fix: avoid updating Message if ChatOutput is connected to ChatInput

[keval718]

This PR fixes an issue where User and AI messages were generated with the same message ID, causing one message to overwrite the other in the chat UI and in network payloads. The issue occurred because the ChatOutput component reused an existing Message instance without generating a new ID.

Root Cause
When input_value is already a Message object, the component mutates it by updating the text but previously did not regenerate the message.id. As a result, both the User message and the AI message could share the same ID if the object was reused along the component chain.

This ID collision caused:

• Messages appearing merged or overwritten
• User and AI messages not rendering separately
• Identical message IDs in network calls

What This Fix Does
When reusing an existing Message instance, we now generate a fresh UUID:
if isinstance(self.input_value, Message):
message = self.input_value
message.text = text
message.id = uuid.uuid4() # Generate new unique ID

Why This Fix Matters
With unique IDs:

• User messages and AI messages are properly distinguished
• No more overwriting in chat history
• UI consistently renders separate bubbles
• Network payloads reflect unique message entries
• Downstream memory/session handling works as expected

Testing & Verification

• Confirmed that reused messages now receive unique IDs
• Verified in Playground UI that User and AI messages display independently
• Checked network payloads to ensure IDs are no longer duplicated

Summary by CodeRabbit

Release Notes

• Bug Fixes
  • Fixed message identity tracking across all starter projects and components to ensure processed messages receive unique identifiers for proper reference and tracking.

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Walkthrough

This PR updates the ChatOutput component across all starter projects and the corresponding Python module to assign a unique UUID to message.id when processing an existing Message input. The changes include adding import uuid and setting message.id = uuid.uuid4() in the message_response path, with corresponding code_hash updates.

Changes

Cohort / File(s)	Summary
Starter Projects (ChatOutput UUID Assignment) src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json, Basic Prompting.json, Blog Writer.json, Custom Component Generator.json, Document Q&A.json, Financial Report Parser.json, Hybrid Search RAG.json, Image Sentiment Analysis.json, Instagram Copywriter.json, Invoice Summarizer.json, Knowledge Retrieval.json, Market Research.json, Meeting Summary.json, Memory Chatbot.json, News Aggregator.json, Nvidia Remix.json, Pokédex Agent.json, Portfolio Website Code Generator.json, Price Deal Finder.json, Research Agent.json, Research Translation Loop.json, SEO Keyword Generator.json, SaaS Pricing.json, Search agent.json, Sequential Tasks Agents.json, Simple Agent.json, Social Media Agent.json, Text Sentiment Analysis.json, Travel Planning Agents.json, Twitter Thread Generator.json, Vector Store RAG.json, Youtube Analysis.json	Added import uuid and assigned a new unique ID (message.id = uuid.uuid4()) to Message objects in ChatOutput.message_response when input_value is already a Message. Updated code_hash metadata from 4848ad3e35d5 to 76077de62755 to reflect these changes.
Python Implementation src/lfx/src/lfx/components/input_output/chat_output.py	Added import uuid and implemented UUID assignment logic for existing Message inputs in ChatOutput component to match starter project updates.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

• Rationale: Although 32+ JSON starter project files are affected, the changes are highly homogeneous—identical UUID assignment logic repeated across all files with consistent code_hash updates. Review focuses on verifying consistency of the pattern rather than analyzing varied logic.
• Areas requiring attention:
  • Verify code_hash values are consistently updated from 4848ad3e35d5 to 76077de62755 across all starter project files
  • Confirm uuid.uuid4() assignment is placed correctly within the message_response path for existing Message inputs
  • Ensure the Python implementation aligns with the starter project patterns

Possibly related PRs

• fix(setup): preserve advanced attribute and generalize starter project JSON #8529: Updates ChatOutput component implementation inside starter-project JSONs with code/metadata changes.
• fix: don't send duplicate messages to Agent #8909: Filters/excludes messages by their id, which depends on the message.id field now being consistently assigned via UUID.

Suggested labels

bug, size:XS, lgtm

Suggested reviewers

• ogabrielluiz
• jordanrfrazier
• edwinjosechittilappilly

Pre-merge checks and finishing touches

❌ Failed checks (1 error, 3 warnings)

Check name	Status	Explanation	Resolution
Test Coverage For New Implementations	❌ Error	PR contains no new or modified test files despite implementing bug fixes for message ID generation in ChatOutput component.	Add comprehensive unit and integration tests for ChatOutput message ID generation, including verification of UUID string casting and proper handling of reused Message instances.
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.
Test Quality And Coverage	⚠️ Warning	PR lacks unit tests for critical UUID fix in ChatOutput component despite modifying 33 files and fixing message ID collision issues identified in review.	Add pytest unit tests verifying UUID generation, string type casting, input immutability, and uniqueness across invocations; add integration tests validating fix prevents message overwrites.
Test File Naming And Structure	⚠️ Warning	PR modifies ChatOutput implementation and starter project JSON files but adds no test files following pytest conventions or other testing patterns.	Add test_chat_output.py with pytest tests covering UUID generation, message ID reuse scenarios, string casting, and instance mutation prevention.

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Excessive Mock Usage Warning	✅ Passed	PR contains no test files or mock-related code changes. Modifications are configuration JSON templates and production code for UUID generation.
Title check	✅ Passed	The title accurately describes the main fix: preventing ChatOutput from overwriting message IDs when connected to ChatInput by generating new UUIDs for reused Message instances.

---

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Actionable comments posted: 7

Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (5)

src/lfx/src/lfx/components/input_output/chat_output.py (1)

121-127: I need to gather more information about the Message class definition and verify which one is used in chat_output.py.

