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Integrate Tools and LLMs (Claude Opus 4.1)

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Robotics & Biotech Research Navigator Agent

Format
Code-aware
Lines
11
Sections
4
Linked challenge
Robotics & Biotech Research Navigator Agent

Prompt source

Original prompt text with formatting preserved for inspection.

11 lines
4 sections
No variables
1 code block
Enhance your `researcher` node to actually use `SerpAPI` for web searches. Modify `analyst` and `synthesizer` nodes to invoke `Claude Opus 4.1` for their respective tasks, ensuring structured prompts for analysis and report generation. Use `ChromaDB` as a temporary storage or lookup for retrieved documents. Configure your LangChain LLM instances with your Claude API key.

```python
from langchain_community.tools import SerpAPIWrapper
from langchain_anthropic import ChatAnthropic
from langchain_community.vectorstores import Chroma
from langchain_community.embeddings import HuggingFaceEmbeddings # Example for Chroma

# Initialize LLM and tools
llm = ChatAnthropic(model='claude-3-opus-20240229', temperature=0.7) # Ensure correct model name
search_tool = SerpAPIWrapper(serpapi_api_key='YOUR_SERPAPI_KEY')

# ... (modify researcher_node, analyst_node, synthesizer_node to use these) ...
```

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.