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dgutierrez
commited on
Commit
•
cc17218
1
Parent(s):
e67d4b1
added pdf
Browse files- aimakerspace/text_utils.py +27 -10
- app.py +34 -13
aimakerspace/text_utils.py
CHANGED
@@ -1,5 +1,6 @@
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import os
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from typing import List
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class TextFileLoader:
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@@ -11,25 +12,40 @@ class TextFileLoader:
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def load(self):
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if os.path.isdir(self.path):
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self.load_directory()
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elif os.path.isfile(self.path)
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self.
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else:
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raise ValueError(
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"Provided path is neither a valid directory nor a .txt file."
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)
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def load_file(self):
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with open(self.path, "r", encoding=self.encoding) as f:
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self.documents.append(f.read())
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def load_directory(self):
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for root, _, files in os.walk(self.path):
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for file in files:
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if file.endswith(".txt"):
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with open(
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os.path.join(root, file), "r", encoding=self.encoding
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) as f:
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self.documents.append(f.read())
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def load_documents(self):
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self.load()
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@@ -52,7 +68,7 @@ class CharacterTextSplitter:
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def split(self, text: str) -> List[str]:
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chunks = []
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for i in range(0, len(text), self.chunk_size - self.chunk_overlap):
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chunks.append(text[i
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return chunks
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def split_texts(self, texts: List[str]) -> List[str]:
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@@ -63,7 +79,8 @@ class CharacterTextSplitter:
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if __name__ == "__main__":
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-
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loader.load()
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splitter = CharacterTextSplitter()
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chunks = splitter.split_texts(loader.documents)
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import os
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from typing import List
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import fitz # PyMuPDF
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class TextFileLoader:
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def load(self):
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if os.path.isdir(self.path):
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self.load_directory()
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elif os.path.isfile(self.path):
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if self.path.endswith(".txt"):
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self.load_file()
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elif self.path.endswith(".pdf"):
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self.load_pdf()
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else:
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raise ValueError("Unsupported file type. Only .txt and .pdf files are supported.")
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else:
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raise ValueError("Provided path is neither a valid directory nor a file.")
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def load_file(self):
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with open(self.path, "r", encoding=self.encoding) as f:
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self.documents.append(f.read())
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def load_pdf(self):
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with fitz.open(self.path) as doc:
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text = ""
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for page in doc:
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text += page.get_text("text")
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self.documents.append(text)
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def load_directory(self):
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for root, _, files in os.walk(self.path):
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for file in files:
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file_path = os.path.join(root, file)
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if file.endswith(".txt"):
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with open(file_path, "r", encoding=self.encoding) as f:
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self.documents.append(f.read())
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elif file.endswith(".pdf"):
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with fitz.open(file_path) as doc:
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text = ""
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for page in doc:
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text += page.get_text("text")
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self.documents.append(text)
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def load_documents(self):
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self.load()
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def split(self, text: str) -> List[str]:
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chunks = []
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for i in range(0, len(text), self.chunk_size - self.chunk_overlap):
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chunks.append(text[i: i + self.chunk_size])
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return chunks
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def split_texts(self, texts: List[str]) -> List[str]:
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if __name__ == "__main__":
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# Example usage with a PDF file
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loader = TextFileLoader("data/sample.pdf")
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loader.load()
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splitter = CharacterTextSplitter()
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chunks = splitter.split_texts(loader.documents)
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app.py
CHANGED
@@ -11,9 +11,10 @@ from aimakerspace.openai_utils.embedding import EmbeddingModel
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from aimakerspace.vectordatabase import VectorDatabase
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from aimakerspace.openai_utils.chatmodel import ChatOpenAI
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import chainlit as cl
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system_template = """\
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Use the following context to answer a
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system_role_prompt = SystemRolePrompt(system_template)
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user_prompt_template = """\
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text_splitter = CharacterTextSplitter()
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def process_text_file(file: AskFileResponse):
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import tempfile
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-
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text_loader = TextFileLoader(temp_file_path)
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documents = text_loader.load_documents()
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texts = text_splitter.split_texts(documents)
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return texts
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@@ -70,10 +91,10 @@ async def on_chat_start():
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files = None
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# Wait for the user to upload a file
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while files
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files = await cl.AskFileMessage(
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content="Please upload a Text File
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accept=["text/plain"],
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max_size_mb=2,
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timeout=180,
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).send()
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)
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await msg.send()
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#
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texts = process_text_file(file)
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print(f"Processing {len(texts)} text chunks")
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async for stream_resp in result["response"]:
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await msg.stream_token(stream_resp)
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await msg.send()
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from aimakerspace.vectordatabase import VectorDatabase
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from aimakerspace.openai_utils.chatmodel import ChatOpenAI
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import chainlit as cl
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import fitz # PyMuPDF for PDF reading
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system_template = """\
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Use the following context to answer a user's question. If you cannot find the answer in the context, say you don't know the answer."""
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system_role_prompt = SystemRolePrompt(system_template)
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user_prompt_template = """\
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text_splitter = CharacterTextSplitter()
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def process_text_file(file: AskFileResponse):
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import tempfile
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file_extension = os.path.splitext(file.name)[-1].lower()
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if file_extension == ".txt":
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with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".txt") as temp_file:
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temp_file_path = temp_file.name
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with open(temp_file_path, "wb") as f:
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f.write(file.content)
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text_loader = TextFileLoader(temp_file_path)
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documents = text_loader.load_documents()
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elif file_extension == ".pdf":
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with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as temp_file:
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temp_file_path = temp_file.name
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with open(temp_file_path, "wb") as f:
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f.write(file.content)
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documents = []
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with fitz.open(temp_file_path) as doc:
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text = ""
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for page in doc:
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text += page.get_text("text")
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documents.append(text)
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else:
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raise ValueError("Unsupported file type. Please upload a .txt or .pdf file.")
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texts = text_splitter.split_texts(documents)
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return texts
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files = None
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# Wait for the user to upload a file
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while files is None:
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files = await cl.AskFileMessage(
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content="Please upload a Text File or PDF to begin!",
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accept=["text/plain", "application/pdf"],
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max_size_mb=2,
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timeout=180,
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).send()
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)
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await msg.send()
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# Load the file
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texts = process_text_file(file)
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print(f"Processing {len(texts)} text chunks")
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async for stream_resp in result["response"]:
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await msg.stream_token(stream_resp)
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await msg.send()
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