feat: upgrade langchain to 0.3.0 and update related dependencies#811
feat: upgrade langchain to 0.3.0 and update related dependencies#811David Gold (dbgold17) wants to merge 3 commits intomainfrom
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Co-Authored-By: David Gold <32782137+dbgold17@users.noreply.github.com>
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Pull Request Overview
This PR upgrades the langchain dependency from version 0.1.16 to 0.3.0, along with necessary related package updates to accommodate langchain's new modular structure where embeddings functionality has been split into separate packages.
Key changes:
- Updated langchain and related dependencies to their 0.3.x versions
- Migrated embedding imports to new langchain package structure (langchain-cohere, langchain-community, langchain-openai)
- Updated Azure OpenAI embedder implementation to use the new
AzureOpenAIEmbeddingsclass with updated parameter names
Reviewed Changes
Copilot reviewed 2 out of 3 changed files in this pull request and generated 2 comments.
| File | Description |
|---|---|
| pyproject.toml | Updated langchain from 0.1.16 to 0.3.0, added new split packages (langchain-cohere, langchain-community, langchain-openai), upgraded openai from 0.27.9 to >=1.40.0, and updated vector-db-based extras |
| airbyte_cdk/destinations/vector_db_based/embedder.py | Updated imports to use new langchain package structure and refactored AzureOpenAIEmbedder to use AzureOpenAIEmbeddings class with updated parameter names |
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| fastavro = { version = ">=1.11.0,<2.0.0", optional = true } | ||
| langchain = { version = "0.1.16", optional = true } | ||
| langchain_core = { version = "0.1.42", optional = true } | ||
| langchain = { version = "0.3.0", optional = true } |
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[nitpick] Consider using a version range (e.g., '>=0.3.0,<0.4.0') instead of pinning to an exact version. This is consistent with how langchain_core and the new langchain packages are specified, and allows for patch updates without requiring dependency updates.
| langchain = { version = "0.3.0", optional = true } | |
| langchain = { version = ">=0.3.0,<0.4.0", optional = true } |
| langchain_core = { version = ">=0.3.0,<0.4.0", optional = true } | ||
| langchain-cohere = { version = ">=0.3.0,<0.5.0", optional = true } | ||
| langchain-community = { version = ">=0.3.0,<0.4.0", optional = true } | ||
| langchain-openai = { version = ">=0.2.0,<0.3.0", optional = true } |
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The version constraint for langchain-openai (>=0.2.0,<0.3.0) appears inconsistent with the other langchain 0.3.x packages. Typically, langchain-openai 0.3.x would be released alongside langchain 0.3.0. Consider verifying if langchain-openai 0.3.x exists and updating to '>=0.3.0,<0.4.0' for consistency.
| langchain-openai = { version = ">=0.2.0,<0.3.0", optional = true } | |
| langchain-openai = { version = ">=0.3.0,<0.4.0", optional = true } |
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Note Other AI code review bot(s) detectedCodeRabbit has detected other AI code review bot(s) in this pull request and will avoid duplicating their findings in the review comments. This may lead to a less comprehensive review. 📝 WalkthroughWalkthroughUpdated LangChain-related dependencies and refactored embedding imports/initialization: embedder classes now use new langchain_* packages and AzureOpenAIEmbedder constructs AzureOpenAIEmbeddings with renamed Azure-specific constructor parameters; dependency versions for langchain/openai were bumped and new optional langchain packages were added. Changes
Sequence Diagram(s)Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes Suggested reviewers
Pre-merge checks and finishing touches✅ Passed checks (3 passed)
✨ Finishing touches🧪 Generate unit tests (beta)
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Actionable comments posted: 3
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⚠️ Outside diff range comments (1)
airbyte_cdk/destinations/vector_db_based/embedder.py (1)
109-113: Update OpenAIEmbedder to useapi_keyfor consistency.Both
OpenAIEmbeddingsandAzureOpenAIEmbeddingsin langchain-openai 0.2.x support theapi_keyparameter. Currently,OpenAIEmbedder(line 110) uses the legacyopenai_api_keywhileAzureOpenAIEmbedder(line 122) uses the modernapi_key. Would you consider standardizing both to useapi_keyfor consistency?
🧹 Nitpick comments (1)
pyproject.toml (1)
67-67: Consider using a version range for langchain instead of exact pin?Line 67 pins langchain to exactly "0.3.0", while line 68 uses a range for langchain_core (">=0.3.0,<0.4.0"). This inconsistency might prevent receiving patch updates for langchain (e.g., 0.3.1, 0.3.2) that could include bug fixes or security patches.
