                    Answer:
+                  """
+
+prompt = PromptTemplate(
+    template=prompt_template, input_variables=["context", "question"]
+)
+
+stuff_chain = load_qa_chain(model, chain_type="stuff", prompt=prompt)
+
+"""### RAG Pipeline: Embedding + LLM"""
+
+from langchain_google_genai import GoogleGenerativeAIEmbeddings
+
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=10000, chunk_overlap=1000)
+context = "\n\n".join(str(p.page_content) for p in pages)
+texts = text_splitter.split_text(context)
+
+# texts
+
+embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
+
+vector_index = Chroma.from_texts(texts, embeddings).as_retriever()
+
+
+@cl.on_message
+async def main(message: cl.Message):
+    docs = vector_index.get_relevant_documents(message.content)
+
+    stuff_answer = stuff_chain(
+        {"input_documents": docs, "question": message.content}, return_only_outputs=True
+    )
+
+    # Access the text content from the dictionary
+    text = stuff_answer['output_text']
+    await cl.Message(
+        content=text,
+    ).send()
+
+

chainlit.md

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+# Welcome to खोप_Bot! 👩‍⚕️💉
+
+Hi there, user! 👋 खोप-Bot is a AI-powered chatbot designed to provide comprehensive and accurate information about immunizations, vaccines, and related topics. Leveraging the power of Gemini Pro for inference, Immuno_bot delivers reliable answers to your immunization queries.
+
+## Why खोप_Bot? 🤱
+
+खोप_Bot is committed to providing accurate and accessible immunization information, dispelling myths, and promoting vaccine confidence. As a reliable source of information, खोप_Bot aims to empower individuals to make informed decisions about their health and the health of their loved ones.😷💬
+
+हामी तपाईंको परिवारको परवाह गर्छौं |😊
+
+

langchain_google_gemini_api.py

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+
+
+from dotenv import load_dotenv
+load_dotenv()
+import warnings
+import google.generativeai as genai
+import os
+from pathlib import Path as p
+from langchain.prompts import PromptTemplate
+from langchain.chains.question_answering import load_qa_chain
+from langchain_community.document_loaders import PyPDFLoader
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import Chroma
+from langchain_google_genai import ChatGoogleGenerativeAI
+warnings.filterwarnings("ignore")
+
+# restart python kernal if issues with langchain import.
+
+genai.configure(api_key=os.environ.get("google_api_key"))
+"""### In Context Information Retreival
+"""
+model = ChatGoogleGenerativeAI(model="gemini-pro", temperature = 0.3)
+
+
+"""### Extract text from the PDF"""
+
+pdf_loader = PyPDFLoader(r"C:\Users\DELL\Downloads\FAQ_on_Immunization_for_Health_Workers-English.pdf")
+
+pages = pdf_loader.load_and_split()
+
+prompt_template = """Answer the question as precise as possible using the provided context. If the answer is
+                    not contained in the context, say "answer not available in context" \n\n
+                    Context: \n {context}?\n
+                    Question: \n {question} \n
+                    Answer:
+                  """
+
+prompt = PromptTemplate(
+    template=prompt_template, input_variables=["context", "question"]
+)
+
+stuff_chain = load_qa_chain(model, chain_type="stuff", prompt=prompt)
+
+"""### RAG Pipeline: Embedding + LLM"""
+
+
+
+from langchain_google_genai import GoogleGenerativeAIEmbeddings
+
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=10000, chunk_overlap=0)
+context = "\n\n".join(str(p.page_content) for p in pages)
+texts = text_splitter.split_text(context)
+
+# texts
+
+embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
+
+vector_index = Chroma.from_texts(texts, embeddings).as_retriever()
+
+#input_ question here
+question = "What are vaccine hesitancy and vaccine confidence?"
+docs = vector_index.get_relevant_documents(question)
+
+stuff_answer = stuff_chain(
+    {"input_documents": docs, "question": question}, return_only_outputs=True
+)
+
+# Access the text content from the dictionary
+text = stuff_answer['output_text']
+
+# Format the text into a paragraph by joining the lines with spaces
+processed_output = " ".join(text.splitlines())
+
+# Print the formatted paragraph
+print(processed_output)

