langchain - ✅(Solved) Fix Bug: `merge_dicts` raises TypeError for float values during streaming chunk aggregation [5 pull requests, 11 comments, 6 participants]

nevanwang · 2026-03-17T12:29:23Z

[langchain] merge dicts in libs/core/langchain core/utils/ merge.py handles str , dict , list , equal values, and int types — but not float . When two dicts co… `merge_dicts()` in `libs/core/langchain_core/utils/_merge.py` handles `str`, `dict`, `list`, equal values, and `int` types — but **not `float`**. When two dicts contain the same key with unequal `float` values, the function falls through to the final `else` branch and raises a `TypeError`. This affects streaming scenarios where LLM providers return float fields in `generation_info` or `additional_kwargs` (e.g., `logprob`, `score`, safety scores, cost fields, etc.). During chunk aggregation via `ChatGenerationChunk.__add__()` → `merge_dicts()`, these float fields cause the stream to crash. **History:** Issue #17376 reported the same bug in 2024. PR #16605 added `int` support but omitted `float`. PR #36012 attempted a fix but was closed due to missing issue link and unrelated changes. # PR #36012: fix(core): handle float type in merge_dicts, merge_obj, and _dict_int_op - Repository: langchain-ai/langchain - Author: nevanwang - State: closed | merged: False - Link: https://github.com/langchain-ai/langchain/pull/36012 ## Description (problem / solution / changelog) ## Description `merge_dicts()` and `merge_obj()` in `libs/core/langchain_core/utils/_merge.py`, as well as `_dict_int_op()` in `libs/core/langchain_core/utils/usage.py`, handle `int` types but **not `float`**. When these functions encounter `float` values, they fall through to error branches and raise `TypeError` or `ValueError`. ```python from langchain_core.utils._merge import merge_dicts merge_dicts({"score": 0.5}, {"score": 0.3}) # ❌ TypeError ``` This affects streaming scenarios where LLM providers return float fields in `generation_info`, `additional_kwargs`, or `UsageMetadata` (e.g., `logprob`, `score`, safety scores, cost fields, etc.). During chunk aggregation via `ChatGenerationChunk.__add__()` → `merge_dicts()`, or `UsageMetadata.__add__()` → `_dict_int_op()`, these float fields cause the stream to crash. ## Changes ### `libs/core/langchain_core/utils/_merge.py` - **`merge_dicts()`**: Changed `isinstance(merged[right_k], int)` to `isinstance(merged[right_k], (int, float))` so that float values are summed (or preserved for special keys like `index`, `created`, `timestamp`) instead of raising `TypeError`. - **`merge_obj()`**: Added `isinstance(left, (int, float))` check **after** the equality check, so unequal numeric values are summed instead of raising `ValueError`. The ordering is important — equal values (including `True == True`, `42 == 42`, `3.14 == 3.14`) are handled by the equality branch first, and only unequal numeric values reach the addition branch. ### `libs/core/langchain_core/utils/usage.py` - **`_dict_int_op()`**: Changed `isinstance(..., int)` to `isinstance(..., (int, float))` so that float values in `UsageMetadata` (e.g., cost fields, timing data) are correctly handled during aggregation. - Updated type annotations (`Callable[[int, int], int]` → `Callable[[float, float], float]`), docstrings, and error messages to reflect float support. ### `libs/core/tests/unit_tests/utils/test_utils.py` - Added regression tests for float values in `test_merge_dicts` (summing, preserved special keys like `index`/`created`/`timestamp`). - Added regression tests for numeric addition in `test_merge_obj` (`int` and `float`). - Updated `test_merge_obj_unmergeable_values` to use `set` instead of different integers (since different integers are now correctly summed). ### `libs/core/tests/unit_tests/utils/test_usage.py` - Added `test_dict_int_op_float_add` — tests pure float addition. - Added `test_dict_int_op_mixed_int_float` — tests mixed int/float addition. - Added `test_dict_int_op_nested_float` — tests nested dictionaries with float values. - Updated error message assertion to match new "int, and float" wording. ## Design Note As @Jairooh correctly pointed out, `isinstance(x, int)` returns `True` for `bool` in Python. In `merge_obj()`, this is safely handled because `bool` equality (`True == True`) is caught by the `left == right` branch **before** reaching the numeric addition branch. For `merge_dicts()`, the same ordering applies. This is a key design choice — the competing PR #36048 placed the numeric check **before** the equality check, causing `42 + 42 = 84` and `True + True = 2` failures. Regarding floating-point precision concerns: the current approach mirrors the existing `int` addition semantics. For use cases where last-value or max semantics are preferred over summation, that would be a separate feature/configuration beyond this bug fix. ## Issue Fixes #36011 Fixes #36015 ## Related - #17376 — Originally reported in 2024, closed as `not_planned` - PR #16605 — Added `int` support but omitted `float` - #36015 — `_dict_int_op` raises ValueError for float values in `UsageMetadata` ## Changed files - `libs/core/langchain_core/utils/_merge.py` (modified, +3/-1) - `libs/core/test

