Upload 17 files

src/agent.py

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+# src/agent.py
+from langchain.agents import create_react_agent, AgentExecutor
+from src.config import groq_llm
+from src.tools.python_tool import python_tool
+from langchain.hub import pull
+from src.tools.serper_search import serper_search_tool
+from src.tools.file_loader import file_loader_tool
+
+
+llm   = groq_llm(model="llama3-70b-8192")
+tools = [python_tool, serper_search_tool, file_loader_tool]
+prompt = pull("hwchase17/react")
+
+agent = create_react_agent(llm=llm, tools=tools, prompt=prompt)
+
+agent_executor = AgentExecutor(
+    agent=agent,
+    tools=tools,
+    verbose=True,
+    handle_parsing_errors=True,   # retry if the model slips
+)
+
+if __name__ == "__main__":
+    print(agent_executor.invoke({
+    "input": "Load this tiny sample CSV and show me the first rows: "
+             "https://people.sc.fsu.edu/~jburkardt/data/csv/hw_200.csv"
+        }))

src/config.py

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+"""
+Central place to load env vars and expose shared singletons.
+"""
+
+from functools import lru_cache
+from pathlib import Path
+
+from dotenv import load_dotenv
+from langchain_groq import ChatGroq
+
+# Load .env once when the module is imported
+load_dotenv(dotenv_path=Path(__file__).resolve().parents[1] / ".env")
+
+@lru_cache
+def groq_llm(model: str = "llama3-70b-8192", temperature: float = 0.0):
+    """Return a memoized Groq chat model instance."""
+    return ChatGroq(model_name=model, temperature=temperature)

src/temp_test.py

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+from src.config import groq_llm
+print(groq_llm().invoke("Ping!"))

src/tools/file_loader.py

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+import io, os, mimetypes, requests, pandas as pd
+from langchain.tools import StructuredTool
+
+def _load_dataset(url_or_path: str, head_only: bool = True) -> str:
+    """Fetch a CSV/JSON file (local or remote) and return either
+    the first ~5 rows or basic stats."""
+    # Grab bytes
+    if url_or_path.startswith(("http://", "https://")):
+        resp = requests.get(url_or_path, timeout=10)
+        resp.raise_for_status()
+        raw = io.BytesIO(resp.content)
+    else:  # local
+        raw = open(os.path.expanduser(url_or_path), "rb")
+
+    # Detect type
+    mime = mimetypes.guess_type(url_or_path)[0] or ""
+    if "json" in mime or url_or_path.lower().endswith(".json"):
+        df = pd.read_json(raw)
+    elif "csv" in mime or url_or_path.lower().endswith(".csv"):
+        df = pd.read_csv(raw)
+    else:
+        raise ValueError("Only CSV or JSON supported.")
+
+    if head_only:
+        return df.head().to_markdown(index=False)
+    return df.describe(include="all").to_markdown()
+
+file_loader_tool = StructuredTool.from_function(
+    name="load_dataset",
+    description=(
+        "Load a CSV or JSON file from a URL or local path. "
+        "Returns a markdown preview of the data."
+    ),
+    func=_load_dataset,
+    return_direct=True,    # skip extra narration
+)

src/tools/news_search.py

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+# from langchain_newsapi import NewsAPISearchRun
+# import os
+
+# news_search_tool = NewsAPISearchRun(
+#     name="news_api_search",
+#     description=(
+#         "Search recent news articles for up-to-date facts. "
+#         "Returns headline, source and short snippet."
+#     ),
+#     news_api_key=os.getenv("NEWSAPI_KEY"),
+# )

src/tools/python_tool.py

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+from langchain_experimental.tools.python.tool import PythonREPLTool
+
+python_tool = PythonREPLTool(
+    description="Executes Python code and returns the result."
+)

src/tools/serper_search.py

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+from langchain_community.utilities import GoogleSerperAPIWrapper
+from langchain.agents import Tool
+
+import os
+
+search_tool = GoogleSerperAPIWrapper(
+    serper_api_key=os.getenv("SERPER_API_KEY"),   # add this to your .env
+    k=3                                          # top-5 results
+)
+
+serper_search_tool = Tool(
+    name="Google Search",
+    func=search_tool.run,
+    description="Useful for answering questions by searching the web."
+)

src/tools/web_search.py

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+from langchain_community.tools.ddg_search import DuckDuckGoSearchRun
+
+# Simple, no-API-key web search
+web_search_tool = DuckDuckGoSearchRun(
+    name="duckduckgo_search",
+    description="Search the web for recent information and return the top snippets."
+)