feat: create agent to pass gaia tests with 30p level 1 + integration langfuse

.env.template

@@ -0,0 +1,49 @@
+# ============================================
+# 1. Model choices/config
+# ============================================
+
+### MAIN MODEL AGENT ###
+PROVIDER=google
+# Available models: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions
+MODEL=gemini-2.5-flash
+TEMPERATURE=0
+
+### VISION MODEL ###
+# Available models: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions
+GOOGLE_VISION_MODEL=gemini-2.5-flash
+
+# ============================================
+# 2. LLM Provider API Keys
+# ============================================
+
+OPENAI_API_KEY=<your_openai_token>
+GOOGLE_API_KEY=<your_google_genai_api_key>
+GROQ_API_KEY=<your_groq_api_key>
+HUGGINGFACEHUB_API_TOKEN=<your_huggingface_token>
+HF_TOKEN=<your_huggingface_token>   # some clients use this instead of HUGGINGFACEHUB_API_TOKEN
+OLLAMA_HOST=http://localhost:11434  # default, change if custom host/port
+
+# ============================================
+# 3. Observability (OTEL, costs, tokens...)
+# ============================================
+
+# LangFuse (if you want to use it)
+# Note: You need to run at least Python 3.11 (GitHub Issue).
+
+LANGFUSE_PUBLIC_KEY=<your-langfuse-public-key>
+LANGFUSE_SECRET_KEY=<your-langfuse-secret-key>
+# 🇪🇺 EU region
+LANGFUSE_HOST=https://cloud.langfuse.com
+
+# LangChain / LangSmith (or if you prefer)
+
+# LANGSMITH_TRACING=true
+# LANGSMITH_ENDPOINT=https://api.smith.langchain.com
+# LANGCHAIN_API_KEY=<your_langsmith_key>
+# LANGCHAIN_PROJECT=<your_project_name>
+
+# ============================================
+# 4. Audio transcoding (mp3 local or distant)
+# ============================================
+
+ASSEMBLYAI_API_KEY=<your_assemblyai_api_key>

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.xls filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,5 @@
+__pycache__
+.env
+myanswers.logs
+.venv
+downloads

.python-version

@@ -0,0 +1 @@
+3.10

.vscode/launch.json

@@ -0,0 +1,15 @@
+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "Python Debugger: Current File",
+            "type": "debugpy",
+            "request": "launch",
+            "program": "app.py",
+            "console": "integratedTerminal"
+        }
+    ]
+}

.vscode/tasks.json

@@ -0,0 +1,19 @@
+{
+  "version": "2.0.0",
+  "tasks": [
+    {
+      "label": "uv: run active file",
+      "type": "shell",
+      "command": "uv",
+      "args": ["run", "${fileBasename}"],
+      "options": {
+        "cwd": "${fileDirname}"
+      },
+      "problemMatcher": [],
+      "group": {
+        "kind": "build",
+        "isDefault": true
+      }
+    }
+  ]
+}   

README.md

@@ -1,5 +1,5 @@
 ---
-title: Template Final Assignment
+title: Final Assignment Agents Course LangGraph
 emoji: 🕵🏻‍♂️
 colorFrom: indigo
 colorTo: indigo
@@ -8,8 +8,24 @@ sdk_version: 5.25.2
 app_file: app.py
 pinned: false
 hf_oauth: true
-# optional, default duration is 8 hours/480 minutes. Max duration is 30 days/43200 minutes.
 hf_oauth_expiration_minutes: 480
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# 1. Getting started wit uv
+
+## 1.1. Download Python into uv’s local cache (~/.uv/)
+uv python install 3.10
+
+## 1.2. Pin this project to use Python 3.10 (writes a config file in the repo)
+uv python pin 3.10
+
+## 1.3. Sync all dependencies from pyproject.toml (installs into .venv by default)
+uv sync
+
+## 1.4. Run your app with the pinned interpreter + venv
+uv run python app.py --reload
+
+## 1.5. (Optional) Generate requirements.txt for Hugging Face Spaces
+uv export --format=requirements-txt > requirements.txt

agent.py

@@ -0,0 +1,245 @@
+import os
+
+from typing import Literal, TypedDict, Annotated, Optional, Any
+from dotenv import load_dotenv
+from langchain_core.messages import HumanMessage, SystemMessage, AnyMessage
+from langchain_ollama import ChatOllama
+from langgraph.graph.message import add_messages
+from langgraph.graph import START, END, StateGraph
+from langgraph.prebuilt import ToolNode, tools_condition
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_openai import ChatOpenAI
+from langchain_groq import ChatGroq
+from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
+from tools import build_tools
+from langchain_core.runnables.graph import CurveStyle, MermaidDrawMethod, NodeStyles
+from langfuse.langchain import CallbackHandler
+
+load_dotenv()
+# Initialize Langfuse CallbackHandler for Langchain (tracing)
+langfuse_handler = CallbackHandler()
+
+
+class AwesomeAgent:
+    def __init__(self):
+        self.all_tools = build_tools()
+        self.react_graph = build_langgraph(
+            os.getenv("PROVIDER"),
+            model=os.getenv("MODEL"),
+            temperature=float(os.getenv("TEMPERATURE")),
+            all_tools=self.all_tools,
+        )
+
+        # Sauvegarder dans un fichier PNG
+        self.react_graph.get_graph().draw_mermaid_png(
+            output_file_path="graph.png",
+            curve_style=CurveStyle.LINEAR,
+            node_colors=NodeStyles(first="#ffdfba", last="#baffc9", default="#fad7de"),
+            wrap_label_n_words=9,
+            draw_method=MermaidDrawMethod.API,
+            background_color="white",
+            padding=10,
+        )
+
+        print("Graph saved to graph.png")
+
+        print("AwesomeAgent initialized.")
+
+    def __call__(self, question: str, input_file: str) -> str:
+        print(f"Agent received question: {question}")
+        if input_file:
+            print(f"A file is associated with it: {input_file}")
+
+        messages = [HumanMessage(content=question)]
+
+        fixed_answer = "Default answer"
+        try:
+            result = self.react_graph.invoke(
+                {"messages": messages, "input_file": input_file}
+            )
+            fixed_answer = result["messages"][-1].content
+        except Exception as e:
+            print(f"Error running agent on question: {e}")
+
+        print(f"Agent returning fixed answer: {fixed_answer}")
+        return fixed_answer
+
+
+class AgentState(TypedDict):
+    input_file: Optional[str]  # Contains file path (PDF/PNG/...)
+    # We want to remember about the history so we use add_messages operator
+    messages: Annotated[list[AnyMessage], add_messages]
+
+
+### How tools are integrated here
+# User → Assistant (LLM+tools) → ToolNode (executes) → Assistant → (loop if more tools) → Answer
+# llm.bind_tools(all_tools) lets the LLM know which tools exist so it can output structured tool_calls (function calling).
+# ToolNode(all_tools) actually executes those tool calls and returns their results as messages.
+# tools_condition routes between the assistant and the tools, closing the loop between “planning” and “acting.”
+
+
+def build_langgraph(
+    provider: str,
+    model: Optional[str] = None,
+    temperature: float = 0.1,
+    all_tools: Optional[list[Any]] = None,
+) -> StateGraph:
+    """Builds and returns the LangGraph agent with the given provider."""
+
+    if all_tools is None:
+        all_tools = []
+
+    # Select model and provider for the chat
+    if provider == "google":
+        llm = ChatGoogleGenerativeAI(
+            model=model or "gemini-2.5-flash", temperature=temperature
+        )
+    elif provider == "openai":
+        llm = ChatOpenAI(model=model or "gpt-4o", temperature=temperature)
+    elif provider == "groq":
+        llm = ChatGroq(model=model or "qwen/qwen3-32b", temperature=temperature)
+    elif provider == "huggingface":
+        llm = ChatHuggingFace(
+            llm=HuggingFaceEndpoint(
+                repo_id=model or "meta-llama/Llama-3.1-8B-Instruct",
+                temperature=temperature,
+            )
+        )
+    elif provider == "ollama":
+        llm = ChatOllama(
+            model=model or "gpt-oss:20b",
+            base_url="http://localhost:11434",
+            temperature=temperature,
+        )
+    else:
+        raise ValueError(
+            "Unsupported provider. Choose from 'openai', 'google', 'groq', 'huggingface', or 'ollama'."
+        )
+
+    llm_with_tools = llm.bind_tools(all_tools)
+    llm_without_tools = llm
+
+    def assistant(state: AgentState):
+        tools_description = """
+WEB & SEARCH:
+- duckduckgo_search: Search the web
+- wikipedia_tool: Search Wikipedia for knowledge
+- visit_webpage: Visit a webpage and extract readable markdown content
+- arxiv_tool: Search arXiv for research papers
+
+CALCULATIONS:
+- calculator: Basic arithmetic (+, -, *, /)
+- advanced_math: Advanced math functions (sqrt, log, trig)
+- python_repl: Execute Python code for complex computations (use carefully)
+
+TEXT PROCESSING:
+- reverse_text: Reverse text character by character
+- reverse_words: Reverse word order in text
+
+IMAGE PROCESSING:
+- ask_question_on_image_content: Ask any question on the image content
+
+MUSIC PROCESSING:
+- transcribe_mp3: Transcribe an MP3 (local path or URL) and return the result
+
+DATA ANALYSIS:
+- read_excel_file: Read Excel file content for content analysis
+
+SYSTEM:
+- shell_tool: Execute shell commands (use carefully)
+"""
+
+        file = state["input_file"]
+        sys_msg = SystemMessage(
+            content=f"""
+You are a LLM agent. You will be given a question.
+Your task it to answer the question using the tools you have access to.
+take time to analyse the steps to answer the question.
+
+# Input File
+Loaded file: {file}
+
+# Available Tools
+{tools_description}
+"""
+        )
+
+        return {
+            "messages": [llm_with_tools.invoke([sys_msg] + state["messages"])],
+            "input_file": state["input_file"],
+        }
+
+    def format(state: AgentState):
+        sys_msg = SystemMessage(
+            content=f"""
+                You are an Answer Summarizer AI assistant.
+
+                Here is the question: {state.get(state["messages"][0].content)}
+
+                Summarize the answer with the following rules:
+                - YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. 
+                - If the question asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. Write numbers using digits.
+                - If the question asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. 
+                - If the question asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
+
+                Here is the content to format:
+            """
+        )
+
+        response = llm_without_tools.invoke(
+            [
+                sys_msg,
+                HumanMessage(
+                    content=state["messages"][-1].content,
+                    config={"callbacks": [langfuse_handler]},
+                ),
+            ]
+        )
+
+        return {
+            # "messages": [llm_with_tools.invoke([sys_msg, state["messages"][-1]])],
+            "messages": [response],
+            "input_file": state["input_file"],
+        }
+
+    def to_format_or_tools(state) -> Literal["tools", "format"]:
+        out = tools_condition(state)
+        return "format" if out == "__end__" else out
+
+    # Build the graph
+    builder = StateGraph(AgentState)
+    builder.add_node("assistant", assistant)
+    builder.add_node("tools", ToolNode(all_tools))
+    builder.add_node("format", format)
+    builder.add_edge(START, "assistant")
+    builder.add_conditional_edges("assistant", to_format_or_tools)
+    builder.add_edge("tools", "assistant")
+    builder.add_edge("format", END)
+    return builder.compile()
+
+
+if __name__ == "__main__":
+    all_tools = build_tools()
+    react_graph = build_langgraph("google", all_tools=all_tools)
+
+    messages = [
+        HumanMessage(content="Calculate the square root of 169, then multiply by 15")
+    ]
+    result = react_graph.invoke({"messages": messages, "input_file": None})
+
+    for m in result["messages"]:
+        m.pretty_print()
+
+    # Example: Knowledge retrieval
+    print("📚 Testing Wikipedia search...")
+    messages = [
+        HumanMessage(
+            content="Who nominated the only Featured Article on English Wikipedia about a dinosaur that was promoted in November 2016?"
+        )
+    ]
+    result = react_graph.invoke({"messages": messages, "input_file": None})
+
+    for m in result["messages"]:
+        m.pretty_print()
+
+    print("\n" + "=" * 60 + "\n")

app.py

@@ -1,34 +1,63 @@
 import os
+
 import gradio as gr
-import requests
-import inspect
 import pandas as pd
+import requests
+from dotenv import load_dotenv
+from langfuse import get_client
+
+from agent import AwesomeAgent
+
+load_dotenv()
+
+langfuse = get_client()
+
+# Verify connection
+if langfuse.auth_check():
+    print("Langfuse client is authenticated and ready!")
+else:
+    print("Authentication failed. Please check your credentials and host.")
+
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-class BasicAgent:
-    def __init__(self):
-        print("BasicAgent initialized.")
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
-
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+
+def get_local_file(
+    api_url: str, task_id: str, file_name: str, folder: str = "downloads"
+) -> str | None:
+    if not file_name:
+        return None
+    os.makedirs(folder, exist_ok=True)
+    local_path = os.path.join(folder, file_name)
+    if os.path.exists(local_path):
+        return local_path
+    try:
+        url = f"{api_url}/file={file_name}"
+        r = requests.get(url, timeout=15)
+        r.raise_for_status()
+    except Exception:
+        url = f"{api_url}/files/{task_id}"
+        r = requests.get(url, timeout=15)
+        r.raise_for_status()
+    with open(local_path, "wb") as f:
+        f.write(r.content)
+    return local_path
+
+
+# Questions available here : https://agents-course-unit4-scoring.hf.space/questions
+# File available here : cca530fc-4052-43b2-b130-b30968d8aa44.png
+def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
+    space_id = os.getenv("SPACE_ID")  # Get the SPACE_ID for sending link to the code
 
     if profile:
-        username= f"{profile.username}"
+        username = f"{profile.username}"
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -40,7 +69,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = BasicAgent()
+        agent = AwesomeAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
@@ -55,16 +84,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         response.raise_for_status()
         questions_data = response.json()
         if not questions_data:
-             print("Fetched questions list is empty.")
-             return "Fetched questions list is empty or invalid format.", None
+            print("Fetched questions list is empty.")
+            return "Fetched questions list is empty or invalid format.", None
         print(f"Fetched {len(questions_data)} questions.")
     except requests.exceptions.RequestException as e:
         print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
     except requests.exceptions.JSONDecodeError as e:
-         print(f"Error decoding JSON response from questions endpoint: {e}")
-         print(f"Response text: {response.text[:500]}")
-         return f"Error decoding server response for questions: {e}", None
+        print(f"Error decoding JSON response from questions endpoint: {e}")
+        print(f"Response text: {response.text[:500]}")
+        return f"Error decoding server response for questions: {e}", None
     except Exception as e:
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
@@ -73,26 +102,66 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     results_log = []
     answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
+
+    ############################################################################################################
+    # TODO: REMOVE THIS PART - AVOID ASKING 50 QUESTIONS
+    # questions_data = questions_data[:5]  # the top 5
+    # questions_data = [questions_data[18]]  # the 19th question
+    keep = {2, 3, 7, 11, 12, 16}
+    questions_data[:] = [x for i, x in enumerate(questions_data, start=1) if i in keep]
+    ############################################################################################################
+
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
+        file_name = item.get("file_name")
+
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent(question_text)
-            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
-            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
+            input_file = get_local_file(api_url, task_id, file_name)
+            submitted_answer = agent(question_text, input_file)
+            answers_payload.append(
+                {"task_id": task_id, "submitted_answer": submitted_answer}
+            )
+            results_log.append(
+                {
+                    "Task ID": task_id,
+                    "Question": question_text,
+                    "Submitted Answer": submitted_answer,
+                }
+            )
         except Exception as e:
-             print(f"Error running agent on task {task_id}: {e}")
-             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
+            print(f"Error running agent on task {task_id}: {e}")
+            results_log.append(
+                {
+                    "Task ID": task_id,
+                    "Question": question_text,
+                    "Submitted Answer": f"AGENT ERROR: {e}",
+                }
+            )
 
     if not answers_payload:
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission 
-    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
+    # ############################################################################################################
+    # # TODO: REMOVE THIS PART - AVOID SUBMISSION
+    # results_df = pd.DataFrame(results_log)
+    # status = (
+    #     f"✅ Dry run complete: processed {len(answers_payload)} question(s). "
+    #     f"Submission skipped."
+    # )
+    # return status, results_df
+    # ############################################################################################################
+
+    # 4. Prepare Submission
+    submission_data = {
+        "username": username.strip(),
+        "agent_code": agent_code,
+        "answers": answers_payload,
+    }
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
 
@@ -142,19 +211,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
-    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown("# Awesome Agent Evaluation Runner")
     gr.Markdown(
         """
         **Instructions:**
 
-        1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
-        2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
-        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
+        1.  Log in to your Hugging Face account using the button below.
+        2.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, submit answers, and see the score.
 
