mirror of
https://github.com/hwchase17/langchain.git
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0d6f915442
fix: Fix LLM mimicking Unicode responses due to forced Unicode
conversion of non-ASCII characters.
- **Description:** This PR fixes an issue where the LLM would mimic
Unicode responses due to forced Unicode conversion of non-ASCII
characters in tool calls. The fix involves disabling the `ensure_ascii`
flag in `json.dumps()` when converting tool calls to OpenAI format.
- **Issue:** Fixes ↓↓↓
input：
```json
{'role': 'assistant', 'tool_calls': [{'type': 'function', 'id': 'call_nv9trcehdpihr21zj9po19vq', 'function': {'name': 'create_customer', 'arguments': '{"customer_name": "你好啊集团"}'}}]}
```
output:
```json
{'role': 'assistant', 'tool_calls': [{'type': 'function', 'id': 'call_nv9trcehdpihr21zj9po19vq', 'function': {'name': 'create_customer', 'arguments': '{"customer_name": "\\u4f60\\u597d\\u554a\\u96c6\\u56e2"}'}}]}
```
then:
llm will mimic outputting unicode. Unicode's vast number of symbols can
lengthen LLM responses, leading to slower performance.
<img width="686" height="277" alt="image"
src="https://github.com/user-attachments/assets/28f3b007-3964-4455-bee2-68f86ac1906d"
/>
---------
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
106 lines
2.8 KiB
Markdown
106 lines
2.8 KiB
Markdown
# langchain-exa
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This package contains the LangChain integrations for Exa Cloud generative models.
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## Installation
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```bash
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pip install -U langchain-exa
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```
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## Exa Search Retriever
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You can retrieve search results as follows
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```python
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from langchain_exa import ExaSearchRetriever
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exa_api_key = "YOUR API KEY"
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# Create a new instance of the ExaSearchRetriever
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exa = ExaSearchRetriever(exa_api_key=exa_api_key)
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# Search for a query and save the results
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results = exa.invoke("What is the capital of France?")
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# Print the results
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print(results)
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```
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### Advanced Features
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You can use advanced features like text limits, summaries, and live crawling:
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```python
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from langchain_exa import ExaSearchRetriever, TextContentsOptions
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# Create a new instance with advanced options
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exa = ExaSearchRetriever(
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exa_api_key="YOUR API KEY",
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k=20, # Number of results (1-100)
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type="auto", # Can be "neural", "keyword", or "auto"
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livecrawl="always", # Can be "always", "fallback", or "never"
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summary=True, # Get an AI-generated summary of each result
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text_contents_options={"max_characters": 3000} # Limit text length
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)
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# Search for a query with custom summary prompt
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exa_with_custom_summary = ExaSearchRetriever(
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exa_api_key="YOUR API KEY",
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summary={"query": "generate one line summary in simple words."} # Custom summary prompt
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)
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```
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## Exa Search Results
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You can run the ExaSearchResults module as follows
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```python
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from langchain_exa import ExaSearchResults
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# Initialize the ExaSearchResults tool
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search_tool = ExaSearchResults(exa_api_key="YOUR API KEY")
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# Perform a search query
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search_results = search_tool._run(
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query="When was the last time the New York Knicks won the NBA Championship?",
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num_results=5,
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text_contents_options=True,
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highlights=True
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)
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print("Search Results:", search_results)
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```
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## Exa Find Similar Results
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You can run the ExaFindSimilarResults module as follows
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```python
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from langchain_exa import ExaFindSimilarResults
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# Initialize the ExaFindSimilarResults tool
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find_similar_tool = ExaFindSimilarResults(exa_api_key="YOUR API KEY")
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# Find similar results based on a URL
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similar_results = find_similar_tool._run(
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url="http://espn.com",
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num_results=5,
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text_contents_options=True,
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highlights=True
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)
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print("Similar Results:", similar_results)
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```
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## Configuration Options
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All Exa tools support the following common parameters:
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- `num_results` (1-100): Number of search results to return
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- `type`: Search type - "neural", "keyword", or "auto"
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- `livecrawl`: Live crawling mode - "always", "fallback", or "never"
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- `summary`: Get AI-generated summaries (True/False or custom prompt dict)
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- `text_contents_options`: Dict to limit text length (e.g. `{"max_characters": 2000}`)
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- `highlights`: Include highlighted text snippets (True/False)
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