requirements.txt

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+aiofiles==23.2.1
+aiohttp==3.9.1
+aiosignal==1.3.1
+annotated-types==0.6.0
+anyio==3.7.1
+asgiref==3.7.2
+asyncer==0.0.2
+attrs==23.2.0
+backoff==2.2.1
+bcrypt==4.1.2
+bidict==0.22.1
+build==1.0.3
+cachetools==5.3.2
+certifi==2023.11.17
+chainlit==1.0.100
+charset-normalizer==3.3.2
+chroma-hnswlib==0.7.3
+chromadb==0.3.29
+click==8.1.7
+colorama==0.4.6
+coloredlogs==15.0.1
+dataclasses-json==0.5.14
+Deprecated==1.2.14
+fastapi==0.100.1
+fastapi-socketio==0.0.10
+filelock==3.13.1
+filetype==1.2.0
+flatbuffers==23.5.26
+frozenlist==1.4.1
+fsspec==2023.12.2
+google-ai-generativelanguage==0.4.0
+google-api-core==2.15.0
+google-auth==2.26.2
+google-generativeai==0.3.2
+googleapis-common-protos==1.62.0
+greenlet==3.0.3
+grpcio==1.60.0
+grpcio-status==1.60.0
+h11==0.14.0
+httpcore==0.17.3
+httptools==0.6.1
+httpx==0.24.1
+huggingface-hub==0.20.2
+humanfriendly==10.0
+idna==3.6
+importlib-metadata==6.11.0
+importlib-resources==6.1.1
+jsonpatch==1.33
+jsonpointer==2.4
+kubernetes==29.0.0
+langchain==0.1.0
+langchain-community==0.0.11
+langchain-core==0.1.10
+langchain-google-genai==0.0.5
+langsmith==0.0.80
+Lazify==0.4.0
+literalai==0.0.102
+marshmallow==3.20.2
+mmh3==4.1.0
+monotonic==1.6
+mpmath==1.3.0
+multidict==6.0.4
+mypy-extensions==1.0.0
+nest-asyncio==1.5.8
+numpy==1.26.3
+oauthlib==3.2.2
+onnxruntime==1.16.3
+opentelemetry-api==1.22.0
+opentelemetry-exporter-otlp==1.22.0
+opentelemetry-exporter-otlp-proto-common==1.22.0
+opentelemetry-exporter-otlp-proto-grpc==1.22.0
+opentelemetry-exporter-otlp-proto-http==1.22.0
+opentelemetry-instrumentation==0.43b0
+opentelemetry-instrumentation-asgi==0.43b0
+opentelemetry-instrumentation-fastapi==0.43b0
+opentelemetry-proto==1.22.0
+opentelemetry-sdk==1.22.0
+opentelemetry-semantic-conventions==0.43b0
+opentelemetry-util-http==0.43b0
+overrides==7.4.0
+packaging==23.2
+posthog==3.3.1
+proto-plus==1.23.0
+protobuf==4.25.2
+pulsar-client==3.4.0
+pyasn1==0.5.1
+pyasn1-modules==0.3.0
+pydantic==2.5.3
+pydantic_core==2.14.6
+PyJWT==2.8.0
+pypdf==3.17.4
+PyPika==0.48.9
+pyproject_hooks==1.0.0
+pyreadline3==3.4.1
+python-dateutil==2.8.2
+python-dotenv==1.0.0
+python-engineio==4.8.2
+python-graphql-client==0.4.3
+python-multipart==0.0.6
+python-socketio==5.11.0
+PyYAML==6.0.1
+requests==2.31.0
+requests-oauthlib==1.3.1
+rsa==4.9
+simple-websocket==1.0.0
+six==1.16.0
+sniffio==1.3.0
+SQLAlchemy==2.0.25
+starlette==0.27.0
+sympy==1.12
+syncer==2.0.3
+tenacity==8.2.3
+tokenizers==0.15.0
+tomli==2.0.1
+tqdm==4.66.1
+typer==0.9.0
+typing-inspect==0.9.0
+typing_extensions==4.9.0
+uptrace==1.22.0
+urllib3==2.1.0
+uvicorn==0.23.2
+watchfiles==0.20.0
+websocket-client==1.7.0
+websockets==12.0
+wrapt==1.16.0
+wsproto==1.2.0
+yarl==1.9.4
+zipp==3.17.0
+