Now I need to find the specific Message class definition used in chat_output.py and check the imports:

Based on my verification, the Message object extends the functionality of Data, and as a Pydantic model subclass, the model_copy() method allows models to be duplicated (with optional updates), which is particularly useful when working with frozen models.

The code at lines 121-127 directly mutates the input_value object by creating a reference assignment (message = self.input_value) and then modifying its properties. Additionally, model_copy() returns a copy (by default, shallow copy) of the model, which should suffice for primitive field updates like text and id.

---

Avoid mutating the input Message instance by creating a defensive copy.

The current code assigns message = self.input_value and then mutates message.text and message.id, which modifies the original object. If input_value is reused elsewhere in the flow, this could cause unexpected behavior. Use model_copy() to create an independent instance:

if isinstance(self.input_value, Message):
    message = self.input_value.model_copy()
    message.text = text
    message.id = uuid.uuid4()
else:
    message = Message(text=text)

The id field accepts UUID objects natively, so no string conversion is needed.

src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json (1)

468-474: Field name mismatch in field_order

field_order lists "store_message" but the input is named "should_store_message". This can cause UI ordering issues or confusion.

-              "store_message",
+              "should_store_message",

src/backend/base/langflow/initial_setup/starter_projects/Nvidia Remix.json (1)

589-700: Avoid mutating input Message and convert UUID to string for consistency

The current code directly mutates self.input_value and assigns a UUID object instead of a string, creating two issues:

1. Mutation side effect: Modifying self.input_value directly affects upstream references (history, caches). Deep-copy the Message before editing.
2. UUID type inconsistency: Assigning uuid.uuid4() (UUID object) instead of str(uuid.uuid4()) is inconsistent with the rest of the codebase (e.g., memory/stubs.py:67 uses string IDs).

Apply this fix inside ChatOutput.message_response:

         if isinstance(self.input_value, Message):
-            message = self.input_value
-            # Update message properties
+            # Avoid side effects on upstream references
+            message = self.input_value.model_copy(deep=True)
             message.text = text
-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())
         else:
             message = Message(text=text)

src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json (2)

803-906: Good fix; make ID JSON-safe and avoid mutating the input Message in place.

Regenerating a new ID solves the overwrite bug. Two tweaks:

• Cast to str to avoid leaking a UUID object into JSON/db payloads.
• Don’t mutate the upstream Message; copy/update to prevent side effects.

Apply:

-        if isinstance(self.input_value, Message):
-            message = self.input_value
-            # Update message properties
-            message.text = text
-            message.id = uuid.uuid4()
+        if isinstance(self.input_value, Message):
+            # Avoid mutating upstream instance; also ensure JSON-safe ID
+            message = self.input_value.copy(update={"text": text, "id": str(uuid.uuid4())})
         else:
             message = Message(text=text)

---

912-940: isinstance with PEP 604 unions will raise at runtime.

These checks use Message | Data | ... inside isinstance, which is invalid and throws TypeError. Use tuples:

-        if isinstance(self.input_value, list) and not all(
-            isinstance(item, Message | Data | DataFrame | str) for item in self.input_value
-        ):
+        ALLOWED_ITEM_TYPES = (Message, Data, DataFrame, str)
+        if isinstance(self.input_value, list) and not all(isinstance(item, ALLOWED_ITEM_TYPES) for item in self.input_value):
             ...

-        if not isinstance(
-            self.input_value,
-            Message | Data | DataFrame | str | list | Generator | type(None),
-        ):
+        ALLOWED_TYPES = (Message, Data, DataFrame, str, list, Generator, type(None))
+        if not isinstance(self.input_value, ALLOWED_TYPES):
             ...

♻️ Duplicate comments (4)

src/backend/base/langflow/initial_setup/starter_projects/Social Media Agent.json (1)

1049-1049: Same fix as Portfolio template — apply string UUID and avoid in-place mutation.

Mirror the prior suggestion:

• Use message.id = str(uuid.uuid4()).
• Clone the input Message before updating to prevent upstream side effects.

-            message = self.input_value
-            message.text = text
-            message.id = uuid.uuid4()
+            message = (
+                self.input_value.model_copy(deep=True)
+                if hasattr(self.input_value, "model_copy")
+                else Message(**getattr(self.input_value, "dict", lambda: {})())
+            )
+            message.text = text
+            message.id = str(uuid.uuid4())

src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json (3)

433-506: Mirror the ID handling and immutability fix here as well.

Same code path as in Hybrid Search RAG: cast UUID to str and copy the Message instead of mutating it in place.

See suggested diff in Hybrid Search RAG comment. Apply the same change here for consistency across starters.

---

506-540: isinstance with unions: same runtime TypeError risk.

Replace isinstance(item, Message | Data | ...) with tuples as shown in the previous file.

---

540-575: Generator-to-text handling: align with decision in the other file.

Ensure Message.text does not receive a Generator; coerce or stream properly.

🧹 Nitpick comments (15)

src/backend/base/langflow/initial_setup/starter_projects/Invoice Summarizer.json (2)

383-383: Use tuple of types in isinstance checks for broader runtime compatibility.

Within this code block, isinstance(item, Message | Data | DataFrame | str) may raise TypeError on some Python versions. Use a tuple.

Apply:

-        if isinstance(self.input_value, list) and not all(
-            isinstance(item, Message | Data | DataFrame | str) for item in self.input_value
-        ):
+        if isinstance(self.input_value, list) and not all(
+            isinstance(item, (Message, Data, DataFrame, str)) for item in self.input_value
+        ):
             invalid_types = [
                 type(item).__name__
                 for item in self.input_value
-                if not isinstance(item, Message | Data | DataFrame | str)
+                if not isinstance(item, (Message, Data, DataFrame, str))
             ]

---

383-383: Preserve traceability by storing previous ID when regenerating.