Would you consider changing this to
">=0.3.0,<0.4.0"for consistency and to allow patch updates? Wdyt?
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🔇 Additional comments (3)
airbyte_cdk/destinations/vector_db_based/embedder.py (1)
10-12: LGTM! Import paths updated for langchain 0.3.0.The import restructuring correctly reflects the new split-package architecture in langchain 0.3.0.
pyproject.toml (2)
73-73: LGTM! OpenAI major version upgrade aligned with langchain-openai requirements.The upgrade from openai 0.27.9 to >=1.40.0,<2.0.0 is a significant change (major version bump), but this aligns with the requirements of langchain-openai 0.2.x. The helpful comment clarifies the dependency relationship.
127-127: LGTM! Extras correctly updated with new split packages.The vector-db-based extras now include all the necessary langchain split packages (langchain_core, langchain-cohere, langchain-community, langchain-openai) alongside the existing dependencies.
| AzureOpenAIEmbeddings( # type: ignore [call-arg] | ||
| api_key=config.openai_key, | ||
| chunk_size=16, | ||
| max_retries=15, | ||
| openai_api_type="azure", | ||
| openai_api_version="2023-05-15", | ||
| openai_api_base=config.api_base, | ||
| deployment=config.deployment, | ||
| api_version="2023-05-15", | ||
| azure_endpoint=config.api_base, | ||
| azure_deployment=config.deployment, | ||
| disallowed_special=(), |
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🧩 Analysis chain
Verify Azure OpenAI parameter mappings with the new SDK.
The parameter renames look aligned with Azure-specific naming conventions (e.g., azure_endpoint, azure_deployment), but since this is a major dependency upgrade, it's worth double-checking these match the langchain-openai 0.2.x API exactly.
As you noted in the PR description, testing with real Azure OpenAI credentials would help confirm the mappings are correct.
🏁 Script executed:
#!/bin/bash
# Description: Check for actual usage patterns of AzureOpenAIEmbeddings in the codebase to ensure parameter names are used correctly
# Search for any other references to AzureOpenAIEmbeddings or AzureOpenAIEmbedder
rg -nP -C5 'AzureOpenAI(Embeddings|Embedder)' --type=pyLength of output: 6311
Let me verify the exact parameter names for langchain-openai 0.2.x:
Let me check the actual implementation more closely and whether the model parameter is being provided:
Add missing model parameter to AzureOpenAIEmbeddings initialization.
The model parameter is required in langchain-openai 0.2.x AzureOpenAIEmbeddings—every official example shows it as the first argument. Your code passes api_key, chunk_size, max_retries, api_version, azure_endpoint, azure_deployment, and disallowed_special, but omits model.
The Azure OpenAI Service embeddings operation supports text-embedding-ada-002 (Version 2), text-embedding-3-large, and text-embedding-3-small models. Wdyt about adding something like model="text-embedding-3-large" (or whichever model your Azure deployment uses) to the initialization?
🤖 Prompt for AI Agents
In airbyte_cdk/destinations/vector_db_based/embedder.py around lines 120 to 127,
the AzureOpenAIEmbeddings initialization is missing the required model parameter
for langchain-openai 0.2.x; add a model argument (e.g.,
model="text-embedding-3-large" or the specific embedding model your Azure
deployment uses) to the constructor call so the embeddings client is created
with the correct model; ensure the chosen model matches the Azure deployment
configuration (deployment/model) and update any config or docs if you introduce
a new default.
| openai_api_version="2023-05-15", | ||
| openai_api_base=config.api_base, | ||
| deployment=config.deployment, | ||
| api_version="2023-05-15", |
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🧩 Analysis chain
Should the Azure OpenAI API version be configurable or more recent?
The api_version is hardcoded to "2023-05-15", which is over 2 years old. Azure OpenAI has released newer API versions since then. This could limit access to newer features or cause compatibility issues.
Consider either:
- Making the API version configurable via
AzureOpenAIEmbeddingConfigModel - Updating to a more recent stable API version (2024-x)
Wdyt about making this configurable for flexibility?
🌐 Web query:
What are the latest Azure OpenAI API versions and which version is recommended for langchain-openai 0.2.x?
