mirror of https://github.com/arc53/DocsGPT
Alex
4 months ago
committed by
GitHub
commit
2e14dec12d
@ -1,5 +1,5 @@
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organization: arc53
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defaultSticker: cln9dm7qz164460gk5ksrgr034
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defaultSticker: clqmdf0ed34290glbvqh0kzxd
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stickers:
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- id: cln9dm7qz164460gk5ksrgr034
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alias: hacktober
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- id: clqmdf0ed34290glbvqh0kzxd
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alias: festive
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from application.llm.base import BaseLLM
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from application.core.settings import settings
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class AnthropicLLM(BaseLLM):
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def __init__(self, api_key=None):
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from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT
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self.api_key = api_key or settings.ANTHROPIC_API_KEY # If not provided, use a default from settings
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self.anthropic = Anthropic(api_key=self.api_key)
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self.HUMAN_PROMPT = HUMAN_PROMPT
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self.AI_PROMPT = AI_PROMPT
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def gen(self, model, messages, engine=None, max_tokens=300, stream=False, **kwargs):
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context = messages[0]['content']
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user_question = messages[-1]['content']
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prompt = f"### Context \n {context} \n ### Question \n {user_question}"
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if stream:
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return self.gen_stream(model, prompt, max_tokens, **kwargs)
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completion = self.anthropic.completions.create(
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model=model,
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max_tokens_to_sample=max_tokens,
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stream=stream,
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prompt=f"{self.HUMAN_PROMPT} {prompt}{self.AI_PROMPT}",
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)
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return completion.completion
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def gen_stream(self, model, messages, engine=None, max_tokens=300, **kwargs):
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context = messages[0]['content']
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user_question = messages[-1]['content']
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prompt = f"### Context \n {context} \n ### Question \n {user_question}"
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stream_response = self.anthropic.completions.create(
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model=model,
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prompt=f"{self.HUMAN_PROMPT} {prompt}{self.AI_PROMPT}",
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max_tokens_to_sample=max_tokens,
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stream=True,
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)
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for completion in stream_response:
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yield completion.completion
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from application.llm.base import BaseLLM
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import json
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import requests
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class DocsGPTAPILLM(BaseLLM):
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def __init__(self, *args, **kwargs):
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self.endpoint = "https://llm.docsgpt.co.uk"
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def gen(self, model, engine, messages, stream=False, **kwargs):
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context = messages[0]['content']
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user_question = messages[-1]['content']
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prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
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response = requests.post(
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f"{self.endpoint}/answer",
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json={
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"prompt": prompt,
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"max_new_tokens": 30
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}
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)
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response_clean = response.json()['a'].split("###")[0]
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return response_clean
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def gen_stream(self, model, engine, messages, stream=True, **kwargs):
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context = messages[0]['content']
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user_question = messages[-1]['content']
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prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
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# send prompt to endpoint /stream
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response = requests.post(
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f"{self.endpoint}/stream",
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json={
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"prompt": prompt,
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"max_new_tokens": 256
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},
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stream=True
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)
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for line in response.iter_lines():
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if line:
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#data = json.loads(line)
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data_str = line.decode('utf-8')
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if data_str.startswith("data: "):
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data = json.loads(data_str[6:])
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yield data['a']
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from urllib.parse import urlparse
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from openapi_parser import parse
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try:
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from application.parser.file.base_parser import BaseParser
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except ModuleNotFoundError:
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from base_parser import BaseParser
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class OpenAPI3Parser(BaseParser):
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def init_parser(self) -> None:
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return super().init_parser()
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def get_base_urls(self, urls):
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base_urls = []
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for i in urls:
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parsed_url = urlparse(i)
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base_url = parsed_url.scheme + "://" + parsed_url.netloc
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if base_url not in base_urls:
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base_urls.append(base_url)
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return base_urls
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def get_info_from_paths(self, path):
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info = ""
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if path.operations:
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for operation in path.operations:
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info += (
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f"\n{operation.method.value}="
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f"{operation.responses[0].description}"
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)
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return info
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def parse_file(self, file_path):
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data = parse(file_path)
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results = ""
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base_urls = self.get_base_urls(link.url for link in data.servers)
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base_urls = ",".join([base_url for base_url in base_urls])
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results += f"Base URL:{base_urls}\n"
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i = 1
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for path in data.paths:
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info = self.get_info_from_paths(path)
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results += (
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f"Path{i}: {path.url}\n"
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f"description: {path.description}\n"
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f"parameters: {path.parameters}\nmethods: {info}\n"
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)
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i += 1
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with open("results.txt", "w") as f:
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f.write(results)
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return results
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@ -0,0 +1,9 @@
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You are a helpful AI assistant, DocsGPT, specializing in document assistance, designed to offer detailed and informative responses.
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If appropriate, your answers can include code examples, formatted as follows:
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```(language)
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(code)
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```
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You effectively utilize chat history, ensuring relevant and tailored responses.
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If a question doesn't align with your context, you provide friendly and helpful replies.
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----------------
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{summaries}
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You are an AI Assistant, DocsGPT, adept at offering document assistance.
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Your expertise lies in providing answer on top of provided context.
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You can leverage the chat history if needed.
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Answer the question based on the context below.
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Keep the answer concise. Respond "Irrelevant context" if not sure about the answer.
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If question is not related to the context, respond "Irrelevant context".
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When using code examples, use the following format:
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```(language)
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(code)
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```
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----------------
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Context:
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{summaries}
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You are a DocsGPT, friendly and helpful AI assistant by Arc53 that provides help with documents. You give thorough answers with code examples if possible.
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QUESTION: How to merge tables in pandas?
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=========
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Content: pandas provides various facilities for easily combining together Series or DataFrame with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations.
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Source: 28-pl
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Content: pandas provides a single function, merge(), as the entry point for all standard database join operations between DataFrame or named Series objects: \n\npandas.merge(left, right, how='inner', on=None, left_on=None, right_on=None, left_index=False, right_index=False, sort=False, suffixes=('_x', '_y'), copy=True, indicator=False, validate=None)
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Source: 30-pl
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=========
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FINAL ANSWER: To merge two tables in pandas, you can use the pd.merge() function. The basic syntax is: \n\npd.merge(left, right, on, how) \n\nwhere left and right are the two tables to merge, on is the column to merge on, and how is the type of merge to perform. \n\nFor example, to merge the two tables df1 and df2 on the column 'id', you can use: \n\npd.merge(df1, df2, on='id', how='inner')
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SOURCES: 28-pl 30-pl
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QUESTION: How are you?
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=========
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CONTENT:
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SOURCE:
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=========
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FINAL ANSWER: I am fine, thank you. How are you?
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SOURCES:
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QUESTION: {{ question }}
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=========
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{{ summaries }}
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=========
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FINAL ANSWER:
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@ -1,33 +0,0 @@
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You are a DocsGPT, friendly and helpful AI assistant by Arc53 that provides help with documents. You give thorough answers with code examples if possible.
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QUESTION: How to merge tables in pandas?
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=========
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Content: pandas provides various facilities for easily combining together Series or DataFrame with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations.
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Source: 28-pl
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Content: pandas provides a single function, merge(), as the entry point for all standard database join operations between DataFrame or named Series objects: \n\npandas.merge(left, right, how='inner', on=None, left_on=None, right_on=None, left_index=False, right_index=False, sort=False, suffixes=('_x', '_y'), copy=True, indicator=False, validate=None)
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Source: 30-pl
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=========
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FINAL ANSWER: To merge two tables in pandas, you can use the pd.merge() function. The basic syntax is: \n\npd.merge(left, right, on, how) \n\nwhere left and right are the two tables to merge, on is the column to merge on, and how is the type of merge to perform. \n\nFor example, to merge the two tables df1 and df2 on the column 'id', you can use: \n\npd.merge(df1, df2, on='id', how='inner')
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SOURCES: 28-pl 30-pl
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QUESTION: How are you?
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=========
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CONTENT:
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SOURCE:
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=========
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FINAL ANSWER: I am fine, thank you. How are you?
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SOURCES:
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QUESTION: {{ historyquestion }}
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=========
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CONTENT:
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SOURCE:
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=========
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FINAL ANSWER: {{ historyanswer }}
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SOURCES:
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QUESTION: {{ question }}
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=========
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{{ summaries }}
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=========
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FINAL ANSWER:
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@ -1,4 +0,0 @@
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Use the following portion of a long document to see if any of the text is relevant to answer the question.
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{{ context }}
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Question: {{ question }}
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Provide all relevant text to the question verbatim. Summarize if needed. If nothing relevant return "-".
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@ -1,106 +1,33 @@
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aiodns==3.0.0
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aiohttp==3.8.5
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aiohttp-retry==2.8.3
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aiosignal==1.3.1
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aleph-alpha-client==2.16.1
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amqp==5.1.1
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async-timeout==4.0.2
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attrs==22.2.0
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billiard==3.6.4.0
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blobfile==2.0.1
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boto3==1.28.20
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celery==5.2.7
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cffi==1.15.1
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charset-normalizer==3.1.0
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click==8.1.3
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click-didyoumean==0.3.0
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click-plugins==1.1.1
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click-repl==0.2.0
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cryptography==41.0.4
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dataclasses-json==0.5.7
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decorator==5.1.1
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dill==0.3.6
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dnspython==2.3.0
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ecdsa==0.18.0
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elasticsearch==8.9.0
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entrypoints==0.4
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faiss-cpu==1.7.3
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filelock==3.9.0
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Flask==2.2.5
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Flask-Cors==3.0.10
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frozenlist==1.3.3
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geojson==2.5.0
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gunicorn==20.1.0
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greenlet==2.0.2
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gpt4all==0.1.7
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huggingface-hub==0.15.1
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humbug==0.3.2
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idna==3.4
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itsdangerous==2.1.2
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Jinja2==3.1.2
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jmespath==1.0.1
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joblib==1.2.0
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kombu==5.2.4
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langchain==0.0.308
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loguru==0.6.0
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lxml==4.9.2
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MarkupSafe==2.1.2
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marshmallow==3.19.0
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marshmallow-enum==1.5.1
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mpmath==1.3.0
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multidict==6.0.4
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multiprocess==0.70.14
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mypy-extensions==1.0.0
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networkx==3.0
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npx
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anthropic==0.12.0
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boto3==1.34.6
|
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celery==5.3.6
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dataclasses_json==0.6.3
|
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docx2txt==0.8
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EbookLib==0.18
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elasticsearch==8.12.0
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escodegen==1.0.11
|
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esprima==4.0.1
|
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faiss-cpu==1.7.4
|
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Flask==3.0.1
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gunicorn==21.2.0
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html2text==2020.1.16
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javalang==0.13.0
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langchain==0.1.4
|
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langchain-openai==0.0.5
|
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nltk==3.8.1
|
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numcodecs==0.11.0
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numpy==1.24.2
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openai==0.27.8
|
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packaging==23.0
|
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pathos==0.3.0
|
||||
Pillow==10.0.1
|
||||
pox==0.3.2
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ppft==1.7.6.6
|
||||
prompt-toolkit==3.0.38
|
||||
py==1.11.0
|
||||
pyasn1==0.4.8
|
||||
pycares==4.3.0
|
||||
pycparser==2.21
|
||||
pycryptodomex==3.17
|
||||
pycryptodome==3.19.0
|
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pydantic==1.10.5
|
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PyJWT==2.6.0
|
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pymongo==4.3.3
|
||||
pyowm==3.3.0
|
||||
openapi3_parser==1.1.16
|
||||
pandas==2.2.0
|
||||
pydantic_settings==2.1.0
|
||||
pymongo==4.6.1
|
||||
PyPDF2==3.0.1
|
||||
PySocks==1.7.1
|
||||
pytest
|
||||
python-dateutil==2.8.2
|
||||
python-dotenv==1.0.0
|
||||
python-jose==3.3.0
|
||||
pytz==2022.7.1
|
||||
PyYAML==6.0
|
||||
redis==4.5.4
|
||||
regex==2022.10.31
|
||||
requests==2.31.0
|
||||
python-dotenv==1.0.1
|
||||
redis==5.0.1
|
||||
Requests==2.31.0
|
||||
retry==0.9.2
|
||||
rsa==4.9
|
||||
scikit-learn==1.2.2
|
||||
scipy==1.10.1
|
||||
sentencepiece
|
||||
six==1.16.0
|
||||
SQLAlchemy==1.4.46
|
||||
sympy==1.11.1
|
||||
tenacity==8.2.2
|
||||
threadpoolctl==3.1.0
|
||||
tiktoken
|
||||
tqdm==4.65.0
|
||||
transformers==4.30.0
|
||||
typer==0.7.0
|
||||
typing-inspect==0.8.0
|
||||
typing_extensions==4.5.0
|
||||
urllib3==1.26.17
|
||||
vine==5.0.0
|
||||
wcwidth==0.2.6
|
||||
yarl==1.8.2
|
||||
sentence-transformers
|
||||
tiktoken==0.5.2
|
||||
torch==2.1.2
|
||||
tqdm==4.66.1
|
||||
transformers==4.36.2
|
||||
unstructured==0.12.2
|
||||
Werkzeug==3.0.1
|
||||
|
||||
@ -0,0 +1,8 @@
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class Document(str):
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||||
"""Class for storing a piece of text and associated metadata."""