-        ---
         **Disclaimers:**
-        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
-        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
+        Once clicking on the "submit button, it can take quite some time (this is the time for the agent to go through all the questions).
         """
     )
 
@@ -162,20 +228,19 @@ with gr.Blocks() as demo:
 
     run_button = gr.Button("Run Evaluation & Submit All Answers")
 
-    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
+    status_output = gr.Textbox(
+        label="Run Status / Submission Result", lines=5, interactive=False
+    )
     # Removed max_rows=10 from DataFrame constructor
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
-    run_button.click(
-        fn=run_and_submit_all,
-        outputs=[status_output, results_table]
-    )
+    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
+    print("\n" + "-" * 30 + " App Starting " + "-" * 30)
     # Check for SPACE_HOST and SPACE_ID at startup for information
     space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
+    space_id_startup = os.getenv("SPACE_ID")  # Get SPACE_ID at startup
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")
@@ -183,14 +248,18 @@ if __name__ == "__main__":
     else:
         print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
 
-    if space_id_startup: # Print repo URLs if SPACE_ID is found
+    if space_id_startup:  # Print repo URLs if SPACE_ID is found
         print(f"✅ SPACE_ID found: {space_id_startup}")
         print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
+        print(
+            f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main"
+        )
     else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
+        print(
+            "ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined."
+        )
 
-    print("-"*(60 + len(" App Starting ")) + "\n")
+    print("-" * (60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)

examples/file_example_XLS_10.xls

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:753e8d18b04ab7c476bdf43a237603ade93d8a985c39f0366cd5f889d15d2dc7
+size 8704

examples/sample.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:200f767e732b49efef5c05d128903ee4d2c34e66fdce7f5593ac123b2e637673
+size 280868

pyproject.toml

@@ -0,0 +1,40 @@
+[project]
+name = "final-assignment-agents-course"
+version = "0.1.0"
+description = "Final assignment Hugging Face agents course"
+readme = "README.md"
+requires-python = "==3.10.*"
+dependencies = [
+    "gradio",
+    "gradio[oauth]",
+    "requests",
+    "langgraph",
+    "langgraph-checkpoint",
+    "langgraph-prebuilt",
+    "langgraph-sdk",
+    "langsmith",
+    "python-dotenv>=1.1.1",
+    "wikipedia",
+    "langchain[openai]",
+    "langchain",
+    "langchain-community",
+    "langchain-core",
+    "langchain-experimental",
+    "langchain-google-genai",
+    "langchain-groq",
+    "langchain-huggingface",
+    "langchain-ollama",
+    "langchain-openai",
+    "langchain-text-splitters",
+    "pandas",
+    "markdownify",
+    "ddgs",
+    "duckduckgo-search",
+    "arxiv",
+    "youtube_transcript_api",
+    "beautifulsoup4",
+    "openpyxl",
+    "xlrd>=2.0.1",
+    "assemblyai",
+    "langfuse",
+]