Regenerating id mutates the same Message instance; upstream references lose the original. Optionally capture it (e.g., message.parent_id) for audit/debug.

Example:

         if isinstance(self.input_value, Message):
             message = self.input_value
             # Update message properties
             message.text = text
-            message.id = uuid.uuid4()
+            prev_id = getattr(message, "id", None)
+            message.id = str(uuid.uuid4())
+            if prev_id and hasattr(message, "additional_kwargs"):
+                message.additional_kwargs = {**getattr(message, "additional_kwargs", {}), "parent_id": prev_id}

src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json (2)

585-585: Prefer tuple in isinstance checks for compatibility.

Mirror the same change to avoid potential TypeError.

Apply:

-        if isinstance(self.input_value, list) and not all(
-            isinstance(item, Message | Data | DataFrame | str) for item in self.input_value
-        ):
+        if isinstance(self.input_value, list) and not all(
+            isinstance(item, (Message, Data, DataFrame, str)) for item in self.input_value
+        ):
             invalid_types = [
                 type(item).__name__
                 for item in self.input_value
-                if not isinstance(item, Message | Data | DataFrame | str)
+                if not isinstance(item, (Message, Data, DataFrame, str))
             ]

---

585-585: Optional: keep original ID for lineage.

Same optional enhancement as in the other file to help debugging.

-            message.id = uuid.uuid4()
+            prev_id = getattr(message, "id", None)
+            message.id = str(uuid.uuid4())
+            if prev_id and hasattr(message, "additional_kwargs"):
+                message.additional_kwargs = {**getattr(message, "additional_kwargs", {}), "parent_id": prev_id}

src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents.json (1)

4193-4193: Consider creating a new Message instead of mutating the inbound object.

Message doesn't define an id field—the assignment stores it in the underlying data dictionary. While Pydantic auto-serializes UUID to string in JSON mode, mutating the inbound Message can surprise upstream holders of that object. Either create a copy with a new ID or construct a fresh Message to avoid side effects.

-            message = self.input_value
-            # Update message properties
-            message.text = text
-            message.id = uuid.uuid4()
+            # Create a new message instead of mutating the input
+            message = Message(
+                text=text,
+                sender=self.input_value.sender,
+                sender_name=self.input_value.sender_name,
+                session_id=self.input_value.session_id,
+                # ... copy other fields ...
+            )

src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json (1)

639-639: Same fix applies here: cast UUID to str and copy instead of mutating.

Mirror the improvements from the other flow to keep behavior consistent across starters.

Apply the same diff in ChatOutput.message_response:

-        if isinstance(self.input_value, Message):
-            message = self.input_value
-            # Update message properties
-            message.text = text
-            message.id = uuid.uuid4()
+        if isinstance(self.input_value, Message):
+            if hasattr(self.input_value, "model_copy"):
+                message = self.input_value.model_copy(update={"text": text, "id": str(uuid.uuid4())})
+            else:
+                message = Message(**{k: v for k, v in self.input_value.__dict__.items() if k not in {"id", "text"}},
+                                  text=text, id=str(uuid.uuid4()))

Optional repo-wide verification (same as above) to confirm Message.id expectations.

src/backend/base/langflow/initial_setup/starter_projects/Youtube Analysis.json (1)

1730-1775: Simplify UUID handling by storing message IDs as strings

The recommendation to cast uuid.uuid4() to string is valid. While the current code functions correctly (the custom serializer converts UUIDs to strings for JSON output), storing IDs consistently as strings improves efficiency by avoiding unnecessary type conversions and ensures uniformity with the API response model, which declares id: str | UUID | None.

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

src/backend/base/langflow/initial_setup/starter_projects/Research Translation Loop.json (3)

480-481: Regenerate ID — cast to string for safety

The fix is right; to avoid type/serialization surprises if Message.id is a str field or JSON payload expects a string, cast the UUID:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

Also consider guarding generator inputs from convert_to_string() before assignment (see note below).

---

480-481: Optional: avoid mutating upstream Message instance

To prevent side effects on upstream nodes, create a new Message instead of mutating self.input_value in place. Keep if you rely on mutation semantics.

---

480-481: Handle Generator from convert_to_string

convert_to_string may return a Generator. Assigning it to message.text can break consumers. Consider branching:

• if str: set message.text
• if Generator: stream via your existing mechanism and set a placeholder text or skip setting text until finalized.

src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json (2)

554-555: Regenerate ID — cast to string for safety

Good fix. Recommend casting to string to match common id: str schemas and ensure JSON-safe payloads:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

Also consider Generator handling as in the other file.

---

554-555: Optional: avoid mutating upstream Message instance

Prefer cloning to avoid side effects on the input Message. Keep as-is if mutation is intentional.

src/backend/base/langflow/initial_setup/starter_projects/Knowledge Retrieval.json (1)

310-311: Regenerate ID — cast to string for safety

Fix looks good. To avoid potential type mismatches or UUID JSON encoding surprises, cast to string:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

Also consider handling Generator from convert_to_string() before assigning to message.text.

src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json (1)

940-975: Generator output may be assigned to Message.text. Verify or coerce.

convert_to_string can return a Generator, but message.text = text assumes a string. If Message.text is not designed for streaming generators, coerce:

-        text = self.convert_to_string()
+        text = self.convert_to_string()
+        if isinstance(text, Generator):
+            # or handle streaming explicitly upstream
+            text = "".join(part for part in text)

src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json (1)

575-575: Avoid mutating upstream Message instance (optional).

To prevent side effects on callers holding the same object, consider creating a new Message and copying fields you need, instead of mutating self.input_value.