|
||||
|
||||
def __new__(cls, page_content: str, metadata: dict):
|
||||
instance = super().__new__(cls, page_content)
|
||||
instance.page_content = page_content
|
||||
instance.metadata = metadata
|
||||
return instance
|
||||
@ -0,0 +1,126 @@
|
||||
from application.vectorstore.base import BaseVectorStore
|
||||
from application.core.settings import settings
|
||||
from application.vectorstore.document_class import Document
|
||||
|
||||
class MongoDBVectorStore(BaseVectorStore):
|
||||
def __init__(
|
||||
self,
|
||||
path: str = "",
|
||||
embeddings_key: str = "embeddings",
|
||||
collection: str = "documents",
|
||||
index_name: str = "vector_search_index",
|
||||
text_key: str = "text",
|
||||
embedding_key: str = "embedding",
|
||||
database: str = "docsgpt",
|
||||
):
|
||||
self._index_name = index_name
|
||||
self._text_key = text_key
|
||||
self._embedding_key = embedding_key
|
||||
self._embeddings_key = embeddings_key
|
||||
self._mongo_uri = settings.MONGO_URI
|
||||
self._path = path.replace("application/indexes/", "").rstrip("/")
|
||||
self._embedding = self._get_embeddings(settings.EMBEDDINGS_NAME, embeddings_key)
|
||||
|
||||
try:
|
||||
import pymongo
|
||||
except ImportError:
|
||||
raise ImportError(
|
||||
"Could not import pymongo python package. "
|
||||
"Please install it with `pip install pymongo`."
|
||||
)
|
||||
|
||||
self._client = pymongo.MongoClient(self._mongo_uri)
|
||||
self._database = self._client[database]
|
||||
self._collection = self._database[collection]
|
||||
|
||||
|
||||
def search(self, question, k=2, *args, **kwargs):
|
||||
query_vector = self._embedding.embed_query(question)
|
||||
|
||||
pipeline = [
|
||||
{
|
||||
"$vectorSearch": {
|
||||
"queryVector": query_vector,
|
||||
"path": self._embedding_key,
|
||||
"limit": k,
|
||||
"numCandidates": k * 10,
|
||||
"index": self._index_name,
|
||||
"filter": {
|
||||
"store": {"$eq": self._path}
|
||||
}
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
cursor = self._collection.aggregate(pipeline)
|
||||
|
||||
results = []
|
||||
for doc in cursor:
|
||||
text = doc[self._text_key]
|
||||
doc.pop("_id")
|
||||
doc.pop(self._text_key)
|
||||
doc.pop(self._embedding_key)
|
||||
metadata = doc
|
||||
results.append(Document(text, metadata))
|
||||
return results
|
||||
|
||||
def _insert_texts(self, texts, metadatas):
|
||||
if not texts:
|
||||
return []
|
||||
embeddings = self._embedding.embed_documents(texts)
|
||||
to_insert = [
|
||||
{self._text_key: t, self._embedding_key: embedding, **m}
|
||||
for t, m, embedding in zip(texts, metadatas, embeddings)
|
||||
]
|
||||
# insert the documents in MongoDB Atlas
|
||||
insert_result = self._collection.insert_many(to_insert)
|
||||
return insert_result.inserted_ids
|
||||
|
||||
def add_texts(self,
|
||||
texts,
|
||||
metadatas = None,
|
||||
ids = None,
|
||||
refresh_indices = True,
|
||||
create_index_if_not_exists = True,
|
||||
bulk_kwargs = None,
|
||||
**kwargs,):
|
||||
|
||||
|
||||
#dims = self._embedding.client[1].word_embedding_dimension
|
||||
# # check if index exists
|
||||
# if create_index_if_not_exists:
|
||||
# # check if index exists
|
||||
# info = self._collection.index_information()
|
||||
# if self._index_name not in info:
|
||||
# index_mongo = {
|
||||
# "fields": [{
|
||||
# "type": "vector",
|
||||
# "path": self._embedding_key,
|
||||
# "numDimensions": dims,
|
||||
# "similarity": "cosine",
|
||||
# },
|
||||
# {
|
||||
# "type": "filter",
|
||||
# "path": "store"
|
||||
# }]
|
||||
# }
|
||||
# self._collection.create_index(self._index_name, index_mongo)
|
||||
|
||||
batch_size = 100
|
||||
_metadatas = metadatas or ({} for _ in texts)
|
||||
texts_batch = []
|
||||
metadatas_batch = []
|
||||
result_ids = []
|
||||
for i, (text, metadata) in enumerate(zip(texts, _metadatas)):
|
||||
texts_batch.append(text)
|
||||
metadatas_batch.append(metadata)
|
||||
if (i + 1) % batch_size == 0:
|
||||
result_ids.extend(self._insert_texts(texts_batch, metadatas_batch))
|
||||
texts_batch = []
|
||||
metadatas_batch = []
|
||||
if texts_batch:
|
||||
result_ids.extend(self._insert_texts(texts_batch, metadatas_batch))
|
||||
return result_ids
|
||||
|
||||
def delete_index(self, *args, **kwargs):
|
||||
self._collection.delete_many({"store": self._path})
|
||||
@ -1,2 +1,2 @@
|
||||
ignore:
|
||||
- "*/tests/*”
|
||||
- "*/tests/*"
|
||||
@ -0,0 +1,22 @@
|
||||
version: "3.9"
|
||||
|
||||
services:
|
||||
frontend:
|
||||
build: ./frontend
|
||||
environment:
|
||||
- VITE_API_HOST=http://localhost:7091
|
||||
- VITE_API_STREAMING=$VITE_API_STREAMING
|
||||
ports:
|
||||
- "5173:5173"
|
||||
depends_on:
|
||||
- mock-backend
|
||||
|
||||
mock-backend:
|
||||
build: ./mock-backend
|
||||
ports:
|
||||
- "7091:7091"
|
||||
|
||||
redis:
|
||||
image: redis:6-alpine
|
||||
ports:
|
||||
- 6379:6379
|
||||
@ -1 +1,51 @@
|
||||
# nextra-docsgpt
|
||||
# nextra-docsgpt
|
||||
|
||||
## Setting Up Docs Folder of DocsGPT Locally
|
||||
|
||||
### 1. Clone the DocsGPT repository:
|
||||
|
||||
```bash
|
||||
git clone https://github.com/arc53/DocsGPT.git
|
||||
```
|
||||
### 2. Navigate to the docs folder:
|
||||
|
||||
```bash
|
||||
cd DocsGPT/docs
|
||||
```
|
||||
|
||||
The docs folder contains the markdown files that make up the documentation. The majority of the files are in the pages directory. Some notable files in this folder include:
|
||||
|
||||
`index.mdx`: The main documentation file.
|
||||
`_app.js`: This file is used to customize the default Next.js application shell.
|
||||
`theme.config.jsx`: This file is for configuring the Nextra theme for the documentation.
|
||||
|
||||
### 3. Verify that you have Node.js and npm installed in your system. You can check by running:
|
||||
|
||||
```bash
|
||||
node --version
|
||||
npm --version
|
||||
```
|
||||
|
||||
### 4. If not installed, download Node.js and npm from the respective official websites.
|
||||
|
||||
### 5. Once you have Node.js and npm running, proceed to install yarn - another package manager that helps to manage project dependencies:
|
||||
|
||||
```bash
|
||||
npm install --global yarn
|
||||
```
|
||||
|
||||
### 6. Install the project dependencies using yarn:
|
||||
|
||||
```bash
|
||||
yarn install
|
||||
```
|
||||
|
||||
### 7. After the successful installation of the project dependencies, start the local server:
|
||||
|
||||
```bash
|
||||
yarn dev
|
||||
```
|
||||
|
||||
- Now, you should be able to view the docs on your local environment by visiting `http://localhost:5000`. You can explore the different markdown files and make changes as you see fit.
|
||||
|
||||
- **Footnotes:** This guide assumes you have Node.js and npm installed. The guide involves running a local server using yarn, and viewing the documentation offline. If you encounter any issues, it may be worth verifying your Node.js and npm installations and whether you have installed yarn correctly.
|
||||
|
||||
@ -1,9 +1,9 @@
|
||||
const withNextra = require('nextra')({
|
||||
theme: 'nextra-theme-docs',
|
||||
themeConfig: './theme.config.jsx'
|
||||
})
|
||||
theme: 'nextra-theme-docs',
|
||||
themeConfig: './theme.config.jsx'
|
||||
})
|
||||
|
||||
module.exports = withNextra()
|
||||
|
||||
module.exports = withNextra()
|
||||
|
||||
// If you have other Next.js configurations, you can pass them as the parameter:
|
||||
// module.exports = withNextra({ /* other next.js config */ })
|
||||
// If you have other Next.js configurations, you can pass them as the parameter:
|
||||
// module.exports = withNextra({ /* other next.js config */ })
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@ -1,31 +1,128 @@
|
||||
## Launching Web App
|
||||
Note: Make sure you have Docker installed
|
||||
**Note**: Make sure you have Docker installed
|
||||
|
||||
On macOS or Linux, just write:
|
||||
**On macOS or Linux:**
|
||||
Just run the following command:
|
||||
|
||||
`./setup.sh`
|
||||
```bash
|
||||
./setup.sh
|
||||
```
|
||||
|
||||
It will install all the dependencies and give you an option to download the local model or use OpenAI
|
||||
This command will install all the necessary dependencies and provide you with an option to use our LLM API, download the local model or use OpenAI.
|
||||
|
||||
Otherwise, refer to this Guide:
|
||||
If you prefer to follow manual steps, refer to this guide:
|
||||
|
||||
1. Open and download this repository with `git clone https://github.com/arc53/DocsGPT.git`.
|
||||
2. Create a `.env` file in your root directory and set your `API_KEY` with your [OpenAI API key](https://platform.openai.com/account/api-keys).