requirements.txt

@@ -1,2 +1,1234 @@
-gradio
-requests
+# This file was autogenerated by uv via the following command:
+#    uv export --format=requirements-txt
+aiofiles==24.1.0 \
+    --hash=sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c \
+    --hash=sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5
+    # via gradio
+aiohappyeyeballs==2.6.1 \
+    --hash=sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558 \
+    --hash=sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8
+    # via aiohttp
+aiohttp==3.12.15 \
+    --hash=sha256:098e92835b8119b54c693f2f88a1dec690e20798ca5f5fe5f0520245253ee0af \
+    --hash=sha256:1004e67962efabbaf3f03b11b4c43b834081c9e3f9b32b16a7d97d4708a9abe6 \
+    --hash=sha256:2776c7ec89c54a47029940177e75c8c07c29c66f73464784971d6a81904ce9d1 \
+    --hash=sha256:2c7d81a277fa78b2203ab626ced1487420e8c11a8e373707ab72d189fcdad20a \
+    --hash=sha256:2ce13fcfb0bb2f259fb42106cdc63fa5515fb85b7e87177267d89a771a660b79 \
+    --hash=sha256:3beb14f053222b391bf9cf92ae82e0171067cc9c8f52453a0f1ec7c37df12a77 \
+    --hash=sha256:40b3fee496a47c3b4a39a731954c06f0bd9bd3e8258c059a4beb76ac23f8e421 \
+    --hash=sha256:4c39e87afe48aa3e814cac5f535bc6199180a53e38d3f51c5e2530f5aa4ec58c \
+    --hash=sha256:4fc61385e9c98d72fcdf47e6dd81833f47b2f77c114c29cd64a361be57a763a2 \
+    --hash=sha256:79b26fe467219add81d5e47b4a4ba0f2394e8b7c7c3198ed36609f9ba161aecb \
+    --hash=sha256:83603f881e11f0f710f8e2327817c82e79431ec976448839f3cd05d7afe8f830 \
+    --hash=sha256:8faa08fcc2e411f7ab91d1541d9d597d3a90e9004180edb2072238c085eac8c2 \
+    --hash=sha256:b6fc902bff74d9b1879ad55f5404153e2b33a82e72a95c89cec5eb6cc9e92fbc \
+    --hash=sha256:b761bac1192ef24e16706d761aefcb581438b34b13a2f069a6d343ec8fb693a5 \
+    --hash=sha256:d5f1b4ce5bc528a6ee38dbf5f39bbf11dd127048726323b72b8e85769319ffc4 \
+    --hash=sha256:e153e8adacfe2af562861b72f8bc47f8a5c08e010ac94eebbe33dc21d677cd5b \
+    --hash=sha256:fc49c4de44977aa8601a00edbf157e9a421f227aa7eb477d9e3df48343311065 \
+    --hash=sha256:fe086edf38b2222328cdf89af0dde2439ee173b8ad7cb659b4e4c6f385b2be3d
+    # via langchain-community
+aiosignal==1.4.0 \
+    --hash=sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e \
+    --hash=sha256:f47eecd9468083c2029cc99945502cb7708b082c232f9aca65da147157b251c7
+    # via aiohttp
+annotated-types==0.7.0 \
+    --hash=sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53 \
+    --hash=sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89
+    # via pydantic
+anyio==4.10.0 \
+    --hash=sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6 \
+    --hash=sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1
+    # via
+    #   gradio
+    #   groq
+    #   httpx
+    #   openai
+    #   starlette
+arxiv==2.2.0 \
+    --hash=sha256:545b8af5ab301efff7697cd112b5189e631b80521ccbc33fbc1e1f9cff63ca4d \
+    --hash=sha256:6072a2211e95697092ef32acde0144d7de2cfa71208e2751724316c9df322cc0
+    # via final-assignment-agents-course
+assemblyai==0.43.1 \
+    --hash=sha256:4e6e11eb07130c5c87aea84cc63d80933a6588e9b3aeee80026c2419756a3513 \
+    --hash=sha256:c39e8ddb4434af316ade3259e51f86be8134c24be821d8cd84502850ea551951
+    # via final-assignment-agents-course
+async-timeout==4.0.3 \
+    --hash=sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f \
+    --hash=sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028
+    # via
+    #   aiohttp
+    #   langchain
+attrs==25.3.0 \
+    --hash=sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3 \
+    --hash=sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b
+    # via aiohttp
+authlib==1.6.3 \
+    --hash=sha256:7ea0f082edd95a03b7b72edac65ec7f8f68d703017d7e37573aee4fc603f2a48 \
+    --hash=sha256:9f7a982cc395de719e4c2215c5707e7ea690ecf84f1ab126f28c053f4219e610
+    # via gradio
+backoff==2.2.1 \
+    --hash=sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba \
+    --hash=sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8
+    # via langfuse
+beautifulsoup4==4.13.5 \
+    --hash=sha256:5e70131382930e7c3de33450a2f54a63d5e4b19386eab43a5b34d594268f3695 \
+    --hash=sha256:642085eaa22233aceadff9c69651bc51e8bf3f874fb6d7104ece2beb24b47c4a
+    # via
+    #   final-assignment-agents-course
+    #   markdownify
+    #   wikipedia
+brotli==1.1.0 \
+    --hash=sha256:0c6244521dda65ea562d5a69b9a26120769b7a9fb3db2fe9545935ed6735b128 \
+    --hash=sha256:1ae56aca0402a0f9a3431cddda62ad71666ca9d4dc3a10a142b9dce2e3c0cda3 \
+    --hash=sha256:1e9a65b5736232e7a7f91ff3d02277f11d339bf34099a56cdab6a8b3410a02b2 \
+    --hash=sha256:38025d9f30cf4634f8309c6874ef871b841eb3c347e90b0851f63d1ded5212da \
+    --hash=sha256:43ce1b9935bfa1ede40028054d7f48b5469cd02733a365eec8a329ffd342915d \
+    --hash=sha256:58d4b711689366d4a03ac7957ab8c28890415e267f9b6589969e74b6e42225ec \
+    --hash=sha256:5dab0844f2cf82be357a0eb11a9087f70c5430b2c241493fc122bb6f2bb0917c \
+    --hash=sha256:7c4855522edb2e6ae7fdb58e07c3ba9111e7621a8956f481c68d5d979c93032e \
+    --hash=sha256:81de08ac11bcb85841e440c13611c00b67d3bf82698314928d0b676362546724 \
+    --hash=sha256:a37b8f0391212d29b3a91a799c8e4a2855e0576911cdfb2515487e30e322253d \
+    --hash=sha256:be36e3d172dc816333f33520154d708a2657ea63762ec16b62ece02ab5e4daf2 \
+    --hash=sha256:c8fd5270e906eef71d4a8d19b7c6a43760c6abcfcc10c9101d14eb2357418de9 \
+    --hash=sha256:e1140c64812cb9b06c922e77f1c26a75ec5e3f0fb2bf92cc8c58720dec276752 \
+    --hash=sha256:e4fe605b917c70283db7dfe5ada75e04561479075761a0b3866c081d035b01c1 \
+    --hash=sha256:e6a904cb26bfefc2f0a6f240bdf5233be78cd2488900a2f846f3c3ac8489ab80 \
+    --hash=sha256:e84799f09591700a4154154cab9787452925578841a94321d5ee8fb9a9a328f0 \
+    --hash=sha256:f66b5337fa213f1da0d9000bc8dc0cb5b896b726eefd9c6046f699b169c41b9e
+    # via gradio
+cachetools==5.5.2 \
+    --hash=sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4 \
+    --hash=sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a
+    # via google-auth
+certifi==2025.8.3 \
+    --hash=sha256:e564105f78ded564e3ae7c923924435e1daa7463faeab5bb932bc53ffae63407 \
+    --hash=sha256:f6c12493cfb1b06ba2ff328595af9350c65d6644968e5d3a2ffd78699af217a5
+    # via
+    #   httpcore
+    #   httpx
+    #   requests
+cffi==1.17.1 ; platform_python_implementation != 'PyPy' \
+    --hash=sha256:045d61c734659cc045141be4bae381a41d89b741f795af1dd018bfb532fd0df8 \
+    --hash=sha256:0f048dcf80db46f0098ccac01132761580d28e28bc0f78ae0d58048063317e15 \
+    --hash=sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824 \
+    --hash=sha256:2bb1a08b8008b281856e5971307cc386a8e9c5b625ac297e853d36da6efe9c17 \
+    --hash=sha256:45398b671ac6d70e67da8e4224a065cec6a93541bb7aebe1b198a61b58c7b702 \
+    --hash=sha256:5da5719280082ac6bd9aa7becb3938dc9f9cbd57fac7d2871717b1feb0902ab6 \
+    --hash=sha256:6883e737d7d9e4899a8a695e00ec36bd4e5e4f18fabe0aca0efe0a4b44cdb13e \
+    --hash=sha256:6b8b4a92e1c65048ff98cfe1f735ef8f1ceb72e3d5f0c25fdb12087a23da22be \
+    --hash=sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67 \
+    --hash=sha256:ad9413ccdeda48c5afdae7e4fa2192157e991ff761e7ab8fdd8926f40b160cc3 \
+    --hash=sha256:c9c3d058ebabb74db66e431095118094d06abf53284d9c81f27300d0e0d8bc7c \
+    --hash=sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14 \
+    --hash=sha256:edae79245293e15384b51f88b00613ba9f7198016a5948b5dddf4917d4d26382
+    # via cryptography
+charset-normalizer==3.4.3 \
+    --hash=sha256:02425242e96bcf29a49711b0ca9f37e451da7c70562bc10e8ed992a5a7a25cc0 \
+    --hash=sha256:07a0eae9e2787b586e129fdcbe1af6997f8d0e5abaa0bc98c0e20e124d67e601 \
+    --hash=sha256:4ca4c094de7771a98d7fbd67d9e5dbf1eb73efa4f744a730437d8a3a5cf994f0 \
+    --hash=sha256:6fce4b8500244f6fcb71465d4a4930d132ba9ab8e71a7859e6a5d59851068d14 \
+    --hash=sha256:74d77e25adda8581ffc1c720f1c81ca082921329452eba58b16233ab1842141c \
+    --hash=sha256:78deba4d8f9590fe4dae384aeff04082510a709957e968753ff3c48399f6f92a \
+    --hash=sha256:c6e490913a46fa054e03699c70019ab869e990270597018cef1d8562132c2669 \
+    --hash=sha256:c6f162aabe9a91a309510d74eeb6507fab5fff92337a15acbe77753d88d9dcf0 \
+    --hash=sha256:cc9370a2da1ac13f0153780040f465839e6cccb4a1e44810124b4e22483c93fe \
+    --hash=sha256:ce571ab16d890d23b5c278547ba694193a45011ff86a9162a71307ed9f86759a \
+    --hash=sha256:d0e909868420b7049dafd3a31d45125b31143eec59235311fc4c57ea26a4acd2 \
+    --hash=sha256:d79c198e27580c8e958906f803e63cddb77653731be08851c7df0b1a14a8fc0f \
+    --hash=sha256:fb7f67a1bfa6e40b438170ebdc8158b78dc465a5a67b6dde178a46987b244a72
+    # via requests
+click==8.2.1 \
+    --hash=sha256:27c491cc05d968d271d5a1db13e3b5a184636d9d930f148c50b038f0d0646202 \
+    --hash=sha256:61a3265b914e850b85317d0b3109c7f8cd35a670f963866005d6ef1d5175a12b
+    # via
+    #   ddgs
+    #   duckduckgo-search
+    #   typer
+    #   uvicorn
+colorama==0.4.6 ; sys_platform == 'win32' \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+    # via
+    #   click
+    #   tqdm
+cryptography==45.0.7 \
+    --hash=sha256:16ede8a4f7929b4b7ff3642eba2bf79aa1d71f24ab6ee443935c0d269b6bc513 \
+    --hash=sha256:18fcf70f243fe07252dcb1b268a687f2358025ce32f9f88028ca5c364b123ef5 \
+    --hash=sha256:1993a1bb7e4eccfb922b6cd414f072e08ff5816702a0bdb8941c247a6b1b287c \
+    --hash=sha256:258e0dff86d1d891169b5af222d362468a9570e2532923088658aa866eb11130 \
+    --hash=sha256:3808e6b2e5f0b46d981c24d79648e5c25c35e59902ea4391a0dcb3e667bf7443 \
+    --hash=sha256:3994c809c17fc570c2af12c9b840d7cea85a9fd3e5c0e0491f4fa3c029216d59 \
+    --hash=sha256:3be4f21c6245930688bd9e162829480de027f8bf962ede33d4f8ba7d67a00cee \
+    --hash=sha256:465ccac9d70115cd4de7186e60cfe989de73f7bb23e8a7aa45af18f7412e75bf \
+    --hash=sha256:48c41a44ef8b8c2e80ca4527ee81daa4c527df3ecbc9423c41a420a9559d0e27 \
+    --hash=sha256:4b1654dfc64ea479c242508eb8c724044f1e964a47d1d1cacc5132292d851971 \
+    --hash=sha256:4bd3e5c4b9682bc112d634f2c6ccc6736ed3635fc3319ac2bb11d768cc5a00d8 \
+    --hash=sha256:577470e39e60a6cd7780793202e63536026d9b8641de011ed9d8174da9ca5339 \
+    --hash=sha256:67285f8a611b0ebc0857ced2081e30302909f571a46bfa7a3cc0ad303fe015c6 \
+    --hash=sha256:7285a89df4900ed3bfaad5679b1e668cb4b38a8de1ccbfc84b05f34512da0a90 \
+    --hash=sha256:81823935e2f8d476707e85a78a405953a03ef7b7b4f55f93f7c2d9680e5e0691 \
+    --hash=sha256:8978132287a9d3ad6b54fcd1e08548033cc09dc6aacacb6c004c73c3eb5d3ac3 \
+    --hash=sha256:a20e442e917889d1a6b3c570c9e3fa2fdc398c20868abcea268ea33c024c4083 \
+    --hash=sha256:a24ee598d10befaec178efdff6054bc4d7e883f615bfbcd08126a0f4931c83a6 \
+    --hash=sha256:b04f85ac3a90c227b6e5890acb0edbaf3140938dbecf07bff618bf3638578cf1 \
+    --hash=sha256:b6a0e535baec27b528cb07a119f321ac024592388c5681a5ced167ae98e9fff3 \
+    --hash=sha256:bef32a5e327bd8e5af915d3416ffefdbe65ed975b646b3805be81b23580b57b8 \
+    --hash=sha256:bfb4c801f65dd61cedfc61a83732327fafbac55a47282e6f26f073ca7a41c3b2 \
+    --hash=sha256:c13b1e3afd29a5b3b2656257f14669ca8fa8d7956d509926f0b130b600b50ab7 \
+    --hash=sha256:c987dad82e8c65ebc985f5dae5e74a3beda9d0a2a4daf8a1115f3772b59e5141 \
+    --hash=sha256:ce7a453385e4c4693985b4a4a3533e041558851eae061a58a5405363b098fcd3 \
+    --hash=sha256:d97cf502abe2ab9eff8bd5e4aca274da8d06dd3ef08b759a8d6143f4ad65d4b4 \
+    --hash=sha256:dad43797959a74103cb59c5dac71409f9c27d34c8a05921341fb64ea8ccb1dd4 \
+    --hash=sha256:dd342f085542f6eb894ca00ef70236ea46070c8a13824c6bde0dfdcd36065b9b \
+    --hash=sha256:de58755d723e86175756f463f2f0bddd45cc36fbd62601228a3f8761c9f58252 \
+    --hash=sha256:f3df7b3d0f91b88b2106031fd995802a2e9ae13e02c36c1fc075b43f420f3a17 \
+    --hash=sha256:fa26fa54c0a9384c27fcdc905a2fb7d60ac6e47d14bc2692145f2b3b1e2cfdbd
+    # via authlib
+dataclasses-json==0.6.7 \
+    --hash=sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a \
+    --hash=sha256:b6b3e528266ea45b9535223bc53ca645f5208833c29229e847b3f26a1cc55fc0
+    # via langchain-community
+ddgs==9.5.5 \
+    --hash=sha256:01fc8017a653ad16501bd8ac9fedcd29291f6500b1f8a7e92a916cdad7fc2fa2 \
+    --hash=sha256:9a09aa9ba24173d14321137c8c1bc54040ed0bf3bad956cb2f9feeda77968770
+    # via final-assignment-agents-course
+defusedxml==0.7.1 \
+    --hash=sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69 \
+    --hash=sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61
+    # via youtube-transcript-api
+distro==1.9.0 \
+    --hash=sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed \
+    --hash=sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2
+    # via
+    #   groq
+    #   openai
+duckduckgo-search==8.1.1 \
+    --hash=sha256:9da91c9eb26a17e016ea1da26235d40404b46b0565ea86d75a9f78cc9441f935 \
+    --hash=sha256:f48adbb06626ee05918f7e0cef3a45639e9939805c4fc179e68c48a12f1b5062
+    # via final-assignment-agents-course
+et-xmlfile==2.0.0 \
+    --hash=sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa \
+    --hash=sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54
+    # via openpyxl
+exceptiongroup==1.3.0 \
+    --hash=sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10 \
+    --hash=sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88
+    # via anyio
+fastapi==0.116.1 \
+    --hash=sha256:c46ac7c312df840f0c9e220f7964bada936781bc4e2e6eb71f1c4d7553786565 \
+    --hash=sha256:ed52cbf946abfd70c5a0dccb24673f0670deeb517a88b3544d03c2a6bf283143
+    # via gradio
+feedparser==6.0.11 \
+    --hash=sha256:0be7ee7b395572b19ebeb1d6aafb0028dee11169f1c934e0ed67d54992f4ad45 \
+    --hash=sha256:c9d0407b64c6f2a065d0ebb292c2b35c01050cc0dc33757461aaabdc4c4184d5
+    # via arxiv
+ffmpy==0.6.1 \
+    --hash=sha256:69a37e2d7d6feb840e233d5640f3499a8b0a8657336774c86e4c52a3219222d4 \
+    --hash=sha256:b5830fd05f72bace05b8fb28724d54a7a63c5119d7f74ca36a75df33f749142d
+    # via gradio
+filelock==3.19.1 \
+    --hash=sha256:66eda1888b0171c998b35be2bcc0f6d75c388a7ce20c3f3f37aa8e96c2dddf58 \
+    --hash=sha256:d38e30481def20772f5baf097c122c3babc4fcdb7e14e57049eb9d88c6dc017d
+    # via huggingface-hub
+filetype==1.2.0 \
+    --hash=sha256:66b56cd6474bf41d8c54660347d37afcc3f7d1970648de365c102ef77548aadb \
+    --hash=sha256:7ce71b6880181241cf7ac8697a2f1eb6a8bd9b429f7ad6d27b8db9ba5f1c2d25
+    # via langchain-google-genai
+frozenlist==1.7.0 \
+    --hash=sha256:1073557c941395fdfcfac13eb2456cb8aad89f9de27bae29fabca8e563b12615 \
+    --hash=sha256:15900082e886edb37480335d9d518cec978afc69ccbc30bd18610b7c1b22a718 \
+    --hash=sha256:1ed8d2fa095aae4bdc7fdd80351009a48d286635edffee66bf865e37a9125c50 \
+    --hash=sha256:24c34bea555fe42d9f928ba0a740c553088500377448febecaa82cc3e88aa1fa \
+    --hash=sha256:2e310d81923c2437ea8670467121cc3e9b0f76d3043cc1d2331d56c7fb7a3a8f \