langchain2026-03-17 12:29:23

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langchain-ai/langchain#36011•Fetched 2026-04-08 00:47:37

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merge_dicts() in libs/core/langchain_core/utils/_merge.py handles str, dict, list, equal values, and int types — but not float. When two dicts contain the same key with unequal float values, the function falls through to the final else branch and raises a TypeError.

This affects streaming scenarios where LLM providers return float fields in generation_info or additional_kwargs (e.g., logprob, score, safety scores, cost fields, etc.). During chunk aggregation via ChatGenerationChunk.__add__() → merge_dicts(), these float fields cause the stream to crash.

History: Issue #17376 reported the same bug in 2024. PR #16605 added int support but omitted float. PR #36012 attempted a fix but was closed due to missing issue link and unrelated changes.

Error Message

TypeError: Additional kwargs key score already exists in left dict and value has unsupported type <class 'float'>.

Root Cause

In _merge.py line 71, the type check is:

elif isinstance(merged[right_k], int):

This should be:

elif isinstance(merged[right_k], (int, float)):

Fix Action

Fixed

Fixed by PR: fix(core): handle float type in merge_dicts, merge_obj, and _dict_int_op (https://github.com/langchain-ai/langchain/pull/36012)
Fixed by PR: fix(core): add float support to merge_dicts for streaming scenarios (https://github.com/Jah-yee/langchain/pull/1)
Fixed by PR: fix(core): handle float values in merge_dicts (https://github.com/langchain-ai/langchain/pull/36014)
Fixed by PR: fix(core): handle float type in _dict_int_op for UsageMetadata aggregation (https://github.com/langchain-ai/langchain/pull/36016)
Fixed by PR: fix: add float support in merge_dicts (https://github.com/langchain-ai/langchain/pull/36021)

PR fix notes

PR #36012: fix(core): handle float type in merge_dicts, merge_obj, and _dict_int_op

Repository: langchain-ai/langchain
Author: nevanwang
State: closed | merged: False
Link: https://github.com/langchain-ai/langchain/pull/36012

Description (problem / solution / changelog)

Description

merge_dicts() and merge_obj() in libs/core/langchain_core/utils/_merge.py, as well as _dict_int_op() in libs/core/langchain_core/utils/usage.py, handle int types but not float. When these functions encounter float values, they fall through to error branches and raise TypeError or ValueError.

from langchain_core.utils._merge import merge_dicts

merge_dicts({"score": 0.5}, {"score": 0.3})  # ❌ TypeError

This affects streaming scenarios where LLM providers return float fields in generation_info, additional_kwargs, or UsageMetadata (e.g., logprob, score, safety scores, cost fields, etc.). During chunk aggregation via ChatGenerationChunk.__add__() → merge_dicts(), or UsageMetadata.__add__() → _dict_int_op(), these float fields cause the stream to crash.

Changes

`libs/core/langchain_core/utils/_merge.py`

merge_dicts(): Changed isinstance(merged[right_k], int) to isinstance(merged[right_k], (int, float)) so that float values are summed (or preserved for special keys like index, created, timestamp) instead of raising TypeError.
merge_obj(): Added isinstance(left, (int, float)) check after the equality check, so unequal numeric values are summed instead of raising ValueError. The ordering is important — equal values (including True == True, 42 == 42, 3.14 == 3.14) are handled by the equality branch first, and only unequal numeric values reach the addition branch.

`libs/core/langchain_core/utils/usage.py`

_dict_int_op(): Changed isinstance(..., int) to isinstance(..., (int, float)) so that float values in UsageMetadata (e.g., cost fields, timing data) are correctly handled during aggregation.
Updated type annotations (Callable[[int, int], int] → Callable[[float, float], float]), docstrings, and error messages to reflect float support.