|
||||
3. Run `docker-compose build && docker-compose up`.
|
||||
4. Navigate to `http://localhost:5173/`.
|
||||
1. Open and download this repository with
|
||||
```bash
|
||||
git clone https://github.com/arc53/DocsGPT.git
|
||||
```
|
||||
2. Create a `.env` file in your root directory and set your `API_KEY` with your [OpenAI API key](https://platform.openai.com/account/api-keys). (optional in case you want to use OpenAI)
|
||||
3. Run the following commands:
|
||||
```bash
|
||||
docker-compose build && docker-compose up
|
||||
```
|
||||
4. Navigate to http://localhost:5173/.
|
||||
|
||||
To stop, simply press **Ctrl + C**.
|
||||
|
||||
**For WINDOWS:**
|
||||
|
||||
To run the setup on Windows, you have two options: using the Windows Subsystem for Linux (WSL) or using Git Bash or Command Prompt.
|
||||
|
||||
**Option 1: Using Windows Subsystem for Linux (WSL):**
|
||||
|
||||
1. Install WSL if you haven't already. You can follow the official Microsoft documentation for installation: (https://learn.microsoft.com/en-us/windows/wsl/install).
|
||||
2. After setting up WSL, open the WSL terminal.
|
||||
3. Clone the repository and create the `.env` file:
|
||||
```bash
|
||||
git clone https://github.com/arc53/DocsGPT.git
|
||||
cd DocsGPT
|
||||
echo "API_KEY=Yourkey" > .env
|
||||
echo "VITE_API_STREAMING=true" >> .env
|
||||
```
|
||||
4. Run the following command to start the setup with Docker Compose:
|
||||
```bash
|
||||
./run-with-docker-compose.sh
|
||||
```
|
||||
6. Open your web browser and navigate to http://localhost:5173/.
|
||||
7. To stop the setup, just press **Ctrl + C** in the WSL terminal
|
||||
|
||||
**Option 2: Using Git Bash or Command Prompt (CMD):**
|
||||
|
||||
1. Install Git for Windows if you haven't already. Download it from the official website: (https://gitforwindows.org/).
|
||||
2. Open Git Bash or Command Prompt.
|
||||
3. Clone the repository and create the `.env` file:
|
||||
```bash
|
||||
git clone https://github.com/arc53/DocsGPT.git
|
||||
cd DocsGPT
|
||||
echo "API_KEY=Yourkey" > .env
|
||||
echo "VITE_API_STREAMING=true" >> .env
|
||||
```
|
||||
4. Run the following command to start the setup with Docker Compose:
|
||||
```bash
|
||||
./run-with-docker-compose.sh
|
||||
```
|
||||
5. Open your web browser and navigate to http://localhost:5173/.
|
||||
6. To stop the setup, just press **Ctrl + C** in the Git Bash or Command Prompt terminal.
|
||||
|
||||
These steps should help you set up and run the project on Windows using either WSL or Git Bash/Command Prompt.
|
||||
**Important:** Ensure that Docker is installed and properly configured on your Windows system for these steps to work.
|
||||
|
||||
|
||||
For WINDOWS:
|
||||
|
||||
To run the given setup on Windows, you can use the Windows Subsystem for Linux (WSL) or a Git Bash terminal to execute similar commands. Here are the steps adapted for Windows:
|
||||
|
||||
Option 1: Using Windows Subsystem for Linux (WSL):
|
||||
|
||||
1. Install WSL if you haven't already. You can follow the official Microsoft documentation for installation: (https://learn.microsoft.com/en-us/windows/wsl/install).
|
||||
2. After setting up WSL, open the WSL terminal.
|
||||
3. Clone the repository and create the `.env` file:
|
||||
```bash
|
||||
git clone https://github.com/arc53/DocsGPT.git
|
||||
cd DocsGPT
|
||||
echo "API_KEY=Yourkey" > .env
|
||||
echo "VITE_API_STREAMING=true" >> .env
|
||||
```
|
||||
4. Run the following command to start the setup with Docker Compose:
|
||||
```bash
|
||||
./run-with-docker-compose.sh
|
||||
```
|
||||
5. Open your web browser and navigate to http://localhost:5173/.
|
||||
6. To stop the setup, just press **Ctrl + C** in the WSL terminal.
|
||||
|
||||
Option 2: Using Git Bash or Command Prompt (CMD):
|
||||
|
||||
1. Install Git for Windows if you haven't already. You can download it from the official website: (https://gitforwindows.org/).
|
||||
2. Open Git Bash or Command Prompt.
|
||||
3. Clone the repository and create the `.env` file:
|
||||
```bash
|
||||
git clone https://github.com/arc53/DocsGPT.git
|
||||
cd DocsGPT
|
||||
echo "API_KEY=Yourkey" > .env
|
||||
echo "VITE_API_STREAMING=true" >> .env
|
||||
```
|
||||
4. Run the following command to start the setup with Docker Compose:
|
||||
```bash
|
||||
./run-with-docker-compose.sh
|
||||
```
|
||||
5. Open your web browser and navigate to http://localhost:5173/.
|
||||
6. To stop the setup, just press **Ctrl + C** in the Git Bash or Command Prompt terminal.
|
||||
|
||||
These steps should help you set up and run the project on Windows using either WSL or Git Bash/Command Prompt. Make sure you have Docker installed and properly configured on your Windows system for this to work.
|
||||
|
||||
To stop, just run `Ctrl + C`.
|
||||
|
||||
### Chrome Extension
|
||||
|
||||
To install the Chrome extension:
|
||||
#### Installing the Chrome extension:
|
||||
To enhance your DocsGPT experience, you can install the DocsGPT Chrome extension. Here's how:
|
||||
|
||||
1. In the DocsGPT GitHub repository, click on the "Code" button and select "Download ZIP".
|
||||
1. In the DocsGPT GitHub repository, click on the **Code** button and select **Download ZIP**.
|
||||
2. Unzip the downloaded file to a location you can easily access.
|
||||
3. Open the Google Chrome browser and click on the three dots menu (upper right corner).
|
||||
4. Select "More Tools" and then "Extensions".
|
||||
5. Turn on the "Developer mode" switch in the top right corner of the Extensions page.
|
||||
6. Click on the "Load unpacked" button.
|
||||
7. Select the "Chrome" folder where the DocsGPT files have been unzipped (docsgpt-main > extensions > chrome).
|
||||
4. Select **More Tools** and then **Extensions**.
|
||||
5. Turn on the **Developer mode** switch in the top right corner of the **Extensions page**.
|
||||
6. Click on the **Load unpacked** button.
|
||||
7. Select the **Chrome** folder where the DocsGPT files have been unzipped (docsgpt-main > extensions > chrome).
|
||||
8. The extension should now be added to Google Chrome and can be managed on the Extensions page.
|
||||
9. To disable or remove the extension, simply turn off the toggle switch on the extension card or click the "Remove" button.
|
||||
9. To disable or remove the extension, simply turn off the toggle switch on the extension card or click the **Remove** button.
|
||||
|
||||
@ -0,0 +1,254 @@
|
||||
|
||||
# Self-hosting DocsGPT on Railway
|
||||
|
||||
|
||||
|
||||
Here's a step-by-step guide on how to host DocsGPT on Railway App.
|
||||
|
||||
|
||||
|
||||
At first Clone and set up the project locally to run , test and Modify.
|
||||
|
||||
|
||||
|
||||
### 1. Clone and GitHub SetUp
|
||||
|
||||
a. Open Terminal (Windows Shell or Git bash(recommended)).
|
||||
|
||||
|
||||
|
||||
b. Type `git clone https://github.com/arc53/DocsGPT.git`
|
||||
|
||||
|
||||
|
||||
#### Download the package information
|
||||
|
||||
|
||||
|
||||
Once it has finished cloning the repository, it is time to download the package information from all sources. To do so, simply enter the following command:
|
||||
|
||||
|
||||
|
||||
`sudo apt update`
|
||||
|
||||
|
||||
|
||||
#### Install Docker and Docker Compose
|
||||
|
||||
|
||||
|
||||
DocsGPT backend and worker use Python, Frontend is written on React and the whole application is containerized using Docker. To install Docker and Docker Compose, enter the following commands:
|
||||
|
||||
|
||||
|
||||
`sudo apt install docker.io`
|
||||
|
||||
|
||||
|
||||
And now install docker-compose:
|
||||
|
||||
|
||||
|
||||
`sudo apt install docker-compose`
|
||||
|
||||
|
||||
|
||||
#### Access the DocsGPT Folder
|
||||
|
||||
|
||||
|
||||
Enter the following command to access the folder in which the DocsGPT docker-compose file is present.
|
||||
|
||||
|
||||
|
||||
`cd DocsGPT/`
|
||||
|
||||
|
||||
|
||||
#### Prepare the Environment
|
||||
|
||||
|
||||
|
||||
Inside the DocsGPT folder create a `.env` file and copy the contents of `.env_sample` into it.
|
||||
|
||||
|
||||
|
||||
`nano .env`
|
||||
|
||||
|
||||
|
||||
Make sure your `.env` file looks like this:
|
||||
|
||||
|
||||
|
||||
```
|
||||
|
||||
OPENAI_API_KEY=(Your OpenAI API key)
|
||||
|
||||
VITE_API_STREAMING=true
|
||||
|
||||
SELF_HOSTED_MODEL=false
|
||||
|
||||
```
|
||||
|
||||
|
||||
|
||||
To save the file, press CTRL+X, then Y, and then ENTER.
|
||||
|
||||
|
||||
|
||||
Next, set the correct IP for the Backend by opening the docker-compose.yml file:
|
||||
|
||||
|
||||
|
||||
`nano docker-compose.yml`
|
||||
|
||||
|
||||
|
||||
And Change line 7 to: `VITE_API_HOST=http://localhost:7091`
|
||||
|
||||
to this `VITE_API_HOST=http://<your instance public IP>:7091`
|
||||
|
||||
|
||||
|
||||
This will allow the frontend to connect to the backend.
|
||||
|
||||
|
||||
|
||||
#### Running the Application
|
||||
|
||||
|
||||
|
||||
You're almost there! Now that all the necessary bits and pieces have been installed, it is time to run the application. To do so, use the following command:
|
||||
|
||||
|
||||
|
||||
`sudo docker-compose up -d`
|
||||
|
||||
|
||||
|
||||
Launching it for the first time will take a few minutes to download all the necessary dependencies and build.
|
||||
|
||||
|
||||
|
||||
Once this is done you can go ahead and close the terminal window.
|
||||
|
||||
|
||||
|
||||
### 2. Pushing it to your own Repository
|
||||
|
||||
|
||||
|
||||
a. Create a Repository on your GitHub.
|
||||
|
||||
|
||||
|
||||
b. Open Terminal in the same directory of the Cloned project.
|
||||
|
||||
|
||||
|
||||
c. Type `git init`
|
||||
|
||||
|
||||
|
||||
d. `git add .`
|
||||
|
||||
|
||||
|
||||
e. `git commit -m "first-commit"`
|
||||
|
||||
|
||||
|
||||
f. `git remote add origin <your repository link>`
|
||||
|
||||
|
||||
|
||||
g. `git push git push --set-upstream origin master`
|
||||
|
||||
Your local files will now be pushed to your GitHub Account. :)
|
||||
|
||||
|
||||
### 3. Create a Railway Account:
|
||||
|
||||
|
||||
|
||||
If you haven't already, create or log in to your railway account do it by visiting [Railway](https://railway.app/)
|
||||
|
||||
|
||||
|
||||
Signup via **GitHub** [Recommended].
|
||||
|
||||
|
||||
|
||||
### 4. Start New Project:
|
||||
|
||||
|
||||
|
||||
a. Open Railway app and Click on "Start New Project."
|
||||
|
||||
|
||||
|
||||
b. Choose any from the list of options available (Recommended "**Deploy from GitHub Repo**")
|
||||
|
||||
|
||||
|
||||
c. Choose the required Repository from your GitHub.
|
||||
|
||||
|
||||
|
||||
d. Configure and allow access to modify your GitHub content from the pop-up window.
|
||||
|
||||
|
||||
|
||||
e. Agree to all the terms and conditions.
|
||||
|
||||
|
||||
|
||||
PS: It may take a few minutes for the account setup to complete.
|
||||
|
||||
|
||||
|
||||
#### You will get A free trial of $5 (use it for trial and then purchase if satisfied and needed)
|
||||
|
||||
|
||||
|
||||
### 5. Connecting to Your newly Railway app with GitHub
|
||||
|
||||
|
||||
|
||||
a. Choose DocsGPT repo from the list of your GitHub repository that you want to deploy now.
|
||||
|
||||
|
||||
|
||||
b. Click on Deploy now.