+    --hash=sha256:3789ebc19cb811163e70fe2bd354cea097254ce6e707ae42e56f45e31e96cb8e \
+    --hash=sha256:400ddd24ab4e55014bba442d917203c73b2846391dd42ca5e38ff52bb18c3c5e \
+    --hash=sha256:41be2964bd4b15bf575e5daee5a5ce7ed3115320fb3c2b71fca05582ffa4dc9e \
+    --hash=sha256:46d84d49e00c9429238a7ce02dc0be8f6d7cd0cd405abd1bebdc991bf27c15bd \
+    --hash=sha256:69cac419ac6a6baad202c85aaf467b65ac860ac2e7f2ac1686dc40dbb52f6577 \
+    --hash=sha256:6eb93efb8101ef39d32d50bce242c84bcbddb4f7e9febfa7b524532a239b4464 \
+    --hash=sha256:716a9973a2cc963160394f701964fe25012600f3d311f60c790400b00e568b61 \
+    --hash=sha256:960d67d0611f4c87da7e2ae2eacf7ea81a5be967861e0c63cf205215afbfac59 \
+    --hash=sha256:9a5af342e34f7e97caf8c995864c7a396418ae2859cc6fdf1b1073020d516a7e \
+    --hash=sha256:a0fd1bad056a3600047fb9462cff4c5322cebc59ebf5d0a3725e0ee78955001d \
+    --hash=sha256:ac64b6478722eeb7a3313d494f8342ef3478dff539d17002f849101b212ef97c \
+    --hash=sha256:af369aa35ee34f132fcfad5be45fbfcde0e3a5f6a1ec0712857f286b7d20cca9 \
+    --hash=sha256:cc4df77d638aa2ed703b878dd093725b72a824c3c546c076e8fdf276f78ee84a \
+    --hash=sha256:f89f65d85774f1797239693cef07ad4c97fdd0639544bad9ac4b869782eb1981
+    # via
+    #   aiohttp
+    #   aiosignal
+fsspec==2025.3.0 \
+    --hash=sha256:a935fd1ea872591f2b5148907d103488fc523295e6c64b835cfad8c3eca44972 \
+    --hash=sha256:efb87af3efa9103f94ca91a7f8cb7a4df91af9f74fc106c9c7ea0efd7277c1b3
+    # via
+    #   gradio-client
+    #   huggingface-hub
+google-ai-generativelanguage==0.6.18 \
+    --hash=sha256:13d8174fea90b633f520789d32df7b422058fd5883b022989c349f1017db7fcf \
+    --hash=sha256:274ba9fcf69466ff64e971d565884434388e523300afd468fc8e3033cd8e606e
+    # via langchain-google-genai
+google-api-core==2.25.1 \
+    --hash=sha256:8a2a56c1fef82987a524371f99f3bd0143702fecc670c72e600c1cda6bf8dbb7 \
+    --hash=sha256:d2aaa0b13c78c61cb3f4282c464c046e45fbd75755683c9c525e6e8f7ed0a5e8
+    # via google-ai-generativelanguage
+google-auth==2.40.3 \
+    --hash=sha256:1370d4593e86213563547f97a92752fc658456fe4514c809544f330fed45a7ca \
+    --hash=sha256:500c3a29adedeb36ea9cf24b8d10858e152f2412e3ca37829b3fa18e33d63b77
+    # via
+    #   google-ai-generativelanguage
+    #   google-api-core
+googleapis-common-protos==1.70.0 \
+    --hash=sha256:0e1b44e0ea153e6594f9f394fef15193a68aaaea2d843f83e2742717ca753257 \
+    --hash=sha256:b8bfcca8c25a2bb253e0e0b0adaf8c00773e5e6af6fd92397576680b807e0fd8
+    # via
+    #   google-api-core
+    #   grpcio-status
+    #   opentelemetry-exporter-otlp-proto-http
+gradio==5.44.1 \
+    --hash=sha256:8527837aa6de4b0d2398dab11baac8e3eac9da69140ed0da6efc6ac497fa818d \
+    --hash=sha256:cb22dd519c3bb2f8c7960cdcc23ca3b869511c85e320f486d7aef6e3627f97b9
+    # via final-assignment-agents-course
+gradio-client==1.12.1 \
+    --hash=sha256:37c0bcd0e6b3794b2b2e0b5039696d6962d8125bdb96960ad1b79412326b1664 \
+    --hash=sha256:64ae7b1d951482194e3a2f8d20cd3fbdaaa13418ee988445d3c9edb28da50ea2
+    # via gradio
+greenlet==3.2.4 ; platform_machine == 'AMD64' or platform_machine == 'WIN32' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'ppc64le' or platform_machine == 'win32' or platform_machine == 'x86_64' \
+    --hash=sha256:0dca0d95ff849f9a364385f36ab49f50065d76964944638be9691e1832e9f86d \
+    --hash=sha256:58b97143c9cc7b86fc458f215bd0932f1757ce649e05b640fea2e79b54cedb31 \
+    --hash=sha256:73f49b5368b5359d04e18d15828eecc1806033db5233397748f4ca813ff1056c \
+    --hash=sha256:8854167e06950ca75b898b104b63cc646573aa5fef1353d4508ecdd1ee76254f \
+    --hash=sha256:8c68325b0d0acf8d91dde4e6f930967dd52a5302cd4062932a6b2e7c2969f47c \
+    --hash=sha256:94385f101946790ae13da500603491f04a76b6e4c059dab271b3ce2e283b2590 \
+    --hash=sha256:9fe0a28a7b952a21e2c062cd5756d34354117796c6d9215a87f55e38d15402c5 \
+    --hash=sha256:c2ca18a03a8cfb5b25bc1cbe20f3d9a4c80d8c3b13ba3df49ac3961af0b1018d \
+    --hash=sha256:c8c9e331e58180d0d83c5b7999255721b725913ff6bc6cf39fa2a45841a4fd4b \
+    --hash=sha256:f10fd42b5ee276335863712fa3da6608e93f70629c631bf77145021600abc23c
+    # via sqlalchemy
+groovy==0.1.2 \
+    --hash=sha256:25c1dc09b3f9d7e292458aa762c6beb96ea037071bf5e917fc81fb78d2231083 \
+    --hash=sha256:7f7975bab18c729a257a8b1ae9dcd70b7cafb1720481beae47719af57c35fa64
+    # via gradio
+groq==0.31.1 \
+    --hash=sha256:4d611e0100cb22732c43b53af37933a1b8a5c5a18fa96132fee14e6c15d737e6 \
+    --hash=sha256:536bd5dd6267dea5b3710e41094c0479748da2d155b9e073650e94b7fb2d71e8
+    # via langchain-groq
+grpcio==1.74.0 \
+    --hash=sha256:136b53c91ac1d02c8c24201bfdeb56f8b3ac3278668cbb8e0ba49c88069e1bdc \
+    --hash=sha256:1733969040989f7acc3d94c22f55b4a9501a30f6aaacdbccfaba0a3ffb255ab7 \
+    --hash=sha256:4e4181bfc24413d1e3a37a0b7889bea68d973d4b45dd2bc68bb766c140718f82 \
+    --hash=sha256:68c8ebcca945efff9d86d8d6d7bfb0841cf0071024417e2d7f45c5e46b5b08eb \
+    --hash=sha256:80d1f4fbb35b0742d3e3d3bb654b7381cd5f015f8497279a1e9c21ba623e01b1 \
+    --hash=sha256:85bd5cdf4ed7b2d6438871adf6afff9af7096486fcf51818a81b77ef4dd30907 \
+    --hash=sha256:9e912d3c993a29df6c627459af58975b2e5c897d93287939b9d5065f000249b5 \
+    --hash=sha256:c3d7bd6e3929fd2ea7fbc3f562e4987229ead70c9ae5f01501a46701e08f1ad9 \
+    --hash=sha256:e154d230dc1bbbd78ad2fdc3039fa50ad7ffcf438e4eb2fa30bce223a70c7486 \
+    --hash=sha256:e8978003816c7b9eabe217f88c78bc26adc8f9304bf6a594b02e5a49b2ef9c11 \
+    --hash=sha256:fe0f540750a13fd8e5da4b3eaba91a785eea8dca5ccd2bc2ffe978caa403090e
+    # via
+    #   google-api-core
+    #   grpcio-status
+grpcio-status==1.74.0 \
+    --hash=sha256:52cdbd759a6760fc8f668098a03f208f493dd5c76bf8e02598bbbaf1f6fc2876 \
+    --hash=sha256:c58c1b24aa454e30f1fc6a7e0dbbc194c54a408143971a94b5f4e40bb5831432
+    # via google-api-core
+h11==0.16.0 \
+    --hash=sha256:4e35b956cf45792e4caa5885e69fba00bdbc6ffafbfa020300e549b208ee5ff1 \
+    --hash=sha256:63cf8bbe7522de3bf65932fda1d9c2772064ffb3dae62d55932da54b31cb6c86
+    # via
+    #   httpcore
+    #   uvicorn
+hf-xet==1.1.9 ; platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64' \
+    --hash=sha256:5aad3933de6b725d61d51034e04174ed1dce7a57c63d530df0014dea15a40127 \
+    --hash=sha256:86754c2d6d5afb11b0a435e6e18911a4199262fe77553f8c50d75e21242193ea \
+    --hash=sha256:96a6139c9e44dad1c52c52520db0fffe948f6bce487cfb9d69c125f254bb3790 \
+    --hash=sha256:9b486de7a64a66f9a172f4b3e0dfe79c9f0a93257c501296a2521a13495a698a \
+    --hash=sha256:a3b6215f88638dd7a6ff82cb4e738dcbf3d863bf667997c093a3c990337d1160 \
+    --hash=sha256:a4c5a840c2c4e6ec875ed13703a60e3523bc7f48031dfd750923b2a4d1a5fc3c \
+    --hash=sha256:ad1022e9a998e784c97b2173965d07fe33ee26e4594770b7785a8cc8f922cd95 \
+    --hash=sha256:c99073ce404462e909f1d5839b2d14a3827b8fe75ed8aed551ba6609c026c803
+    # via huggingface-hub
+httpcore==1.0.9 \
+    --hash=sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55 \
+    --hash=sha256:6e34463af53fd2ab5d807f399a9b45ea31c3dfa2276f15a2c3f00afff6e176e8
+    # via httpx
+httpx==0.28.1 \
+    --hash=sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc \
+    --hash=sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad
+    # via
+    #   assemblyai
+    #   gradio
+    #   gradio-client
+    #   groq
+    #   langfuse
+    #   langgraph-sdk
+    #   langsmith
+    #   ollama
+    #   openai
+    #   safehttpx
+httpx-sse==0.4.1 \
+    --hash=sha256:8f44d34414bc7b21bf3602713005c5df4917884f76072479b21f68befa4ea26e \
+    --hash=sha256:cba42174344c3a5b06f255ce65b350880f962d99ead85e776f23c6618a377a37
+    # via langchain-community
+huggingface-hub==0.34.4 \
+    --hash=sha256:9b365d781739c93ff90c359844221beef048403f1bc1f1c123c191257c3c890a \
+    --hash=sha256:a4228daa6fb001be3f4f4bdaf9a0db00e1739235702848df00885c9b5742c85c
+    # via
+    #   gradio
+    #   gradio-client
+    #   langchain-huggingface
+    #   tokenizers
+idna==3.10 \
+    --hash=sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9 \
+    --hash=sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3
+    # via
+    #   anyio
+    #   httpx
+    #   requests
+    #   yarl
+importlib-metadata==8.7.0 \
+    --hash=sha256:d13b81ad223b890aa16c5471f2ac3056cf76c5f10f82d6f9292f0b415f389000 \
+    --hash=sha256:e5dd1551894c77868a30651cef00984d50e1002d06942a7101d34870c5f02afd
+    # via opentelemetry-api
+itsdangerous==2.2.0 \
+    --hash=sha256:c6242fc49e35958c8b15141343aa660db5fc54d4f13a1db01a3f5891b98700ef \
+    --hash=sha256:e0050c0b7da1eea53ffaf149c0cfbb5c6e2e2b69c4bef22c81fa6eb73e5f6173
+    # via gradio
+jinja2==3.1.6 \
+    --hash=sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d \
+    --hash=sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67
+    # via gradio
+jiter==0.10.0 \
+    --hash=sha256:03997d2f37f6b67d2f5c475da4412be584e1cec273c1cfc03d642c46db43f8cf \
+    --hash=sha256:07a7142c38aacc85194391108dc91b5b57093c978a9932bd86a36862759d9500 \
+    --hash=sha256:286299b74cc49e25cd42eea19b72aa82c515d2f2ee12d11392c56d8701f52224 \
+    --hash=sha256:32bb468e3af278f095d3fa5b90314728a6916d89ba3d0ffb726dd9bf7367285e \
+    --hash=sha256:66e989410b6666d3ddb27a74c7e50d0829704ede652fd4c858e91f8d64b403d0 \
+    --hash=sha256:6ed5649ceeaeffc28d87fb012d25a4cd356dcd53eff5acff1f0466b831dda2a7 \
+    --hash=sha256:aa8b3e0068c26ddedc7abc6fac37da2d0af16b921e288a5a613f4b86f050354f \
+    --hash=sha256:b2ab0051160cb758a70716448908ef14ad476c3774bd03ddce075f3c1f90a3d6 \
+    --hash=sha256:b532d3af9ef4f6374609a3bcb5e05a1951d3bf6190dc6b176fdb277c9bbf15ee \
+    --hash=sha256:c404a99352d839fed80d6afd6c1d66071f3bacaaa5c4268983fc10f769112e90 \
+    --hash=sha256:cd2fb72b02478f06a900a5782de2ef47e0396b3e1f7d5aba30daeb1fce66f303 \
+    --hash=sha256:da9be20b333970e28b72edc4dff63d4fec3398e05770fb3205f7fb460eb48dd4 \
+    --hash=sha256:f59e533afed0c5b0ac3eba20d2548c4a550336d8282ee69eb07b37ea526ee4e5
+    # via openai
+jsonpatch==1.33 \
+    --hash=sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade \
+    --hash=sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c
+    # via langchain-core
+jsonpointer==3.0.0 \
+    --hash=sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942 \
+    --hash=sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef
+    # via jsonpatch
+langchain==0.3.27 \
+    --hash=sha256:7b20c4f338826acb148d885b20a73a16e410ede9ee4f19bb02011852d5f98798 \
+    --hash=sha256:aa6f1e6274ff055d0fd36254176770f356ed0a8994297d1df47df341953cec62
+    # via
+    #   final-assignment-agents-course
+    #   langchain-community
+langchain-community==0.3.29 \
+    --hash=sha256:1f3d37973b10458052bb3cc02dce9773a8ffbd02961698c6d395b8c8d7f9e004 \
+    --hash=sha256:c876ec7ef40b46353af164197f4e08e157650e8a02c9fb9d49351cdc16c839fe
+    # via
+    #   final-assignment-agents-course
+    #   langchain-experimental
+langchain-core==0.3.75 \
+    --hash=sha256:03ca1fadf955ee3c7d5806a841f4b3a37b816acea5e61a7e6ba1298c05eea7f5 \
+    --hash=sha256:ab0eb95a06ed6043f76162e6086b45037690cb70b7f090bd83b5ebb8a05b70ed
+    # via
+    #   final-assignment-agents-course
+    #   langchain
+    #   langchain-community
+    #   langchain-experimental
+    #   langchain-google-genai
+    #   langchain-groq
+    #   langchain-huggingface
+    #   langchain-ollama
+    #   langchain-openai
+    #   langchain-text-splitters
+    #   langgraph
+    #   langgraph-checkpoint
+    #   langgraph-prebuilt
+langchain-experimental==0.3.4 \
+    --hash=sha256:2e587306aea36b60fa5e5fc05dc7281bee9f60a806f0bf9d30916e0ee096af80 \
+    --hash=sha256:937c4259ee4a639c618d19acf0e2c5c2898ef127050346edc5655259aa281a21
+    # via final-assignment-agents-course
+langchain-google-genai==2.1.10 \
+    --hash=sha256:247e38908d6b37fb4c4892ca09ae224c7510158b54b0582a9f39a7ddf37a0e2c \
+    --hash=sha256:3d091aa61284d7256b2887966e806689adce35e55bc46f705162e5ede8aacda9
+    # via final-assignment-agents-course
+langchain-groq==0.3.7 \
+    --hash=sha256:2e13870534c032fe1facde3a6ab1fb59af6f1e7a2763125ad549d8e403fc9d00 \
+    --hash=sha256:4d799aa565f31e51c632f0f20c588f21c5a0e6c6dd2303efaef43351f9b41bd4
+    # via final-assignment-agents-course
+langchain-huggingface==0.3.1 \
+    --hash=sha256:0a145534ce65b5a723c8562c456100a92513bbbf212e6d8c93fdbae174b41341 \
+    --hash=sha256:de10a692dc812885696fbaab607d28ac86b833b0f305bccd5d82d60336b07b7d
+    # via final-assignment-agents-course
+langchain-ollama==0.3.7 \
+    --hash=sha256:845192a75a1671bd36bc8c54baae2e929c3b1b0e3c8c618438df20354b0231de \
+    --hash=sha256:9deeca09a44fb8c5a46b1e43d670a7301f1d1e73196fa9191a89f9883217903b
+    # via final-assignment-agents-course
+langchain-openai==0.3.32 \
+    --hash=sha256:3354f76822f7cc76d8069831fe2a77f9bc7ff3b4f13af788bd94e4c6e853b400 \
+    --hash=sha256:782ad669bd1bdb964456d8882c5178717adcfceecb482cc20005f770e43d346d
+    # via
+    #   final-assignment-agents-course
+    #   langchain
+langchain-text-splitters==0.3.11 \
+    --hash=sha256:7a50a04ada9a133bbabb80731df7f6ddac51bc9f1b9cab7fa09304d71d38a6cc \
+    --hash=sha256:cf079131166a487f1372c8ab5d0bfaa6c0a4291733d9c43a34a16ac9bcd6a393
+    # via
+    #   final-assignment-agents-course
+    #   langchain
+langfuse==3.3.4 \
+    --hash=sha256:15b9d20878cf39a48ca9cfa7e52acdfeb043603d3a9cef8cf451687a4d838c6b \
+    --hash=sha256:e5df4e7284298990b522e02a1dc6c3c72ebc4a7a411dc7d39255fb8c2e5a7c3a
+    # via final-assignment-agents-course
+langgraph==0.6.6 \
+    --hash=sha256:a2283a5236abba6c8307c1a485c04e8a0f0ffa2be770878782a7bf2deb8d7954 \
+    --hash=sha256:e7d3cefacf356f8c01721b166b67b3bf581659d5361a3530f59ecd9b8448eca7
+    # via final-assignment-agents-course
+langgraph-checkpoint==2.1.1 \
+    --hash=sha256:5a779134fd28134a9a83d078be4450bbf0e0c79fdf5e992549658899e6fc5ea7 \
+    --hash=sha256:72038c0f9e22260cb9bff1f3ebe5eb06d940b7ee5c1e4765019269d4f21cf92d
+    # via
+    #   final-assignment-agents-course
+    #   langgraph
+    #   langgraph-prebuilt
+langgraph-prebuilt==0.6.4 \
+    --hash=sha256:819f31d88b84cb2729ff1b79db2d51e9506b8fb7aaacfc0d359d4fe16e717344 \
+    --hash=sha256:e9e53b906ee5df46541d1dc5303239e815d3ec551e52bb03dd6463acc79ec28f
+    # via
+    #   final-assignment-agents-course
+    #   langgraph
+langgraph-sdk==0.2.6 \
+    --hash=sha256:477216b573b8177bbd849f4c754782a81279fbbd88bfadfeda44422d14b18b08 \
+    --hash=sha256:7db27cd86d1231fa614823ff416fcd2541b5565ad78ae950f31ae96d7af7c519
+    # via
+    #   final-assignment-agents-course
+    #   langgraph
+langsmith==0.4.25 \
+    --hash=sha256:56f0c45810384fba37582ca17fdbcf6ead51934d26d72672e5a810452c0d4ae3 \
+    --hash=sha256:adb61784ff58e65f0290ba45770626219fb06a776e69fbcf98aec580478b4686
+    # via