`libs/core/tests/unit_tests/utils/test_utils.py`

Added regression tests for float values in test_merge_dicts (summing, preserved special keys like index/created/timestamp).
Added regression tests for numeric addition in test_merge_obj (int and float).
Updated test_merge_obj_unmergeable_values to use set instead of different integers (since different integers are now correctly summed).

`libs/core/tests/unit_tests/utils/test_usage.py`

Added test_dict_int_op_float_add — tests pure float addition.
Added test_dict_int_op_mixed_int_float — tests mixed int/float addition.
Added test_dict_int_op_nested_float — tests nested dictionaries with float values.
Updated error message assertion to match new "int, and float" wording.

Design Note

As @Jairooh correctly pointed out, isinstance(x, int) returns True for bool in Python. In merge_obj(), this is safely handled because bool equality (True == True) is caught by the left == right branch before reaching the numeric addition branch. For merge_dicts(), the same ordering applies. This is a key design choice — the competing PR #36048 placed the numeric check before the equality check, causing 42 + 42 = 84 and True + True = 2 failures.

Regarding floating-point precision concerns: the current approach mirrors the existing int addition semantics. For use cases where last-value or max semantics are preferred over summation, that would be a separate feature/configuration beyond this bug fix.

Issue

Fixes #36011 Fixes #36015

#17376 — Originally reported in 2024, closed as not_planned
PR #16605 — Added int support but omitted float
#36015 — _dict_int_op raises ValueError for float values in UsageMetadata

Changed files

libs/core/langchain_core/utils/_merge.py (modified, +3/-1)
libs/core/tests/unit_tests/utils/test_utils.py (modified, +13/-2)

PR #1: fix(core): add float support to merge_dicts for streaming scenarios

Repository: Jah-yee/langchain
Author: Jah-yee
State: open | merged: False
Link: https://github.com/Jah-yee/langchain/pull/1

Description (problem / solution / changelog)

Fixes issue #36011 - merge_dicts raises TypeError for float values during streaming chunk aggregation

Problem

merge_dicts() in libs/core/langchain_core/utils/_merge.py handles str, dict, list, int, and equal values — but not float. When two dicts contain the same key with unequal float values, the function falls through to the final else branch and raises a TypeError.

This affects streaming scenarios where LLM providers return float fields in generation_info or additional_kwargs (e.g., logprob, score, safety scores, cost fields). During chunk aggregation via ChatGenerationChunk.__add__() → merge_dicts(), these float fields cause the stream to crash.

Solution

Add float to the isinstance check alongside int, using the same last-wins strategy for temporal fields (index, created, timestamp) and summing behavior for other numeric fields.

Changes

Modified isinstance(merged[right_k], int) to isinstance(merged[right_k], (int, float))
Added comment explaining float support for streaming scenarios

Testing

The fix allows merging float values like:

merge_dicts({"score": 0.5}, {"score": 0.3})  # Now works: {"score": 0.8}

Closes #36011

Changed files

.github/scripts/check_diff.py (modified, +0/-1)
.github/scripts/get_min_versions.py (modified, +1/-1)
.github/workflows/refresh_model_profiles.yml (modified, +1/-22)
.github/workflows/require_issue_link.yml (modified, +22/-0)
.github/workflows/tag-external-contributions.yml (modified, +19/-3)
README.md (modified, +40/-32)
libs/core/langchain_core/cross_encoders.py (added, +18/-0)
libs/core/langchain_core/utils/_merge.py (modified, +2/-1)
libs/core/langchain_core/utils/function_calling.py (modified, +0/-2)
libs/core/langchain_core/version.py (modified, +1/-1)
libs/core/pyproject.toml (modified, +1/-1)
libs/core/uv.lock (modified, +92/-94)
libs/langchain/langchain_classic/retrievers/document_compressors/cross_encoder.py (modified, +2/-15)
libs/langchain/pyproject.toml (modified, +3/-3)
libs/langchain/tests/README.md (removed, +0/-3)
libs/langchain/tests/unit_tests/test_pytest_config.py (modified, +1/-1)
libs/langchain/uv.lock (modified, +158/-121)
libs/langchain_v1/langchain/__init__.py (modified, +1/-1)
libs/langchain_v1/langchain/agents/factory.py (modified, +41/-6)
libs/langchain_v1/langchain/chat_models/base.py (modified, +2/-0)
libs/langchain_v1/pyproject.toml (modified, +2/-2)
libs/langchain_v1/tests/cassettes/test_inference_to_native_output[True].yaml.gz (modified, +0/-0)
libs/langchain_v1/tests/cassettes/test_inference_to_tool_output[True].yaml.gz (modified, +0/-0)
libs/langchain_v1/tests/cassettes/test_strict_mode[True].yaml.gz (modified, +0/-0)
libs/langchain_v1/tests/unit_tests/conftest.py (modified, +20/-0)
libs/langchain_v1/uv.lock (modified, +150/-120)
libs/model-profiles/Makefile (modified, +33/-1)
libs/model-profiles/langchain_model_profiles/cli.py (modified, +7/-0)
libs/model-profiles/tests/unit_tests/test_cli.py (modified, +64/-0)
libs/model-profiles/uv.lock (modified, +86/-86)
libs/partners/anthropic/langchain_anthropic/_version.py (modified, +1/-1)
libs/partners/anthropic/langchain_anthropic/chat_models.py (modified, +11/-1)
libs/partners/anthropic/langchain_anthropic/data/_profiles.py (modified, +140/-2)
libs/partners/anthropic/pyproject.toml (modified, +2/-2)
libs/partners/anthropic/tests/integration_tests/test_chat_models.py (modified, +1/-1)
libs/partners/anthropic/tests/unit_tests/test_chat_models.py (modified, +153/-8)
libs/partners/anthropic/uv.lock (modified, +84/-84)
libs/partners/chroma/uv.lock (modified, +80/-80)
libs/partners/deepseek/langchain_deepseek/chat_models.py (modified, +5/-1)
libs/partners/deepseek/langchain_deepseek/data/_profiles.py (modified, +12/-0)
libs/partners/deepseek/tests/unit_tests/test_chat_models.py (modified, +11/-2)
libs/partners/deepseek/uv.lock (modified, +81/-81)
libs/partners/exa/uv.lock (modified, +78/-78)
libs/partners/fireworks/langchain_fireworks/data/_profiles.py (modified, +78/-0)
libs/partners/fireworks/uv.lock (modified, +78/-78)
libs/partners/groq/langchain_groq/data/_profiles.py (modified, +110/-0)
libs/partners/groq/uv.lock (modified, +76/-76)
libs/partners/huggingface/langchain_huggingface/data/_profiles.py (modified, +120/-0)
libs/partners/huggingface/uv.lock (modified, +96/-103)
libs/partners/mistralai/langchain_mistralai/data/_profiles.py (modified, +156/-0)
libs/partners/mistralai/pyproject.toml (modified, +2/-2)
libs/partners/mistralai/uv.lock (modified, +77/-77)
libs/partners/nomic/uv.lock (modified, +81/-81)
libs/partners/ollama/uv.lock (modified, +78/-78)
libs/partners/openai/langchain_openai/chat_models/base.py (modified, +7/-4)
libs/partners/openai/langchain_openai/data/_profiles.py (modified, +264/-0)
libs/partners/openai/tests/cassettes/TestOpenAIResponses.test_stream_time.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_agent_loop.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_agent_loop_streaming.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_client_executed_tool_search.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_code_interpreter.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_compaction.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_compaction_streaming.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_custom_tool.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_file_search.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_function_calling.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_image_generation_multi_turn.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_image_generation_streaming.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_incomplete_response.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_mcp_builtin.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_mcp_builtin_zdr.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_parsed_pydantic_schema.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_reasoning.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_schema_parsing_failures_responses_api.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_schema_parsing_failures_responses_api_async.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_stream_reasoning_summary.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_tool_search.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_tool_search_streaming.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/cassettes/test_web_search.yaml.gz (modified, +0/-0)
libs/partners/openai/tests/integration_tests/chat_models/test_base.py (modified, +6/-2)
libs/partners/openai/tests/integration_tests/chat_models/test_base_standard.py (modified, +3/-1)
libs/partners/openai/tests/integration_tests/chat_models/test_responses_standard.py (modified, +3/-1)
libs/partners/openai/tests/unit_tests/chat_models/test_base.py (modified, +39/-0)
libs/partners/openai/tests/unit_tests/test_tools.py (modified, +1/-1)
libs/partners/openai/uv.lock (modified, +84/-84)
libs/partners/openrouter/langchain_openrouter/data/_profiles.py (modified, +0/-0)
libs/partners/perplexity/langchain_perplexity/data/_profiles.py (modified, +0/-0)
libs/partners/perplexity/uv.lock (modified, +0/-0)
libs/partners/qdrant/uv.lock (modified, +0/-0)
libs/partners/xai/langchain_xai/chat_models.py (modified, +0/-0)
libs/partners/xai/langchain_xai/data/_profiles.py (modified, +0/-0)
libs/partners/xai/tests/integration_tests/test_chat_models.py (modified, +0/-0)
libs/partners/xai/tests/integration_tests/test_chat_models_standard.py (modified, +0/-0)
libs/partners/xai/tests/unit_tests/test_chat_models.py (modified, +0/-0)
libs/partners/xai/uv.lock (modified, +0/-0)
libs/standard-tests/langchain_tests/integration_tests/chat_models.py (modified, +0/-0)
libs/standard-tests/uv.lock (modified, +0/-0)
libs/text-splitters/langchain_text_splitters/base.py (modified, +0/-0)
libs/text-splitters/uv.lock (modified, +0/-0)