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
c. Select Variables Tab.
|
||||
|
||||
|
||||
|
||||
d. Upload the env file here that you used for local setup.
|
||||
|
||||
|
||||
|
||||
e. Go to Settings Tab now.
|
||||
|
||||
|
||||
|
||||
f. Go to "Networking" and click on Generate Domain Name, to get the URL of your hosted project.
|
||||
|
||||
|
||||
|
||||
g. You can update the Root directory, build command, installation command as per need.
|
||||
|
||||
*[However recommended not the disturb these options and leave them as default if not that needed.]*
|
||||
|
||||
|
||||
|
||||
|
||||
Your own DocsGPT is now available at the Generated domain URl. :)
|
||||
@ -1,29 +1,44 @@
|
||||
### To start chatwoot extension:
|
||||
1. Prepare and start the DocsGPT itself (load your documentation too). Follow our [wiki](https://github.com/arc53/DocsGPT/wiki) to start it and to [ingest](https://github.com/arc53/DocsGPT/wiki/How-to-train-on-other-documentation) data.
|
||||
2. Go to chatwoot, **Navigate** to your profile (bottom left), click on profile settings, scroll to the bottom and copy **Access Token**.
|
||||
3. Navigate to `/extensions/chatwoot`. Copy `.env_sample` and create `.env` file.
|
||||
4. Fill in the values.
|
||||
## Chatwoot Extension Setup Guide
|
||||
|
||||
```
|
||||
docsgpt_url=<docsgpt_api_url>
|
||||
chatwoot_url=<chatwoot_url>
|
||||
docsgpt_key=<openai_api_key or other llm key>
|
||||
chatwoot_token=<from part 2>
|
||||
```
|
||||
### Step 1: Prepare and Start DocsGPT
|
||||
|
||||
5. Start with `flask run` command.
|
||||
- **Launch DocsGPT**: Follow the instructions in our [DocsGPT Wiki](https://github.com/arc53/DocsGPT/wiki) to start DocsGPT. Make sure to load your documentation.
|
||||
|
||||
If you want for bot to stop responding to questions for a specific user or session, just add a label `human-requested` in your conversation.
|
||||
### Step 2: Get Access Token from Chatwoot
|
||||
|
||||
- Go to Chatwoot.
|
||||
- In your profile settings (located at the bottom left), scroll down and copy the **Access Token**.
|
||||
|
||||
### Optional (extra validation)
|
||||
In `app.py` uncomment lines 12-13 and 71-75
|
||||
### Step 3: Set Up Chatwoot Extension
|
||||
|
||||
in your `.env` file add:
|
||||
- Navigate to `/extensions/chatwoot`.
|
||||
- Copy the `.env_sample` file and create a new file named `.env`.
|
||||
- Fill in the values in the `.env` file as follows:
|
||||
|
||||
```env
|
||||
docsgpt_url=<Docsgpt_API_URL>
|
||||
chatwoot_url=<Chatwoot_URL>
|
||||
docsgpt_key=<OpenAI_API_Key or Other_LLM_Key>
|
||||
chatwoot_token=<Token from Step 2>
|
||||
```
|
||||
account_id=(optional) 1
|
||||
|
||||
### Step 4: Start the Extension
|
||||
|
||||
- Use the command `flask run` to start the extension.
|
||||
|
||||
### Step 5: Optional - Extra Validation
|
||||
|
||||
- In app.py, uncomment lines 12-13 and 71-75.
|
||||
- Add the following lines to your .env file:
|
||||
```account_id=(optional) 1
|
||||
assignee_id=(optional) 1
|
||||
```
|
||||
These Chatwoot values help ensure you respond to the correct widget and handle questions assigned to a specific user.
|
||||
|
||||
### Stopping Bot Responses for Specific User or Session
|
||||
|
||||
- If you want the bot to stop responding to questions for a specific user or session, add a label `human-requested` in your conversation.
|
||||
|
||||
### Additional Notes
|
||||
|
||||
Those are chatwoot values and will allow you to check if you are responding to correct widget and responding to questions assigned to specific user.
|
||||
- For further details on training on other documentation, refer to our [wiki](https://github.com/arc53/DocsGPT/wiki/How-to-train-on-other-documentation).
|
||||
@ -1,4 +1,27 @@
|
||||
## To customize a main prompt, navigate to `/application/prompt/combine_prompt.txt`
|
||||
# Customizing the Main Prompt
|
||||
|
||||
You can try editing it to see how the model responses.
|
||||
Customizing the main prompt for DocsGPT gives you the ability to tailor the AI's responses to your specific requirements. By modifying the prompt text, you can achieve more accurate and relevant answers. Here's how you can do it:
|
||||
|
||||
1. Navigate to `/application/prompts/combine_prompt.txt`.
|
||||
|
||||
2. Open the `combine_prompt.txt` file and modify the prompt text to suit your needs. You can experiment with different phrasings and structures to observe how the model responds. The main prompt serves as guidance to the AI model on how to generate responses.
|
||||
|
||||
## Example Prompt Modification
|
||||
|
||||
**Original Prompt:**
|
||||
```markdown
|
||||
You are a DocsGPT, friendly and helpful AI assistant by Arc53 that provides help with documents. You give thorough answers with code examples if possible.
|
||||
Use the following pieces of context to help answer the users question. If it's not relevant to the question, provide friendly responses.
|
||||
You have access to chat history, and can use it to help answer the question.
|
||||
When using code examples, use the following format:
|
||||
|
||||
(code)
|
||||
{summaries}
|
||||
```
|
||||
|
||||
Feel free to customize the prompt to align it with your specific use case or the kind of responses you want from the AI. For example, you can focus on specific document types, industries, or topics to get more targeted results.
|
||||
|
||||
## Conclusion
|
||||
|
||||
Customizing the main prompt for DocsGPT allows you to tailor the AI's responses to your unique requirements. Whether you need in-depth explanations, code examples, or specific insights, you can achieve it by modifying the main prompt. Remember to experiment and fine-tune your prompts to get the best results.
|
||||
|
||||
|
||||
@ -1,36 +1,48 @@
|
||||
Fortunately, there are many providers for LLM's and some of them can even be run locally
|
||||
# Setting Up Local Language Models for Your App
|
||||
|
||||
There are two models used in the app:
|
||||
1. Embeddings.
|
||||
2. Text generation.
|
||||
Your app relies on two essential models: Embeddings and Text Generation. While OpenAI's default models work seamlessly, you have the flexibility to switch providers or even run the models locally.
|
||||
|
||||
By default, we use OpenAI's models but if you want to change it or even run it locally, it's very simple!
|
||||
## Step 1: Configure Environment Variables
|
||||
|
||||
### Go to .env file or set environment variables:
|
||||
Navigate to the `.env` file or set the following environment variables:
|
||||
|
||||
`LLM_NAME=<your Text generation>`
|
||||
```env
|
||||
LLM_NAME=<your Text Generation model>
|
||||
API_KEY=<API key for Text Generation>
|
||||
EMBEDDINGS_NAME=<LLM for Embeddings>
|
||||
EMBEDDINGS_KEY=<API key for Embeddings>
|
||||
VITE_API_STREAMING=<true or false>
|
||||
```
|
||||
|
||||
`API_KEY=<api_key for Text generation>`
|
||||
You can omit the keys if users provide their own. Ensure you set `LLM_NAME` and `EMBEDDINGS_NAME`.
|
||||
|
||||
`EMBEDDINGS_NAME=<llm for embeddings>`
|
||||
## Step 2: Choose Your Models
|
||||
|
||||
`EMBEDDINGS_KEY=<api_key for embeddings>`
|
||||
**Options for `LLM_NAME`:**
|
||||
- openai ([More details](https://platform.openai.com/docs/models))
|
||||
- anthropic ([More details](https://docs.anthropic.com/claude/reference/selecting-a-model))
|
||||
- manifest ([More details](https://python.langchain.com/docs/integrations/llms/manifest))
|
||||
- cohere ([More details](https://docs.cohere.com/docs/llmu))
|
||||
- llama.cpp ([More details](https://python.langchain.com/docs/integrations/llms/llamacpp))
|
||||
- huggingface (Arc53/DocsGPT-7B by default)
|
||||
- sagemaker ([Mode details](https://aws.amazon.com/sagemaker/))
|
||||
|
||||
`VITE_API_STREAMING=<true or false (true if using openai, false for all others)>`
|
||||
|
||||
You don't need to provide keys if you are happy with users providing theirs, so make sure you set `LLM_NAME` and `EMBEDDINGS_NAME`.
|
||||
Note: for huggingface you can choose any model inside application/llm/huggingface.py or pass llm_name on init, loads
|
||||
|
||||
Options:
|
||||
LLM_NAME (openai, manifest, cohere, Arc53/docsgpt-14b, Arc53/docsgpt-7b-falcon, llama.cpp)
|
||||
EMBEDDINGS_NAME (openai_text-embedding-ada-002, huggingface_sentence-transformers/all-mpnet-base-v2, huggingface_hkunlp/instructor-large, cohere_medium)
|
||||
**Options for `EMBEDDINGS_NAME`:**
|
||||
- openai_text-embedding-ada-002
|
||||
- huggingface_sentence-transformers/all-mpnet-base-v2
|
||||
- huggingface_hkunlp/instructor-large
|
||||
- cohere_medium
|
||||
|
||||
If using Llama, set the `EMBEDDINGS_NAME` to `huggingface_sentence-transformers/all-mpnet-base-v2` and be sure to download [this model](https://d3dg1063dc54p9.cloudfront.net/models/docsgpt-7b-f16.gguf) into the `models/` folder: `https://d3dg1063dc54p9.cloudfront.net/models/docsgpt-7b-f16.gguf`.
|
||||
If you want to be completely local, set `EMBEDDINGS_NAME` to `huggingface_sentence-transformers/all-mpnet-base-v2`.
|
||||
|
||||
Alternatively, if you wish to run Llama locally, you can run `setup.sh` and choose option 1 when prompted. You do not need to manually add the DocsGPT model mentioned above to your `models/` folder if you use `setup.sh`, as the script will manage that step for you.
|
||||
For llama.cpp Download the required model and place it in the `models/` folder.
|
||||
|
||||
That's it!
|
||||
Alternatively, for local Llama setup, run `setup.sh` and choose option 1. The script handles the DocsGPT model addition.
|
||||
|
||||
### Hosting everything locally and privately (for using our optimised open-source models)
|
||||
If you are working with important data and don't want anything to leave your premises.
|
||||
## Step 3: Local Hosting for Privacy
|
||||
|
||||
Make sure you set `SELF_HOSTED_MODEL` as true in your `.env` variable and for your `LLM_NAME` you can use anything that's on Hugging Face.
|
||||
If working with sensitive data, host everything locally by setting `LLM_NAME`, llama.cpp or huggingface, use any model available on Hugging Face, for llama.cpp you need to convert it into gguf format.
|
||||
That's it! Your app is now configured for local and private hosting, ensuring optimal security for critical data.