+    #   final-assignment-agents-course
+    #   langchain
+    #   langchain-community
+    #   langchain-core
+lxml==6.0.1 \
+    --hash=sha256:07038c62fd0fe2743e2f5326f54d464715373c791035d7dda377b3c9a5d0ad77 \
+    --hash=sha256:0abfbaf4ebbd7fd33356217d317b6e4e2ef1648be6a9476a52b57ffc6d8d1780 \
+    --hash=sha256:11a052cbd013b7140bbbb38a14e2329b6192478344c99097e378c691b7119551 \
+    --hash=sha256:1ebbf2d9775be149235abebdecae88fe3b3dd06b1797cd0f6dffe6948e85309d \
+    --hash=sha256:21344d29c82ca8547ea23023bb8e7538fa5d4615a1773b991edf8176a870c1ea \
+    --hash=sha256:2b3a882ebf27dd026df3801a87cf49ff791336e0f94b0fad195db77e01240690 \
+    --hash=sha256:3b38e20c578149fdbba1fd3f36cb1928a3aaca4b011dfd41ba09d11fb396e1b9 \
+    --hash=sha256:4588806a721552692310ebe9f90c17ac6c7c5dac438cd93e3d74dd60531c3211 \
+    --hash=sha256:50b5e54f6a9461b1e9c08b4a3420415b538d4773bd9df996b9abcbfe95f4f1fd \
+    --hash=sha256:615bb6c73fed7929e3a477a3297a797892846b253d59c84a62c98bdce3849a0a \
+    --hash=sha256:6f393e10685b37f15b1daef8aa0d734ec61860bb679ec447afa0001a31e7253f \
+    --hash=sha256:7a44a5fb1edd11b3a65c12c23e1049c8ae49d90a24253ff18efbcb6aa042d012 \
+    --hash=sha256:8466faa66b0353802fb7c054a400ac17ce2cf416e3ad8516eadeff9cba85b741 \
+    --hash=sha256:8f5cf2addfbbe745251132c955ad62d8519bb4b2c28b0aa060eca4541798d86e \
+    --hash=sha256:a389e9f11c010bd30531325805bbe97bdf7f728a73d0ec475adef57ffec60547 \
+    --hash=sha256:a57d9eb9aadf311c9e8785230eec83c6abb9aef2adac4c0587912caf8f3010b8 \
+    --hash=sha256:aa8f130f4b2dc94baa909c17bb7994f0268a2a72b9941c872e8e558fd6709050 \
+    --hash=sha256:c43460f4aac016ee0e156bfa14a9de9b3e06249b12c228e27654ac3996a46d5b \
+    --hash=sha256:d877874a31590b72d1fa40054b50dc33084021bfc15d01b3a661d85a302af821 \
+    --hash=sha256:f1b60a3287bf33a2a54805d76b82055bcc076e445fd539ee9ae1fe85ed373691 \
+    --hash=sha256:f7bbfb0751551a8786915fc6b615ee56344dacc1b1033697625b553aefdd9837
+    # via
+    #   ddgs
+    #   duckduckgo-search
+markdown-it-py==4.0.0 ; sys_platform != 'emscripten' \
+    --hash=sha256:87327c59b172c5011896038353a81343b6754500a08cd7a4973bb48c6d578147 \
+    --hash=sha256:cb0a2b4aa34f932c007117b194e945bd74e0ec24133ceb5bac59009cda1cb9f3
+    # via rich
+markdownify==1.2.0 \
+    --hash=sha256:48e150a1c4993d4d50f282f725c0111bd9eb25645d41fa2f543708fd44161351 \
+    --hash=sha256:f6c367c54eb24ee953921804dfe6d6575c5e5b42c643955e7242034435de634c
+    # via final-assignment-agents-course
+markupsafe==3.0.2 \
+    --hash=sha256:3809ede931876f5b2ec92eef964286840ed3540dadf803dd570c3b7e13141a3b \
+    --hash=sha256:38a9ef736c01fccdd6600705b09dc574584b89bea478200c5fbf112a6b0d5579 \
+    --hash=sha256:57cb5a3cf367aeb1d316576250f65edec5bb3be939e9247ae594b4bcbc317dfb \
+    --hash=sha256:6af100e168aa82a50e186c82875a5893c5597a0c1ccdb0d8b40240b1f28b969a \
+    --hash=sha256:7e94c425039cde14257288fd61dcfb01963e658efbc0ff54f5306b06054700f8 \
+    --hash=sha256:9e2d922824181480953426608b81967de705c3cef4d1af983af849d7bd619158 \
+    --hash=sha256:b424c77b206d63d500bcb69fa55ed8d0e6a3774056bdc4839fc9298a7edca171 \
+    --hash=sha256:bbcb445fa71794da8f178f0f6d66789a28d7319071af7a496d4d507ed566270d \
+    --hash=sha256:e07c3764494e3776c602c1e78e298937c3315ccc9043ead7e685b7f2b8d47b3c \
+    --hash=sha256:ee55d3edf80167e48ea11a923c7386f4669df67d7994554387f84e7d8b0a2bf0 \
+    --hash=sha256:fcabf5ff6eea076f859677f5f0b6b5c1a51e70a376b0579e0eadef8db48c6b50
+    # via
+    #   gradio
+    #   jinja2
+marshmallow==3.26.1 \
+    --hash=sha256:3350409f20a70a7e4e11a27661187b77cdcaeb20abca41c1454fe33636bea09c \
+    --hash=sha256:e6d8affb6cb61d39d26402096dc0aee12d5a26d490a121f118d2e81dc0719dc6
+    # via dataclasses-json
+mdurl==0.1.2 ; sys_platform != 'emscripten' \
+    --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \
+    --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba
+    # via markdown-it-py
+multidict==6.6.4 \
+    --hash=sha256:01d0959807a451fe9fdd4da3e139cb5b77f7328baf2140feeaf233e1d777b729 \
+    --hash=sha256:0af5f9dee472371e36d6ae38bde009bd8ce65ac7335f55dcc240379d7bed1495 \
+    --hash=sha256:163c7ea522ea9365a8a57832dea7618e6cbdc3cd75f8c627663587459a4e328f \
+    --hash=sha256:17d2cbbfa6ff20821396b25890f155f40c986f9cfbce5667759696d83504954f \
+    --hash=sha256:27d8f8e125c07cb954e54d75d04905a9bba8a439c1d84aca94949d4d03d8601c \
+    --hash=sha256:4bb7627fd7a968f41905a4d6343b0d63244a0623f006e9ed989fa2b78f4438a0 \
+    --hash=sha256:8c9854df0eaa610a23494c32a6f44a3a550fb398b6b51a56e8c6b9b3689578db \
+    --hash=sha256:9a950b7cf54099c1209f455ac5970b1ea81410f2af60ed9eb3c3f14f0bfcf987 \
+    --hash=sha256:a1b20a9d56b2d81e2ff52ecc0670d583eaabaa55f402e8d16dd062373dbbe796 \
+    --hash=sha256:ad887a8250eb47d3ab083d2f98db7f48098d13d42eb7a3b67d8a5c795f224ace \
+    --hash=sha256:b8aa6f0bd8125ddd04a6593437bad6a7e70f300ff4180a531654aa2ab3f6d58f \
+    --hash=sha256:b9e5853bbd7264baca42ffc53391b490d65fe62849bf2c690fa3f6273dbcd0cb \
+    --hash=sha256:c5c97aa666cf70e667dfa5af945424ba1329af5dd988a437efeb3a09430389fb \
+    --hash=sha256:caebafea30ed049c57c673d0b36238b1748683be2593965614d7b0e99125c877 \
+    --hash=sha256:ce9a40fbe52e57e7edf20113a4eaddfacac0561a0879734e636aa6d4bb5e3fb0 \
+    --hash=sha256:d24f351e4d759f5054b641c81e8291e5d122af0fca5c72454ff77f7cbe492de8 \
+    --hash=sha256:d2d4e4787672911b48350df02ed3fa3fffdc2f2e8ca06dd6afdf34189b76a9dd \
+    --hash=sha256:db6a3810eec08280a172a6cd541ff4a5f6a97b161d93ec94e6c4018917deb6b7 \
+    --hash=sha256:ecab51ad2462197a4c000b6d5701fc8585b80eecb90583635d7e327b7b6923eb \
+    --hash=sha256:ed8358ae7d94ffb7c397cecb62cbac9578a83ecefc1eba27b9090ee910e2efb6
+    # via
+    #   aiohttp
+    #   yarl
+mypy-extensions==1.1.0 \
+    --hash=sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505 \
+    --hash=sha256:52e68efc3284861e772bbcd66823fde5ae21fd2fdb51c62a211403730b916558
+    # via typing-inspect
+numpy==2.2.6 \
+    --hash=sha256:0b605b275d7bd0c640cad4e5d30fa701a8d59302e127e5f79138ad62762c3e3d \
+    --hash=sha256:37e990a01ae6ec7fe7fa1c26c55ecb672dd98b19c3d0e1d1f326fa13cb38d163 \
+    --hash=sha256:5a6429d4be8ca66d889b7cf70f536a397dc45ba6faeb5f8c5427935d9592e9cf \
+    --hash=sha256:74d4531beb257d2c3f4b261bfb0fc09e0f9ebb8842d82a7b4209415896adc680 \
+    --hash=sha256:7befc596a7dc9da8a337f79802ee8adb30a552a94f792b9c9d18c840055907db \
+    --hash=sha256:8e41fd67c52b86603a91c1a505ebaef50b3314de0213461c7a6e99c9a3beff90 \
+    --hash=sha256:8fc377d995680230e83241d8a96def29f204b5782f371c532579b4f20607a289 \
+    --hash=sha256:b093dd74e50a8cba3e873868d9e93a85b78e0daf2e98c6797566ad8044e8363d \
+    --hash=sha256:b412caa66f72040e6d268491a59f2c43bf03eb6c96dd8f0307829feb7fa2b6fb \
+    --hash=sha256:ce47521a4754c8f4593837384bd3424880629f718d87c5d44f8ed763edd63543 \
+    --hash=sha256:d042d24c90c41b54fd506da306759e06e568864df8ec17ccc17e9e884634fd00 \
+    --hash=sha256:e29554e2bef54a90aa5cc07da6ce955accb83f21ab5de01a62c8478897b264fd \
+    --hash=sha256:efd28d4e9cd7d7a8d39074a4d44c63eda73401580c5c76acda2ce969e0a38e83 \
+    --hash=sha256:f0fd6321b839904e15c46e0d257fdd101dd7f530fe03fd6359c1ea63738703f3 \
+    --hash=sha256:fc7b73d02efb0e18c000e9ad8b83480dfcd5dfd11065997ed4c6747470ae8915
+    # via
+    #   gradio
+    #   langchain-community
+    #   pandas
+ollama==0.5.3 \
+    --hash=sha256:40b6dff729df3b24e56d4042fd9d37e231cee8e528677e0d085413a1d6692394 \
+    --hash=sha256:a8303b413d99a9043dbf77ebf11ced672396b59bec27e6d5db67c88f01b279d2
+    # via langchain-ollama
+openai==1.106.1 \
+    --hash=sha256:5f575967e3a05555825c43829cdcd50be6e49ab6a3e5262f0937a3f791f917f1 \
+    --hash=sha256:bfdef37c949f80396c59f2c17e0eda35414979bc07ef3379596a93c9ed044f3a
+    # via langchain-openai
+openpyxl==3.1.5 \
+    --hash=sha256:5282c12b107bffeef825f4617dc029afaf41d0ea60823bbb665ef3079dc79de2 \
+    --hash=sha256:cf0e3cf56142039133628b5acffe8ef0c12bc902d2aadd3e0fe5878dc08d1050
+    # via final-assignment-agents-course
+opentelemetry-api==1.36.0 \
+    --hash=sha256:02f20bcacf666e1333b6b1f04e647dc1d5111f86b8e510238fcc56d7762cda8c \
+    --hash=sha256:9a72572b9c416d004d492cbc6e61962c0501eaf945ece9b5a0f56597d8348aa0
+    # via
+    #   langfuse
+    #   opentelemetry-exporter-otlp-proto-http
+    #   opentelemetry-sdk
+    #   opentelemetry-semantic-conventions
+opentelemetry-exporter-otlp-proto-common==1.36.0 \
+    --hash=sha256:0fc002a6ed63eac235ada9aa7056e5492e9a71728214a61745f6ad04b923f840 \
+    --hash=sha256:6c496ccbcbe26b04653cecadd92f73659b814c6e3579af157d8716e5f9f25cbf
+    # via opentelemetry-exporter-otlp-proto-http
+opentelemetry-exporter-otlp-proto-http==1.36.0 \
+    --hash=sha256:3d769f68e2267e7abe4527f70deb6f598f40be3ea34c6adc35789bea94a32902 \
+    --hash=sha256:dd3637f72f774b9fc9608ab1ac479f8b44d09b6fb5b2f3df68a24ad1da7d356e
+    # via langfuse
+opentelemetry-proto==1.36.0 \
+    --hash=sha256:0f10b3c72f74c91e0764a5ec88fd8f1c368ea5d9c64639fb455e2854ef87dd2f \
+    --hash=sha256:151b3bf73a09f94afc658497cf77d45a565606f62ce0c17acb08cd9937ca206e
+    # via
+    #   opentelemetry-exporter-otlp-proto-common
+    #   opentelemetry-exporter-otlp-proto-http
+opentelemetry-sdk==1.36.0 \
+    --hash=sha256:19c8c81599f51b71670661ff7495c905d8fdf6976e41622d5245b791b06fa581 \
+    --hash=sha256:19fe048b42e98c5c1ffe85b569b7073576ad4ce0bcb6e9b4c6a39e890a6c45fb
+    # via
+    #   langfuse
+    #   opentelemetry-exporter-otlp-proto-http
+opentelemetry-semantic-conventions==0.57b0 \
+    --hash=sha256:609a4a79c7891b4620d64c7aac6898f872d790d75f22019913a660756f27ff32 \
+    --hash=sha256:757f7e76293294f124c827e514c2a3144f191ef175b069ce8d1211e1e38e9e78
+    # via opentelemetry-sdk
+orjson==3.11.3 \
+    --hash=sha256:0c212cfdd90512fe722fa9bd620de4d46cda691415be86b2e02243242ae81873 \
+    --hash=sha256:1c0603b1d2ffcd43a411d64797a19556ef76958aef1c182f22dc30860152a98a \
+    --hash=sha256:29cb1f1b008d936803e2da3d7cba726fc47232c45df531b29edf0b232dd737e7 \
+    --hash=sha256:58533f9e8266cb0ac298e259ed7b4d42ed3fa0b78ce76860626164de49e0d467 \
+    --hash=sha256:5ff835b5d3e67d9207343effb03760c00335f8b5285bfceefd4dc967b0e48f6a \
+    --hash=sha256:90368277087d4af32d38bd55f9da2ff466d25325bf6167c8f382d8ee40cb2bbc \
+    --hash=sha256:976c6f1975032cc327161c65d4194c549f2589d88b105a5e3499429a54479770 \
+    --hash=sha256:97dceed87ed9139884a55db8722428e27bd8452817fbf1869c58b49fecab1120 \
+    --hash=sha256:bb93562146120bb51e6b154962d3dadc678ed0fce96513fa6bc06599bb6f6edc \
+    --hash=sha256:d7d18dd34ea2e860553a579df02041845dee0af8985dff7f8661306f95504ddf \
+    --hash=sha256:d8b11701bc43be92ea42bd454910437b355dfb63696c06fe953ffb40b5f763b4 \
+    --hash=sha256:f5aa4682912a450c2db89cbd92d356fef47e115dffba07992555542f344d301b \
+    --hash=sha256:f8d902867b699bcd09c176a280b1acdab57f924489033e53d0afe79817da37e6 \
+    --hash=sha256:fd7ff459fb393358d3a155d25b275c60b07a2c83dcd7ea962b1923f5a1134569
+    # via
+    #   gradio
+    #   langgraph-sdk
+    #   langsmith
+ormsgpack==1.10.0 \
+    --hash=sha256:060f67fe927582f4f63a1260726d019204b72f460cf20930e6c925a1d129f373 \
+    --hash=sha256:10f6f3509c1b0e51b15552d314b1d409321718122e90653122ce4b997f01453a \
+    --hash=sha256:137aab0d5cdb6df702da950a80405eb2b7038509585e32b4e16289604ac7cb84 \
+    --hash=sha256:3e666cb63030538fa5cd74b1e40cb55b6fdb6e2981f024997a288bf138ebad07 \
+    --hash=sha256:51c1edafd5c72b863b1f875ec31c529f09c872a5ff6fe473b9dfaf188ccc3227 \
+    --hash=sha256:7f7a27efd67ef22d7182ec3b7fa7e9d147c3ad9be2a24656b23c989077e08b16 \
+    --hash=sha256:8a52c7ce7659459f3dc8dec9fd6a6c76f855a0a7e2b61f26090982ac10b95216 \
+    --hash=sha256:c780b44107a547a9e9327270f802fa4d6b0f6667c9c03c3338c0ce812259a0f7 \
+    --hash=sha256:e7058ef6092f995561bf9f71d6c9a4da867b6cc69d2e94cb80184f579a3ceed5
+    # via langgraph-checkpoint
+packaging==25.0 \
+    --hash=sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484 \
+    --hash=sha256:d443872c98d677bf60f6a1f2f8c1cb748e8fe762d2bf9d3148b5599295b0fc4f
+    # via
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   langchain-core
+    #   langfuse
+    #   langsmith
+    #   marshmallow
+pandas==2.3.2 \
+    --hash=sha256:21bb612d148bb5860b7eb2c10faacf1a810799245afd342cf297d7551513fbb6 \
+    --hash=sha256:220cc5c35ffaa764dd5bb17cf42df283b5cb7fdf49e10a7b053a06c9cb48ee2b \
+    --hash=sha256:42c05e15111221384019897df20c6fe893b2f697d03c811ee67ec9e0bb5a3424 \
+    --hash=sha256:52bc29a946304c360561974c6542d1dd628ddafa69134a7131fdfd6a5d7a1a35 \
+    --hash=sha256:ab7b58f8f82706890924ccdfb5f48002b83d2b5a3845976a9fb705d36c34dcdb \
+    --hash=sha256:b62d586eb25cb8cb70a5746a378fc3194cb7f11ea77170d59f889f5dfe3cec7a \
+    --hash=sha256:cc03acc273c5515ab69f898df99d9d4f12c4d70dbfc24c3acc6203751d0804cf \
+    --hash=sha256:d25c20a03e8870f6339bcf67281b946bd20b86f1a544ebbebb87e66a8d642cba
+    # via
+    #   final-assignment-agents-course
+    #   gradio
+pillow==11.3.0 \
+    --hash=sha256:040a5b691b0713e1f6cbe222e0f4f74cd233421e105850ae3b3c0ceda520f42e \
+    --hash=sha256:19d2ff547c75b8e3ff46f4d9ef969a06c30ab2d4263a9e287733aa8b2429ce8f \
+    --hash=sha256:1b9c17fd4ace828b3003dfd1e30bff24863e0eb59b535e8f80194d9cc7ecf860 \
+    --hash=sha256:3828ee7586cd0b2091b6209e5ad53e20d0649bbe87164a459d0676e035e8f523 \
+    --hash=sha256:3cee80663f29e3843b68199b9d6f4f54bd1d4a6b59bdd91bceefc51238bcb967 \
+    --hash=sha256:4445fa62e15936a028672fd48c4c11a66d641d2c05726c7ec1f8ba6a572036ae \
+    --hash=sha256:527b37216b6ac3a12d7838dc3bd75208ec57c1c6d11ef01902266a5a0c14fc27 \
+    --hash=sha256:65dc69160114cdd0ca0f35cb434633c75e8e7fad4cf855177a05bf38678f73ad \
+    --hash=sha256:7107195ddc914f656c7fc8e4a5e1c25f32e9236ea3ea860f257b0436011fddd0 \
+    --hash=sha256:71f511f6b3b91dd543282477be45a033e4845a40278fa8dcdbfdb07109bf18f9 \
+    --hash=sha256:819931d25e57b513242859ce1876c58c59dc31587847bf74cfe06b2e0cb22d2f \
+    --hash=sha256:89bd777bc6624fe4115e9fac3352c79ed60f3bb18651420635f26e643e3dd1f6 \
+    --hash=sha256:8dc70ca24c110503e16918a658b869019126ecfe03109b754c402daff12b3d9f \
+    --hash=sha256:b5f56c3f344f2ccaf0dd875d3e180f631dc60a51b314295a3e681fe8cf851fbe \
+    --hash=sha256:be5463ac478b623b9dd3937afd7fb7ab3d79dd290a28e2b6df292dc75063eb8a \
+    --hash=sha256:cc3e831b563b3114baac7ec2ee86819eb03caa1a2cef0b481a5675b59c4fe23b \
+    --hash=sha256:d000f46e2917c705e9fb93a3606ee4a819d1e3aa7a9b442f6444f07e77cf5e25 \
+    --hash=sha256:e67d793d180c9df62f1f40aee3accca4829d3794c95098887edc18af4b8b780c \
+    --hash=sha256:f1f182ebd2303acf8c380a54f615ec883322593320a9b00438eb842c1f37ae50
+    # via gradio
+primp==0.15.0 \
+    --hash=sha256:1af8ea4b15f57571ff7fc5e282a82c5eb69bc695e19b8ddeeda324397965b30a \
