"second commit"

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/chabi.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPep8NamingInspection" enabled="true" level="WEAK WARNING" enabled_by_default="true">
+      <option name="ignoredErrors">
+        <list>
+          <option value="N802" />
+        </list>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.10 (chabi)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (chabi)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/chabi.iml" filepath="$PROJECT_DIR$/.idea/chabi.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+    <mapping directory="$PROJECT_DIR$/chabi" vcs="Git" />
+  </component>
+</project>

README.md

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+---
+title: chabi
+app_file: main.py
+sdk: gradio
+sdk_version: 4.12.0
+---

info.txt

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+this is a trial file to add some lines
+the main purpose of this file is testing our own chatbot
+this bot isn't for answering general questions
+here in computer and automation engineering we are learning about large language model 

main.py

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+from langchain.chains import RetrievalQA, ConversationalRetrievalChain
+from langchain.vectorstores import Chroma
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.document_loaders import DirectoryLoader, TextLoader
+from transformers import pipeline
+from langchain.llms import HuggingFacePipeline
+from langchain.embeddings import HuggingFaceInstructEmbeddings
+import gradio as gr
+from InstructorEmbedding import INSTRUCTOR
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-base")
+
+model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
+pipe = pipeline(
+    "text2text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    max_length=512,
+    temperature=0.5,
+    top_p=0.95,
+    repetition_penalty=1.15
+)
+
+local_llm = HuggingFacePipeline(pipeline=pipe)
+print(local_llm('What is the capital of Syria?'))
+
+loader = TextLoader('info.txt')
+document = loader.load()
+text_spliter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+texts = text_spliter.split_documents(document)
+embedding = HuggingFaceInstructEmbeddings()
+docsearch = Chroma.from_documents(texts, embedding, persist_directory='db')
+
+retriever = docsearch.as_retriever(search_kwargs={"k": 3})
+qa_chain = RetrievalQA.from_chain_type(llm=local_llm,
+                                       chain_type="map_reduce",
+                                       retriever=retriever,
+                                       return_source_documents=True)
+
+question = input('prompt: ')
+result = qa_chain({'query': question})
+print('result: ', result['result'])
+
+def gradinterface(query):
+    result = qa_chain({'query': query})
+    return result['result']
+
+
+demo = gr.ChatInterface(fn=gradinterface, title='OUR_OWN_BOT')
+
+if __name__ == "__main__":
+    demo.launch(show_api=False, share=True)