Initial implementation of multidoc qa

README.md

@@ -1,10 +1,7 @@
 ---
-title: Bllm W2a2 Multidoc Query
-emoji: 🦀
-colorFrom: gray
-colorTo: red
+title: Lewis Carroll's Alice in Wonderland and Through the Looking Glass
 sdk: gradio
-sdk_version: 3.32.0
+sdk_version: 3.27.0
 app_file: app.py
 pinned: false
 license: apache-2.0

app.py

@@ -0,0 +1,46 @@
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.document_loaders import GutenbergLoader
+from langchain.vectorstores import Chroma
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.chains.question_answering import load_qa_chain
+from langchain.llms import OpenAI
+
+
+docs = [
+    doc
+    for path in ['cache/epub/35688/pg35688.txt', 'files/23718/23718-readme.txt']
+    for doc in GutenbergLoader(f'https://www.gutenberg.org/{path}').load()
+]
+text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0, separator = "\n")
+texts = text_splitter.split_documents(docs)
+
+chain = None
+embeddings = None
+docsearch = None
+
+
+def make_inference(openai_api_key, query):
+    global chain, embeddings, docsearch
+
+    if chain is None:
+        chain = load_qa_chain(OpenAI(temperature=0, openai_api_key=openai_api_key.strip()), chain_type="stuff")
+        embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
+        docsearch = Chroma.from_documents(texts, embeddings, metadatas=[{"source": str(i)} for i in range(len(texts))]).as_retriever()
+
+    docs = docsearch.get_relevant_documents(query)
+    return(chain.run(input_documents=docs, question=query))
+
+if __name__ == "__main__":
+    # make a gradio interface
+    import gradio as gr
+
+    gr.Interface(
+        make_inference,
+        [
+            gr.inputs.Textbox(lines=1, label="OpenAI API Key"),
+            gr.inputs.Textbox(lines=2, label="Query"),
+        ],
+        gr.outputs.Textbox(label="Response"),
+        title="Multiple Document QA with LangChain",
+        description="Ask me anything about Lewis Carroll's Alice in Wonderland and Through the Looking-Glass",
+    ).launch()

requirements.txt

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+langchain
+openai
+tiktoken
+chromadb