+    --hash=sha256:1b281f4ca41a0c6612d4c6e68b96e28acfe786d226a427cd944baa8d7acd644f \
+    --hash=sha256:489cbab55cd793ceb8f90bb7423c6ea64ebb53208ffcf7a044138e3c66d77299 \
+    --hash=sha256:592f6079646bdf5abbbfc3b0a28dac8de943f8907a250ce09398cda5eaebd260 \
+    --hash=sha256:5a728e5a05f37db6189eb413d22c78bd143fa59dd6a8a26dacd43332b3971fe8 \
+    --hash=sha256:6b84a6ffa083e34668ff0037221d399c24d939b5629cd38223af860de9e17a83 \
+    --hash=sha256:aeb6bd20b06dfc92cfe4436939c18de88a58c640752cf7f30d9e4ae893cdec32 \
+    --hash=sha256:c18b45c23f94016215f62d2334552224236217aaeb716871ce0e4dcfa08eb161 \
+    --hash=sha256:e985a9cba2e3f96a323722e5440aa9eccaac3178e74b884778e926b5249df080
+    # via
+    #   ddgs
+    #   duckduckgo-search
+propcache==0.3.2 \
+    --hash=sha256:0d0fda578d1dc3f77b6b5a5dce3b9ad69a8250a891760a548df850a5e8da87f3 \
+    --hash=sha256:20d7d62e4e7ef05f221e0db2856b979540686342e7dd9973b815599c7057e168 \
+    --hash=sha256:2183111651d710d3097338dd1893fcf09c9f54e27ff1a8795495a16a469cc90b \
+    --hash=sha256:22d9962a358aedbb7a2e36187ff273adeaab9743373a272976d2e348d08c7770 \
+    --hash=sha256:3def3da3ac3ce41562d85db655d18ebac740cb3fa4367f11a52b3da9d03a5cc3 \
+    --hash=sha256:404d70768080d3d3bdb41d0771037da19d8340d50b08e104ca0e7f9ce55fce70 \
+    --hash=sha256:4927842833830942a5d0a56e6f4839bc484785b8e1ce8d287359794818633ba0 \
+    --hash=sha256:55ffda449a507e9fbd4aca1a7d9aa6753b07d6166140e5a18d2ac9bc49eac220 \
+    --hash=sha256:5f559e127134b07425134b4065be45b166183fdcb433cb6c24c8e4149056ad50 \
+    --hash=sha256:6107ddd08b02654a30fb8ad7a132021759d750a82578b94cd55ee2772b6ebea2 \
+    --hash=sha256:64a67fb39229a8a8491dd42f864e5e263155e729c2e7ff723d6e25f596b1e8cb \
+    --hash=sha256:70bd8b9cd6b519e12859c99f3fc9a93f375ebd22a50296c3a295028bea73b9e7 \
+    --hash=sha256:7435d766f978b4ede777002e6b3b6641dd229cd1da8d3d3106a45770365f9ad9 \
+    --hash=sha256:98f1ec44fb675f5052cccc8e609c46ed23a35a1cfd18545ad4e29002d858a43f \
+    --hash=sha256:9bec58347a5a6cebf239daba9bda37dffec5b8d2ce004d9fe4edef3d2815137e \
+    --hash=sha256:9da1cf97b92b51253d5b68cf5a2b9e0dafca095e36b7f2da335e27dc6172a614 \
+    --hash=sha256:aff2e4e06435d61f11a428360a932138d0ec288b0a31dd9bd78d200bd4a2b339 \
+    --hash=sha256:fb075ad271405dcad8e2a7ffc9a750a3bf70e533bd86e89f0603e607b93aa64c
+    # via
+    #   aiohttp
+    #   yarl
+proto-plus==1.26.1 \
+    --hash=sha256:13285478c2dcf2abb829db158e1047e2f1e8d63a077d94263c2b88b043c75a66 \
+    --hash=sha256:21a515a4c4c0088a773899e23c7bbade3d18f9c66c73edd4c7ee3816bc96a012
+    # via
+    #   google-ai-generativelanguage
+    #   google-api-core
+protobuf==6.32.0 \
+    --hash=sha256:501fe6372fd1c8ea2a30b4d9be8f87955a64d6be9c88a973996cef5ef6f0abf1 \
+    --hash=sha256:75a2aab2bd1aeb1f5dc7c5f33bcb11d82ea8c055c9becbb41c26a8c43fd7092c \
+    --hash=sha256:84f9e3c1ff6fb0308dbacb0950d8aa90694b0d0ee68e75719cb044b7078fe741 \
+    --hash=sha256:a81439049127067fc49ec1d36e25c6ee1d1a2b7be930675f919258d03c04e7d2 \
+    --hash=sha256:a8bdbb2f009cfc22a36d031f22a625a38b615b5e19e558a7b756b3279723e68e \
+    --hash=sha256:ba377e5b67b908c8f3072a57b63e2c6a4cbd18aea4ed98d2584350dbf46f2783 \
+    --hash=sha256:d52691e5bee6c860fff9a1c86ad26a13afbeb4b168cd4445c922b7e2cf85aaf0
+    # via
+    #   google-ai-generativelanguage
+    #   google-api-core
+    #   googleapis-common-protos
+    #   grpcio-status
+    #   opentelemetry-proto
+    #   proto-plus
+pyasn1==0.6.1 \
+    --hash=sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629 \
+    --hash=sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034
+    # via
+    #   pyasn1-modules
+    #   rsa
+pyasn1-modules==0.4.2 \
+    --hash=sha256:29253a9207ce32b64c3ac6600edc75368f98473906e8fd1043bd6b5b1de2c14a \
+    --hash=sha256:677091de870a80aae844b1ca6134f54652fa2c8c5a52aa396440ac3106e941e6
+    # via google-auth
+pycparser==2.22 ; platform_python_implementation != 'PyPy' \
+    --hash=sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6 \
+    --hash=sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc
+    # via cffi
+pydantic==2.11.7 \
+    --hash=sha256:d989c3c6cb79469287b1569f7447a17848c998458d49ebe294e975b9baf0f0db \
+    --hash=sha256:dde5df002701f6de26248661f6835bbe296a47bf73990135c7d07ce741b9623b
+    # via
+    #   assemblyai
+    #   fastapi
+    #   gradio
+    #   groq
+    #   langchain
+    #   langchain-core
+    #   langchain-google-genai
+    #   langfuse
+    #   langgraph
+    #   langsmith
+    #   ollama
+    #   openai
+    #   pydantic-settings
+pydantic-core==2.33.2 \
+    --hash=sha256:0069c9acc3f3981b9ff4cdfaf088e98d83440a4c7ea1bc07460af3d4dc22e72d \
+    --hash=sha256:031c57d67ca86902726e0fae2214ce6770bbe2f710dc33063187a68744a5ecac \
+    --hash=sha256:0405262705a123b7ce9f0b92f123334d67b70fd1f20a9372b907ce1080c7ba02 \
+    --hash=sha256:0a39979dcbb70998b0e505fb1556a1d550a0781463ce84ebf915ba293ccb7e22 \
+    --hash=sha256:0e03262ab796d986f978f79c943fc5f620381be7287148b8010b4097f79a39ec \
+    --hash=sha256:0e5b2671f05ba48b94cb90ce55d8bdcaaedb8ba00cc5359f6810fc918713983d \
+    --hash=sha256:1a8695a8d00c73e50bff9dfda4d540b7dee29ff9b8053e38380426a85ef10052 \
+    --hash=sha256:2058a32994f1fde4ca0480ab9d1e75a0e8c87c22b53a3ae66554f9af78f2fe8c \
+    --hash=sha256:2b3d326aaef0c0399d9afffeb6367d5e26ddc24d351dbc9c636840ac355dc5d8 \
+    --hash=sha256:4b25d91e288e2c4e0662b8038a28c6a07eaac3e196cfc4ff69de4ea3db992a1b \
+    --hash=sha256:5c4aa4e82353f65e548c476b37e64189783aa5384903bfea4f41580f255fddfa \
+    --hash=sha256:6bdfe4b3789761f3bcb4b1ddf33355a71079858958e3a552f16d5af19768fef2 \
+    --hash=sha256:73662edf539e72a9440129f231ed3757faab89630d291b784ca99237fb94db2b \
+    --hash=sha256:7cb8bc3605c29176e1b105350d2e6474142d7c1bd1d9327c4a9bdb46bf827acc \
+    --hash=sha256:87b31b6846e361ef83fedb187bb5b4372d0da3f7e28d85415efa92d6125d6e6d \
+    --hash=sha256:a11c8d26a50bfab49002947d3d237abe4d9e4b5bdc8846a63537b6488e197808 \
+    --hash=sha256:aa9d91b338f2df0508606f7009fde642391425189bba6d8c653afd80fd6bb64e \
+    --hash=sha256:b0379a2b24882fef529ec3b4987cb5d003b9cda32256024e6fe1586ac45fc640 \
+    --hash=sha256:d53b22f2032c42eaaf025f7c40c2e3b94568ae077a606f006d206a463bc69572 \
+    --hash=sha256:d946c8bf0d5c24bf4fe333af284c59a19358aa3ec18cb3dc4370080da1e8ad29 \
+    --hash=sha256:efec8db3266b76ef9607c2c4c419bdb06bf335ae433b80816089ea7585816f6a \
+    --hash=sha256:f8de619080e944347f5f20de29a975c2d815d9ddd8be9b9b7268e2e3ef68605a \
+    --hash=sha256:fa754d1850735a0b0e03bcffd9d4b4343eb417e47196e4485d9cca326073a42c
+    # via pydantic
+pydantic-settings==2.10.1 \
+    --hash=sha256:06f0062169818d0f5524420a360d632d5857b83cffd4d42fe29597807a1614ee \
+    --hash=sha256:a60952460b99cf661dc25c29c0ef171721f98bfcb52ef8d9ea4c943d7c8cc796
+    # via langchain-community
+pydub==0.25.1 \
+    --hash=sha256:65617e33033874b59d87db603aa1ed450633288aefead953b30bded59cb599a6 \
+    --hash=sha256:980a33ce9949cab2a569606b65674d748ecbca4f0796887fd6f46173a7b0d30f
+    # via gradio
+pygments==2.19.2 ; sys_platform != 'emscripten' \
+    --hash=sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887 \
+    --hash=sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b
+    # via rich
+python-dateutil==2.9.0.post0 \
+    --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \
+    --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427
+    # via pandas
+python-dotenv==1.1.1 \
+    --hash=sha256:31f23644fe2602f88ff55e1f5c79ba497e01224ee7737937930c448e4d0e24dc \
+    --hash=sha256:a8a6399716257f45be6a007360200409fce5cda2661e3dec71d23dc15f6189ab
+    # via
+    #   final-assignment-agents-course
+    #   pydantic-settings
+python-multipart==0.0.20 \
+    --hash=sha256:8a62d3a8335e06589fe01f2a3e178cdcc632f3fbe0d492ad9ee0ec35aab1f104 \
+    --hash=sha256:8dd0cab45b8e23064ae09147625994d090fa46f5b0d1e13af944c331a7fa9d13
+    # via gradio
+pytz==2025.2 \
+    --hash=sha256:360b9e3dbb49a209c21ad61809c7fb453643e048b38924c765813546746e81c3 \
+    --hash=sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00
+    # via pandas
+pyyaml==6.0.2 \
+    --hash=sha256:0a9a2848a5b7feac301353437eb7d5957887edbf81d56e903999a75a3d743086 \
+    --hash=sha256:23502f431948090f597378482b4812b0caae32c22213aecf3b55325e049a6c68 \
+    --hash=sha256:29717114e51c84ddfba879543fb232a6ed60086602313ca38cce623c1d62cfbf \
+    --hash=sha256:2e99c6826ffa974fe6e27cdb5ed0021786b03fc98e5ee3c5bfe1fd5015f42b99 \
+    --hash=sha256:7c36280e6fb8385e520936c3cb3b8042851904eba0e58d277dca80a5cfed590b \
+    --hash=sha256:8824b5a04a04a047e72eea5cec3bc266db09e35de6bdfe34c9436ac5ee27d237 \
+    --hash=sha256:936d68689298c36b53b29f23c6dbb74de12b4ac12ca6cfe0e047bedceea56180 \
+    --hash=sha256:a4d3091415f010369ae4ed1fc6b79def9416358877534caf6a0fdd2146c87a3e \
+    --hash=sha256:d584d9ec91ad65861cc08d42e834324ef890a082e591037abe114850ff7bbc3e \
+    --hash=sha256:ec031d5d2feb36d1d1a24380e4db6d43695f3748343d99434e6f5f9156aaa2ed
+    # via
+    #   gradio
+    #   huggingface-hub
+    #   langchain
+    #   langchain-community
+    #   langchain-core
+regex==2025.9.1 \
+    --hash=sha256:113d5aa950f428faf46fd77d452df62ebb4cc6531cb619f6cc30a369d326bfbd \
+    --hash=sha256:1ec2bd3bdf0f73f7e9f48dca550ba7d973692d5e5e9a90ac42cc5f16c4432d8b \
+    --hash=sha256:4bcdff370509164b67a6c8ec23c9fb40797b72a014766fdc159bb809bd74f7d8 \
+    --hash=sha256:5c3b96ed0223b32dbdc53a83149b6de7ca3acd5acd9c8e64b42a166228abe29c \
+    --hash=sha256:67a74456f410fe5e869239ee7a5423510fe5121549af133809d9591a8075893f \
+    --hash=sha256:7383efdf6e8e8c61d85e00cfb2e2e18da1a621b8bfb4b0f1c2747db57b942b8f \
+    --hash=sha256:88ac07b38d20b54d79e704e38aa3bd2c0f8027432164226bdee201a1c0c9c9ff \
+    --hash=sha256:8c2ff5c01d5e47ad5fc9d31bcd61e78c2fa0068ed00cab86b7320214446da766 \
+    --hash=sha256:94533e32dc0065eca43912ee6649c90ea0681d59f56d43c45b5bcda9a740b3dd \
+    --hash=sha256:9627e887116c4e9c0986d5c3b4f52bcfe3df09850b704f62ec3cbf177a0ae374 \
+    --hash=sha256:a874a61bb580d48642ffd338570ee24ab13fa023779190513fcacad104a6e251 \
+    --hash=sha256:c5aa2a6a73bf218515484b36a0d20c6ad9dc63f6339ff6224147b0e2c095ee55 \
+    --hash=sha256:d49dc84e796b666181de8a9973284cad6616335f01b52bf099643253094920fc \
+    --hash=sha256:d9914fe1040874f83c15fcea86d94ea54091b0666eab330aaab69e30d106aabe \
+    --hash=sha256:e71bceb3947362ec5eabd2ca0870bb78eae4edfc60c6c21495133c01b6cd2df4 \
+    --hash=sha256:fcdeb38de4f7f3d69d798f4f371189061446792a84e7c92b50054c87aae9c07c
+    # via tiktoken
+requests==2.32.5 \
+    --hash=sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6 \
+    --hash=sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf
+    # via
+    #   arxiv
+    #   final-assignment-agents-course
+    #   google-api-core
+    #   huggingface-hub
+    #   langchain
+    #   langchain-community
+    #   langfuse
+    #   langsmith
+    #   opentelemetry-exporter-otlp-proto-http
+    #   requests-toolbelt
+    #   tiktoken
+    #   wikipedia
+    #   youtube-transcript-api
+requests-toolbelt==1.0.0 \
+    --hash=sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6 \
+    --hash=sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06
+    # via langsmith
+rich==14.1.0 ; sys_platform != 'emscripten' \
+    --hash=sha256:536f5f1785986d6dbdea3c75205c473f970777b4a0d6c6dd1b696aa05a3fa04f \
+    --hash=sha256:e497a48b844b0320d45007cdebfeaeed8db2a4f4bcf49f15e455cfc4af11eaa8
+    # via typer
+rsa==4.9.1 \
+    --hash=sha256:68635866661c6836b8d39430f97a996acbd61bfa49406748ea243539fe239762 \
+    --hash=sha256:e7bdbfdb5497da4c07dfd35530e1a902659db6ff241e39d9953cad06ebd0ae75
+    # via google-auth
+ruff==0.12.12 ; sys_platform != 'emscripten' \
+    --hash=sha256:01543c137fd3650d322922e8b14cc133b8ea734617c4891c5a9fccf4bfc9aa92 \
+    --hash=sha256:0c0945246f5ad776cb8925e36af2438e66188d2b57d9cf2eed2c382c58b371e5 \
+    --hash=sha256:173be2bfc142af07a01e3a759aba6f7791aa47acf3604f610b1c36db888df7b1 \
+    --hash=sha256:26a1b5a2bf7dd2c47e3b46d077cd9c0fc3b93e6c6cc9ed750bd312ae9dc302ee \
+    --hash=sha256:2a8199cab4ce4d72d158319b63370abf60991495fb733db96cd923a34c52d093 \
+    --hash=sha256:2afc2fa864197634e549d87fb1e7b6feb01df0a80fd510d6489e1ce8c0b1cc45 \
+    --hash=sha256:42a67d16e5b1ffc6d21c5f67851e0e769517fb57a8ebad1d0781b30888aa704e \
+    --hash=sha256:59f909c0fdd8f1dcdbfed0b9569b8bf428cf144bec87d9de298dcd4723f5bee8 \
+    --hash=sha256:5f12856123b0ad0147d90b3961f5c90e7427f9acd4b40050705499c98983f489 \
+    --hash=sha256:7acd6045e87fac75a0b0cdedacf9ab3e1ad9d929d149785903cff9bb69ad9727 \
+    --hash=sha256:968e77094b1d7a576992ac078557d1439df678a34c6fe02fd979f973af167577 \
+    --hash=sha256:9ac93d87047e765336f0c18eacad51dad0c1c33c9df7484c40f98e1d773876f5 \
+    --hash=sha256:a0fbafe8c58e37aae28b84a80ba1817f2ea552e9450156018a478bf1fa80f4e4 \
+    --hash=sha256:abf4073688d7d6da16611f2f126be86523a8ec4343d15d276c614bda8ec44edb \
+    --hash=sha256:b216ec0a0674e4b1214dcc998a5088e54eaf39417327b19ffefba1c4a1e4971e \
+    --hash=sha256:b86cd3415dbe31b3b46a71c598f4c4b2f550346d1ccf6326b347cc0c8fd063d6 \
+    --hash=sha256:b9c456fb2fc8e1282affa932c9e40f5ec31ec9cbb66751a316bd131273b57c23 \
+    --hash=sha256:de1c4b916d98ab289818e55ce481e2cacfaad7710b01d1f990c497edf217dafc \
+    --hash=sha256:e99620bf01884e5f38611934c09dd194eb665b0109104acae3ba6102b600fd0d
+    # via gradio
+safehttpx==0.1.6 \
+    --hash=sha256:407cff0b410b071623087c63dd2080c3b44dc076888d8c5823c00d1e58cb381c \
+    --hash=sha256:b356bfc82cee3a24c395b94a2dbeabbed60aff1aa5fa3b5fe97c4f2456ebce42
+    # via gradio
+semantic-version==2.10.0 \
+    --hash=sha256:bdabb6d336998cbb378d4b9db3a4b56a1e3235701dc05ea2690d9a997ed5041c \
+    --hash=sha256:de78a3b8e0feda74cabc54aab2da702113e33ac9d9eb9d2389bcf1f58b7d9177
+    # via gradio
+sgmllib3k==1.0.0 \
+    --hash=sha256:7868fb1c8bfa764c1ac563d3cf369c381d1325d36124933a726f29fcdaa812e9
+    # via feedparser
+shellingham==1.5.4 ; sys_platform != 'emscripten' \
+    --hash=sha256:7ecfff8f2fd72616f7481040475a65b2bf8af90a56c89140852d1120324e8686 \
+    --hash=sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de
+    # via typer
+six==1.17.0 \
+    --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \
+    --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81
+    # via
+    #   markdownify
+    #   python-dateutil
+sniffio==1.3.1 \
+    --hash=sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2 \
+    --hash=sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc
+    # via
+    #   anyio
+    #   groq
+    #   openai
+soupsieve==2.8 \
+    --hash=sha256:0cc76456a30e20f5d7f2e14a98a4ae2ee4e5abdc7c5ea0aafe795f344bc7984c \
