How to return citations from Agent?

[DEENUU1]

Checked other resources

• I added a very descriptive title to this question.
• I searched the LangChain documentation with the integrated search.
• I used the GitHub search to find a similar question and didn't find it.

Commit to Help

• I commit to help with one of those options 👆

Example Code

def get_llm(provider: str, model: str, temperature: float) -> Any:
    if provider == "openai":
        return ChatOpenAI(model=model, temperature=temperature, openai_api_key=settings.OPENAI_API_KEY, streaming=True)
    else:
        raise ValueError(f"Unsupported provider: {provider}")


def get_prompt() -> ChatPromptTemplate:
    return ChatPromptTemplate.from_messages(
        [
            (
                "system",
                "You are a helpful assistant.",
            ),
            ("placeholder", "{chat_history}"),
            ("human", "{input}"),
            ("placeholder", "{agent_scratchpad}"),
        ]
    )

def get_tools() -> list:
    serper_tool = get_google_serper_tool()
    return [
        # serper_tool,
        GoogleDriveTool(),
        CurrentTimeTool(),
        WeatherTool(),
        AskNewsSearch(),
        WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper()),
        # YahooFinanceNewsTool(),
        ScraperTool(),
        BraveSearchWrapper.from_api_key(api_key=settings.BRAVE_API_KEY, search_kwargs={"count": 5})
    ]

async def get_agent(session_id: str, llm: LLM, user_id: str) -> RunnableWithMessageHistory:
    llm = get_llm(llm.provider, model=llm.model, temperature=0)
    tools = get_tools()
    prompt = get_prompt()

    agent = create_tool_calling_agent(llm, tools, prompt)

    agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

    agent_with_chat = RunnableWithMessageHistory(
        agent_executor,
        lambda session_id: get_session_history(session_id, user_id),
        input_messages_key="input",
        history_messages_key="chat_history",
    )

    return agent_with_chat


agent = await get_agent(str(session_id), llm_model, str(user_id))

async for event in agent.astream_events(
                    {"input": full_input},
                    config={"configurable": {"session_id": session_id, "user_id": str(user_id)}},
                    version="v1",
            ):
                kind = event["event"]
                if kind == "on_chat_model_stream":
                    content = event["data"]["chunk"].content
                    if content:
                        await websocket.send_json({"type": "chunk", "content": content, "message_id": ai_message.id})
                        full_response += content

                elif kind == "on_tool_start":
                    await websocket.send_json(
                        {"type": "tool_start", "tool_name": event["name"], "run_id": event["run_id"]}
                    )

                elif kind == "on_tool_end":
                    tool_output = event.get("data", {}).get("output", "")
                    processed_output = process_tool_output(tool_output)

                    tool_output_obj = create_tool_output(db, ToolOutputInputSchema(
                        content=json.dumps(processed_output),
                        tool_name=event["name"],
                        run_id=event["run_id"],
                        message_id=ai_message.id
                    ))
                    tool_output_objs.append(tool_output_obj.model_dump())

                    await websocket.send_json(
                        {"type": "tool_end", "tool_name": event["name"], "run_id": event["run_id"]}
                    )
                    await websocket.send_json(
                        {"tool_object": tool_output_obj.model_dump(), "message_id": ai_message.id})

Description

Hi, I am using Agent from Langchain and would like to return inline citations in a text. For example: "Messi is a.... [1]" where [1] is a citation and I can display it.

Currently, my application allows me to return output from tools so I have access to the whole fetched content from different tools but I would like to add inline citations with core information.
Is it possible to do it?

I saw the documentation but I don't understand how to add it to Agent.