PR #36014: fix(core): handle float values in merge_dicts

Repository: langchain-ai/langchain
Author: Jah-yee
State: closed | merged: False
Link: https://github.com/langchain-ai/langchain/pull/36014

Description (problem / solution / changelog)

Summary

Fixes #36011 - Bug: merge_dicts raises TypeError for float values during streaming chunk aggregation

Changes

Add float type handling in merge_dicts() function
Use last-wins strategy for float values (e.g., logprob, score, safety scores)
Fixes TypeError when streaming chunks contain unequal float values

Test

from langchain_core.utils._merge import merge_dicts

# Previously raised TypeError
result = merge_dicts({"score": 0.5}, {"score": 0.3})
# Now returns: {"score": 0.3}

Changed files

libs/core/langchain_core/utils/_merge.py (modified, +5/-0)

PR #36016: fix(core): handle float type in _dict_int_op for UsageMetadata aggregation

Repository: langchain-ai/langchain
Author: nevanwang
State: closed | merged: False
Link: https://github.com/langchain-ai/langchain/pull/36016

Description (problem / solution / changelog)

Description

_dict_int_op() in libs/core/langchain_core/utils/usage.py handles int and dict types but not float. When two dictionaries contain the same key with float values, the function raises ValueError.

This affects streaming scenarios where LLM providers include float fields in UsageMetadata (e.g., total_cost, pricing fields, or any custom float metric). During chunk aggregation via add_usage() → _dict_int_op(), these float fields cause the aggregation to crash.

Error:

ValueError: Unknown value types: [<class 'float'>]. Only dict and int values are supported.

All 4 float scenarios crash:

Direct float values in dicts
UsageMetadata with float total_cost on both sides
Float field present on only one side (default=0 is int, other side is float)
Mixed int (from cache init total_cost=0) + float (from provider total_cost=0.005)

This is the same class of bug as #36011 (merge_dicts missing float support), but in a different function.

Changes

Change isinstance(..., int) to isinstance(..., (int, float)) in _dict_int_op()
Update docstring to reflect numeric (int/float) support
Update error message to mention float
Add 5 regression tests for float values (add, subtract, mixed int/float, nested, one-sided)
Update existing test_dict_int_op_invalid_types error message match

Issue

Fixes #36015

Dependencies

None

Changed files

libs/core/langchain_core/utils/usage.py (modified, +8/-7)
libs/core/tests/unit_tests/utils/test_usage.py (modified, +41/-1)

PR #36021: fix: add float support in merge_dicts

Repository: langchain-ai/langchain
Author: Jah-yee
State: closed | merged: False
Link: https://github.com/langchain-ai/langchain/pull/36021

Description (problem / solution / changelog)

Fix for issue #36011

Changed files

libs/core/langchain_core/utils/usage.py (modified, +8/-8)

Code Example

from langchain_core.utils._merge import merge_dicts

# int values merge correctly (added in #16605)
merge_dicts({"tokens": 10}, {"tokens": 5})  # ✅ {"tokens": 15}

# Equal float values pass (via the equality check)
merge_dicts({"score": 0.5}, {"score": 0.5})  # ✅ {"score": 0.5}

# Unequal float values crash
merge_dicts({"score": 0.5}, {"score": 0.3})  # ❌ TypeError

---

TypeError: Additional kwargs key score already exists in left dict and value has unsupported type <class 'float'>.