+    --hash=sha256:e2dd4a40a628cb5f28f6d4b0db8800b8f581b65bb380b97de22ba5ca8d72572f
+    # via beautifulsoup4
+sqlalchemy==2.0.43 \
+    --hash=sha256:022e436a1cb39b13756cf93b48ecce7aa95382b9cfacceb80a7d263129dfd019 \
+    --hash=sha256:1681c21dd2ccee222c2fe0bef671d1aef7c504087c9c4e800371cfcc8ac966fc \
+    --hash=sha256:4bf0edb24c128b7be0c61cd17eef432e4bef507013292415f3fb7023f02b7d4b \
+    --hash=sha256:70322986c0c699dca241418fcf18e637a4369e0ec50540a2b907b184c8bca069 \
+    --hash=sha256:788bfcef6787a7764169cfe9859fe425bf44559619e1d9f56f5bddf2ebf6f417 \
+    --hash=sha256:87accdbba88f33efa7b592dc2e8b2a9c2cdbca73db2f9d5c510790428c09c154 \
+    --hash=sha256:9c2e02f06c68092b875d5cbe4824238ab93a7fa35d9c38052c033f7ca45daa18 \
+    --hash=sha256:c00e7845d2f692ebfc7d5e4ec1a3fd87698e4337d09e58d6749a16aedfdf8612 \
+    --hash=sha256:c5e73ba0d76eefc82ec0219d2301cb33bfe5205ed7a2602523111e2e56ccbd20 \
+    --hash=sha256:e7a903b5b45b0d9fa03ac6a331e1c1d6b7e0ab41c63b6217b3d10357b83c8b00
+    # via
+    #   langchain
+    #   langchain-community
+starlette==0.47.3 \
+    --hash=sha256:6bc94f839cc176c4858894f1f8908f0ab79dfec1a6b8402f6da9be26ebea52e9 \
+    --hash=sha256:89c0778ca62a76b826101e7c709e70680a1699ca7da6b44d38eb0a7e61fe4b51
+    # via
+    #   fastapi
+    #   gradio
+tenacity==9.1.2 \
+    --hash=sha256:1169d376c297e7de388d18b4481760d478b0e99a777cad3a9c86e556f4b697cb \
+    --hash=sha256:f77bf36710d8b73a50b2dd155c97b870017ad21afe6ab300326b0371b3b05138
+    # via
+    #   langchain-community
+    #   langchain-core
+tiktoken==0.11.0 \
+    --hash=sha256:10331d08b5ecf7a780b4fe4d0281328b23ab22cdb4ff65e68d56caeda9940ecc \
+    --hash=sha256:195d84bec46169af3b1349a1495c151d37a0ff4cba73fd08282736be7f92cc6c \
+    --hash=sha256:3c518641aee1c52247c2b97e74d8d07d780092af79d5911a6ab5e79359d9b06a \
+    --hash=sha256:8a9b517d6331d7103f8bef29ef93b3cca95fa766e293147fe7bacddf310d5917 \
+    --hash=sha256:b062c82300341dc87e0258c69f79bed725f87e753c21887aea90d272816be882 \
+    --hash=sha256:b4ddb1849e6bf0afa6cc1c5d809fb980ca240a5fffe585a04e119519758788c0 \
+    --hash=sha256:fe91581b0ecdd8783ce8cb6e3178f2260a3912e8724d2f2d49552b98714641a1
+    # via langchain-openai
+tokenizers==0.22.0 \
+    --hash=sha256:1626cb186e143720c62c6c6b5371e62bbc10af60481388c0da89bc903f37ea0c \
+    --hash=sha256:2e33b98525be8453f355927f3cab312c36cd3e44f4d7e9e97da2fa94d0a49dcb \
+    --hash=sha256:4136e1558a9ef2e2f1de1555dcd573e1cbc4a320c1a06c4107a3d46dc8ac6e4b \
+    --hash=sha256:71784b9ab5bf0ff3075bceeb198149d2c5e068549c0d18fe32d06ba0deb63f79 \
+    --hash=sha256:76cf6757c73a10ef10bf06fa937c0ec7393d90432f543f49adc8cab3fb6f26cb \
+    --hash=sha256:790bad50a1b59d4c21592f9c3cf5e5cf9c3c7ce7e1a23a739f13e01fb1be377a \
+    --hash=sha256:8337ca75d0731fc4860e6204cc24bb36a67d9736142aa06ed320943b50b1e7ed \
+    --hash=sha256:a89264e26f63c449d8cded9061adea7b5de53ba2346fc7e87311f7e4117c1cc8 \
+    --hash=sha256:c78174859eeaee96021f248a56c801e36bfb6bd5b067f2e95aa82445ca324f00 \
+    --hash=sha256:cdf5954de3962a5fd9781dc12048d24a1a6f1f5df038c6e95db328cd22964206 \
+    --hash=sha256:da589a61cbfea18ae267723d6b029b84598dc8ca78db9951d8f5beff72d8507c \
+    --hash=sha256:dbf9d6851bddae3e046fedfb166f47743c1c7bd11c640f0691dd35ef0bcad3be \
+    --hash=sha256:ea8562fa7498850d02a16178105b58803ea825b50dc9094d60549a7ed63654bb \
+    --hash=sha256:eaa9620122a3fb99b943f864af95ed14c8dfc0f47afa3b404ac8c16b3f2bb484 \
+    --hash=sha256:ec5b71f668a8076802b0241a42387d48289f25435b86b769ae1837cad4172a17
+    # via langchain-huggingface
+tomlkit==0.13.3 \
+    --hash=sha256:430cf247ee57df2b94ee3fbe588e71d362a941ebb545dec29b53961d61add2a1 \
+    --hash=sha256:c89c649d79ee40629a9fda55f8ace8c6a1b42deb912b2a8fd8d942ddadb606b0
+    # via gradio
+tqdm==4.67.1 \
+    --hash=sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2 \
+    --hash=sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2
+    # via
+    #   huggingface-hub
+    #   openai
+typer==0.17.3 ; sys_platform != 'emscripten' \
+    --hash=sha256:0c600503d472bcf98d29914d4dcd67f80c24cc245395e2e00ba3603c9332e8ba \
+    --hash=sha256:643919a79182ab7ac7581056d93c6a2b865b026adf2872c4d02c72758e6f095b
+    # via gradio
+typing-extensions==4.15.0 \
+    --hash=sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466 \
+    --hash=sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548
+    # via
+    #   aiosignal
+    #   anyio
+    #   assemblyai
+    #   beautifulsoup4
+    #   exceptiongroup
+    #   fastapi
+    #   gradio
+    #   gradio-client
+    #   groq
+    #   huggingface-hub
+    #   langchain-core
+    #   multidict
+    #   openai
+    #   opentelemetry-api
+    #   opentelemetry-exporter-otlp-proto-http
+    #   opentelemetry-sdk
+    #   opentelemetry-semantic-conventions
+    #   pydantic
+    #   pydantic-core
+    #   sqlalchemy
+    #   starlette
+    #   typer
+    #   typing-inspect
+    #   typing-inspection
+    #   uvicorn
+typing-inspect==0.9.0 \
+    --hash=sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f \
+    --hash=sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78
+    # via dataclasses-json
+typing-inspection==0.4.1 \
+    --hash=sha256:389055682238f53b04f7badcb49b989835495a96700ced5dab2d8feae4b26f51 \
+    --hash=sha256:6ae134cc0203c33377d43188d4064e9b357dba58cff3185f22924610e70a9d28
+    # via
+    #   pydantic
+    #   pydantic-settings
+tzdata==2025.2 \
+    --hash=sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8 \
+    --hash=sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9
+    # via pandas
+urllib3==2.5.0 \
+    --hash=sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760 \
+    --hash=sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc
+    # via
+    #   gradio
+    #   requests
+uvicorn==0.35.0 ; sys_platform != 'emscripten' \
+    --hash=sha256:197535216b25ff9b785e29a0b79199f55222193d47f820816e7da751e9bc8d4a \
+    --hash=sha256:bc662f087f7cf2ce11a1d7fd70b90c9f98ef2e2831556dd078d131b96cc94a01
+    # via gradio
+websockets==15.0.1 \
+    --hash=sha256:0a34631031a8f05657e8e90903e656959234f3a04552259458aac0b0f9ae6fd9 \
+    --hash=sha256:0c9e74d766f2818bb95f84c25be4dea09841ac0f734d1966f415e4edfc4ef1c3 \
+    --hash=sha256:0fdfe3e2a29e4db3659dbd5bbf04560cea53dd9610273917799f1cde46aa725e \
+    --hash=sha256:1009ee0c7739c08a0cd59de430d6de452a55e42d6b522de7aa15e6f67db0b8e1 \
+    --hash=sha256:1234d4ef35db82f5446dca8e35a7da7964d02c127b095e172e54397fb6a6c256 \
+    --hash=sha256:39c1fec2c11dc8d89bba6b2bf1556af381611a173ac2b511cf7231622058af41 \
+    --hash=sha256:3d00075aa65772e7ce9e990cab3ff1de702aa09be3940d1dc88d5abf1ab8a09c \
+    --hash=sha256:4c2529b320eb9e35af0fa3016c187dffb84a3ecc572bcee7c3ce302bfeba52bf \
+    --hash=sha256:5756779642579d902eed757b21b0164cd6fe338506a8083eb58af5c372e39d9a \
+    --hash=sha256:5df592cd503496351d6dc14f7cdad49f268d8e618f80dce0cd5a36b93c3fc08d \
+    --hash=sha256:76d1f20b1c7a2fa82367e04982e708723ba0e7b8d43aa643d3dcd404d74f1475 \
+    --hash=sha256:82544de02076bafba038ce055ee6412d68da13ab47f0c60cab827346de828dee \
+    --hash=sha256:ac1e5c9054fe23226fb11e05a6e630837f074174c4c2f0fe442996112a6de4fb \
+    --hash=sha256:ac60e3b188ec7574cb761b08d50fcedf9d77f1530352db4eef1707fe9dee7205 \
+    --hash=sha256:b359ed09954d7c18bbc1680f380c7301f92c60bf924171629c5db97febb12f04 \
+    --hash=sha256:cad21560da69f4ce7658ca2cb83138fb4cf695a2ba3e475e0559e05991aa8122 \
+    --hash=sha256:d63efaa0cd96cf0c5fe4d581521d9fa87744540d4bc999ae6e08595a1014b45b \
+    --hash=sha256:f29d80eb9a9263b8d109135351caf568cc3f80b9928bccde535c235de55c22d9 \
+    --hash=sha256:f7a866fbc1e97b5c617ee4116daaa09b722101d4a3c170c787450ba409f9736f
+    # via
+    #   assemblyai
+    #   gradio-client
+wikipedia==1.4.0 \
+    --hash=sha256:db0fad1829fdd441b1852306e9856398204dc0786d2996dd2e0c8bb8e26133b2
+    # via final-assignment-agents-course
+wrapt==1.17.3 \
+    --hash=sha256:33486899acd2d7d3066156b03465b949da3fd41a5da6e394ec49d271baefcf05 \
+    --hash=sha256:343e44b2a8e60e06a7e0d29c1671a0d9951f59174f3709962b5143f60a2a98bd \
+    --hash=sha256:7171ae35d2c33d326ac19dd8facb1e82e5fd04ef8c6c0e394d7af55a55051c22 \
+    --hash=sha256:88bbae4d40d5a46142e70d58bf664a89b6b4befaea7b2ecc14e03cedb8e06c04 \
+    --hash=sha256:a36692b8491d30a8c75f1dfee65bef119d6f39ea84ee04d9f9311f83c5ad9390 \
+    --hash=sha256:af338aa93554be859173c39c85243970dc6a289fa907402289eeae7543e1ae18 \
+    --hash=sha256:afd964fd43b10c12213574db492cb8f73b2f0826c8df07a68288f8f19af2ebe6 \
+    --hash=sha256:e6b13af258d6a9ad602d57d889f83b9d5543acd471eee12eb51f5b01f8eb1bc2 \
+    --hash=sha256:e6f40a8aa5a92f150bdb3e1c44b7e98fb7113955b2e5394122fa5532fec4b418 \
+    --hash=sha256:f66eb08feaa410fe4eebd17f2a2c8e2e46d3476e9f8c783daa8e09e0faa666d0 \
+    --hash=sha256:f9b2601381be482f70e5d1051a5965c25fb3625455a2bf520b5a077b22afb775 \
+    --hash=sha256:fd341868a4b6714a5962c1af0bd44f7c404ef78720c7de4892901e540417111c
+    # via langfuse
+xlrd==2.0.2 \
+    --hash=sha256:08b5e25de58f21ce71dc7db3b3b8106c1fa776f3024c54e45b45b374e89234c9 \
+    --hash=sha256:ea762c3d29f4cca48d82df517b6d89fbce4db3107f9d78713e48cd321d5c9aa9
+    # via final-assignment-agents-course
+xxhash==3.5.0 \
+    --hash=sha256:1328f6d8cca2b86acb14104e381225a3d7b42c92c4b86ceae814e5c400dbb415 \
+    --hash=sha256:2014c5b3ff15e64feecb6b713af12093f75b7926049e26a580e94dcad3c73d8c \
+    --hash=sha256:3171f693dbc2cef6477054a665dc255d996646b4023fe56cb4db80e26f4cc520 \
+    --hash=sha256:3dbbd9892c5ebffeca1ed620cf0ade13eb55a0d8c84e0751a6653adc6ac40d0c \
+    --hash=sha256:4cc2d67fdb4d057730c75a64c5923abfa17775ae234a71b0200346bfb0a7f482 \
+    --hash=sha256:4e2febf914ace002132aa09169cc572e0d8959d0f305f93d5828c4836f9bc5a6 \
+    --hash=sha256:5a74f23335b9689b66eb6dbe2a931a88fcd7a4c2cc4b1cb0edba8ce381c7a1da \
+    --hash=sha256:5d0d307d27099bb0cbeea7260eb39ed4fdb99c5542e21e94bb6fd29e49c57a23 \
+    --hash=sha256:5d3a10609c51da2a1c0ea0293fc3968ca0a18bd73838455b5bca3069d7f8e32b \
+    --hash=sha256:61c722ed8d49ac9bc26c7071eeaa1f6ff24053d553146d5df031802deffd03da \
+    --hash=sha256:7c5d3e570ef46adaf93fc81b44aca6002b5a4d8ca11bd0580c07eac537f36680 \
+    --hash=sha256:7cb29a034301e2982df8b1fe6328a84f4b676106a13e9135a0d7e0c3e9f806da \
+    --hash=sha256:84f2caddf951c9cbf8dc2e22a89d4ccf5d86391ac6418fe81e3c67d0cf60b45f \
+    --hash=sha256:893074d651cf25c1cc14e3bea4fceefd67f2921b1bb8e40fcfeba56820de80c6 \
+    --hash=sha256:8d47ebd9f5d9607fd039c1fbf4994e3b071ea23eff42f4ecef246ab2b7334198 \
+    --hash=sha256:9bed5144c6923cc902cd14bb8963f2d5e034def4486ab0bbe1f58f03f042f9a9 \
+    --hash=sha256:b96d559e0fcddd3343c510a0fe2b127fbff16bf346dd76280b82292567523442 \
+    --hash=sha256:c0342aafd421795d740e514bc9858ebddfc705a75a8c5046ac56d85fe97bf196 \
+    --hash=sha256:ec28adb204b759306a3d64358a5e5c07d7b1dd0ccbce04aa76cb9377b7b70296 \
+    --hash=sha256:ece616532c499ee9afbb83078b1b952beffef121d989841f7f4b3dc5ac0fd212 \
+    --hash=sha256:fab81ef75003eda96239a23eda4e4543cedc22e34c373edcaf744e721a163986
+    # via langgraph
+yarl==1.20.1 \
+    --hash=sha256:0c869f2651cc77465f6cd01d938d91a11d9ea5d798738c1dc077f3de0b5e5fed \
+    --hash=sha256:1f8a891e4a22a89f5dde7862994485e19db246b70bb288d3ce73a34422e55b23 \
+    --hash=sha256:21242b4288a6d56f04ea193adde174b7e347ac46ce6bc84989ff7c1b1ecea84e \
+    --hash=sha256:2c7b34d804b8cf9b214f05015c4fee2ebe7ed05cf581e7192c06555c71f4446a \
+    --hash=sha256:33f29ecfe0330c570d997bcf1afd304377f2e48f61447f37e846a6058a4d33b2 \
+    --hash=sha256:41ebd28167bc6af8abb97fec1a399f412eec5fd61a3ccbe2305a18b84fb4ca73 \
+    --hash=sha256:46b5e0ccf1943a9a6e766b2c2b8c732c55b34e28be57d8daa2b3c1d1d4009309 \
+    --hash=sha256:6032e6da6abd41e4acda34d75a816012717000fa6839f37124a47fcefc49bec4 \
+    --hash=sha256:62915e6688eb4d180d93840cda4110995ad50c459bf931b8b3775b37c264af1e \
+    --hash=sha256:6c4fbf6b02d70e512d7ade4b1f998f237137f1417ab07ec06358ea04f69134f8 \
+    --hash=sha256:76d12524d05841276b0e22573f28d5fbcb67589836772ae9244d90dd7d66aa13 \
+    --hash=sha256:835ab2cfc74d5eb4a6a528c57f05688099da41cf4957cf08cad38647e4a83b30 \
+    --hash=sha256:83b8eb083fe4683c6115795d9fc1cfaf2cbbefb19b3a1cb68f6527460f483a77 \
+    --hash=sha256:aef6c4d69554d44b7f9d923245f8ad9a707d971e6209d51279196d8e8fe1ae16 \
+    --hash=sha256:b982fa7f74c80d5c0c7b5b38f908971e513380a10fecea528091405f519b9ebb \
+    --hash=sha256:bea21cdae6c7eb02ba02a475f37463abfe0a01f5d7200121b03e605d6a0439f8 \
+    --hash=sha256:d017a4997ee50c91fd5466cef416231bb82177b93b029906cefc542ce14c35ac \
+    --hash=sha256:dd803820d44c8853a109a34e3660e5a61beae12970da479cf44aa2954019bf70 \
+    --hash=sha256:df47c55f7d74127d1b11251fe6397d84afdde0d53b90bedb46a23c0e534f9d24
+    # via aiohttp
+youtube-transcript-api==1.2.2 \
+    --hash=sha256:5f67cfaff3621d969778817a3d7b2172c16784855f45fcaed4f0529632e2fef4 \
+    --hash=sha256:feca8c7f7c9d65188ef6377fc0e01cf466e6b68f1b3e648019646ab342f994d2
+    # via final-assignment-agents-course
+zipp==3.23.0 \
+    --hash=sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e \
+    --hash=sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166
+    # via importlib-metadata
+zstandard==0.24.0 \
+    --hash=sha256:0c9c3cba57f5792532a3df3f895980d47d78eda94b0e5b800651b53e96e0b604 \
+    --hash=sha256:0f6d9a146e07458cb41423ca2d783aefe3a3a97fe72838973c13b8f1ecc7343a \
+    --hash=sha256:35f13501a8accf834457d8e40e744568287a215818778bc4d79337af2f3f0d97 \
+    --hash=sha256:388aad2d693707f4a0f6cc687eb457b33303d6b57ecf212c8ff4468c34426892 \
+    --hash=sha256:561123d05681197c0e24eb8ab3cfdaf299e2b59c293d19dad96e1610ccd8fbc6 \
+    --hash=sha256:5e941654cef13a1d53634ec30933722eda11f44f99e1d0bc62bbce3387580d50 \
+    --hash=sha256:7ac6e4d727521d86d20ec291a3f4e64a478e8a73eaee80af8f38ec403e77a409 \
+    --hash=sha256:7de5869e616d426b56809be7dc6dba4d37b95b90411ccd3de47f421a42d4d42c \
+    --hash=sha256:869bf13f66b124b13be37dd6e08e4b728948ff9735308694e0b0479119e08ea7 \
+    --hash=sha256:87ae1684bc3c02d5c35884b3726525eda85307073dbefe68c3c779e104a59036 \
+    --hash=sha256:92be52ca4e6e604f03d5daa079caec9e04ab4cbf6972b995aaebb877d3d24e13 \
+    --hash=sha256:962ea3aecedcc944f8034812e23d7200d52c6e32765b8da396eeb8b8ffca71ce \
+    --hash=sha256:af1394c2c5febc44e0bbf0fc6428263fa928b50d1b1982ce1d870dc793a8e5f4 \
+    --hash=sha256:bf02f915fa7934ea5dfc8d96757729c99a8868b7c340b97704795d6413cf5fe6 \
+    --hash=sha256:d6975f2d903bc354916a17b91a7aaac7299603f9ecdb788145060dde6e573a16 \
+    --hash=sha256:dd91b0134a32dfcd8be504e8e46de44ad0045a569efc25101f2a12ccd41b5759 \
+    --hash=sha256:fe3198b81c00032326342d973e526803f183f97aa9e9a98e3f897ebafe21178f
+    # via langsmith