System Info

aiohappyeyeballs==2.4.0
aiohttp==3.10.5
aiosignal==1.3.1
alembic==1.13.2
annotated-types==0.7.0
anyio==4.4.0
asgiref==3.8.1
asknews==0.7.43
asyncpg==0.29.0
attrs==24.2.0
bcrypt==4.2.0
beautifulsoup4==4.12.3
cachetools==5.5.0
certifi==2024.8.30
cffi==1.17.1
charset-normalizer==3.3.2
click==8.1.7
colorama==0.4.6
cryptography==42.0.6
dataclasses-json==0.6.7
Deprecated==1.2.14
dirtyjson==1.0.8
distro==1.9.0
dnspython==2.6.1
ecdsa==0.19.0
email_validator==2.2.0
fastapi==0.114.0
fastapi-cli==0.0.5
frozenlist==1.4.1
fsspec==2024.9.0
google-api-core==2.20.0
google-api-python-client==2.147.0
google-auth==2.35.0
google-auth-httplib2==0.2.0
google-auth-oauthlib==1.2.1
googleapis-common-protos==1.65.0
greenlet==3.0.3
h11==0.14.0
httpcore==1.0.5
httplib2==0.22.0
httptools==0.6.1
httpx==0.27.2
idna==3.8
itsdangerous==2.2.0
Jinja2==3.1.4
jiter==0.5.0
joblib==1.4.2
jsonpatch==1.33
jsonpointer==3.0.0
langchain==0.2.16
langchain-community==0.2.16
langchain-core==0.3.9
langchain-openai==0.1.23
langchain-text-splitters==0.2.4
langgraph==0.2.34
langgraph-checkpoint==2.0.1
langsmith==0.1.132
llama-cloud==0.1.0
llama-index==0.11.14
llama-index-agent-openai==0.3.4
llama-index-cli==0.3.1
llama-index-core==0.11.15
llama-index-embeddings-openai==0.2.5
llama-index-indices-managed-llama-cloud==0.4.0
llama-index-legacy==0.9.48.post3
llama-index-llms-openai==0.2.10
llama-index-multi-modal-llms-openai==0.2.1
llama-index-program-openai==0.2.0
llama-index-question-gen-openai==0.2.0
llama-index-readers-file==0.2.2
llama-index-readers-llama-parse==0.3.0
llama-parse==0.5.6
Mako==1.3.5
markdown-it-py==3.0.0
MarkupSafe==2.1.5
marshmallow==3.22.0
mdurl==0.1.2
msgpack==1.1.0
multidict==6.0.5
mypy-extensions==1.0.0
nest-asyncio==1.6.0
networkx==3.3
nltk==3.9.1
numpy==1.26.4
oauthlib==3.2.2
openai==1.44.0
orjson==3.10.7
packaging==24.1
pandas==2.2.3
pillow==10.4.0
proto-plus==1.24.0
protobuf==5.28.2
psycopg2-binary==2.9.9
pyasn1==0.6.1
pyasn1_modules==0.4.1
pycparser==2.22
pydantic==2.9.0
pydantic-extra-types==2.9.0
pydantic-settings==2.4.0
pydantic_core==2.23.2
Pygments==2.18.0
pyparsing==3.1.4
pypdf==4.3.1
python-dateutil==2.9.0.post0
python-dotenv==1.0.1
python-jose==3.3.0
python-multipart==0.0.9
pytz==2024.2
PyYAML==6.0.2
regex==2024.7.24
requests==2.32.3
requests-oauthlib==2.0.0
requests-toolbelt==1.0.0
rich==13.8.0
rsa==4.9
shellingham==1.5.4
six==1.16.0
sniffio==1.3.1
soupsieve==2.6
SQLAlchemy==2.0.34
starlette==0.38.5
striprtf==0.0.26
tenacity==8.5.0
tiktoken==0.7.0
tqdm==4.66.5
typer==0.12.5
typing-inspect==0.9.0
typing_extensions==4.12.2
tzdata==2024.1
ujson==5.10.0
uritemplate==4.1.1
urllib3==2.2.2
uvicorn==0.30.6
watchfiles==0.24.0
websockets==13.0.1
wikipedia==1.4.0
wrapt==1.16.0
yarl==1.10.0