💡 Result:
Short answer
- Latest Azure OpenAI API surfaces (as of Oct 23, 2025): the new unified v1 OpenAI-style API (opt‑in since mid‑2025) plus dateed preview versions (notably 2025-03-01-preview for Responses/features) and the most recent date-based GA/preview releases (examples: 2024-06-01 / 2024-10-21 / 2025-03-01-preview). [1][2][3]
Recommended version for langchain-openai 0.2.x
- Use the API version LangChain v0.2 docs show: set OPENAI_API_VERSION = 2023-12-01-preview (LangChain v0.2 guidance). If you can move to the newer unified v1/OpenAI-style endpoints and your LangChain version supports them, prefer the v1 spec for access to the latest features; otherwise pin to 2023-12-01-preview for stability with langchain-openai 0.2.x. [4][1]
Sources
- Microsoft: Responses API / Azure OpenAI docs (v1 + preview notes). [1][2]
- Microsoft: Azure OpenAI API lifecycle (unified v1 rollout / api-version guidance). [1]
- LangChain v0.2 Azure OpenAI docs (recommended OPENAI_API_VERSION = 2023-12-01-preview). [4]
References (links shown as numbered sources above).
Update the Azure OpenAI API version to match LangChain compatibility requirements.
The api_version is hardcoded to "2023-05-15", but LangChain v0.2 docs recommend setting OPENAI_API_VERSION = 2023-12-01-preview for langchain-openai 0.2.x. This 7-month gap may cause compatibility issues or limit access to features.
Would updating to 2023-12-01-preview work for your use case? Additionally, consider making this configurable via AzureOpenAIEmbeddingConfigModel for flexibility across different deployment scenarios.
🤖 Prompt for AI Agents
In airbyte_cdk/destinations/vector_db_based/embedder.py around line 124, the
api_version is hardcoded to "2023-05-15"; update it to "2023-12-01-preview" to
match LangChain v0.2 expectations and avoid compatibility issues, and make this
value configurable by adding a new field (e.g., openai_api_version) to
AzureOpenAIEmbeddingConfigModel with default "2023-12-01-preview"; then replace
the hardcoded string with the config value when constructing the Azure OpenAI
client so existing behavior remains unchanged if the config is not set.
| langchain-cohere = { version = ">=0.3.0,<0.5.0", optional = true } | ||
| langchain-community = { version = ">=0.3.0,<0.4.0", optional = true } | ||
| langchain-openai = { version = ">=0.2.0,<0.3.0", optional = true } |
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🧩 Analysis chain
Verify version range compatibility across langchain packages.
The new langchain packages have different version constraints:
langchain-cohere: 0.3.x-0.4.xlangchain-community: 0.3.x onlylangchain-openai: 0.2.x only
While this might be intentional due to different release schedules, it's worth verifying these ranges are compatible with each other and with langchain 0.3.0, especially since langchain-openai is on a different major version.
🌐 Web query:
Are langchain 0.3.0, langchain-openai 0.2.x, langchain-community 0.3.x, and langchain-cohere 0.3.x-0.4.x compatible with each other?
💡 Result:
Short answer: No — mix of 0.3.0 (langchain) with langchain-openai 0.2.x is not compatible. All LangChain packages that depend on langchain-core should stay in the same minor series (use >=0.3,<0.4 for the 0.3 line). In other words, use langchain-openai, langchain-community, langchain-cohere all in the 0.3.x family (or otherwise upgrade the whole stack together). [1][2][3]
Sources:
- LangChain v0.3 docs — recommended constraint >=0.3,<0.4 for core and companion packages. [1]
- LangChain forum guidance to keep packages within the same minor series (v0.3). [2]
- langchain-cohere release listings / package notes showing 0.3/0.4 series as integrations tied to langchain-core. [3]
Fix langchain-openai version constraint — currently incompatible with langchain 0.3.0
All LangChain packages that depend on langchain-core should stay in the same minor series. The current constraint langchain-openai = ">=0.2.0,<0.3.0" pins to the 0.2.x series, which is incompatible with langchain 0.3.0 and the other 0.3.x packages. Use >=0.3,<0.4 for all packages.
Additionally, langchain-cohere = ">=0.3.0,<0.5.0" allows 0.4.x versions—should this be <0.4.0 for consistency, wdyt?
🤖 Prompt for AI Agents
In pyproject.toml around lines 69 to 71, the langchain-openai version constraint
is pinned to the 0.2.x series which is incompatible with langchain 0.3.x and the
other 0.3.x packages; update langchain-openai to use ">=0.3.0,<0.4.0" so it
stays in the same minor series as langchain-core, and also narrow
langchain-cohere to ">=0.3.0,<0.4.0" for consistency with the 0.3.x family
(langchain-community is already using the correct <0.4.0 range).