|
||||
|
||||
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|
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@ -0,0 +1,3 @@
|
||||
/// <reference types="react" />
|
||||
declare function App(): JSX.Element;
|
||||
export default App;
|
||||
@ -0,0 +1 @@
|
||||
export { DocsGPTWidget } from "./DocsGPTWidget";
|
||||
@ -1 +0,0 @@
|
||||
/// <reference types="vite/client" />
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,7 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" width="33" height="33" viewBox="0 0 33 33" fill="none">
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<path d="M8.25 13.75V11C8.25 6.44875 9.625 2.75 16.5 2.75C23.375 2.75 24.75 6.44875 24.75 11V13.75" stroke="#ECECF1" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
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<path d="M23.375 30.25H9.625C4.125 30.25 2.75 28.875 2.75 23.375V20.625C2.75 15.125 4.125 13.75 9.625 13.75H23.375C28.875 13.75 30.25 15.125 30.25 20.625V23.375C30.25 28.875 28.875 30.25 23.375 30.25Z" stroke="#ECECF1" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
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<path d="M16.4938 22H16.5061" stroke="#ECECF1" stroke-width="3" stroke-linecap="round" stroke-linejoin="round"/>
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<path d="M10.9924 22H11.0048" stroke="#ECECF1" stroke-width="3" stroke-linecap="round" stroke-linejoin="round"/>
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</svg>
|
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<svg xmlns="http://www.w3.org/2000/svg" width="36" height="36" viewBox="0 0 36 36" fill="none">
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<path d="M12.75 28.4551H12C6 28.4551 3 26.9551 3 19.4551V11.9551C3 5.95508 6 2.95508 12 2.95508H24C30 2.95508 33 5.95508 33 11.9551V19.4551C33 25.4551 30 28.4551 24 28.4551H23.25C22.785 28.4551 22.335 28.6801 22.05 29.0551L19.8 32.0551C18.81 33.3751 17.19 33.3751 16.2 32.0551L13.95 29.0551C13.71 28.7251 13.17 28.4551 12.75 28.4551Z" stroke="#ECECF1" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
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<path d="M12 13.05L9 16.05L12 19.05" stroke="#ECECF1" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
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<path d="M24 13.05L27 16.05L24 19.05" stroke="#ECECF1" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
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<path d="M19.5 12.5549L16.5 19.545" stroke="#ECECF1" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
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</svg>
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<svg width="36" height="36" viewBox="0 0 36 36" fill="none" xmlns="http://www.w3.org/2000/svg">
|
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<path d="M12.75 28.455H12C6 28.455 3 26.955 3 19.455V11.955C3 5.95496 6 2.95496 12 2.95496H24C30 2.95496 33 5.95496 33 11.955V19.455C33 25.455 30 28.455 24 28.455H23.25C22.785 28.455 22.335 28.68 22.05 29.055L19.8 32.055C18.81 33.375 17.19 33.375 16.2 32.055L13.95 29.055C13.71 28.725 13.17 28.455 12.75 28.455Z" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path d="M12 13.05L9 16.05L12 19.05" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path d="M24 13.05L27 16.05L24 19.05" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path d="M19.5 12.5549L16.5 19.545" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<g id="vuesax/linear/message-programming">
|
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<g id="message-programming">
|
||||
<path id="Vector" d="M12.75 28.455H12C6 28.455 3 26.955 3 19.455V11.955C3 5.95496 6 2.95496 12 2.95496H24C30 2.95496 33 5.95496 33 11.955V19.455C33 25.455 30 28.455 24 28.455H23.25C22.785 28.455 22.335 28.68 22.05 29.055L19.8 32.055C18.81 33.375 17.19 33.375 16.2 32.055L13.95 29.055C13.71 28.725 13.17 28.455 12.75 28.455Z" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path id="Vector_2" d="M12 13.05L9 16.05L12 19.05" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path id="Vector_3" d="M24 13.05L27 16.05L24 19.05" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path id="Vector_4" d="M19.5 12.555L16.5 19.545" stroke="#3E3434" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
</g>
|
||||
</g>
|
||||
</svg>
|
||||
|
||||
|
Before Width: | Height: | Size: 951 B After Width: | Height: | Size: 1.1 KiB |
@ -0,0 +1,5 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" width="29" height="29" viewBox="0 0 29 29" fill="none">
|
||||
<path d="M10.2708 22.9584H9.66663C4.83329 22.9584 2.41663 21.7501 2.41663 15.7084V9.66675C2.41663 4.83341 4.83329 2.41675 9.66663 2.41675H19.3333C24.1666 2.41675 26.5833 4.83341 26.5833 9.66675V15.7084C26.5833 20.5417 24.1666 22.9584 19.3333 22.9584H18.7291C18.3545 22.9584 17.992 23.1397 17.7625 23.4417L15.95 25.8584C15.1525 26.9217 13.8475 26.9217 13.05 25.8584L11.2375 23.4417C11.0441 23.1759 10.597 22.9584 10.2708 22.9584Z" stroke="#ECECF1" stroke-width="2" stroke-miterlimit="10" stroke-linecap="round" stroke-linejoin="round"/>
|
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<path d="M8.45837 9.66675H20.5417" stroke="#ECECF1" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path d="M8.45837 15.7083H15.7084" stroke="#ECECF1" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 880 B |
@ -1,18 +0,0 @@
|
||||
export default function Avatar({
|
||||
avatar,
|
||||
size,
|
||||
className,
|
||||
}: {
|
||||
avatar: string;
|
||||
size?: 'SMALL' | 'MEDIUM' | 'LARGE';
|
||||
className: string;
|
||||
}) {
|
||||
const styles = {
|
||||
transform: 'scale(-1, 1)',
|
||||
};
|
||||
return (
|
||||
<div style={styles} className={className}>
|
||||
{avatar}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@ -0,0 +1,15 @@
|
||||
import { Link } from 'react-router-dom';
|
||||
|
||||
export default function PageNotFound() {
|
||||
return (
|
||||
<div className="mx-5 grid min-h-screen md:mx-36">
|
||||
<p className="mx-auto my-auto mt-20 flex w-full max-w-6xl flex-col place-items-center gap-6 rounded-3xl bg-gray-100 p-6 text-jet lg:p-10 xl:p-16">
|
||||
<h1>404</h1>
|
||||
<p>The page you are looking for does not exist.</p>
|
||||
<button className="pointer-cursor mr-4 flex cursor-pointer items-center justify-center rounded-full bg-blue-1000 py-2 px-4 text-white hover:bg-blue-3000">
|
||||
<Link to="/">Go Back Home</Link>
|
||||
</button>
|
||||
</p>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@ -0,0 +1,822 @@
|
||||
import React, { useState, useEffect } from 'react';
|
||||
import { useSelector, useDispatch } from 'react-redux';
|
||||
import Arrow2 from './assets/dropdown-arrow.svg';
|
||||
import ArrowLeft from './assets/arrow-left.svg';
|
||||
import ArrowRight from './assets/arrow-right.svg';
|
||||
import Trash from './assets/trash.svg';
|
||||
import {
|
||||
selectPrompt,
|
||||
setPrompt,
|
||||
selectSourceDocs,
|
||||
} from './preferences/preferenceSlice';
|
||||
import { Doc } from './preferences/preferenceApi';
|
||||
import { useDarkTheme } from './hooks';
|
||||
import { Light } from 'react-syntax-highlighter';
|
||||
type PromptProps = {
|
||||
prompts: { name: string; id: string; type: string }[];
|
||||
selectedPrompt: { name: string; id: string; type: string };
|
||||
onSelectPrompt: (name: string, id: string, type: string) => void;
|
||||
setPrompts: (prompts: { name: string; id: string; type: string }[]) => void;
|
||||
apiHost: string;
|
||||
};
|
||||
|
||||
const Setting: React.FC = () => {
|
||||
const tabs = ['General', 'Prompts', 'Documents'];
|
||||
//const tabs = ['General', 'Prompts', 'Documents', 'Widgets'];
|
||||
|
||||
const [activeTab, setActiveTab] = useState('General');
|
||||
const [prompts, setPrompts] = useState<
|
||||
{ name: string; id: string; type: string }[]
|
||||
>([]);
|
||||
const selectedPrompt = useSelector(selectPrompt);
|
||||
const [isAddPromptModalOpen, setAddPromptModalOpen] = useState(false);
|
||||
const documents = useSelector(selectSourceDocs);
|
||||
const [isAddDocumentModalOpen, setAddDocumentModalOpen] = useState(false);
|
||||
|
||||
const dispatch = useDispatch();
|
||||
|
||||
const apiHost = import.meta.env.VITE_API_HOST || 'https://docsapi.arc53.com';
|
||||
const [widgetScreenshot, setWidgetScreenshot] = useState<File | null>(null);
|
||||
|
||||
const updateWidgetScreenshot = (screenshot: File | null) => {
|
||||
setWidgetScreenshot(screenshot);
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
const fetchPrompts = async () => {
|
||||
try {
|
||||
const response = await fetch(`${apiHost}/api/get_prompts`);
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to fetch prompts');
|
||||
}
|
||||
const promptsData = await response.json();
|
||||
setPrompts(promptsData);
|
||||
} catch (error) {
|
||||
console.error(error);
|
||||
}
|
||||
};
|
||||
|
||||
fetchPrompts();
|
||||
}, []);
|
||||
|
||||
const onDeletePrompt = (name: string, id: string) => {
|
||||
setPrompts(prompts.filter((prompt) => prompt.id !== id));
|
||||
|
||||
fetch(`${apiHost}/api/delete_prompt`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
// send id in body only
|
||||
body: JSON.stringify({ id: id }),
|
||||
})
|
||||
.then((response) => {
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to delete prompt');
|
||||
}
|
||||
})
|
||||
.catch((error) => {
|
||||
console.error(error);
|
||||
});
|
||||
};
|
||||
|
||||
const handleDeleteClick = (index: number, doc: Doc) => {
|
||||
const docPath = 'indexes/' + 'local' + '/' + doc.name;
|
||||
|
||||
fetch(`${apiHost}/api/delete_old?path=${docPath}`, {
|
||||
method: 'GET',
|
||||
})
|
||||
.then(() => {
|
||||
// remove the image element from the DOM
|
||||
const imageElement = document.querySelector(
|
||||
`#img-${index}`,