Example sketch:

-            message = self.input_value
-            message.text = text
-            message.id = str(uuid.uuid4())
+            src = self.input_value
+            message = Message(text=text)
+            message.id = str(uuid.uuid4())
+            # copy fields you rely on, e.g.:
+            message.data = getattr(src, "data", None)
+            message.files = getattr(src, "files", None)

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📥 Commits

Reviewing files that changed from the base of the PR and between ba68eea and 1cfa90a.

📒 Files selected for processing (33)

• src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Custom Component Generator.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Financial Report Parser.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Hybrid Search RAG.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment Analysis.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Invoice Summarizer.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Knowledge Retrieval.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Market Research.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Meeting Summary.json (6 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/News Aggregator.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Nvidia Remix.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Pokédex Agent.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Portfolio Website Code Generator.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Price Deal Finder.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Research Translation Loop.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/SaaS Pricing.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Search agent.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Social Media Agent.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Text Sentiment Analysis.json (4 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json (2 hunks)
• src/backend/base/langflow/initial_setup/starter_projects/Youtube Analysis.json (2 hunks)
• src/lfx/src/lfx/components/input_output/chat_output.py (2 hunks)

🧰 Additional context used

🧠 Learnings (1)

📚 Learning: 2025-06-26T19:43:18.260Z

Learnt from: ogabrielluiz
Repo: langflow-ai/langflow PR: 0
File: :0-0
Timestamp: 2025-06-26T19:43:18.260Z
Learning: In langflow custom components, the `module_name` parameter is now propagated through template building functions to add module metadata and code hashes to frontend nodes for better component tracking and debugging.

Applied to files:

• src/backend/base/langflow/initial_setup/starter_projects/Custom Component Generator.json
• src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json

🔇 Additional comments (43)

src/lfx/src/lfx/components/input_output/chat_output.py (1)

5-5: Import looks good.

The uuid import is correctly placed and necessary for generating unique message IDs.

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting.json (1)

587-587: Metadata updates look correct.

The code_hash and embedded code updates properly reflect the changes made to the ChatOutput component in the Python source file.

Also applies to: 661-661

src/backend/base/langflow/initial_setup/starter_projects/Price Deal Finder.json (1)

419-419: Metadata updates are consistent.

The starter project configuration correctly reflects the ChatOutput component changes, with matching code_hash and embedded code updates.

Also applies to: 495-495

src/backend/base/langflow/initial_setup/starter_projects/Portfolio Website Code Generator.json (1)

329-329: LGTM on metadata update.

code_hash bump is consistent with the embedded code change.

src/backend/base/langflow/initial_setup/starter_projects/Social Media Agent.json (1)

974-974: LGTM on metadata update.

code_hash reflects the ChatOutput change.

src/backend/base/langflow/initial_setup/starter_projects/News Aggregator.json (2)

883-883: code_hash correctly updated to reflect ChatOutput component changes.

The metadata hash has been updated, which is expected given the changes to the embedded ChatOutput component code.

---

958-958: UUID import and message ID regeneration fix properly implemented in ChatOutput.message_response.

The fix correctly addresses the PR objective:

• Added import uuid at the module level
• When reusing an existing Message instance (isinstance(self.input_value, Message)), the code now assigns message.id = uuid.uuid4() to ensure uniqueness
• This prevents ID collisions between User and AI messages flowing through the component chain

The logic is sound: the message properties are updated (text, sender, session_id, etc.), and critically, a fresh UUID is generated to guarantee distinct message IDs in network payloads and UI rendering.

src/backend/base/langflow/initial_setup/starter_projects/Research Agent.json (3)

1720-1798: Fix correctly generates unique IDs when reusing Message instances.

The implementation properly addresses the issue where User and AI messages could share IDs. When an existing Message is reused (line 1753: message.id = uuid.uuid4()), a fresh UUID is generated before further processing, preventing ID collisions in the chat UI and network payloads.

The logic flow is sound:

• Check if input_value is already a Message instance (line 1750)
• If true, mutate the existing object with updated text and new ID (lines 1752-1753)
• If false, create a new Message (line 1755)
• Complete remaining properties setup downstream (lines 1758-1761)

---

1720-1730: UUID import is correctly positioned.

The import uuid statement is added at line 1724 alongside other imports. The placement follows Python conventions and makes the standard library dependency explicit for this component.

---

1644-1644: Code hash metadata updated appropriately.

The code_hash value has been changed to "76077de62755" to reflect the logic modifications in the ChatOutput component's message_response method. This ensures the component's signature is correctly tracked for caching and versioning purposes.

src/backend/base/langflow/initial_setup/starter_projects/Meeting Summary.json (1)

642-642: Consistent and correct update across all ChatOutput instances.

All three ChatOutput component instances (ChatOutput-9KeOi, ChatOutput-iChI5, ChatOutput-R039P) have been properly updated with:

• import uuid statement at the top of the code
• Logic to generate a fresh UUID when reusing an existing Message instance: message.id = uuid.uuid4()
• Consistent code_hash value "76077de62755" reflecting the changes
• Identical code implementations across all instances

The fix correctly addresses the PR objective of preventing message ID collisions by ensuring each message processed through ChatOutput receives a unique ID, even when the same Message object instance is reused along the component chain.

Also applies to: 718-718, 921-921, 997-997, 1200-1200, 1276-1276

src/backend/base/langflow/initial_setup/starter_projects/Sequential Tasks Agents.json (1)

4117-4117: code_hash bump acknowledged.

Hash update aligns with the ChatOutput change (uuid import + new id assignment). No further action from this file.

Please confirm the same ChatOutput code (with UUID regeneration) and corresponding code_hash updates are applied consistently across other starter projects in this PR.

src/backend/base/langflow/initial_setup/starter_projects/Search agent.json (2)

569-570: Code hash updated appropriately for ChatOutput implementation changes.

