mirror of
https://github.com/hwchase17/langchain
synced 2024-11-16 06:13:16 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
66 lines
1.9 KiB
Python
66 lines
1.9 KiB
Python
import datetime
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import json
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from typing import List
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseLoader
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def concatenate_rows(message: dict, title: str) -> str:
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"""
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Combine message information in a readable format ready to be used.
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Args:
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message: Message to be concatenated
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title: Title of the conversation
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Returns:
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Concatenated message
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"""
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if not message:
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return ""
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sender = message["author"]["role"] if message["author"] else "unknown"
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text = message["content"]["parts"][0]
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date = datetime.datetime.fromtimestamp(message["create_time"]).strftime(
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"%Y-%m-%d %H:%M:%S"
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)
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return f"{title} - {sender} on {date}: {text}\n\n"
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class ChatGPTLoader(BaseLoader):
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"""Load conversations from exported `ChatGPT` data."""
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def __init__(self, log_file: str, num_logs: int = -1):
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"""Initialize a class object.
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Args:
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log_file: Path to the log file
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num_logs: Number of logs to load. If 0, load all logs.
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"""
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self.log_file = log_file
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self.num_logs = num_logs
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def load(self) -> List[Document]:
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with open(self.log_file, encoding="utf8") as f:
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data = json.load(f)[: self.num_logs] if self.num_logs else json.load(f)
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documents = []
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for d in data:
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title = d["title"]
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messages = d["mapping"]
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text = "".join(
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[
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concatenate_rows(messages[key]["message"], title)
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for idx, key in enumerate(messages)
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if not (
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idx == 0
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and messages[key]["message"]["author"]["role"] == "system"
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)
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]
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)
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metadata = {"source": str(self.log_file)}
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documents.append(Document(page_content=text, metadata=metadata))
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return documents
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