PyTest Results (Full)3 805 tests 3 793 ✅ 11m 12s ⏱️ Results for commit 11d5bf0. ♻️ This comment has been updated with latest results. |
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Devin, check the linter failures. Some methods expect |
Co-Authored-By: David Gold <32782137+dbgold17@users.noreply.github.com>
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Devin: |
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The pytz error is pre-existing - it was already failing in the previous CI run before my changes. My changes fixed the SecretStr errors that you originally flagged:
The pytz stub issue is unrelated to the langchain upgrade. Should I fix it in this PR or leave it for a separate fix? |
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Devin, it's possible that the non-zero exist status (aka failing lint check) is from the prior message and not from the pytz issue. |
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You're right! The pytz error is new - it's because the langchain upgrade brought in dependencies that use pytz, and we don't have the type stubs installed. The linter passes on main. I'll add |
Co-Authored-By: David Gold <32782137+dbgold17@users.noreply.github.com>
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Actionable comments posted: 0
♻️ Duplicate comments (1)
pyproject.toml (1)
71-71: Fix langchain-openai version incompatibility with langchain 0.3.0The langchain-openai package has 0.3.x versions available, but the constraint
>=0.2.0,<0.3.0pins to 0.2.x, which is incompatible with langchain 0.3.0 and the other 0.3.x packages in this file (langchain_core, langchain-community). All LangChain packages in the 0.3 ecosystem should stay in the same minor series—wdyt about updating to>=0.3.0,<0.4.0for consistency?-langchain-openai = { version = ">=0.2.0,<0.3.0", optional = true } +langchain-openai = { version = ">=0.3.0,<0.4.0", optional = true }
🧹 Nitpick comments (1)
pyproject.toml (1)
67-67: Consider using version range for langchain (consistency and flexibility)Line 67 pins langchain to an exact version (
0.3.0), while langchain_core and other LangChain packages use ranges (e.g.,>=0.3.0,<0.4.0). This approach is more flexible and allows patch-level updates without requiring manual version bumps. Wdyt about aligning with the pattern used for other packages?-langchain = { version = "0.3.0", optional = true } +langchain = { version = ">=0.3.0,<0.4.0", optional = true }
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🔇 Additional comments (3)
pyproject.toml (3)
69-69: Verify langchain-cohere version range upper boundLine 69 allows langchain-cohere versions up to
0.5.0(>=0.3.0,<0.5.0), whereas the other 0.3.x packages in this file (langchain_core, langchain-community) are constrained to<0.4.0. Should langchain-cohere also be narrowed to<0.4.0for consistency with the 0.3.x family, or is the broader range<0.5.0intentional?
122-122: Good addition to resolve mypy stubs issueAdding
types-pytz = "*"to dev dependencies addresses the mypy error mentioned in the PR comments about missing stubs for pytz. This is a solid fix for typing support.
128-128: Extras correctly updated to include new langchain packagesThe
vector-db-basedextras have been properly updated to include all the new langchain packages (langchain_core, langchain-cohere, langchain-community, langchain-openai) alongside the existing dependencies. This ensures users can access the full embedding/vectorization functionality with the new package structure.
Upgrade langchain to 0.3.0 and update related dependencies
Summary
Upgraded the Python CDK to use langchain 0.3.0 as requested, with minimal necessary dependency updates. The main changes include:
Dependency updates:
langchain: 0.1.16 → 0.3.0langchain_core: 0.1.42 → >=0.3.0,<0.4.0langchain-cohere,langchain-community,langchain-openai(required by langchain 0.3.0's new architecture)openai: 0.27.9 → >=1.40.0,<2.0.0 (required by langchain-openai)Code changes in
embedder.py:langchain.embeddings.*to separate packages)AzureOpenAIEmbedderto useAzureOpenAIEmbeddingsclass instead ofOpenAIEmbeddingswith Azure parameters (breaking change in langchain-openai 0.2.x)openai_api_key→api_key,openai_api_base→azure_endpoint,deployment→azure_deployment, etc.SecretStrwrapper for API keys to satisfy mypy type checking requirementsReview & Testing Checklist for Human
SecretStrwrapper doesn't break Cohere embeddings at runtime.Test Plan
Notes
SecretStrwrapper is required by the new langchain libraries' type signaturesLink to Devin run: https://app.devin.ai/sessions/b82c85600676421da2957652757b3b66
Requested by: David Gold (David Gold (@dbgold17))
Summary by CodeRabbit
Chores
Refactor