The code_hash has been updated to reflect the added uuid import and the UUID regeneration logic in message_response(). This ensures consistency across the component versioning system.

---

629-683: Based on my verification of the codebase and the specific starter project structure:

The review comment's concern does not apply to this starter project.

The Search agent.json flow has a linear architecture: ChatInput → intermediate nodes → ChatOutput (single terminal node). The Message object flows through once and reaches a single ChatOutput component. Since ChatOutput is the terminal/final component in the flow, the mutations to message.text and message.id occur at the end of processing with no downstream propagation. There is no scenario where the same Message object is passed to multiple nodes that would cause the unintended state changes described in the review.

The underlying mutation pattern (directly modifying self.input_value without cloning) does exist in the code, but it is not problematic for this specific starter project's structure.

src/backend/base/langflow/initial_setup/starter_projects/Document Q&A.json (2)

413-414: Code hash matches across starter projects (consistent implementation).

Both starter projects (Search agent.json and Document Q&A.json) reference the same code_hash ("76077de62755"), confirming that ChatOutput implementations are synchronized and the UUID regeneration fix is uniformly applied.

---

488-489: Same UUID implementation as previous file—no duplicate concerns.

This file's ChatOutput code is identical to the Search agent.json variant. The same verification regarding UUID type compatibility (UUID object vs. string) and message mutation side effects applies here. Both starter projects are correctly updated in lockstep.

src/backend/base/langflow/initial_setup/starter_projects/Instagram Copywriter.json (1)

1045-1045: Meta update acknowledged.

code_hash change looks consistent with code edits; no action needed.

src/backend/base/langflow/initial_setup/starter_projects/SEO Keyword Generator.json (1)

565-565: Meta update acknowledged.

code_hash reflects the code change; no further action.

src/backend/base/langflow/initial_setup/starter_projects/Pokédex Agent.json (2)

395-395: code_hash update OK

Hash reflects code changes; no concerns.

---

471-710: Assign string UUIDs to message.id to avoid type/serialization issues

If Message.id is expected to be a string, assigning a UUID object can break JSON encoding and ID comparisons in UI/payloads. Use str(uuid.uuid4()).

Apply this diff inside ChatOutput.message_response:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

src/backend/base/langflow/initial_setup/starter_projects/Basic Prompt Chaining.json (2)

635-635: code_hash update OK

Matches underlying code change; all good.

---

709-710: Based on my investigation, I cannot fully verify the review comment because the Message schema is defined in message.py, but I couldn't access the exact type annotation for the id field in the Message class.

However, I can confirm the following:

1. JSON Serialization: In JSON mode, UUID instances are serialized as strings, and orjson serializes uuid.UUID instances to RFC 4122 format. The code uses both jsonable_encoder() and orjson.dumps(), so technical serialization will work regardless.

2. Type Consistency Patterns: The codebase shows explicit UUID-to-string conversion patterns in similar contexts, suggesting preference for type explicitness.

The concern about using str(uuid.uuid4()) is reasonable for ensuring consistent types, but whether it's critical depends on the actual type annotation of Message.id (whether it's str, UUID, or str | UUID). Without access to that specific field definition, I cannot definitively confirm if this change is a type correctness issue or a best-practice recommendation.

src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json (2)

426-426: Metadata-only change

code_hash update acknowledged. Nothing to review functionally.

---

500-731: Cast UUID to string to ensure consistent serialization and schema compatibility

The code assigns message.id = uuid.uuid4() which creates a UUID object. While Pydantic's arbitrary_types_allowed=True permits this, the codebase pattern and MessageResponse schema (which prefers str | UUID | None) indicate IDs should be serialized as strings for API compatibility and database operations.

Apply the suggested cast:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

Optionally, use model_copy() to avoid mutating the upstream input object:

-            message = self.input_value
-            message.text = text
-            message.id = str(uuid.uuid4())
+            base = self.input_value
+            message = base.model_copy(update={"text": text, "id": str(uuid.uuid4())})

src/backend/base/langflow/initial_setup/starter_projects/Youtube Analysis.json (1)

1654-1654: Metadata-only change

code_hash update acknowledged. No functional impact.

src/backend/base/langflow/initial_setup/starter_projects/Research Translation Loop.json (1)

405-405: Metadata hash update

Hash bump reflects code change; no concerns.

src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json (1)

480-480: Metadata hash update

Hash bump is expected; no further action.

src/backend/base/langflow/initial_setup/starter_projects/Knowledge Retrieval.json (1)

235-235: Metadata hash update

Acknowledged.

src/backend/base/langflow/initial_setup/starter_projects/Text Sentiment Analysis.json (1)

716-716: Consistent UUID regeneration applied to both ChatOutput nodes.

Both ChatOutput instances now correctly import uuid and assign a fresh message.id = uuid.uuid4() when reusing an existing Message instance. The code_hash values ("76077de62755") are consistent across both nodes, confirming the changes are synchronized.

The logic correctly handles message reuse: when self.input_value is already a Message object, it updates the text and regenerates the ID before setting other properties. This prevents ID collisions between User and AI messages.

Also applies to: 791-791, 998-998, 1073-1073

src/backend/base/langflow/initial_setup/starter_projects/Custom Component Generator.json (2)

2240-2240: Code hash update noted

Hash reflects the ChatOutput change. No action needed.

---

2316-2629: Regenerate ID on reused Message — good fix; two hardening tweaks

Verified: MessageResponse.id accepts str|UUID|None (src/lfx/src/lfx/schema/message.py) and the repo uses Pydantic v2 APIs (model_dump/model_copy present). Apply both hardening changes:

• Normalize id type: convert new id to str when the original id is a string (frontend expects string).
• Avoid mutating upstream Message: deep-copy (use model_copy(deep=True) when available, fallback to Message(**self.input_value.model_dump())).