|
||||
) as HTMLElement;
|
||||
const parentElement = imageElement.parentNode as HTMLElement;
|
||||
parentElement.parentNode?.removeChild(parentElement);
|
||||
})
|
||||
.catch((error) => console.error(error));
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="p-4 pt-20 md:p-12 wa">
|
||||
<p className="text-2xl font-bold text-eerie-black dark:text-bright-gray">Settings</p>
|
||||
<div className="mt-6 flex flex-row items-center space-x-4 overflow-x-auto md:space-x-8 ">
|
||||
<div className="md:hidden">
|
||||
<button
|
||||
onClick={() => scrollTabs(-1)}
|
||||
className="flex h-8 w-8 items-center justify-center rounded-full border-2 border-purple-30 transition-all hover:bg-gray-100"
|
||||
>
|
||||
<img src={ArrowLeft} alt="left-arrow" className="h-6 w-6" />
|
||||
</button>
|
||||
</div>
|
||||
<div className="flex flex-nowrap space-x-4 overflow-x-auto md:space-x-8">
|
||||
{tabs.map((tab, index) => (
|
||||
<button
|
||||
key={index}
|
||||
onClick={() => setActiveTab(tab)}
|
||||
className={`h-9 rounded-3xl px-4 font-bold ${activeTab === tab
|
||||
? 'bg-purple-3000 text-purple-30 dark:bg-dark-charcoal'
|
||||
: 'text-gray-6000'
|
||||
}`}
|
||||
>
|
||||
{tab}
|
||||
</button>
|
||||
))}
|
||||
</div>
|
||||
<div className="md:hidden">
|
||||
<button
|
||||
onClick={() => scrollTabs(1)}
|
||||
className="flex h-8 w-8 items-center justify-center rounded-full border-2 border-purple-30 hover:bg-gray-100"
|
||||
>
|
||||
<img src={ArrowRight} alt="right-arrow" className="h-6 w-6" />
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
{renderActiveTab()}
|
||||
|
||||
{/* {activeTab === 'Widgets' && (
|
||||
<Widgets
|
||||
widgetScreenshot={widgetScreenshot}
|
||||
onWidgetScreenshotChange={updateWidgetScreenshot}
|
||||
/>
|
||||
)} */}
|
||||
</div>
|
||||
);
|
||||
|
||||
function scrollTabs(direction: number) {
|
||||
const container = document.querySelector('.flex-nowrap');
|
||||
if (container) {
|
||||
container.scrollLeft += direction * 100; // Adjust the scroll amount as needed
|
||||
}
|
||||
}
|
||||
|
||||
function renderActiveTab() {
|
||||
switch (activeTab) {
|
||||
case 'General':
|
||||
return <General />;
|
||||
case 'Prompts':
|
||||
return (
|
||||
<Prompts
|
||||
prompts={prompts}
|
||||
selectedPrompt={selectedPrompt}
|
||||
onSelectPrompt={(name, id, type) =>
|
||||
dispatch(setPrompt({ name: name, id: id, type: type }))
|
||||
}
|
||||
setPrompts={setPrompts}
|
||||
apiHost={apiHost}
|
||||
/>
|
||||
);
|
||||
case 'Documents':
|
||||
return (
|
||||
<Documents
|
||||
documents={documents}
|
||||
handleDeleteDocument={handleDeleteClick}
|
||||
/>
|
||||
);
|
||||
case 'Widgets':
|
||||
return (
|
||||
<Widgets
|
||||
widgetScreenshot={widgetScreenshot} // Add this line
|
||||
onWidgetScreenshotChange={updateWidgetScreenshot} // Add this line
|
||||
/>
|
||||
);
|
||||
default:
|
||||
return null;
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const General: React.FC = () => {
|
||||
const themes = ['Light', 'Dark'];
|
||||
const languages = ['English'];
|
||||
const [isDarkTheme, toggleTheme] = useDarkTheme();
|
||||
const [selectedTheme, setSelectedTheme] = useState(isDarkTheme ? 'Dark' : 'Light');
|
||||
const [selectedLanguage, setSelectedLanguage] = useState(languages[0]);
|
||||
return (
|
||||
<div className="mt-[59px]">
|
||||
<div className="mb-4">
|
||||
<p className="font-bold text-jet dark:text-bright-gray">Select Theme</p>
|
||||
<Dropdown
|
||||
options={themes}
|
||||
selectedValue={selectedTheme}
|
||||
onSelect={(option:string)=>{
|
||||
setSelectedTheme(option);
|
||||
option !==selectedTheme && toggleTheme();
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
<div>
|
||||
<p className="font-bold text-jet dark:text-bright-gray">Select Language</p>
|
||||
<Dropdown
|
||||
options={languages}
|
||||
selectedValue={selectedLanguage}
|
||||
onSelect={setSelectedLanguage}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default Setting;
|
||||
|
||||
const Prompts: React.FC<PromptProps> = ({
|
||||
prompts,
|
||||
selectedPrompt,
|
||||
onSelectPrompt,
|
||||
setPrompts,
|
||||
apiHost,
|
||||
}) => {
|
||||
const handleSelectPrompt = ({
|
||||
name,
|
||||
id,
|
||||
type,
|
||||
}: {
|
||||
name: string;
|
||||
id: string;
|
||||
type: string;
|
||||
}) => {
|
||||
setNewPromptName(name);
|
||||
onSelectPrompt(name, id, type);
|
||||
};
|
||||
const [newPromptName, setNewPromptName] = useState(selectedPrompt.name);
|
||||
const [newPromptContent, setNewPromptContent] = useState('');
|
||||
|
||||
const handleAddPrompt = async () => {
|
||||
try {
|
||||
const response = await fetch(`${apiHost}/api/create_prompt`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
name: newPromptName,
|
||||
content: newPromptContent,
|
||||
}),
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to add prompt');
|
||||
}
|
||||
const newPrompt = await response.json();
|
||||
if (setPrompts) {
|
||||
setPrompts([
|
||||
...prompts,
|
||||
{ name: newPromptName, id: newPrompt.id, type: 'private' },
|
||||
]);
|
||||
}
|
||||
onSelectPrompt(newPromptName, newPrompt.id, newPromptContent);
|
||||
setNewPromptName(newPromptName);
|
||||
} catch (error) {
|
||||
console.error(error);
|
||||
}
|
||||
};
|
||||
|
||||
const handleDeletePrompt = () => {
|
||||
setPrompts(prompts.filter((prompt) => prompt.id !== selectedPrompt.id));
|
||||
console.log('selectedPrompt.id', selectedPrompt.id);
|
||||
|
||||
fetch(`${apiHost}/api/delete_prompt`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({ id: selectedPrompt.id }),
|
||||
})
|
||||
.then((response) => {
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to delete prompt');
|
||||
}
|
||||
// get 1st prompt and set it as selected
|
||||
if (prompts.length > 0) {
|
||||
onSelectPrompt(prompts[0].name, prompts[0].id, prompts[0].type);
|
||||
setNewPromptName(prompts[0].name);
|
||||
}
|
||||
})
|
||||
.catch((error) => {
|
||||
console.error(error);
|
||||
});
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
const fetchPromptContent = async () => {
|
||||
console.log('fetching prompt content');
|
||||
try {
|
||||
const response = await fetch(
|
||||
`${apiHost}/api/get_single_prompt?id=${selectedPrompt.id}`,
|
||||
{
|
||||
method: 'GET',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
},
|
||||
);
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to fetch prompt content');
|
||||
}
|
||||
const promptContent = await response.json();
|
||||
setNewPromptContent(promptContent.content);
|
||||
} catch (error) {
|
||||
console.error(error);
|
||||
}
|
||||
};
|
||||
|
||||
fetchPromptContent();
|
||||
}, [selectedPrompt]);
|
||||
|
||||
const handleSaveChanges = () => {
|
||||
fetch(`${apiHost}/api/update_prompt`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
id: selectedPrompt.id,
|
||||
name: newPromptName,
|
||||
content: newPromptContent,
|
||||
}),
|
||||
})
|
||||
.then((response) => {
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to update prompt');
|
||||
}
|
||||
onSelectPrompt(newPromptName, selectedPrompt.id, selectedPrompt.type);
|
||||
setNewPromptName(newPromptName);
|
||||
})
|
||||
.catch((error) => {
|
||||
console.error(error);
|
||||
});
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="mt-[59px]">
|
||||
<div className="mb-4">
|
||||
<p className="font-semibold dark:text-bright-gray">Active Prompt</p>
|
||||
<DropdownPrompt
|
||||
options={prompts}
|
||||
selectedValue={selectedPrompt.name}
|
||||
onSelect={handleSelectPrompt}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="mb-4">
|
||||
<p className='dark:text-bright-gray'>Prompt name </p>{' '}
|
||||
<p className="mb-2 text-xs italic text-eerie-black dark:text-bright-gray">
|
||||
start by editing name
|
||||
</p>
|
||||
<input
|
||||
type="text"
|
||||
value={newPromptName}
|
||||
placeholder="Active Prompt Name"
|
||||
className="w-full rounded-lg border-2 p-2 dark:border-chinese-silver dark:bg-transparent dark:text-white"
|
||||
onChange={(e) => setNewPromptName(e.target.value)}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="mb-4">
|
||||
<p className="mb-2 dark:text-bright-gray">Prompt content</p>
|
||||
<textarea
|
||||
className="h-32 w-full rounded-lg border-2 p-2 dark:border-chinese-silver dark:text-white dark:bg-transparent"
|
||||
value={newPromptContent}
|
||||
onChange={(e) => setNewPromptContent(e.target.value)}
|
||||
placeholder="Active prompt contents"
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="flex justify-between">
|
||||
<button
|
||||
className={`rounded-lg bg-green-500 px-4 py-2 font-bold text-white transition-all hover:bg-green-700 ${newPromptName === selectedPrompt.name
|
||||
? 'cursor-not-allowed opacity-50'
|
||||
: ''
|
||||
}`}
|
||||
onClick={handleAddPrompt}
|
||||
disabled={newPromptName === selectedPrompt.name}
|
||||
>
|
||||
Add New Prompt
|
||||
</button>
|
||||
<button
|
||||
className={`rounded-lg bg-red-500 px-4 py-2 font-bold text-white transition-all hover:bg-red-700 ${selectedPrompt.type === 'public'
|
||||
? 'cursor-not-allowed opacity-50'
|
||||
: ''
|
||||
}`}
|
||||
onClick={handleDeletePrompt}
|
||||
disabled={selectedPrompt.type === 'public'}
|
||||
>
|
||||
Delete Prompt
|
||||
</button>
|
||||
<button
|
||||
className={`rounded-lg bg-blue-500 px-4 py-2 font-bold text-white transition-all hover:bg-blue-700 ${selectedPrompt.type === 'public'
|
||||
? 'cursor-not-allowed opacity-50'
|
||||
: ''
|
||||
}`}
|
||||
onClick={handleSaveChanges}
|
||||
disabled={selectedPrompt.type === 'public'}
|
||||
>
|
||||
Save Changes
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
function DropdownPrompt({
|
||||
options,
|
||||
selectedValue,
|
||||
onSelect,
|
||||
}: {
|
||||
options: { name: string; id: string; type: string }[];
|
||||
selectedValue: string;