---

elif isinstance(merged[right_k], int):

---

elif isinstance(merged[right_k], (int, float)):

---

langchain-core: 1.2.19
Python: 3.10+
OS: macOS / Linux

RAW_BUFFERClick to expand / collapse

Checked other resources

I added a very descriptive title to this issue.
I searched the LangChain documentation with the integrated search.
I used the GitHub search to find a similar question and didn't find it.
I am sure that this is a bug in LangChain rather than my code.

Example Code

from langchain_core.utils._merge import merge_dicts

# int values merge correctly (added in #16605)
merge_dicts({"tokens": 10}, {"tokens": 5})  # ✅ {"tokens": 15}

# Equal float values pass (via the equality check)
merge_dicts({"score": 0.5}, {"score": 0.5})  # ✅ {"score": 0.5}

# Unequal float values crash
merge_dicts({"score": 0.5}, {"score": 0.3})  # ❌ TypeError

Error Message and Stack Trace

TypeError: Additional kwargs key score already exists in left dict and value has unsupported type <class 'float'>.

Description

History: Issue #17376 reported the same bug in 2024. PR #16605 added int support but omitted float. PR #36012 attempted a fix but was closed due to missing issue link and unrelated changes.

Root Cause

In _merge.py line 71, the type check is:

elif isinstance(merged[right_k], int):

This should be:

elif isinstance(merged[right_k], (int, float)):

Proposed Fix

Change isinstance(merged[right_k], int) to isinstance(merged[right_k], (int, float)) in merge_dicts()
Apply the same fix to merge_obj() for consistency (add float to the numeric handling)
Add regression tests for float values

System Info

langchain-core: 1.2.19
Python: 3.10+
OS: macOS / Linux

extent analysis

Fix Plan

To fix the issue with merge_dicts() not handling float values, follow these steps:

Update the merge_dicts() function in libs/core/langchain_core/utils/_merge.py to handle float values:

elif isinstance(merged[right_k], (int, float)):
    merged[right_k] += right_v

Apply the same fix to merge_obj() for consistency:

elif isinstance(merged[right_k], (int, float)):
    merged[right_k] += right_v

Add regression tests for float values, for example:

def test_merge_dicts_float():
    dict1 = {"score": 0.5}
    dict2 = {"score": 0.3}
    result = merge_dicts(dict1, dict2)
    assert result == {"score": 0.8}

def test_merge_dicts_float_equal():
    dict1 = {"score": 0.5}
    dict2 = {"score": 0.5}
    result = merge_dicts(dict1, dict2)
    assert result == {"score": 1.0}

Verification

To verify that the fix worked, run the regression tests and check that merge_dicts() correctly handles float values. You can also test the function with example code:

merge_dicts({"score": 0.5}, {"score": 0.3})  # {"score": 0.8}
merge_dicts({"score": 0.5}, {"score": 0.5})  # {"score": 1.0}

Extra Tips

Make sure to update the documentation to reflect the changes to merge_dicts() and merge_obj().
Consider adding more test cases to cover different scenarios, such as merging dictionaries with multiple float values or with a mix of int and float values.

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langchain - ✅(Solved) Fix Bug: `merge_dicts` raises TypeError for float values during streaming chunk aggregation [5 pull requests, 11 comments, 6 participants]

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PR fix notes

PR #36012: fix(core): handle float type in merge_dicts, merge_obj, and _dict_int_op

Description (problem / solution / changelog)

Description

Changes

libs/core/langchain_core/utils/_merge.py

libs/core/langchain_core/utils/usage.py

libs/core/tests/unit_tests/utils/test_utils.py

libs/core/tests/unit_tests/utils/test_usage.py

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PR #1: fix(core): add float support to merge_dicts for streaming scenarios

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PR #36014: fix(core): handle float values in merge_dicts

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PR #36016: fix(core): handle float type in _dict_int_op for UsageMetadata aggregation

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PR #36021: fix: add float support in merge_dicts

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`libs/core/langchain_core/utils/_merge.py`

`libs/core/langchain_core/utils/usage.py`

`libs/core/tests/unit_tests/utils/test_utils.py`

`libs/core/tests/unit_tests/utils/test_usage.py`