Suggested patch (still relevant):

@@ async def message_response(self) -> Message:
-        if isinstance(self.input_value, Message):
-            message = self.input_value
-            # Update message properties
-            message.text = text
-            message.id = uuid.uuid4()
+        if isinstance(self.input_value, Message):
+            # Deep-copy to avoid mutating upstream instances
+            if hasattr(self.input_value, "model_copy"):  # pydantic v2
+                message = self.input_value.model_copy(deep=True)
+            else:
+                try:
+                    message = Message(**self.input_value.model_dump())
+                except Exception:
+                    message = Message(text=str(self.input_value))
+            # Update message properties and normalize id type
+            new_id = uuid.uuid4()
+            message.text = text
+            message.id = str(new_id) if isinstance(getattr(self.input_value, "id", ""), str) else new_id

Optional (if streaming/generator inputs are possible):

-        text = self.convert_to_string()
+        text = self.convert_to_string()
+        if isinstance(text, Generator):
+            text = "".join(list(text))

src/backend/base/langflow/initial_setup/starter_projects/Simple Agent.json (1)

642-642: Code hash update noted

Hash change aligns with ChatOutput update.

src/backend/base/langflow/initial_setup/starter_projects/Financial Report Parser.json (3)

228-229: UUID generation fix correctly addresses message ID collision issue. The implementation properly generates a fresh UUID when reusing an existing Message instance, ensuring distinct User and AI messages with unique IDs. The message.id = uuid.uuid4() assignment in the message_response() method (within the if isinstance(self.input_value, Message): block) directly resolves the root cause described in the PR objectives.

---

153-153: Code hash updated to reflect internal changes. The metadata code_hash has been updated from a previous value to "76077de62755", appropriately tracking the modifications to import statements and the message_response() logic.

---

228-229: Generator handling is properly implemented and consistent.

The code correctly imports Generator from collections.abc, validates it as an acceptable input type in _validate_input(), and handles it specifically in convert_to_string() by returning it unchanged. The return type annotation str | Generator[Any, None, None] confirms this is intentional. No inconsistencies between validation and method behavior were found.

src/backend/base/langflow/initial_setup/starter_projects/Nvidia Remix.json (1)

514-514: Code hash update acknowledged

Metadata code_hash reflects the ChatOutput change. No concerns.

src/backend/base/langflow/initial_setup/starter_projects/Market Research.json (3)

479-479: Code hash correctly updated to reflect ChatOutput implementation changes.

The hash has been updated from 4848ad3e35d5 to 76077de62755, properly documenting the changes to the ChatOutput component. This ensures the version tracking is consistent with the new UUID generation logic.

---

537-553: ChatOutput correctly implements fresh UUID generation for reused Message instances.

The embedded Python code properly addresses the root cause of message ID collisions:

• import uuid is correctly added at the top
• The message_response method detects when self.input_value is already a Message instance
• A fresh message.id = uuid.uuid4() is assigned, preventing ID reuse
• Other message properties (sender, sender_name, session_id, context_id, flow_id) are properly updated

This fix ensures User and AI messages receive unique IDs and will render as separate chat bubbles in the UI without overwriting each other.

---

447-707: Consistency verified across all starter project files.

The verification confirms that all 32 starter project JSON files have been updated consistently. Each ChatOutput component includes the uuid import and the message.id = uuid.uuid4() assignment without exception, ensuring uniform implementation and preventing regressions.

src/backend/base/langflow/initial_setup/starter_projects/Twitter Thread Generator.json (2)

763-763: Message ID regeneration correctly implemented.

The ChatOutput component now properly generates unique UUIDs for message IDs when reusing existing Message instances. The uuid import is correctly added, and the logic in message_response() properly assigns message.id = uuid.uuid4() before further processing. This addresses the root cause of message ID collisions that could cause one message to overwrite another in the UI.

---

688-688: Code hash updated appropriately.

The metadata code_hash for the ChatOutput node has been updated to reflect the changes in the component implementation, maintaining consistency with the modified code.

src/backend/base/langflow/initial_setup/starter_projects/Travel Planning Agents.json (2)

501-501: Code hash bump looks good.

Metadata reflects the behavioral change in ChatOutput.

---

575-575: Regenerate ID is correct; ensure ID type consistency.

If Message.id is a string elsewhere (common for storage/clients), set a string UUID to avoid type/serialization mismatches.

Suggested tweak:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

To verify the field type across the repo:

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Ensure regenerated ID is a string for consistency across storage, UI, and payloads.

Same pattern here: assign str(uuid.uuid4()) instead of a UUID object.

Apply:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

To verify consistency across all starter projects:

---

🏁 Script executed:

#!/bin/bash
# Count sites still using raw UUIDs
rg -nP 'message\.id\s*=\s*uuid\.uuid4\(\)' src/backend/base/langflow/initial_setup/starter_projects | sort

Length of output: 259253

---

Fix UUID ID assignment across all starter project templates

The issue extends beyond Image Sentiment Analysis.json. The search confirms message.id = uuid.uuid4() appears in 32 starter project files. Apply this fix consistently:

-            message.id = uuid.uuid4()
+            message.id = str(uuid.uuid4())

Affected files:

• Basic Prompt Chaining.json:709
• Basic Prompting.json:661
• Blog Writer.json:554
• Custom Component Generator.json:2316
• Document Q&A.json:488
• Financial Report Parser.json:229
• Hybrid Search RAG.json:803
• Image Sentiment Analysis.json:585
• Instagram Copywriter.json:1119
• Invoice Summarizer.json:383
• Knowledge Retrieval.json:310
• Market Research.json:553
• Meeting Summary.json:718, 997, 1276
• Memory Chatbot.json:500
• News Aggregator.json:958
• Nvidia Remix.json:589
• Pokédex Agent.json:471
• Portfolio Website Code Generator.json:405
• Price Deal Finder.json:495
• Research Agent.json:1720
• Research Translation Loop.json:480
• SEO Keyword Generator.json:639
• SaaS Pricing.json:448
• Search agent.json:645
• Sequential Tasks Agents.json:4193
• Simple Agent.json:718
• Social Media Agent.json:1049
• Text Sentiment Analysis.json:791, 1073
• Travel Planning Agents.json:575
• Twitter Thread Generator.json:763
• Vector Store RAG.json:1140
• Youtube Analysis.json:1730

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change

"value": "from collections.abc import Generator\nfrom typing import Any\n\nimport orjson\nimport uuid\nfrom fastapi.encoders import jsonable_encoder\n\nfrom lfx.base.io.chat import ChatComponent\nfrom lfx.helpers.data import safe_convert\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, HandleInput, MessageTextInput\nfrom lfx.schema.data import Data\nfrom lfx.schema.dataframe import DataFrame\nfrom lfx.schema.message import Message\nfrom lfx.schema.properties import Source\nfrom lfx.template.field.base import Output\nfrom lfx.utils.constants import (\n MESSAGE_SENDER_AI,\n MESSAGE_SENDER_NAME_AI,\n MESSAGE_SENDER_USER,\n)\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n documentation: str = \"https://docs.langflow.org/components-io#chat-output\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n minimized = True\n\n inputs = [\n HandleInput(\n name=\"input_value\",\n display_name=\"Inputs\",\n info=\"Message to be passed as output.\",\n input_types=[\"Data\", \"DataFrame\", \"Message\"],\n required=True,\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"context_id\",\n display_name=\"Context ID\",\n info=\"The context ID of the chat. Adds an extra layer to the local memory.\",\n value=\"\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n BoolInput(\n name=\"clean_data\",\n display_name=\"Basic Clean Data\",\n value=True,\n advanced=True,\n info=\"Whether to clean data before converting to string.\",\n ),\n ]\n outputs = [\n Output(\n display_name=\"Output Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, id_: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if id_:\n source_dict[\"id\"] = id_\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n # Handle case where source is a ChatOpenAI object\n if hasattr(source, \"model_name\"):\n source_dict[\"source\"] = source.model_name\n elif hasattr(source, \"model\"):\n source_dict[\"source\"] = str(source.model)\n else:\n source_dict[\"source\"] = str(source)\n return Source(**source_dict)\n\n async def message_response(self) -> Message:\n # First convert the input to string if needed\n text = self.convert_to_string()\n\n # Get source properties\n source, _, display_name, source_id = self.get_properties_from_source_component()\n\n # Create or use existing Message object\n if isinstance(self.input_value, Message):\n message = self.input_value\n # Update message properties\n message.text = text\n message.id = uuid.uuid4()\n else:\n message = Message(text=text)\n\n # Set message properties\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.context_id = self.context_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(source_id, display_name, source)\n\n # Store message if needed\n if self.session_id and self.should_store_message:\n stored_message = await self.send_message(message)\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n\n def _serialize_data(self, data: Data) -> str:\n \"\"\"Serialize Data object to JSON string.\"\"\"\n # Convert data.data to JSON-serializable format\n serializable_data = jsonable_encoder(data.data)\n # Serialize with orjson, enabling pretty printing with indentation\n json_bytes = orjson.dumps(serializable_data, option=orjson.OPT_INDENT_2)\n # Convert bytes to string and wrap in Markdown code blocks\n return \"```json\\n\" + json_bytes.decode(\"utf-8\") + \"\\n```\"\n\n def _validate_input(self) -> None:\n \"\"\"Validate the input data and raise ValueError if invalid.\"\"\"\n if self.input_value is None:\n msg = \"Input data cannot be None\"\n raise ValueError(msg)\n if isinstance(self.input_value, list) and not all(\n isinstance(item, Message | Data | DataFrame | str) for item in self.input_value\n ):\n invalid_types = [\n type(item).__name__\n for item in self.input_value\n if not isinstance(item, Message | Data | DataFrame | str)\n ]\n msg = f\"Expected Data or DataFrame or Message or str, got {invalid_types}\"\n raise TypeError(msg)\n if not isinstance(\n self.input_value,\n Message | Data | DataFrame | str | list | Generator | type(None),\n ):\n type_name = type(self.input_value).__name__\n msg = f\"Expected Data or DataFrame or Message or str, Generator or None, got {type_name}\"\n raise TypeError(msg)\n\n def convert_to_string(self) -> str | Generator[Any, None, None]:\n \"\"\"Convert input data to string with proper error handling.\"\"\"\n self._validate_input()\n if isinstance(self.input_value, list):\n clean_data: bool = getattr(self, \"clean_data\", False)\n return \"\\n\".join([safe_convert(item, clean_data=clean_data) for item in self.input_value])\n if isinstance(self.input_value, Generator):\n return self.input_value\n return safe_convert(self.input_value)\n"