|
||||
onSelect: (value: { name: string; id: string; type: string }) => void;
|
||||
}) {
|
||||
const [isOpen, setIsOpen] = useState(false);
|
||||
|
||||
return (
|
||||
<div className="relative mt-2 w-32">
|
||||
<button
|
||||
onClick={() => setIsOpen(!isOpen)}
|
||||
className="flex w-full cursor-pointer items-center rounded-xl border-2 dark:border-chinese-silver bg-white p-3 dark:bg-transparent"
|
||||
>
|
||||
<span className="flex-1 overflow-hidden text-ellipsis dark:text-bright-gray">
|
||||
{selectedValue}
|
||||
</span>
|
||||
<img
|
||||
src={Arrow2}
|
||||
alt="arrow"
|
||||
className={`transform ${isOpen ? 'rotate-180' : 'rotate-0'
|
||||
} h-3 w-3 transition-transform`}
|
||||
/>
|
||||
</button>
|
||||
{isOpen && (
|
||||
<div className="absolute left-0 right-0 z-50 -mt-3 rounded-b-xl border-2 dark:border-chinese-silver bg-white dark:bg-dark-charcoal shadow-lg">
|
||||
{options.map((option, index) => (
|
||||
<div
|
||||
key={index}
|
||||
className="flex cursor-pointer items-center justify-between hover:bg-gray-100 dark:hover:bg-purple-taupe dark:text-bright-gray "
|
||||
>
|
||||
<span
|
||||
onClick={() => {
|
||||
onSelect(option);
|
||||
setIsOpen(false);
|
||||
}}
|
||||
className="ml-2 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3"
|
||||
>
|
||||
{option.name}
|
||||
</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
function Dropdown({
|
||||
options,
|
||||
selectedValue,
|
||||
onSelect,
|
||||
showDelete,
|
||||
onDelete,
|
||||
}: {
|
||||
options: string[];
|
||||
selectedValue: string;
|
||||
onSelect: (value: string) => void;
|
||||
showDelete?: boolean; // optional
|
||||
onDelete?: (value: string) => void; // optional
|
||||
}) {
|
||||
const [isOpen, setIsOpen] = useState(false);
|
||||
|
||||
return (
|
||||
<div className="relative mt-2 w-32">
|
||||
<button
|
||||
onClick={() => setIsOpen(!isOpen)}
|
||||
className="flex w-full cursor-pointer items-center rounded-xl border-2 dark:border-chinese-silver bg-white p-3 dark:bg-transparent"
|
||||
>
|
||||
<span className="flex-1 overflow-hidden text-ellipsis dark:text-bright-gray">
|
||||
{selectedValue}
|
||||
</span>
|
||||
<img
|
||||
src={Arrow2}
|
||||
alt="arrow"
|
||||
className={`transform ${isOpen ? 'rotate-180' : 'rotate-0'
|
||||
} h-3 w-3 transition-transform`}
|
||||
/>
|
||||
</button>
|
||||
{isOpen && (
|
||||
<div className="absolute left-0 right-0 z-50 -mt-3 rounded-b-xl border-2 bg-white dark:border-chinese-silver dark:bg-dark-charcoal shadow-lg">
|
||||
{options.map((option, index) => (
|
||||
<div
|
||||
key={index}
|
||||
className="flex cursor-pointer items-center justify-between hover:bg-gray-100 dark:hover:bg-purple-taupe"
|
||||
>
|
||||
<span
|
||||
onClick={() => {
|
||||
onSelect(option);
|
||||
setIsOpen(false);
|
||||
}}
|
||||
className="ml-2 flex-1 overflow-hidden overflow-ellipsis whitespace-nowrap py-3 dark:text-light-gray"
|
||||
>
|
||||
{option}
|
||||
</span>
|
||||
{showDelete && onDelete && (
|
||||
<button onClick={() => onDelete(option)} className="p-2">
|
||||
{/* Icon or text for delete button */}
|
||||
Delete
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
type AddPromptModalProps = {
|
||||
newPromptName: string;
|
||||
onNewPromptNameChange: (name: string) => void;
|
||||
onAddPrompt: () => void;
|
||||
onClose: () => void;
|
||||
};
|
||||
|
||||
const AddPromptModal: React.FC<AddPromptModalProps> = ({
|
||||
newPromptName,
|
||||
onNewPromptNameChange,
|
||||
onAddPrompt,
|
||||
onClose,
|
||||
}) => {
|
||||
return (
|
||||
<div className="fixed top-0 left-0 flex h-screen w-screen items-center justify-center bg-gray-900 bg-opacity-50">
|
||||
<div className="rounded-3xl bg-white p-4">
|
||||
<p className="mb-2 text-2xl font-bold text-jet">Add New Prompt</p>
|
||||
<input
|
||||
type="text"
|
||||
placeholder="Enter Prompt Name"
|
||||
value={newPromptName}
|
||||
onChange={(e) => onNewPromptNameChange(e.target.value)}
|
||||
className="mb-4 w-full rounded-3xl border-2 dark:border-chinese-silver p-2"
|
||||
/>
|
||||
<button
|
||||
onClick={onAddPrompt}
|
||||
className="rounded-3xl bg-purple-300 px-4 py-2 font-bold text-white transition-all hover:bg-purple-600"
|
||||
>
|
||||
Save
|
||||
</button>
|
||||
<button
|
||||
onClick={onClose}
|
||||
className="mt-4 rounded-3xl px-4 py-2 font-bold text-red-500"
|
||||
>
|
||||
Cancel
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
type DocumentsProps = {
|
||||
documents: Doc[] | null;
|
||||
handleDeleteDocument: (index: number, document: Doc) => void;
|
||||
};
|
||||
|
||||
const Documents: React.FC<DocumentsProps> = ({
|
||||
documents,
|
||||
handleDeleteDocument,
|
||||
}) => {
|
||||
return (
|
||||
<div className="mt-8">
|
||||
<div className="flex flex-col">
|
||||
{/* <h2 className="text-xl font-semibold">Documents</h2> */}
|
||||
|
||||
<div className="mt-[27px] overflow-x-auto border dark:border-chinese-silver rounded-xl w-max">
|
||||
<table className="block w-full table-auto content-center justify-center text-center dark:text-bright-gray" >
|
||||
<thead>
|
||||
<tr>
|
||||
<th className="border-r p-4 md:w-[244px]">Document Name</th>
|
||||
<th className="border-r px-4 py-2 w-[244px]">Vector Date</th>
|
||||
<th className="border-r px-4 py-2 w-[244px]">Type</th>
|
||||
<th className="px-4 py-2"></th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{documents &&
|
||||
documents.map((document, index) => (
|
||||
<tr key={index}>
|
||||
<td className="border-r border-t px-4 py-2">{document.name}</td>
|
||||
<td className="border-r border-t px-4 py-2">{document.date}</td>
|
||||
<td className="border-r border-t px-4 py-2">
|
||||
{document.location === 'remote'
|
||||
? 'Pre-loaded'
|
||||
: 'Private'}
|
||||
</td>
|
||||
<td className="border-t px-4 py-2">
|
||||
{document.location !== 'remote' && (
|
||||
<img
|
||||
src={Trash}
|
||||
alt="Delete"
|
||||
className="h-4 w-4 cursor-pointer hover:opacity-50"
|
||||
id={`img-${index}`}
|
||||
onClick={(event) => {
|
||||
event.stopPropagation();
|
||||
handleDeleteDocument(index, document);
|
||||
}}
|
||||
/>
|
||||
)}
|
||||
</td>
|
||||
</tr>
|
||||
))}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
{/* <button
|
||||
onClick={toggleAddDocumentModal}
|
||||
className="mt-10 w-32 rounded-lg bg-purple-300 px-4 py-2 font-bold text-white transition-all hover:bg-purple-600"
|
||||
>
|
||||
Add New
|
||||
</button> */}
|
||||
</div>
|
||||
|
||||
{/* {isAddDocumentModalOpen && (
|
||||
<AddDocumentModal
|
||||
newDocument={newDocument}
|
||||
onNewDocumentChange={setNewDocument}
|
||||
onAddDocument={addDocument}
|
||||
onClose={toggleAddDocumentModal}
|
||||
/>
|
||||
)} */}
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
type Document = {
|
||||
name: string;
|
||||
vectorDate: string;
|
||||
vectorLocation: string;
|
||||
};
|
||||
|
||||
// Modal for adding a new document
|
||||
type AddDocumentModalProps = {
|
||||
newDocument: Document;
|
||||
onNewDocumentChange: (document: Document) => void;
|
||||
onAddDocument: () => void;
|
||||
onClose: () => void;
|
||||
};
|
||||
|
||||
const AddDocumentModal: React.FC<AddDocumentModalProps> = ({
|
||||
newDocument,
|
||||
onNewDocumentChange,
|
||||
onAddDocument,
|
||||
onClose,
|
||||
}) => {
|
||||
return (
|
||||
<div className="fixed top-0 left-0 flex h-screen w-screen items-center justify-center bg-gray-900 bg-opacity-50">
|
||||
<div className="w-[50%] rounded-lg bg-white p-4">
|
||||
<p className="mb-2 text-2xl font-bold text-jet">Add New Document</p>
|
||||
<input
|
||||
type="text"
|
||||
placeholder="Document Name"
|
||||
value={newDocument.name}
|
||||
onChange={(e) =>
|
||||
onNewDocumentChange({ ...newDocument, name: e.target.value })
|
||||
}
|
||||
className="mb-4 w-full rounded-lg border-2 p-2"
|
||||
/>
|
||||
<input
|
||||
type="text"
|
||||
placeholder="Vector Date"
|
||||
value={newDocument.vectorDate}
|
||||
onChange={(e) =>
|
||||
onNewDocumentChange({ ...newDocument, vectorDate: e.target.value })
|
||||
}
|
||||
className="mb-4 w-full rounded-lg border-2 p-2"
|
||||
/>
|
||||
<input
|
||||
type="text"
|
||||
placeholder="Vector Location"
|
||||
value={newDocument.vectorLocation}
|
||||
onChange={(e) =>
|
||||
onNewDocumentChange({
|
||||
...newDocument,
|
||||
vectorLocation: e.target.value,
|
||||
})
|
||||
}
|
||||
className="mb-4 w-full rounded-lg border-2 p-2"
|
||||
/>
|
||||
<button
|
||||
onClick={onAddDocument}
|
||||
className="rounded-lg bg-purple-300 px-4 py-2 font-bold text-white transition-all hover:bg-purple-600"
|
||||
>
|
||||
Save
|
||||
</button>
|
||||
<button
|
||||
onClick={onClose}
|
||||
className="mt-4 rounded-lg px-4 py-2 font-bold text-red-500"
|
||||
>
|
||||
Cancel
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
const Widgets: React.FC<{
|
||||
widgetScreenshot: File | null;
|
||||
onWidgetScreenshotChange: (screenshot: File | null) => void;
|
||||
}> = ({ widgetScreenshot, onWidgetScreenshotChange }) => {
|
||||
const widgetSources = ['Source 1', 'Source 2', 'Source 3'];
|
||||
const widgetMethods = ['Method 1', 'Method 2', 'Method 3'];
|
||||
const widgetTypes = ['Type 1', 'Type 2', 'Type 3'];
|
||||
|
||||
const [selectedWidgetSource, setSelectedWidgetSource] = useState(
|
||||
widgetSources[0],
|
||||
);
|
||||
const [selectedWidgetMethod, setSelectedWidgetMethod] = useState(
|
||||
widgetMethods[0],
|
||||
);
|
||||
const [selectedWidgetType, setSelectedWidgetType] = useState(widgetTypes[0]);
|
||||
|
||||
// const [widgetScreenshot, setWidgetScreenshot] = useState<File | null>(null);
|
||||
const [widgetCode, setWidgetCode] = useState<string>(''); // Your widget code state
|
||||
|
||||
const handleScreenshotChange = (
|
||||
event: React.ChangeEvent<HTMLInputElement>,
|
||||
) => {
|
||||
const files = event.target.files;
|
||||
