95 lines
2.8 KiB
Plaintext
95 lines
2.8 KiB
Plaintext
---
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title: '💬 chat'
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---
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`chat()` method allows you to chat over your data sources using a user-friendly chat API. You can find the signature below:
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### Parameters
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<ParamField path="input_query" type="str">
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Question to ask
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</ParamField>
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<ParamField path="config" type="BaseLlmConfig" optional>
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Configure different llm settings such as prompt, temprature, number_documents etc.
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</ParamField>
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<ParamField path="dry_run" type="bool" optional>
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The purpose is to test the prompt structure without actually running LLM inference. Defaults to `False`
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</ParamField>
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<ParamField path="where" type="dict" optional>
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A dictionary of key-value pairs to filter the chunks from the vector database. Defaults to `None`
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</ParamField>
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<ParamField path="citations" type="bool" optional>
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Return citations along with the LLM answer. Defaults to `False`
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</ParamField>
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### Returns
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<ResponseField name="answer" type="str | tuple">
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If `citations=False`, return a stringified answer to the question asked. <br />
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If `citations=True`, returns a tuple with answer and citations respectively.
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</ResponseField>
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## Usage
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### With citations
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If you want to get the answer to question and return both answer and citations, use the following code snippet:
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```python With Citations
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from embedchain import Pipeline as App
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# Initialize app
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app = App()
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# Add data source
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app.add("https://www.forbes.com/profile/elon-musk")
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# Get relevant answer for your query
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answer, sources = app.chat("What is the net worth of Elon?", citations=True)
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print(answer)
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# Answer: The net worth of Elon Musk is $221.9 billion.
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print(sources)
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# [
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# (
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# 'Elon Musk PROFILEElon MuskCEO, Tesla$247.1B$2.3B (0.96%)Real Time Net Worthas of 12/7/23 ...',
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# {'url': 'https://www.forbes.com/profile/elon-musk', ...}
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# ),
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# (
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# '74% of the company, which is now called X.Wealth HistoryHOVER TO REVEAL NET WORTH BY YEARForbes ...',
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# {'url': 'https://www.forbes.com/profile/elon-musk', ...}
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# ),
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# (
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# 'founded in 2002, is worth nearly $150 billion after a $750 million tender offer in June 2023 ...',
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# {'url': 'https://www.forbes.com/profile/elon-musk', ...}
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# )
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# ]
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```
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<Note>
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When `citations=True`, note that the returned `sources` are a list of tuples where each tuple has three elements (in the following order):
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1. source chunk
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2. link of the source document
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3. document id (used for book keeping purposes)
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</Note>
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### Without citations
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If you just want to return answers and don't want to return citations, you can use the following example:
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```python Without Citations
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from embedchain import Pipeline as App
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# Initialize app
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app = App()
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# Add data source
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app.add("https://www.forbes.com/profile/elon-musk")
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# Chat on your data using `.chat()`
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answer = app.chat("What is the net worth of Elon?")
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print(answer)
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# Answer: The net worth of Elon Musk is $221.9 billion.
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```
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