"value": "from collections.abc import Generator\nfrom typing import Any\n\nimport orjson\nimport uuid\nfrom fastapi.encoders import jsonable_encoder\n\nfrom lfx.base.io.chat import ChatComponent\nfrom lfx.helpers.data import safe_convert\nfrom lfx.inputs.inputs import BoolInput, DropdownInput, HandleInput, MessageTextInput\nfrom lfx.schema.data import Data\nfrom lfx.schema.dataframe import DataFrame\nfrom lfx.schema.message import Message\nfrom lfx.schema.properties import Source\nfrom lfx.template.field.base import Output\nfrom lfx.utils.constants import (\n MESSAGE_SENDER_AI,\n MESSAGE_SENDER_NAME_AI,\n MESSAGE_SENDER_USER,\n)\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n documentation: str = \"https://docs.langflow.org/components-io#chat-output\"\n icon = \"MessagesSquare\"\n name = \"ChatOutput\"\n minimized = True\n\n inputs = [\n HandleInput(\n name=\"input_value\",\n display_name=\"Inputs\",\n info=\"Message to be passed as output.\",\n input_types=[\"Data\", \"DataFrame\", \"Message\"],\n required=True,\n ),\n BoolInput(\n name=\"should_store_message\",\n display_name=\"Store Messages\",\n info=\"Store the message in the history.\",\n value=True,\n advanced=True,\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n value=MESSAGE_SENDER_AI,\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=MESSAGE_SENDER_NAME_AI,\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"context_id\",\n display_name=\"Context ID\",\n info=\"The context ID of the chat. Adds an extra layer to the local memory.\",\n value=\"\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n BoolInput(\n name=\"clean_data\",\n display_name=\"Basic Clean Data\",\n value=True,\n advanced=True,\n info=\"Whether to clean data before converting to string.\",\n ),\n ]\n outputs = [\n Output(\n display_name=\"Output Message\",\n name=\"message\",\n method=\"message_response\",\n ),\n ]\n\n def _build_source(self, id_: str | None, display_name: str | None, source: str | None) -> Source:\n source_dict = {}\n if id_:\n source_dict[\"id\"] = id_\n if display_name:\n source_dict[\"display_name\"] = display_name\n if source:\n # Handle case where source is a ChatOpenAI object\n if hasattr(source, \"model_name\"):\n source_dict[\"source\"] = source.model_name\n elif hasattr(source, \"model\"):\n source_dict[\"source\"] = str(source.model)\n else:\n source_dict[\"source\"] = str(source)\n return Source(**source_dict)\n\n async def message_response(self) -> Message:\n # First convert the input to string if needed\n text = self.convert_to_string()\n\n # Get source properties\n source, _, display_name, source_id = self.get_properties_from_source_component()\n\n # Create or use existing Message object\n if isinstance(self.input_value, Message):\n message = self.input_value\n # Update message properties\n message.text = text\n message.id = str(uuid.uuid4())\n else:\n message = Message(text=text)\n\n # Set message properties\n message.sender = self.sender\n message.sender_name = self.sender_name\n message.session_id = self.session_id\n message.context_id = self.context_id\n message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n message.properties.source = self._build_source(source_id, display_name, source)\n\n # Store message if needed\n if self.session_id and self.should_store_message:\n stored_message = await self.send_message(message)\n self.message.value = stored_message\n message = stored_message\n\n self.status = message\n return message\n\n def _serialize_data(self, data: Data) -> str:\n \"\"\"Serialize Data object to JSON string.\"\"\"\n # Convert data.data to JSON-serializable format\n serializable_data = jsonable_encoder(data.data)\n # Serialize with orjson, enabling pretty printing with indentation\n json_bytes = orjson.dumps(serializable_data, option=orjson.OPT_INDENT_2)\n # Convert bytes to string and wrap in Markdown code blocks\n return \"

🤖 Prompt for AI Agents

In src/backend/base/langflow/initial_setup/starter_projects/Image Sentiment
Analysis.json around line 585, the code sets message.id = uuid.uuid4() which
assigns a UUID object where a string ID is expected; change it to assign a
string (e.g., message.id = str(uuid.uuid4())). Apply the same replacement
(uuid.uuid4() -> str(uuid.uuid4())) for the identical occurrences across all
listed starter project JSON files to ensure consistent string IDs.

[lucaseduoli]

LGTM

[github-actions]

Frontend Unit Test Coverage Report

Coverage Summary

Lines	Statements	Branches	Functions
	15.3% (4188/27372)	8.5% (1778/20915)	9.6% (579/6029)

Unit Test Results

Tests	Skipped	Failures	Errors	Time
1638	0 💤	0 ❌	0 🔥	20.872s ⏱️

[codecov]

Codecov Report

❌ Patch coverage is 70.00000% with 3 lines in your changes missing coverage. Please review.
✅ Project coverage is 32.40%. Comparing base (a2aec42) to head (d03a34e).
⚠️ Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
...c/lfx/src/lfx/custom/custom_component/component.py	57.14%	2 Missing and 1 partial ⚠️

❌ Your project status has failed because the head coverage (40.22%) is below the target coverage (60.00%). You can increase the head coverage or adjust the target coverage.

Additional details and impacted files

@@            Coverage Diff             @@
##             main   #10586      +/-   ##
==========================================
+ Coverage   32.38%   32.40%   +0.01%     
==========================================
  Files        1366     1366              
  Lines       62943    62953      +10     
  Branches     9304     9305       +1     
==========================================
+ Hits        20387    20397      +10     
+ Misses      41532    41528       -4     
- Partials     1024     1028       +4     

Flag	Coverage Δ
backend	51.05% <ø> (-0.03%)	⬇️
frontend	14.14% <ø> (ø)
lfx	40.22% <70.00%> (+0.04%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines	Coverage Δ
src/lfx/src/lfx/graph/utils.py	35.71% <100.00%> (+1.76%)	⬆️
...c/lfx/src/lfx/custom/custom_component/component.py	58.57% <57.14%> (-0.02%)	⬇️

... and 5 files with indirect coverage changes

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[lucaseduoli]

lgtm

[ogabrielluiz]

Hey @keval718

Could you give me some examples of this happening?
This is actually a feature not a bug because the Agent creates a generic message and the ChatOutput component can update the message's params (sender name, etc.)

If an Agent sends a message, then the ChatOutput creates a new message, it would duplicate the message in the playground.