|
||||
if (files && files.length > 0) {
|
||||
const selectedScreenshot = files[0];
|
||||
onWidgetScreenshotChange(selectedScreenshot); // Update the screenshot in the parent component
|
||||
}
|
||||
};
|
||||
|
||||
const handleCopyToClipboard = () => {
|
||||
// Create a new textarea element to select the text
|
||||
const textArea = document.createElement('textarea');
|
||||
textArea.value = widgetCode;
|
||||
document.body.appendChild(textArea);
|
||||
|
||||
// Select and copy the text
|
||||
textArea.select();
|
||||
document.execCommand('copy');
|
||||
|
||||
// Clean up the textarea element
|
||||
document.body.removeChild(textArea);
|
||||
};
|
||||
|
||||
return (
|
||||
<div>
|
||||
<div className="mt-[59px]">
|
||||
<p className="font-bold text-jet">Widget Source</p>
|
||||
<Dropdown
|
||||
options={widgetSources}
|
||||
selectedValue={selectedWidgetSource}
|
||||
onSelect={setSelectedWidgetSource}
|
||||
/>
|
||||
</div>
|
||||
<div className="mt-5">
|
||||
<p className="font-bold text-jet">Widget Method</p>
|
||||
<Dropdown
|
||||
options={widgetMethods}
|
||||
selectedValue={selectedWidgetMethod}
|
||||
onSelect={setSelectedWidgetMethod}
|
||||
/>
|
||||
</div>
|
||||
<div className="mt-5">
|
||||
<p className="font-bold text-jet">Widget Type</p>
|
||||
<Dropdown
|
||||
options={widgetTypes}
|
||||
selectedValue={selectedWidgetType}
|
||||
onSelect={setSelectedWidgetType}
|
||||
/>
|
||||
</div>
|
||||
<div className="mt-6">
|
||||
<p className="font-bold text-jet">Widget Code Snippet</p>
|
||||
<textarea
|
||||
rows={4}
|
||||
value={widgetCode}
|
||||
onChange={(e) => setWidgetCode(e.target.value)}
|
||||
className="mt-3 w-full rounded-lg border-2 p-2"
|
||||
/>
|
||||
</div>
|
||||
<div className="mt-1">
|
||||
<button
|
||||
onClick={handleCopyToClipboard}
|
||||
className="rounded-lg bg-blue-400 px-2 py-2 font-bold text-white transition-all hover:bg-blue-600"
|
||||
>
|
||||
Copy
|
||||
</button>
|
||||
</div>
|
||||
|
||||
<div className="mt-4">
|
||||
<p className="text-lg font-semibold">Widget Screenshot</p>
|
||||
<input type="file" accept="image/*" onChange={handleScreenshotChange} />
|
||||
</div>
|
||||
|
||||
{widgetScreenshot && (
|
||||
<div className="mt-4">
|
||||
<img
|
||||
src={URL.createObjectURL(widgetScreenshot)}
|
||||
alt="Widget Screenshot"
|
||||
className="max-w-full rounded-lg border border-gray-300"
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
};
|
||||
@ -0,0 +1,10 @@
|
||||
<svg width="17" height="17" viewBox="0 0 17 17" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<g clip-path="url(#clip0_2494_3464)">
|
||||
<path d="M7.43717 14.1667C7.43717 14.4485 7.54912 14.7187 7.74837 14.918C7.94763 15.1172 8.21788 15.2292 8.49967 15.2292C8.78147 15.2292 9.05172 15.1172 9.25098 14.918C9.45023 14.7187 9.56217 14.4485 9.56217 14.1667V9.56249H14.1663C14.4481 9.56249 14.7184 9.45055 14.9176 9.2513C15.1169 9.05204 15.2288 8.78179 15.2288 8.49999C15.2288 8.2182 15.1169 7.94795 14.9176 7.74869C14.7184 7.54944 14.4481 7.43749 14.1663 7.43749H9.56217V2.83333C9.56217 2.55154 9.45023 2.28128 9.25098 2.08203C9.05172 1.88277 8.78147 1.77083 8.49967 1.77083C8.21788 1.77083 7.94763 1.88277 7.74837 2.08203C7.54912 2.28128 7.43717 2.55154 7.43717 2.83333V7.43749H2.83301C2.55122 7.43749 2.28096 7.54944 2.08171 7.74869C1.88245 7.94795 1.77051 8.2182 1.77051 8.49999C1.77051 8.78179 1.88245 9.05204 2.08171 9.2513C2.28096 9.45055 2.55122 9.56249 2.83301 9.56249H7.43717V14.1667Z" fill="#5D5D5D" />
|
||||
</g>
|
||||
<defs>
|
||||
<clipPath id="clip0_2494_3464">
|
||||
<rect width="17" height="17" fill="white"/>
|
||||
</clipPath>
|
||||
</defs>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 1.1 KiB |
@ -0,0 +1,3 @@
|
||||
<svg width="13" height="23" viewBox="0 0 13 23" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<path d="M12.3183 20.8523C12.4198 20.9597 12.4991 21.0861 12.5518 21.2242C12.6044 21.3622 12.6294 21.5093 12.6252 21.657C12.621 21.8047 12.5878 21.9502 12.5274 22.0851C12.467 22.2199 12.3807 22.3416 12.2733 22.4431C12.1659 22.5446 12.0395 22.6239 11.9014 22.6766C11.7634 22.7293 11.6163 22.7542 11.4686 22.75C11.3208 22.7459 11.1754 22.7126 11.0405 22.6522C10.9057 22.5919 10.784 22.5055 10.6825 22.3981L1.12001 12.2731C0.922533 12.0642 0.812501 11.7877 0.812501 11.5002C0.812501 11.2128 0.922533 10.9362 1.12001 10.7273L10.6825 0.601207C10.7833 0.49145 10.905 0.40282 11.0403 0.340468C11.1757 0.278115 11.3221 0.243281 11.4711 0.23799C11.62 0.232697 11.7685 0.257054 11.908 0.309644C12.0474 0.362231 12.175 0.442004 12.2834 0.544328C12.3917 0.646653 12.4787 0.769488 12.5392 0.9057C12.5997 1.04191 12.6325 1.18878 12.6357 1.33779C12.639 1.48679 12.6126 1.63495 12.5581 1.77367C12.5036 1.91238 12.4221 2.03889 12.3183 2.14583L3.48476 11.5002L12.3183 20.8523Z" fill="#7D54D1"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 1.1 KiB |
@ -0,0 +1,3 @@
|
||||
<svg width="13" height="23" viewBox="0 0 13 23" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<path d="M0.681741 20.8523C0.580245 20.9597 0.500899 21.0861 0.448232 21.2242C0.395564 21.3622 0.370607 21.5093 0.374785 21.657C0.378964 21.8047 0.412197 21.9502 0.472586 22.0851C0.532974 22.2199 0.619336 22.3416 0.726741 22.4431C0.834146 22.5446 0.96049 22.6239 1.09856 22.6766C1.23663 22.7293 1.38372 22.7542 1.53144 22.75C1.67915 22.7459 1.8246 22.7126 1.95947 22.6522C2.09434 22.5919 2.216 22.5055 2.31749 22.3981L11.88 12.2731C12.0775 12.0642 12.1875 11.7877 12.1875 11.5002C12.1875 11.2128 12.0775 10.9362 11.88 10.7273L2.31749 0.601207C2.21666 0.49145 2.09503 0.40282 1.95967 0.340468C1.8243 0.278115 1.67789 0.243281 1.52895 0.23799C1.38 0.232697 1.23149 0.257054 1.09204 0.309644C0.95259 0.362231 0.824978 0.442004 0.716618 0.544328C0.608256 0.646653 0.521307 0.769488 0.46082 0.9057C0.400333 1.04191 0.367515 1.18878 0.364269 1.33779C0.361025 1.48679 0.387418 1.63495 0.441917 1.77367C0.496417 1.91238 0.577936 2.03889 0.681739 2.14583L9.51524 11.5002L0.681741 20.8523Z" fill="#7D54D1"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 1.1 KiB |
|
Before Width: | Height: | Size: 1.0 KiB After Width: | Height: | Size: 1.0 KiB |
@ -1,3 +1 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" width="14" height="11" viewBox="0 0 14 11" fill="none">
|
||||
<path d="M4.95919 10.1906C4.84318 10.1902 4.72847 10.166 4.62222 10.1194C4.51596 10.0729 4.42041 10.0049 4.34152 9.91985L0.229353 5.54538C0.0756344 5.38157 -0.00671208 5.1634 0.000428491 4.93886C0.00756906 4.71433 0.103612 4.50183 0.267428 4.34812C0.431245 4.1944 0.649417 4.11205 0.873948 4.11919C1.09848 4.12633 1.31098 4.22238 1.4647 4.38619L4.95073 8.10068L12.0666 0.316329C12.1389 0.226405 12.2287 0.152193 12.3306 0.0982513C12.4326 0.0443098 12.5445 0.0117775 12.6594 0.00265255C12.7744 -0.00647237 12.89 0.00800286 12.9992 0.045189C13.1084 0.082375 13.2088 0.141487 13.2943 0.218894C13.3798 0.296301 13.4485 0.390369 13.4964 0.49532C13.5442 0.600272 13.57 0.713891 13.5723 0.829198C13.5746 0.944506 13.5534 1.05907 13.5098 1.16585C13.4662 1.27263 13.4012 1.36937 13.3189 1.45014L5.58533 9.91139C5.50718 9.998 5.41197 10.0675 5.30567 10.1156C5.19938 10.1636 5.0843 10.1892 4.96766 10.1906H4.95919Z" fill="#747474"/>
|
||||
</svg>
|
||||
<svg width="16px" height="16px" viewBox="0 0 1024 1024" class="icon" version="1.1" xmlns="http://www.w3.org/2000/svg" fill="#11ee1c" stroke="#11ee1c" stroke-width="83.96799999999999"><g id="SVGRepo_bgCarrier" stroke-width="0"></g><g id="SVGRepo_tracerCarrier" stroke-linecap="round" stroke-linejoin="round"></g><g id="SVGRepo_iconCarrier"><path d="M866.133333 258.133333L362.666667 761.6l-204.8-204.8L98.133333 618.666667 362.666667 881.066667l563.2-563.2z" fill="#11ee1c"></path></g></svg>
|
||||
|
Before Width: | Height: | Size: 1.0 KiB After Width: | Height: | Size: 490 B |
@ -1,3 +1,3 @@
|
||||
<svg width="14" height="17" stroke-width="1.15" viewBox="0 0 14 17" >
|
||||
<svg width="13" height="16" stroke-width="1.15" viewBox="0 0 14 17" >
|
||||
<path d="M13.8013 5.01282L8.80645 0.191795C8.67953 0.0691399 8.50734 0.000152609 8.32774 0H6.09677C5.43801 0 4.80623 0.252586 4.34041 0.702193C3.8746 1.1518 3.6129 1.7616 3.6129 2.39744V3.48718H2.48387C1.82511 3.48718 1.19332 3.73977 0.727509 4.18937C0.261693 4.63898 0 5.24878 0 5.88462V14.6026C0 15.2384 0.261693 15.8482 0.727509 16.2978C1.19332 16.7474 1.82511 17 2.48387 17H8.80645C9.46521 17 10.097 16.7474 10.5628 16.2978C11.0286 15.8482 11.2903 15.2384 11.2903 14.6026V13.5128H11.5161C12.1749 13.5128 12.8067 13.2602 13.2725 12.8106C13.7383 12.361 14 11.7512 14 11.1154V5.44872C13.9929 5.28447 13.9219 5.12884 13.8013 5.01282ZM9.03226 2.23179L11.6877 4.79487H9.03226V2.23179ZM9.93548 14.6026C9.93548 14.8916 9.81653 15.1688 9.6048 15.3731C9.39306 15.5775 9.10589 15.6923 8.80645 15.6923H2.48387C2.18443 15.6923 1.89726 15.5775 1.68552 15.3731C1.47379 15.1688 1.35484 14.8916 1.35484 14.6026V5.88462C1.35484 5.5956 1.47379 5.31842 1.68552 5.11405C1.89726 4.90968 2.18443 4.79487 2.48387 4.79487H3.6129V11.1154C3.6129 11.7512 3.8746 12.361 4.34041 12.8106C4.80623 13.2602 5.43801 13.5128 6.09677 13.5128H9.93548V14.6026ZM11.5161 12.2051H6.09677C5.79734 12.2051 5.51016 12.0903 5.29843 11.886C5.08669 11.6816 4.96774 11.4044 4.96774 11.1154V2.39744C4.96774 2.10842 5.08669 1.83124 5.29843 1.62687C5.51016 1.4225 5.79734 1.30769 6.09677 1.30769H7.67742V5.44872C7.67976 5.62143 7.75188 5.78643 7.87842 5.90856C8.00496 6.03069 8.1759 6.10031 8.35484 6.10256H12.6452V11.1154C12.6452 11.4044 12.5262 11.6816 12.3145 11.886C12.1027 12.0903 11.8156 12.2051 11.5161 12.2051Z" fill="#949494"/>
|
||||
</svg>
|
||||
|
||||
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</svg>
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After Width: | Height: | Size: 192 B |
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Reference in New Issue