tools.py

@@ -0,0 +1,348 @@
+import base64
+import math
+import os
+import re
+from typing import Optional
+
+import pandas as pd
+import requests
+from dotenv import load_dotenv
+from langchain_core.messages import HumanMessage
+from langchain_core.tools import tool
+from langchain_google_genai import ChatGoogleGenerativeAI
+from markdownify import markdownify
+from requests.exceptions import RequestException
+
+# Built-in LangChain tools
+from langchain_community.tools import (
+    WikipediaQueryRun,
+    DuckDuckGoSearchRun,
+    ArxivQueryRun,
+    ShellTool,
+)
+from langchain_community.utilities import (
+    WikipediaAPIWrapper,
+    DuckDuckGoSearchAPIWrapper,
+    ArxivAPIWrapper,
+)
+from langchain_experimental.tools import PythonREPLTool
+from langchain_community.document_loaders import AssemblyAIAudioTranscriptLoader
+from langchain_community.document_loaders.assemblyai import TranscriptFormat
+
+# Youtube related tools
+from youtube_transcript import (
+    get_youtube_transcript_tool,
+    get_youtube_title_description_tool,
+)
+
+load_dotenv()
+
+# Initialize vision_llm at module level (commented out by default)
+# Uncomment and configure as needed
+# vision_llm = ChatOllama(
+#     model="qwen2-vl:7b",
+#     base_url="http://localhost:11434"
+# )
+vision_llm = ChatGoogleGenerativeAI(model=os.getenv("GOOGLE_VISION_MODEL"))
+
+# ============== CUSTOM TOOLS (not available in LangChain) ==============
+
+
+@tool
+def reverse_text(text: str) -> str:
+    """
+    Reverse the given text character by character.
+
+    Example:
+    Input: "hello"
+    Output: "olleh"
+    """
+    return text[::-1]
+
+
+@tool
+def reverse_words(text: str) -> str:
+    """
+    Reverse the order of words in the given text.
+
+    Example:
+    Input: "LangChain makes graphs easy"
+    Output: "easy graphs makes LangChain"
+    """
+    return " ".join(text.split()[::-1])
+
+
+@tool
+def calculator(expression: str) -> str:
+    """
+    Perform mathematical calculations safely. Supports basic arithmetic operations.
+
+    Example:
+    Input: "10 + 2 * 3 - 4 / 2"
+    Output: "14.0"
+    """
+    try:
+        # Safe evaluation - only allow basic math operations
+        allowed_chars = set("0123456789+-*/.() ")
+        if all(c in allowed_chars for c in expression):
+            result = eval(expression)
+            return str(result)
+        else:
+            return "Error: Invalid characters in expression"
+    except Exception as e:
+        return f"Calculation error: {str(e)}"
+
+
+@tool
+def advanced_math(operation: str, num1: float, num2: Optional[float] = None) -> str:
+    """
+    Perform advanced math operations.
+    Supported: sqrt, log, sin, cos, tan, power.
+
+    Examples:
+    Input: operation="sqrt", num1=16
+    Output: "4.0"
+
+    Input: operation="power", num1=2, num2=3
+    Output: "8.0"
+    """
+    try:
+        if operation == "sqrt":
+            return str(math.sqrt(num1))
+        elif operation == "log":
+            return str(math.log(num1))
+        elif operation == "sin":
+            return str(math.sin(num1))
+        elif operation == "cos":
+            return str(math.cos(num1))
+        elif operation == "tan":
+            return str(math.tan(num1))
+        elif operation == "power":
+            if num2 is None:
+                return "power operation requires two numbers"
+            return str(math.pow(num1, num2))
+        else:
+            return f"Unknown operation: {operation}"
+    except Exception as e:
+        return f"Math error: {str(e)}"
+
+
+# @tool
+# def extract_text_from_image(img_path: str) -> str:
+#     """Extract text from an image file using a multimodal model."""
+#     try:
+#         if "vision_llm" not in globals():
+#             return "Error: Vision LLM not configured. Please uncomment and configure vision_llm."
+
+#         with open(img_path, "rb") as image_file:
+#             image_bytes = image_file.read()
+
+#         image_base64 = base64.b64encode(image_bytes).decode("utf-8")
+
+#         message = [
+#             HumanMessage(
+#                 content=[
+#                     {
+#                         "type": "text",
+#                         "text": "Extract all the text from this image. Return only the extracted text, no explanations.",
+#                     },
+#                     {
+#                         "type": "image_url",
+#                         "image_url": {"url": f"data:image/png;base64,{image_base64}"},
+#                     },
+#                 ]
+#             )
+#         ]
+
+#         response_content = vision_llm.invoke(message).content.strip()
+#         return response_content
+#     except Exception as e:
+#         return f"Multimodal text extraction error: {str(e)}"
+
+
+@tool
+def ask_question_on_image_content(question: str, img_path: str) -> str:
+    """Ask specific question on image content."""
+    try:
+        if "vision_llm" not in globals():
+            return "Error: Vision LLM not configured. Please uncomment and configure vision_llm."
+
+        with open(img_path, "rb") as image_file:
+            image_bytes = image_file.read()
+
+        image_base64 = base64.b64encode(image_bytes).decode("utf-8")
+
+        message = [
+            HumanMessage(
+                content=[
+                    {
+                        "type": "text",
+                        "text": question,
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/png;base64,{image_base64}"},
+                    },
+                ]
+            )
+        ]
+
+        response_content = vision_llm.invoke(message).content.strip()
+        return response_content
+    except Exception as e:
+        return f"Multimodal text extraction error: {str(e)}"
+
+
+@tool
+def read_excel_file(file_path: str, sheet_name: Optional[str] = None) -> str:
+    """
+    Read an Excel file and return its content.
+    """
+    try:
+        if sheet_name:
+            json_str = pd.read_excel(file_path, sheet_name=sheet_name).to_json(
+                orient="records", date_format="iso", force_ascii=False
+            )
+        else:
+            json_str = pd.read_excel(file_path).to_json(
+                orient="records", date_format="iso", force_ascii=False
+            )
+        return json_str
+    except Exception as e:
+        return f"Excel reading error: {str(e)}"
+
+
+@tool
+def visit_webpage(url: str) -> str:
+    """
+    Visits a webpage at the given URL and returns its content as a markdown string.
+    Use this to browse and extract readable content from webpages.
+    """
+    try:
+        response = requests.get(url, timeout=20)
+        response.raise_for_status()
+        markdown_content = markdownify(response.text).strip()
+        markdown_content = re.sub(r"\n{3,}", "\n\n", markdown_content)
+        MAX_LEN = 40000
+        if len(markdown_content) > MAX_LEN:
+            return (
+                markdown_content[: MAX_LEN // 2]
+                + f"\n\n...[Content truncated to {MAX_LEN} chars]...\n\n"
+                + markdown_content[-MAX_LEN // 2 :]
+            )
+        return markdown_content
+    except requests.exceptions.Timeout:
+        return "Timeout while trying to access the webpage."
+    except RequestException as e:
+        return f"Request error: {str(e)}"
+    except Exception as e:
+        return f"Unexpected error: {str(e)}"
+
+
+@tool
+def transcribe_mp3(
+    file_path: str,
+) -> str:
+    """
+    Transcribe an MP3 (local path or URL) using AssemblyAI and return the result.
+    """
+    try:
+        tfmt = getattr(TranscriptFormat, "TEXT", TranscriptFormat.TEXT)
+
+        loader = AssemblyAIAudioTranscriptLoader(
+            file_path=file_path,
+            transcript_format=tfmt,
+        )
+        docs = loader.load()
+
+        # Concatenate documents
+        text = "\n\n".join(d.page_content for d in docs)
+        MAX = 40000
+        if len(text) > MAX:
+            return text[:MAX] + f"\n\n...[truncated {len(text) - MAX} chars]..."
+        return text
+    except Exception as e:
+        return f"Transcription error: {str(e)}"
+
+
+def build_tools():
+    """
+    Initialize and return a list of built-in and custom LangChain tools.
+    """
+    # Initialize built-in LangChain tools
+    wikipedia_tool = WikipediaQueryRun(
+        api_wrapper=WikipediaAPIWrapper(doc_content_chars_max=2000)
+    )
+    duckduckgo_search = DuckDuckGoSearchRun(
+        api_wrapper=DuckDuckGoSearchAPIWrapper(max_results=15)
+    )
+    arxiv_tool = ArxivQueryRun(api_wrapper=ArxivAPIWrapper())
+    python_repl = PythonREPLTool()
+    shell_tool = ShellTool()
+
+    # Combine built-in tools with custom tools
+    all_tools = [
+        # Built-in LangChain tools
+        wikipedia_tool,
+        duckduckgo_search,
+        arxiv_tool,
+        python_repl,
+        shell_tool,
+        # Custom tools for specialized tasks
+        visit_webpage,
+        read_excel_file,
+        get_youtube_transcript_tool,
+        get_youtube_title_description_tool,
+        reverse_text,
+        reverse_words,
+        calculator,
+        advanced_math,
+        ask_question_on_image_content,
+        transcribe_mp3,
+    ]
+    return all_tools
+
+
+if __name__ == "__main__":
+    from pprint import pprint
+
+    print("\n--- reverse_text ---")
+    pprint(reverse_text.invoke({"text": "hello"}))
+
+    print("\n--- reverse_words ---")
+    pprint(reverse_words.invoke({"text": "LangChain makes graphs easy"}))
+
+    print("\n--- calculator ---")
+    pprint(calculator.invoke({"expression": "10 + 2 * 3 - 4 / 2"}))
+
+    print("\n--- advanced_math ---")
+    pprint(advanced_math.invoke({"operation": "sqrt", "num1": 16}))
+    pprint(advanced_math.invoke({"operation": "power", "num1": 2, "num2": 3}))
+
+    print("\n--- read_excel_file ---")
+    pprint(read_excel_file.invoke({"file_path": "examples/file_example_XLS_10.xls"}))
+    pprint(
+        read_excel_file.invoke(
+            {"file_path": "examples/file_example_XLS_10.xls", "sheet_name": "Sheet2"}
+        )
+    )
+
+    print("\n--- visit_webpage ---")
+    result = visit_webpage.invoke({"url": "https://example.com"})
+    print(result[:200] + "...\n")  # tronqué pour affichage
+
+    # print("\n--- extract_text_from_image ---")
+    # pprint(extract_text_from_image.invoke({"img_path": "examples/receipt.png"}))
+
+    print("\n--- ask_question_on_image_content ---")
+    pprint(
+        ask_question_on_image_content.invoke(
+            {
+                "question": "How many apples are in the basket?",
+                "img_path": "examples/apples.png",
+            }
+        )
+    )
+
+    print("\n--- transcribe_mp3 ---")
+    pprint(transcribe_mp3.invoke({"file_path": "./examples/sample.mp3"}))

youtube_transcript.py

@@ -0,0 +1,135 @@
+from __future__ import annotations
+
+import requests
+from bs4 import BeautifulSoup
+from langchain_core.tools import tool
+from markdownify import markdownify as md
+from youtube_transcript_api import YouTubeTranscriptApi
+from youtube_transcript_api._errors import (
+    TranscriptsDisabled,
+    NoTranscriptFound,
+    VideoUnavailable,
+)
+
+# ---- Config -----------------------------------------------------------------
+
+DEFAULT_TIMEOUT = 30
+DEFAULT_HEADERS = {
+    # Helps avoid consent/anti-bot interstitials on some sites
+    "User-Agent": (
+        "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
+        "(KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
+    )
+}
+
+
+# ---- Small helpers ----------------------------------------------------------
+
+
+def _fetch_html(url: str, *, timeout: int = DEFAULT_TIMEOUT) -> str:
+    """Download raw HTML for a URL or raise on HTTP errors."""
+    resp = requests.get(url, headers=DEFAULT_HEADERS, timeout=timeout)
+    resp.raise_for_status()
+    return resp.text
+
+
+def _html_to_markdown(html: str) -> str:
+    """Convert HTML to clean Markdown (scripts/styles removed)."""
+    soup = BeautifulSoup(html, "html.parser")
+    for tag in soup(["script", "style"]):
+        tag.extract()
+    return md(str(soup), strip=["script", "style"], heading_style="ATX").strip()
+
+
+# ---- Pure functions (safe to call directly in Python) -----------------------
+
+
+def fetch_webpage(url: str, convert_to_markdown: bool = True) -> str:
+    """
+    Fetch a web page and return Markdown or raw HTML.
+    Keep it simple: HTML -> (optional) Markdown, nothing else.
+    """
+    html = _fetch_html(url)
+    return _html_to_markdown(html) if convert_to_markdown else html
+
+
+def get_youtube_transcript(video_id: str) -> str:
+    """
+    Return YouTube transcript text for a given video ID.
+    One line per chunk; raises a clear error if transcript is unavailable.
+
+    Example of video_id:
+    For youtube video: https://www.youtube.com/watch?v=1htKBjuUWec
+    The video id is: dQw4w9WgXcQ
+    """
+    try:
+        # Initialize the YouTubeTranscriptApi
+        ytt_api = YouTubeTranscriptApi()
+        fetched_transcript = ytt_api.fetch(video_id)
+        raw_data = fetched_transcript.to_raw_data()
+        # raw data is in the form of [{        'text': 'Hey there',        'start': 0.0,        'duration': 1.54    },    {        'text': 'how are you',,        'start': 1.54,        'duration': 4.16    },   ... ] we will return ony the text element as lines
+        transcript = "\n".join([item["text"] for item in raw_data])
+        return transcript
+    except (TranscriptsDisabled, NoTranscriptFound, VideoUnavailable) as e:
+        raise RuntimeError(f"Transcript unavailable: {e}") from e
+
+
+def get_youtube_title_description(video_url: str) -> str:
+    """
+    get_youtube title and description from youtube url (ex: https://www.youtube.com/watch?v=1htKBjuUWec)
+
+    Extract YouTube title + description from Open Graph meta tags.
+    Falls back to standard <meta name="title"/"description"> if needed.
+    """
+    html = _fetch_html(video_url)
+    soup = BeautifulSoup(html, "html.parser")
+
+    title_tag = soup.find("meta", property="og:title") or soup.find(
+        "meta", attrs={"name": "title"}
+    )
+    desc_tag = soup.find("meta", property="og:description") or soup.find(
+        "meta", attrs={"name": "description"}
+    )
+
+    title = (title_tag.get("content") if title_tag else None) or "No title found"
+    description = (
+        desc_tag.get("content") if desc_tag else None
+    ) or "No description found"
+
+    return f"Title: {title}\nDescription: {description}"
+
+
+# ---- LangChain tool wrappers (for agents; call with .invoke) ----------------
+
+
+@tool("fetch_webpage")
+def fetch_webpage_tool(url: str, convert_to_markdown: bool = True) -> str:
+    """Tool: fetch a web page and return Markdown or raw HTML."""
+    return fetch_webpage(url, convert_to_markdown)
+
+
+@tool("get_youtube_transcript")
+def get_youtube_transcript_tool(video_id: str) -> str:
+    """Tool: return YouTube transcript text for a video ID."""
+    return get_youtube_transcript(video_id)
+
+
+@tool("get_youtube_title_description")
+def get_youtube_title_description_tool(video_url: str) -> str:
+    """Tool: return YouTube title + description for a video URL."""
+    return get_youtube_title_description(video_url)
+
+
+# ---- Minimal demo -----------------------------------------------------------
+
+if __name__ == "__main__":
+    video_id = "1htKBjuUWec"
+    url = f"https://www.youtube.com/watch?v={video_id}"
+
+    print(get_youtube_title_description(url))
+    try:
+        print("\n--- Transcript (first 500 chars) ---")
+        tx = get_youtube_transcript(video_id)
+        print(tx[:500] + ("..." if len(tx) > 500 else ""))
+    except Exception as e:
+        print(f"Transcript error: {e}")